A Method of Mining Machinery Flaw Identification Based on Clustering Algorithm Optimized GRBF

According to the nonstationarity of mining machinery flaw signals in ultrasonic testing,the method used for defect identification based on WPT and Clustering Algorithm optimized GRBF.Focus on WPT extract the different defects characteristics and GRBF Algorithm classify the different flaws.Experimental study the mining machinery Welding flaws.Compared with the BP,experimental results shows that this algorithm has high accuracy of flaw classification.