Intermittent fault detection in nonstationary processes via a Wald‐based control chart

Summary In this article, the problem of intermittent fault (IF) detection is investigated for nonstationary processes in the multivariate statistics framework. By combining the moving window technique with maximum likelihood estimation (MLE), the moving window Wald‐based control chart is proposed to...

Full description

Saved in:
Bibliographic Details
Published in:International journal of adaptive control and signal processing 2024-09, Vol.38 (9), p.2952-2971
Main Authors: Liu, Yifan, Zhao, Yinghong, Gao, Ming, Sheng, Li
Format: Article
Language:English
Subjects:
Control charts
fault detectability
Fault detection
intermittent fault
Iterative algorithms
Maximum likelihood estimation
nonstationary processes
Simulated annealing
Wald test
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites cdi_FETCH-LOGICAL-c1842-32b4709bbcb45d1b83a1d5fed00f9625ec1f89794f220224b1b23c1865437db3
container_end_page 2971
container_issue 9
container_start_page 2952
container_title International journal of adaptive control and signal processing
container_volume 38
creator Liu, Yifan
Zhao, Yinghong
Gao, Ming
Sheng, Li
description Summary In this article, the problem of intermittent fault (IF) detection is investigated for nonstationary processes in the multivariate statistics framework. By combining the moving window technique with maximum likelihood estimation (MLE), the moving window Wald‐based control chart is proposed to realize the detection of IFs in nonstationary processes. The computational efficiency and the convergence properties are discussed for the designed iterative algorithm of MLE. Then, necessary and sufficient conditions are presented to guarantee the detectability of IFs with the consideration of window lengths. Moreover, the alarm delays are analyzed for the appearance and disappearance of IFs. In virtue of the above analysis, the optimal window length is derived by minimizing the supremum of alarm delays. In order to estimate the time of IFs' appearance and disappearance, an algorithm is designed with the inspiration of simulated annealing strategy. Finally, a simulation on rotary steerable drilling tool system is provided to verify the effectiveness of the proposed method.
doi_str_mv 10.1002/acs.3852
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_3099329720</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3099329720</sourcerecordid><originalsourceid>FETCH-LOGICAL-c1842-32b4709bbcb45d1b83a1d5fed00f9625ec1f89794f220224b1b23c1865437db3</originalsourceid><addsrcrecordid>eNp1kM9KAzEQxoMoWKvgIwS8eNk6SXa7m2Mp_ikUPFjQW0iyCW7ZJjXJKr35CD6jT2JqvXoahvnNzPd9CF0SmBAAeiN1nLCmokdoRIDzghBSHaMRNByKKaP1KTqLcQ2QZ4SN0MvCJRM2XUrGJWzl0CfcmmR06rzDncPOu5jkvpNhh7fBaxOjifi9k1jiZ9m3359fSkbTYu1dCr7H-lWGdI5OrOyjufirY7S6u13NH4rl4_1iPlsWmjQlLRhVZQ1cKa3KqiWqYZK0lTUtgOVTWhlNbMNrXlpKgdJSEUVZXp1WJatbxcbo6nA2K3sbTExi7Yfg8kfBskVGeU0hU9cHSgcfYzBWbEO3yYYEAbGPTeTYxD62jBYH9KPrze5fTszmT7_8D-HRb2Q</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3099329720</pqid></control><display><type>article</type><title>Intermittent fault detection in nonstationary processes via a Wald‐based control chart</title><source>Wiley-Blackwell Read &amp; Publish Collection</source><creator>Liu, Yifan ; Zhao, Yinghong ; Gao, Ming ; Sheng, Li</creator><creatorcontrib>Liu, Yifan ; Zhao, Yinghong ; Gao, Ming ; Sheng, Li</creatorcontrib><description>Summary In this article, the problem of intermittent fault (IF) detection is investigated for nonstationary processes in the multivariate statistics framework. By combining the moving window technique with maximum likelihood estimation (MLE), the moving window Wald‐based control chart is proposed to realize the detection of IFs in nonstationary processes. The computational efficiency and the convergence properties are discussed for the designed iterative algorithm of MLE. Then, necessary and sufficient conditions are presented to guarantee the detectability of IFs with the consideration of window lengths. Moreover, the alarm delays are analyzed for the appearance and disappearance of IFs. In virtue of the above analysis, the optimal window length is derived by minimizing the supremum of alarm delays. In order to estimate the time of IFs' appearance and disappearance, an algorithm is designed with the inspiration of simulated annealing strategy. Finally, a simulation on rotary steerable drilling tool system is provided to verify the effectiveness of the proposed method.</description><identifier>ISSN: 0890-6327</identifier><identifier>EISSN: 1099-1115</identifier><identifier>DOI: 10.1002/acs.3852</identifier><language>eng</language><publisher>Bognor Regis: Wiley Subscription Services, Inc</publisher><subject>Control charts ; fault detectability ; Fault detection ; intermittent fault ; Iterative algorithms ; Maximum likelihood estimation ; nonstationary processes ; Simulated annealing ; Wald test</subject><ispartof>International journal of adaptive control and signal processing, 2024-09, Vol.38 (9), p.2952-2971</ispartof><rights>2024 John Wiley &amp; Sons Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c1842-32b4709bbcb45d1b83a1d5fed00f9625ec1f89794f220224b1b23c1865437db3</cites><orcidid>0000-0003-2940-209X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Liu, Yifan</creatorcontrib><creatorcontrib>Zhao, Yinghong</creatorcontrib><creatorcontrib>Gao, Ming</creatorcontrib><creatorcontrib>Sheng, Li</creatorcontrib><title>Intermittent fault detection in nonstationary processes via a Wald‐based control chart</title><title>International journal of adaptive control and signal processing</title><description>Summary In this article, the problem of intermittent fault (IF) detection is investigated for nonstationary processes in the multivariate statistics framework. By combining the moving window technique with maximum likelihood estimation (MLE), the moving window Wald‐based control chart is proposed to realize the detection of IFs in nonstationary processes. The computational efficiency and the convergence properties are discussed for the designed iterative algorithm of MLE. Then, necessary and sufficient conditions are presented to guarantee the detectability of IFs with the consideration of window lengths. Moreover, the alarm delays are analyzed for the appearance and disappearance of IFs. In virtue of the above analysis, the optimal window length is derived by minimizing the supremum of alarm delays. In order to estimate the time of IFs' appearance and disappearance, an algorithm is designed with the inspiration of simulated annealing strategy. Finally, a simulation on rotary steerable drilling tool system is provided to verify the effectiveness of the proposed method.</description><subject>Control charts</subject><subject>fault detectability</subject><subject>Fault detection</subject><subject>intermittent fault</subject><subject>Iterative algorithms</subject><subject>Maximum likelihood estimation</subject><subject>nonstationary processes</subject><subject>Simulated annealing</subject><subject>Wald test</subject><issn>0890-6327</issn><issn>1099-1115</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp1kM9KAzEQxoMoWKvgIwS8eNk6SXa7m2Mp_ikUPFjQW0iyCW7ZJjXJKr35CD6jT2JqvXoahvnNzPd9CF0SmBAAeiN1nLCmokdoRIDzghBSHaMRNByKKaP1KTqLcQ2QZ4SN0MvCJRM2XUrGJWzl0CfcmmR06rzDncPOu5jkvpNhh7fBaxOjifi9k1jiZ9m3359fSkbTYu1dCr7H-lWGdI5OrOyjufirY7S6u13NH4rl4_1iPlsWmjQlLRhVZQ1cKa3KqiWqYZK0lTUtgOVTWhlNbMNrXlpKgdJSEUVZXp1WJatbxcbo6nA2K3sbTExi7Yfg8kfBskVGeU0hU9cHSgcfYzBWbEO3yYYEAbGPTeTYxD62jBYH9KPrze5fTszmT7_8D-HRb2Q</recordid><startdate>202409</startdate><enddate>202409</enddate><creator>Liu, Yifan</creator><creator>Zhao, Yinghong</creator><creator>Gao, Ming</creator><creator>Sheng, Li</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0003-2940-209X</orcidid></search><sort><creationdate>202409</creationdate><title>Intermittent fault detection in nonstationary processes via a Wald‐based control chart</title><author>Liu, Yifan ; Zhao, Yinghong ; Gao, Ming ; Sheng, Li</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1842-32b4709bbcb45d1b83a1d5fed00f9625ec1f89794f220224b1b23c1865437db3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Control charts</topic><topic>fault detectability</topic><topic>Fault detection</topic><topic>intermittent fault</topic><topic>Iterative algorithms</topic><topic>Maximum likelihood estimation</topic><topic>nonstationary processes</topic><topic>Simulated annealing</topic><topic>Wald test</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Yifan</creatorcontrib><creatorcontrib>Zhao, Yinghong</creatorcontrib><creatorcontrib>Gao, Ming</creatorcontrib><creatorcontrib>Sheng, Li</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>International journal of adaptive control and signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Yifan</au><au>Zhao, Yinghong</au><au>Gao, Ming</au><au>Sheng, Li</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Intermittent fault detection in nonstationary processes via a Wald‐based control chart</atitle><jtitle>International journal of adaptive control and signal processing</jtitle><date>2024-09</date><risdate>2024</risdate><volume>38</volume><issue>9</issue><spage>2952</spage><epage>2971</epage><pages>2952-2971</pages><issn>0890-6327</issn><eissn>1099-1115</eissn><abstract>Summary In this article, the problem of intermittent fault (IF) detection is investigated for nonstationary processes in the multivariate statistics framework. By combining the moving window technique with maximum likelihood estimation (MLE), the moving window Wald‐based control chart is proposed to realize the detection of IFs in nonstationary processes. The computational efficiency and the convergence properties are discussed for the designed iterative algorithm of MLE. Then, necessary and sufficient conditions are presented to guarantee the detectability of IFs with the consideration of window lengths. Moreover, the alarm delays are analyzed for the appearance and disappearance of IFs. In virtue of the above analysis, the optimal window length is derived by minimizing the supremum of alarm delays. In order to estimate the time of IFs' appearance and disappearance, an algorithm is designed with the inspiration of simulated annealing strategy. Finally, a simulation on rotary steerable drilling tool system is provided to verify the effectiveness of the proposed method.</abstract><cop>Bognor Regis</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/acs.3852</doi><tpages>20</tpages><orcidid>https://orcid.org/0000-0003-2940-209X</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 0890-6327
ispartof International journal of adaptive control and signal processing, 2024-09, Vol.38 (9), p.2952-2971
issn 0890-6327
1099-1115
language eng
recordid cdi_proquest_journals_3099329720
source Wiley-Blackwell Read & Publish Collection
subjects Control charts
fault detectability
Fault detection
intermittent fault
Iterative algorithms
Maximum likelihood estimation
nonstationary processes
Simulated annealing
Wald test
title Intermittent fault detection in nonstationary processes via a Wald‐based control chart
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-29T18%3A41%3A03IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Intermittent%20fault%20detection%20in%20nonstationary%20processes%20via%20a%20Wald%E2%80%90based%20control%20chart&rft.jtitle=International%20journal%20of%20adaptive%20control%20and%20signal%20processing&rft.au=Liu,%20Yifan&rft.date=2024-09&rft.volume=38&rft.issue=9&rft.spage=2952&rft.epage=2971&rft.pages=2952-2971&rft.issn=0890-6327&rft.eissn=1099-1115&rft_id=info:doi/10.1002/acs.3852&rft_dat=%3Cproquest_cross%3E3099329720%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c1842-32b4709bbcb45d1b83a1d5fed00f9625ec1f89794f220224b1b23c1865437db3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=3099329720&rft_id=info:pmid/&rfr_iscdi=true