Intelligent fault diagnosis and health assessment for complex electro-mechanical systems / Weihua Li, Xiaoli Zhang, Ruqiang Yan.

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Intelligent fault diagnosis and health assessment for complex electro-mechanical systems / Weihua Li, Xiaoli Zhang, Ruqiang Yan.

9789819935376 (electronic bk.)
9819935377 (electronic bk.)
9789819935369
9819935369

Singapore : Springer, 2023.

English

1 online resource (xi, 467 pages) : illustrations (some color)

10.1007/978-981-99-3537-6 doi

TA169.6

620/.00452

Based on AI and machine learning, this book systematically presents the theories and methods for complex electro-mechanical system fault prognosis, intelligent diagnosis, and health state assessment in modern industry. The book emphasizes feature extraction, incipient fault prediction, fault classification, and degradation assessment, which are based on supervised-, semi-supervised-, manifold-, and deep learning; machinery degradation state tracking and prognosis by phase space reconstruction; and complex electro-mechanical system reliability assessment and health maintenance based on running state info. These theories and methods are integrated with practical industrial applications, which can help the readers get into the field more smoothly and provide an important reference for their study, research, and engineering practice.

Includes bibliographical references.

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Online resource; title from PDF title page (SpringerLink, viewed September 19, 2023).

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