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Transfer Learning for Rotary Machine Fault Diagnosis and Prognosis
Transfer Learning for Rotary Machine Fault Diagnosis and Prognosis
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Transfer Learning for Rotary Machine Fault Diagnosis and Prognosis provides an overview of the theory and applications of transfer learning in rotary machine fault diagnosis and prognosis,with case studies and technical details.
Format: Unspecified
Length: 312 pages
Publication date: 24 November 2023
Publisher: Elsevier - Health Sciences Division
Transfer Learning for Rotary Machine Fault Diagnosis and Prognosis delves into the realm of transfer learning, exploring its theoretical foundations and cutting-edge applications in the field of rotary machine fault diagnosis and prognosis. This innovative book serves as a comprehensive guide, synthesizing recent advancements from both academia and industry to offer systematic guidance on this relatively new subject. Before delving into the core topics, the book provides a foundational understanding of the basic principles involved. It then addresses key questions such as the applicability of transfer learning to rotary machine fault diagnosis and prognosis, delving into technical details of models and introducing the concept of deep transfer learning. To enhance the reader's understanding and practical application of the techniques described, comprehensive case studies are provided for each method. These case studies showcase real-world applications and help readers apply the methodologies outlined in their own work, fostering a deeper understanding of transfer learning in the field of rotary machine fault diagnosis and prognosis.
Dimension: 229 x 152 (mm)
ISBN-13: 9780323999892
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