Buch, Englisch, 549 Seiten, Format (B × H): 157 mm x 234 mm, Gewicht: 953 g
Decision Support Systems in Condition Monitoring and Diagnosis
Buch, Englisch, 549 Seiten, Format (B × H): 157 mm x 234 mm, Gewicht: 953 g
ISBN: 978-1-4665-8405-1
Verlag: CRC Press
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.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Massive Field Data Collection: Issues and Challenges. Condition Monitoring: Available Techniques. Challenges of Condition Monitoring Using AI Techniques. Input and Output Data. Two-Stage Response Surface Approaches to Modeling Drug Interaction. Nearest-Neighbor-Based Techniques. Clustering-Based Techniques. Statistical Techniques. Information Theory-Based Techniques. Uncertainty Management.