Online Detection of Laser Cladding Cracks using Acoustic Emission and Wavelet Denoising

In order to achieve online detection of cladding defects (such as cracks) during the laser cladding process, this paper proposes a novel method based on acoustic emission (AE) signal analysis. A microphone is utilized to collect the AE signals generated during the laser cladding process. These signals contain valuable information about the occurrence of cracks. To improve the signal-to-noise ratio and enhance the accuracy of crack detection, wavelet threshold denoising is applied to the collected audio signals. This technique effectively removes unwanted noise while preserving the essential characteristics of the crack-induced AE signals, enabling accurate identification and analysis of crack defects in real-time during the laser cladding process.