# Experimental Study on Acoustic Emission Signals Under Different Processing States of Laser-Assisted Machining of SiC Ceramics

## TL;DR

This study analyzes acoustic emission signals during laser machining of SiC ceramics to identify different processing states and quantify ceramic softening.

## Contribution

A novel method using low-frequency band energy ratio to numerically characterize ceramic softening during laser-assisted machining is introduced.

## Key findings

- Three processing states (brittle, plastic, thermal damage) were identified based on laser power ranges.
- Wavelet packet denoising and spectrum analysis revealed characteristic frequencies and amplitude trends in AE signals.
- Low-frequency band energy ratio was proposed as an indirect measure of ceramic softening degree.

## Abstract

In this paper, laser-assisted machining (LAM) of SiC ceramics was taken as the research object, and the different spectrum and energy spectrum characteristics and their changing trends of acoustic emission (AE) signals under processing states of brittleness, plasticity and thermal damage were analyzed. The numerical characterization of ceramic softening degree was indirectly realized by the energy spectrum characteristics of low-frequency band energy ratio, marking a methodological breakthrough in transitioning from qualitative analysis to quantitative detection for identifying plastic processing state. First, the surface morphology of the machined surface based on the single-factor experiment of laser power was analyzed, and three different processing states and ranges of laser power were determined, namely brittle state (0–185 W), plastic state (185–225 W) and thermal damage state (>225 W). Then, the wavelet packet denoising and spectrum analysis of AE signals under different processing states were carried out to obtain the corresponding frequency of the maximum amplitude and the amplitude change trend of the characteristic frequency (515 kHz) in the high-frequency domain. Finally, the energy spectrum analysis of acoustic emission signals was carried out, and the method of indirect characterization of ceramic softening degree by low-frequency band energy ratio was proposed. This paper provides a numerical characterization method and theoretical guidance for the detection and identification of the plastic processing state of ceramic laser-assisted cutting.