摘要
针对当前液压支架放煤过程中落煤时间和落煤量监测主要依赖于人工观察、自动化程度不高的问题,提出了一种基于声源定位的落煤状态识别方法,通过声源的识别与定位得到当前落煤的液压支架位置与落煤状态。设计了基于STM32的声音传感器阵列的数据采集系统。针对传统算法识别宽带信号和多声源定位困难的问题,采用基于压缩感知的多声源宽带定位算法,通过对信号进行分解得到不同频带的定位结果。仿真结果表明,该方法能准确识别170台液压支架落煤声源位置,在信噪比(SNR)为-5 dB时双声源识别率达到98%。
Aiming at the problem of relying on manual observation for monitoring the coal dropping time and quantity during the coal unloading process of hydraulic support,which lacks automation,a coal dropping state recognition method based on sound source localization was proposed.The current position of the hydraulic support and the coal dropping state were obtained through sound source identification and localization.A data acquisition system based on an STM32 microcontroller and a sound sensor array was designed.Aiming at the difficulty of traditional algorithms in identifying broadband signals and localizing multiple sound sources,a compressive sensing-based multi-source broadband localization algorithm was adopted.By decomposing the signals,the localization results of different frequency bands were obtained.Simulation results show that the method can accurately identify the sound source locations of 170 hydraulic supports,with a dual sound sourcesrecognition rate of 98%at a signal-to-noise ratio(SNR)of-5 dB.
作者
张文
李玉鹏
袁有全
王毅
高珺
Zhang Wen;Li Yupeng;Yuan Youquan;Wang Yi;Gao Jun(Huangling Jianzhuang Coal Mining Co.,Ltd.,Shaanxi Coal and Chemical Industry Group,Yan’an 719315,China;CCTEG Xi’an Research Institute(Group)Co.,Ltd.,Xi’an 710077,China)
出处
《煤矿机械》
2024年第3期180-185,共6页
Coal Mine Machinery
关键词
放顶煤
液压支架
声源识别
压缩感知
嵌入式系统
top-coal caving
hydraulic support
sound source identification
compressive sensing
embedded system
