Machine Performance Degradation Assessment : Convex Optimization Models and Their Interpretable Data Fusion Applications

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  • 電子書籍

Machine Performance Degradation Assessment : Convex Optimization Models and Their Interpretable Data Fusion Applications

  • 著者名:Wang PhD, Dong/Yan B.E., Tongtong
  • 価格 ¥32,111 (本体¥29,192)
  • Elsevier(2025/10/17発売)
  • ポイント 291pt (実際に付与されるポイントはご注文内容確認画面でご確認下さい)
  • 言語:ENG
  • ISBN:9780443440076
  • eISBN:9780443440083

ファイル: /

Description

Machine Performance Degradation Assessment: Convex Optimization Models and Their Interpretable Data Fusion Applications is an essential resource for industry professionals and researchers seeking to understand the latest trends in performance degradation assessment technologies. This comprehensive guide delves into the fundamental theories of convex optimization models while exploring cutting-edge research methods. Readers will gain valuable insights into interpretable data fusion models and their applications, providing practical and theoretical knowledge to advance their understanding of machine performance degradation. In addition to the core mathematical elements, the book includes advanced techniques for formulating degradation properties into convex optimization models for health index construction.Real-world applications and examples demonstrate how these innovative methods can be applied in practice. By presenting novel concepts and analytical frameworks, this book offers fresh perspectives to help readers navigate the complexities of machine performance degradation assessment.- Provides valuable insights on the evolving challenges in machinery performance monitoring and optimization- Includes the background and roadmaps of machine performance degradation assessment technologies, which are described in-depth- Presents real-world applications and examples of practical experience

Table of Contents

1. Machine performance degradation assessment2. Fundamentals of convex optimization3. Machine degradation processes related mathematical properties4. Generalized health index weight optimization models based on degradation properties and amplitude fusion in the frequency domain5. Generalized health index weight optimization models based on fault feature sparsity and amplitude fusion in the envelope spectral domain6. Conclusions