Data-Driven Fault Detection and Reasoning for Industrial Monitoring (Intelligent Control and Learning Systems, #3)

by Jing Wang, Jinglin Zhou, and Xiaolu Chen

0 ratings • 0 reviews • 0 shelved
Book cover for Data-Driven Fault Detection and Reasoning for Industrial Monitoring

Bookhype may earn a small commission from qualifying purchases. Full disclosure.


This open access book assesses the potential of data-driven methods in industrial process monitoring engineering. The process modeling, fault detection, classification, isolation, and reasoning are studied in detail. These methods can be used to improve the safety and reliability of industrial processes. Fault diagnosis, including fault detection and reasoning, has attracted engineers and scientists from various fields such as control, machinery, mathematics, and automation engineering. Combining the diagnosis algorithms and application cases, this book establishes a basic framework for this topic and implements various statistical analysis methods for process monitoring. This book is intended for senior undergraduate and graduate students who are interested in fault diagnosis technology, researchers investigating automation and industrial security, professional practitioners and engineers working on engineering modeling and data processing applications.

This is an open access book.

  • ISBN13 9789811680434
  • Publish Date 4 January 2022
  • Publish Status Active
  • Publish Country SG
  • Imprint Springer Verlag, Singapore
  • Edition 1st ed. 2022
  • Format Hardcover
  • Pages 264
  • Language English