Grinding Burn Detection Based on Cross Wavelet and Wavelet Coherence Analysis by Acoustic Emission Signal

Abstract

Grinding burn monitoring is of great importance to guarantee the surface integrity of the workpiece. Existing methods monitor overall signal variation. However, the signals produced by metal burn are always weak. Therefore, the detection rate of grinding burn still needs to be improved. The paper presents a novel grinding burn detection method basing on acoustic emission (AE) signals. It is achieved by establishing the coherence relationship of pure metal burn and grinding burn signals. Firstly, laser and grinding experiments were carried out to produce pure metal burn signals and grinding burn signals. No-burn and burn surfaces were generated and AE signals were captured separately. Then, the cross wavelet transform (XWT) and wavelet coherence (WTC) were applied to reveal the coherence relationship of the pure metal burn signal and grinding burn signal. The methods can reduce unwanted AE sources and background noise. Novel parameters based on XWT and WTC are proposed to quantify the degree of coherence and monitor the grinding burn. The grinding burn signals were recognized successfully by the proposed indexes under same grinding condition.