基于改进小波变换的自动化电气设备故障点检测

Fault detection of automatic electrical equipment based on improved wavelet transform

传统的自动化电气设备故障点检测方法通常采用梯度扩散法确认故障信号波,但该方法并未对信号奇异性进行分析,获取的信号函数峰值较低,检测准确度不高。为此,提出了基于改进小波变换的自动化电气设备故障点检测方法。首先考虑环境对设备的影响,分析电气设备特性,同时为了提高电气设备故障信号的质量,添加数字滤波器,然后运用改进后的小波变换理论对设备故障信号进行分析。最后,分析小波分析后的异常信号奇异性,运用双端检测对奇异信号进行测距,得出故障点位置,完成自动化电气设备故障点检测。实验结果显示,本文所设计的故障点检测方法获得的信号函数峰值更高,检测的准确度更高,满足设计需求。

Traditional automatic electrical equipment fault point detection method usually uses gradient diffusion method to confirm the fault signal wave,but this method does not analyze the signal singularity.The peak value of the signal function obtained is low,and the detection accuracy is not high.Therefore,this paper proposes a fault point detection method of automatic electrical equipment based on improved wavelet transform.Firstly,considering the influence of environment on equipment,the characteristics of electrical equipment are analyzed.At the same time,in order to improve the quality of electrical equipment fault signal,digital filter is added,and then the improved wavelet transform theory is used to analyze the equipment fault signal.Finally,the singularity of abnormal signal after wavelet analysis is analyzed,and the location of fault point is obtained by using double terminal detection to detect the fault point of automatic electrical equipment.The experimental results show that the peak value of the signal function obtained by the proposed method is higher,and the detection accuracy is higher,which meets the design requirements.