Abstract
The overall performance of a mechanical device under random shocks, fatigue, and gradual degradation may continuously deteriorate over time, leading to multi-state health conditions. This deterioration can be represented by a continuous-time degradation process - with multiple discrete states - that reflects the relative degree of deterioration. This paper focuses on a condition-monitored device with multi-state deterioration, where its degradation state is not directly observable and only incomplete information is available through condition monitoring. After modeling this multi-state device, an unsupervised parameter estimation method is developed, which employs historical condition monitoring information to estimate the unknown characteristic parameters of the degradation process and the observation process. The results are evaluated through numerical experiments.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 94-103 |
| Number of pages | 10 |
| Journal | Reliability Engineering and System Safety |
| Volume | 106 |
| DOIs | |
| State | Published - Oct 2012 |
| Externally published | Yes |
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Keywords
- Condition monitoring
- Continuous-time degradation process
- Multi-state deterioration
- Unsupervised parameter estimation
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Safety, Risk, Reliability and Quality
- Applied Mathematics
Cite this
A parameter estimation method for a condition-monitored device under multi-state deterioration. / Moghaddass, Ramin; Zuo, Ming J.
In: Reliability Engineering and System Safety, Vol. 106, 10.2012, p. 94-103.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A parameter estimation method for a condition-monitored device under multi-state deterioration
AU - Moghaddass, Ramin
AU - Zuo, Ming J.
PY - 2012/10
Y1 - 2012/10
N2 - The overall performance of a mechanical device under random shocks, fatigue, and gradual degradation may continuously deteriorate over time, leading to multi-state health conditions. This deterioration can be represented by a continuous-time degradation process - with multiple discrete states - that reflects the relative degree of deterioration. This paper focuses on a condition-monitored device with multi-state deterioration, where its degradation state is not directly observable and only incomplete information is available through condition monitoring. After modeling this multi-state device, an unsupervised parameter estimation method is developed, which employs historical condition monitoring information to estimate the unknown characteristic parameters of the degradation process and the observation process. The results are evaluated through numerical experiments.
AB - The overall performance of a mechanical device under random shocks, fatigue, and gradual degradation may continuously deteriorate over time, leading to multi-state health conditions. This deterioration can be represented by a continuous-time degradation process - with multiple discrete states - that reflects the relative degree of deterioration. This paper focuses on a condition-monitored device with multi-state deterioration, where its degradation state is not directly observable and only incomplete information is available through condition monitoring. After modeling this multi-state device, an unsupervised parameter estimation method is developed, which employs historical condition monitoring information to estimate the unknown characteristic parameters of the degradation process and the observation process. The results are evaluated through numerical experiments.
KW - Condition monitoring
KW - Continuous-time degradation process
KW - Multi-state deterioration
KW - Unsupervised parameter estimation
UR - http://www.scopus.com/inward/record.url?scp=84863459246&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84863459246&partnerID=8YFLogxK
U2 - 10.1016/j.ress.2012.05.004
DO - 10.1016/j.ress.2012.05.004
M3 - Article
VL - 106
SP - 94
EP - 103
JO - Reliability Engineering and System Safety
JF - Reliability Engineering and System Safety
SN - 0951-8320
ER -