Least Squares and Contribution Plot Based Approach for Quality-Related Process Monitoring | Zendy

Guang Wang | Zendy; Jianduo Li | Zendy; Chengyuan Sun | Zendy; Jianfang Jiao | Zendy

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Least Squares and Contribution Plot Based Approach for Quality-Related Process Monitoring

Author(s) -

Guang Wang,

Jianduo Li,

Chengyuan Sun,

Jianfang Jiao

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2871455

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

In this paper, a new contribution plots approach based on least squares is proposed to realize fault detection and diagnosis for quality-related sensor faults in industrial processes. The proposed approach can achieve the quality-related fault detection and diagnosis simultaneously using an indicator of contribution plots. The process variables are decomposed into two orthogonal subspaces, which are quality-related and quality-unrelated. Then, the variable contributions to statistics are calculated in each subspace, and quality-related fault detection and diagnostics are achieved by analyzing the contribution plots of all variables. Finally, the validity of the fault diagnosis method proposed in this paper is verified by simulation analysis of the Tennessee-Eastman process.

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