Machine Learning Based Fault Diagnosis for Industrial Engineering Systems is popular PDF and ePub book, written by Rui Yang in 2022-06-16, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Machine Learning Based Fault Diagnosis for Industrial Engineering Systems can be Read Online from any device for your convenience.
Machine Learning Based Fault Diagnosis for Industrial Engineering Systems Book PDF Summary
This book provides advanced techniques for precision compensation and fault diagnosis of precision motion systems and rotating machinery. Techniques and applications through experiments and case studies for intelligent precision compensation and fault diagnosis are offered along with the introduction of machine learning and deep learning methods. Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems discusses how to formulate and solve precision compensation and fault diagnosis problems. The book includes experimental results on hardware equipment used as practical examples throughout the book. Machine learning and deep learning methods used in intelligent precision compensation and intelligent fault diagnosis are introduced. Applications to deal with relevant problems concerning CNC machining and rotating machinery in industrial engineering systems are provided in detail along with applications used in precision motion systems. Methods, applications, and concepts offered in this book can help all professional engineers and students across many areas of engineering and operations management that are involved in any part of Industry 4.0 transformation.
Detail Book of Machine Learning Based Fault Diagnosis for Industrial Engineering Systems PDF
- Author : Rui Yang
- Release : 16 June 2022
- Publisher : CRC Press
- ISBN : 9781000594935
- Genre : Technology & Engineering
- Total Page : 87 pages
- Language : English
- PDF File Size : 7,7 Mb
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