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Fault diagnosis and prognostics based on cognitive computing and geometric space transformation

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Fault diagnosis and prognostics based on cognitive computing and geometric space transformation/ by Chen Lu ... [et al.].
其他作者:	Lu, Chen.
出版者:	Singapore :Springer Nature Singapore : : 2024.,
面頁冊數:	xiv, 554 p. :ill. (chiefly color), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Fault location (Engineering) - Data processing. -
電子資源:	https://doi.org/10.1007/978-981-99-8917-1
ISBN:	9789819989171

Fault diagnosis and prognostics based on cognitive computing and geometric space transformation
Fault diagnosis and prognostics based on cognitive computing and geometric space transformation[electronic resource] /by Chen Lu ... [et al.]. - Singapore :Springer Nature Singapore :2024. - xiv, 554 p. :ill. (chiefly color), digital ;24 cm.

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.

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.

ISBN: 9789819989171

Standard No.: 10.1007/978-981-99-8917-1doiSubjects--Topical Terms:

1135268
Fault location (Engineering)
--Data processing.

LC Class. No.: TA169.6

Dewey Class. No.: 620.0044

Fault diagnosis and prognostics based on cognitive computing and geometric space transformation
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520 $a 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.
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