基于改进的GA优化BP神经网络的煤矿设备的故障诊断
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摘要
面对越来越多的煤矿设备出现的故障,本文提出了将遗传算法(GA)和BP神经网络结合进行预测的方法。针对遗传算法存在收敛速度慢,容易陷入局部最优的情况,本文首先采用混沌和反向学习初始化个体,其次运用差分算法对个体最优进行操作,最后,将改进的适应度函数运用到选择操作中,通过变异概率和交叉概率提高操作的准确率。将改进后的算法运用到BP神经网络中提高了样本训练效果,仿真实验表明本文算法相比于传统BP神经网络提高了精度和增强了稳定性
In the face of more and more coal mine equipment failure, this paper proposes a method of combining genetic algorithm(GA) and BP neural network. For genetic algorithm, the convergence speed is slow and easy to fall into local optimum. In this paper, we first use chaos and backward learning to initialize the individual. Secondly, we use the differential algorithm to operate the individual. Finally, the improved fitness function is applied to the selection operation. The improved algorithm is applied to the BP neural network to improve the training effect. The simulation results show that the proposed algorithm can improve the accuracy and stability compared with the traditional BP neural network.
In the face of more and more coal mine equipment failure, this paper proposes a method of combining genetic algorithm(GA) and BP neural network. For genetic algorithm, the convergence speed is slow and easy to fall into local optimum. In this paper, we first use chaos and backward learning to initialize the individual. Secondly, we use the differential algorithm to operate the individual. Finally, the improved fitness function is applied to the selection operation. The improved algorithm is applied to the BP neural network to improve the training effect. The simulation results show that the proposed algorithm can improve the accuracy and stability compared with the traditional BP neural network.
引文
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[3]刘丽丽,蒋玉凤,魏振长.基于差分进化算法在煤矿水泵故障诊断中的应用[J].矿山机械,2015,43(1):113-115.
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[5]薛彦波.基于小波变换的煤矿井下水泵故障诊断[J].煤矿机械,2015,36(4):307-309.
[6]张涛,罗奕.基于权值优化的BP神经网络的煤矿配电网故障诊断[J].煤矿机械,2015,36(5):309-311.
[7]高兵兵,蒋占四,张应红.煤矿风机小波神经网络故障诊断系统研究[J].煤矿机械,2014,35(3):227-228.
[8]陈婀娜.尺度自适应提升小波变换在煤矿电机轴承故障诊断中应用[J].煤矿机械,2014,35(1):237-238.
[9]张飞,何雅琴,张珂.改进BP网络在煤矿通风系统故障检测中的应用[J].工矿自动化,2013,39(3):61-63.
[10]Afshar M H.Rebirthing genetic algorithm for storm sewer network desing[J].Scientia Iranica,2012,19(1):11-19.
[2]赵华玮.基于能量算子的煤矿机电设备故障诊断方法[J].煤炭技术,2015,34(9):253-254.
[3]刘丽丽,蒋玉凤,魏振长.基于差分进化算法在煤矿水泵故障诊断中的应用[J].矿山机械,2015,43(1):113-115.
[4]董晓钧.煤矿井下机械设备管理与故障诊断[J].煤炭工程,2015,47(1):63-65.
[5]薛彦波.基于小波变换的煤矿井下水泵故障诊断[J].煤矿机械,2015,36(4):307-309.
[6]张涛,罗奕.基于权值优化的BP神经网络的煤矿配电网故障诊断[J].煤矿机械,2015,36(5):309-311.
[7]高兵兵,蒋占四,张应红.煤矿风机小波神经网络故障诊断系统研究[J].煤矿机械,2014,35(3):227-228.
[8]陈婀娜.尺度自适应提升小波变换在煤矿电机轴承故障诊断中应用[J].煤矿机械,2014,35(1):237-238.
[9]张飞,何雅琴,张珂.改进BP网络在煤矿通风系统故障检测中的应用[J].工矿自动化,2013,39(3):61-63.
[10]Afshar M H.Rebirthing genetic algorithm for storm sewer network desing[J].Scientia Iranica,2012,19(1):11-19.