基于听觉特征融合的煤矸识别方法研究

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Abstract Aiming at the problem that it is difficult to recognize the caving coal gangue in the process of fully mechanized caving mining under the background of strong noise, a coal and gangue recognition method fusing low-level auditory feature Mel spectrum and high-level auditory feature auditory neurotransmitter firing rate is proposed. Firstly, according to the frequency spectrum characteristics of the sound signal of the tail beam of collapsed coal and gangue impact hydraulic support, an auditory model suitable for the coal gangue recognition task is established based on the auditory neural filter bank model. Then, the auditory model is used to analyze the sound signal of collapsed coal and gangue to obtain auditory neurotransmitter firing rate. Afterwards, the auditory neurotransmitter firing rate is fused with the peak feature extracted by Mel spectrum to obtain the auditory perception diagram of coal and gangue sound. Finally, coal and gangue were recognized with the ConvNeXt model based on the fusion auditory features constructed. The experimental results showed that the proposed coal and gangue recognition method with fusion auditory features had high recognition accuracy under different signal-to-noise ratios, and its superiority was particularly evident under the condition of large background noise (signal-to-noise ratio of -5dB), with accuracy reaching 91.52%, which was significantly superior to the method using low-level auditory features and spectrum as recognition features and using time-frequency domain features combined with machine learning, verifying the robustness of the proposed method to noise.

Key words： top coal caving coal gangue recognition auditory model auditory neurotransmitter feature fusion convolutional neural network

Received: 30 May 2023 Published: 28 April 2024

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	Articles by authors
	YANG Zheng1
	WANG Shibo1
	2
	RAO Zhushi3
	YANG Shanguo1
	2
	YANG Jianhua1
	2
	LIU Songyong1
	2
	LIU Houguang1
	2

Cite this article:

YANG Zheng1,WANG Shibo1,2, et al. Research on coal and gangue recognition method based on auditory feature fusion[J]. JOURNAL OF VIBRATION AND SHOCK, 2024, 43(8): 136-144.

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http://jvs.sjtu.edu.cn/EN/ OR http://jvs.sjtu.edu.cn/EN/Y2024/V43/I8/136

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