摘要
在惯导器件的故障检测中,针对传统的状态x2检验法无法对缓变故障持续时间进行准确判定的问题,提出一种基于小波变换的状态x2改进检测算法。该方法首先利用小波变换后的模极大值在不同尺度上的衰减速度找出信号突变点;然后将检测结果反馈给Kalman滤波器,通过引入状态修正项,修正状态误差值,使故障检测曲线能够反映缓变故障的持续时间。仿真验证表明,采用基于小波变换的状态x2检测算法较好地解决了缓变故障持续时间无法准确判定的问题,大大提高了系统故障检测的准确性。
In view of the problem that traditional state chi-square test can＇t accurately determine the fault duration in soft fault detection, an improved state chi-square test method based on wavelet-transform was presented. Firstly, the signal jumping point was identified by using the decay speed of wavelet transform modulus maxima on the different scales. Then, the detection results were feedback to the Kalman filter. By introducing state correction term to correct the state error, the soft fault duration can be determined by the curve of fault detection. The simulation results show that the proposed method solve the problem of soft fault duration, and greatly improve the accuracy of fault detection.
出处
《中国惯性技术学报》
EI
CSCD
北大核心
2013年第1期136-140,共5页
Journal of Chinese Inertial Technology
基金
国家973基础研究项目(2011CB613156)
西北工业大学基础研究基金(GBKY1009)
