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Published in: Journal of Intelligent Manufacturing 3/2024

24-03-2023

Prognostics and health management for induction machines: a comprehensive review

Authors: Chao Huang, Siqi Bu, Hiu Hung Lee, Kwong Wah Chan, Winco K. C. Yung

Published in: Journal of Intelligent Manufacturing | Issue 3/2024

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Abstract

Induction machines (IMs) are utilized in different industrial sectors such as manufacturing, transportation, transmission, and energy due to their ruggedness, low cost, and high efficiency. If IMs fail without advanced warning, unscheduled maintenance needs to be performed, leading to downtime and maintenance costs for asset owners. To avoid these, conducting prognostics and health management (PHM) for IMs is indispensable. There are different PHM methods (expert knowledge, physics-based, and machine learning) to analyze the health and estimate the remaining useful life (RUL) of IMs. It is essential to select appropriate methods and algorithms to solve practical engineering problems by comparing their pros and cons. This paper will systematically summarize the application of the PHM framework to IMs and comprehensively present how to select appropriate general methods as well as specific algorithms applied in the PHM for IMs to solve practical engineering problems, aiming to provide some guidance for future researchers and practitioners.

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Metadata
Title
Prognostics and health management for induction machines: a comprehensive review
Authors
Chao Huang
Siqi Bu
Hiu Hung Lee
Kwong Wah Chan
Winco K. C. Yung
Publication date
24-03-2023
Publisher
Springer US
Published in
Journal of Intelligent Manufacturing / Issue 3/2024
Print ISSN: 0956-5515
Electronic ISSN: 1572-8145
DOI
https://doi.org/10.1007/s10845-023-02103-6

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