School of Electromechanic and Information, China University of Mining and Technology (Beiing)

针对现有煤岩硬度性状识别方法不能满足采煤机滚筒实现自动调高技术的需要,提出摇臂振动信号时频域能量特征识别煤岩硬度的方法。采用自主研发并取得煤安认证的矿用振动加速度传感器开展井下测试,以综采工作面采煤机摇臂处实测振动加速度信号为研究对象,利用小波包信号分析方法,得到第3层4个频率成分的时频域分解信号,根据系数重构后的函数表达式,计算各个频段内的信号能量作为特征向量,确定采煤机截割煤岩时摇臂振动特征。MG180/420-BWD薄煤层采煤机在兖矿集团南屯煤矿测试结果表明,小波包时频域能量特征向量对截割煤岩硬度敏感,该特征向量间接判定截割工况效果良好。

According to the available character identification method of the coal and rock hardness could not meet the requirements of the automatic height- adjust ment technology realized by the cutting drum of the coal shearer, an identification method of the coal and rock hardness was provided with the energy features of the vi bration signal time- frequency domain in the ranging boom. A self developed mine vibration accelerometer with a MA certificate was applied to the tests in the undergro und mine. With the vibration acceleration signal measured at the ranging boom of the coal shearer in the fully mechanized coal mining face as the study object, the wav elet packet signal analysis method was applied to have the solution signal of the time- frequency domain with four frequency contents from No.3 strata. According to th e function expression after the coefficient restructured, the signal energy at each frequency section was calculated as the eigenvector and was applied to determine the vibration features of the ranging boom during the coal and rock cutting period of the coal shearer. Based on the measured data of MG180 1420- BWD thin seam shearer operated in Nantun Mine of Yanzhou Coal Mining Group, The results showed that the energy feature vector of the wavelet packet time- frequency domain would be sens itive to the hard.

国家重点基础研究发展计划(973计划)资助项目(2014CB046306)；