作者：韩文虹, 高淑婷

作者单位：河南农业职业学院电子信息工程系, 河南 郑州 451450

关键词：传感器节点; 故障诊断; 免疫遗传; BP神经网络

摘要：

为实现对节点进行实时有效的故障诊断,提出一种基于SOM自组织网映射算法和免疫遗传神经网络的故障诊断方法。首先,设计节点故障诊断的通用模型;然后采用自组织网映射(self organize mapping,SOM)算法对故障特征数据进行离散化以提高诊断模型的泛化性能,并通过主成分分析法(principal component analysis,PCA)对特征数据属性进行约简以减少数据量;最后,建立三层的BP神经网络节点故障诊断模型,并通过免疫遗传算法(immune gene algorithm,IGA)对BP神经网络优化从而得到最终优化的节点故障诊断模型。仿真实验证明该法能有效进行故障诊断,且与其他方法相比,具有诊断效率高和精度高的优点。

Fault diagnosis of sensor node based on SOM and immune gene algorithm optimizing neural network

HAN Wen-hong, GAO Shu-ting

Department of Electronic and Information Engineering, Henan Vocational College of Agriculture, Zhengzhou 451450, China

Abstract: In order to diagnose the fault in real-time and effectively, a fault diagnosis method based on SOM algorithm and immune gene neural network was proposed. Firstly, the general model for node fault diagnosis was designed, and then the SOM algorithm was used to get the discrete data to improve the generalization ability of the diagnosis model, and PCA (principal component Analysis) was used to reduce the dimension of data. Finally, the three layer node diagnosis model was built, and the improved immune gene algorithm was designed to train the network and the final node diagnostic mode was obtained. The simulation result shows that the proposed method can achieve sensor nodes fault diagnosis effectively and compared with other methods, it can diagnose node fault accurately in a shorter time.

Keywords: sensor node; fault diagnosis; immune gene; BP neutral network

2014, 40(5): 88-91  收稿日期: 2013-10-16;收到修改稿日期: 2013-12-3

基金项目: 

作者简介: 韩文虹(1968-),女,河南南阳市人,副教授,硕士,研究方向为自动控制。

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