05/12/2019
4 Easy Ways to Set Smart Oil Analysis Alarms
4 Easy Ways to Set Smart Oil Analysis
Alarms
Ray Garvey, Emerson Process Management
Tags: oil analysis
Oil analysis is performed to monitor equipment and lubricant health. Alarm limits
are used to trigger an activity for either the analyst or the maintenance staff.
Alarm limits are threshold values, beyond which the measurement indicates a
potential unhealthy machine or lubricant condition. Wear and contaminationrelated parameters reflect equipment health while physical and chemical
properties of the oil reflect lubricant quality.
There are at least four different ways to determine the alarm status for oil
analysis reports. Each method has advantages. Whether oil analysis is
performed onsite or offsite, most analysts selectively use all four for the various
measured parameters.
1. No Predefined Limits
This method relies exclusively on human judgment and is based on experience
and overall interpretation. Experienced analysts review all data at one time while
considering the equipment and lubricant information supplied. Often, this
information is sketchy at best, or even nonexistent, when the sample arrives at
the lab.
Under these circumstances, the analyst tends to deduce information from the
measured parameters to compensate for the missing information, which the
customer failed to send along with the sample.
For instance, a sample that has a kinematic viscosity historically around 315 cSt
at 40°C with high zinc and phosphorous, is likely to be an ISO VG 320 gear oil.
Unless something in the analysis or label indicates differently, the analyst will
probably make this assumption and continue.
The experienced analyst has the ability to fill in missing pieces of information
using logic along with available data. He also identifies any data anomalies. He
relies on the combination of measurements to draw a conclusion, considering,
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for example, neutralization number, color and viscosity at the same time rather
than individually.
Some of this method’s advantages are flexibility, ability to make the best use of
incomplete information and opportunity to raise and to resolve questions. This
method is particularly useful in a lab that deals with various oils and applications.
Possible disadvantages of this method are inconsistency (particularly with
multiple analysts) and errors due to overlooked or misinterpreted information.
2. Industry Standard Limits or “Rules of Thumb”
Sometimes industry standards or original equipment manufacturer (OEM)
standard limits are published. These limits are normally statistically derived from
a large number of samples or from a controlled evaluation program. Engine
manufacturers and large fleet owners often recommend alarm limits for specific
equipment.
When available, these limits are probably the best ones to use. Unfortunately
this information is not available for the majority of lubricated machinery found in
industrial plants. Also, variation in the way individual machines or groups of
machines are operated and maintained can lead to poor conclusions.
In a few cases, industry standards organizations publish suggested limits for
certain parameters. The National Fluid Power Association (NFPA) has published
suggested ISO 4406 cleanliness levels for various types of equipment. Table 1
reports its recommended cleanliness codes (for example, alarm limits) for
hydraulic fluid power applications.
This information is also available at http://www.nfpa.com. Rules of thumb are
general guidelines or starting points for setting alarm limits. Three rules of thumb
for determining when to change oil due to its chemical oxidation include:
Base Number (BN) limit is half the value measured for new engine oil.
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Acid Number (AN) limit is two units higher than new industrial oil’s measured
value.
Dielectric limit is an increase of 0.10 units from value measured for new oil.
Notice that a percentage drop in BN and an absolute increase in AN or dielectric
is used to determine when to change oil. It is important to keep in mind that most
alarm limits are set from a baseline that may be either zero or a finite number
based on an earlier new or used oil sample measurement. The alarm limits may
be percentages or absolute values. They may be based on an increase in value
from the baseline, a decrease or both.
Some rules of thumb simply state that less is better. In the case of water
contamination, Pall Corporation reports that whatever the moisture-in-oil may be,
eliminating 75 percent of it can double the component’s relative life factor.1
British Hydromechanics Research Association (BHRA) studies make similar
statements about particulate contamination.
Rules of thumb should be implemented with some flexibility. The rules make
sense, yet alarm limits should have other supporting rationale.
3. Statistical Alarm Limits
If the OEM does not supply the statistical alarm limits, then the analyst should
determine the limits. After three months, plenty of data for a good statistical
baseline should be available.
Commercial software can generate a statistical histogram like the one shown in
Figure 1.
Click here to see Figure 1
This graph shows all the data measured on a single parameter for one alarm
limit (for example, an equipment type). The plot shows minimum to maximum
values measured on the X-axis compared to the percent of samples falling below
that value on the Y-axis.
The software helps identify multiple alarm levels corresponding to predefined
percentages. This method typically uses a series of alarms from low alert at the
80th percentile to extreme at the 98th percentile. These values should be
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recalculated each year. If the histogram-based alarm levels go down over time,
overall reliability is improving.
Calculated standard deviation is another useful statistical alarm method. Given
at least 30 measurements of a single parameter from an alarm limit, 1-sigma, 2sigma and 3-sigma standard deviations can be calculated (See Alarms and
Limits - Field-Tested Database Techniques on page 14).
For a one-tailed distribution, there is approximately a 15 percent chance that a
new measurement will be 1-sigma above the mean, a 3 percent chance that it
will be 2-sigma above, and much less than 1 percent chance that it will be 3sigma above the mean for all measured values. The sigma-limits should be used
in a manner similar to histogram percentiles to set statistical alarms.
4. Trend-based or Rate-of-change Limits
Trend-based or rate-of-change limits are the mathematical method used
intuitively by analysts who don’t use alarm limits. In this case, a departure from a
trend instead of an absolute value to trigger the alarm should be identified. In his
presentation at the Practicing Oil Analysis ‘99 Conference and Exhibition,
“Interpreting Oil Analysis Test Results,” Jack Poley suggested three practical
ways to automatically accomplish trend or rate-of-change alarms.2
1. Relative Magnitudes
This method looks for abrupt changes in consecutive historical data. A 60
percent increase from 5.0 to 8.0 will trip this alarm.
2. Rolling Average
This is similar to relative magnitudes except that it compares the new
measurement to an average of several historical measurements.
3. Factoring Delta Settings
Here, the problem with small values is addressed. This method requires
very large percent increases to trigger rate-of-change alarms for small
values (less than 5 percent) with diminishing percentages for larger
magnitude values. Using this method, the increase to trigger the alarm might
be 50 percent in the range of 50 to 80 but only 37 percent in the range of
200 to 400.
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The most commonly used method for rate-of-change alarming is graphical
trending. Normally this requires human interpretation, so it fits under the No
Predefined Limits category. In this method the analyst looks for a knee, or bend
in the trend plot. A hockey-stick plot, which is straight for a length of time and
then sharply rises, is good when measuring financial growth, but it is
symptomatic of a serious problem for most oil parameters.
There is not a schoolbook-approved solution for setting alarm limits on oil
analysis parameters. The important thing to keep in mind is that every
measurement reveals something about the machine wear, lubricant system
contamination or oil chemistry. Alarm limits should be used to focus attention on
the values indicating possible problems.
Alarm limits need not necessarily be set for every oil analysis parameter. Some
numbers on the lab report are there because the measuring instrument puts out
those numbers along with others, not because they are critical to the situation. It
is important to focus on the critical few parameters that reveal possible problems.
If alarm limits are not used, then it is necessary to rely on the analyst’s
experience. This works well if there is a lot of variation and only a few samples.
However, a computer could provide valuable assistance to the analyst by always
checking at least some of the alarms before looking at the data.
Industry standard alarms or rules of thumb are very useful, particularly when the
OEM supplies them. Statistical methods including histogram and standard
deviation-based alarming are excellent methods for setting alarms and
measuring overall changes in asset reliability. Trend-based and rate-of-change
alarms are also valuable techniques that software can use to flag possible
problems for the analyst.
Probably the best approach uses software-based alarms to consistently check all
the data. Then the analyst can resolve inconsistencies, draw conclusions and
make recommendations.
This article was originally published in CSI’s OilView News, Bulletin #88.
References
1. Pall Corporation (1993). "Contamination Control and Filtration
Fundamentals", PIHC-SEM93, p. 16.
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2. Poley, J. (1999). Interpreting Oil Analysis Test Results. "Practicing Oil
Analysis ‘99 Conference".
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