Experimental study on laser assisted machining of silicon nitride ceramics based on acoustic emission detection

Abstract

Laser-assisted machining has been studied for more than 30 years. However, the research is still in the laboratory research stage. The fundamental reason is that the constant plastic machining can not be realized. So, to realize the real-time pattern recognition of plastic machining state, brittle machining state and thermal damage state is the key to the success, and also the bottleneck problem to be solved. In this paper, a real-time recognition method of machining state by detecting the acoustic emission signal of machining process is proposed. The mapping relationship between the acoustic emission signal of laser-assisted machining of silicon nitride ceramics and the machining state is found. The energy ratio coefficient of the frequency band of 0 kHz ∼ 19.53125 kHz and the root mean square are extracted as the characteristic parameters used to characterize and identify the machining state. The pattern recognition model of machining state is constructed.