| 基于GA-PSO-BP的发电机组故障诊断 |
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| 引用本文： | 钱玉良,张浩,彭道刚,夏飞.基于GA-PSO-BP的发电机组故障诊断[J].华东电力,2012(7):1214-1217. |
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| 作者姓名： | 钱玉良 张浩 彭道刚 夏飞 |
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| 作者单位： | 同济大学电子与信息工程学院;上海电力学院电力与自动化工程学院 |
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| 基金项目： | 国家自然科学基金重点项目(61034004);上海市“创新行动计划”部分地方院校能力建设专项项目(10250502000);上海市教育委员会科研创新重点项目(12ZZ177)~~ |
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| 摘 要： | 介绍了一种具有遗传算法中的选择、交叉、变异操作的遗传—粒子群算法(GA-PSO),解释了用于BP神经网络的参数优化过程。阐述了通过转子振动试验台上的仿真将GA-PSO-BP用于发电机组故障诊断的测试,表明GA-PSO-BP在训练速度及诊断准确率等方面优于传统BP及PSO-BP。
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| 关 键 词： | BP神经网络 遗传-粒子群算法(GA-PSO) 发电机组 故障诊断 |
Generator Unit Fault Diagnosis Based on GA-PSO-BP |
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| QIAN Yu-liang,ZHANG Hao,PENG Dao-gang,XIA Fei.Generator Unit Fault Diagnosis Based on GA-PSO-BP[J].East China Electric Power,2012(7):1214-1217. |
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| Authors: | QIAN Yu-liang ZHANG Hao PENG Dao-gang XIA Fei |
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| Affiliation: | 1,2(1.School of Electronics and Information,Tongji University,Shanghai 201804,China;2.School of Electric Power and Automation Engineering,Shanghai University of Electric Power,,Shanghai 200090,China) |
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| Abstract: | This paper introduces the GA(genetic algorithm)-PSO(particle swarm optimization) algorithm,which can perform the GA operations of selection,crossover and mutation,and expounds the parameter optimization process applied to BP neural network.Then this GA-PSO-BP neural network is applied in fault diagnosis of generator units,and the simulation test has been conducted on rotor test-bed,which shows that GA-PSO-BP is superior to conventional BP and PSO-BP in training speed and diagnosis accuracy. |
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| Keywords: | BP neural network GA-PSO algorithm generator unit fault diagnosis |
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