A comparative study of statistical machine learning methods for condition monitoring of electric drive trains in supply chains

Fault detection and identification are critical for the accurate maintenance and management of industrial machinery. In this regard, data-driven condition monitoring models play an important role in machinery fault diagnosis and management. This study investigates the applicability of various statis...

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Bibliographic Details

Published in:	Supply Chain Analytics Vol. 2; p. 100011
Main Author:	Lahmiri, Salim
Format:	Journal Article
Language:	English
Published:	Elsevier 01.06.2023
Subjects:	Discriminant analysis Fault diagnosis K-Nearest Neighbor algorithm Kernel naïve Bayes Machine learning Support vector machine
ISSN:	2949-8635, 2949-8635
Online Access:	Get full text
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