Knowledge Commons of Institute of Automation,CAS
Sensitive Quality-Relevant Fault Monitoring using Enhanced Sparse Projection to Latent Structures | |
Bai, Xiwei1,2; Wang, Xuelei1; Tan, Jie1; Qin, Wei3; Zhang, Tianren4; Sun, Wei4 | |
2018 | |
会议名称 | 2018 13th World Congress on Intelligent Control and Automation |
会议日期 | July 4-8, 2018 |
会议地点 | Changsha, China |
摘要 | As one of the most common and effective quality-relevant fault monitoring techniques, projection to latent structures(PLS) and its improved algorithms have been wildly used in many industries to provide assurance for high-quality products. In this paper, a new enhanced sparse projection to latent structures(ESPLS) algorithm is proposed to achieve quality-relevant fault monitoring with better sensitivity. The algorithm implements sparse orthogonal decomposition on input process variable space. Two indices based on quality-relevant subspace and quality-irrelevant subspace with major variation are developed for fault detection and analysis. Experiments on Tennessee Eastman Process (TEP) chemical benchmark reveal its outstanding performance in fault detection and superior accuracy in differentiating the quality-relevant and irrelevant impact of the given fault. |
收录类别 | EI |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/39264 |
专题 | 中科院工业视觉智能装备工程实验室_工业智能技术与系统 |
通讯作者 | Tan, Jie |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences 3.Sinopec Zhongyuan Oilfield Puguang company gas production plant 4.Zhejiang Tianneng Energy Technology Co., Ltd. |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Bai, Xiwei,Wang, Xuelei,Tan, Jie,et al. Sensitive Quality-Relevant Fault Monitoring using Enhanced Sparse Projection to Latent Structures[C],2018. |
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