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    ASTM D7669-2011 8750 Standard Guide for Practical Lubricant Condition Data Trend Analysis《实际润滑条件数据趋势分析的标准指南》.pdf

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    ASTM D7669-2011 8750 Standard Guide for Practical Lubricant Condition Data Trend Analysis《实际润滑条件数据趋势分析的标准指南》.pdf

    1、Designation: D7669 11Standard Guide forPractical Lubricant Condition Data Trend Analysis1This standard is issued under the fixed designation D7669; the number immediately following the designation indicates the year oforiginal adoption or, in the case of revision, the year of last revision. A number

    2、 in parentheses indicates the year of last reapproval. Asuperscript epsilon () indicates an editorial change since the last revision or reapproval.INTRODUCTIONMaximum reliability of in-service machine components and fluids requires a program of conditionmonitoring to provide timely indications of pe

    3、rformance and remaining usable life. In order todiagnose and predict machinery and fluid condition, the rate of change must be trended. Level alarmsonly state how much damage has occurred. The predictive or forecasting nature of conditionmonitoring is based on trending in order to determine the degr

    4、ee of damage and remaining useful lifeof the component or fluid.Equipment maintainers expect condition-monitoring information to clearly and consistently indicatemachinery condition, that is, the rate-of-change of component damage over time and the risk offailure. The data trending procedure must au

    5、tomatically adapt to equipment usage and samplingcircumstances and provide numbers that reflect equipment condition change in an incremental fashion.1. Scope1.1 This guide covers practical techniques for condition datatrend analysis.1.2 The techniques may be utilized for all instrumentationthat prov

    6、ides numerical test results. This guide is writtenspecifically for data obtained from lubricant samples. Otherdata obtained and associated with the machine may also beused in determining the machine condition.1.3 This standard does not purport to address all of thesafety concerns, if any, associated

    7、 with its use. It is theresponsibility of the user of this standard to establish appro-priate safety and health practices and determine the applica-bility of regulatory limitations prior to use.2. Referenced Documents2.1 ASTM Standards:2D4057 Practice for Manual Sampling of Petroleum andPetroleum Pr

    8、oductsD4177 Practice for Automatic Sampling of Petroleum andPetroleum Products3. Terminology3.1 Definitions of Terms Specific to This Standard:3.1.1 alarm limit, nset-point threshold used to determinethe status of the magnitude or trend of parametric conditiondata.3.1.2 dead oil sampling, noil sampl

    9、e taken that is notrepresentative of the circulating or system oil due to one ofseveral reasons, including the fluid in the system is static, thesample is taken from a non-flowing zone, and the sample pointor tube within the oil was not flushed to remove the stagnant oilin the tube.3.1.3 lubricant c

    10、ondition monitoring, nfield of technicalactivity in which selected physical parameters associated withan operating machine are periodically or continuously sensed,measured, and recorded for the interim purpose of reducing,analyzing, comparing, and displaying the data and informationso obtained and f

    11、or the ultimate purpose of using interimresults to support decisions related to the operation andmaintenance of the machine.3.1.4 machinery health, nqualitative expression of theoperational status of a machine subcomponent, component, orentire machine, used to communicate maintenance and opera-tiona

    12、l recommendations or requirements in order to continueoperation, schedule maintenance, or take immediate mainte-nance action.3.1.5 optimum sample interval, noptimum (standard)sample interval is derived from failure profile data. It is afraction of the time between initiation of a critical failure mo

    13、deand equipment failure. In general, sample intervals should beshort enough to provide at least two samples prior to failure.The interval is established for the shortest critical failure mode.3.1.6 prognostics, nforecast of the condition or remainingusable life of a machine, fluid, or component part

    14、.1This guide is under the jurisdiction of ASTM Committee D02 on PetroleumProducts and Lubricants and is the direct responsibility of Subcommittee D02.96.04on Guidelines for In-Services Lubricants Analysis.Current edition approved Feb. 15, 2011. Published April 2011. DOI:10.1520/D766911.2For referenc

    15、ed ASTM standards, visit the ASTM website, www.astm.org, orcontact ASTM Customer Service at serviceastm.org. For Annual Book of ASTMStandards volume information, refer to the standards Document Summary page onthe ASTM website.1Copyright ASTM International, 100 Barr Harbor Drive, PO Box C700, West Co

    16、nshohocken, PA 19428-2959, United States.3.1.7 remaining usable life, nsubjective estimate basedupon observations or average estimates of similar items,components, or systems, or a combination thereof, of thenumber of remaining time that an item, component, or systemis estimated to be able to functi

    17、on in accordance with itsintended purpose before replacement.3.1.8 sample population, ngroup of samples organized forstatistical analysis.3.1.9 trend analysis, nmonitoring of the level and rate ofchange over operating time of measured parameters.3.2 Symbols:Avg = averageC = current sampleH = usage m

    18、etric (for example, hours)OI = time on-oil intervalP = previous samplePP = predicted prior sampleSSI = standard sample intervalT = trend4. Summary of Guide4.1 This guide provides practical methods for the trendanalysis of condition data in the dynamic machinery operatingenvironment. Various trending

    19、 techniques and formulae arepresented with their associated benefits and limitations.5. Significance and Use5.1 This guide is intended to provide machinery mainte-nance and monitoring personnel with a guideline for perform-ing trend analysis to aid in the interpretation of machinerycondition data.6.

    20、 Interferences6.1 Sampling, maintenance, filter, and oil changes are rarelyperformed at precise intervals. These irregular, opportunisticintervals have a profound effect on measurement data andinterfere with trending techniques.6.2 Machinery OperationOperational intensity can im-pact how quickly a c

    21、omponent wears and how rapidly a faultprogresses.3,4A relevant indicator of machine usage must beincluded in any calculations. The selected usage indicator mustreflect actual machine usage, that is, life consumed (forexample, stop/start cycles, megawatt hours, hours of use, orfuel consumption).6.3 M

    22、aintenance EventsComponent, filter, and oilchanges impact the monitoring of machine performance, weardebris, contamination ingress and fluid condition. Maintenanceevents should always occur after a sample is taken (orcondition test is performed). All maintenance events should bedocumented and taken

    23、into account during condition datainterpretation. In all cases, maintenance events, if not reported,will reduce trending reliability.6.4 Sampling ProceduresImproper or poor sampling tech-niques can profoundly impact condition test data (see PracticesD4057 and D4177). A significant difference in the

    24、test datacould trigger a false trend alarm. Examples of poor samplingtechniques are:6.4.1 Stagnant sampling,6.4.2 Sampling after component change out,6.4.3 Sampling after oil, or filter changes, or both,6.4.4 Irregular sample intervals,6.4.5 Sampling intermittent or standby equipment withoutcirculat

    25、ing the oil and bringing the equipment to operatingtemperatures.6.5 Laboratory and Testing PracticesThe tools used toperform the condition monitoring tests impact the data.6.5.1 Analytical instrument differences impact data reliabil-ity. Trending should only be performed on results from thesame make

    26、 and model of test instrument. For example,trending atomic emission inductively coupled plasma (ICP)results should be from ICPs with the same sample introductionconfiguration, same plasma energy, and preferably, the samemanufacturer and model.6.5.2 Analytical instruments with poor measurement repeat

    27、-ability and reproducibility will result in correspondingly poortrending. Testing repeatability should also be included with thetrending studies.6.5.3 Inappropriate analysis techniques can hide or distortinterpretational conclusions. The condition-monitoring toolchosen must provide evidence of the c

    28、ritical failure modesunder review.6.6 Machinery Wear ProcessWear metal concentrationsin oil are subject to variability.46.6.1 Filters remove the majority of debris particles greaterthan filter pore size. Thus an oil sample only captures new wearand small, suspended, old wear.6.6.2 Wear particle rele

    29、ase is event driven; increased load orspeed can result in increased wear.6.6.3 The rate of wear debris release is not linear with time.For many fault mechanisms, wear occurs in bursts.6.6.4 Wear metal analysis methods can have particle sizelimitations that should be included in the evaluations. Fore

    30、xample, ICP metal analyses are limited to those particlesbelow nominally 8 microns.6.7 Reservoir/Sump VolumesFluid and wear conditionparameters are concentration measurements and are affected byreservoir/sump size. Varying the oil volumes in a reservoir canimpact the trending analysis. For example,

    31、infrequent top upsallows the oil volume to decrease and thus concentrate the weardebris and contaminants. Alternatively, large volumes ofmake-up oil dilute the concentrations. Small, routine oiltop-ups reduce this interference. The fluid make-up rate shouldbe considered as apart of the evaluation pr

    32、actice.6.8 When trending for a specific piece of equipment, oneshould look at the difference between the current sample and anaverage of a group of previous samples from that piece ofequipment or a group of samples from as many similar units aspossible. Basing a trend on just two data points can lea

    33、vesignificant room for error and misjudgment.3Forster, N., et.al., “Assessing the Potential of a Commercial Oil Debris Sensoras a Prognostic Device for Gas Turbine Engine Bearings,” ISHM, August 2005.4Toms, Larry A., and Toms, Allison M., Machinery Oil Analysis - Methods,Automation diagnostics; prog

    34、nostics; remain-ing usable life; trend analysisFIG. 2 Cumulative Trend Plot of Real-Time Sensor DataD7669 114ASTM International takes no position respecting the validity of any patent rights asserted in connection with any item mentionedin this standard. Users of this standard are expressly advised

    35、that determination of the validity of any such patent rights, and the riskof infringement of such rights, are entirely their own responsibility.This standard is subject to revision at any time by the responsible technical committee and must be reviewed every five years andif not revised, either reap

    36、proved or withdrawn. Your comments are invited either for revision of this standard or for additional standardsand should be addressed to ASTM International Headquarters. Your comments will receive careful consideration at a meeting of theresponsible technical committee, which you may attend. If you

    37、 feel that your comments have not received a fair hearing you shouldmake your views known to the ASTM Committee on Standards, at the address shown below.This standard is copyrighted by ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959,United States. Individual

    38、reprints (single or multiple copies) of this standard may be obtained by contacting ASTM at the aboveaddress or at 610-832-9585 (phone), 610-832-9555 (fax), or serviceastm.org (e-mail); or through the ASTM website(www.astm.org). Permission rights to photocopy the standard may also be secured from the ASTM website (www.astm.org/COPYRIGHT/).FIG. 3 Adaptive Trend Plot when Sample Interval is Greater than 1.5 Times the Standard IntervalD7669 115


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