Abstract：In order to identify the magnitude of rainfall from the rain sound signals,a rainfall recognition algorithm based on emprirical wowelet transform and support vector machine is proposed in this paper.The collected rain sound signal is denoised first,then the signal is decomposed by empirical wavelet transform,and several empircal wavelet function components are obtained,and then feature of each empircal wavelet function component is extracted through Matlab,forming an evaluation feature matrix in time and frequency domains.Finally,the feature matrix is classified and identified by SVM.Through simulation experiments,it is found that for the same signal,empirical wavelet transform has better adaptability than empirical mode decomposition and overcomes the aliasing phenomenon and endpoint effect of empirical mode decomposition.The research results show that the empirical wavelet transform and support vector machine method has good performance in the field of rainfall recognition and the research method lays a good foundation for the development of rainfall recognition and intelligent raingauge.
2024, Vol. 41 
