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Outlier detection for process control data based on a non-linear Auto-Regression Hidden Markov Model method
Liu, Fang; Mao, Zhizhong; Su WX(苏卫星)
Department信息服务与智能控制技术研究室
Source PublicationTRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
ISSN0142-3312
2012
Volume34Issue:5Pages:527-538
Indexed BySCI ; EI
EI Accession number20122415107343
WOS IDWOS:000304884400003
Contribution Rank2
Funding OrganizationGratitude is extended to the National High-Tech R&D Program of China, under Grant No. 2007AA04Z194 and No. 2007AA041401.
KeywordAuto-regression Hidden Markov Model Industrial Process Control Outlier Detection Radial Basis Function Network Time Series
AbstractThis paper focuses on the issue of outlier detection for time series in the process industry. Considering the characteristics of time series in process control systems, such as high non-linearity, strong noise and the special relationship between the input and output of the controlled object, a new outlier detection algorithm is proposed. The algorithm adopts an improved Radial Basis Function Network to construct the model of the controlled object and an Auto-Regression Hidden Markov Model to detect outliers. Unlike many conventional outlier detection methods, this algorithm does not need any prior data and can detect outliers accurately without preselecting the threshold. The proposed detection algorithm is validated by the application to the electrode regulator system of an arc furnace and comparison with Takeuchi's auto-regressive model detection approach.
Language英语
WOS HeadingsScience & Technology ; Technology
WOS SubjectAutomation & Control Systems ; Instruments & Instrumentation
WOS KeywordNOVELTY DETECTION ; RBF NETWORKS ; TIME-SERIES ; SELECTION
WOS Research AreaAutomation & Control Systems ; Instruments & Instrumentation
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Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/9970
Collection信息服务与智能控制技术研究室
Corresponding AuthorLiu, Fang
Affiliation1.Northeastern University, School of Information Science and Engineering, Shenyang, China
2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
Recommended Citation
GB/T 7714
Liu, Fang,Mao, Zhizhong,Su WX. Outlier detection for process control data based on a non-linear Auto-Regression Hidden Markov Model method[J]. TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL,2012,34(5):527-538.
APA Liu, Fang,Mao, Zhizhong,&Su WX.(2012).Outlier detection for process control data based on a non-linear Auto-Regression Hidden Markov Model method.TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL,34(5),527-538.
MLA Liu, Fang,et al."Outlier detection for process control data based on a non-linear Auto-Regression Hidden Markov Model method".TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 34.5(2012):527-538.
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