Parameter Estimation of a Multistate Model for an Aging Piece of Equipment under Condition-Based Maintenance
We study a multistate model for an aging piece of equipment under condition-based maintenance and apply an expectation maximization algorithm to obtain maximum likelihood estimates of the model parameters. Because of the monitoring discontinuity, we cannot observe any state's duration. The obse...
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2012/347675 |
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doaj-9bc921111bc64d2b8d2d9922e47994102020-11-24T20:58:42ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472012-01-01201210.1155/2012/347675347675Parameter Estimation of a Multistate Model for an Aging Piece of Equipment under Condition-Based MaintenanceQihong Duan0Xiang Chen1Dengfu Zhao2Zheng Zhao3Department of Mathematics, Faculty of Science, Xi'an Jiaotong University, Shaanxi, Xi'an 710049, ChinaDepartment of Mathematics, Faculty of Science, Xi'an Jiaotong University, Shaanxi, Xi'an 710049, ChinaSchool of Electrical Engineering, Xi'an Jiaotong University, Xi'an 710049, ChinaSchool of Electrical Engineering, Xi'an Jiaotong University, Xi'an 710049, ChinaWe study a multistate model for an aging piece of equipment under condition-based maintenance and apply an expectation maximization algorithm to obtain maximum likelihood estimates of the model parameters. Because of the monitoring discontinuity, we cannot observe any state's duration. The observation consists of the equipment's state at an inspection or right after a repair. Based on a proper construction of stochastic processes involved in the model, calculation of some probabilities and expectations becomes tractable. Using these probabilities and expectations, we can apply an expectation maximization algorithm to estimate the parameters in the model. We carry out simulation studies to test the accuracy and the efficiency of the algorithm.http://dx.doi.org/10.1155/2012/347675 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Qihong Duan Xiang Chen Dengfu Zhao Zheng Zhao |
spellingShingle |
Qihong Duan Xiang Chen Dengfu Zhao Zheng Zhao Parameter Estimation of a Multistate Model for an Aging Piece of Equipment under Condition-Based Maintenance Mathematical Problems in Engineering |
author_facet |
Qihong Duan Xiang Chen Dengfu Zhao Zheng Zhao |
author_sort |
Qihong Duan |
title |
Parameter Estimation of a Multistate Model for an Aging Piece of Equipment under Condition-Based Maintenance |
title_short |
Parameter Estimation of a Multistate Model for an Aging Piece of Equipment under Condition-Based Maintenance |
title_full |
Parameter Estimation of a Multistate Model for an Aging Piece of Equipment under Condition-Based Maintenance |
title_fullStr |
Parameter Estimation of a Multistate Model for an Aging Piece of Equipment under Condition-Based Maintenance |
title_full_unstemmed |
Parameter Estimation of a Multistate Model for an Aging Piece of Equipment under Condition-Based Maintenance |
title_sort |
parameter estimation of a multistate model for an aging piece of equipment under condition-based maintenance |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2012-01-01 |
description |
We study a multistate model for an aging piece of equipment under condition-based maintenance and apply an expectation maximization algorithm to obtain maximum likelihood estimates of the model parameters. Because of the monitoring discontinuity, we cannot observe any state's duration. The observation consists of the equipment's state at an inspection or right after a repair. Based on a proper construction of stochastic processes involved in the model, calculation of some probabilities and expectations becomes tractable. Using these probabilities and expectations, we can apply an expectation maximization algorithm to estimate the parameters in the model. We carry out simulation studies to test the accuracy and the efficiency of the algorithm. |
url |
http://dx.doi.org/10.1155/2012/347675 |
work_keys_str_mv |
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1716784941253001216 |