Degradation Data–Driven Analysis for Estimation of the Remaining Useful Life of a Motor
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 7, Issue 2
Abstract
Highly dynamic loading conditions on clutch motors used in four-wheeled passenger vehicles cause them to fail quite often. The current diagnostic tools have proven to be inefficient to detect the onset of system degradation. This paper presents a degradation model to exhibit the state of health of the clutch. A novel condition indicator (CI) and a threshold for conditionally independent noisy signal from the motor subjected to cumulative degradation have been established. A dominating feature characterizing the motor health was discerned to be spectral entropy kurtosis which was identified while analyzing the time-series signal composed of agglomeration of different frequencies that produce higher octaves. Tests for monotonocity and trendability metrics affirmed that spectral entropy kurtosis is a distinguishing CI. Principal component analysis (PCA) allowed the fusion of features for the selection of the best-performing CI. The proposed CI was used in an exponential degradation model to predict the remaining useful life (RUL) of the motor with improved accuracy.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The first author expresses sincere gratitude to Shri. Prasanta Sarkar, General Manager, for granting permission to work in the Advanced Engineering Research Centre of Tata Motors. The authors extend their sincere thanks to Tata Motors for allowing the first author to work on the HIL setup.
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ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 7 • Issue 2 • June 2021
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© 2021 American Society of Civil Engineers.
History
Received: Mar 20, 2020
Accepted: Oct 8, 2020
Published online: Feb 27, 2021
Published in print: Jun 1, 2021
Discussion open until: Jul 27, 2021
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