为了提高纯电动汽车电驱总成的故障诊断准确率,提出了一种基于粒子群优化(Particle Swarm Optimizing,PSO)算法的改进BP(Improved Back Propagation,IBP)神经网络(PSO-IBP)故障诊断方法。应用线性整流单元(Rectified Linear Unit,ReLU)...为了提高纯电动汽车电驱总成的故障诊断准确率,提出了一种基于粒子群优化(Particle Swarm Optimizing,PSO)算法的改进BP(Improved Back Propagation,IBP)神经网络(PSO-IBP)故障诊断方法。应用线性整流单元(Rectified Linear Unit,ReLU)作为BP神经网络的激活函数,通过粒子群优化算法对BP神经网络权值和阈值进行动态寻优,构建PSO-IBP模型。通过采集纯电动汽车电驱总成故障数据,分别对PSO-IBP神经网络模型、BP神经网络模型和概率神经网络(Probabilistic Neural Network,PNN)模型进行训练与仿真,结果表明,相比于BP神经网络方法及概率神经网络方法,基于PSO-IBP神经网络模型的纯电动汽车电驱总成故障诊断方法具有更高的准确率。展开更多
Based on the back progpagation neural network (BPNN) applied for transformer fault diagnosis, an improved algorithm of BPNN is introduced, and some basic conceptions of data reliability analysis are adopted to pre pro...Based on the back progpagation neural network (BPNN) applied for transformer fault diagnosis, an improved algorithm of BPNN is introduced, and some basic conceptions of data reliability analysis are adopted to pre process the input data of BPNN. The results of verification show that satisfactory accuracy and good application of this method could be acquired.展开更多
文摘为了提高纯电动汽车电驱总成的故障诊断准确率,提出了一种基于粒子群优化(Particle Swarm Optimizing,PSO)算法的改进BP(Improved Back Propagation,IBP)神经网络(PSO-IBP)故障诊断方法。应用线性整流单元(Rectified Linear Unit,ReLU)作为BP神经网络的激活函数,通过粒子群优化算法对BP神经网络权值和阈值进行动态寻优,构建PSO-IBP模型。通过采集纯电动汽车电驱总成故障数据,分别对PSO-IBP神经网络模型、BP神经网络模型和概率神经网络(Probabilistic Neural Network,PNN)模型进行训练与仿真,结果表明,相比于BP神经网络方法及概率神经网络方法,基于PSO-IBP神经网络模型的纯电动汽车电驱总成故障诊断方法具有更高的准确率。
文摘Based on the back progpagation neural network (BPNN) applied for transformer fault diagnosis, an improved algorithm of BPNN is introduced, and some basic conceptions of data reliability analysis are adopted to pre process the input data of BPNN. The results of verification show that satisfactory accuracy and good application of this method could be acquired.
