It takes the average reader 4 hours and 44 minutes to read Data-Driven Fault Detection and Reasoning for Industrial Monitoring by Jing Wang
Assuming a reading speed of 250 words per minute. Learn more
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.
Data-Driven Fault Detection and Reasoning for Industrial Monitoring by Jing Wang is 277 pages long, and a total of 71,189 words.
This makes it 93% the length of the average book. It also has 87% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes 6 hours and 29 minutes to read Data-Driven Fault Detection and Reasoning for Industrial Monitoring aloud.
Data-Driven Fault Detection and Reasoning for Industrial Monitoring is suitable for students ages 12 and up.
Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.
When deciding what to show young students always use your best judgement and consult a professional.
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