Lubrication Oil Condition Monitoring and Remaining Useful Life Prediction with Particle Filtering
##plugins.themes.bootstrap3.article.main##
##plugins.themes.bootstrap3.article.sidebar##
Published
Nov 1, 2020
Junda Zhu
Jae M. Yoon
David He
Yongzhi Qu
Eric Bechhoefer
Abstract
In order to reduce the costs of wind energy, it is necessary to improve the wind turbine availability and reduce the operational and maintenance costs. The reliability and availability of a functioning wind turbine depend largely on the protective properties of the lubrication oil for its drive train subassemblies such as the gearbox and means for lubrication oil condition monitoring and degradation detection. The wind industry currently uses lubrication oil analysis for detecting gearbox and bearing wear but cannot detect the functional failures of the lubrication oils. The main purpose of lubrication oil condition monitoring and degradation detection is to determine whether the oils have deteriorated to such a degree that they no longer fulfill their functions. This paper describes a research on developing online lubrication oil condition monitoring and remaining useful life prediction using particle filtering technique and commercially available online sensors. It first introduces the lubrication oil condition monitoring and degradation detection for wind turbines. Viscosity and dielectric constant are selected as the performance parameters to model the degradation of lubricants. In particular, the lubricant performance evaluation and remaining useful life prediction of degraded lubrication oil with viscosity and dielectric constant data using particle filtering are presented. A simulation study based on lab verified models is provided to demonstrate the effectiveness of the developed technique.
##plugins.themes.bootstrap3.article.details##
Keywords
on-line condition monitoring, Remaining Useful Life Estimation, lubrication oil
References
Agoston, A., Otsch, C., and Jakoby, B., 2005, "Viscosity sensors for engine oil condition monitoring-Application and interpretation of results.", Sensors and Actuators A, Vol. 121, pp. 327 - 332.
Agoston, A., Dorr, N., and Jakoby, B., 2006, "Online Application of sensors monitoring lubricating oil properties in biogas engines.", IEEE Sensors 2006, EXCO, Daegu, Korea, October 22 - 25, 2006
Agoston, A., Otsch, C., Zhuravleva, J., and Jakoby, B., 2004, “An IR-absorption sensor system for the determination of engine oil deterioration.”, Proceeding of IEEE, sensors, Vienna, Austria, Otc. 24 – 27, 2004, Vol. 1, pp. 463 – 466.
Agoston, A., Schneidhofer, C., Dorr, N., and Jakoby, B., 2008, "A concept of an infrared sensor system for oil condition monitoring", Elekrotechnik & Informationstechnik., Vol. 125/3, pp. 71 - 75.
Arulampalam, S.M., Maskell, S., Gordon, N., and Clapp, T., 2002, “A Tutorial on Particle Filters for Online Nonlinear/Non-Gaussian Bayesian Tracking”, IEEE Transactions on Signal Processing, Vol. 50, No. 2, pp. 174 – 188.
Benner, J.J., Sadeghi, F., Hoeprich, M.R., and Frank. M.C., 2006, "Lubricating properties of water oil emulsions." Journal of Tribology, Transaction of ASME, April 2006. Vol. 128, pp. 296 - 311.
Beran, E., Los M. and Kmiecik, A., 2008, "Influence of thermo-oxidative degradation on the biodegradability of lubricant base oils", Journal of Synthetic Lubrication, Vol. 28, pp. 75 - 83.
BHRA, 1988, Condition Monitoring Supplement, Cranfield, Bedfordshire: BHRA.
Bozchalooi, I.S. and Liang, M., 2009, "Oil Debris Signal Analysis Based on Empirical Mode Decomposition for Machinery Condition Monitoring", 2009 American Control Conference, June 10 - 12, 2009, St. Louis, MO, USA
Butler, S. and Ringwood, J., 2010, “Particle Filters for Remaining Useful Life Estimation of Abatement Equipment used in Semiconductor Manufacturing”, Proceedings of the First Conference on Control and Fault-Tolerant Systems, Nice, France, pp. 436 - 441.
Byington C., Palmer C., Argenna G., and Mackos N., 2010, “An integrated, real-time oil quality monitor and debris measurement capability for drive train and engine systems” Proceedings of American Helicopter Society 66th Annual Forum and Technology Display, Pheonix, Arizona, May 11 – 13, 2010
Byington, C., Mackos, N., Argenna, G., Palladino, A., Reimann, J., and Schmitigal, J., 2012, “Application of symbolic regression to electrochemical impedance spectroscopy data for lubricating oil health evaluation”, Proceedings of Annual Conference of Prognostics and Health Management Society 2012, Minneapolis, Minnesota, September 23 – 27, 2012
Doucet, A., Godsill, S., and Andrieu, C., 2000, “On Sequential Monte Carlo Sampling Methods for Bayesian Filtering”, Statistics and Computing, Vol. 10, pp. 197 – 208.
Doucet, A., Godsill, S., and Andrieu, C., 2000, “On Sequential Monte Carlo Sampling Methods for Bayesian Filtering”, Statistics and Computing, Vol. 10, pp. 197 – 208.
Durdag, K., 2008, "Solid state acoustic wave sensors for realtime in_line measurement of oil viscosity.", Sensor Review, Vol. 28/1, pp.68 – 73.
Guan, L., Feng, X.L., Xiong G., and Xie, J.A., 2011, "Application of dielectric spectroscopy for engine lubricating oil degradation. ", Sensors and Actuators A, Vol. 168, pp. 22 - 29
Halderman, J. D., 1996, Automotive Technology, New York: McGraw-Hill.
He, D., Bechhoefer, E., Dempsey, P., and Ma, J., 2012, “An Integrated Approach for Gear Health Prognostics”, Proceedings of the 2012 AHS Forum, Fort Worth, TX, April 30 – May 3, 2012.
JJakoby, B., Buskies, M., Scherer, M., Henzler, S., Eisenschmid, H., and Schatz, O., 2001, "Advanced Microsystems for Automotive Applications", Springer, Berlin/Heidelberg/New York, 2001, pp. 157 – 165.
Jakoby B. and Vellekoop, M.J., 2004, "Physical sensors for water-in-oil emulsions." Sensors and Actuators A, Vol. 110, pp. 28 - 32.
Jakoby, B., Scherer, M., Buskies, M., and Eisenschmid, H., 2002, "Micro viscosity sensor for automobile applications. ", IEEE Sensors, Vol. 2, pp. 1587 - 1590.
Jakoby, B., Scherer, M., Buskies, M., and Eisenschmid, H., 2003, "An automotive engine oil viscosity sensor", IEEE Sensors. J, Vol. 3, pp. 562 – 568.
Kittiwake Developments. Ltd. 2011, "Monitoring water in lubricant oil - maintain equipment & reduce downtime", Critical Things to Monitor, Water in Lube Oil.
Kumar, S., Mukherjee, P. S., and Mishra, N. M., 2005, "Online condition monitoring of engine oil", Industrial Lubrication and Tribology, Vol. 57, No. 6, pp. 260 - 267.
Merwe, R., Doucet, A., Freitas, N., and Wan E., 2000, “Unscented particle filter”, Cambridge University Engineering Department Technical Report cued/f-infeng/TR 380.
Orchard M.E. and Vachtsevanos, G.J., 2011, “A Particle-filtering Approach for Online Fault Diagnosis and Failure Prognosis”, Transactions of the Institute of Measurement and Control, Vol. 31, pp. 221 – 246.
Poley,J., 2012, “The metamorphosis of oil analysis”, Machinery Failure Prevention Technology (MFPT) Conference, Condition Based Maintenance Section 1, Conference Proceedings, Dayton, Ohio, April 24 – 26, 2012.
Raadnui, S. and Kleesuwan, S., 2005, "Low-cost condition monitoring sensor for used oil analysis", Wear, Vol. 259, pp. 1502 - 1506.
Saha, B., Goebel, K., Poll, S., and Christophersen, J., 2009), “Prognostics Methods for Battery Health Monitoring Using a Bayesian Framework”, IEEE Transactions on Instrumentation and Measurement, Vol. 58, No. 2, pp. 291-296.
Schmitigal, J. and Moyer, S., 2005, "Evaluation of sensors for on-board diesel oil condition monitoring of U.S. Army ground equipment", TACOM/TARDEC, Report No. 14113.
Sharma, B.C. and Gandhi, O.P., 2008, "Performance evaluation and analysis of lubricating oil using parameter profile approach", Industrial Lubrication and Tribology, Vol. 60, No. 3, pp. 131 - 137.
Stachowiak, G.W. and Batchelor, A.W., 2005, “Physical Property of Lubricants”, Engineering Tribology, 3rd edition, pp. 3, ISBN-13: 978-0-7506-7836-0, ISBN-10: 0-7506-7836-4
Turner, J.D. and Austin, L., 2003, "Electrical techniques for monitoring the condition of lubrication oil.", Measurement Science and Technology, Vol. 14, pp. 1794 - 1800.
Yoon, J., 2012, “A Comparative Study of Adaptive MCMC Based Particle Filtering Methods”, M.S. Thesis, University of Florida
Zio, E. and Peloni, G., 2011, “Particle Filtering Prognostic Estimation of the Remaining Useful Life of Nonlinear Components”, Reliability Engineering and System Safety, Vol. 96, pp. 403 - 409.
Zhu, J, He, D., and Bechhoefer, E, 2012, “Survey of lubrication oil condition monitoring, diagnostics, and prognostics techniques and systems”, Machine Failure Prevention Technology (MFPT), Conference Proceeding, April 24 – 26, 2012, Dayton, Ohio, USA
Zhu, J, He, D., and Bechhoefer, E, 2013, “Survey of lubrication oil condition monitoring, diagnostics, and prognostics techniques and systems”, Journal of Chemical Science and Technology (JCST), (To appear)
Agoston, A., Dorr, N., and Jakoby, B., 2006, "Online Application of sensors monitoring lubricating oil properties in biogas engines.", IEEE Sensors 2006, EXCO, Daegu, Korea, October 22 - 25, 2006
Agoston, A., Otsch, C., Zhuravleva, J., and Jakoby, B., 2004, “An IR-absorption sensor system for the determination of engine oil deterioration.”, Proceeding of IEEE, sensors, Vienna, Austria, Otc. 24 – 27, 2004, Vol. 1, pp. 463 – 466.
Agoston, A., Schneidhofer, C., Dorr, N., and Jakoby, B., 2008, "A concept of an infrared sensor system for oil condition monitoring", Elekrotechnik & Informationstechnik., Vol. 125/3, pp. 71 - 75.
Arulampalam, S.M., Maskell, S., Gordon, N., and Clapp, T., 2002, “A Tutorial on Particle Filters for Online Nonlinear/Non-Gaussian Bayesian Tracking”, IEEE Transactions on Signal Processing, Vol. 50, No. 2, pp. 174 – 188.
Benner, J.J., Sadeghi, F., Hoeprich, M.R., and Frank. M.C., 2006, "Lubricating properties of water oil emulsions." Journal of Tribology, Transaction of ASME, April 2006. Vol. 128, pp. 296 - 311.
Beran, E., Los M. and Kmiecik, A., 2008, "Influence of thermo-oxidative degradation on the biodegradability of lubricant base oils", Journal of Synthetic Lubrication, Vol. 28, pp. 75 - 83.
BHRA, 1988, Condition Monitoring Supplement, Cranfield, Bedfordshire: BHRA.
Bozchalooi, I.S. and Liang, M., 2009, "Oil Debris Signal Analysis Based on Empirical Mode Decomposition for Machinery Condition Monitoring", 2009 American Control Conference, June 10 - 12, 2009, St. Louis, MO, USA
Butler, S. and Ringwood, J., 2010, “Particle Filters for Remaining Useful Life Estimation of Abatement Equipment used in Semiconductor Manufacturing”, Proceedings of the First Conference on Control and Fault-Tolerant Systems, Nice, France, pp. 436 - 441.
Byington C., Palmer C., Argenna G., and Mackos N., 2010, “An integrated, real-time oil quality monitor and debris measurement capability for drive train and engine systems” Proceedings of American Helicopter Society 66th Annual Forum and Technology Display, Pheonix, Arizona, May 11 – 13, 2010
Byington, C., Mackos, N., Argenna, G., Palladino, A., Reimann, J., and Schmitigal, J., 2012, “Application of symbolic regression to electrochemical impedance spectroscopy data for lubricating oil health evaluation”, Proceedings of Annual Conference of Prognostics and Health Management Society 2012, Minneapolis, Minnesota, September 23 – 27, 2012
Doucet, A., Godsill, S., and Andrieu, C., 2000, “On Sequential Monte Carlo Sampling Methods for Bayesian Filtering”, Statistics and Computing, Vol. 10, pp. 197 – 208.
Doucet, A., Godsill, S., and Andrieu, C., 2000, “On Sequential Monte Carlo Sampling Methods for Bayesian Filtering”, Statistics and Computing, Vol. 10, pp. 197 – 208.
Durdag, K., 2008, "Solid state acoustic wave sensors for realtime in_line measurement of oil viscosity.", Sensor Review, Vol. 28/1, pp.68 – 73.
Guan, L., Feng, X.L., Xiong G., and Xie, J.A., 2011, "Application of dielectric spectroscopy for engine lubricating oil degradation. ", Sensors and Actuators A, Vol. 168, pp. 22 - 29
Halderman, J. D., 1996, Automotive Technology, New York: McGraw-Hill.
He, D., Bechhoefer, E., Dempsey, P., and Ma, J., 2012, “An Integrated Approach for Gear Health Prognostics”, Proceedings of the 2012 AHS Forum, Fort Worth, TX, April 30 – May 3, 2012.
JJakoby, B., Buskies, M., Scherer, M., Henzler, S., Eisenschmid, H., and Schatz, O., 2001, "Advanced Microsystems for Automotive Applications", Springer, Berlin/Heidelberg/New York, 2001, pp. 157 – 165.
Jakoby B. and Vellekoop, M.J., 2004, "Physical sensors for water-in-oil emulsions." Sensors and Actuators A, Vol. 110, pp. 28 - 32.
Jakoby, B., Scherer, M., Buskies, M., and Eisenschmid, H., 2002, "Micro viscosity sensor for automobile applications. ", IEEE Sensors, Vol. 2, pp. 1587 - 1590.
Jakoby, B., Scherer, M., Buskies, M., and Eisenschmid, H., 2003, "An automotive engine oil viscosity sensor", IEEE Sensors. J, Vol. 3, pp. 562 – 568.
Kittiwake Developments. Ltd. 2011, "Monitoring water in lubricant oil - maintain equipment & reduce downtime", Critical Things to Monitor, Water in Lube Oil.
Kumar, S., Mukherjee, P. S., and Mishra, N. M., 2005, "Online condition monitoring of engine oil", Industrial Lubrication and Tribology, Vol. 57, No. 6, pp. 260 - 267.
Merwe, R., Doucet, A., Freitas, N., and Wan E., 2000, “Unscented particle filter”, Cambridge University Engineering Department Technical Report cued/f-infeng/TR 380.
Orchard M.E. and Vachtsevanos, G.J., 2011, “A Particle-filtering Approach for Online Fault Diagnosis and Failure Prognosis”, Transactions of the Institute of Measurement and Control, Vol. 31, pp. 221 – 246.
Poley,J., 2012, “The metamorphosis of oil analysis”, Machinery Failure Prevention Technology (MFPT) Conference, Condition Based Maintenance Section 1, Conference Proceedings, Dayton, Ohio, April 24 – 26, 2012.
Raadnui, S. and Kleesuwan, S., 2005, "Low-cost condition monitoring sensor for used oil analysis", Wear, Vol. 259, pp. 1502 - 1506.
Saha, B., Goebel, K., Poll, S., and Christophersen, J., 2009), “Prognostics Methods for Battery Health Monitoring Using a Bayesian Framework”, IEEE Transactions on Instrumentation and Measurement, Vol. 58, No. 2, pp. 291-296.
Schmitigal, J. and Moyer, S., 2005, "Evaluation of sensors for on-board diesel oil condition monitoring of U.S. Army ground equipment", TACOM/TARDEC, Report No. 14113.
Sharma, B.C. and Gandhi, O.P., 2008, "Performance evaluation and analysis of lubricating oil using parameter profile approach", Industrial Lubrication and Tribology, Vol. 60, No. 3, pp. 131 - 137.
Stachowiak, G.W. and Batchelor, A.W., 2005, “Physical Property of Lubricants”, Engineering Tribology, 3rd edition, pp. 3, ISBN-13: 978-0-7506-7836-0, ISBN-10: 0-7506-7836-4
Turner, J.D. and Austin, L., 2003, "Electrical techniques for monitoring the condition of lubrication oil.", Measurement Science and Technology, Vol. 14, pp. 1794 - 1800.
Yoon, J., 2012, “A Comparative Study of Adaptive MCMC Based Particle Filtering Methods”, M.S. Thesis, University of Florida
Zio, E. and Peloni, G., 2011, “Particle Filtering Prognostic Estimation of the Remaining Useful Life of Nonlinear Components”, Reliability Engineering and System Safety, Vol. 96, pp. 403 - 409.
Zhu, J, He, D., and Bechhoefer, E, 2012, “Survey of lubrication oil condition monitoring, diagnostics, and prognostics techniques and systems”, Machine Failure Prevention Technology (MFPT), Conference Proceeding, April 24 – 26, 2012, Dayton, Ohio, USA
Zhu, J, He, D., and Bechhoefer, E, 2013, “Survey of lubrication oil condition monitoring, diagnostics, and prognostics techniques and systems”, Journal of Chemical Science and Technology (JCST), (To appear)
Section
Technical Papers