Diagnosis and Prognosis of Degradation Process via Hidden Semi-Markov Model

The intelligent estimation of degradation state and the prediction of remaining useful life (RUL) are important for the maintenance of industrial equipment. In this study, the degradation process of equipment is modeled as an improved hidden semi-Markov model (HSMM), in which the dependence of durat...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE/ASME transactions on mechatronics Jg. 23; H. 3; S. 1456 - 1466
Hauptverfasser:	Liu, Tongshun, Zhu, Kunpeng, Zeng, Liangcai
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 01.06.2018
Schlagworte:	Degradation Degradation process Estimation Feature extraction Filtering forward–backward algorithm health monitoring Hidden Markov models Hidden semi-Markov Monitoring remaining useful life (RUL)
ISSN:	1083-4435, 1941-014X
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Abstract	The intelligent estimation of degradation state and the prediction of remaining useful life (RUL) are important for the maintenance of industrial equipment. In this study, the degradation process of equipment is modeled as an improved hidden semi-Markov model (HSMM), in which the dependence of durations of adjacent degradation states is described and modeled in the HSMM. To avoid underflow problem in computing the forward and backward variables, a modified forward-backward algorithm is proposed in the HSMM. Based on the improved algorithm, online estimation of degradation state and the distribution of RUL can be obtained. Case studies on tool wearing diagnosis and prognosis have verified the effectiveness of this model.
AbstractList	The intelligent estimation of degradation state and the prediction of remaining useful life (RUL) are important for the maintenance of industrial equipment. In this study, the degradation process of equipment is modeled as an improved hidden semi-Markov model (HSMM), in which the dependence of durations of adjacent degradation states is described and modeled in the HSMM. To avoid underflow problem in computing the forward and backward variables, a modified forward-backward algorithm is proposed in the HSMM. Based on the improved algorithm, online estimation of degradation state and the distribution of RUL can be obtained. Case studies on tool wearing diagnosis and prognosis have verified the effectiveness of this model.
Author	Zhu, Kunpeng Liu, Tongshun Zeng, Liangcai
Author_xml	– sequence: 1 givenname: Tongshun surname: Liu fullname: Liu, Tongshun email: zkdlts@mail.ustc.edu.cn organization: Department of Automation, University of Science and Technology of China, Hefei, China – sequence: 2 givenname: Kunpeng surname: Zhu fullname: Zhu, Kunpeng email: kunpengz@hotmail.com organization: Institute of Advanced Manufacturing Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Changzhou, China – sequence: 3 givenname: Liangcai orcidid: 0000-0003-0702-0162 surname: Zeng fullname: Zeng, Liangcai email: zengliangcai@wust.edu.cn organization: School of Machinery and Automation, Wuhan University of Science and Technology, Wuhan, China
BookMark	eNp9kM9KAzEQh4NUsK2-gF7yAlsnM9nd9ChtdcUWBSt4W9JNtkTbjSRLwbd3-wcPHjzN_Gb4huEbsF7jG8vYtYCREDC-XS5mk2KEINQIFRIhnLG-GEuRgJDvva4HRYmUlF6wQYwfACAFiD57mjq9bnx0kevG8JfgT8nXfGrXQRvdOt_sF5WNke-c5oUzxjb81W5dstDh0-_4whu7uWTntd5Ee3WqQ_Z2P1tOimT-_PA4uZsnFWZ5m6yAMiOkAlT5WEmkVGZdqiFNBdZIWlegFWg0kpBUneXUzVdS5bZCqZGGTB3vVsHHGGxdVq49vNkG7TalgHIvpTxIKfdSypOUDsU_6FdwWx2-_4dujpCz1v4CikioDOkHXp9t6A
CODEN	IATEFW
CitedBy_id	crossref_primary_10_1109_TIE_2021_3135520 crossref_primary_10_1016_j_ymssp_2025_113042 crossref_primary_10_1109_TIM_2021_3086881 crossref_primary_10_1007_s00158_022_03425_4 crossref_primary_10_1016_j_ymssp_2021_107714 crossref_primary_10_1080_09617353_2022_2051140 crossref_primary_10_1109_TMECH_2022_3144351 crossref_primary_10_1088_1361_6501_acf876 crossref_primary_10_1007_s11831_020_09422_4 crossref_primary_10_3390_s24134117 crossref_primary_10_1002_nav_21947 crossref_primary_10_1016_j_eswa_2022_117758 crossref_primary_10_1109_TMECH_2020_2995757 crossref_primary_10_1016_j_ymssp_2019_06_021 crossref_primary_10_1016_j_apm_2021_10_015 crossref_primary_10_1109_TMECH_2023_3311435 crossref_primary_10_1177_1748006X241238582 crossref_primary_10_33693_2313_223X_2025_12_1_34_47 crossref_primary_10_3390_e24030402 crossref_primary_10_1007_s10845_022_01973_6 crossref_primary_10_1016_j_ymssp_2025_113015 crossref_primary_10_1109_ACCESS_2023_3285722 crossref_primary_10_1016_j_ress_2025_111286 crossref_primary_10_1109_ACCESS_2023_3267960 crossref_primary_10_1016_j_cie_2023_109433 crossref_primary_10_1007_s00170_021_08047_6 crossref_primary_10_1016_j_isatra_2023_12_031 crossref_primary_10_1177_1748006X21990527 crossref_primary_10_1088_1361_6501_ad4fb1 crossref_primary_10_1109_TII_2020_3004445 crossref_primary_10_1186_s10033_021_00576_1 crossref_primary_10_1016_j_jmsy_2023_11_003 crossref_primary_10_3390_su142416810 crossref_primary_10_1155_2019_8716979 crossref_primary_10_1080_0951192X_2019_1686174 crossref_primary_10_1007_s00170_022_10778_z crossref_primary_10_1016_j_ress_2022_108568 crossref_primary_10_1109_TR_2019_2930195 crossref_primary_10_1007_s00170_020_06272_z crossref_primary_10_1109_TIM_2023_3251391 crossref_primary_10_1016_j_ress_2022_108322 crossref_primary_10_1016_j_energy_2022_126279 crossref_primary_10_1016_j_ymssp_2023_110691 crossref_primary_10_1109_TIM_2023_3256469 crossref_primary_10_1002_qre_70064 crossref_primary_10_1109_TITS_2021_3052801
Cites_doi	10.1016/j.arcontrol.2004.12.002 10.1109/TII.2012.2205583 10.1109/TII.2016.2535368 10.1109/TIE.2010.2098369 10.1109/TIE.2015.2396877 10.1016/j.ymssp.2010.04.002 10.1007/978-1-4757-3437-9_1 10.1115/1.4001247 10.1115/1.4026841 10.1109/TIM.2010.2050974 10.1016/j.artint.2009.11.011 10.1109/TIE.2015.2464297 10.1016/j.ymssp.2008.04.010 10.1109/TMECH.2007.902131 10.1016/j.ymssp.2015.03.029 10.1109/TASE.2009.2038170 10.1016/j.ymssp.2012.08.016 10.1109/5326.897073 10.1109/TIE.2015.2392713 10.1155/2014/632702 10.1109/TSP.2006.872540 10.1109/TMECH.2009.2016956 10.1109/ICPHM.2011.6024333 10.1016/j.ejor.2010.11.018 10.1080/00207540412331327727 10.1109/TPAMI.2003.1159947 10.1109/TII.2015.2500098 10.1016/j.mechatronics.2015.05.009 10.1109/TIE.2016.2535111 10.1109/TAC.2009.2039548 10.1109/TIE.2013.2274422 10.1109/TR.2012.2194177 10.1109/TMECH.2015.2440331 10.1109/TIE.2014.2308133 10.1016/j.precisioneng.2013.06.006 10.1109/TDEI.2010.5595566 10.1016/j.cirp.2010.05.010 10.1115/1.1475320 10.1016/j.ymssp.2006.12.007 10.1109/TMECH.2014.2322652 10.1016/j.patrec.2009.09.011 10.1109/TIE.2015.2455055
ContentType	Journal Article
DBID	97E RIA RIE AAYXX CITATION
DOI	10.1109/TMECH.2018.2823320
DatabaseName	IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef
DatabaseTitle	CrossRef
DatabaseTitleList
Database_xml	– sequence: 1 dbid: RIE name: IEL url: https://ieeexplore.ieee.org/ sourceTypes: Publisher
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering
EISSN	1941-014X
EndPage	1466
ExternalDocumentID	10_1109_TMECH_2018_2823320 8331862
Genre	orig-research
GrantInformation_xml	– fundername: Chinese Academy of Sciences, and in part by the National Natural Science Foundation of China grantid: 51475443
GroupedDBID	-~X 0R~ 29I 4.4 5GY 5VS 6IK 97E 9M8 AAJGR AARMG AASAJ AAWTH ABAZT ABQJQ ABVLG ACGFS ACIWK ACKIV AETIX AGQYO AGSQL AHBIQ AI. AIBXA AKJIK AKQYR ALLEH ALMA_UNASSIGNED_HOLDINGS ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 EBS EJD F5P H~9 IFIPE IFJZH IPLJI JAVBF LAI M43 OCL RIA RIE RNS TN5 VH1 AAYXX CITATION
ID	FETCH-LOGICAL-c267t-b036d148028798423546480f05512f23aac0a80a2d43238f67312fb487ec24a23
IEDL.DBID	RIE
ISICitedReferencesCount	51
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000435338300045&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	1083-4435
IngestDate	Tue Nov 18 22:36:04 EST 2025 Sat Nov 29 06:33:06 EST 2025 Wed Aug 27 02:50:51 EDT 2025
IsPeerReviewed	true
IsScholarly	true
Issue	3
Language	English
License	https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c267t-b036d148028798423546480f05512f23aac0a80a2d43238f67312fb487ec24a23
ORCID	0000-0003-0702-0162
PageCount	11
ParticipantIDs	crossref_citationtrail_10_1109_TMECH_2018_2823320 ieee_primary_8331862 crossref_primary_10_1109_TMECH_2018_2823320
PublicationCentury	2000
PublicationDate	2018-June 2018-6-00
PublicationDateYYYYMMDD	2018-06-01
PublicationDate_xml	– month: 06 year: 2018 text: 2018-June
PublicationDecade	2010
PublicationTitle	IEEE/ASME transactions on mechatronics
PublicationTitleAbbrev	TMECH
PublicationYear	2018
Publisher	IEEE
Publisher_xml	– name: IEEE
References	wu (ref35) 0 ref13 ref34 ref12 braglia (ref6) 2014; 136 ref37 ref15 ref36 ref14 ref31 ref30 ref33 ref32 ref10 ref2 mallat (ref43) 1998 ref1 ref17 ref38 ref16 ref19 ref18 ref24 ref45 ref23 ref26 ref25 ref20 ref42 ref41 ref22 ref44 ref21 ref28 ref27 ref29 ref8 ref7 ref9 ref4 ref3 ref5 ref40 gersho (ref39) 2012 van (ref11) 2016; 12
References_xml	– ident: ref3 doi: 10.1016/j.arcontrol.2004.12.002 – ident: ref26 doi: 10.1109/TII.2012.2205583 – ident: ref17 doi: 10.1109/TII.2016.2535368 – ident: ref24 doi: 10.1109/TIE.2010.2098369 – ident: ref25 doi: 10.1109/TIE.2015.2396877 – ident: ref36 doi: 10.1016/j.ymssp.2010.04.002 – ident: ref42 doi: 10.1007/978-1-4757-3437-9_1 – ident: ref20 doi: 10.1115/1.4001247 – volume: 136 year: 2014 ident: ref6 article-title: Diffusion theory applied to tool-life stochastic modeling under a progressive wear process publication-title: J Manuf Sci Eng doi: 10.1115/1.4026841 – ident: ref13 doi: 10.1109/TIM.2010.2050974 – ident: ref38 doi: 10.1016/j.artint.2009.11.011 – ident: ref12 doi: 10.1109/TIE.2015.2464297 – ident: ref31 doi: 10.1016/j.ymssp.2008.04.010 – ident: ref2 doi: 10.1109/TMECH.2007.902131 – ident: ref32 doi: 10.1016/j.ymssp.2015.03.029 – ident: ref30 doi: 10.1109/TASE.2009.2038170 – ident: ref5 doi: 10.1016/j.ymssp.2012.08.016 – ident: ref29 doi: 10.1109/5326.897073 – ident: ref10 doi: 10.1109/TIE.2015.2392713 – ident: ref37 doi: 10.1155/2014/632702 – ident: ref40 doi: 10.1109/TSP.2006.872540 – ident: ref9 doi: 10.1109/TMECH.2009.2016956 – ident: ref34 doi: 10.1109/ICPHM.2011.6024333 – ident: ref41 doi: 10.1016/j.ejor.2010.11.018 – ident: ref21 doi: 10.1080/00207540412331327727 – ident: ref22 doi: 10.1109/TPAMI.2003.1159947 – volume: 12 start-page: 124 year: 2016 ident: ref11 article-title: Bearing defect classification based on individual wavelet local fisher discriminant analysis with particle swarm optimization publication-title: IEEE Trans Ind Informat doi: 10.1109/TII.2015.2500098 – ident: ref7 doi: 10.1016/j.mechatronics.2015.05.009 – ident: ref18 doi: 10.1109/TIE.2016.2535111 – ident: ref19 doi: 10.1109/TAC.2009.2039548 – ident: ref27 doi: 10.1109/TIE.2013.2274422 – year: 1998 ident: ref43 publication-title: A Wavelet Tour of Signal Processing – ident: ref33 doi: 10.1109/TR.2012.2194177 – ident: ref16 doi: 10.1109/TMECH.2015.2440331 – ident: ref4 doi: 10.1109/TIE.2014.2308133 – year: 2012 ident: ref39 publication-title: Vector Quantization and Signal Compression – ident: ref45 doi: 10.1016/j.precisioneng.2013.06.006 – start-page: 1408 year: 0 ident: ref35 article-title: Integrated prognosis of AC servo motor driven linear actuator using hidden semi-Markov models publication-title: Proc IEEE Int Conf Elect Mach Drives – ident: ref28 doi: 10.1109/TDEI.2010.5595566 – ident: ref1 doi: 10.1016/j.cirp.2010.05.010 – ident: ref23 doi: 10.1115/1.1475320 – ident: ref14 doi: 10.1016/j.ymssp.2006.12.007 – ident: ref15 doi: 10.1109/TMECH.2014.2322652 – ident: ref44 doi: 10.1016/j.patrec.2009.09.011 – ident: ref8 doi: 10.1109/TIE.2015.2455055
SSID	ssj0004101
Score	2.4396968
Snippet	The intelligent estimation of degradation state and the prediction of remaining useful life (RUL) are important for the maintenance of industrial equipment. In...
SourceID	crossref ieee
SourceType	Enrichment Source Index Database Publisher
StartPage	1456
SubjectTerms	Degradation Degradation process Estimation Feature extraction Filtering forward–backward algorithm health monitoring Hidden Markov models Hidden semi-Markov Monitoring remaining useful life (RUL)
Title	Diagnosis and Prognosis of Degradation Process via Hidden Semi-Markov Model
URI	https://ieeexplore.ieee.org/document/8331862
Volume	23
WOSCitedRecordID	wos000435338300045&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVIEE databaseName: IEL customDbUrl: eissn: 1941-014X dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0004101 issn: 1083-4435 databaseCode: RIE dateStart: 19960101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1bS8MwFA5z-KAP3qY4b-TBN83WJlnSPsouDNQxcMreymmaQmG2stvvN0m7uQcRfGtLQsuX0HNOe77vQ-ieCw4gRUqopoJwiBMSmqhMWCwhBCaEdE00Hy9yNAqm03BcQ49bLozW2jWf6ZY9dP_yk0Kt7KeydsDMDrQv3D0pZcnV-uFA-s7q2DcpBeHmbhuCjBe2J6_97tB2cQUtU2AwZr29d4LQjquKCyqD4_89zgk6qpJH_FSu9imq6fwMHe5ICjbQc6_sncsWGPIEj-dFdVakuGeFIUoPJVwRBPA6Azy0MiI5ftOfGbHcnWKNrUXa7By9D_qT7pBUhglEUSGXJDbhKDH1jckZZBiYRKljliLwUs-kRTSlDEB5EHhAE85MqE6FZOZ6bGoWrSgHyi5QPS9yfYlwR_BYSx9UElMeAw0FcK1TbXWMEwlBE_kbBCNVqYlbU4tZ5KoKL4wc6pFFPapQb6KH7ZyvUkvjz9ENC_l2ZIX21e-Xr9GBnVw2cd2g-nK-0rdoX62X2WJ-57bKNydquQ8
linkProvider	IEEE
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1bS8MwFD6MKagP3qY4r3nwTbO1SZa0j7ILlV0YOGVvJW1TKMxWdvv9Jm039yCCb21JL3wJPee05_s-gEfGmZSCx5gowjGTQYRdHZUxDYR0JeVc5E00HwMxGjnTqTuuwPOWC6OUypvPVMNs5v_yoyxcmU9lTYfqFWheuHstxohdsLV-WJB2bnZs66QCM32_DUXGcpuTYbftmT4up6FLDEqNu_dOGNrxVcnDSu_kfw90Csdl-oheivk-g4pKz-FoR1SwBv1O0T2XLJBMIzSeZ-VeFqOOkYYoXJRQSRFA60QizwiJpOhNfSbYsHeyNTImabMLeO91J20Pl5YJOCRcLHGgA1KkKxydNQjX0alSS0-GY8WWToxITKiUoSUdS5KIUR2sYy6oPh7oqkWFhElCL6GaZqm6AtTiLFDClmEUEBZI4nLJlIqVUTKOhHTqYG8Q9MNST9zYWsz8vK6wXD9H3Teo-yXqdXjanvNVqGn8ObpmIN-OLNG-_v3wAxx4k-HAH7yO-jdwaC5UtHTdQnU5X6k72A_Xy2Qxv8-XzTf3mLxW
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Diagnosis+and+Prognosis+of+Degradation+Process+via+Hidden+Semi-Markov+Model&rft.jtitle=IEEE%2FASME+transactions+on+mechatronics&rft.au=Liu%2C+Tongshun&rft.au=Zhu%2C+Kunpeng&rft.au=Zeng%2C+Liangcai&rft.date=2018-06-01&rft.pub=IEEE&rft.issn=1083-4435&rft.volume=23&rft.issue=3&rft.spage=1456&rft.epage=1466&rft_id=info:doi/10.1109%2FTMECH.2018.2823320&rft.externalDocID=8331862
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1083-4435&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1083-4435&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1083-4435&client=summon