Fault Diagnosis and Prognostics Based on Cognitive Computing and Geometric Space Transformation - Lu, Chen; Tao, Laifa; Ma, Jian; - Prospero Internet Bookshop

Fault Diagnosis and Prognostics Based on Cognitive Computing and Geometric Space Transformation
 
Product details:

ISBN13:9789819989164
ISBN10:9819989167
Binding:Hardback
No. of pages:554 pages
Size:235x155 mm
Language:English
Illustrations: 76 Illustrations, black & white; 281 Illustrations, color
684
Category:

Fault Diagnosis and Prognostics Based on Cognitive Computing and Geometric Space Transformation

 
Edition number: 2024
Publisher: Springer
Date of Publication:
Number of Volumes: 1 pieces, Book
 
Normal price:

Publisher's listprice:
EUR 235.39
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99 852 HUF (95 097 HUF + 5% VAT)
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Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
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  Piece(s)

 
Short 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.

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.

Table 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.