Research on Traveling Wave Head Detection Algorithm for Wavelet Multi-Scale Information Fusion

A wavelet transform multi-scale information synthesis algorithm for traveling wave head detection is proposed. Firstly, the fault traveling wave signal is processed using the multi-scale analysis of wavelet transform to obtain the modulus maximum values of wavelet coefficients at various scales. Then, the modulus maximum values are sequentially calibrated in a parallel coordinate system to form a grayscale image. Finally, a convolutional neural network is used to build a wave head detection model. This algorithm cleverly links wavelet transform with convolutional neural network using a parallel coordinate system, combining information from wavelet transform at multiple scales, providing a new approach for detecting traveling wave heads.