摘要
针对高湿、高粉尘、易腐蚀的恶劣工作环境下管状带式输送机齿轮箱早期微弱故障特征提取困难的问题,提出了基于改进变分模态分解(VMD)的带式输送机齿轮箱故障诊断方法。首先利用齿轮箱故障机理模型确定模态分量个数,通过优化搜索选择最优的频带惩罚因子,得到最优的满足适应度函数的分解参数组合,克服了人为随机设置分解参数对分解结果带来的不确定性;然后利用参数优化后的VMD对齿轮箱故障信号进行分解,并对各个分量进行包络解调分析来提取齿轮故障特征。仿真信号和工程实际信号的分析结果表明,该方法能够准确、清晰地提取齿轮箱故障特征。
Aiming at the problem of fault feature extraction in the early stage of tubular belt conveyor gearbox under the harsh working environment of high humidity,high dust and easy corrosion,a fault diagnosis method based on improved variational modal decomposition(VMD) was proposed.Firstly the number of modal components was determined by using the gearbox fault mechanism model,and the optimal frequency band penalty factor was selected through optimization search to obtain the optimal decomposition parameter combination satisfying the fitness function,which overcomes the uncertainty of the decomposition results caused by artificially setting the decomposition parameters randomly.Then the optimized VMD was used to decompose the gearbox fault signal,and the envelope demodulation analysis was carried out for each component to extract the gear fault characteristics.The analysis results of simulation signals and engineering signals show that this method can extract gearbox fault features accurately and clearly.
作者
王艳双
王建华
任磊
史更新
彭程程
臧廷朋
肖望强
Wang Yanshuang;Wang Jianhua;Ren Lei;Shi Gengxin;Peng Chengcheng;Zang Tingpeng;Xiao Wangqiang(Zhungeer Energy Group Co.,Ltd.,CHN Energy Group,Ordos 017000,China;CHN Energy Lucency Enviro-Tech Co.,Ltd.,Beijing 100039,China;School of Aerospace Engineering,Xiamen University,Xiamen 361000,China)
出处
《煤矿机械》
2022年第10期177-179,共3页
Coal Mine Machinery
基金
国家自然科学基金项目(51875490)。