Despite critical components, very little attention has been paid for wet friction clutches in the monitoring and prognostics research field. This paper presents and discusses an overall methodology for assessing the health (performance) and predicting the remaining useful life (RUL) of wet friction clutches. Three principle features extracted from relative velocity signal measured between the input and output shaft of the clutch, namely (i) the normalized engagement duration, (ii) the normalized Euclidean distance and (iii) the Spectral Angle Mapper (SAM) distance are fused with a logistic regression technique into a single value called the health index. In logistic regression analysis, the output of the logistic model (i.e. the health index) is restricted between 0 and 1. Accordingly, the logistic model can guide the users to assess the state of a wet friction clutch either in healthy state (e.g. health index value of (close to) 1) or in failed state (e.g. health index value of (close to) 0). In terms of prognostics, the logarithm of the odds-of-success g defined as g = log[h/(1−h)], where h denotes the health index, is used as the predicted variable. Once a history data is sufficient for prediction, the weighted mean slope (WMS) method is implemented in this study to adaptively build a prognostics model and to predict the trajectory of g until it crosses a predetermined threshold. This way, the remaining useful life (RUL) of a clutch can be determined. Furthermore, an experimental verification of the proposed methodology has been performed on two history datasets obtained by performing accelerated life tests (ALTs) on two clutch packs with different friction materials but the same lubricant. The experimental results confirm that the proposed methodology is promising and has a potential to be implemented for real-life applications. As was expected, the estimated RUL converges to the actual RUL and the uncertainty Agusmian Partogi Ompusunggu et.al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. interval decreases over time that may indicate that the prognostics model improves as more evidence becomes available.
How to Cite
prognostics, Wet friction clutches, logistic regression, dissimilarity measures, automatic transmissions
Basseville, M., Benveniste, A., Gach-Devauchelle, B., Goursat, M., Bonnecase, D., Dorey, P., et al. (1993). In situdamage monitoring in vibration mechanics: diagnostics and predictive maintenance. Mechanical Systems and Signal Processing, 7(5), 401 - 423.
Bey-Temsamani, A., Engels, M., Motten, A., Vandenplas, S., & Ompusunggu, A. P. (2009a). Condition-Based Maintenance for OEM’s by application of data mining and prediction techniques. In Proceedings of the 4th World Congress on Engineering Asset Management.
Bey-Temsamani, A., Engels, M., Motten, A., Vandenplas, S., & Ompusunggu, A. P. (2009b). A Practical Approach to Combine DataMining and Prognostics for Improved Predictive Maintenance. In The 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Czepiel, S. (n.d.). Maximum likelihood estimation of logistic regression models: theory and implementation. Available from http://czep.net/stat/mlelr.pdf
Fei, J., Li, H.-J., Qi, L.-H., Fu, Y.-W., & Li, X.-T. (2008). Carbon-Fiber Reinforced Paper-Based Friction Material: Study on Friction Stability as a Function of Operating Variables. Journal of Tribology, 130(4), 041605.
Gao, H., & Barber, G. C. (2002). Microcontact Model for Paper-BasedWet Friction Materials. Journal of Tribology, 124(2), 414 - 419.
Gao, H., Barber, G. C., & Chu, H. (2002). Friction Characteristics of a Paper-based Friction Material. International Journal of Automotive Technology, 3(4), 171 - 176.
Garcia, M. C., Sanz-Bobi, M. A., & Pico, J. del. (2006). SIMAP: Intelligent System for Predictive Maintenance: Application to the health condition monitoring of a wind turbine gearbox. Computers in Industry, 57(6), 552 - 568.
Guan, J. J., Willermet, P. A., Carter, R. O., & Melotik., D. J. (1998). Interaction Between ATFs and Friction Material for Modulated Torque Converter Clutches. SAE Technical Paper, 981098, 245 - 252.
Jullien, A., Meurisse, M., & Berthier, Y. (1996). Determination of tribological history and wear through visualisation in lubricated contacts using a carbon-based composite. Wear, 194(1 - 2), 116 - 125.
Kruse, F., Lefkoff, A., Boardman, J., Heidebrecht, K., Shapiro, A., Barloon, P., et al. (1993). The spectral image processing system (SIPS) - interactive visualization and analysis of imaging spectrometer data. Remote Sensing of Environment, 44(2-3), 145 - 163.
Lemeshow, D., & Hosmer, S. (2000). Applied Logistic Regression. New York: Willey. ISBN 0-471-35632-8.
Li, S., Devlin, M., Tersigni, S. H., Jao, T. C., Yatsunami, K., & Cameron., T. M. (2003). Fundamentals of Anti-Shudder Durability: Part I-Clutch Plate Study. SAE Technical Paper, 2003-01-1983, 51 - 62.
Maeda, M., & Murakami, Y. (2003). Testing method and effect of ATF performance on degradation of wet friction materials. SAE Technical Paper, 2003-01-1982, 45 - 50.
Matsuo, K., & Saeki, S. (1997). Study on the change of friction characteristics with use in the wet clutch of automatic transmission. SAE Technical Paper, 972928, 93 - 98.
Meeker, W., & Escobar, L. (1998). Statistical Methods for Reliability Data. Wiley, New York.
Mobley, R. K. (2002). An introduction to predictive maintenance. Butterworth-Heinemann.
Nyman, P.,M¨aki, R., Olsson, R., & Ganemi, B. (2006). Influence of surface topography on friction characteristics in wet clutch applications. Wear, 261(1), 46 - 52. (Papers presented at the 11th Nordic Symposium on Tribology, NORDTRIB 2004)
Ompusunggu, A., Papy, J.-M., Vandenplas, S., Sas, P., & VanBrussel, H. (2009). Exponential data fitting for features extraction in condition monitoring of paper based wet clutches. In C. Gentile, F. Benedettini, R. Brincker, & N. Moller (Eds.), The Proceedings of the 3rd International OperationalModal Analysis Conference (IOMAC) (Vol. 1, p. 323-330). Starrylink Editrice Brescia.
Ompusunggu, A., Papy, J.-M., Vandenplas, S., Sas, P., & Van-Brussel, H. (2012). Condition Monitoring Method for Automatic Transmission Clutches. International Journal of Prognostics and Health Management (IJPHM), 3.
Ompusunggu, A., Sas, P., VanBrussel, H., Al-Bender, F., Papy, J.-M., & Vandenplas, S. (2010). Pre-filtered Hankel Total Least Squares method for condition monitoring of wet friction clutches. In The Proceedings of the 7th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies (CM-MFPT). Coxmor Publishing Company.
Ompusunggu, A., Sas, P., VanBrussel, H., Al-Bender, F., & Vandenplas, S. (2010). Statistical feature extraction of pre-lockup torsional vibration signals for condition monitoring of wet friction clutches. In Proceedings of ISMA2010 Including USD2010.
Ost, W., Baets, P. D., & Degrieck, J. (2001). The tribological behaviour of paper friction plates for wet clutch application investigated on SAE # II and pin-on-disk test rigs. Wear, 249(5-6), 361 - 371.
Paclik, P., & Duin, R. P. W. (2003). Dissimilarity-based classification of spectra: computational issues. Real-Time Imaging, 9(4), 237 - 244.
Srinivas, J., Murthy, B. S. N., & Yang, S. H. (2007). Damage diagnosis in drive-lines using response-based optimization. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 221(11), 1399 - 1404.
Yan, J., Koc,M., & Lee, J. (2004). A prognostic algorithm for machine performance assessment and its application. Production Planning & Control, 15(8), 796-801.
Yan, J., & Lee, J. (2005). Degradation Assessment and Fault Modes Classification Using Logistic Regression. Journal of Manufacturing Science and Engineering, 127(4), 912-914.
Yang, Y., & Lam, R. C. (1998). Theoretical and experimental studies on the interface phenomena during the engagement of automatic transmission clutch. Tribology Letters, 5, 57 - 67.
Yang, Y., Lam, R. C., Chen, Y. F., & Yabe, H. (1995). Modeling of heat transfer and fluid hydrodynamics for a multidisc wet clutch. SAE Technical Paper, 950898, 1 - 15.
Yang, Y., Twaddell, P. S., Chen, Y. F., & Lam, R. C. (1997). Theoretical and experimental studies on the thermal degradation of wet friction materials. SAE Technical Paper, 970978, 175 - 183.
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