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Record Nr. |
UNINA9911015871803321 |
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Autore |
Liu Hui |
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Titolo |
Prognostics and Health Management for Intelligent Electromechanical Systems / / by Hui Liu, Fang Cheng, Yanfei Li |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
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ISBN |
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Edizione |
[1st ed. 2025.] |
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Descrizione fisica |
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1 online resource (257 pages) |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Mechatronics |
Computational intelligence |
Engineering - Data processing |
Computational Intelligence |
Data Engineering |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Introduction -- Feature extraction of bearing vibration signal -- Ensemble intelligent diagnosis for bearing faults -- Deep learning based prediction for bearing remaining useful life.-Optimization based prediction for IGBT remaining useful life. |
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Sommario/riassunto |
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This book gives a detailed introduction to the technical background, feature extraction methods, PHM models and big data embedding methods of the big data theory in PHM for intelligent electromechanical systems. Combination with deep learning and big data, this book explains the hybrid algorithm framework of PHM such as ensemble intelligence and optimized intelligence and introduces PHM models for bearing, IGBT, MOSFET and other components and their big data embedding platform. This book improves the PHM method and theory of electromechanical system under industrial big data and provides reference for the development of intelligent electromechanical equipment and intelligent industrial production in the future. . |
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