CM2008 / MFPT2008 CONFERENCE PROGRAMME
Tuesday 15th July
12:00 – 18:30
Registration
A
14:00-16:00
WORKSHOP: Acoustic emission for
condition monitoring: an introduction
Dr T Holroyd, Holroyd Instruments
Chair: Dr S King, Rolls-Royce
16:00-18:00
WORKSHOP: Condition monitoring
3rd party certification -your best option
Dr S Roe, PCN/BINDT
Chair: Prof L Kuravsky, Russian
Aviation Co.
B
WORKSHOP: Data management for condition
monitoring
Dr M Provost1, Mr C Mott2, Dr M Jessop3,
Bombardier Transportation1, nCode2,
University of York3
Chair: Mr J McAvoy, Cybula
WORKSHOP: Mathematical modelling and
computer simulation for supporting gear
diagnostic inference
Prof W Bartelmus, Wroclaw University of
Technology
Chair: Prof S Radkowski, Warsaw University
of Technology
C
WORKSHOP: Revisiting prediction methods
and the prognosis of remaining useful life
Dr C Byington, Impact Technologies
Chair: Prof L Kuravsky, Russian Aviation Co.
OPEN SESSION: Impact Technologies’
activities
Dr C Byington, Impact Technologies
Chair: Prof L Kuravsky
18:30 – 19:30
Welcome reception for CM2008/MFPT2008 Committee members and cash sponsors – by invitation only
19:30
CM2008 / MFPT2008 Welcome buffet
Wednesday 16th July
08:00
08:30
08:50
09:25
10:00
Registration
Opening ceremony
Plenary keynote lecture: [184] The significance of assets condition monitoring in the development of engineering asset management, Prof J Mathew,
Dr F Stapelberg, Australia
Chair: Mr R Lyon, President - BINDT
Plenary invited distinguished lecture: Wavelength diversity super-resolution for condition based maintenance, HRB Prof N Bose, USA
Chair: Mr R Lyon, President - BINDT
Tea, coffee & exhibition
1A
1B
1C
1D
1E
1F
Multidimensional
diagnostics of complex
mechanical systems
CHAIR: Prof S Radkowski,
Warsaw University of
Technology
[1] Vibro-acoustic
diagnostics of low-energy
stage of failures evolution
S Radkowski, Warsaw
University of Technology
Advanced signal
processing for condition
monitoring (1)
CHAIR: Dr N Martin, Gipsalab
NDE and health
monitoring of complex
structures
CHAIR: Prof L Fradkin,
London South Bank
University
[14] Special Presentation:
The role of acoustic
emission in monitoring
machines, processes and
structures
CHAIRS: Prof K Holford, Dr
R Pullin, Cardiff University
[19] The role of acoustic
emission in monitoring
machines and structures
R Reuben, Heriot Watt
University
Trained structures and
statistical methods for
condition monitoring (1)
CHAIRS: Prof L Kuravsky,
Dr S Baranov, Russian
Aviation Co.
[29] Development of the
wavelet-based confirmatory
factor analysis for
monitoring of system
factors
L Kuravsky, S Baranov,
Russian Aviation Co.
Experimental and virtual
models for machines and
plant diagnostics
CHAIR: Prof A Lucifredi,
University of Genova
Diagnostics of gas
turbine engines
CHAIR: Dr Y Li, Cranfield
University
[35] On the development of
virtual models, interfaced to
hardware and software
instruments, to support the
experimental activity for
diagnostic applications
A Lucifredi, P Silvestri,
University of Genova
[40] Model based diagnosis
technique for the
cogeneration system (effect
of operational condition on
characteristics of turbine
and compressor)
T Kawai1, Y Kamada2,
Osaka City University1,
Nissan Motor Co. Ltd2
10:50
[2] Usage of symbolic
analysis in condition
monitoring
A Galezia, S Radkowski,
Warsaw University of
Technology
[8] Space vector analysis
for the diagnosis of high
frequency amplitude and
phase modulations in
induction motor stator
current
M Chabert, B Trajin, J
Regnier, J Faucher,
ENSEEIHT
[20] Development and
application of higher
functionality acoustic
emission (AE) sensors
T Holroyd, Holroyd
Instruments
[34] Reliability-based
design of a slat track
fatigue life using mesh
morphing technology
R d’Ippolito1, S Donders1, M
Hack1, N Tzannetakis2, G
Van der Linden3, LMS1,
NOESIS Solutions2, ASCO
Industries3
[41] Gas path prognostic
analysis for an industrial
gas turbine
Y Li1, P Nilkitsaranont2,
Cranfield University1,
Chevron Thailand
Exploration and Production2
11:10
[3] Dynamic of ships shaft
line
A Grzadziela, Naval
University of Gdynia
[9] Complex-valued signal
processing for condition
monitoring
P Granjon, GIPSA-lab
[27] A new method of
localisation of vibration
sources and operational
defects in complex
constructions based on the
time reversal and the finite
element model of system
(part 1: theoretical
researches)
P Artelny, P Korotin, A
Suvorov, Institute of
Applied Physics RAS
[28] A new method of
localization of vibration
sources and operational
defects in complex
constructions based on the
time reversal and the finite
element model of system
(Part 2. Experimental
works)
P Artelny, P Korotin, A
Suvorov, Institute of
Applied Physics RAS
[33] Vibration analysis of
virtual damaged gears
C Carmignani, P Forte, G
Melani, University of Pisa
[42] A comprehensive
approach for measurement
validation and health state
determination of gas
turbines: methodology and
field application
M Venturini, R Bettocchi, M
Pinelli, P Spina, University
of Ferrara
10:25
[7] Frequency and
amplitude tracking for short
non stationary and
nonlinear signals
N Martin, M Vieira, Gipsalab
Non-destructive testing as a
tool in the space shuttle
Columbia accident
investigation
S McDanels, NASA
[18] Automatic NDT method
for crack detection
T Merazi, A University of
Sciences & Technology
[21] A Framework for
detecting fatigue fractures
using acoustic emission
J Hensman, K Worden, R
Pullin, K Holford, M Eaton,
S Evans, Cardiff University
1G
11:30
11:50
12:10
12:30
12:50
13:35
14:10
[4] Use of the principal
components analysis in the
diesel engine diagnostics
based on the spectrum of
the vibroacoustic signal
M Jasinski, G Boruta,
Warminsko-Mazurski
University
[5] Support Vector
machines and cluster
analysis for fault detection
and classification of rotating
equipment
K Gryllias, C Yiakopoulas, I
Antoniadis, National
Technical University of
Athens
[10] Comparison between
the frequency spectrogram
and polynomial modelling in
the characterisation of
cross-modulated vibration
components
F Leonard, Institut de
Recherche d’Hydro-Quebec
[11] Analysing MBN signals
of different materials by
time-frequency methods
L Padovese1, N Martin2,
University of Sao Paulo1,
GIPSA-lab2
[16] Modelling propagation
of ultrasonic guided waves
in the layered
steel/grout/steel structures
L Fradkin1, V Zernov1, P
Mudge2, London South
Bank University1, The
Welding Institute2
[17] Recent advances in
simulation of NDT
configurations
P Calmon, CEA LIST
[22] Acoustic emission for
corrosion detection
P Cole, J Watson, Physical
Acoustics
[26] Diagnosis and
monitoring complex
industrial processes based
on self-organising maps
C Frey, Fraunhofer Institute
[193] Virtual experimental
modal analysis: an
application of simulation
models to diagnostics
A Lucifredi, P Silvestri
University of Genova
[43] Turbomachinery
performance diagnostics –
a practical approach using
gas path analysis
P Escher1, J Zumbrunn1, J
Tan2, EscherTec1, Mariterm
SA2
[23] An attempt to correlate
gas void fraction with
acoustic emission
generated from two-phase
air / water flow
D Mba, S Al-lababidi, A
Addali, Cranfield University
[37] Using model-based
fault detection to simplify
predictive maintenance
A Bates, Artesis
[44] Gas path analysis
applied to an aero
derivative gas turbine used
for power generation
E Tsoutsanis1, Y Li1, P
Pildis1, M Newby2, Cranfield
University2, Manx Electricity
Authority2
[6] The application of
condition monitoring
methodologies for
certification of reliability in
electric landing gear
actuators
P Phillips1, D Diston1, J
Payne2, S Pandya2, A
Starr1, University of
Manchester1, Messier
Dowty2, University of
Hertfordshire3
[179] Calibration free,
optical measurements of
gas composition for
industrial process control in
harsh environments
W Johnstone, A McGettrick,
K Duffin, G Stewart,
University of Strathclyde
[12] Handling systems
condition monitoring using
vibrations and motor
current
S Sieg-Zieba, E Tructin, L
Jaubert, CETIM
Application of ultrasonic
guided waves for
monitoring components in
service
P Mudge, TWI
[24] Flight test of acoustic
emission damage detection
system on a military jet
I Read, P Foote, D
Tunnicliffe, J McFeat, Y
MacPheat, BAE Systems
[30] Studying influence of
manoeuvring loads
occurrences and climatic
conditions of basing on
aircraft damage
accumulation rate with the
aid of trained structures
S Baranov, L Kuravsky, N
Baranov, Russian Aviation
Co.
[31] Psychological training
on the base of a neuronet
technology
L Kuravsky, A Margolis, G
Yuriev, Moscow State
University of Psychology
and Education
[38] Role of support vector
classifiers in optimal model
selection fault detection of
rolling element bearings
Z Hameed, Y Hong, Y Cho,
C Song, Seoul National
University
[45] Detection of blades
rubs and looseness in gas
turbines – operational field
experience and laboratory
study
S Leong, L Hee, Malaysian
University of Technology
[13] A method for
distinguishing between
complex transient signals in
condition monitoring
applications
T Pinpart, G West, S
Galloway, M Judd,
University of Strathclyde
[187] A de-convolution
technique used for NDT in
x-ray & CT
K Chui1, A Wride1, D
Stanfield1, S Chui1, Image
Enhancement Technology1
Ltd, Worcester Acute
Hospital2
[25] Modelling and
quantification of acoustic
emission testing
P Wilcox, J Scholey, M
Wisnom, M Friswell,
University of Bristol
[32] Cepstral and statistical
analysis to determine the
fatigue crack depth in a
rotor system
T Malysheva, A Zakhezin,
South-Ural State University
[39] A new method of
damage detection by using
the reciprocal and timereversal properties of
elastic waves
H Go, Inha University
[46] Random and regular
modes of monitoring
V Giniotis1, M Rybokas1, A
Hope2, Vilnius Gediminas
Technical University1,
Southampton Solent
University2
Lunch & exhibition
Plenary keynote lecture: [190] Optical diagnostics for developing and testing clean combustion technologies, Prof D Greenhalgh, UK
Chair: Prof K Holmberg, VTT
Plenary invited distinguished lecture: Vibro-acoustic diagnostics of low energy faults, Prof S Radkowski, Poland
Chair: Prof K Holmberg, VTT
14:45
Tea, coffee exhibition
15:00
Britannia visit, dinner and guided Edinburgh tour
Thursday 17th July
08:00
08:30
09:05
09:40
Registration
Plenary keynote lecture: [106] Advanced signal processing in mechanical fault diagnosis, Prof S Lahdelma, Dr E Juuso, Finland
Chair: Prof L Gelman, Cranfield University
Plenary keynote lecture: [185] Condition monitoring and diagnostics as tools for maintenance, Prof J Vizintin, Slovenia
Chair: Mr R Lyon, President - BINDT
Tea, Coffee & Exhibition
2A
2B
2C
2D
2E
2F
2G
Integrated vehicle health
management (IVHM) –
advancements in CM,
sensor technology and
IVHM integration
frameworks and service
interfaces
CHAIR: Dr S Roe,
PCN/BINDT
[80] Integrated vehicle
health management (IVHM)
the next evolution within
condition monitoring
S Roe, PCN/BINDT
Incipient and developing
fault detection and
monitoring (1)
CHAIRS: Dr F Balitsky, Dr A
Sokolova, Machinery
Engineering Research
Institute, Russian Academy
of Science
[89] Condition monitoring of
the equipment in real-timetechnology of safe-save
maintenance of the 21st
century
V Kostyukov, SPC
Dynamics
[75] A resources based
engineering asset
management model
A Haider,University of
South Australia
[81] Knowledge
representation framework
for railway rolling stock
maintenance processes
D Lane1, E Miguelanez1, K
Brown1, A Roselli2, HeriotWatt University1,
MERMEC2
[82] Advanced rotorcraft oil
debris monitoring for the
21st century
S Greenfield, Eaton
Aerospace
[76] Hidden markov models
for condition monitoring of
bearing damage
E Karatoprak, Istanbul
Technical University
[188] A review, and
challenges in the
application of AE to
machinery monitoring
D Mba, Cranfield University
Damage detection and
diagnosis
CHAIR: Prof L Gelman,
Cranfield University
Diagnostics through
pattern recognition and
novelty detection (1)
CHAIR: Dr S King, Rolls
Royce
Pipeline and underground
asset condition
monitoring
CHAIR: Prof K
Horoshenkov, University of
Bradford
E-maintenance
CHAIR: Prof K Holmberg,
VTT
Trained structures and
statistical methods for
condition monitoring (2)
CHAIRS: Prof L Kuravsky,
Dr S Baranov, Russian
Aviation Co.
10:10
[47] Novel higher order
spectra for damage
detection in transient
conditions
L Gelman, E Lapena,
Cranfield University
[53] Pilot evaluation of
GRID technology for EHM
applications
S King, Rolls Royce
[60] The effect of
roughness on the
attenuation of eigen-modes
in water pipes
K Horoshenkov, G
Maximov, E Podjachev, E
Ortega, University of
Bradford
[66] Actors and roles in emaintenance
E Jantunen1, A Adgar2, A
Arnaiz3, VTT1, University of
Sunderland2, Fundacion
Tekniker3
10:35
[48] Quality assessment of
a laser cut based on
captured acoustic emission
signals
J Grum, T Kek, The
University of Ljubljana
[54] Incipient failure
prediction in aero engines
via empirical mode
decomposition
A Bird, Rolls Royce
[61] Sonic characterisation
of change in pipes
K Horoshenkov, A Tolstoy,
T Bin Ali, University of
Bradford
[67] The complexity of RFID
in reality – a Volvo case
S Apel, A Stromdahl, Volvo
[73] Fiber bragg gratings for
detection of planetary gear
damage in helicopter
transmissions
J Coker1, D Pines1, P
Samuel1, J Kiddy2, C
Baldwin2, University of
Maryland1, Aither
Engineering2
[74] Statistical techniques
for condition monitoring of
manufacturing processes
D Clifton, Oxford University
10:55
[49] Condition monitoring in
reality-widening horizons
beyond the machine: Part 1
K Innes, R Parchewsky,
Shell
[55] Constructing and retraining models for
condition monitoring in jet
engines
P Bannister, D Clifton, L
Tarassenko Oxford
University
[62] Using acoustic
reflectometry to detect
blockages in natural gas
pipe lines
B Lennox, K
Papadopoulou, X Wang, J
Turner, K Lewis, University
of Manchester
[68] Semantic web services
for a distributed emaintenance framework
E Gilabert, S Ferreiro, A
Arnaiz, Fundacion Tekniker
11:15
[49] Condition monitoring in
reality-widening horizons
beyond the machine: Part 2
K Innes, R Parchewsky,
Shell
[56] Gaussian process
latent variable models and
isomap for fault detection
within engine health
monitoring context
L Ecizola1, D King1, C
Fairbrother1, M Walters1, D
Ault1, I Sever1, S King1, V
Kadirkamanathan2, Rolls
Royce1, The University of
Sheffield2
[63] Rotating optical
geometry sensor for pipe
inspection
C Frey, Fraunhofer Institute
IITB
[69] Wireless sensing
strategies for plant
monitoring in DYNAMITE
project
S Mekid, R Pietruszkiewicz,
The University of
Manchester
[90] Incipient fault detection
as an obligatory component
of condition monitoring for
up-to-date predictive
maintenance
A Sokolova, F Balitsky,
MERI RAS
[135] Vibration condition
monitoring as a means of
service life management of
IBR-2 movable-reflector
modulator
V Sizarev, N Dollezhal,
Research and Development
Institute of Power
Engineering
[88] Rolling bearing field
fault detection and
diagnostics technique to
employ for gas turbine unit
casing vibration
A Sokolova, F Balitsky,
MERI RAS
11:35
[50] Vibration damage
detection in a aircraft
engine gearbox
F Combet1, L Gelman1, P
Anuzis2, R Slater2,
Cranfield University1, RollsRoyce2
[58] Overview of wireless
sensor research at the
Rolls-Royce control and
systems university
technology centre
H Thompson, Rolls Royce
Diagnosis and monitoring of
complex industrial
processes based on selforganising maps
C Frey, Fraunhofer
Institute, IITB
[70] A system for mobile
maintenance decision
support
J Campos1, E Jantunen2, O
Prakash1, Vaxjo University1,
VTT1
11:55
[52] Damage detection
through nonlinear excitation
and system identification
M Hajj, G Bordonaro,
Virginia Polytechnic
Institute and State
University
[142] In-service fatigue
prediction in turbomachinery
L Gelman, T Noble,
Cranfield University
[59] High dimensional
visualisation for novelty
detection
D Clifton, Oxford University
[64] Modelling wear
damage accumulation in
slurry pipeline systems
M Lipsett, University of
Alberta
[101] Engine health
monitoring and high
dimensional data
M Alkarouri, A Hills, V
Kadirkamanathan, The
University of Sheffield
[65] The development of
online wear debris analysis
sensor using pseudo 3D
images of particles and flow
control
R Matdan, M Khan, D
Cooper, A Starr,The
University of Manchester
[71] Vibrodiagnostic service
of compressor units of the
main line stations at the
level of gas-transport
conpany
V Zasetskij, A Tikhvinskij,
VNIIGAZ
[72] Investigation of
uncertainty in rotating
machinery vibration
monitoring and reliability of
diagnostics
M Eidukeviciute, Kaunas
University of Technology
12:15
12:35
13:50
14:25
15:00
[77] A validated model for
the prediction of
combustion related faults in
medium-speed diesel
engines using crankshaft
torsional vibration
P Charles, University of
Manchester
[79] Sensor fusion in CM
applications
T Bradshaw, Physical
Acoustics
[83] Monitoring of diesel
fuel injection using acoustic
emission (AE)
W Abdou, C Hunter, M
Shehadeh, J Steel, R
Reuben, Heriot-Watt
University
[134] Formation of
orthogonal diagnostic
attributes for
vibrodiagnostic purposes
V Kostjukov, SPC
Dynamics
[84] Automated decision
support system for lubricant
evaluation
M Timusk, G Dalton,
Laurentian University
[192] Dynamic behaviour of
a de-laminated composite
beam
I Ullah, J Sinha, University
of Manchester
[183] Mastering predictive
maintenance: static and
dynamic motor testing as
part of a predictive
maintenance program
T Thomas, Baker
Instrument Company
[85] Advanced acoustic
methods for on-stream
inspection
P Cole, Physical Acoustics
Ltd
[169] Diagnosis of incipient
gear failure using optimal
frequencies selection
method
L Castillo, UNED
Lunch & Exhibition
Plenary keynote lecture: [191] Predictive modelling of damage progression for reinforced composite materials, Prof A Long, UK
Chair: Prof K Holmberg, VTT
Plenary invited distinguished lecture: 5 steps to heaven: a Rolls-Royce perspective, Prof I Jennions, UK
Chair: Prof L Gelman, Cranfield University
Tea, coffee exhibition
3F
3G
Gear and bearing
condition monitoring and
diagnostics (1)
CHAIR: Prof W Bartelmus,
Wroclaw University of
Technology
3A
Optical sensors for
condition monitoring of
key plants
CHAIR: Dr P Niewczas,
University of Strathclyde
3B
Advanced signal
processing for condition
monitoring (2)
CHAIR: Prof S Lahdelma,
University of Oulu
3C
Ultrasonic guided waves
CHAIR: Dr T Gan, The
Welding Institute
3D
Prognostics
CHAIR: Mr V Fox, BAE
Systems
3E
Education and training in
maintenance
CHAIR: Dr C
Emmanouilidis, CETI
Institute
15:25
[96] External load yielding
statistical characteristics as
measures of machine
condition
W Bartelmus, R Zimroz,
Wroclaw University of
Technology
[182] Optical sensors for
condition monitoring of key
plants in energy production
P Niewczas, University of
Strathclyde
Advanced signal
processing in fault
diagnosis
S Lahdelma, E Juuso,
University of Oulu
[113] Long range inspection
of engineering assets using
guided ultrasonic waves
C Ennaceur, P Mudge, T
Gan, The Welding Institute
[120] Application of RAM-T
case for machinery failure
prevention
V Fox, BAE Systems
15:50
[97] Gearbox fault
diagnosis using Hilbert
transform and segmented
regression
M Hoseini, M Mandal, M
Zuo, G Mani, University of
Alberta
[180] Distributed optical
fibre sensing of
temperature using timecorrelated two-photon
excited fluorescence
C Dalzell, I Ruddock, T
Han, University of
Strathclyde
[107] New time domain
method for the detection of
roller bearing defects
T Doguer, J Strackeljan,
Otto-von-GuerickeUniversität Magdeburg
[114] Modelling of guided
ultrasonic waves in aircraft
wiring
Y Gharaibeh1, 2, S Soua1, S
Chan1, T Gan1, G
Edwards1, The Welding
Institute2, Brunel University2
[121] Revisiting prediction
methods and the prognosis
of remaining useful life
C Byington, M Roemer, G
Vachtsevanos, Impact
Technologies
[127] Current trends in etraining and m-training and
prospects for maintenance
vocational training
C Emmanouilidis, N
Papathanassiou, A
Papakonstantinou, CETI
Institute
[128] Next generation
maintenance systems
(NGMS): emerging
educational and training
needs to support an
adaptive approach to
maintenance planning and
improve decision support
A Labib, University of
Portsmouth
Incipient and developing
fault detection and
monitoring (2)
CHAIRS: Dr A Sokolva, Dr
F Balitsky, Machinery
Engineering Research
Institute, Russian Academy
of Science
[137] Classification of the
state monitoring systems
S Boichenko, SPC
Dynamics
[138] Correcting amplitude
and phase measurement of
accelerometer in frequency
domain
A Badri, K Sinha, University
of Manchester
16:10
[92] Application of signals
separation / extraction
techniques for diagnostics
of driving units in mining
machines
R Zimroz, Wroclaw
University of Technology
[181] In-fibre point sensing
of magnetic field strength
using novel photonic sensor
configurations
P Orr1, P Niewczas1, J
McDonald1, M Walsh2, W
Morris2, University of
Strathclyde1,
EURATOM/UKAEA2
[108] Radio frequency
measurements of bearing
currents in an induction
motor
V Särkimäki, J Ahola, T
Lindh, R Tiainen,
Lappeenranta University of
Technology
[115] Long term monitoring
of offshore installations
using ultrasonic guided
waves
P Mudge, M Kayous, S
Chan, The Welding Institute
[122] High frequency
vibration monitoring system
for incipient fault detection
and isolations of gears,
bearings and
shafts/couplings
C Byington, M Watson, J
Sheldon, H Lee, S Amin,
Impact Technologies
[129] An analysis of
maintenance education and
training needs in European
SME’s and an IT platform
enriching maintenance
curricula with industrial
expertise
Y Bakouros, S
Panagiotidou, University of
Western Macedonia+
16:30
[93] Examination of the
condition of gear wheels
affected by the complex
cases of gear transmission
damage
T Figlus, Silesian University
of Technology
[109] Design considerations
of energy harvesting
wireless sensors for
condition monitoring of
electric motors
J Ahola, V Särkimäki, T
Ahonen, A Kosonen, R
Tiainen, T Lindh,
Lappeenranta University of
Technology
[116] Modelling of long
range ultrasonic waves in
complex structures
S Soua, S Chan, T Gan,
The Welding Institute
[123] Power converter
prognostics
L Casey, M Prestero, G
Davis, F Flynn, J
Perkinson, SatCon
[130] Some European
initiatives in requirements
within the maintenance
function
J Franlund, UTEK
16:50
[95] Analytical description
and numerical simulation of
the dynamic behaviour of a
gear transmission with a
broken tooth
F Chaari, National School
of Engineers of Sfax,
Tunisia
[98] Instantaneous power
as a diagnostic symptom of
bearing damage
A Dzwonkowski1, L
Swedrowski1, J Rusek2,
Gdansk University of
Technology1, University of
Mining and Metallurgy2
[94] A study upon
vibroactivity of the
transmission housing with
the addition of ribs
T Figlus, Silesian University
of Technology
[178] Concept level
evaluation of a full-scale
deployment of fibre bragg
grating sensors for
measuring forces in JET
during plasma disruption
events
P Niewczas1, G Fusiek1, C
Lescure2, M Johnson2, E
Ivings2, A West2, P Crolla1,
M Walsh2,
University of Strathclyde1,
EURATOM/UKAEA2
[176] Wavelet analysis for
the investigation of
misaligned geophone
features
E Tshitshonu1, S Heyns2,
Vaal University of
Technology1, University of
Pretoria2
[157] Condition monitoring
using thin film ultrasonic
sensors
J Elgoyhen, J Hood, D
Hutson, K Kirk, University
of the West of Scotland
[154] Case-based condition
monitoring in large scale
systems
T Ahola1, E Juuso2,
Outokumpu Tornio Works1,
University of Oulu2
[117] Development of a
permanent installation tool
for structural health
monitoring
M Kayous, G Penney, I
Daniel, P Jackson, Plant
Integrity Ltd
[124] Predictive wear debris
characteristics for
prognosis of scuffing under
lubricated reciprocated
sliding
T Itoh, Oita Technical
College
[131] Analysis of the skills
gap and training
requirements within the
maintenance function
A Adgar, D Baglee,
University of Sunderland
[139] High energy x-ray
diffraction as a method of
strain analysis
S Zhang1, A Korsunsky2,
ISIS Facility1, University of
Oxford
[110] Acoustic emissions
from oil lubricated metal on
metal sliding contacts
L Wang, R Wood, J Sun,
University of Southampton
[118] Training and
certification in long range
ultrasonic testing
M Spicer, C Ennaceur, P
Mudge, The Welding
Institute
[125] Motor condition
monitoring: efficiency does
matter
T Thomas, Baker
Instrument Company
[132] Integrated equipment
effectiveness (IEE)
F Anvari1, R Edwards1, A
Starr2, The University of
Manchester1, The
University of Hertfordshire2
[87] Problems of technical
diagnostics of machines
and equipment
A Lukiyanov, S Eliseev, A
Khomenko, Irkutsk State
University of Railway
Engineering
[102] An artificial
intelligence approach for
measurement and
monitoring of pressure at
the residual limb/socket
interface
P Sewell1, S Noroozi1, J
Vinney1, R Amali2, S
Andrews3, Bournemouth
University1, University of
the West of England2,
Southmead Hospital3
[111] Monitoring bending
fatigue failure in helical
gears using acoustic
emission, vibration and online oil debris analysis: a
comparative study
A Onsy1, R Bicker1, B
Shaw1, C Rowland2, T
Kent3, Newcastle
University1, University of
Southampton2, Kittiwake3
[119] Monitoring of
hydrogen assisted cracking
in high strength bolts using
leave-in-place ultrasonic
sensors
D Xiang1, G Zhao1, R
Bayles2, Intelligent
Automation Inc1, Naval
Research Laboratory2
[126] A preliminary study
for the efficiency of the
wear debris analysis and
thermography as
independent or integrated
fault diagnosis methods in
tool wear monitoring
P Botsaris, I Tsanakas, I
Siouris, Demokritos
University of Thrace
17:10
17:30
18:00
18:00 – 18:45
19:45 for 20:00
Exhibition close
International Scientific Advisory Committee meeting (Session room B)
Conference Dinner
[133] Carbon nanotube
thread for multifunctional
structures
M Schulz1, N Mallik1, C
Jayasinghe1, P Salunke1, G
Li, D Hurd1, W Cho1, E
Head1, V Shanov1, X Zhu1,
T Wang1, M Abu-Ali1, B
Walker1, J Lee1, M Kumar1,
S Yarmolenko2, J Sankar2
University of Cincinnati1,
North Carolina Agricultural
and Technical State
University2
[158] Acoustic emission
techniques applied to
steam wastage estimation
and fault detection in an
industrial process heating
application
S Ramadas, University of
Southampton
[86] A new approach to
machinery vibration
analysis
A Prygunov, Murmansk
State Technical University
Friday 18th July
08:00
09:00
09:35
10:10
10:30
11:05
Registration
Plenary keynote lecture: [189] The role of IVHM in delivering competitive strategies, Prof T Baines, UK
Chair: Prof L Gelman, Cranfield University
Plenary invited distinguished lecture: Multi-agent approaches for IVHM architectures, Dr A Tsourdos, UK
Chair: Prof L Gelman, Cranfield University
Tea & coffee
Plenary invited distinguished lecture: Health monitoring and reliability, Mr P Anuzis, UK
Chair: Prof L Gelman, Cranfield University
Panel Session: Future directions in condition monitoring and failure prevention
4C
4D
4E
4F
4G
Damage detection,
diagnosis and prognosis
CHAIR: Dr W Matta,
Vitrociset
4A
Diagnostics through
pattern recognition and
novelty detection (2)
CHAIR: Dr S King, Rolls
Royce
Advanced reasoning and
diagnosis in condition
monitoring
CHAIR: Dr E Juuso,
University of Oulu
Condition based
monitoring – how to make
it a friend
CHAIR: Dr T Lago, Acticut
International
Integrated techniques for
diagnostics
CHAIR: Prof J Vizintin,
University of Ljubljana
12:20
Key example of integrated
logistics support
A Bucaioni, Vitrociset
[100] A data mining
approach to reveal patterns
in aircraft engine and
operational data
S Sundaram, Oxford
BioSignals
[152] Intelligent condition
indices in fault diagnosis
E Juuso, S Lahdelma,
University of Oulu
[159] Condition based
monitoring – how to make it
a friend
T Lago, Acticut
International
Advanced prognostic
technologies and
reliability of structures
CHAIR: Prof S Fu,
Shanghai Jiao Tong
University
[146] A probabilistic “design
allowable” method of
composite laminates
H Fan, X Chen, H Wang,
Shanghai Jiao Tong
University
12:45
Vitrociset activities in the
area of health management
W Matta, Vitrociset
[103] Condition monitoring
of electric motor based on
parameter identification
using genetic algorithm
J Treetrong1, J Sinha1, F
Gu2, A Ball2, The University
of Manchester1, The
University of Huddersfield2
[160] Classification of
production line data, a
challenging task?
A Brandt, T Lago, Acticut
International
[140] Asset management,
maintenance and condition
monitoring techniques
explained to the layman
D Manning-Ohren, ERIKS
[99] Model based fault
diagnosis in a rotor-bearing
system
N Vyas, N Ramakrishna,
Indian Institute of
Technology
[172] A method for
generalized prognostics of
a component using paris
law and kalman filter
Eric Bechhoefer1, W
Wang2, Goodrich Sensors
and Integrated Systems1,
Defence Science and
Technology Organisation2
[173] Localised fault
diagnosis in rolling element
bearings in gearboxes
N Sawalhi, R Randall, The
University of New South
Wales
[147] In-plane elastic
constants FEM prediction of
stitched composite
sandwich structure with
foam core
H Yang, X Zhang, H Wang,
Shanghai Jiao Tong
University
13:05
[153] Artificial immune
system approach for the
fault detection in rotating
machinery
J Strackeljan1, K
Leiviska2,Otto-vonGuericke-Universitat
Magdeburg1, University of
Oulu2
[156] Wear debris basic
shapes classification by
using fuzzy logic
M A Khan1, D Cooper1, R
Matdan1, A Starr2,
University of Manchester1,
University of Hertfordshire2
[164] Development of an
intelligent rotating
machinery diagnostics
programme
B Suhac1, J Vizintin1, B
Krzn1, U Benko2, D Juricic2,
University of Ljubljana2,
Jozef Stefan Institute2
[165] Pitting detection of
operating gears using
cyclostationary vibration
analysis
P Boskoski1 , D Juricic1, J
Vizintin, Jozef Stefan
Institute1, University of
Ljubljana2
Gear and bearing
condition monitoring and
diagnostics (2)
CHAIR: Dr W Wang,
Defence Science and
Technology Organisation
[171] Autoregressive model
based diagnostics for gears
and bearings
W Wang, Defence Science
and Technology
Organisation
13:25
Lunch
4B
[161] Classification of metal
cutting vibrations, is it all
chatter?
L Hakansson, T Lago,
Acticut International
[166] Assessing the quality
of electrical motors by
means of integrated
diagnostic techniques
D Juricic, J Petrovcic, B
Musizza, U Benko, G
Dolanc, Jozef Stefan
Institute
[150] Experimental study of
flaws detection at the
transition zone of sucker
rod using guided waves
based on magnetostritive
effect
J Xu, X Wu, L Wang, C
Huang, Y Kang, Huazhong
University of Science and
Technology
14:05
[141] Bayesian data fusion:
ignoring and mitigating the
constraint of feature
independence
N Sedgwick, Cambridge
Algorithmica
[136] High temperature thin
film transducers for
condition monitoring
J Hood, J Elgoyhen D
Hutson, K Kirk, University
of the West of Scotland
[155] Tuning of linguistic
equations for failure mode
identification using genetic
algorithms
O Yahyaoui1, S Gebus2, E
Juuso2, M Ruusunen2,
ESSTIN1, University of
Oulu2
14:25
[144] Optimal filtering of
gear signals for early
damage detection based on
the spectral kurtosis
F Combet, L Gelman,
Cranfield University
[177] Oil film measurement
in rolling bearing using thin
film ultrasonic transducer
K Kirk1, J Elgoyhen1, J
Zhang2, B Drinkwater2, R
Dwyer-Joyce3, University of
the West of Scotland1,
University of Bristol2,
University of Sheffield3
[145] Optimisation of
damage detection in
transient case
L Gelman, I Petrunin,
Cranfield University
14:45
Conference close
[162] Condition monitoring
application for the
production line of
compressors
P Potocnik1, P Muzic1, E
Govekar1, V Dragos2, T
Strmec2, University of
Ljubljana1, Danfoss
Compressors2
[105] Instantaneous angular
speed monitoring of a
reciprocating compressor
model
A Sasi1, A Ball2, The High
Institute of Industry1, The
University of Huddersfield2
[167] On-line wear and
lubrication condition
monitoring
B Krzan, J Vizintin,
University of Ljubljana
[174] Fault detection in gear
boxes using a non-contact
rotational position sensor
M Taylor1, C Mechefske1, M
Timusk2, Queen’s
University1, Laurentian
University2
[149] Stochastic responses
of energy absorption
mechanism of composite
cylinder in thermal
environment
Y Yan, Q Tian, X Wang, J
Xu, Shanghai Jiao Tong
University
[168] System of forecasting
and non-destructive control
over operational frictionalwear parameters of
machines’ frictional knots
V Khovanaskiy, Institute of
Tribology
[175] Intelligent gearing
system – solution to
understand and correct
operational conditions that
reduce the fatigue life of a
girth gear
D Dyk, David Brown Gear
Industries Ltd
[170] Noise cancellation in
sonic non-destructive
testing
A Joghatae, Foam i