Lu, Chen. creator author. aut http://id.loc.gov/vocabulary/relators/aut Tao, Laifa. author. aut http://id.loc.gov/vocabulary/relators/aut Ma, Jian. author. aut http://id.loc.gov/vocabulary/relators/aut Cheng, Yujie. author. aut http://id.loc.gov/vocabulary/relators/aut Ding, Yu. author. aut http://id.loc.gov/vocabulary/relators/aut SpringerLink (Online service) text si 2024 1st ed. 2024. monographic eng

electronic

electronic resource

access XIV, 554 p. 357 illus., 281 illus. in color. online resource. 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. 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. by Chen Lu, Laifa Tao, Jian Ma, Yujie Cheng, Yu Ding. Computational intelligence Artificial intelligence Control engineering Computational Intelligence Artificial Intelligence Control and Systems Theory Q342 9789819989171 https://doi.org/10.1007/978-981-99-8917-1 https://doi.org/10.1007/978-981-99-8917-1 250102 20251030114918.0 978-981-99-8917-1