Wear state evaluation of inner-diameter saw blade based on vibration and noise signals during processing

Abstract

Slicing and cutting processing by inner-diameter saw blade has advantages of low cost and convenient adjustment of machine tool. In small size and batch processing, inner-diameter saw blade slicing and cutting is a common-used processing method. However, the wear of inner-diameter saw blade will seriously affect surface quality of workpiece cross section. It is necessary to monitor and evaluate the wear in real time. Based on the short-time Fourier transform, this article introduces a new method for assessing the wear of inner-diameter saw blade. By measuring and analyzing time–frequency characteristics of vibration and machining noise signals, wear is monitored in real time. The results show that it is a good method to monitor the wear of inner-diameter saw blade based on vibration of machine and machining noise signals. In addition, this method has no interference and influence on cutting work of inner-diameter saw blade, which provides a new idea for other forms of tool wear detection in engineering.