A denoising method for acoustic emission signals based on discrete wavelet transform in WEDM

Changhong Liu; Rongdong Chen; Shaohu Peng; Hongyin Li

doi:10.1117/12.3032851

5 July 2024 A denoising method for acoustic emission signals based on discrete wavelet transform in WEDM

Changhong Liu, Rongdong Chen, Shaohu Peng, Hongyin Li

Proceedings Volume 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024); 131840T (2024) https://doi.org/10.1117/12.3032851
Event: 3rd International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 2024, Kuala Lumpur, Malaysia

Abstract

As a non-destructive and real-time detection technology, acoustic emission (AE) testing has been widely applied in the state prediction and fault diagnosis in wire electrical discharge machining (WEDM). However, there has been limited research investigating the sources of interference affecting AE signals during the machining process. These sources of interference can induce noise, resulting in AE signals distortion. Therefore, this study designs a filtering algorithm based on discrete wavelet transform (DWT) to reduce the impact of noise on the AE signals. The experimental results indicate that noise mainly resides within the frequency ranges of [500,000Hz, 1,000,000Hz] and [0Hz, 15,600Hz], while AE signals generated by the workpiece are primarily distributed in the range of [32,300Hz, 500,000Hz]. The signal-to-noise ratio (SNR) of the filtered AE signal is 10.7dB, which is beneficial to analyze and extract features of signals in the follow-on work.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Changhong Liu, Rongdong Chen, Shaohu Peng, and Hongyin Li "A denoising method for acoustic emission signals based on discrete wavelet transform in WEDM", Proc. SPIE 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 131840T (5 July 2024); https://doi.org/10.1117/12.3032851

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