摘要
为提高放顶煤的自动化和智能化水平,实现综放工作面的少人化和无人化,利用自主研制的测振记录仪,获得了不同测点处煤矿井下综放工作面顶煤、矸石与顶板岩石垮落等工况下,液压支架后尾梁与后部刮板输送机的振动信号时域指标,经统计分析发现方差、偏度与峭度指标对工况变化敏感,可作为综放工作面煤岩性状识别的评判依据,其中峭度指标最为敏感,分析了液压支架后尾梁与后部刮板输送机振动信号获取的难易程度,得出液压支架后尾梁更适合作为综放工作面煤岩性状识别的测点。
In order to improve the automation and intelligence of top coal caving, and lay a foundation to realize the target of less quantities of workers even no worker in the fully-mechanized top coal caving face, using the self-developed mine portable vibration data recorder, the time-domain indexes of vibration signals at the hydraulic support tail beam and the rear scraper conveyor were acquired under the different conditions of coal caving, gangue caving and roof rock caving in the fully-mechanized top coal caving face.The above signals were extracted and comparatively analyzed,some conclusions were drawn that the variance,skewness and kurtosis index of the vibration signals were sen- sitive to working condition changes,and the kurtosis index was the most sensitive.These indexes could be used as the evaluation indicator for the coal and rock character recognition in the fully-mechanized top coal caving face.Due to the complexity of the vibration signal acqui- sition,the measure pointed at the rear tail beam of sublevel caving hydraulic support was more suitable than the rear scraper conveyor for the coal and rock trait identification in the fully-mechanized top coal caving face.
出处
《煤炭科学技术》
CAS
北大核心
2015年第12期92-97,共6页
Coal Science and Technology
基金
国家重点基础研究发展计划(973计划)资助项目(2014CB046300)
中央高校基本科研业务费专项基金资助项目(2009QJ16)
关键词
煤岩性状识别
时域特征
振动信号
综放工作面
coal and rock character recognition
time-domain characteristic
vibration signal
fully-mechanized top coal caving face
作者简介
薛光辉（1977-），男，河南汝州人，副教授，硕士生导师，博士，现任中国矿业大学（北京）机电与信息工程学院测控技术与仪器系主任。
