| 基于改进BP的煤矿供电系统故障诊断研究 |
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| 引用本文： | 窦新宇.基于改进BP的煤矿供电系统故障诊断研究[J].唐山学院学报,2016,29(3):28-30. |
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| 作者姓名： | 窦新宇 |
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| 作者单位： | 唐山学院 智能与信息工程学院, 河北 唐山 063020 |
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| 基金项目： | 2014年度唐山市科技计划项目(14110212a) |
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| 摘 要： | 针对煤矿供电系统故障的特点,以开关、保护等信息为基础,将粗糙集理论与BP神经网络相结合建立煤矿供电系统故障诊断模型。首先通过遗传算法对供电系统故障中的决策表进行约简,去掉冗余信息,保留必要的要素,使神经网络输入神经元数目减少,结构得到优化;然后在训练过程中应用思维进化算法优化神经网络的权值和阈值,并对处理后的信息进行诊断。仿真结果证明,该故障诊断系统有效地提高了诊断效率,增强了故障诊断的容错能力。
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| 关 键 词： | 煤矿供电系统 粗糙集 神经网络 故障诊断 |
A Fault Diagnosis of the Coal Mine Power Supply System Based on the Improved BP Neural Network |
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| DOU Xin-yu.A Fault Diagnosis of the Coal Mine Power Supply System Based on the Improved BP Neural Network[J].Journal of Tangshan College,2016,29(3):28-30. |
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| Authors: | DOU Xin-yu |
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| Institution: | College of Intelligence and Information Engineering, Tangshan University, Tangshan 063020, China |
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| Abstract: | In view of the fault characteristics of the coal mine power supply system and on the basis of switches and protection, the author of this paper has created a fault diagnosis model for the power supply system in coal mines by combining rough set theory with BP neural network. Firstly the decision table of the fault diagnosis of the power supply system has been simplified by removing the redundant information and retaining only the necessary elements with genetic algorithm, which has reduced the number of neural network input neurons and improved the structure. Then, in the training process, the weights and thresholds of the neural network have been optimized with the thought evolution algorithm and the processed information is diagnosed. The simulation results show that the fault diagnosis system can effectively improve the diagnostic efficiency and increase the capacity for fault diagnosis. |
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| Keywords: | coal power supply system rough sets theory neural network fault diagnosis |
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