Remaining useful life prediction based on noisy condition monitoring signals using constrained Kalman filter
In this paper, a statistical prognostic method to predict the remaining useful life (RUL) of individual units based on noisy condition monitoring signals is proposed. The prediction accuracy of existing data-driven prognostic methods depends on the capability of accurately modeling the evolution of...
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| Published in | Reliability engineering & system safety Vol. 152; pp. 38 - 50 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.08.2016
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0951-8320 1879-0836 |
| DOI | 10.1016/j.ress.2016.02.006 |
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| Abstract | In this paper, a statistical prognostic method to predict the remaining useful life (RUL) of individual units based on noisy condition monitoring signals is proposed. The prediction accuracy of existing data-driven prognostic methods depends on the capability of accurately modeling the evolution of condition monitoring (CM) signals. Therefore, it is inevitable that the RUL prediction accuracy depends on the amount of random noise in CM signals. When signals are contaminated by a large amount of random noise, RUL prediction even becomes infeasible in some cases. To mitigate this issue, a robust RUL prediction method based on constrained Kalman filter is proposed. The proposed method models the CM signals subject to a set of inequality constraints so that satisfactory prediction accuracy can be achieved regardless of the noise level of signal evolution. The advantageous features of the proposed RUL prediction method is demonstrated by both numerical study and case study with real world data from automotive lead-acid batteries.
•A computationally efficient constrained Kalman filter is proposed.•Proposed filter is integrated into an online failure prognosis framework.•A set of proper constraints significantly improves the failure prediction accuracy.•Promising results are reported in the application of battery failure prognosis. |
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| AbstractList | In this paper, a statistical prognostic method to predict the remaining useful life (RUL) of individual units based on noisy condition monitoring signals is proposed. The prediction accuracy of existing data-driven prognostic methods depends on the capability of accurately modeling the evolution of condition monitoring (CM) signals. Therefore, it is inevitable that the RUL prediction accuracy depends on the amount of random noise in CM signals. When signals are contaminated by a large amount of random noise, RUL prediction even becomes infeasible in some cases. To mitigate this issue, a robust RUL prediction method based on constrained Kalman filter is proposed. The proposed method models the CM signals subject to a set of inequality constraints so that satisfactory prediction accuracy can be achieved regardless of the noise level of signal evolution. The advantageous features of the proposed RUL prediction method is demonstrated by both numerical study and case study with real world data from automotive lead-acid batteries. In this paper, a statistical prognostic method to predict the remaining useful life (RUL) of individual units based on noisy condition monitoring signals is proposed. The prediction accuracy of existing data-driven prognostic methods depends on the capability of accurately modeling the evolution of condition monitoring (CM) signals. Therefore, it is inevitable that the RUL prediction accuracy depends on the amount of random noise in CM signals. When signals are contaminated by a large amount of random noise, RUL prediction even becomes infeasible in some cases. To mitigate this issue, a robust RUL prediction method based on constrained Kalman filter is proposed. The proposed method models the CM signals subject to a set of inequality constraints so that satisfactory prediction accuracy can be achieved regardless of the noise level of signal evolution. The advantageous features of the proposed RUL prediction method is demonstrated by both numerical study and case study with real world data from automotive lead-acid batteries. •A computationally efficient constrained Kalman filter is proposed.•Proposed filter is integrated into an online failure prognosis framework.•A set of proper constraints significantly improves the failure prediction accuracy.•Promising results are reported in the application of battery failure prognosis. |
| Author | Son, Junbo Du, Xinyu Zhang, Yilu Zhou, Shiyu Sankavaram, Chaitanya |
| Author_xml | – sequence: 1 givenname: Junbo surname: Son fullname: Son, Junbo organization: Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA – sequence: 2 givenname: Shiyu surname: Zhou fullname: Zhou, Shiyu email: shiyuzhou@wisc.edu organization: Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA – sequence: 3 givenname: Chaitanya surname: Sankavaram fullname: Sankavaram, Chaitanya organization: General Motors Global Research & Development, Warren, MI 48092, USA – sequence: 4 givenname: Xinyu surname: Du fullname: Du, Xinyu organization: General Motors Global Research & Development, Warren, MI 48092, USA – sequence: 5 givenname: Yilu surname: Zhang fullname: Zhang, Yilu organization: General Motors Global Research & Development, Warren, MI 48092, USA |
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| Cites_doi | 10.1115/1.1789153 10.1016/j.ress.2010.08.009 10.1002/(SICI)1097-0258(19980930)17:18<2061::AID-SIM896>3.0.CO;2-O 10.1080/07408170590929018 10.1016/j.ymssp.2012.08.016 10.1080/00401706.1993.10485038 10.1080/00401706.2013.830074 10.1109/ICPHM.2014.7036386 10.2307/2529876 10.1111/j.2517-6161.1961.tb00408.x 10.1080/01621459.1995.10476485 10.1109/TASE.2011.2160538 10.1109/7.993234 10.1016/j.automatica.2011.11.002 10.1080/0740817X.2012.706376 10.1109/TR.2010.2046804 10.1016/j.ymssp.2011.10.009 10.1109/TAC.1971.1099833 10.1080/0740817X.2011.618175 10.2307/2347752 10.1109/TR.2010.2044610 10.1007/978-0-85729-320-6_42 10.1109/TR.2013.2259205 10.1016/0165-1765(79)90111-3 10.1049/iet-cta.2009.0032 10.2307/2533118 10.1080/0740817X.2013.876126 10.1080/00207720903042970 10.1016/j.ejor.2010.11.018 10.1109/AFGR.1998.670960 10.1002/qre.1609 10.1016/j.ymssp.2014.08.006 10.1080/03610929008830197 10.1109/TR.2014.2355531 |
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| References | Cartinhour (bib4) 1990; 19 Chen, Vachtsevanos, Orchard (bib5) 2012; 28 Si, Wang, Hu, Zhou (bib19) 2011; 213 Leppard, Tallis (bib12) 1989; 38 Klein, Moeschberger (bib9) 2003 Straka, Dunik, Simandl (bib27) 2012; 48 Tsiatis, DeGruttola, Wulfsohn (bib30) 1995; 90 Son, Zhou, Zhou, Mao, Salman (bib26) 2013; 62 Son, Zhang, Sankavaram, Zhou (bib25) 2015; 64 Shimada N, Shirai Y, Kuno Y, Miura J. Hand gesture estimation and model refinement using monocular camera – ambiguity limitation by inequality constraints. In: Proceedings of the 3rd IEEE international conference on automatic face and gesture recognition; 1998. p. 268−273. Zhou, Son, Zhou, Mao, Salman (bib36) 2014; 46 Sun, Li, Xi (bib28) 2012; 9 Byon, Ntaimo, Ding (bib3) 2010; 59 Simon (bib24) 2010; 4 Liao H, Zhao W, Guo H. Predicting remaining useful life of an individual unit using proportional hazards model and logistic regression model. In: Proceedings of the annual reliability and maintainability symposium, Newport Beach, CA; 2006 Lim, Mba (bib14) 2015; 52 Simon, Chia (bib21) 2002; 39 Zhou, Gebraeel, Serban (bib37) 2012; 44 Bluvband Z, Porotsky S, Tropper S. Critical zone recognition: classification vs. regression. In: Proceedings of the IEEE conference on prognostics and health management; 2014. p. 1–5. Gebraeel, Lawley, Li, Ryan (bib7) 2005; 3 Chen, Tsui (bib6) 2013; 45 Zio, Peloni (bib38) 2011; 96 Gorjian N, Ma L, Mittinty M, Yarlagadda P, Sun Y, A. review on degradation models in reliability analysis. In: engineering asset lifecycle management – Proceedings of the 4th world congress on engineering asset management (WCEAM); 2010. p. 369–384. Manjunath, Wilhelm (bib16) 2012; 1206 Simon, Simon (bib22) 2005; 127 Bycott, Taylor (bib2) 1998; 17 Rhodes (bib17) 1971; AC-16 Tallis (bib29) 1961; 23 Wulfsohn, Tsiatis (bib31) 1997; 53 Yu, Fuh (bib34) 2010; 59 Si, Wang, Hu, Chen, Zhou (bib20) 2013; 35 Lu, Meeker (bib15) 1993; 35 Ye, Chen (bib32) 2014; 56 Ye, Chen, Tsui (bib33) 2015; 31 Zarchan, Musoff (bib35) 2005 Simon, Simon (bib23) 2010; 41 Laird, Ware (bib10) 1982; 38 Lee (bib11) 1979; 3 Chen (10.1016/j.ress.2016.02.006_bib6) 2013; 45 10.1016/j.ress.2016.02.006_bib18 10.1016/j.ress.2016.02.006_bib13 Wulfsohn (10.1016/j.ress.2016.02.006_bib31) 1997; 53 Simon (10.1016/j.ress.2016.02.006_bib21) 2002; 39 Son (10.1016/j.ress.2016.02.006_bib26) 2013; 62 Zhou (10.1016/j.ress.2016.02.006_bib36) 2014; 46 Zhou (10.1016/j.ress.2016.02.006_bib37) 2012; 44 Son (10.1016/j.ress.2016.02.006_bib25) 2015; 64 Cartinhour (10.1016/j.ress.2016.02.006_bib4) 1990; 19 10.1016/j.ress.2016.02.006_bib8 Zio (10.1016/j.ress.2016.02.006_bib38) 2011; 96 Byon (10.1016/j.ress.2016.02.006_bib3) 2010; 59 Simon (10.1016/j.ress.2016.02.006_bib24) 2010; 4 Lee (10.1016/j.ress.2016.02.006_bib11) 1979; 3 Yu (10.1016/j.ress.2016.02.006_bib34) 2010; 59 Klein (10.1016/j.ress.2016.02.006_bib9) 2003 Chen (10.1016/j.ress.2016.02.006_bib5) 2012; 28 Laird (10.1016/j.ress.2016.02.006_bib10) 1982; 38 Bycott (10.1016/j.ress.2016.02.006_bib2) 1998; 17 Ye (10.1016/j.ress.2016.02.006_bib33) 2015; 31 Leppard (10.1016/j.ress.2016.02.006_bib12) 1989; 38 Rhodes (10.1016/j.ress.2016.02.006_bib17) 1971; AC-16 Si (10.1016/j.ress.2016.02.006_bib19) 2011; 213 Zarchan (10.1016/j.ress.2016.02.006_bib35) 2005 Lim (10.1016/j.ress.2016.02.006_bib14) 2015; 52 Lu (10.1016/j.ress.2016.02.006_bib15) 1993; 35 Si (10.1016/j.ress.2016.02.006_bib20) 2013; 35 10.1016/j.ress.2016.02.006_bib1 Simon (10.1016/j.ress.2016.02.006_bib22) 2005; 127 Ye (10.1016/j.ress.2016.02.006_bib32) 2014; 56 Straka (10.1016/j.ress.2016.02.006_bib27) 2012; 48 Tallis (10.1016/j.ress.2016.02.006_bib29) 1961; 23 Gebraeel (10.1016/j.ress.2016.02.006_bib7) 2005; 3 Tsiatis (10.1016/j.ress.2016.02.006_bib30) 1995; 90 Sun (10.1016/j.ress.2016.02.006_bib28) 2012; 9 Manjunath (10.1016/j.ress.2016.02.006_bib16) 2012; 1206 Simon (10.1016/j.ress.2016.02.006_bib23) 2010; 41 |
| References_xml | – year: 2003 ident: bib9 publication-title: Survival analysis – techniques for censored and truncated data – volume: 39 start-page: 128 year: 2002 end-page: 136 ident: bib21 article-title: Kalman filtering with state equality constraints publication-title: IEEE Trans Aerosp Electron Syst – volume: 48 start-page: 273 year: 2012 end-page: 286 ident: bib27 article-title: Truncation nonlinear filters for state estimation with nonlinear inequality constraints publication-title: Automatica – volume: 17 start-page: 2061 year: 1998 end-page: 2077 ident: bib2 article-title: A comparison of smoothing techniques for CD4 data measured with error in a time-dependent Cox proportional hazards model publication-title: Stat Med – volume: 4 start-page: 1303 year: 2010 end-page: 1318 ident: bib24 article-title: Kalman filtering with state constraints: a survey of linear and nonlinear algorithms publication-title: IET Control Theory Appl – volume: 53 start-page: 330 year: 1997 end-page: 339 ident: bib31 article-title: A joint model for survival and longitudinal data measured with error publication-title: Biometrics – volume: 96 start-page: 403 year: 2011 end-page: 409 ident: bib38 article-title: Particle filtering prognostic estimation of the remaining useful life of nonlinear components publication-title: Reliab Eng Syst Saf – volume: 38 start-page: 543 year: 1989 end-page: 553 ident: bib12 article-title: Algorithm AS 249: evaluation of the mean and covariance of the truncated multinormal distribution publication-title: Appl Stat – volume: 52 start-page: 426 year: 2015 end-page: 435 ident: bib14 article-title: Switching Kalman filter for failure prognostics publication-title: Mech Syst Signal Process – reference: Shimada N, Shirai Y, Kuno Y, Miura J. Hand gesture estimation and model refinement using monocular camera – ambiguity limitation by inequality constraints. In: Proceedings of the 3rd IEEE international conference on automatic face and gesture recognition; 1998. p. 268−273. – volume: 90 start-page: 27 year: 1995 end-page: 37 ident: bib30 article-title: Modeling the relationship of survival to longitudinal data measured with error: applications to survival and CD4 counts in patients with AIDS publication-title: J Am Stat Assoc – volume: 59 start-page: 405 year: 2010 end-page: 412 ident: bib34 article-title: Estimation of time to hard failure distributions using a three-stage method publication-title: IEEE Trans Reliab – volume: 3 start-page: 165 year: 1979 end-page: 169 ident: bib11 article-title: On the first and second moments of the truncated multi-normal distribution and a simple estimator publication-title: Econ Lett – volume: 35 start-page: 161 year: 1993 end-page: 174 ident: bib15 article-title: Using degradation measures to estimate a time-to-failure distribution publication-title: Technometrics – reference: Liao H, Zhao W, Guo H. Predicting remaining useful life of an individual unit using proportional hazards model and logistic regression model. In: Proceedings of the annual reliability and maintainability symposium, Newport Beach, CA; 2006 – reference: Bluvband Z, Porotsky S, Tropper S. Critical zone recognition: classification vs. regression. In: Proceedings of the IEEE conference on prognostics and health management; 2014. p. 1–5. – volume: 56 start-page: 302 year: 2014 end-page: 311 ident: bib32 article-title: The inverse Gaussian process as a degradation model publication-title: Technometrics – volume: 1206 start-page: 5387v1 year: 2012 ident: bib16 article-title: Moment calculation for the doubly truncated multivariate normal density publication-title: arXiv – volume: 9 start-page: 209 year: 2012 end-page: 212 ident: bib28 article-title: Modified two-stage degradation model for dynamic maintenance threshold calculation considering uncertainty publication-title: IEEE Trans Autom Sci Eng – volume: 35 start-page: 219 year: 2013 end-page: 237 ident: bib20 article-title: A Wiener-process-based degradation model with a recursive filter algorithm for remaining useful life estimation publication-title: Mech Syst Signal Process – volume: 28 start-page: 597 year: 2012 end-page: 607 ident: bib5 article-title: Machine remaining useful life prediction: an integrated adaptive neuro-fuzzy and high-order particle filtering approach publication-title: Mech Syst Signal Process – volume: 127 start-page: 323 year: 2005 end-page: 328 ident: bib22 article-title: Aircraft turbofan engine health estimation using constrained Kalman filtering publication-title: J Eng Gas Turbines Power – volume: 64 start-page: 182 year: 2015 end-page: 196 ident: bib25 article-title: RUL prediction for individual units based on condition monitoring signals with a change point publication-title: IEEE Trans Reliab – volume: 23 start-page: 223 year: 1961 end-page: 229 ident: bib29 article-title: The moment generating function of the truncated multinormal distribution publication-title: J R Stat Soc, Ser B (Methodol) – reference: Gorjian N, Ma L, Mittinty M, Yarlagadda P, Sun Y, A. review on degradation models in reliability analysis. In: engineering asset lifecycle management – Proceedings of the 4th world congress on engineering asset management (WCEAM); 2010. p. 369–384. – volume: 45 start-page: 939 year: 2013 end-page: 952 ident: bib6 article-title: Condition monitoring and remaining useful life prediction using degradation signals: revisited publication-title: IIE Trans – volume: 3 start-page: 543 year: 2005 end-page: 557 ident: bib7 article-title: Residual-life distribution from component degradation signals: a Bayesian approach publication-title: IIE Trans – volume: 62 start-page: 379 year: 2013 end-page: 394 ident: bib26 article-title: Evaluation and comparison of mixed effects model based prognosis for hard failure publication-title: IEEE Trans Reliab – volume: AC-16 start-page: 688 year: 1971 end-page: 706 ident: bib17 article-title: A tutorial introduction to estimation and filtering publication-title: IEEE Trans Autom Control – volume: 31 start-page: 513 year: 2015 end-page: 522 ident: bib33 article-title: A Bayesian approach to condition monitoring with imperfect inspections publication-title: Qual Reliab Eng Int – volume: 41 start-page: 159 year: 2010 end-page: 171 ident: bib23 article-title: Constrained Kalman filtering via density function truncation for turbofan engine health estimation publication-title: Int J Syst Sci – volume: 59 start-page: 393 year: 2010 end-page: 404 ident: bib3 article-title: Optimal maintenance strategies for wind turbine systems under stochastic weather conditions publication-title: IEEE Trans Reliab – volume: 46 start-page: 1017 year: 2014 end-page: 1030 ident: bib36 article-title: Remaining useful life prediction of individual units subject to hard failure publication-title: IIE Trans – volume: 44 start-page: 793 year: 2012 end-page: 803 ident: bib37 article-title: Degradation modeling and monitoring of truncated degradation signals publication-title: IIE Trans – year: 2005 ident: bib35 article-title: Polynomial Kalman filters, fundamentals of Kalman filtering; a practical approach – volume: 19 start-page: 197 year: 1990 end-page: 203 ident: bib4 article-title: One-dimensional marginal density functions of a truncated multivariate normal density function publication-title: Commun Stat – Theory Method – volume: 213 start-page: 1 year: 2011 end-page: 14 ident: bib19 article-title: Remaining useful life estimation – a review on the statistical data driven approaches publication-title: Eur J Oper Res – volume: 38 start-page: 963 year: 1982 end-page: 974 ident: bib10 article-title: Random-effects models for longitudinal data publication-title: Biometrics – volume: 127 start-page: 323 issue: 2 year: 2005 ident: 10.1016/j.ress.2016.02.006_bib22 article-title: Aircraft turbofan engine health estimation using constrained Kalman filtering publication-title: J Eng Gas Turbines Power doi: 10.1115/1.1789153 – volume: 96 start-page: 403 year: 2011 ident: 10.1016/j.ress.2016.02.006_bib38 article-title: Particle filtering prognostic estimation of the remaining useful life of nonlinear components publication-title: Reliab Eng Syst Saf doi: 10.1016/j.ress.2010.08.009 – volume: 17 start-page: 2061 issue: 18 year: 1998 ident: 10.1016/j.ress.2016.02.006_bib2 article-title: A comparison of smoothing techniques for CD4 data measured with error in a time-dependent Cox proportional hazards model publication-title: Stat Med doi: 10.1002/(SICI)1097-0258(19980930)17:18<2061::AID-SIM896>3.0.CO;2-O – volume: 3 start-page: 543 issue: 4 year: 2005 ident: 10.1016/j.ress.2016.02.006_bib7 article-title: Residual-life distribution from component degradation signals: a Bayesian approach publication-title: IIE Trans doi: 10.1080/07408170590929018 – volume: 35 start-page: 219 year: 2013 ident: 10.1016/j.ress.2016.02.006_bib20 article-title: A Wiener-process-based degradation model with a recursive filter algorithm for remaining useful life estimation publication-title: Mech Syst Signal Process doi: 10.1016/j.ymssp.2012.08.016 – volume: 35 start-page: 161 year: 1993 ident: 10.1016/j.ress.2016.02.006_bib15 article-title: Using degradation measures to estimate a time-to-failure distribution publication-title: Technometrics doi: 10.1080/00401706.1993.10485038 – volume: 56 start-page: 302 issue: 3 year: 2014 ident: 10.1016/j.ress.2016.02.006_bib32 article-title: The inverse Gaussian process as a degradation model publication-title: Technometrics doi: 10.1080/00401706.2013.830074 – ident: 10.1016/j.ress.2016.02.006_bib1 doi: 10.1109/ICPHM.2014.7036386 – volume: 38 start-page: 963 issue: 4 year: 1982 ident: 10.1016/j.ress.2016.02.006_bib10 article-title: Random-effects models for longitudinal data publication-title: Biometrics doi: 10.2307/2529876 – volume: 1206 start-page: 5387v1 year: 2012 ident: 10.1016/j.ress.2016.02.006_bib16 article-title: Moment calculation for the doubly truncated multivariate normal density publication-title: arXiv – volume: 23 start-page: 223 issue: 1 year: 1961 ident: 10.1016/j.ress.2016.02.006_bib29 article-title: The moment generating function of the truncated multinormal distribution publication-title: J R Stat Soc, Ser B (Methodol) doi: 10.1111/j.2517-6161.1961.tb00408.x – volume: 90 start-page: 27 issue: 429 year: 1995 ident: 10.1016/j.ress.2016.02.006_bib30 article-title: Modeling the relationship of survival to longitudinal data measured with error: applications to survival and CD4 counts in patients with AIDS publication-title: J Am Stat Assoc doi: 10.1080/01621459.1995.10476485 – year: 2005 ident: 10.1016/j.ress.2016.02.006_bib35 – volume: 9 start-page: 209 issue: 1 year: 2012 ident: 10.1016/j.ress.2016.02.006_bib28 article-title: Modified two-stage degradation model for dynamic maintenance threshold calculation considering uncertainty publication-title: IEEE Trans Autom Sci Eng doi: 10.1109/TASE.2011.2160538 – volume: 39 start-page: 128 year: 2002 ident: 10.1016/j.ress.2016.02.006_bib21 article-title: Kalman filtering with state equality constraints publication-title: IEEE Trans Aerosp Electron Syst doi: 10.1109/7.993234 – volume: 48 start-page: 273 year: 2012 ident: 10.1016/j.ress.2016.02.006_bib27 article-title: Truncation nonlinear filters for state estimation with nonlinear inequality constraints publication-title: Automatica doi: 10.1016/j.automatica.2011.11.002 – volume: 45 start-page: 939 issue: 9 year: 2013 ident: 10.1016/j.ress.2016.02.006_bib6 article-title: Condition monitoring and remaining useful life prediction using degradation signals: revisited publication-title: IIE Trans doi: 10.1080/0740817X.2012.706376 – volume: 59 start-page: 393 issue: 2 year: 2010 ident: 10.1016/j.ress.2016.02.006_bib3 article-title: Optimal maintenance strategies for wind turbine systems under stochastic weather conditions publication-title: IEEE Trans Reliab doi: 10.1109/TR.2010.2046804 – volume: 28 start-page: 597 year: 2012 ident: 10.1016/j.ress.2016.02.006_bib5 article-title: Machine remaining useful life prediction: an integrated adaptive neuro-fuzzy and high-order particle filtering approach publication-title: Mech Syst Signal Process doi: 10.1016/j.ymssp.2011.10.009 – ident: 10.1016/j.ress.2016.02.006_bib13 – volume: AC-16 start-page: 688 issue: 6 year: 1971 ident: 10.1016/j.ress.2016.02.006_bib17 article-title: A tutorial introduction to estimation and filtering publication-title: IEEE Trans Autom Control doi: 10.1109/TAC.1971.1099833 – volume: 44 start-page: 793 issue: 9 year: 2012 ident: 10.1016/j.ress.2016.02.006_bib37 article-title: Degradation modeling and monitoring of truncated degradation signals publication-title: IIE Trans doi: 10.1080/0740817X.2011.618175 – year: 2003 ident: 10.1016/j.ress.2016.02.006_bib9 – volume: 38 start-page: 543 year: 1989 ident: 10.1016/j.ress.2016.02.006_bib12 article-title: Algorithm AS 249: evaluation of the mean and covariance of the truncated multinormal distribution publication-title: Appl Stat doi: 10.2307/2347752 – volume: 59 start-page: 405 issue: 2 year: 2010 ident: 10.1016/j.ress.2016.02.006_bib34 article-title: Estimation of time to hard failure distributions using a three-stage method publication-title: IEEE Trans Reliab doi: 10.1109/TR.2010.2044610 – ident: 10.1016/j.ress.2016.02.006_bib8 doi: 10.1007/978-0-85729-320-6_42 – volume: 62 start-page: 379 issue: 2 year: 2013 ident: 10.1016/j.ress.2016.02.006_bib26 article-title: Evaluation and comparison of mixed effects model based prognosis for hard failure publication-title: IEEE Trans Reliab doi: 10.1109/TR.2013.2259205 – volume: 3 start-page: 165 year: 1979 ident: 10.1016/j.ress.2016.02.006_bib11 article-title: On the first and second moments of the truncated multi-normal distribution and a simple estimator publication-title: Econ Lett doi: 10.1016/0165-1765(79)90111-3 – volume: 4 start-page: 1303 issue: 8 year: 2010 ident: 10.1016/j.ress.2016.02.006_bib24 article-title: Kalman filtering with state constraints: a survey of linear and nonlinear algorithms publication-title: IET Control Theory Appl doi: 10.1049/iet-cta.2009.0032 – volume: 53 start-page: 330 year: 1997 ident: 10.1016/j.ress.2016.02.006_bib31 article-title: A joint model for survival and longitudinal data measured with error publication-title: Biometrics doi: 10.2307/2533118 – volume: 46 start-page: 1017 issue: 10 year: 2014 ident: 10.1016/j.ress.2016.02.006_bib36 article-title: Remaining useful life prediction of individual units subject to hard failure publication-title: IIE Trans doi: 10.1080/0740817X.2013.876126 – volume: 41 start-page: 159 issue: 2 year: 2010 ident: 10.1016/j.ress.2016.02.006_bib23 article-title: Constrained Kalman filtering via density function truncation for turbofan engine health estimation publication-title: Int J Syst Sci doi: 10.1080/00207720903042970 – volume: 213 start-page: 1 year: 2011 ident: 10.1016/j.ress.2016.02.006_bib19 article-title: Remaining useful life estimation – a review on the statistical data driven approaches publication-title: Eur J Oper Res doi: 10.1016/j.ejor.2010.11.018 – ident: 10.1016/j.ress.2016.02.006_bib18 doi: 10.1109/AFGR.1998.670960 – volume: 31 start-page: 513 year: 2015 ident: 10.1016/j.ress.2016.02.006_bib33 article-title: A Bayesian approach to condition monitoring with imperfect inspections publication-title: Qual Reliab Eng Int doi: 10.1002/qre.1609 – volume: 52 start-page: 426 issue: 53 year: 2015 ident: 10.1016/j.ress.2016.02.006_bib14 article-title: Switching Kalman filter for failure prognostics publication-title: Mech Syst Signal Process doi: 10.1016/j.ymssp.2014.08.006 – volume: 19 start-page: 197 year: 1990 ident: 10.1016/j.ress.2016.02.006_bib4 article-title: One-dimensional marginal density functions of a truncated multivariate normal density function publication-title: Commun Stat – Theory Method doi: 10.1080/03610929008830197 – volume: 64 start-page: 182 issue: 1 year: 2015 ident: 10.1016/j.ress.2016.02.006_bib25 article-title: RUL prediction for individual units based on condition monitoring signals with a change point publication-title: IEEE Trans Reliab doi: 10.1109/TR.2014.2355531 |
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| Snippet | In this paper, a statistical prognostic method to predict the remaining useful life (RUL) of individual units based on noisy condition monitoring signals is... |
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| SubjectTerms | Accuracy Condition monitoring Condition monitoring signals Constrained Kalman filter Constraints Evolution Kalman filters Mathematical models Noise levels Random noise Remaining useful life |
| Title | Remaining useful life prediction based on noisy condition monitoring signals using constrained Kalman filter |
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