Fault Diagnosis and Prognostics Based on Cognitive Computing and Geometric Space Transformation
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Product details:
- Edition number 2024
- Publisher Springer Nature Singapore
- Date of Publication 3 January 2025
- Number of Volumes 1 pieces, Book
- ISBN 9789819989164
- Binding Hardback
- No. of pages554 pages
- Size 235x155 mm
- Language English
- Illustrations XIV, 554 p. 357 illus., 281 illus. in color. Illustrations, black & white 576
Categories
Long description:
This monograph introduces readers to new theories and methods applying cognitive computing and geometric space transformation to the field of fault diagnosis and prognostics. It summarizes the basic concepts and technical aspects of fault diagnosis and prognostics technology. Existing bottleneck problems are examined, and the advantages of applying cognitive computing and geometric space transformation are explained. In turn, the book highlights fault diagnosis, prognostic, and health assessment technologies based on cognitive computing methods, including deep learning, transfer learning, visual cognition, and compressed sensing. Lastly, it covers technologies based on differential geometry, space transformation, and pattern recognition.
MoreTable of Contents:
Chapter 1 Introduction.- Chapter 2 Fault Diagnosis and Prognosis based on Deep Learning and Transfer Learning.- Chapter 3 Fault Diagnosis and Evaluation Based on Visual Cognitive Computing.- Chapter 4 Fault Diagnosis Based on Compressed Sensing.- Chapter 5 Fault Diagnosis and Evaluation Based on Differential Geometry.- Chapter 6 Performance Degradation Prediction and Assessment based on Geometric Space Transformation and Morphology Recognition.
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