In this paper, a feature extraction method based on intrinsic mode function (IMF)energy moment is presented for extracting the features of noise produced by the working shearing machines. And, by combining the BP neural network (BPNN) and support vector machine(SVM), a hybrid BPNN-SVM model is proposed for tool wear condition monitoring of spent fuel shearing machines. Empirical study on the working noise samples of the spent fuel shearing machine under four tool wear states(normal, mild wear, severe wear and damage) is carried out. The results...
