Abstract
The remaining useful life prediction of the aircraft engine is getting more difficult for its complex structure. Although the prediction methods have achieved certain success in practical application, there are some problems in the GM(1,1) model, such as model method biased, transformation inconsistent and first number of the initial sequence not functioning high precision prediction in model after an accumulated generating operation. Based on the grey prediction theory and with an analysis of the disadvantages of the GM(1,1) model, the improved GM(1,1) model is proposed by introducing linear time-vary terms. The model has been used for prediction and analysis with data of the aircraft engine system, the result shows that the proposed model has largely improves fitting and predicting precision, and widens the adaptation range.
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Abbreviations
- X (0) :
-
Original data sequence
- X (1) :
-
Accumulated generation sequence
- Z (1) :
-
Mean sequence
- a :
-
Developing coefficient
- b :
-
Grey input coefficient
- dt:
-
Time step
- \({\hat{\text{u}}}_{k}\) :
-
Growth rate
- B, Y :
-
Parameter matrix
- \((a_{1} ,{ }a_{2} )\) :
-
Time-varying developing parameters
- \(\left( {{ }b_{1} ,{ }b_{2} } \right)\) :
-
Time-varying grey input parameters
- \(\beta\) :
-
Amendable coefficient
- i, j, k :
-
Index
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Niu, W., Zhao, J., Wang, G., Wang, J. (2022). Remaining Useful Life Prediction of Aircraft Engine Based on Grey Model. In: Jing, X., Ding, H., Wang, J. (eds) Advances in Applied Nonlinear Dynamics, Vibration and Control -2021. ICANDVC 2021. Lecture Notes in Electrical Engineering, vol 799. Springer, Singapore. https://doi.org/10.1007/978-981-16-5912-6_83
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DOI: https://doi.org/10.1007/978-981-16-5912-6_83
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