Process Monitoring and Fault Diagnosis Based on Multivariable Statistical Analysis

Xiangyu Kong received the B.S. degree in optical engineering from Beijing Institute of Technology, P. R. China, in 1990, the M.S. degree in mechanical and electrical engineering from Xi'an Institute of Hi-Tech, in 2000, and the Ph.D. degree in automation science and engineering from Xi'an Jiaotong University, P. R. China, in 2005. He is currently a professor in the Department of Control Engineering of Xi'an Institute of Hi-Tech. His research interests include adaptive signal processing, neural networks and feature extraction, process monitoring, and fault diagnosis. He has published six monographs (all first author), including an English monograph published by Springer, and more than 150 papers, in which more than 40 articles were published in premier journals including IEEE Transactions on Signal Processing, IEEE Transactions on Neural Networks and Learning Systems, and Neural Networks. He has been PIs of four grants from the National Natural Science Foundation of China. Jiayu Luo received Bachelor's degree from Hunan University, Hunan, China, in 2017, and Master's degree from Xi'an Institute of Hi-Tech., Xi'an, China, in 2019. He is currently pursuing Ph.D. degree in Xi'an Institute of Hi-Tech. He has published one book and 11 articles in IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Instrumentation and Measurement, IEEE Transactions on Signal Processing, and other journals. His research interests include feature extraction, complex process monitoring, and fault diagnosis. Xiaowei Feng received his Bachelor's, Master's, and Ph.D. degrees from Xi'an Institute of High Tech., Xi'an, in 2008, 2011, and 2016, respectively. Now, he is working as a lecturer at Xi'an Institute of Hi-Tech. He has authored or co-authored more than 20 journal papers on IEEE Transactions on Signal Processing, IEEE Transactions on Neural Networks and Learning Systems,and other journals and has published 1 monograph. His research interests include feature extraction, industrial process monitoring, and fault diagnosis.