GA-BP神经网络在带式输送机故障监测系统中的应用  

Application of GA-BP Neural Network in Fault Monitoring System of Belt Conveyor

作　　者：张金红[1] 王菲菲 武玉英[1] Zhang Jinhong;Wang Feifei;Wu Yuying(Hebei College of Industry and Technology,Shijiazhuang 050091,China)

机构地区：[1]河北工业职业技术学院,石家庄050091

出　　处：《煤矿机械》2020年第12期129-131,共3页Coal Mine Machinery

摘　　要：为提高带式输送机故障监测系统的识别精度,利用遗传算法(GA)改进BP神经网络,将GA-BP神经网络应用于带式输送机故障监测系统中。分析了带式输送机常见故障及目前故障监测系统存在的不足,运用GA全局搜索能力和内在并行性,建立基于GA-BP神经网络的输送机故障监测系统模型,优化网络结构,克服了BP神经网络易陷入局部最小化、收敛速度慢的缺点。MATLAB仿真实验结果表明,该模型收敛速度快,故障识别准确度高,可应用于带式输送机的故障监测系统中。In order to improve the recognition accuracy of the fault monitoring system of belt conveyor,the BP neural network was improved by genetic algorithm(GA),and the GA-BP neural network was applied to the fault monitoring system of belt conveyor.Analyzed the common faults of belt conveyor and the shortcomings of the current fault monitoring system.By using the global search ability and internal parallelism of GA,the model of conveyor fault monitoring system based on GA-BP neural network was established,and the network structure was optimized.The shortcomings of BP neural network easily falling into local minimization and slow convergence speed were overcome.The simulation results of MATLAB show that the model is with fast convergence and high accuracy of fault identification,which can be used in the fault monitoring system of belt conveyor.

关 键 词：GA BP神经网络 故障识别 

分 类 号：TD528.1[矿业工程—矿山机电]