TY - GEN
T1 - Process monitoring of nonlinear industrial process on quality variables based on kernel MPLS
AU - Ren, Zelin
AU - An, Baoran
AU - Yin, Shen
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/6/8
Y1 - 2018/6/8
N2 - In this paper, a data-driven process monitoring method for quality variables is presented in this paper. Modified partial least squares (MPLS) approach is a kind of lineai multivariate statistical analysis methods, which has a good effeci on process monitoring of linear industrial system. However, it ii not suitable for monitoring nonlinear complex industrial systems Based on it, a nonlinear process monitoring method, kerne modified partial least squares (MKPLS) approach, is obtained by introducing the nuclear method into the MPLS method, in order to detect the fault that can affect quality variables. Firsi of all, the fundamental thoughts of the kernel method are given Then, introduce kernel method to MPLS approach to get MKPLS method. After that, the monitoring effect of MKPLS method on the nonlinear process is tested by nonlinear numerical simulation Finally, MKPLS method is applied to the wastewater treatmen process (WWTP) and process monitoring results are presented in the form of figure.
AB - In this paper, a data-driven process monitoring method for quality variables is presented in this paper. Modified partial least squares (MPLS) approach is a kind of lineai multivariate statistical analysis methods, which has a good effeci on process monitoring of linear industrial system. However, it ii not suitable for monitoring nonlinear complex industrial systems Based on it, a nonlinear process monitoring method, kerne modified partial least squares (MKPLS) approach, is obtained by introducing the nuclear method into the MPLS method, in order to detect the fault that can affect quality variables. Firsi of all, the fundamental thoughts of the kernel method are given Then, introduce kernel method to MPLS approach to get MKPLS method. After that, the monitoring effect of MKPLS method on the nonlinear process is tested by nonlinear numerical simulation Finally, MKPLS method is applied to the wastewater treatmen process (WWTP) and process monitoring results are presented in the form of figure.
KW - Data-driven
KW - MKPLS
KW - Process monitoring
KW - Quality variables
UR - https://www.scopus.com/pages/publications/85050776853
U2 - 10.1109/ICCRE.2018.8376480
DO - 10.1109/ICCRE.2018.8376480
M3 - 会议稿件
AN - SCOPUS:85050776853
T3 - 2018 3rd International Conference on Control and Robotics Engineering, ICCRE 2018
SP - 280
EP - 284
BT - 2018 3rd International Conference on Control and Robotics Engineering, ICCRE 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Conference on Control and Robotics Engineering, ICCRE 2018
Y2 - 20 April 2018 through 23 April 2018
ER -