Comparative Study of Data-Driven Models in Motor RUL Estimation
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 8, Issue 1
Abstract
The extremely complex loading conditions on the clutch of a four-wheeled passenger vehicle frequently results in malfunction of the motor. The latest diagnostic methods for detecting the initiation of device failure have proven to be unreliable. The present research has been carried out to demonstrate the state of health of the motor on the basis of a nonlinear real time estimation approach. In order to fulfil this task, a systematic review was undertaken of the unscented particle filter (UPF) approach to handle the evolved noisy signal with in real time. Research facilitates the modeling of nonlinear behavior of elements via state-space equations embedded with a set of available real time measurements. The remaining useful life (RUL) of the motor (system) as a distribution function is estimated. The study highlights that the state space framework provides better results than the degradation modeling scheme to forecast the RUL of the system.
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Data Availability Statement
Some of the data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. The items are listed below:
1.
The feature set used in the study has been obtained using the author’s previous work [Banerjee et al. (2021)].
2.
Table 1 provides the parameter values of the empirical fitting that were used in the process of RUL prediction.
Acknowledgments
The first author expresses his sincere gratitude to Mr. Prasanta Sarkar for granting permission to work in the Advanced Engineering Research Centre of TATA Motors. The authors also extend their sincere thanks to TATA Motors for allowing the first author to make use of their HIL.
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Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 8 • Issue 1 • March 2022
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Feb 24, 2021
Accepted: Jul 25, 2021
Published online: Oct 18, 2021
Published in print: Mar 1, 2022
Discussion open until: Mar 18, 2022
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