RESEARCH INITIATIVES FOR IMPROVING THE SAFETY OF OFFSHORE HELICOPTER OPERATIONS* David Andrew Howson (dave.howson@srg.caa.co.uk) Research Project Manager UK Civil Aviation Authority, London, UK Abstract Since the late 1980’s, the UK Civil Aviation Authority (CAA) has been leading a programme of research aimed at improving the safety of offshore helicopter operations. The motivation for this initiative came from a major joint CAA/Industry review of helicopter airworthiness, commissioned in 1982. This study led to a number of research projects and other reviews which, in turn, led to further research projects. A total of over 20 projects have been undertaken covering airworthiness and operational issues, and covering helicopters and helidecks. This programme of work has been jointly funded and monitored by the UK CAA-run Helicopter Safety Research Management Committee (HSRMC). This paper provides a top-level summary of current activities on the seven main ‘live’ research projects. Introduction [1] following the loss of 45 lives in the Chinook accident in 1986. The committee is still thriving and has evolved over time expanding its membership to include the UK MoD, the UK helicopter operators (BHAB), the new European Aviation Safety Agency (EASA), the Norwegian CAA, the Norwegian oil industry (OLF), and the European Helicopter Association (EHA). In the 1970’s and early 80’s the disappointing safety record of helicopters transporting people to work on oil rigs in the North Sea led to the formation of the Helicopter Airworthiness Review Panel (HARP). This group reported its findings in the HARP Report (CAP 491) [1] in 1984, which contained recommendations for research into helicopter health and usage monitoring, crashworthiness and ditching. The HARP Report also called for an investigation of human factors-related accidents which led to the formation of the Helicopter Human Factors Working Group. This group reported its findings in CAA Paper 87007 [2] in 1987, which included recommendations for research into a further seven, mainly operational areas. To date, the committee has overseen over £8M of research funding spread over a wide range of helicopter safety issues, the majority of which have their ultimate origins in the HARP Report. The remainder of this paper provides a top-level summary of current activities on the following seven main ‘live’ projects overseen by the HSRMC: In addition to these two initiatives, a major review of offshore safety and survival was commissioned in 1993 in response to an AAIB recommendation following the fatal accident at the Cormorant A platform in 1992. This study was conducted by the Review of Helicopter Offshore Safety and Survival (RHOSS) working group, which reported its findings in CAP 641 [3] in 1995. The overall effect of this exercise on the helicopter safety research programme was to add impetus to the crashworthiness (water impact) and ditching projects. The resulting programme of helicopter safety research has been funded and monitored by the UK CAA-run Helicopter Safety Research Management Committee (HSRMC). The HSRMC was originally set up by UK CAA in the late 1980's to manage a joint UK CAA/UK Government/UK oil industry (UKOOA) research fund that was created to progress the recommendations of * Helicopter Health & Usage Monitoring Systems (HUMS) - Advanced Analysis Techniques. Helicopter Emergency Flotation. Helideck Environmental Issues - Turbulence Criterion. Operations to Moving Helidecks. Helideck Lighting. Helicopter Flight Data Monitoring - Extension to Low Airspeed Regime. Use of GPS for Offshore Helicopter Operations - Low Visibility Approaches. Helicopter Health & Usage Monitoring Systems (HUMS) - Advanced Analysis Techniques Background The first vibration health monitoring (VHM) systems (known as ‘HUMS’) were installed on the North Sea Presented at the International Helicopter Safety Symposium 2005, Montréal, Canada, September 26-28, 2005. Copyright © 2005 by the American Helicopter Society International, Inc. All rights reserved. 1 helicopter fleet in the early 1990s which, the CAA believes, contributed significantly to a reduction in the airworthiness-related accident rate. Although inservice experience continues to demonstrate significant safety benefits, it is generally acknowledged that there is room for improvement in the diagnostic performance of HUMS. One study has suggested that for every four ‘successes’ there is one where a propagating defect was subsequently judged to be ‘evident’ but no warning was given as no warning threshold was exceeded. Experience has shown that the above issues can be mitigated through the use of well-trained and experienced human analysts. In the in-service environment, however, it is impractical for human analysts to examine all data in sufficient depth due to the large quantities generated on a daily basis. Hence a crucial factor in improving the effectiveness of HUMS is the establishment of a more sophisticated means of identifying the sections of data of interest. If this can be achieved it will result in a reduction of the quantity of data requiring detailed analysis, enabling human analysts to focus their efforts where their skills are still essential. In addition to the in-service experience, the ongoing review of the results of the two HSRMC funded helicopter main rotor gearbox (MRGB) seeded defect test programmes has indicated that there is scope for improving the effectiveness of HUMS data analysis. The main issues identified as requiring attention are: robust and capable analysis technique is therefore required if effectiveness is to be improved. accommodation of reducing gear indicator trends - certain types of defect can manifest themselves as reducing indicator trends. A technique is required that can detect these. improvement of warning time (i.e. the time between warning and component failure) - when conducting retrospective analyses, the presence of defects is nearly always apparent to analysts in the data in advance of any indicator thresholds having being exceeded, and hence any warnings being generated. It should be borne in mind, however, that if a warning and the associated indicator histories are not judged conclusive, it is common practice to fly-on while ‘close monitoring’ for a defect. Hence improvement in warning time must not be at the expense of the warning’s ‘quality’ for maintenance decision making. detection of build defects - many warning thresholds are tailored on installation of the component/assembly using a simple ‘learning’ process. This improves sensitivity without increasing the false alarm rate. However, in the event of a build anomaly or defect these thresholds are set too high, effectively desensitising the analysis to the subsequent propagation of defects. Additionally, during the ‘learning’ period the threshold will, at best, be at a higher fleet average based level, further reducing the protection against defects introduced by build/maintenance errors. Hence a system that can provide increased sensitivity without increasing the false alarm rate and without requiring a ‘learning’ period after each maintenance action would represent a significant improvement. accommodation of unexpected gear indicator reactions - the identification of defects in a timely manner can be compromised by the rigid application preconceived ideas on how defects will manifest themselves in the vibration data. Experience has demonstrated that a wide range of reactions is possible, both in terms of which indicators react and how they respond. A more Earlier Research As part of CAA’s helicopter MRGB seeded defect test programme, a number of alternative health monitoring techniques were evaluated. These included alternative sensors (e.g. stresswave sensors, acoustic sensors), and a number of alternative analysis techniques. In general, these alternatives were not able to demonstrate any significant improvement over the VHM techniques in-service at the time they were evaluated. One notable exception was the programme of work aimed at demonstrating the benefits of supervised and unsupervised machine learning techniques. The scope of the project included the blind analysis of data from two of the S61 MRGB seeded defect tests. The work was completed in 1998 and the final report was published as CAA Paper 99006 [4]. The analysis of the seeded defect test data is covered in Study II of [4], and it is this section of the work that is of direct relevance to the current research. Although success was achieved with supervised machine learning, the absence of large numbers of examples of all possible failure conditions is expected to limit this technique to a retrospective response to in-service incidents. Conversely, given the vast quantities of data available to characterise serviceable components and/or systems and in view of the results of the blind analysis, unsupervised machine learning is considered to have great potential as a proactive tool. This work was presented to both the CAA/Industry Helicopter Health Monitoring Advisory Group (HHMAG) in 1999 and to a Royal Aeronautical Society conference in March 2000, and CAA encouraged industry to exploit the results and develop the techniques for use in-service on civil helicopters. 2 Current Research most promising ideas cited in the literature. No further development of advanced HUMS data analysis techniques had taken place by 2003, however, when a significant HUMS missed detection involving a Super Puma bevel pinion occurred. The seriousness of this incident persuaded CAA to take the lead in developing the technology and, following a competitive tendering process, Smiths Aerospace Electronic Systems - Southampton, UK, were commissioned to conduct the research required. The overall objective of the project is to demonstrably improve the effectiveness of HUMS through the enhancement of VHM data analysis, and comprises the following tasks: The extensive archive of BHL HUMS data downloads has been decoded, ‘cleaned’ and catalogued in a SQL Server database in preparation for system development and testing. This was a significant but necessary task and included data for Super Puma main rotor, intermediate, tail and left and right accessory gearboxes. Analysis of this data so far has shown it to be ‘noisy’ and, as expected, revealed that gearboxes tend to exhibit individual behaviour. Another challenge has been the inability to identify a ‘healthy’ data set for the development of anomaly detection models. All data has been found to contain some anomalies and, because of the lack of feedback from overhauls, the status of all data not containing documented faults can only be classed as ‘unknown’. A further challenge is the fact that the data contains many step changes, which are assumed to be due to unidentified maintenance actions on other parts of the helicopter. This has resulted in the work becoming more of a research effort than was originally envisaged. Furthermore, whilst data normalization techniques should be utilized wherever possible, for the VHM data pre-processing options are limited to filtering, and relatively simple techniques for characterising indicator trends. This places more emphasis on modelling and the analysis of model information. However, as a result of an intensive data analysis effort, there is now a high confidence that cluster modelling can reveal anomalous behaviour and can be used to characterise the significance of anomalies. The key on-going task is to determine the optimum structure for these models and define the best anomaly metrics. a review of existing literature judged to be relevant to the project, CAA Paper 99006 in particular; development of the advanced HUMS data analysis techniques based on historical data; the design and production of analysis software; an off-line demonstration of the system and any consequent refinement; an in-service demonstration of the system. The in-service demonstration is to be performed by Bristow Helicopters Ltd (BHL) at their Aberdeen, UK, base. The system will be installed/implemented in parallel with the existing HUMS ground station such that incoming HUMS data is analysed concurrently. This will be accomplished in a manner that does not affect the integrity of the existing ground station or analysis, i.e. all warnings provided by the existing analysis will be acted upon as usual, regardless of the output of the improved analysis. Differences between the reactions of the existing and new analyses will be noted and compared. Feedback from any inspections or other maintenance actions or strip reports will be collected and catalogued with the associated results from both the new and existing analysis techniques. An important aspect of the in-service trial is the evaluation of the system in terms of ease of use and workload. BHL are tasked with reporting on this aspect of the work from a user’s perspective. Progress on Current Research As at end June 2005 the literature survey had been completed and a large number of references on anomaly detection identified. Although many focussed on ‘intrusion detection’ on computer networks, most had general applicability. A few papers were related to aircraft health monitoring, the most relevant being related to novelty detection in jet engines. The survey confirmed that the data mining tool proposed for the research has the algorithms necessary to evaluate the Figure 1 - Cluster plot of 2 VHM indicators from AS332L LH Accessory Gearbox. 3 By way of an illustration, the plot in Figure 1 presents data trend information for two HUMS parameters in a multi-parameter cluster model. The light areas show outlying regions in the parameter space being modelled by a particular ‘anomaly cluster’. Any data trends moving into these regions would be classed as anomalous. that occupants who do not escape from the cabin within seconds are likely to drown. Additional emergency flotation systems were devised (e.g. see Figure 2) to prevent total inversion following capsize. A total of ten schemes were initially proposed and ranked by a team of naval architects and helicopter designers. The top three were tested using a helicopter model in a wave tank, and two found to be practical and effective [8]. Subject to a satisfactory off-line demonstration of the system, the in-service trial is scheduled to start late 2005 and will last for six months. The project includes an option to extend the trial for a further six months should this be judged necessary. Helicopter Emergency Flotation Forced landing on the water (‘ditching’) For extended over water flights (being in the UK beyond autorotation distance from land for a single engine helicopter, and more than 10 minutes flying time from a suitable forced landing site for a multiengine helicopter), emergency flotation systems (EFS) have been mandated on UK offshore helicopters since the 1970s. However, it is difficult or impossible to design practical flotation systems that will keep a helicopter afloat and stable in the severest weather conditions. In [5] it was shown that, on average in the North Sea, a helicopter making a controlled landing on the water, and fitted with an emergency flotation system compliant with the guidance [6], might expect to be capsized by the waves in about 30% of cases. Figure 2 - Tank test model of helicopter fitted with additional auxiliary emergency flotation to prevent total inversion [8]. Figure 3 shows the floating attitude of the helicopter following capsize, illustrating that the windows and doors remain above the waterline on one side of the fuselage. In addition, there is a significant air pocket remaining in the cabin, removing the time pressure to escape. Research into the design of EFS was undertaken in an attempt to improve the odds. Model tests conducted by British Hovercraft Corporation in the mid 1980s had investigated raising the float attachment positions in order to float the helicopter lower into the water, and the addition of water scoops to the emergency flotation bags (as routinely used on inflatable liferafts in order to improve stability). The former was found to give variable and inconclusive results, depending primarily on helicopter type and loading condition. The latter was seen to provide a uniform benefit, however, increasing the helicopter capsize threshold by about one sea-state. The benefits of float scoops, and their relatively low cost were described in [7]. Even with float scoops fitted, the probability of a capsize when alighting on the water on the UK continental shelf was still considered to be too high, hence the decision was taken to attempt to mitigate the consequences of a capsize by preventing the helicopter from turning to a completely inverted attitude. When this happens the cabin rapidly fills with water, and escape becomes very difficult and hazardous because all the escape routes are submerged. The incompatibility between the time needed to escape and typical breath hold times in the low water temperatures prevalent in the region means Figure 3 - Floating attitude with auxiliary flotation following capsize [8]. Following the demonstration that the auxiliary flotation was practical and effective, a human factors study was conducted in a helicopter underwater escape trainer (HUET) to check that it was indeed easier to escape from a side-floating helicopter than a fully inverted one. 4 The study used 30 naive subjects who were trained, and then evaluated in simulated escapes from fully inverted and side floating cabins in the training facility tank. This confirmed the expected benefits of the side floating arrangement [9]. Work on a helicopter typespecific design study on emergency flotation systems designed to prevent total inversion following capsize originally scheduled for 2002 was delayed due to budgetary pressures following 9/11. It is now planned that work will start in 2005. This study is necessary to establish the practicality of the scheme for both retrofit to existing helicopters and for new build aircraft. expected to improve performance following a severe impact. A high level cost benefit analysis indicated that the modifications were also cost-effective, and a number are already incorporated into modern EFS design. Crashes onto water The primary purpose of emergency flotation systems has always been to keep the helicopter afloat following a controlled landing on the water. These systems tend to be much less effective when a helicopter crashes into the water either because they are damaged in the impact, or because they have to be manually triggered to inflate by the pilot who may be disabled by the impact. Studies of helicopter crashes onto water [10, 11, 12, 13, 14] have concluded that the primary cause of loss of life following water impact is drowning, and that improvements in the capability of helicopters to remain afloat after impact long enough for the survivors to escape is the major factor in improving occupant survivability. Figure 4 – Example result from [15] showing plastic strain experienced by airframe during a vertical impact with the water. In contrast to the detailed deterministic investigation of three crash scenarios, the second study [16] looked at the statistics and variability of the wide range of possible crash scenarios and sea conditions. It was found that, as expected, the variability in crash velocity and loading was extremely large as can be seen in Figure 5. Research was therefore commissioned by CAA to investigate ways of improving the crashworthiness of emergency flotation systems. Two studies were performed [15, 16]. The first investigated water impacts and their effect on the helicopter airframe in general, and on the emergency flotation system in particular. Non-linear finite element analysis was used to study three specific accident scenarios from which there were a significant number of survivors, but which were all outside the Federal Aviation Administration proposed 95% survivability ditching envelope [1]. The three scenarios comprised a vertical drop from a helideck, a horizontal ‘fly-in’ impact, and a loss of control accident featuring intermediate vertical and horizontal impact velocities. A review of EFS design was also undertaken to identify design features that would improve overall system functionality, reliability and operation following an impact. A high-level cost benefit analysis and a review of regulatory requirements were also performed. Again, three basic crash scenarios were investigated together with a forced landing or ‘ditching’, using a Monte Carlo simulation to exercise the variability of the impact parameters including the velocities, angles and sea states. The clouds of points in Figure 5 show the variability in vertical and horizontal impact velocity experienced by the helicopter in the simulation. The four main crash and ditching scenario populations are labelled. In each case the indicate occurrences where the flotation system design loads were not exceeded, while each + indicates overload and presumed failure. The figure also shows the impact velocity boundaries for the current ditching flotation system certification requirements, and the FAA proposed 95% survivability envelope. This study concluded that a very substantial increase in flotation design loads would be required in order to make a difference to the survivability. In fact doubling the design loads would only result in a very modest improvement in crashworthiness. Although good validation was achieved for vertical impacts, the results from the non-linear finite element analysis demonstrated a number of major difficulties in adequately modelling the physics of the airframe / water impact for horizontal ‘fly-in’ scenarios. Figure 4 shows an example result, in this case for a vertical water impact. The study also came up with several EFS design modifications (automatic EFS arming/deployment in particular) that would be The most important outcome of this study was in highlighting the major benefits of flotation unit redundancy, particularly additional flotation units in a less vulnerable impact location high on the cabin walls. (The same floats proposed for preventing total 5 inversion, and shown in Figures 2 and 3.) 30% probability that the 4-flotation unit helicopter will sink, whilst with 6 units the helicopter has sufficient redundancy to remain afloat in the severest of the crashes modelled. Figure 6 shows results from three different flotation configurations with different levels of redundancy. It can be seen that for high impact crashes there is a Figure 5 – Scatter plot from [16] showing vertical and horizontal impact velocities of helicopter for four different scenarios: loads on fuselage panel greater and less than design load. Percentage of impact events where the helicopter sinks, within each impact severity index curve, for different panel configurations 50 4 panels 5 panels 40 6 panels Percentage 30 20 10 0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 Impact severity index Figure 6 – Percentage of sea impacts causing helicopter to sink. Up to 6 flotation units, with 4 required to remain afloat [16]. 6 Potential changes to airworthiness requirements criterion in CAP 437 in combination with a system of operational feedback (turbulence report forms) appears to have served to contain the situation, the absence of a specific turbulence criterion in CAP 437 is regarded as anomalous and unsatisfactory. The CAA presented the findings from its ditching and water impact research to the JAA Helicopter Offshore Safety and Survivability (HOSS) working group and to the FAA/JAA/Industry Joint Harmonisation Working Group (JHWG) on Water Impact, Ditching Design and Crashworthiness (WIDDCWG). Both groups produced working papers recommending similar changes to the current JAR/FAR 27 and 29 airworthiness requirements relating to helicopter ditching and water impact crashworthiness, both of which have been published in annexes to CAA Paper 2005/06 [17]. Development of a Turbulence Criterion In 2000, the CAA therefore commissioned a programme of work with the primary objective of developing an easyto-use maximum safe turbulence criterion for all helicopter operations to offshore helidecks. The basic assumption behind the approach taken to this work was that the margin of safety available at any point during the sections of flight of interest is inversely proportional to pilot workload, i.e. the higher the workload, the lower the margin of safety. Hence, in order to establish a maximum safe turbulence criterion, it was necessary to: The need for a review of the requirements was accepted by the JAA/FAA Rotorcraft Steering Group (RSG). The issues raised in the working papers were split into those requiring changes to the advisory material only, and those involving rule changes. Unfortunately little progress has been made. The two follow-on groups called for by the JAA/FAA RSG have yet to be set up, and the JAA has now been superseded by the new European Aviation Safety Agency (EASA), which assumed responsibility for airworthiness requirements in September 2003. The follow-on tasking, however, presently forms part of EASA’s 2005/7 work programme. quantify pilot workload and define a maximum safe limit; and establish a generic relationship between pilot workload and an appropriate measure of turbulence. A well-established and widely accepted measure of pilot workload exists in the Cooper-Harper aircraft handling qualities rating (HQR) scale devised by NASA in the 1960’s [21]. This involves structured pilot debriefing to arrive at a rating on a scale of 1 to 10 where 1 is benign and 10 is unacceptable (see Figure 7). A safe upper limit of pilot workload can readily be identified by reference to the descriptions of task performance and pilot workload associated with each rating. CAA plans to complete the helicopter type specific design study on emergency flotation systems designed to prevent total inversion following capsize in time to feed the results into the regulatory activities. Helideck Environmental Issues - Turbulence Criterion Background A top-down review of helideck environmental issues, commissioned by UK CAA and the Offshore Safety Division of the UK Health and Safety Executive (HSE) in response to a UK Air Accidents Investigation Branch (AAIB) recommendation following the heavy landing on the Claymore Accommodation Platform on 18 August 1995 [18], highlighted the absence of a specific turbulence criterion. The final report for this study, published as CAA Paper 99004 [19], recommended that a scientific basis be established for a limit on the permitted level of turbulence in the vicinity of offshore platforms. The importance of considering turbulence as a specific hazard had also previously been illustrated in the results of a questionnaire survey of offshore helicopter pilots, reported in CAA Paper 97009 [20]. In this study, turbulence around platforms was ranked by pilots as being the greatest of the fifteen factors contributing to workload and safety hazards that were considered. Hence, although the existing vertical wind speed Figure 7 - Workload rating scale. No precedents for establishing a relationship between pilot workload and turbulence were found to exist, however, and so addressing this issue effectively formed the main focus of the research. Although challenging in 7 its own right, this task was exacerbated by the requirement that the resulting relationship be generic, i.e. not dependent on pilot, aircraft or offshore platform. The results from the tests provided a 3-axis turbulent environment with realistic spatial variation in mean velocity and turbulence. Using this data, complete approaches could be flown in the simulator in a realistic turbulence field. A number of tools and models were assembled in the course of the programme. The key components are illustrated in Figure 8 and are briefly described below. Piloted Simulation The left hand stream of work in Figure 8 is the piloted simulation that employs a helicopter model and visual database to allow a pilot to assess the severity of the platform airwake, as measured in the wind tunnel tests, and award a Cooper-Harper handling qualities rating to flying tasks in various wind conditions. The simulation was targeted at a single helicopter/platform combination using a computer model of the Sikorsky S-76 and a visual database of the Brae-A platform. The piloted simulation exercise formed the core of the project and produced the relationship between turbulence and pilot workload used to establish the turbulence criterion. The three pilots that took part were all experienced and qualified test pilots who had flown recently to offshore platforms, although not necessarily the Brae A platform modelled for this study. A range of test points were flown whilst varying wind speed, wind direction and aircraft weight. Wind directions were chosen such that various parts of the platform superstructure were positioned directly upwind of the helideck as well as one direction where there were no such obstructions. Desktop Simulation In the centre of Figure 8 is the desktop simulation that uses the same helicopter model as the piloted simulation, but a pilot model and workload predictor replaces the human in the loop. The pilot model synthesises the control activity required to perform manoeuvres in the presence of the measured flow, and the workload predictor estimates the level of workload indicated by the control activity. The result is a workload rating expressed on a scale that parallels the CooperHarper HQR scale. Some of the data from the piloted simulation was required as ‘training data’ to configure the workload predictor, but the bulk of the information has been used to validate both the workload predictor in isolation and the entire desktop simulation process. Figure 8 - Overview of tools and models for prediction of pilot workload. Wind Tunnel Tests At the top of Figure 8 is the wind tunnel data that provides measurements of the disturbed airwake around the offshore platform of interest. Such data are normally generated for new or modified platforms before entering service during the development of an appropriate safety case. However, due to the unsuitability of this data it was necessary to collect new data specifically for this project. A special series of tests was performed on a 1:100 scale model of the North Sea Brae A platform in order to provide input for the piloted flight simulation trials and the desktop simulation exercises. The platform model was rotated on a turntable in the wind tunnel to represent a range of wind directions. These directions were chosen so that the flow was sampled when the helideck was upwind and unobstructed, and also when it was downwind of identifiable obstructions to the wind flow such as the drilling derricks, or gas turbine exhaust stacks. The exact form of the workload predictor is as follows: Workload Rating = c1 + c2 σ(ξ) + c3 σ*(ξ) + c4 σ(η) + c5 σ*(η) + c6 σ(θ0) + c7 σ*(θ0) where: c1 – c7 = predictor coefficients ξ = lateral cyclic position η = longitudinal cyclic position θ0 = collective lever position 8 σ(x) = function : standard deviation of x σ*(x) = function : standard deviation of first derivative of x with time standard deviation of the vertical flow gives the turbulence criterion in its current form: The standard deviation of the vertical flow must be less than 2.4 m/s for safe flight to be maintained. The yaw pedal position was excluded from the workload predictor, as this was not seen to contribute significantly to the overall workload during development of the predictor. The overall role of the desktop simulation in the development of the turbulence criterion was to provide a relatively detailed model with which to explore the generality of the relationship between turbulence and workload without recourse to a multitude of expensive and time consuming piloted simulation trials to consider different helicopter and platform combinations. The methodology was to validate the desktop simulation against the available data for S-76 / Brae-A piloted simulation exercise, and then to investigate the influence of key helicopter design parameters on the predicted workload, and to apply the desktop simulation to other platforms and compare the results with predictions using the relationship established between turbulence and workload from the piloted simulation exercise. Turbulence Criterion for Safe Helicopter Operations Lastly, on the right of Figure 8 is the relationship between turbulence and workload, developed to define the turbulence criterion that is applied to wind tunnel test results to establish a safe operating envelope for the corresponding offshore platform. The criterion is required to be easily applied and appropriate for use across any helicopter / platform combination. Figure 9 - Pilot HQR plotted against standard deviation of vertical wind velocity component. All the samples of turbulence used for the piloted simulation trial were examined to establish a suitable metric for use in defining a relationship between turbulence level and pilot workload. The properties of the data were found to be such that only a single parameter was required, the optimum parameter being the standard deviation of the vertical component of the wind velocity. This parameter is shown plotted against the HQR ratings awarded by the three pilots in Figure 9. Also shown on the plot is the best fit line that is given by the following relationship: HQR = 2.77 + 1.571*(std. devn. of vertical velocity) Applying this relationship to the wind tunnel data for the Brae A yields the workload predictions illustrated in Figure 10. The workload ratings are placed on a compass rose where the bearing represents the wind direction and the distance from the centre of the rose represents the wind speed. The arc of the coloured segment represents the angle projected by the width of the obstruction. Figure 10 - Workload predictions for Brae A using the turbulence /workload relationship established from piloted simulation trials. Using this value and combining it with the identified relationship for workload rating as a function of the 9 Comparison of Figure 10 with the entry for the Brae A in the Helicopter Limitations List (HLL) has indicated that the results of applying the relationship between turbulence level and pilot workload to the wind tunnel data for the Brae A are broadly consistent with current operational experience. Ongoing Work The research described above has been fully reported in CAA Paper 2004/3 [22]. Although considered highly successful, the research to develop the turbulence criterion necessarily embraced a number of assumptions and approximations and, as is normally the case with work of this nature, there is a need to validate both the modelling process used, and the limiting criterion established prior to incorporation of the criterion in the guidance [23]. Figure 11 - Super Puma helicopter tipped over on the West Navion drillship. The approach adopted for this task has been to implement the collective and cyclic control movementbased pilot workload algorithms in the Helicopter Operations Monitoring Programme (HOMP) [24] analysis software, and use archived HOMP data to map the environments around offshore helidecks and compare the results with helicopter operational experience as documented in the HLL. This accident again focused attention on the wave motion limits applied to helidecks on ships and floating platforms. The setting of these limits should involve consideration of two aspects; motion limits for executing a safe landing, and limits for safely remaining on the deck for the period necessary to effect passenger and cargo transfer (usually not more than 10 minutes). The first phase of this work, entailing the adaption of the technique to HOMP flight data records, has been successfully completed. As at June 2005, the resulting analysis is being applied to approximately one year’s worth of archived HOMP data, comprising around 20,000 approaches to 50 different platforms. The former is relatively easy to judge visually. The pilot can see the movements of the ship, judge whether it is safe to make the landing and can choose the appropriate moment to set the helicopter down. The latter is much more difficult because it should involve a prediction of the helideck motions over the next 10 minutes while the helicopter will be on the helideck, and an assessment of the statistical risk of unsafe motions. Furthermore, there is little that the pilot can do in the event of excessive motion building up whilst on the helideck. An attractive ‘spin-off’ from this exercise is a means of continuously monitoring the environments around all offshore platforms if the HOMP-based approach is successful. Up until now the motion limits have normally been specified in terms of a maximum pitch, roll and heave amplitude, but it is clear from the physics of the situation that it is the helideck accelerations that will cause a helicopter to slide or topple over. This is further complicated by the fact that a commercial helicopter with its rotor turning will be generating significant lift. Even with the collective at its lowest setting, as would normally be the case on the helideck, it is likely that about 30% of the weight of the helicopter is being carried in rotor lift with wind speeds of only 20 - 25 kts, and wind gusts will also have a major effect. Operations to Moving Helidecks On the UK continental shelf there have been a number of helicopter accidents and incidents on ship helidecks caused by excessive wave motions. The most recent (see Figure 11) occurred in November 2001 on the West Navion drillship west of Shetland, and is believed to have been caused by a failure in the ship’s dynamic positioning heading control. This caused the vessel to turn out of the wave/wind heading, resulting in a marked increase in helideck motion and a shift in the direction of the wind relative to the helicopter. The helicopter that was on the deck awaiting passenger embarkation was tipped over, resulting in serious injury to the co-pilot who was outside of the aircraft conducting his ‘walk-round’ checks at the time. A program of research [25] has been carried out to devise and validate a new Motion Severity Index (MSI). The aspect of the helideck motion that will cause the helicopter to slide or topple is simply the ratio of the horizontal and vertical accelerations: 10 I s ( X tt Ytt )1/ 2 / Z tt and changes in mean wind direction are to be addressed by the deck status scheme described below. where: Refinement of the overall scheme is in progress to add the concept of deck status to control on-deck handling procedures, and thereby address scenarios like the West Navion accident where changes in the vessel’s heading to the wind and/or waves occur after landing. Green status will equate to normal deck handling procedures and will be in force when the least stable aircraft is calculated to remain within limits regardless of post landing vessel or wind heading changes. By definition, any helicopter type will be able to land on any deck at green status. Amber status will apply when the deck is within limits for the most stable helicopter, but when a high risk of exceeding operating limits would exist in the event of a vessel or wind heading change after landing. Revised deck handling procedures will be employed for amber status to reduce the risk of a tip or slide, and to maximise the opportunity for the helicopter to lift off in the event of problems developing. It is possible that a deck at amber status may be out of limits for less stable helicopters having lower operating limits. Red status applies when the deck is out of limits for all helicopter types, and the helideck is consequently closed. A risk assessment is to be conducted to ensure that the green/amber and amber/red boundaries are set such that the overall safety level is acceptable. 2 2 X tt resultant surge acceleration parallel to the deck Ytt resultant sway acceleration parallel to the deck Z tt heave acceleration perpendicular to the deck The MSI is a statistical prediction of a maximum value of the motion severity that will be experienced during the period the helicopter remains on the helideck, and can be expressed as: MSI 2{2.Ln( N / )}1/ 2 .mo 1/ 2 where: N number of response cycles in the 10 minute time history (approximately 600/Tp, where Tp is the mean period). an assigned probability of exceedance. mo 1/ 2 the root mean square of the signal I s . It is intended that a standard accelerometer package will be mounted under the helideck to directly measure the accelerations. The rms value of Is, and hence the MSI, will be calculated from the acceleration data over the 10 minute period prior to the helicopter arrival on a continuous basis. A standard value of for use in the formula is to be established from a risk analysis. The main outstanding work stream for the project has been the validation of the computer model developed to establish helicopter limits of operability (in terms of the MSI and WSI). Field trials provided a degree of validation but insufficient confidence existed in the modelling of the aerodynamic effects, particularly at higher wind speeds when they become very significant and where experimental data is difficult to obtain safely. The recently completed analysis of full scale Sikorsky S76 rotor loads data from wind tunnel tests performed by NASA Ames [26], however, has resolved these difficulties and preliminary helicopter operating limits should be available for the S-76 and the Eurocopter Super Puma by autumn 2005. The single MSI number will be transmitted to the helicopter pilot, who will compare it with the limiting values established for his helicopter type and contained in the Company Operations Manual. The limiting values were originally expected to be dependent only on wind speed. Analysis of data from the West Navion accident and studies using the computer model developed for determining the limiting values of the MSI for individual helicopter types, however, have led to the replacement of wind speed as a controlling parameter in the individual helicopter operating limits with a wind severity index (WSI). The WSI is to be generated by the same motion sensing system that calculates the MSI using anemometer data provided via an industry standard interface. The WSI takes account of mean wind speed changes during the subsequent 10 minute period, and is calculated in a similar fashion to the MSI, i.e. a 10minute moving window of wind data is analysed to produce the statistically most likely maximum value for the subsequent 10-minute period while the helicopter will be on the helideck. The effects of wind gusting are to be accounted for in setting the helicopter operating limits, It is expected that the MSI and WSI values will be simple to transmit, with less risk of confusion than has been the case in the past with pitch, roll and heave motion values. The standard instrumentation and analysis to provide the MSI and WSI will also remove the current variability and uncertainty in the quality of the pitch, roll and heave estimates. More significantly, the MSI, WSI and associated helicopter operating limits will directly relate to the risk of the helicopter sliding or tipping on the deck, will be independent of the location of the helideck on the vessel and the vessel type (motion characteristics), and will address the period during which the helicopter is on the deck and exposed to the risk. 11 Helideck Lighting The UK CAA has, for a number of years, been seeking to improve the performance of lighting schemes on offshore helidecks. Current systems suffer from three main problems: the location of the helideck on the platform is difficult to establish due to the lack of conspicuity of the perimeter lights - the yellow perimeter lights blend in with the yellow light from the sodium floodlights widely used for general platform lighting; helideck floodlighting systems are frequently a source of glare and loss of pilots’ night vision on the deck, and further reduce the conspicuity of the helideck perimeter lights during the approach; the performance of most helideck floodlighting systems in illuminating the central landing area is inadequate, leading to a lack of visual cues and the so-called ‘black hole’ effect. Starting in 1995, a number of experimental lighting schemes were evaluated during a series of onshore and offshore flight trials, culminating in three dedicated trials at the NAM K14B satellite in the southern North Sea. During these trials, a number of changes to the current standard helideck lighting were evaluated. These included; Key Green Perimeter Light Yellow Perimeter Light Yellow LED Strip (1.5m/ 1m) Hatch White Floodlight Fire Extinguisher Green ELP (1m / 0.5m) Loudspeaker/ Bird Scarer changing the colour of the standard perimeter lights from yellow to green; using green electro luminescent panel (ELP) lighting in lieu of the standard perimeter lighting; adding hoods to the floodlights; turning the floodlights off; illuminating the ‘H’ in the centre of the landing area with green ELP; illuminating the inner and outer edges of the landing circle with yellow light-emitting diode (LED) strips. Green LED Strip (1m) Stairs Figure 12 - Experimental lighting equipment locations trialled on the K14B platform [27]. The overall conclusions of this work were that: The layout of this equipment on the trials helideck is illustrated in Figure 12. These changes were applied in a number of combinations, and the relative benefits were assessed by means of questionnaires that were completed at the end of each approach by the trials pilots while the next lighting configuration was being set up. Ratings for presentation and workload were awarded by the pilots on a ten-point scale. Each of the three trials commenced with an approach to the standard lighting configuration (yellow perimeter lights and floodlights without hoods), which was pre-allocated mid-scale workload and presentation ratings of five in order to ‘calibrate’ the pilots. changing the colour of the perimeter lights from yellow to green greatly increased the conspicuity of the helideck and extended the acquisition range; illuminating the ‘H’ in the centre of the helideck with green ELPs significantly enhanced the visual cueing environment during the final approach; illuminating the inner and outer edges of the landing circle with yellow light-emitting diode (LED) strips significantly enhanced the visual cueing environment from the final approach through to touchdown; the floodlights, with or without hoods, degraded the conspicuity of the helideck during acquisition and were a source of dazzle to the pilots while the helicopter was on the deck. As a result of these trials, the currently recommended lighting configuration for providing a significantly enhanced visual cueing environment is; green 12 incandescent perimeter lights, yellow LED strips illuminating the inner and outer edges of the landing circle, green luminescent illuminated ‘H’, and no floodlights. A photograph of this configuration taken during the trials is given in Figure 13. The final report on the NAM K14 trials has now been published [27]. obtain the information required to characterise the landing circle and ‘H’ lighting, to evaluate the suitability of a number of current products and try out some new ideas. A total of five trials were completed and the ‘highlights’ included: Figure 13 – Photograph of preferred lighting configuration as determined by the trials undertaken on the K14B platform [27]. The preferred configuration from the K14B trials was installed at Longside airfield near Aberdeen, UK, for further experimentation. The main aims of these trials were to evaluate a single lit landing circle (as opposed to a double circle), an outline ‘H’ (instead of a solid ‘H’), and the effect of a helideck net on the various lighting configurations. Two trials were completed during 2002, one without a helideck net installed and one with. The overall conclusions of these trials were: Without a net, a single ring of yellow LED strips around the landing circle was found to be adequate, and it was judged that this should be located midway between the inner and outer edges of the yellow painted marking. Without a net, an outline ELP ‘H’ was found to be better than the solid version. With a net fitted, there was a greater preference for two rings of yellow LED strips than was the case without the net. With a net fitted, the solid 'H' was much better than the outline version. A minimum acceptable baseline for the yellow LED landing circle has been established in terms of coverage (length of LED strips vs. length of gaps), LED density and LED intensity. An effective interim floodlighting configuration, comprising two high-mounted halogen floods at the Limited Obstacle Sector (LOS) with two deck level xenon floods on the opposite edge of the deck, has been identified. Green perimeter lights meeting the revised vertical intensity distribution have been evaluated and were favourably received by the trials pilots. No adverse effects of the increased intensity were noted. An LED Obstacle Free Sector (OFS) chevron marker has been evaluated and found to be useful, but only during the very final stages of the approach and landing. The cueing provided was not considered to match that provided by the ELP ‘H’. An outline ‘H’ formed using laser driven optical fibre has been trialled and found to perform much better than the existing ELP ‘H’; this technology is more affordable, more robust and the on-deck hardware is completely inert. The effect of rain on the cockpit windows has been evaluated and found to be insignificant if not non-existent. The effect of vertical approach profile on the range of the LED circle has been investigated and useful results obtained. The application of laser driven optical fibre to illuminate the helideck net has been trialled, but the result was considered to be too artificial or synthetic by the pilots. The effects of a helideck net on the key lighting configurations have been evaluated, and no significant problems were encountered. A specification for the illuminated landing circle and ‘H’ marking (in lieu of floodlighting) for the recommended lighting configuration has been produced and will be tendered with a view to producing prototype equipment for installation on an offshore platform for an extended in-service trial. The purpose of these trials will be to expose the lighting to a larger number of pilots, and to evaluate the lighting in a broader range of meteorological conditions. The final report on these trials has been completed and has been published in CAA Paper 2005/01 [28]. A new test bed was then installed at Norwich Airport to continue the trials work started at Longside airfield. The overall objective of this series of trials was to further improve and refine the revised helideck lighting system, Changes to the Annex 14 Volume 2 material have been accepted at ICAO. Guidance material has been 13 produced for the recommended interim lighting scheme (changing the colour of the perimeter lights to green and replacing the deck level floodlights with the new improved configuration), and formally issued to the UK Industry pending update of CAP 437 [23]. A number of helidecks in the UK sector of the North Sea have already installed the new green perimeter lighting. to ICAO Annex 6 Part III as a Recommended Practice for flight data recorder-equipped helicopters. Low Airspeed Measurement An aspect of flight operations monitoring unique to helicopters is the need for a measure of low airspeed in order to fully monitor the operation of the aircraft during the more demanding flight phases of take-off and landing. The pitot-static systems with which helicopters are equipped become increasingly inaccurate with reducing airspeed, primarily due to the influence of the main rotor wake, and effectively cease to function below a threshold airspeed of 20 to 50 knots (depending on helicopter type), and in sideways or rearwards flight. Helicopter Flight Data Monitoring - Extension to Low Airspeed Regime Background Flight operations monitoring (FDM) is a mature and wellestablished practice among a number of UK commercial airlines (e.g. British Airways, Britannia Airways and British Midland), with widely acknowledged safety benefits. In essence, it comprises the routine analysis of aircraft flight data to monitor compliance with defined operational criteria using a specialised computer program. The operational criteria include the corresponding aircraft flight manual limitations, safe margins around the operational interpretation of the flight manual, and definitions of the good practice and airmanship that pilot training programmes seek to instill. Where comparison of the actual operation of the aircraft with the defined criteria reveals reduced margins or noncompliances, appropriate action is taken within the airline to improve unsatisfactory practices. As this process is continuous, the effectiveness of any corrective action taken is automatically monitored. Specialised mechanically based sensors do exist for providing enhanced low airspeed information, but these suffer from a number of disadvantages (e.g. cost, maintenance and calibration overhead) which effectively render them inappropriate for a flight data monitoring programme. Alternative algorithmic-based solutions have been developed and trialled with varying degrees of success, but most require input parameters that are not currently available and are difficult/expensive to provide on helicopter flight data recording systems (e.g. AUM, cg location, servo positions). A potential alternative non-mechanical approach to synthesising low airspeed utilising only existing flight data parameters is to employ an Artificial Neural Network (ANN). Earlier work performed by Warwick University and Westland Helicopters Ltd in the UK, has demonstrated the potential of ANNs to predict low airspeed (and direction). An accuracy level of 4 knots (95%) was obtained when the technique was applied to Lynx and EH101 flight data that had been collected during low speed handling and performance trials. An in-service trial of the application of FDM to helicopters, known as the Helicopter Operations Monitoring Programme (HOMP), involving five Bristow Helicopters Super Puma aircraft was commissioned in 2000 and was funded by UK CAA and Shell Aircraft Limited. The trial was concluded at the end of August 2001 and the final project report published as CAA Paper 2002/02 [29]. The trial was very successful and the Industry decided to proceed with full implementation of helicopter FDM on the North Sea fleet in advance of any regulatory action. Current Research Following a competitive tendering process, work on developing an ANN based measure of helicopter low airspeed specifically for helicopter FDM programmes was launched at the end of January 2000 at Westland Helicopters Ltd. The first phase of this work entailed the use of an existing set of flight data recorder (FDR) records from 800 Super Puma flight sectors to train an ANN. The flight data comprised the normal FDR parameters, together with a measure of low airspeed provided by a hardware-based sensor. The sensor used was a gimbal-mounted pitot-static system known as HADS or LASSIE. Of the 25 analogue parameters available, the 20 detailed in the Table 1 were selected to train the ANN on the basis of their links to the prediction of airspeed established from other analytical methods. CAA continued to promote helicopter FDM by funding its extension to a second helicopter type (Sikorsky S76) and to a second offshore helicopter operator (CHC Scotia) in conjunction with the Industry-led full-scale implementation plan. These trials demonstrated the successful transfer of the safety benefits of helicopter FDM, and usefully identified significant differences between operators and between helicopter types. This work was reported in CAA Paper 2004/12 [30]. The ICAO Helicopter Tiltrotor Study Group (HTSG) was also impressed by the research and, in 2004, unanimously agreed to propose to add helicopter FDM 14 No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Parameter Pressure Altitude Collective Pitch Lateral Cyclic Pitch Fore/aft Cyclic Pitch Yaw Rate Indicated Airspeed Lateral Acceleration Fore/aft Acceleration Normal Acceleration Outside Air Temp. Pitch Attitude Radio Altitude Roll Attitude Main Rotor rpm Tail Rotor Pitch Mean Eng. Torque Rate of climb Pitch Rate Roll Rate Mass Units feet deg % % deg Kts g g g celsius deg feet deg rpm/10 deg Nm feet/s deg/s deg/s lb using the Super Puma FDR data. In order to simplify the problem, two MLPs were trained and tested. One was trained to predict longitudinal airspeed, and the second was trained to predict lateral airspeed. The training procedure comprised the following three stages: The pre-processing applied entailed modifying the input parameters so that their mean values were all zero, and their standard deviations were all unity. The network weights and bias units were generated using the Nguyen-Widrow [31] method to ensure that the active region of the layer’s neurons would be roughly evenly distributed over the input space. A comparison of the Levenberg-Marquardt [32] and Bayesian Regularisation [33] training algorithms was performed, and the latter selected as it was found to produce an MLP with significantly better generalisation. The performance of the longitudinal and lateral airspeed MLPs in training and testing is given in the Table 2. Table 1 - ANN input parameters. Three different types of ANN architecture were evaluated for the project: linear; multi-layer perceptron (MLP); radial basis function (RBF). All three were applied to the task of predicting longitudinal airspeed of an EH101 helicopter. The linear network achieved an accuracy of 9 Kts, and was significantly out-performed by the MLP and RBF versions which achieved accuracies of 4.3 Kts and 4.9 Kts respectively. The MLP architecture was judged superior to the RBF because of its greater simplicity and slightly better performance. A schematic of the basic MLP architecture is given in Figure 14. Input Layer Hidden Layer Pre-process data. Initialise network weights and bias units. Train network. MLP/Error Longitudinal Airspeed Predictor Lateral Airspeed Predictor 95% Error Deviation (Kts) Training Test ±3.6 ±11.2 ±2.5 ±5.4 Table 2 - Initial ANN performance. A sensitivity analysis was performed on the MLPs to attempt to identify the cause of the poorer than expected performance on the test data. In the case of the longitudinal airspeed MLP, collective pitch and radio altitude were found to be two of the key parameters which suggested that the MLP had learnt the flight profile rather than the relationship between the helicopter’s controls, state and airspeed. Radio altitude was also a key input for the lateral airspeed MLP, but to a lesser extent. Reference to the earlier Lynx and EH101 research indicated that, although collective pitch and radio altitude were significant factors, their contribution to the accuracy of the ANN was relatively small compared to fore/aft and lateral cyclic pitch. Collective pitch and radio altitude were therefore removed from the training data set and the MLPs retrained and re-tested with the following results. MLP/Error Longitudinal Airspeed Predictor Lateral Airspeed Predictor Output Layer Figure 14 - Schematic of a MLP with a single hidden layer; bias units are omitted. 95% Error Deviation (Kts) Re-training Re-test ±4.6 ±9.9 ±2.6 ±4.7 Table 3 - ANN performance following re-training. Although the results show an improvement, the performance was still disappointing. Further efforts to improve the performance of the MLPs were Having selected the ANN architecture and the input parameters, the next step was to train and test the ANN 15 unsuccessful, and attention eventually focused on the training data. Investigations then revealed that the calibration accuracy of the HADS used to provide the ‘truth’ reference to be ±8Kts. determine whether any of them were unacceptable. The generic form of the offshore approach is shown in Figures 15 and 16. A key feature of offshore approaches is the absence of a fixed final approach track; the approach is normally flown substantially into wind. Allowing the approach to be up to 10 out of wind would still result in 18 approaches per oil rig and there are 300+ rigs in the North Sea. Programming all of these into the navigation data base would clearly be impractical and, because manual entry of approach waypoints is not permitted (established pilot data entry error rates are too high for this critical flight phase) it is not possible to operate the GPS in approach mode. A second phase was therefore been added to the programme to conduct a flight trials programme to generate a more accurate training data set, repeat the Phase 1 exercise, and produce a module for incorporation into the helicopter FDM analysis software. All preparation work for the trials has been completed and the conduct of the trials presently awaits a suitable weather window. Use of GPS for Offshore Helicopter Operations - Low Visibility Approaches The best that can therefore be achieved is to operate the GPS in terminal mode, giving a full scale (2 dots) course deviation indicator (CDI) deflection of 1 NM and RAIM alarm limit of 1 NM. This is clearly inadequate for use with an offset initiation point (OIP) and a missed approach point (MAPt) at 1.5 NM and 0.75 NM respectively from the destination. It was therefore determined that the use of GPS be essentially restricted to providing an independent cross-check of the weather radar. Background Low visibility approaches to offshore platforms are currently based on the use of weather radar for navigation and as a means of detecting obstacles on the approach path. Although it has been used for this purpose for a number of years, weather radar is neither designed nor certificated for such operations. In addition, these operations were identified by the Human Factors Working Group [2] as an area of potential safety improvement. Consequently, UK CAA has been investigating alternative means of conducting these operations. These investigations have focussed on the use of GPS, and have included a series of trials activities and follow-on data analysis exercises which have been reported in CAA Papers 2000/5, 2003/2 and 2003/7 [34, 35, 36]. UK CAA believes that the results of these investigations have demonstrated GPS to have significant potential for use as an offshore approach aid. This is achieved by entering the destination as a waypoint and then using the GPS range and bearing information to check the position of the target on the weather radar display, i.e. using GPS as a psuedo VOR/DME station located at the destination. The proposed procedure comprises the following steps: Selection from the area navigation system database (fixed installations) or manual entry (mobile installations) of the destination. Manual entry of the IW (a GPS waypoint 5 NM downwind of the destination, i.e. half way between the intermediate fix (IF) and the final approach fix (FAF)) as a range and bearing from the destination. Operation of the GPS equipment in terminal mode. Comparison of weather radar and GPS range and bearing data to assist identification of the destination. Use of GPS guidance (via the CDI) to guide the aircraft towards the FAF. Use of GPS guidance (via the CDI) from the IW towards the OIP, using the CDI to establish the helicopter on the correct approach track and hence heading. Transition from GPS guidance to navigation on headings once the track is stabilised and before reaching 2.5 NM range from the destination. (NB: This represents a convenient and well defined point, because it is where the crew usually change scale on the weather radar.) Following on from this work, a hazard analysis of the use of GPS for helicopter offshore approaches is being conducted. This exercise has been split into two parts; the first deals with the use of existing North Sea helicopter GPS equipment to enhance the existing weather radar approaches; the second will focus on a GPS-based offshore approach for which new aircraft equipment will be required. GPS-Assisted Weather Radar Approaches The objective of this part of the study was to determine whether and how existing North Sea helicopter GPS equipment fits could be employed to improve the safety of the current airborne radar approach (ARA) procedures. The methodology employed was to: establish whether and how GPS could be used to mitigate the hazards associated with ARAs, and analyse the hazards associated with the defined GPS-assisted offshore approach procedure to 16 100 OIP IAF FAF IF MAPt Destination Figure 15 - ARA approach procedure (horizontal). IAF MAPt OIP FAF IF =>1500ft =>1000ft 0 1 2 3 4 5 6 NM Figure 16 - ARA approach procedure (vertical profile). Use of GPS range and bearing to the destination during the first segment of the final approach (IW to OIP) to cross-check weather radar information (for correct ‘painting’ of destination and, hence, other obstacles). Use of GPS range to the destination to enhance confidence in the weather radar determination of arrival at the OIP and MAPt. Use of GPS range and bearing to the destination to monitor separation from the destination. performed, however, to ensure that the use of GPS did not add any unacceptable hazards. The study employed the probability, severity and risk matrix criteria of JAA AMJ 25.1309. The table below summarises the results of this study which indicated no unacceptable risks. This procedure has been evaluated in simulator trials by two of the major North Sea helicopter operators and judged appropriate. For cross checking of range and bearing between the weather radar and GPS, analysis of the errors indicates a maximum expected discrepancy of 600m in range and 13 in bearing (at 4NM where the main check is to be performed). As a result of feedback from the simulator trials these figures were altered to the more conservative values of 550m (0.3 NM) and 10 respectively, to simplify the task. The benefits of this procedure are; assisting the identification of the destination; providing CDI guidance for establishment on the correct track (and therefore heading); and for cross checking the weather radar for gross errors. A hazard analysis of the procedure was Initial cause of deviation Helicopter tries to land on unsafe rig Conflict with another helicopter Incorrect flight crew waypoint selection/ IW entry/database checking causes deviation from intended path TOLERABLE TOLERABLE Incorrect flight crew waypoint entry causes deviation from intended path TOLERABLE TOLERABLE Incorrect aeronautical data causes deviation from intended path TOLERABLE TOLERABLE Incorrect position estimation causes the deviation from the correct approach path TOLERABLE TOLERABLE Table 4 - Hazards and risk tolerability. 17 Note that any hazards related specifically to the weather radar, such as failure to detect obstacles, are not included in the analysis as they are not a consequence of the use of GPS. the UK Continental Shelf, the results can clearly be applied to helicopter-based offshore oil and gas support operations anywhere in the world. Operating arenas where weather conditions are similar to those experienced around the UK for a significant proportion of the year, and/or where cessation of operations in bad weather is either undesirable or untenable may especially benefit from the application of the results of this work. GPS Approaches This section of the study will commence with a safety assessment of existing weather radar approaches to identify the weaknesses that a full GPS approach will need to address. The aircraft hardware and an associated operating procedure will then be formulated and subjected to a hazard analysis. Acknowledgements In addition to the hazard analysis, a European Union research initiative led by INNECO of Spain includes optional work on the North Sea helicopter application of GPS. The option presently comprises a data collection exercise to establish suitability of the European Geostationary Navigation Overlay Service (EGNOS) to provide the wide area differential corrections that are expected to be required, and simulator trials (at Eurocopter) for pilot evaluation of the approach procedures. The author would like to recognise the good work of the engineers and scientists at CAA’s research contractors who performed, and/or are performing, the research described in this paper. They are: BMT Fluid Mechanics, QinetiQ (Bedford), Atkins Process (Bristol and Epsom), Glasgow Caledonian University, Smiths Aerospace Electronic Systems Southampton, Westland Helicopters, Helios Technology and RGIT Montrose. References Following successful completion of the current work, full in-service trials of the DGPS based approach guidance system and procedures will be required to validate the system and procedure design prior to implementation. This will involve the development and installation of prototype equipment on a limited number of helicopters for evaluation. The evaluation will include the recording and analysis of system technical performance data, and the collection and analysis of flight crew feedback via questionnaires. [1] Helicopter Airworthiness Review Panel (HARP) of the Airworthiness Requirements Board, Review of helicopter airworthiness, CAP 491, CAA, London, June 1984 [2] Report of the Helicopter Human Factors Working Group, CAA Paper 87007, CAA, London, 1987. [3] Report on the Review of Helicopter Offshore Safety and Survival (“RHOSS”), CAP 641, CAA, London, February 1995. [4] Intelligent Management of HUMS Data, CAA Paper 99006, CAA, London, September 1999. [5] Laspalles, P.J. Rowe, S.J., Wave Height Probabilities on Helicopter Routes, BMT Fluid Mechanics Report 44140r13, July 1997. [6] FAA, Advisory Circular AC29-2C relating to JAR/FAR 29.801 Ditching 30th September 1999. [7] Helicopter Float Scoops, CAA Paper 95010, CAA, London, December 1995. [8] Devices to Prevent Helicopter Total Inversion Following a Ditching, CAA Paper 97010, CAA, London, December 1997. [9] Helicopter Ditching Research – Egress from SideFloating Helicopters, CAA Paper 2001/10, CAA, London, September 2001. [10] Westland Helicopters Limited, A review of UK military and world civil helicopter water impacts over the period 1971-1992, Stress Department report no. SDR 146, November 1993, published in CAA Paper 96005, CAA, London, July 1996. [11] Westland Helicopters Limited, An analysis of the response of helicopter structures to water impact, Stress Department report no. SDR 156, March Conclusions It has been the purpose of this paper to provide a brief overview of the origins of the UK CAA-led helicopter safety research programme, and to summarise current activities on the seven main ‘live’ research projects. The research programme has already led directly to significant progress being made in addressing a number of key safety issues. In particular; with regard to airworthiness, all UK North Sea offshore helicopters are fitted with HUMS; concerning operational matters, helicopter FDM either has been or is being implemented by all UK and Norwegian offshore helicopter operators. The current research on both of these initiatives is aimed at further enhancing their effectiveness. In addition, work on a number of the other significant safety initiatives covered in this paper is nearing completion and it is hoped that the results and lessons learned can be implemented in the near future. Although the work has been primarily aimed at improving levels of safety for helicopter operations on 18 [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] 1995, published in CAA Paper 96005, CAA, London, July 1996. Federal Aviation Administration, Survey and analysis of rotorcraft flotation systems, US Department of Transportation, Office of Aviation Research, report no. DOT/FAA/AR-95/53, 1996. Federal Aviation Administration, Rotorcraft ditchings and water related impacts that occurred from 1982 to 1989 - phase I, US Department of Transportation, Federal Aviation Administration Technical Center report no. DOT/FAA/CT-92/13, 1993. Federal Aviation Administration, Rotorcraft ditchings and water related impacts that occurred from 1982 to 1989 - phase II, US Department of Transportation, Federal Aviation Administration Technical Center report no. DOT/FAA/CT-92/14, 1993. Crashworthiness of Helicopter Emergency Flotation Systems, CAA Paper 2001/02 (Part 1), CAA, London, September 2001. Crashworthiness of Helicopter Emergency Flotation Systems, CAA Paper 2001/02 (Part 2), CAA, London, September 2001. Summary Report on Helicopter Ditching and Crashworthiness Research, CAA Paper 2005/06, CAA, London, 2005. Heavy Landing on Claymore Accommodation Platform, UK AAIB Bulletin No. 3/96, 18 August 1995. Research on Offshore Helideck Environmental Issues, CAA Paper 99004, London, August 2000. A questionnaire survey of workload and safety hazards associated with North Sea and Irish Sea helicopter operations, CAA Paper 97009, CAA, London, June 1997. Cooper G E, Harper R P, The Use of Pilot Rating in the Evaluation of Aircraft Handling Qualities, Report No.NASA-TN-D-5153, April 1969. Helicopter Turbulence Criteria for Operations to Offshore Platforms, CAA Paper 2004/03, CAA, London, September 2004. Offshore helicopter landing areas - guidance on standards, CAP 437, Third edition, CAA, London, October 1998. Larder, B. D., Final Report on the Helicopter Operations Monitoring Programme (HOMP) Trial, CAA Paper 2002/02, CAA, London, September 2002. Gallagher, P., Helicopter Operations to Moving Decks, Proceedings of Conference, “Helicopter Operations in the Maritime Environment”, Royal Aeronautical Society, London, March 2001. Shinoda, P.M and Johnson, W., Performance Results from a Test of an S-76 Rotor in the NASA Ames 80- by 120-Foot Wind Tunnel, AIAA 11th Applied Aerodynamics Conference, Monterey, CA, August 1993. AIAA-93-3414. [27] Enhancing Offshore Helideck Lighting – NAM K14 Trials, CAA Paper 2004/01, CAA, London, January 2004. [28] Enhancing Offshore Helideck Lighting – Onshore Trials at Longside Airfield, CAA Paper 2005/01, CAA, London, April 2005. [29] Final Report on the Helicopter Operations Monitoring Programme (HOMP) Trial, CAA Paper 2002/02, CAA, London, September 2002. [30] Final Report on the Follow-On Activities to the HOMP Trial, CAA Paper 2004/12, CAA, London, October 2004. [31] Nguyen, D. and Widrow, B., Improving the learning speed of 2-layer neural networks by choosing initial values of the adaptive weights, Proceedings of the International Joint Conference on Neural Networks, vol.3, July 1990, pp. 21-26. [32] Hagan, M.T. and Menhaj, M., Training feedforward networks with the Marquardt algorithm, IEEE Transactions on Neural Networks, vol.5, no.6, 1994, pp. 989-993. [33] Foresee, F.D. and Hagan, M.T., Gauss-Newton approximation to Bayesian Learning, Proceedings of the 1997 International Joint Conference on Neural Networks, 1997, pp. 1930-35. [34] DGPS Guidance for Helicopter Approaches to Offshore Platforms, CAA Paper 2000/05, CAA, London, November 2000. [35] DGPS Guidance for Helicopter Approaches to Offshore Platforms - Follow On Studies, CAA Paper 2003/02, CAA, London, June 2003. [36] Effect of Helicopter Rotors on GPS Reception, CAA Paper 2003/07, CAA, London, December 2003. 19