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.
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2022, Vol. 43 
