摘要
研究声学信号处理技术在煤矿设备安全监控中的应用,提出一种基于声学信号特征提取与异常检测的监控方法。通过多模态特征分析和对比学习模型,实现对煤矿设备运行状态的实时监控与隐患识别。实验结果表明,该方法在不同煤矿设备和运行工况下表现出高准确率、低误报率以及快速响应能力,为煤矿设备安全运行提供可靠的技术支持。
The application of acoustic signal processing technology in coal mine equipment safety monitoring is studied,and a monitoring method based on acoustic signal feature extraction and anomaly detection is proposed.Through multi-modal feature analysis and comparative learning model,the real-time monitoring and hidden danger identification of coal mine equipment operation state are realized.The experimental results show that this method has high accuracy,low false alarm rate and fast response ability under different coal mine equipment and operating conditions,which provides reliable technical support for the safe operation of coal mine equipment.
作者
郝晓宇
赵国
HAO Xiaoyu;ZHAO Guo(Shanxi Heshun Tianchi Energy Co.,Ltd.,Jinzhong 032700,China)
出处
《电声技术》
2025年第5期191-193,共3页
Audio Engineering
关键词
声学信号处理技术
煤矿设备
安全监控
acoustic signal processing
coal mine equipment
safety monitoring
