Degradation data analysis based on a generalized Wiener process subject to measurement error

[Display omitted] •A generalized Wiener process degradation model with measurement errors is proposed.•A simple method to determine the transformed time scale forms is presented.•The probability distribution function is derived based on the first hitting time.•Maximum likelihood estimation method is...

Full description

Saved in:

Bibliographic Details
Published in:	Mechanical systems and signal processing Vol. 94; pp. 57 - 72
Main Authors:	Li, Junxing, Wang, Zhihua, Zhang, Yongbo, Fu, Huimin, Liu, Chengrui, Krishnaswamy, Sridhar
Format:	Journal Article
Language:	English
Published:	Berlin Elsevier Ltd 15.09.2017 Elsevier BV
Subjects:	Computer simulation Correlation analysis Data analysis Degradation Degradation analysis Distribution functions Error analysis Maximum likelihood estimation Measurement errors Parameter estimation Performance degradation Probability distribution Probability distribution functions Resistors Time correlation functions Wear Wiener process Measurement errors Maximum likelihood estimation Wiener process Degradation analysis
ISSN:	0888-3270, 1096-1216
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	[Display omitted] •A generalized Wiener process degradation model with measurement errors is proposed.•A simple method to determine the transformed time scale forms is presented.•The probability distribution function is derived based on the first hitting time.•Maximum likelihood estimation method is used to estimate the unknown parameters.•Simulation and real examples are used to illustrate the efficiency of the model. Wiener processes have received considerable attention in degradation modeling over the last two decades. In this paper, we propose a generalized Wiener process degradation model that takes unit-to-unit variation, time-correlated structure and measurement error into considerations simultaneously. The constructed methodology subsumes a series of models studied in the literature as limiting cases. A simple method is given to determine the transformed time scale forms of the Wiener process degradation model. Then model parameters can be estimated based on a maximum likelihood estimation (MLE) method. The cumulative distribution function (CDF) and the probability distribution function (PDF) of the Wiener process with measurement errors are given based on the concept of the first hitting time (FHT). The percentiles of performance degradation (PD) and failure time distribution (FTD) are also obtained. Finally, a comprehensive simulation study is accomplished to demonstrate the necessity of incorporating measurement errors in the degradation model and the efficiency of the proposed model. Two illustrative real applications involving the degradation of carbon-film resistors and the wear of sliding metal are given. The comparative results show that the constructed approach can derive a reasonable result and an enhanced inference precision.
AbstractList	Wiener processes have received considerable attention in degradation modeling over the last two decades. In this paper, we propose a generalized Wiener process degradation model that takes unit-to-unit variation, time-correlated structure and measurement error into considerations simultaneously. The constructed methodology subsumes a series of models studied in the literature as limiting cases. A simple method is given to determine the transformed time scale forms of the Wiener process degradation model. Then model parameters can be estimated based on a maximum likelihood estimation (MLE) method. The cumulative distribution function (CDF) and the probability distribution function (PDF) of the Wiener process with measurement errors are given based on the concept of the first hitting time (FHT). The percentiles of performance degradation (PD) and failure time distribution (FTD) are also obtained. Finally, a comprehensive simulation study is accomplished to demonstrate the necessity of incorporating measurement errors in the degradation model and the efficiency of the proposed model. Two illustrative real applications involving the degradation of carbon-film resistors and the wear of sliding metal are given. The comparative results show that the constructed approach can derive a reasonable result and an enhanced inference precision. [Display omitted] •A generalized Wiener process degradation model with measurement errors is proposed.•A simple method to determine the transformed time scale forms is presented.•The probability distribution function is derived based on the first hitting time.•Maximum likelihood estimation method is used to estimate the unknown parameters.•Simulation and real examples are used to illustrate the efficiency of the model. Wiener processes have received considerable attention in degradation modeling over the last two decades. In this paper, we propose a generalized Wiener process degradation model that takes unit-to-unit variation, time-correlated structure and measurement error into considerations simultaneously. The constructed methodology subsumes a series of models studied in the literature as limiting cases. A simple method is given to determine the transformed time scale forms of the Wiener process degradation model. Then model parameters can be estimated based on a maximum likelihood estimation (MLE) method. The cumulative distribution function (CDF) and the probability distribution function (PDF) of the Wiener process with measurement errors are given based on the concept of the first hitting time (FHT). The percentiles of performance degradation (PD) and failure time distribution (FTD) are also obtained. Finally, a comprehensive simulation study is accomplished to demonstrate the necessity of incorporating measurement errors in the degradation model and the efficiency of the proposed model. Two illustrative real applications involving the degradation of carbon-film resistors and the wear of sliding metal are given. The comparative results show that the constructed approach can derive a reasonable result and an enhanced inference precision.
Author	Wang, Zhihua Zhang, Yongbo Li, Junxing Fu, Huimin Liu, Chengrui Krishnaswamy, Sridhar
Author_xml	– sequence: 1 givenname: Junxing surname: Li fullname: Li, Junxing organization: School of Aeronautic Science and Engineering, Beihang University, Beijing, China – sequence: 2 givenname: Zhihua surname: Wang fullname: Wang, Zhihua email: wangzhihua@buaa.edu.cn organization: School of Aeronautic Science and Engineering, Beihang University, Beijing, China – sequence: 3 givenname: Yongbo surname: Zhang fullname: Zhang, Yongbo organization: School of Aeronautic Science and Engineering, Beihang University, Beijing, China – sequence: 4 givenname: Huimin surname: Fu fullname: Fu, Huimin organization: School of Aeronautic Science and Engineering, Beihang University, Beijing, China – sequence: 5 givenname: Chengrui surname: Liu fullname: Liu, Chengrui organization: Beijing Institute of Control Engineering, Beijing, China – sequence: 6 givenname: Sridhar surname: Krishnaswamy fullname: Krishnaswamy, Sridhar organization: Department of Mechanical Engineering, Northwestern University, Evanston, USA
BookMark	eNqFkEtLw0AQgBepYKv-Ai8LnhP3kSbdgwepTyh4UbwIyz4mZUOb1J1EqL_ebevJg57mwXzDzDcho7ZrgZALznLOeHnV5Ns14iYXjFc5EzmT_IiMOVNlxgUvR2TMZrNZJkXFTsgEsWGMqYKVY_J-C8tovOlD19IUDDWtWW0xILUGwdPUNnQJLUSzCl-p8RZ2Bd3EzgEixcE24Hrad3QNBocIa2h7CjF28Ywc12aFcP4TT8nr_d3L_DFbPD88zW8WmZOV6jMooKh97VVdC2ehmgqvvJfeypSWNZeukr6qSls7W7rClN5Z67yxXhhfKCdPyeVhbzrqYwDsddMNMf2BmqtCVIWaTXmakocpFzvECLXexLA2cas50zuNutF7jXqnUTOhk8ZEqV-UC_1eVx9NWP3DXh9YSM9_BogaXbLnwIeYnGnfhT_5by22lUU
CitedBy_id	crossref_primary_10_1002_qre_2325 crossref_primary_10_23919_JSEE_2022_000068 crossref_primary_10_1109_TR_2022_3172416 crossref_primary_10_1016_j_eswa_2021_115627 crossref_primary_10_1016_j_measurement_2024_115312 crossref_primary_10_1016_j_ress_2024_110289 crossref_primary_10_1016_j_ress_2022_108913 crossref_primary_10_1109_TIE_2019_2908617 crossref_primary_10_1016_j_jfoodeng_2023_111471 crossref_primary_10_1016_j_measurement_2024_115364 crossref_primary_10_1109_ACCESS_2019_2906325 crossref_primary_10_1016_j_ress_2019_106751 crossref_primary_10_1155_2021_6475056 crossref_primary_10_1016_j_ress_2019_04_031 crossref_primary_10_1080_03610926_2025_2464079 crossref_primary_10_1109_ACCESS_2020_3044681 crossref_primary_10_1016_j_ress_2020_107138 crossref_primary_10_1080_00949655_2022_2143502 crossref_primary_10_1016_j_apm_2022_03_039 crossref_primary_10_1109_TII_2023_3288225 crossref_primary_10_1109_TIM_2021_3085935 crossref_primary_10_1109_TR_2019_2908492 crossref_primary_10_1016_j_ress_2021_108087 crossref_primary_10_1016_j_ymssp_2025_113089 crossref_primary_10_1155_2018_9734189 crossref_primary_10_1088_2632_959X_ac7c81 crossref_primary_10_1016_j_ymssp_2017_10_021 crossref_primary_10_1016_j_ress_2022_108854 crossref_primary_10_1016_j_ymssp_2018_12_039 crossref_primary_10_1007_s11432_020_3134_8 crossref_primary_10_1016_j_ress_2021_108099 crossref_primary_10_1016_j_microrel_2022_114640 crossref_primary_10_1080_03610918_2019_1710194 crossref_primary_10_1109_JAS_2021_1003859 crossref_primary_10_1016_j_ress_2017_11_003 crossref_primary_10_1002_qre_3688 crossref_primary_10_1016_j_cam_2020_113081 crossref_primary_10_1016_j_measurement_2024_115885 crossref_primary_10_1016_j_engfailanal_2019_06_035 crossref_primary_10_3390_math7050416 crossref_primary_10_1002_qre_3729 crossref_primary_10_1016_j_cam_2019_06_003 crossref_primary_10_1016_j_ymssp_2021_107785 crossref_primary_10_1109_JSEN_2021_3082953 crossref_primary_10_1016_j_compeleceng_2024_109603 crossref_primary_10_1016_j_ress_2020_107231 crossref_primary_10_1016_j_ress_2021_107895 crossref_primary_10_3390_sym16101364 crossref_primary_10_1007_s12206_019_1037_z crossref_primary_10_1016_j_microrel_2021_114277 crossref_primary_10_1109_ACCESS_2019_2945566
Cites_doi	10.1109/TR.2013.2284733 10.1016/j.microrel.2010.09.013 10.1109/TR.2009.2026784 10.1002/qre.1489 10.1016/j.engfailanal.2011.12.004 10.1002/qre.1547 10.5957/jsr.1990.34.3.199 10.1023/A:1009664101413 10.1002/nav.10042 10.1016/j.ejor.2012.03.028 10.1016/j.ress.2012.10.015 10.1016/j.ejor.2010.11.018 10.6339/JDS.2007.05(3).351 10.1007/s10985-005-5237-8 10.1007/s11771-014-2455-9 10.1016/j.ress.2013.11.011 10.1214/ss/1177010132 10.1007/BF00985762 10.1109/TR.2011.2182221 10.1080/00401706.1993.10485038 10.1016/j.jspi.2011.06.008 10.3390/en7020520
ContentType	Journal Article
Copyright	2017 Elsevier Ltd Copyright Elsevier BV Sep 15, 2017
Copyright_xml	– notice: 2017 Elsevier Ltd – notice: Copyright Elsevier BV Sep 15, 2017
DBID	AAYXX CITATION 7SC 7SP 8FD JQ2 L7M L~C L~D
DOI	10.1016/j.ymssp.2017.02.031
DatabaseName	CrossRef Computer and Information Systems Abstracts Electronics & Communications Abstracts Technology Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional
DatabaseTitle	CrossRef Technology Research Database Computer and Information Systems Abstracts – Academic Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Professional
DatabaseTitleList	Technology Research Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering
EISSN	1096-1216
EndPage	72
ExternalDocumentID	10_1016_j_ymssp_2017_02_031 S088832701730095X
GroupedDBID	--K --M .~1 0R~ 1B1 1~. 1~5 4.4 457 4G. 5GY 5VS 7-5 71M 8P~ 9JN AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAXUO AAYFN ABBOA ABJNI ABMAC ABYKQ ACDAQ ACGFS ACRLP ACZNC ADBBV ADEZE ADTZH AEBSH AECPX AEKER AENEX AFKWA AFTJW AGHFR AGUBO AGYEJ AHHHB AHJVU AHZHX AIALX AIEXJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD AXJTR BJAXD BKOJK BLXMC CS3 DM4 DU5 EBS EFBJH EFLBG EJD EO8 EO9 EP2 EP3 F5P FDB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ IHE J1W JJJVA KOM LG5 LG9 LY7 M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 ROL RPZ SDF SDG SDP SES SPC SPCBC SPD SST SSV SSZ T5K XPP ZMT ZU3 ~G- 29M 9DU AAQXK AATTM AAXKI AAYWO AAYXX ABDPE ABEFU ABFNM ABWVN ABXDB ACLOT ACNNM ACRPL ACVFH ADCNI ADFGL ADJOM ADMUD ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP ASPBG AVWKF AZFZN CAG CITATION COF EFKBS FEDTE FGOYB G-2 HLZ HVGLF HZ~ R2- SBC SET SEW WUQ ~HD 7SC 7SP 8FD JQ2 L7M L~C L~D
ID	FETCH-LOGICAL-c379t-e4e4fdfd9ff2cbe752d9dd3db37526f13c73d776bfcb6c4a6dcbbcdabd2ad49c3
ISICitedReferencesCount	58
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000400203700004&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0888-3270
IngestDate	Sun Nov 30 03:52:45 EST 2025 Sat Nov 29 02:08:12 EST 2025 Tue Nov 18 22:23:41 EST 2025 Fri Feb 23 02:29:57 EST 2024
IsPeerReviewed	true
IsScholarly	true
Keywords	Measurement errors Maximum likelihood estimation Wiener process Degradation analysis
Language	English
LinkModel	OpenURL
MergedId	FETCHMERGED-LOGICAL-c379t-e4e4fdfd9ff2cbe752d9dd3db37526f13c73d776bfcb6c4a6dcbbcdabd2ad49c3
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
PQID	1942749851
PQPubID	2045429
PageCount	16
ParticipantIDs	proquest_journals_1942749851 crossref_primary_10_1016_j_ymssp_2017_02_031 crossref_citationtrail_10_1016_j_ymssp_2017_02_031 elsevier_sciencedirect_doi_10_1016_j_ymssp_2017_02_031
PublicationCentury	2000
PublicationDate	2017-09-15
PublicationDateYYYYMMDD	2017-09-15
PublicationDate_xml	– month: 09 year: 2017 text: 2017-09-15 day: 15
PublicationDecade	2010
PublicationPlace	Berlin
PublicationPlace_xml	– name: Berlin
PublicationTitle	Mechanical systems and signal processing
PublicationYear	2017
Publisher	Elsevier Ltd Elsevier BV
Publisher_xml	– name: Elsevier Ltd – name: Elsevier BV
References	Singpurwalla (b0025) 1995 Tang, Guo, Zhou (b0130) 2014; 5 Tsai, Tseng, Balakrishnan (b0040) 2011; 141 Park, Padgett (b0050) 2005; 11 Tseng, Peng (b0085) 2007; 5 Tang, Yu, Wang, Guo, Si (b0115) 2014; 7 Soares (b0020) 1990; 34 Meeker, Escobar (b0015) 2014 Wang, Jiang, Guo, Cheng (b0060) 2014; 30 Wang, Fu, Zhang (b0105) 2014; 30 Tang, Guo, Zhou, Zhou, Zhang (b0120) 2014 Guo, Wang, Guo, Si (b0045) 2013; 111 Whitmore (b0075) 1995; 1 L. Davis, Handbook of genetic algorithms, 1991. Tseng, Tang, Ku (b0095) 2003; 50 Si, Wang, Hu, Zhou (b0055) 2011; 213 Wang, Balakrishnan, Guo (b0100) 2014; 124 Pan, Wang (b0110) 2014 Jin, Liu, Zhou, Zhou (b0005) 2012; 22 Ye, Wang, Tsui, Pecht (b0090) 2013; 62 Peng, Tseng (b0035) 2009; 58 Whitmore, Schenkelberg (b0080) 1997; 3 Lu, Meeker (b0010) 1993; 35 Ye, Shen, Xie (b0030) 2012; 221 Wang, Carr, Xu, Kobbacy (b0065) 2011; 51 Si, Wang, Hu, Zhou, Pecht (b0070) 2012; 61 Tseng (10.1016/j.ymssp.2017.02.031_b0085) 2007; 5 Tang (10.1016/j.ymssp.2017.02.031_b0115) 2014; 7 Park (10.1016/j.ymssp.2017.02.031_b0050) 2005; 11 Whitmore (10.1016/j.ymssp.2017.02.031_b0080) 1997; 3 Guo (10.1016/j.ymssp.2017.02.031_b0045) 2013; 111 10.1016/j.ymssp.2017.02.031_b0125 Tang (10.1016/j.ymssp.2017.02.031_b0120) 2014 Tang (10.1016/j.ymssp.2017.02.031_b0130) 2014; 5 Ye (10.1016/j.ymssp.2017.02.031_b0030) 2012; 221 Tseng (10.1016/j.ymssp.2017.02.031_b0095) 2003; 50 Pan (10.1016/j.ymssp.2017.02.031_b0110) 2014 Jin (10.1016/j.ymssp.2017.02.031_b0005) 2012; 22 Wang (10.1016/j.ymssp.2017.02.031_b0100) 2014; 124 Wang (10.1016/j.ymssp.2017.02.031_b0060) 2014; 30 Singpurwalla (10.1016/j.ymssp.2017.02.031_b0025) 1995 Wang (10.1016/j.ymssp.2017.02.031_b0065) 2011; 51 Tsai (10.1016/j.ymssp.2017.02.031_b0040) 2011; 141 Soares (10.1016/j.ymssp.2017.02.031_b0020) 1990; 34 Whitmore (10.1016/j.ymssp.2017.02.031_b0075) 1995; 1 Si (10.1016/j.ymssp.2017.02.031_b0055) 2011; 213 Ye (10.1016/j.ymssp.2017.02.031_b0090) 2013; 62 Peng (10.1016/j.ymssp.2017.02.031_b0035) 2009; 58 Wang (10.1016/j.ymssp.2017.02.031_b0105) 2014; 30 Lu (10.1016/j.ymssp.2017.02.031_b0010) 1993; 35 Meeker (10.1016/j.ymssp.2017.02.031_b0015) 2014 Si (10.1016/j.ymssp.2017.02.031_b0070) 2012; 61
References_xml	– volume: 11 start-page: 511 year: 2005 end-page: 527 ident: b0050 article-title: Accelerated degradation models for failure based on geometric Brownian motion and gamma processes publication-title: Lifetime Data Anal. – start-page: 1 year: 2014 end-page: 5 ident: b0110 article-title: Analysis of degradation process with measurement errors publication-title: Reliability and Maintainability Symposium (RAMS), 2014 Annual – volume: 5 start-page: 315 year: 2007 end-page: 333 ident: b0085 article-title: Stochastic diffusion modeling of degradation data publication-title: J. Data Sci. – volume: 58 start-page: 444 year: 2009 end-page: 455 ident: b0035 article-title: Mis-specification analysis of linear degradation models publication-title: IEEE Trans. Reliab. – volume: 61 start-page: 50 year: 2012 end-page: 67 ident: b0070 article-title: Remaining useful life estimation based on a nonlinear diffusion degradation process publication-title: IEEE Trans. Reliab. – year: 2014 ident: b0015 article-title: Statistical Methods for Reliability Data – volume: 34 start-page: 199 year: 1990 end-page: 205 ident: b0020 article-title: Stochastic modeling of maximum still-water load effects in ship structures publication-title: J. Ship. Res. – volume: 3 start-page: 27 year: 1997 end-page: 45 ident: b0080 article-title: Modeling accelerated degradation data using Wiener diffusion with a time scale transformation publication-title: Lifetime Data Anal. – volume: 124 start-page: 13 year: 2014 end-page: 23 ident: b0100 article-title: Residual life estimation based on a generalized Wiener degradation process publication-title: Reliab. Eng. Syst. Safe. – volume: 22 start-page: 50 year: 2012 end-page: 63 ident: b0005 article-title: RePofe: reliability physics of failure estimation based on stochastic performance degradation for the momentum wheel publication-title: Eng. Fail. Anal. – start-page: 86 year: 1995 end-page: 103 ident: b0025 article-title: Survival in dynamic environments publication-title: Stat. Sci. – volume: 1 start-page: 307 year: 1995 end-page: 319 ident: b0075 article-title: Estimating degradation by a Wiener diffusion process subject to measurement error publication-title: Lifetime Data Anal. – year: 2014 ident: b0120 article-title: Real time remaining useful life prediction based on nonlinear Wiener based degradation processes with measurement errors publication-title: J. Cent. South Univ. – volume: 62 start-page: 772 year: 2013 end-page: 780 ident: b0090 article-title: Degradation data analysis using Wiener processes with measurement errors publication-title: IEEE Trans. Reliab. – volume: 141 start-page: 3725 year: 2011 end-page: 3735 ident: b0040 article-title: Mis-specification analyses of gamma and Wiener degradation processes publication-title: J. Stat. Plan. Infer. – volume: 5 start-page: 478 year: 2014 end-page: 487 ident: b0130 article-title: Mis-specification analysis of linear Wiener process-based degradation models for the remaining useful life estimation publication-title: Proc. Inst. Mech. Eng. Part O: J. Risk Reliab. – reference: L. Davis, Handbook of genetic algorithms, 1991. – volume: 50 start-page: 1 year: 2003 end-page: 14 ident: b0095 article-title: Determination of burn-in parameters and residual life for highly reliable products publication-title: Naval Res. Logist. (NRL) – volume: 30 start-page: 1275 year: 2014 end-page: 1283 ident: b0105 article-title: Analyzing degradation by an independent increment process publication-title: Qual. Reliab. Eng. Int. – volume: 7 start-page: 520 year: 2014 end-page: 547 ident: b0115 article-title: Remaining useful life prediction of lithium-ion batteries based on the wiener process with measurement error publication-title: Energies – volume: 51 start-page: 285 year: 2011 end-page: 293 ident: b0065 article-title: A model for residual life prediction based on Brownian motion with an adaptive drift publication-title: Microelectron. Reliab. – volume: 35 start-page: 161 year: 1993 end-page: 174 ident: b0010 article-title: Using degradation measures to estimate a time-to-failure distribution publication-title: Technometrics – volume: 111 start-page: 183 year: 2013 end-page: 194 ident: b0045 article-title: A maintenance optimization model for mission-oriented systems based on wiener degradation publication-title: Reliab. Eng. Syst. Safe. – volume: 213 start-page: 1 year: 2011 end-page: 14 ident: b0055 article-title: Remaining useful life estimation – a review on the statistical data driven approaches publication-title: Eur. J. Oper. Res. – volume: 30 start-page: 205 year: 2014 end-page: 220 ident: b0060 article-title: Real-time reliability evaluation with a general wiener process-based degradation model publication-title: Qual. Reliab. Eng. Int. – volume: 221 start-page: 360 year: 2012 end-page: 367 ident: b0030 article-title: Degradation-based burn-in with preventive maintenance publication-title: Eur. J. Oper. Res. – volume: 62 start-page: 772 year: 2013 ident: 10.1016/j.ymssp.2017.02.031_b0090 article-title: Degradation data analysis using Wiener processes with measurement errors publication-title: IEEE Trans. Reliab. doi: 10.1109/TR.2013.2284733 – volume: 51 start-page: 285 year: 2011 ident: 10.1016/j.ymssp.2017.02.031_b0065 article-title: A model for residual life prediction based on Brownian motion with an adaptive drift publication-title: Microelectron. Reliab. doi: 10.1016/j.microrel.2010.09.013 – volume: 58 start-page: 444 year: 2009 ident: 10.1016/j.ymssp.2017.02.031_b0035 article-title: Mis-specification analysis of linear degradation models publication-title: IEEE Trans. Reliab. doi: 10.1109/TR.2009.2026784 – volume: 30 start-page: 205 year: 2014 ident: 10.1016/j.ymssp.2017.02.031_b0060 article-title: Real-time reliability evaluation with a general wiener process-based degradation model publication-title: Qual. Reliab. Eng. Int. doi: 10.1002/qre.1489 – volume: 22 start-page: 50 year: 2012 ident: 10.1016/j.ymssp.2017.02.031_b0005 article-title: RePofe: reliability physics of failure estimation based on stochastic performance degradation for the momentum wheel publication-title: Eng. Fail. Anal. doi: 10.1016/j.engfailanal.2011.12.004 – volume: 30 start-page: 1275 year: 2014 ident: 10.1016/j.ymssp.2017.02.031_b0105 article-title: Analyzing degradation by an independent increment process publication-title: Qual. Reliab. Eng. Int. doi: 10.1002/qre.1547 – volume: 34 start-page: 199 year: 1990 ident: 10.1016/j.ymssp.2017.02.031_b0020 article-title: Stochastic modeling of maximum still-water load effects in ship structures publication-title: J. Ship. Res. doi: 10.5957/jsr.1990.34.3.199 – volume: 3 start-page: 27 year: 1997 ident: 10.1016/j.ymssp.2017.02.031_b0080 article-title: Modeling accelerated degradation data using Wiener diffusion with a time scale transformation publication-title: Lifetime Data Anal. doi: 10.1023/A:1009664101413 – volume: 50 start-page: 1 year: 2003 ident: 10.1016/j.ymssp.2017.02.031_b0095 article-title: Determination of burn-in parameters and residual life for highly reliable products publication-title: Naval Res. Logist. (NRL) doi: 10.1002/nav.10042 – volume: 221 start-page: 360 year: 2012 ident: 10.1016/j.ymssp.2017.02.031_b0030 article-title: Degradation-based burn-in with preventive maintenance publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2012.03.028 – volume: 111 start-page: 183 year: 2013 ident: 10.1016/j.ymssp.2017.02.031_b0045 article-title: A maintenance optimization model for mission-oriented systems based on wiener degradation publication-title: Reliab. Eng. Syst. Safe. doi: 10.1016/j.ress.2012.10.015 – volume: 213 start-page: 1 year: 2011 ident: 10.1016/j.ymssp.2017.02.031_b0055 article-title: Remaining useful life estimation – a review on the statistical data driven approaches publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2010.11.018 – ident: 10.1016/j.ymssp.2017.02.031_b0125 – volume: 5 start-page: 315 year: 2007 ident: 10.1016/j.ymssp.2017.02.031_b0085 article-title: Stochastic diffusion modeling of degradation data publication-title: J. Data Sci. doi: 10.6339/JDS.2007.05(3).351 – volume: 11 start-page: 511 year: 2005 ident: 10.1016/j.ymssp.2017.02.031_b0050 article-title: Accelerated degradation models for failure based on geometric Brownian motion and gamma processes publication-title: Lifetime Data Anal. doi: 10.1007/s10985-005-5237-8 – start-page: 1 year: 2014 ident: 10.1016/j.ymssp.2017.02.031_b0110 article-title: Analysis of degradation process with measurement errors – year: 2014 ident: 10.1016/j.ymssp.2017.02.031_b0120 article-title: Real time remaining useful life prediction based on nonlinear Wiener based degradation processes with measurement errors publication-title: J. Cent. South Univ. doi: 10.1007/s11771-014-2455-9 – year: 2014 ident: 10.1016/j.ymssp.2017.02.031_b0015 – volume: 124 start-page: 13 year: 2014 ident: 10.1016/j.ymssp.2017.02.031_b0100 article-title: Residual life estimation based on a generalized Wiener degradation process publication-title: Reliab. Eng. Syst. Safe. doi: 10.1016/j.ress.2013.11.011 – start-page: 86 year: 1995 ident: 10.1016/j.ymssp.2017.02.031_b0025 article-title: Survival in dynamic environments publication-title: Stat. Sci. doi: 10.1214/ss/1177010132 – volume: 1 start-page: 307 year: 1995 ident: 10.1016/j.ymssp.2017.02.031_b0075 article-title: Estimating degradation by a Wiener diffusion process subject to measurement error publication-title: Lifetime Data Anal. doi: 10.1007/BF00985762 – volume: 61 start-page: 50 year: 2012 ident: 10.1016/j.ymssp.2017.02.031_b0070 article-title: Remaining useful life estimation based on a nonlinear diffusion degradation process publication-title: IEEE Trans. Reliab. doi: 10.1109/TR.2011.2182221 – volume: 35 start-page: 161 year: 1993 ident: 10.1016/j.ymssp.2017.02.031_b0010 article-title: Using degradation measures to estimate a time-to-failure distribution publication-title: Technometrics doi: 10.1080/00401706.1993.10485038 – volume: 141 start-page: 3725 year: 2011 ident: 10.1016/j.ymssp.2017.02.031_b0040 article-title: Mis-specification analyses of gamma and Wiener degradation processes publication-title: J. Stat. Plan. Infer. doi: 10.1016/j.jspi.2011.06.008 – volume: 7 start-page: 520 year: 2014 ident: 10.1016/j.ymssp.2017.02.031_b0115 article-title: Remaining useful life prediction of lithium-ion batteries based on the wiener process with measurement error publication-title: Energies doi: 10.3390/en7020520 – volume: 5 start-page: 478 year: 2014 ident: 10.1016/j.ymssp.2017.02.031_b0130 article-title: Mis-specification analysis of linear Wiener process-based degradation models for the remaining useful life estimation publication-title: Proc. Inst. Mech. Eng. Part O: J. Risk Reliab.
SSID	ssj0009406
Score	2.468753
Snippet	[Display omitted] •A generalized Wiener process degradation model with measurement errors is proposed.•A simple method to determine the transformed time scale... Wiener processes have received considerable attention in degradation modeling over the last two decades. In this paper, we propose a generalized Wiener process...
SourceID	proquest crossref elsevier
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	57
SubjectTerms	Computer simulation Correlation analysis Data analysis Degradation Degradation analysis Distribution functions Error analysis Maximum likelihood estimation Measurement errors Parameter estimation Performance degradation Probability distribution Probability distribution functions Resistors Time correlation functions Wear Wiener process
Title	Degradation data analysis based on a generalized Wiener process subject to measurement error
URI	https://dx.doi.org/10.1016/j.ymssp.2017.02.031 https://www.proquest.com/docview/1942749851
Volume	94
WOSCitedRecordID	wos000400203700004&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: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1096-1216 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0009406 issn: 0888-3270 databaseCode: AIEXJ dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9NAEF6FlgMcEE-1UNAeEBfjKvEze6wgFaAQOKRtQEirfZmmau3gJFXgb_CHmfGuHZeKCA5cLGcT29HO553Z2Z3vI-Q5Vn0b1AiD6EP7EBFnvtDK-F0jk4wZkbGKeP54mI5G_cmEfex0fta1MJfnaZ73Vys2-6-mhjYwNpbO_oO5m5tCA5yD0eEIZofjXxn-NdI_WKUkD_d_eqLmHUGPpXF1QKBwMiajpj-g4WSKH7yZLRnw5kuJuRkMSi_WCUTPlGVRtkPZ9waLhm1VpaU9rxYicEMIVnfZu9WOEbf8TG0VSL5qNZ64dPXn0-npsvEQTRb7U5F_lUWDsWXlKJcoRNbOVoAHRLWFeJ1Ca8pojq8MdH0_DKyAyL6xAzFMrfxeYOsw65GaRa2h1vJaX_MANhlxtv_9Yj5HPtJeWnGyOldzhW979IEfHg2HfDyYjF_MvvkoRYZL9k6X5QbZDtKYwVC5ffB2MHm35nKOKsnW5m_XZFbVtsFrz_1TwPOb66_imfFdcsdNROiBBdA90jH5fXK7RU_5gHxpQYkilGgNJVpBiUKzoC0oUQsl6oxPHZTooqAtKNEKSg_J0eFg_OqN79Q4fBWmbOGbyESZzjTLskBJk8aBZlqHWoZwmmS9UKWhTtNEZkomKhKJVlIqLaQOhI6YCh-RrbzIzQ6hWT9QWsbMhEJFELHLBK5PQiEYTAj6cXeXBHWXceWo6lEx5ZzXexLPeNXPHPuZdwMO_bxLXjYXzSxTy-afJ7UtuAs2bRDJAUmbL9yrLcfdaz_nPRYFacRg-vJ489dPyK31a7FHthbl0jwlN9XlYjovnzmk_QJvbq8w
linkProvider	Elsevier
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=Degradation+data+analysis+based+on+a+generalized+Wiener+process+subject+to+measurement+error&rft.jtitle=Mechanical+systems+and+signal+processing&rft.au=Li%2C+Junxing&rft.au=Wang%2C+Zhihua&rft.au=Zhang%2C+Yongbo&rft.au=Fu%2C+Huimin&rft.date=2017-09-15&rft.pub=Elsevier+BV&rft.issn=0888-3270&rft.eissn=1096-1216&rft.volume=94&rft.spage=57&rft_id=info:doi/10.1016%2Fj.ymssp.2017.02.031&rft.externalDBID=NO_FULL_TEXT
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0888-3270&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0888-3270&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0888-3270&client=summon