基于小波变换的智能脱扣器改进算法研究

STUDY ON IMPROVED ALGORITHM FOR INTELECTUALIZED DISCONNECTED APPARATUS BASED ON WAVELET TRANSFORMATION

根据智能脱扣器的工作原理 ,针对常规傅立叶变换判断故障电流响应缓慢等问题 ,提出了利用小波变换和傅立叶变换的改进算法 ,将两种算法有机结合用小波算法找出故障信号中的突变点 ,再用傅立叶算法确定该突变点是否过阈值 ,得出真正的故障情况。这样充分发挥了小波算法检测突变信号的多尺度分析优点 ,保留了傅立叶算法的判据 ,避免了单独使用小波算法使可靠性降低的因素 。

According to the work principle of intellectualized disconnected apparatus. The response is slow in detecting wrong current by FFT transformation. The wavelet transformation possesses good localization characteristics, rapid response and good sensitivity. But it has to take many points and to calculate much work, it is very easy to make wrong . The discussed improved algorithm combines these two algorithms organically. At first, the true wrong point is detected by wavelet transformation in the questionable wrong points. Then the valid value of the signal is calculated so as to detect the true faults. The advantage of wavelet for detecting signal is developed and FFT is remained. The disadvantage that the reliability is decreased by using wavelet alone is avoided. So the disconnected apparatus works reliably.