Lifetime Estimation for Multi-Phase Deteriorating Process with Random Abrupt Jumps
Owing to operating condition changing, physical mutation, and sudden shocks, degradation trajectories usually exhibit multi-phase features, and the abrupt jump often appears at the changing time, which makes the traditional methods of lifetime estimation unavailable. In this paper, we mainly focus o...
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| Format: | Article |
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MDPI AG
2019-03-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/6/1472 |
| _version_ | 1811263271531970560 |
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| author | Jianxun Zhang Xiaosheng Si Dangbo Du Chen Hu Changhua Hu |
| author_facet | Jianxun Zhang Xiaosheng Si Dangbo Du Chen Hu Changhua Hu |
| author_sort | Jianxun Zhang |
| collection | DOAJ |
| description | Owing to operating condition changing, physical mutation, and sudden shocks, degradation trajectories usually exhibit multi-phase features, and the abrupt jump often appears at the changing time, which makes the traditional methods of lifetime estimation unavailable. In this paper, we mainly focus on how to estimate the lifetime of the multi-phase degradation process with abrupt jumps at the change points under the concept of the first passage time (FPT). Firstly, a multi-phase degradation model with jumps based on the Wiener process is formulated to describe the multi-phase degradation pattern. Then, we attain the lifetime’s closed-form expression for the two-phase model with fixed jump relying on the distribution of the degradation state at the change point. Furthermore, we continue to investigate the lifetime estimation of the degradation process with random effect caused by unit-to-unit variability and the multi-phase degradation process. We extend the results of the two-phase case with fixed parameters to these two cases. For better implementation, a model identification method with off-line and on-line parts based on Expectation Maximization (EM) algorithm and Bayesian rule is proposed. Finally, a numerical case study and a practical example of gyro are provided for illustration. |
| first_indexed | 2024-04-12T19:41:45Z |
| format | Article |
| id | doaj.art-1f35683c720643048324640ca0338db3 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-12T19:41:45Z |
| publishDate | 2019-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-1f35683c720643048324640ca0338db32022-12-22T03:19:03ZengMDPI AGSensors1424-82202019-03-01196147210.3390/s19061472s19061472Lifetime Estimation for Multi-Phase Deteriorating Process with Random Abrupt JumpsJianxun Zhang0Xiaosheng Si1Dangbo Du2Chen Hu3Changhua Hu4Department of Automation, Xi’an Research Institute of High-Tech, Xi’an 710025, ChinaDepartment of Automation, Xi’an Research Institute of High-Tech, Xi’an 710025, ChinaDepartment of Automation, Xi’an Research Institute of High-Tech, Xi’an 710025, ChinaDepartment of Automation, Xi’an Research Institute of High-Tech, Xi’an 710025, ChinaDepartment of Automation, Xi’an Research Institute of High-Tech, Xi’an 710025, ChinaOwing to operating condition changing, physical mutation, and sudden shocks, degradation trajectories usually exhibit multi-phase features, and the abrupt jump often appears at the changing time, which makes the traditional methods of lifetime estimation unavailable. In this paper, we mainly focus on how to estimate the lifetime of the multi-phase degradation process with abrupt jumps at the change points under the concept of the first passage time (FPT). Firstly, a multi-phase degradation model with jumps based on the Wiener process is formulated to describe the multi-phase degradation pattern. Then, we attain the lifetime’s closed-form expression for the two-phase model with fixed jump relying on the distribution of the degradation state at the change point. Furthermore, we continue to investigate the lifetime estimation of the degradation process with random effect caused by unit-to-unit variability and the multi-phase degradation process. We extend the results of the two-phase case with fixed parameters to these two cases. For better implementation, a model identification method with off-line and on-line parts based on Expectation Maximization (EM) algorithm and Bayesian rule is proposed. Finally, a numerical case study and a practical example of gyro are provided for illustration.https://www.mdpi.com/1424-8220/19/6/1472life prognosticsreliabilitymulti-phase degradationexpectation maximization algorithmrandom jump |
| spellingShingle | Jianxun Zhang Xiaosheng Si Dangbo Du Chen Hu Changhua Hu Lifetime Estimation for Multi-Phase Deteriorating Process with Random Abrupt Jumps Sensors life prognostics reliability multi-phase degradation expectation maximization algorithm random jump |
| title | Lifetime Estimation for Multi-Phase Deteriorating Process with Random Abrupt Jumps |
| title_full | Lifetime Estimation for Multi-Phase Deteriorating Process with Random Abrupt Jumps |
| title_fullStr | Lifetime Estimation for Multi-Phase Deteriorating Process with Random Abrupt Jumps |
| title_full_unstemmed | Lifetime Estimation for Multi-Phase Deteriorating Process with Random Abrupt Jumps |
| title_short | Lifetime Estimation for Multi-Phase Deteriorating Process with Random Abrupt Jumps |
| title_sort | lifetime estimation for multi phase deteriorating process with random abrupt jumps |
| topic | life prognostics reliability multi-phase degradation expectation maximization algorithm random jump |
| url | https://www.mdpi.com/1424-8220/19/6/1472 |
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