摘要
在现有的故障诊断与预测方法的基础上,提出了一种基于小波及ARMA模型的预测方法。首先给出了小波去噪的原理,以及ARMA模型预测的思想,结合民机故障率的特点,对实际的故障率数据进行小波去噪,保留故障发展的主要趋势,对主要趋势进行ARMA建模预测,并将预测结果与实际值进行比较。结果说明,进行小波去噪后的ARMA建模预测的结果有较高的准确率。
On the basis of the method of fault diagnosis and prediction, a prediction method based on wavelet and ARMA model is given. Firstly, wavelet denoising principle and prediction method based on ARMA model are given. Then, combined with the characteristics of the civil airplane failure rate, wavelet denoising is done for failure rate data to keep the main trend of the failure, a prediction method based on ARMA model for the main trend is established. Finally, the comparison of prediction result and the actual value is given. Conclusion shows that the prediction method based on wavelet and ARMA model has a higher accuracy.
出处
《测控技术》
CSCD
北大核心
2014年第10期43-46,50,共5页
Measurement & Control Technology
关键词
故障率预测
小波去噪
ARMA模型
可靠性
failure rate prediction
wavelet denoising
ARMA model
reliability
作者简介
茹斌（1988-）,男,陕西宝鸡人,硕士研究生,主要研究领域为机载设备故障诊断、航空电子自动测试、飞行品质监控等.
