基于BP神经网络的煤矿电机故障诊断预测

Fault Diagnosis Prediction of Mine Motor Based on BP Neural Network

电机软故障辨识诊断一直是困扰电机维修工程师一大难题。引入BP神经网络概念,利用采集到的样本数据训练BP神经网络,得出最优网络模型。通过典型故障状态参数测试新方法的辨别能力。结合对煤矿电机参数的训练测试,通过仿真实验验证了这种新方法对电气故障诊断的有效性。

The motor maintenance engineer has plagued by the identification diagnosis of motor soft fault. The paper introduces the concept of BP neural network, and uses the sample data collected to train BP neural network, and then obtains the optimal network model. The typical fault state parameter is used to test the discrimination ability of the new method. By the training and test of coal mine motor parameters, the simulation can verify the effectiveness of the new method for electric fault diagnosis.