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portada Intelligent Fault Diagnosis and Prognosis for Industrial Systems: Cross-Domain, Zero-Sample, and Degradation Modeling Methods
Type
Physical Book
Publisher
Author
Language
English
Pages
222
Format
Paperback
ISBN13
9780443442919

Intelligent Fault Diagnosis and Prognosis for Industrial Systems: Cross-Domain, Zero-Sample, and Degradation Modeling Methods

Hongpeng Yin Phd; Li Cai B.e.; Peng Zhang B.e. (Author) · Elsevier · Paperback

Intelligent Fault Diagnosis and Prognosis for Industrial Systems: Cross-Domain, Zero-Sample, and Degradation Modeling Methods - Hongpeng Yin Phd; Li Cai B.E.; Peng Zhang B.E.

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Synopsis "Intelligent Fault Diagnosis and Prognosis for Industrial Systems: Cross-Domain, Zero-Sample, and Degradation Modeling Methods"

Industrial Fault Diagnosis and Remaining Useful Life Prediction: Cross-Domain, Zero-Sample, and Degradation Modeling Methods introduces zero-sample learning methods that enable fault diagnosis and Predict Remaining Useful Life (RUL) without the need for labelled fault data. This is particularly valuable in industrial settings where labelled data is scarce or unavailable. Offers step-by-step guidance on implementing zero-shot learning models using real industrial data, reducing the learning curve for practitioners; includes real-world industrial case studies to demonstrate the application of zero-sample learning techniques in various industries, such as manufacturing, energy, and transportation. Such case studies provide readers with actionable insights and practical solutions. The book covers advanced methodologies for predicting the remaining useful life of industrial equipment, supporting readers in optimizing maintenance schedules, reducing downtime and extending the lifespan of critical assets. Covers state-of-the-art algorithms, including deep learning, transfer learning and domain adaptation, tailored for zero-sample scenarios. These tools empower readers to develop robust fault diagnosis and RUL prediction systems, enhancing predictive maintenance capabilities and ensuring the reliability of industrial systems.

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