Prediction method of aero-engine life on wing based on LS-SVM algorithm and performance reliability

MA Xiao-jun; REN Shu-hong; ZUO Hong-fu; WEN Zhen-hua

doi:10.19818/j.cnki.1671-1637.2015.03.011

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MA Xiao-jun, REN Shu-hong, ZUO Hong-fu, WEN Zhen-hua. Prediction method of aero-engine life on wing based on LS-SVM algorithm and performance reliability[J]. Journal of Traffic and Transportation Engineering, 2015, 15(3): 92-100. doi: 10.19818/j.cnki.1671-1637.2015.03.011

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MA Xiao-jun, REN Shu-hong, ZUO Hong-fu, WEN Zhen-hua. Prediction method of aero-engine life on wing based on LS-SVM algorithm and performance reliability[J]. Journal of Traffic and Transportation Engineering, 2015, 15(3): 92-100. doi: 10.19818/j.cnki.1671-1637.2015.03.011

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Prediction method of aero-engine life on wing based on LS-SVM algorithm and performance reliability

doi: 10.19818/j.cnki.1671-1637.2015.03.011

1.
School of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, Jiangsu, China
2.
Department of Aeronautical Engineering, Zhengzhou Institute of Aeronautical Industry Management, Zhengzhou 450015, Henan, China
3.
School of Mechatronics Engineering, Zhengzhou Institute of Aeronautical Industry Management, Zhengzhou 450015, Henan, China

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Author Bio:
MA Xiao-jun(1962-), male, doctoral student, +86-25-84890647, maxiaojun@comac.cc

ZUO Hong-fu(1959-), male, professor, +86-25-84891098, rms@nuaa.edu.cn
Received Date: 2015-01-17
Publish Date: 2015-06-20

Abstract

Abstract

Based on the monitoring data of practical performance for aero-engine, the degradation model of time-varying performance was established, and the performance trend was predicted. According to the much information related to aero-engine life on wing in the monitoring data, the relation between the performance degradation process and the failure distribution function was analyzed, and the aero-engine life on wing under a given reliability was obtained. Based on the practical life data on wing for aero-engine, the distribution model of life on wing was tested by using K-S fitting test method, and the model parameters was determined by using least squares- support vector machine (LS-SVM). Combined with the performance degradation trend, the revised life on wing for aero-engine was calculated, and example verification on six PW4000 aero-engines was carried out. Analysis result shows that when regularization parameters are 25, 37, 28, 40, 27 and 35 respectively, the practical lives on wing for six PW4000 aero-engines are 6 921, 7 160, 7 820, 8 490, 8 498, 6 921 cycles in order, while the corresponding prediction values are 6 534, 6 726, 7 378, 7 940, 9 103, 6 534 cycles in order. The maximum relative error is 0. 071 190, the minimum relative error is 0. 055 917, and the mean relative error is 0.060 824. The practical engineering requirement can be commendably satisfied by using the proposed method.
- aero-engine,
- life on wing,
- performance reliability,
- times series,
- Weibull distribution,
- LS-SVM

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References

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Prediction method of aero-engine life on wing based on LS-SVM algorithm and performance reliability

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