在煤矿生产领域中，矿井提升机作为一种辅助运输的设备，在矿井整个运输工程中承担着非常重要的作用，其安全性和稳定性直接影响着煤矿生产效率和井下工作人员生命安全。矿井提升机故障发生后，其声音信号也会随着设备运行状态而改变，因此可以通过分析该声音的特征来检测设备是否处于不正常运行状态。鉴于此提出了基于MFCC-CS-MUSIC实现的矿井提升机故障源精准识别方法。通过采集提升机音频信号，应用MFCC（梅尔频率倒谱系数）算法提取多个通道声音信号梅尔频率倒谱系数进行故障识别；应用MUSIC（多信号分类）故障识别后的音频信号进行定位求得信号的最小化波达方向。将MUSIC算法求得的DOA（波达方向定位）值作为优化变量，以计算DOA和测量DOA之间的差异为目标函数，利用CS（布谷鸟）算法对目标函数进行寻优，从而实现对提升机故障源精准定位。试验和应用结果均表明，利用CS算法优化后MUSIC算法得到的定位坐标误差Δψ在5°以内，实际位置坐标方位角误差Δθ在4°以内。该方法实现了提升机故障准确识别和提升机故障源的精准定位，大幅缩短了排查矿井提升机故障位置的时间，显著提升了矿井提升机的工作效率。

In the field of coal mine production, the mine hoist, as a kind of auxiliary transportation equipment, plays a very important role in the whole transportation engineering of the mine. Its safety and stability directly affect the production efficiency of the coal mine and the safety of underground workers. After the failure of mine hoist, its sound signal will also change with the operation state of the equipment, so the abnormal operation state of the equipment can be detected by analyzing the characteristics of the sound. In order to ensure its safe and reliable operation and improve coal mine transportation efficiency, an accurate fault identification method of mine hoist based on MFCCS-MUSIC was proposed. By collecting the hoist audio signals, MFCC algorithm was used to extract the Cepstrum coefficients of multiple channels for fault identification. The acoustic signal after MUSIC fault identification is used to locate the signal and the minimal direction of arrival is obtained. The DOA value obtained by MUSIC algorithm is taken as the optimization variable, the difference between calculating DOA and measuring DOA is taken as the objective function, and the CS algorithm is used to optimize the objective function, so as to realize the precise location of the hoist fault source. The experimental and application results show that the azimuth error Δψ between the music algorithm and the actual position coordinate after CS algorithm optimization is less than 5°, Δθ is less than 4°. This method can accurately identify the hoist fault and accurately locate the hoist fault source, greatly shorten the troubleshooting time of the mine hoist fault location, and significantly improve the work efficiency of the mine hoist.

0 引言 1 矿井提升机故障识别算法分析 2 CS优化的MUSIC定位算法 2.1 CS-MUSIC算法分析 2.2 CS-MUSIC定位 3 应用实例分析 3.1 矿井提升机故障源精准定位系统设计 3.2 矿井提升机结构 3.3 数据样本分析 3.4 故障识别结果分析 4 结语