基于遗传算法和ARMA模型的航空发电机寿命预测

针对航空发电机剩余使用寿命难以准确预测的问题,提出一种基于遗传算法(GA)优化的自回归与移动平均(ARMA)模型.运用航空发电机寿命专用试验平台,对某型航空发电机寿命进行长期试验,获取该航空发电机寿命相关数据.深入分析寿命试验数据,并对其建立ARMA模型.在此基础上,采用遗传算法对ARMA模型的阶数进行优化,分别采用A...

Life Prognostics for Aero-generator Based on Genetic Algorithm and ARMA Model

To improve the aero-generator life prediction accuracy, an optimized auto-regressive and moving average (ARMA) model based on the genetic algorithm(GA) is presented. A specific experimental platform is used to perform long-term life prediction experiments on a certain type of aero-generator and collect the related test data. After a thorough analysis of these test data, a corresponding ARMA model is designed, and the genetic algorithm is used to carry on the exponent number optimization of the model. Then the original and the optimized ARMA models are used respectively to conduct life prediction research on the service life of the aero-generator. The result shows that these two models can realize the function of predicting the service life of an aero-generator. The average relative prognostic error of the ARMA model after the optimization is 2.26%, which is less than 4.33%, the error of the original model without optimization. Thus a conclusion can be drawn that the optimized ARMA model can predict the service life of an aero-generator more accurately and this model may find wide application in engineering practice.