Experimental Impact Acoustic NDE System Using Spindle-Deviation Minimization Method

Classification is an important part in artificial intelligence system. In this paper, we build an experimental impact acoustic NDE (non-destructive evaluation) system based on spindle-deviation minimization (SDM) method extended from Fisher criterion. The structure of system will be given, and the performance of SDM is discussed. The results show that the SDM method works well, and the right rate could reach to 100% with extracting meticulous feature vectors.