kNN Fault Detection Based on Reconstruction Error and Multi-block Modeling Strategy

Authors

Jing Zheng, 1.China Key Laboratory of Advanced Process Control for Light Industry Ministry of Education, Jiangnan University, Wuxi 214122, China;2.School of the Internet of Things Engineering, Jiangnan University, Wuxi 214122, China;Follow
Weili Xiong, 1.China Key Laboratory of Advanced Process Control for Light Industry Ministry of Education, Jiangnan University, Wuxi 214122, China;2.School of the Internet of Things Engineering, Jiangnan University, Wuxi 214122, China;Follow
Xiaodong Wu, 1.China Key Laboratory of Advanced Process Control for Light Industry Ministry of Education, Jiangnan University, Wuxi 214122, China;2.School of the Internet of Things Engineering, Jiangnan University, Wuxi 214122, China;

Abstract

Abstract: For the fault monitoring algorithm based on k-nearest neighbor (kNN), the abnormal information that caused the fault is easy to be overwhelmed by the normal operating condition information, which leads to the problem of untimely fault detection and low alarm rate. A kNN fault monitoring method based on reconstruction error is proposed using auto-encoder and multi-block modeling strategy. The method uses the normal working condition data set to train the auto-encoder model, and extracts the reconstruction error based on the model to solve the problem that abnormal information is easy to be overwhelmed. Further considering the fault characteristics such as micro-offset and oscillation, a multi-block modeling strategy is adopted to calculate statistics for each sub-block and merge the detection. Through a numerical example and Tennessee-Eastman (Tennessee-Eastman, TE) process simulation and analysis, the results verify the effectiveness of the proposed method and the improvement of monitoring performance.

Recommended Citation

Zheng, Jing; Xiong, Weili; and Wu, Xiaodong (2023) "kNN Fault Detection Based on Reconstruction Error and Multi-block Modeling Strategy," Journal of System Simulation: Vol. 35: Iss. 1, Article 8.
DOI: 10.16182/j.issn1004731x.joss.21-0689
Available at: https://dc-china-simulation.researchcommons.org/journal/vol35/iss1/8

First Page

95

Revised Date

2021-10-02

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.21-0689

Last Page

109

CLC

TP 277

Recommended Citation

Jing Zheng, Weili Xiong, Xiaodong Wu. kNN Fault Detection Based on Reconstruction Error and Multi-block Modeling Strategy[J]. Journal of System Simulation, 2023, 35(1): 95-109.

Corresponding Author

Weili Xiong,greenpre@163.com

DOI

10.16182/j.issn1004731x.joss.21-0689