TY - GEN
T1 - Research and application of KICA-AROMF based fault diagnosis
AU - Zhu, Qun Xiong
AU - Meng, Qian Qian
AU - Xu, Yuan
AU - He, Yan Lin
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/18
Y1 - 2017/7/18
N2 - With the development of the modern industrial system, data-driven fault diagnosis methods have attracted more and more attention. Fault diagnosis of complex industrial processes based on one-dimensional adaptive rank-order morphological filter (AROMF) may miss key information because of excessive dimension reduction of process data. To solve this problem, a method combining the kernel independent component analysis (KICA) with one-dimensional AROMF is proposed. Firstly, KICA is used for nonlinear feature extraction, getting the template signal and the test signal of each pattern. Then, a fault diagnosis method via multi-dimensional signals classification method based on AROMF is presented in this paper. The advantage of the proposed method was confirmed by the simulation of the Tennessee Eastman process.
AB - With the development of the modern industrial system, data-driven fault diagnosis methods have attracted more and more attention. Fault diagnosis of complex industrial processes based on one-dimensional adaptive rank-order morphological filter (AROMF) may miss key information because of excessive dimension reduction of process data. To solve this problem, a method combining the kernel independent component analysis (KICA) with one-dimensional AROMF is proposed. Firstly, KICA is used for nonlinear feature extraction, getting the template signal and the test signal of each pattern. Then, a fault diagnosis method via multi-dimensional signals classification method based on AROMF is presented in this paper. The advantage of the proposed method was confirmed by the simulation of the Tennessee Eastman process.
UR - http://www.scopus.com/inward/record.url?scp=85034031588&partnerID=8YFLogxK
U2 - 10.1109/ADCONIP.2017.7983783
DO - 10.1109/ADCONIP.2017.7983783
M3 - Conference contribution
AN - SCOPUS:85034031588
T3 - 2017 6th International Symposium on Advanced Control of Industrial Processes, AdCONIP 2017
SP - 215
EP - 220
BT - 2017 6th International Symposium on Advanced Control of Industrial Processes, AdCONIP 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th International Symposium on Advanced Control of Industrial Processes, AdCONIP 2017
Y2 - 28 May 2017 through 31 May 2017
ER -