采煤机截割部传动系统故障信号小波包分解方法研究
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摘要
采煤机主要通过截割部上的滚筒截割煤岩,若其传动系统发生故障将导致采煤工作中断,造成巨大的经济损失。以MG2×70/325采煤机为依托,采用PRO/E建立了断齿、裂纹齿轮和缺陷轴承等常见故障模型,利用ANSYS及ADAMS建立了引入故障形式的采煤机截割部刚柔耦合虚拟样机模型,提取各惰轮轴轴向和径向受力数据,作为建立故障诊断系统的样本。用Coif4小波对数据进行小波包分解,求各子带能量值,作为神经网络输入向量,结合Elman神经网络建立采煤机截割煤岩时的故障诊断模型,仿真结果表明:该方法可有效地诊断传动系统的故障零件和类型,对于复杂工况下,采煤机故障检测以及在线实时监测具有一定的指导意义。
The shearer cut coal and rock mainly through the drum on the cutting unit. If the transmission system fails, the mining work will be interrupted, resulting in huge economic losses. Based on MG2×70/325 shearer, the common fault models of broken teeth, cracked gears and defective bearings were established by PRO/E, and the rigid-flexible coupling virtual prototype model of shearer cutting unit was established by using ANSYS and ADAMS. The axial and radial force data of each idler shaft were extracted as samples to establish the fault diagnosis system. Coif4 wavelet was used to decompose the data, and the energy value of each sub-band was obtained as the input vector of neural network. Combined with Elman neural network, the fault diagnosis model of shearer cutting coal and rock was established.The simulation results showed that this method can effectively diagnose the fault parts and types of transmission system, and has certain guiding significance for shearer fault detection and on-line real-time monitoring under complex working conditions.
The shearer cut coal and rock mainly through the drum on the cutting unit. If the transmission system fails, the mining work will be interrupted, resulting in huge economic losses. Based on MG2×70/325 shearer, the common fault models of broken teeth, cracked gears and defective bearings were established by PRO/E, and the rigid-flexible coupling virtual prototype model of shearer cutting unit was established by using ANSYS and ADAMS. The axial and radial force data of each idler shaft were extracted as samples to establish the fault diagnosis system. Coif4 wavelet was used to decompose the data, and the energy value of each sub-band was obtained as the input vector of neural network. Combined with Elman neural network, the fault diagnosis model of shearer cutting coal and rock was established.The simulation results showed that this method can effectively diagnose the fault parts and types of transmission system, and has certain guiding significance for shearer fault detection and on-line real-time monitoring under complex working conditions.
引文
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[10]刘晓乐,刘后广,程刚,等.基于ADAMS的两级行星齿轮断齿故障动态特性分析[J].机械传动,2015,39(6):98-102.LIU Xiaole,LIU Houguang,CHENG Gang,et al.Dynamic characteristic analysis of two-stage planetary gear with broken tooth fault based on ADAMS[J].Journal of Mechanical Transmission,2015,39(6):98-102.
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[12]周久华.神东矿区采煤机故障统计与原因分析[J].煤炭科学技术,2015,43(增刊2):139-143.ZHOU Jiuhua.Fault statistics and causes analysis on coal shearer in Shendong mining area[J].Coal Science and Technology,2015,43(Sup 2):139-143.
[13]SAIDI L,BEN A J,BENBOUZID M,et al.The use of SESK as a trend parameter for localized bearing fault diagnosis in induction machines[J].Isa Transactions,2016,63:436-447.
[14]SMITH W A,RANDALL R B.Rolling element bearing diagnostics using the Case Western Reserve University data:a benchmark study[J].Mechanical Systems&Signal Processing,2015,65:100-131.
[15]刘旭南,赵丽娟,冯认金,等.薄煤层采煤机运动学参数最佳匹配问题研究[J].机械科学与技术,2017,36(11):1701-1707.LIU Xunan,ZHAO Lijuan,FENG Renjin,et al.The research on kinematic parameter optimum matching of thin coal seam shearer[J].Mechanical Science and Technology for Aerospace Engineering,2017,36(11):1701-1707.
[16]赵丽娟,田震.薄煤层采煤机振动特性研究[J].振动与冲击,2015,34(1):195-199.ZHAO Lijuan,TIAN Zhen.Vibration characteristics of thin coal seam shearer[J].Journal of Vibration and Shock,2015,34(1):195-199.
[17]张建宇,刘鑫博,张飞斌.裂纹齿轮啮合刚度的劣化特性[J].振动、测试与诊断,2014,34(6):1124-1128.ZHANG Jianyu,LIU Xinbo,ZHANG Feibin.Degradation characteristics of meshing stiffness of spur gears with root crack[J].Journal of Vibration,Measurement&Diagnosis,2014,34(6):1124-1128.
[18]卓震,刘雪东,黄宇新,等.“多点应力法”测量多级离心泵轴向力和径向力[J].流体机械,2002(10):8-10.ZHUO Zhen,LIU Xuedong,HUANG Yuxin,et al.Measuring of axial force and radial force of multistage centrifugal pump by multipoint stress method[J].Fluid Machinery,2002(10):8-10.
[2]冯泾若,杨健康,米朝阳.国内外大功率大采高采煤机技术与发展动向[J].煤矿开采,2007,12(2):13-14.FENG Jingruo,YANG Jiankang,MI Zhaoyang.Large power coal cutter for thick coal seam technique and development at home and abroad[J].Coal Mine Machinery,2007,12(2):13-14.
[3]许景崑.SIRUS-400型采煤机液压系统故障的判断和处理[J].煤矿机电,1987(1):35-38.XU Jingkun.Fault diagnosis and treatment of hydraulic system of SIRUS-400 shearer[J].Colliery Mechanical&Electrical Technology,1987(1):35-38.
[4]徐常胜,周兆英,刘思行,等.基于神经网络和专家系统的故障诊断[J].控制与决策,1995(4):342-346.XU Changsheng,ZHOU Zhaoying,LIU Sixing,et al.Fault diagnosis based on neural network and expert system[J].Control and Decision,1995(4):342-346.
[5]贺仰兴,裴兴元.采煤机械的工况监测[J].山西机械,2001(增刊1):1-3.HE Yangxing,PEI Xingyuan.Working condition monitoring of coal mining machinery[J].Shanxi Machinery,2001(Sup1):1-3.
[6]谢国民.基于时频联合小波法的采煤机关键部件故障诊断研究[D].阜新:辽宁工程技术大学,2012.
[7]彭学前.采煤机故障诊断与故障预测研究[D].南京:南京理工大学,2013.
[8]杨高宏.基于虚拟样机技术的采煤机截割减速器故障仿真研究[D].太原:太原理工大学,2009.
[9]弓晓凤,马宪民,张永强.小波包分析在采煤机减速器故障诊断中的应用[J].煤炭技术,2014,33(7):196-199.GONG Xiaofeng,MA Xianmin,ZHANG Yongqiang.Applicaiton of wavelet packet analysis in fault diagnosis of coal cutter reducer[J].Coal Technology,2014,33(7):196-199.
[10]刘晓乐,刘后广,程刚,等.基于ADAMS的两级行星齿轮断齿故障动态特性分析[J].机械传动,2015,39(6):98-102.LIU Xiaole,LIU Houguang,CHENG Gang,et al.Dynamic characteristic analysis of two-stage planetary gear with broken tooth fault based on ADAMS[J].Journal of Mechanical Transmission,2015,39(6):98-102.
[11]郝志勇,陈志强,毛君.采煤机摇臂惰轮轴载荷分析与实验研究[J].机械强度,2017,39(1):40-46.HAO Zhiyong,CHEN Zhiqiang,MAO Jun.Load analysis and experimental research of idler shaft on rocker arm shearer[J].Journal of Mechanical Strength,2017,39(1):40-46.
[12]周久华.神东矿区采煤机故障统计与原因分析[J].煤炭科学技术,2015,43(增刊2):139-143.ZHOU Jiuhua.Fault statistics and causes analysis on coal shearer in Shendong mining area[J].Coal Science and Technology,2015,43(Sup 2):139-143.
[13]SAIDI L,BEN A J,BENBOUZID M,et al.The use of SESK as a trend parameter for localized bearing fault diagnosis in induction machines[J].Isa Transactions,2016,63:436-447.
[14]SMITH W A,RANDALL R B.Rolling element bearing diagnostics using the Case Western Reserve University data:a benchmark study[J].Mechanical Systems&Signal Processing,2015,65:100-131.
[15]刘旭南,赵丽娟,冯认金,等.薄煤层采煤机运动学参数最佳匹配问题研究[J].机械科学与技术,2017,36(11):1701-1707.LIU Xunan,ZHAO Lijuan,FENG Renjin,et al.The research on kinematic parameter optimum matching of thin coal seam shearer[J].Mechanical Science and Technology for Aerospace Engineering,2017,36(11):1701-1707.
[16]赵丽娟,田震.薄煤层采煤机振动特性研究[J].振动与冲击,2015,34(1):195-199.ZHAO Lijuan,TIAN Zhen.Vibration characteristics of thin coal seam shearer[J].Journal of Vibration and Shock,2015,34(1):195-199.
[17]张建宇,刘鑫博,张飞斌.裂纹齿轮啮合刚度的劣化特性[J].振动、测试与诊断,2014,34(6):1124-1128.ZHANG Jianyu,LIU Xinbo,ZHANG Feibin.Degradation characteristics of meshing stiffness of spur gears with root crack[J].Journal of Vibration,Measurement&Diagnosis,2014,34(6):1124-1128.
[18]卓震,刘雪东,黄宇新,等.“多点应力法”测量多级离心泵轴向力和径向力[J].流体机械,2002(10):8-10.ZHUO Zhen,LIU Xuedong,HUANG Yuxin,et al.Measuring of axial force and radial force of multistage centrifugal pump by multipoint stress method[J].Fluid Machinery,2002(10):8-10.
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