基于小波降噪与ResNet分类网络的异常电子蜂鸣音识别系统设计

doi:10.3969/j.issn.1000-1158.2022.11.15

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Abstract Electronic products usually use electronic beep as an alarm function. In order to detect whether the buzzer notification function is qualified in the quality inspection link of electronic products in the factory environment, wavelet noise reduction combined with ResNet network classification technology is used for buzzer detection. A buzzer sound recognition system is designed, the buzzer signal s1 with the PC sound card and the radio microphone, and uses the wavelet packet scale coefficient comparison method to realize the noise reduction and preprocessing of the collected buzzer signal to obtain the signal s2, and obtain the signal time-frequency characteristics through the wavelet transform of the signal s2 figure p, then use the ResNet18 network model to analyze the feature map p to get the buzzer detection result,the recognition accuracy is 97.5%. The system uses PyQt5 to design a human-computer interaction interface, which mainly includes functions such as signal feature display, signal acquisition parameter setting, identification object selection, data communication, and data persistence. Experiments have proved that the system is simple to operate, stable in operation, and strong in scalability.

Key words： metrology electronic buzzer detection wavelet denoising ResNet PyQt5

Received: 13 October 2021 Published: 14 November 2022

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	WEN Yi-kai
	CHEN Le
	FU Ya-qiong

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WEN Yi-kai,CHEN Le,FU Ya-qiong. Design of Abnormal Electronic Beep Recognition System Based on Wavelet Denoising and ResNet Classification Network[J]. Acta Metrologica Sinica, 2022, 43(11): 1486-1491.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2022.11.15 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2022/V43/I11/1486

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