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Record Nr. |
UNINA9910373900603321 |
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Autore |
Verma Nishchal K |
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Titolo |
Intelligent Condition Based Monitoring : For Turbines, Compressors, and Other Rotating Machines / / by Nishchal K. Verma, Al Salour |
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Pubbl/distr/stampa |
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Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (XXX, 302 p.) |
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Collana |
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Studies in Systems, Decision and Control, , 2198-4182 ; ; 256 |
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Disciplina |
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Soggetti |
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Machinery |
Computational intelligence |
Quality control |
Reliability |
Industrial safety |
Machinery and Machine Elements |
Computational Intelligence |
Quality Control, Reliability, Safety and Risk |
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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 bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Introduction -- Faults And Data Acquisition -- Preprocessing -- Feature Extraction -- Feature Selection -- Fault Recognisition -- Fault Diagnosis System For Air Compressor Using Palmtop -- Improved Fault Detection Model -- Fault Diagnosis System Using Smartphone -- References. |
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Sommario/riassunto |
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This book discusses condition based monitoring of rotating machines using intelligent adaptive systems. The book employs computational intelligence and fuzzy control principles to deliver a module that can adaptively monitor and optimize machine health and performance. This book covers design and performance of such systems and provides case studies and data models for fault detection and diagnosis. The contents cover everything from optimal sensor positioning to fault diagnosis. The principles laid out in this book can be applied across rotating machinery such as turbines, compressors, and aircraft engines. The adaptive fault diagnostics systems presented can be used in multiple time and safety critical applications in domains such as |
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aerospace, automotive, deep earth and deep water exploration, and energy. . |
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