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The influence study of wavelet properties on transient power disturbance signals detection

机译:小波特性对暂态功率干扰信号检测的影响研究

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Wavelet transform is widely used in the transient disturbance signals detection. However, wavelet properties have great impact on detection results. If wavelet choice is improper, it will lead to failures in disturbances detection. Based on analyzing the cancellation, support set, smoothness and other properties of wavelet, make detection for different disturbances by using wavelet modulus maxima principles. The view that the wavelet with higher cancellation, longer support length and better smoothness should be chosen in transient power quality disturbance signals detection is first proposed in this paper. Select four typical wavelets, i.e. Haar, Symlet8, DB2, DB10 wavelet to make detection for voltage sag and oscillatory transient disturbances. Experimental results show that selection principles proposed in this paper is correct and reliable.
机译:小波变换被广泛用于瞬态干扰信号的检测。但是,小波性质对检测结果有很大的影响。如果小波选择不当,将导致干扰检测失败。在分析小波的消除,支持集,平滑度等特性的基础上,利用小波模极大值原理对不同的扰动进行检测。本文首先提出了在暂态电能质量扰动信号检测中应选择抵消度更高,支持长度更长,平滑度更好的小波的观点。选择四个典型的小波,即Haar,Symlet8,DB2,DB10小波,以检测电压骤降和振荡瞬态干扰。实验结果表明,本文提出的选择原则是正确和可靠的。

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