| 书目名称 | Intelligent Fault Diagnosis and Health Assessment for Complex Electro-Mechanical Systems | | 编辑 | Weihua Li,Xiaoli Zhang,Ruqiang Yan | | 视频video | | | 概述 | Presents advanced machine learning paradigms for complex electro-mechanical system fault diagnosis and health assessment.Covers a wide range of research directions in intelligent fault diagnosis and h | | 图书封面 |  | | 描述 | 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. | | 出版日期 | Book 2023 | | 关键词 | Intelligent Fault Diagnosis; Health Assessment; Complex Electro-mechanical System; Machine Learning; Art | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-99-3537-6 | | isbn_softcover | 978-981-99-3539-0 | | isbn_ebook | 978-981-99-3537-6 | | copyright | National Defense Industry Press 2023 |
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发表于 2025-3-21 17:14:26
