一种基于阵列多波束的听觉煤矸识别方法
By combining an auditory sensor array with a deep learning network, the problem of environmental noise interference in coal gangue identification was solved, achieving efficient and accurate coal gangue identification and automated control.
CN120748438BActive Publication Date: 2026-07-17HUANENG COAL TECH RES CO LTD +1
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HUANENG COAL TECH RES CO LTD
- Filing Date
- 2025-06-20
- Publication Date
- 2026-07-17
AI Technical Summary
Technical Problem
In existing technologies, coal gangue identification in fully mechanized longwall mining suffers from problems such as unsafe manual control, low efficiency, and insufficient accuracy due to the complex underground environment and equipment noise interference.
Method used
An auditory sensor array is used for coal gangue identification. Beamforming algorithms and deep learning networks are used to reduce environmental noise interference and improve identification accuracy.
Benefits of technology
It enables efficient and accurate coal and gangue identification in complex underground environments, improves the identification rate and reduces manual intervention, and supports unmanned and automated control.
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure CN120748438B_ABST
Abstract
本发明提供一种煤矸识别方法，所述方法包括：首先，确定听觉传感器阵列的布局；接着，采集煤矸音频信号，得到各阵元接收信号；然后，对各阵元接收信号实施波束形成算法，获得波束形成信号中表征煤矸差异性信息的音频特征；接着将得到的音频特征进行处理，得到包含煤矸音频特征的多维张量矩阵χ；最后以多维张量矩阵χ作为输入，使用深度学习网络对煤矸进行识别，得到煤矸识别结果。本发明提供的听觉煤矸识别方法采用听觉传感器阵列，通过对目标区域的音频信号实施波束形成，能够显著减少噪声以及井下设备干扰等因素对煤矸音频识别的影响；并结合分类识别模型对煤矸进行智能识别，提高了煤矸识别准确率。
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