连续小波变换在传感器故障诊断中的应用

小波变换在信号分析与处理中有良好的局部性质.主要研究基于连续小波变换极值点的方法在传感器故障诊断中的应用.对输入信号输出信号进行连续小波变换,利用该变换求出输入输出信号的奇异值,然后去除由于输入突变所引起的极值点,则其余的极值点对应于传感器的故障.在MATLAB平台下,仿真结果表明,该故障诊断方法可以有效地进行故障检测和定位.

Fault Diagnose of Sensor on Wavelet Transform

Wavelet transform has powerful ability in signal processing. Since wavelet transformation can localize sensor signal characteristics both in time and frequency domain. We mostly study the fault diagnose of sensor based on the singularity of continuous wavelet transformation. Firstly according to the wavelet transformation of signal of input and output, we can locate the singularity of signal. Secondly, we can judge the maximum, which is mutated by input. So we can get the fault of sensor before the rest is fault of sensor when we get rid of the maximum. Through a large amount of simulations it indicates that the sensor faults detection method based on the theory of wavelet has the characteristic such as good sensitivity, high accuracy rate and robust ability to overcome noise. The result of simulation achieves satisfying result and testifies the advantage of using wavelet method in sensors faults detection.