基于LM-BP神经网络的采煤机液压系统故障诊断研究  

Research on Fault Diagnosis of Shearer Hydraulic System Based on LM-BP Neural Network

作　　者：芮雪 吴德佩[2] RUI Xue;WU Depei(Changzhi Vocational and Technical College,Changzhi 046000,China;School of Computer and Artificial Intelligence,Zhengzhou University,Zhengzhou 450000,China)

机构地区：[1]长治职业技术学院,山西长治046000 [2]郑州大学计算机与人工智能学院,郑州450000

出　　处：《煤炭技术》2023年第7期187-189,共3页Coal Technology

摘　　要：针对采煤机液压系统故障率高,故障种类多样的问题,使用基于LM-BP神经网络对采煤机液压系统故障进行故障诊断。首先对常见故障类型进行分类,制作故障样本库,然后设计并训练基于LM-BP神经网络的采煤机液压系统故障分类模型,最后与BP神经网络模型性能对比,结果表明,模型的故障辨识率和识别速度更好。Aiming at the problems of high failure rate and various types of faults in the hydraulic system of the shearer,the fault diagnosis of the hydraulic system of the shearer based on LM-BP neural network is used.First,the common fault types are classified,and the fault sample database is made.Then,the fault classification model of the shearer hydraulic system based on the LM-BP neural network is designed and trained.Finally,the performance of the model is compared with the BP neural network model,rate and recognition speed are better.

关 键 词：LM-BP神经网络 采煤机液压系统 故障诊断 BP神经网络 

分 类 号：TD421[矿业工程—矿山机电] TP183[自动化与计算机技术—控制理论与控制工程]