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

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 indicato...
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Autor*in:	Guang Wang [verfasserIn] Jianduo Li [verfasserIn] Chengyuan Sun [verfasserIn] Jianfang Jiao [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	Fault diagnosis fault detection contribution plot least squares

Übergeordnetes Werk:	In: IEEE Access - IEEE, 2014, 6(2018), Seite 54158-54166
Übergeordnetes Werk:	volume:6 ; year:2018 ; pages:54158-54166

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/ACCESS.2018.2871455

Katalog-ID:	DOAJ047748419

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allfields	10.1109/ACCESS.2018.2871455 doi (DE-627)DOAJ047748419 (DE-599)DOAJd79aa3fb0591448fbe90d51fe614e28a DE-627 ger DE-627 rakwb eng TK1-9971 Guang Wang verfasserin aut Least Squares and Contribution Plot Based Approach for Quality-Related Process Monitoring 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Fault diagnosis fault detection contribution plot least squares Electrical engineering. Electronics. Nuclear engineering Jianduo Li verfasserin aut Chengyuan Sun verfasserin aut Jianfang Jiao verfasserin aut In IEEE Access IEEE, 2014 6(2018), Seite 54158-54166 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:6 year:2018 pages:54158-54166 https://doi.org/10.1109/ACCESS.2018.2871455 kostenfrei https://doaj.org/article/d79aa3fb0591448fbe90d51fe614e28a kostenfrei https://ieeexplore.ieee.org/document/8468961/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2018 54158-54166
spelling	10.1109/ACCESS.2018.2871455 doi (DE-627)DOAJ047748419 (DE-599)DOAJd79aa3fb0591448fbe90d51fe614e28a DE-627 ger DE-627 rakwb eng TK1-9971 Guang Wang verfasserin aut Least Squares and Contribution Plot Based Approach for Quality-Related Process Monitoring 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Fault diagnosis fault detection contribution plot least squares Electrical engineering. Electronics. Nuclear engineering Jianduo Li verfasserin aut Chengyuan Sun verfasserin aut Jianfang Jiao verfasserin aut In IEEE Access IEEE, 2014 6(2018), Seite 54158-54166 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:6 year:2018 pages:54158-54166 https://doi.org/10.1109/ACCESS.2018.2871455 kostenfrei https://doaj.org/article/d79aa3fb0591448fbe90d51fe614e28a kostenfrei https://ieeexplore.ieee.org/document/8468961/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2018 54158-54166
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allfieldsSound	10.1109/ACCESS.2018.2871455 doi (DE-627)DOAJ047748419 (DE-599)DOAJd79aa3fb0591448fbe90d51fe614e28a DE-627 ger DE-627 rakwb eng TK1-9971 Guang Wang verfasserin aut Least Squares and Contribution Plot Based Approach for Quality-Related Process Monitoring 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Fault diagnosis fault detection contribution plot least squares Electrical engineering. Electronics. Nuclear engineering Jianduo Li verfasserin aut Chengyuan Sun verfasserin aut Jianfang Jiao verfasserin aut In IEEE Access IEEE, 2014 6(2018), Seite 54158-54166 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:6 year:2018 pages:54158-54166 https://doi.org/10.1109/ACCESS.2018.2871455 kostenfrei https://doaj.org/article/d79aa3fb0591448fbe90d51fe614e28a kostenfrei https://ieeexplore.ieee.org/document/8468961/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2018 54158-54166
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topic_facet	Fault diagnosis fault detection contribution plot least squares Electrical engineering. Electronics. Nuclear engineering
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authorswithroles_txt_mv	Guang Wang @@aut@@ Jianduo Li @@aut@@ Chengyuan Sun @@aut@@ Jianfang Jiao @@aut@@
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callnumber-first	T - Technology
author	Guang Wang
spellingShingle	Guang Wang misc TK1-9971 misc Fault diagnosis misc fault detection misc contribution plot misc least squares misc Electrical engineering. Electronics. Nuclear engineering Least Squares and Contribution Plot Based Approach for Quality-Related Process Monitoring
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topic_title	TK1-9971 Least Squares and Contribution Plot Based Approach for Quality-Related Process Monitoring Fault diagnosis fault detection contribution plot least squares
topic	misc TK1-9971 misc Fault diagnosis misc fault detection misc contribution plot misc least squares misc Electrical engineering. Electronics. Nuclear engineering
topic_unstemmed	misc TK1-9971 misc Fault diagnosis misc fault detection misc contribution plot misc least squares misc Electrical engineering. Electronics. Nuclear engineering
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title	Least Squares and Contribution Plot Based Approach for Quality-Related Process Monitoring
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title_full	Least Squares and Contribution Plot Based Approach for Quality-Related Process Monitoring
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title_sort	least squares and contribution plot based approach for quality-related process monitoring
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title_auth	Least Squares and Contribution Plot Based Approach for Quality-Related Process Monitoring
abstract	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.
abstractGer	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.
abstract_unstemmed	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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title_short	Least Squares and Contribution Plot Based Approach for Quality-Related Process Monitoring
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