Fault Diagnosis and Prognostics Based on Cognitive Computing and Geometric Space Transformation
Lu, Chen.
Fault Diagnosis and Prognostics Based on Cognitive Computing and Geometric Space Transformation [electronic resource] / by Chen Lu, Laifa Tao, Jian Ma, Yujie Cheng, Yu Ding. - 1st ed. 2024. - XIV, 554 p. 357 illus., 281 illus. in color. online resource.
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.
9789819989171
Computational intelligence.
Artificial intelligence.
Control engineering.
Computational Intelligence.
Artificial Intelligence.
Control and Systems Theory.
Q342
006.3
Fault Diagnosis and Prognostics Based on Cognitive Computing and Geometric Space Transformation [electronic resource] / by Chen Lu, Laifa Tao, Jian Ma, Yujie Cheng, Yu Ding. - 1st ed. 2024. - XIV, 554 p. 357 illus., 281 illus. in color. online resource.
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.
9789819989171
Computational intelligence.
Artificial intelligence.
Control engineering.
Computational Intelligence.
Artificial Intelligence.
Control and Systems Theory.
Q342
006.3
