Avionics Equipment Failure Prediction Based on Genetic Programming and Grey Model

被引：0

作者：

Deng, Xiujian ^{[1
]}

Luo, Qiang ^{[2
]}

Zhao, Yiyang ^{[2
]}

Feng, Qi ^{[2
]}

机构：

[1] Sci & Technol Avion Integrat Lab, Shanghai 200233, Peoples R China

[2] Northwestern Polytech Univ, Sch Elect Informat, Xian 710072, Peoples R China

来源：

SEVENTH INTERNATIONAL CONFERENCE ON ELECTRONICS AND INFORMATION ENGINEERING | 2017年 / 10322卷

关键词：

Avionics equipment; system reliability; fault diagnosis; failure prediction; genetic programming; GM (1,1) model; GP-GM (1,1) model; system performance;

D O I：

10.1117/12.2265227

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Avionics equipment failure prediction by conventional GM (Grey Model) may yield large forecasting errors. Combining GM (1, 1) model with genetic programming algorithm, a kind of GP-GM (1, 1) forecast model was established to minimize such errors. Forecasting sequence was calculated by means of GM (1, 1) model, then genetic programming algorithm was used to modify them further, and the degradation trend prediction of characteristic parameters of avionics equipment was realized. The validity of GP-GM (1, 1) prediction model was testified by tracking and forecasting the experiment data of avionics equipment in real environment.

引用

页数：7

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