Artificial Intelligence Tools : Decision Support Systems in Condition Monitoring and DIagnosis
Language: English
Published by Taylor & Francis, CRC Press, 2020
- Softcover
- New

Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
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Add to basketItem description from seller
nach der Bestellung gedruckt Neuware - Printed after ordering - Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource:Addresses nearest-neighbor-based, clustering-based, statistical, and information theory-based techniquesConsiders the merits of each technique as well as the issues associated with real-life applicationCovers classification methods, from neural networks to Bayesian and support vector machinesProposes fuzzy logic to explain the uncertainties associated with diagnostic processes Provides data sets, sample signals, and MATLAB® code for algorithm testingArtificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis delivers a thorough evaluation of the latest AI tools for CM, describing the most common fault diagnosis techniques used and the data acquired when these techniques are applied.…
Seller Inventory # 9780367738358
- Title
- Artificial Intelligence Tools : Decision Support Systems in Condition Monitoring and DIagnosis
- Author
- Diego Galar Pascual
- Publisher
- Taylor & Francis, CRC Press
- Publication year
- 2020
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 036773835X
- ISBN 13
- 9780367738358
- Item weight
- 830 grams
- Dimensions
- 234x156x29 mm
Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource:
- Addresses nearest-neighbor-based, clustering-based, statistical, and information theory-based techniques
- Considers the merits of each technique as well as the issues associated with real-life application
- Covers classification methods, from neural networks to Bayesian and support vector machines
- Proposes fuzzy logic to explain the uncertainties associated with diagnostic processes
- Provides data sets, sample signals, and MATLAB® code for algorithm testing
Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis delivers a thorough evaluation of the latest AI tools for CM, describing the most common fault diagnosis techniques used and the data acquired when these techniques are applied.
"Synopsis" may belong to another edition of this title.
About the Author
Diego Galar Pascual holds an M.Sc and Ph.D from Saragossa University, Zaragoza, Spain. He has been a professor at several universities, including Saragossa University and the European University of Madrid, Spain. At Saragossa University, he also served as director of academic innovation, director of international relations, pro-vice-chancellor, and senior researcher in the Aragon Institute of Engineering Research (i3A). In addition, he has been the technological director and CBM manager of international firms such as Volvo, Saab, Boliden, Scania, Tetrapak, Heinz, and Atlas Copco. Currently, he is the professor of condition monitoring in the Division of Operation and Maintenance of the Luleå University of Technology (LTU), Sweden, where he also is involved with the LTU-SKF University Technology Center. Widely published, Dr. Galar Pascual serves as a visiting professor at the University of Valencia (Spain), Polytechnic of Braganza (Portugal), Valley University (Mexico), Sunderland University (UK), University of Maryland (College Park, USA), and Northern Illinois University (DeKalb, USA).
"About the title" may belong to another edition of this title.
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