Fault detection strategy based on density standard error associated with locality preserving projections

被引：2
|
作者：
Zhang C. [1 ]
Guo Q.-X. [1 ]
Feng L.-W. [1 ]
Li Y. [1 ]
机构：
[1] Research Center for Technical Process Fault Diagnosis and Safety, Shenyang University of Chemical Technology, Shenyang, 110142, Liaoning
来源：
Li, Yuan (li-yuan@mail.tsinghua.edu.cn) | 1757年 / South China University of Technology卷 / 37期
基金：
中国国家自然科学基金;
关键词：
Fault detection; K nearest neighbor; Locality preserving projections; Multimodal process; Principal component analysis;
D O I：
10.7641/CTA.2020.90406
中图分类号：
学科分类号：
摘要：
Aiming at the fault detection of multimodal processes with significant variation in covariance of each mode, a fault detection strategy based on density standard error associated with locality preserving projections (LPP-DSE) is proposed in this paper. Firstly, calculate the cutoff distance according to sample distance matrix. Secondly, calculate respectively the intrinsic density and the estimated density of a sample through cutoff distance. Finally, build a new statistic to accomplish process monitoring. In LPP-DSE, the timeliness of process monitoring is guaranteed by using locality preserving projections (LPP); meanwhile, the fault detection rate of a multimode process is improved through using density standard error (DSE) statistic. Moreover, the proposed fault diagnosis method based on contribution chart is able to identify accurately the abnormal variables. Compared with principal component analysis, neighborhood preserving embedding, LPP, k nearest neighbor rule and other methods, the effectiveness of LPP-DSE is verified by a numerical case and semiconductor etching process. © 2020, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.
引用
收藏
页码：1757 / 1765
页数：8
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