Acoustic emission signal feature extraction method based on pressure-bearing equipment activity defect monitoring

The invention relates to an acoustic emission signal feature extraction method based on pressure-bearing equipment activity defect monitoring, and the method comprises the steps: extracting acoustic emission waveform feature parameters according to the actual parameter features of an acoustic emission signal for the pressure-bearing equipment activity defect monitoring; using the extracted feature parameters as feature vectors, and defining distances between variables by using similarity coefficients; hierarchical clustering is carried out, the parameters are classified into one class one by one according to similarity coefficients among the parameters, and an acoustic emission characteristic parameter correlation hierarchical clustering tree is obtained; setting a correlation threshold, and reserving parameters with correlation coefficients below the correlation threshold as feature vectors of clustering analysis; and on the basis of determining the clustering analysis feature vector, performing K-mean clust