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.