ASTM D7669-11
(Guide)Standard Guide for Practical Lubricant Condition Data Trend Analysis
Standard Guide for Practical Lubricant Condition Data Trend Analysis
SIGNIFICANCE AND USE
This guide is intended to provide machinery maintenance and monitoring personnel with a guideline for performing trend analysis to aid in the interpretation of machinery condition data.
SCOPE
1.1 This guide covers practical techniques for condition data trend analysis.
1.2 The techniques may be utilized for all instrumentation that provides numerical test results. This guide is written specifically for data obtained from lubricant samples. Other data obtained and associated with the machine may also be used in determining the machine condition.
1.3 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.
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Designation: D7669 − 11
StandardGuide for
Practical Lubricant Condition Data Trend Analysis
This standard is issued under the fixed designation D7669; the number immediately following the designation indicates the year of
original adoption or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. A
superscript epsilon (´) indicates an editorial change since the last revision or reapproval.
INTRODUCTION
Maximum reliability of in-service machine components and fluids requires a program of condition
monitoring to provide timely indications of performance and remaining usable life. In order to
diagnose and predict machinery and fluid condition, the rate of change must be trended. Level alarms
only state how much damage has occurred. The predictive or forecasting nature of condition
monitoring is based on trending in order to determine the degree of damage and remaining useful life
of the component or fluid.
Equipment maintainers expect condition-monitoring information to clearly and consistently
indicate machinery condition, that is, the rate-of-change of component damage over time and the risk
of failure. The data trending procedure must automatically adapt to equipment usage and sampling
circumstancesandprovidenumbersthat reflect equipment condition change in an incremental fashion.
1. Scope 3. Terminology
3.1 Definitions of Terms Specific to This Standard:
1.1 Thisguidecoverspracticaltechniquesforconditiondata
trend analysis.
3.1.1 alarm limit, n—set-point threshold used to determine
the status of the magnitude or trend of parametric condition
1.2 The techniques may be utilized for all instrumentation
data.
that provides numerical test results. This guide is written
specifically for data obtained from lubricant samples. Other
3.1.2 dead oil sampling, n—oil sample taken that is not
data obtained and associated with the machine may also be
representative of the circulating or system oil due to one of
used in determining the machine condition.
several reasons, including the fluid in the system is static, the
sample is taken from a non-flowing zone, and the sample point
1.3 This standard does not purport to address all of the
ortubewithintheoilwasnotflushedtoremovethestagnantoil
safety concerns, if any, associated with its use. It is the
in the tube.
responsibility of the user of this standard to establish appro-
priate safety and health practices and determine the applica-
3.1.3 lubricant condition monitoring, n—field of technical
bility of regulatory limitations prior to use.
activity in which selected physical parameters associated with
an operating machine are periodically or continuously sensed,
2. Referenced Documents
measured, and recorded for the interim purpose of reducing,
analyzing, comparing, and displaying the data and information
2.1 ASTM Standards:
so obtained and for the ultimate purpose of using interim
D4057 Practice for Manual Sampling of Petroleum and
results to support decisions related to the operation and
Petroleum Products
maintenance of the machine.
D4177 Practice for Automatic Sampling of Petroleum and
Petroleum Products
3.1.4 machinery health, n—qualitative expression of the
operational status of a machine subcomponent, component, or
entire machine, used to communicate maintenance and opera-
1 tional recommendations or requirements in order to continue
This guide is under the jurisdiction of ASTM Committee D02 on Petroleum
Products and Lubricants and is the direct responsibility of Subcommittee D02.96.04
operation, schedule maintenance, or take immediate mainte-
on Guidelines for In-Services Lubricants Analysis.
nance action.
Current edition approved Feb. 15, 2011. Published April 2011. DOI:10.1520/
D7669–11.
3.1.5 optimum sample interval, n—optimum (standard)
For referenced ASTM standards, visit the ASTM website, www.astm.org, or
sample interval is derived from failure profile data. It is a
contact ASTM Customer Service at service@astm.org. For Annual Book of ASTM
fraction of the time between initiation of a critical failure mode
Standards volume information, refer to the standard’s Document Summary page on
the ASTM website. and equipment failure. In general, sample intervals should be
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United States
D7669 − 11
short enough to provide at least two samples prior to failure. debris, contamination ingress and fluid condition. Maintenance
The interval is established for the shortest critical failure mode. events should always occur after a sample is taken (or
condition test is performed).All maintenance events should be
3.1.6 prognostics, n—forecast of the condition or remaining
documented and taken into account during condition data
usable life of a machine, fluid, or component part.
interpretation. In all cases, maintenance events, if not reported,
3.1.7 remaining usable life, n—subjective estimate based
will reduce trending reliability.
upon observations or average estimates of similar items,
6.4 Sampling Procedures—Improper or poor sampling tech-
components, or systems, or a combination thereof, of the
niques can profoundly impact condition test data (see Practices
number of remaining time that an item, component, or system
D4057 and D4177). A significant difference in the test data
is estimated to be able to function in accordance with its
could trigger a false trend alarm. Examples of poor sampling
intended purpose before replacement.
techniques are:
3.1.8 sample population, n—group of samples organized for
6.4.1 Stagnant sampling,
statistical analysis.
6.4.2 Sampling after component change out,
3.1.9 trend analysis, n—monitoring of the level and rate of
6.4.3 Sampling after oil, or filter changes, or both,
change over operating time of measured parameters.
6.4.4 Irregular sample intervals,
3.2 Symbols:
6.4.5 Sampling intermittent or standby equipment without
circulating the oil and bringing the equipment to operating
temperatures.
Avg = average
6.5 Laboratory and Testing Practices—The tools used to
C = current sample
perform the condition monitoring tests impact the data.
H = usage metric (for example, hours)
OI = time on-oil interval 6.5.1 Analytical instrument differences impact data reliabil-
P = previous sample
ity. Trending should only be performed on results from the
PP = predicted prior sample
same make and model of test instrument. For example,
SSI = standard sample interval
trending atomic emission inductively coupled plasma (ICP)
T = trend
results should be from ICPs with the same sample introduction
configuration, same plasma energy, and preferably, the same
4. Summary of Guide
manufacturer and model.
4.1 This guide provides practical methods for the trend
6.5.2 Analytical instruments with poor measurement repeat-
analysis of condition data in the dynamic machinery operating
ability and reproducibility will result in correspondingly poor
environment. Various trending techniques and formulae are
trending. Testing repeatability should also be included with the
presented with their associated benefits and limitations.
trending studies.
6.5.3 Inappropriate analysis techniques can hide or distort
5. Significance and Use
interpretational conclusions. The condition-monitoring tool
5.1 This guide is intended to provide machinery mainte- chosen must provide evidence of the critical failure modes
nance and monitoring personnel with a guideline for perform- under review.
ing trend analysis to aid in the interpretation of machinery
6.6 Machinery Wear Process—Wearmetalconcentrationsin
condition data. 4
oil are subject to variability.
6.6.1 Filters remove the majority of debris particles greater
6. Interferences
thanfilterporesize.Thusanoilsampleonlycapturesnewwear
6.1 Sampling, maintenance, filter, and oil changes are rarely
and small, suspended, old wear.
performed at precise intervals. These irregular, opportunistic
6.6.2 Wear particle release is event driven; increased load or
intervals have a profound effect on measurement data and
speed can result in increased wear.
interfere with trending techniques.
6.6.3 The rate of wear debris release is not linear with time.
6.2 Machinery Operation—Operationalintensitycanimpact For many fault mechanisms, wear occurs in bursts.
how quickly a component wears and how rapidly a fault 6.6.4 Wear metal analysis methods can have particle size
3,4
progresses. A relevant indicator of machine usage must be limitations that should be included in the evaluations. For
included in any calculations.The selected usage indicator must example, ICP metal analyses are limited to those particles
reflect actual machine usage, that is, life consumed (for below nominally 8 microns.
example, stop/start cycles, megawatt hours, hours of use, or
6.7 Reservoir/Sump Volumes—Fluid and wear condition
fuel consumption).
parametersareconcentrationmeasurementsandareaffectedby
6.3 Maintenance Events—Component, filter, and oil reservoir/sump size. Varying the oil volumes in a reservoir can
changes impact the monitoring of machine performance, wear
impact the trending analysis. For example, infrequent top ups
allowstheoilvolumetodecreaseandthusconcentratethewear
debris and contaminants. Alternatively, lar
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