Remaining Useful Life Prediction Method for Stochastic Degrading Devices Considering Predictive Maintenance
Abstract
:1. Introduction
2. Motivation and Degradation Modeling
2.1. Motivation
- (1)
- The assumption is made that the same batch of degrading devices consists of M components, with each component functioning independently and exhibiting individual variability in the degradation process. denotes the detection interval, which is usually considered negligible.
- (2)
- The preventive maintenance activities for devices are imperfect maintenance activities, and the number of such activities is limited.
- (3)
- The lifetime and RUL discussed in this study are mainly concerned with the working time of the devices, without taking into account the downtime resulting from preventive maintenance activities.
- (4)
- The degradation processes of components, both prior to and following preventive maintenance activities, are assumed to be statistically independent.
2.2. Degradation Model Incorporating Imperfect Maintenance
3. RUL Prediction Incorporating Imperfect Maintenance
4. Model Parameter Identification and Updating
4.1. Parameter Estimation of Residual Degradation State
4.2. Parameter Estimation of Degradation Model
5. Case Study
5.1. Numerical Simulation
5.2. A Case Study of the Gyroscope
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Acronyms, Abbreviations and Nomenclatures
Acronyms and Abbreviations | |
PdM | predictive maintenance |
RUL | remaining useful life |
probability density function | |
CDF | cumulative density function |
AR(1) | autoregressive model of order 1 |
FHT | first hitting time |
CM | condition monitoring |
MLE | maximum likelihood estimation |
RE | relative error |
MSE | mean squared error |
INS | inertial navigation system |
Nomenclatures | |
failure threshold | |
preventive maintenance threshold | |
degradation state | |
drift term | |
diffusion coefficient | |
standard Brownian motion | |
residual degradation state | |
change coefficient |
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Parameter | Values | Parameter | Values |
---|---|---|---|
Initial drift term | 1.8 | Residual degradation hyperparameter | 2 |
Diffusion coefficient of drift term | 0.1 | Residual degradation hyperparameter | 5 |
Change coefficient means | 1.2 | Maintenance frequency | 3 |
Standard deviation of coefficient change | 0.3 | Failure threshold | 3.5 |
Diffusion coefficient | 0.35 | Preventive maintenance threshold | 3 |
Time interval | 0.01 | Nonlinear parameter | 1.2 |
Time | RE of RUL Prediction | MSE of RUL Prediction | ||||
---|---|---|---|---|---|---|
M0 | M1 | M2 | M0 | M1 | M2 | |
0.6 | 2.30% | 11.62% | 44.74% | 0.0025 | 0.0626 | 0.9424 |
1.8 | 5.31% | 16.87% | \ | 0.0026 | 0.0268 | \ |
2.2 | 0.85% | 7.82% | \ | 2.34 × 10−5 | 0.002 | \ |
2.6 | 1.27% | 17.05% | \ | 4.67 × 10−6 | 8.40 × 10−4 | \ |
Monitoring Point/h | M0 | M1 | Actual RUL/h |
---|---|---|---|
MSE | MSE | ||
260 | 0.1600 | 0.3260 | 22.5 |
262.5 | 0.1024 | 0.2401 | 20 |
265 | 0.1089 | 0.1296 | 17.5 |
267.5 | 0.0441 | 0.1849 | 15 |
270 | 0.1225 | 0.3249 | 12.5 |
272.5 | 0.0484 | 0.1600 | 10 |
275 | 0.0289 | 0.1444 | 7.5 |
277.5 | 0.0062 | 0.0115 | 5 |
280 | 0.00089 | 0.0014 | 2.5 |
Score | 5.2228 | 5.6447 | \ |
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Dong, Q.; Pei, H.; Hu, C.; Zheng, J.; Du, D. Remaining Useful Life Prediction Method for Stochastic Degrading Devices Considering Predictive Maintenance. Sensors 2025, 25, 1218. https://doi.org/10.3390/s25041218
Dong Q, Pei H, Hu C, Zheng J, Du D. Remaining Useful Life Prediction Method for Stochastic Degrading Devices Considering Predictive Maintenance. Sensors. 2025; 25(4):1218. https://doi.org/10.3390/s25041218
Chicago/Turabian StyleDong, Qing, Hong Pei, Changhua Hu, Jianfei Zheng, and Dangbo Du. 2025. "Remaining Useful Life Prediction Method for Stochastic Degrading Devices Considering Predictive Maintenance" Sensors 25, no. 4: 1218. https://doi.org/10.3390/s25041218
APA StyleDong, Q., Pei, H., Hu, C., Zheng, J., & Du, D. (2025). Remaining Useful Life Prediction Method for Stochastic Degrading Devices Considering Predictive Maintenance. Sensors, 25(4), 1218. https://doi.org/10.3390/s25041218