故障诊断论文数据挖掘在光纤故障诊断中的应用研究.docVIP

故障诊断论文：数据挖掘在光纤故障诊断中的应用研究 【中文摘要】随着计算机和网络技术的迅猛发展,人们的社会活动越来越依赖于通信网络。这就需要提供和支撑这些数据交互的网络平台具有更高的可靠性和稳定性。通信的载体光纤具有通信容量大、中继距离长、必威体育官网网址性能好、适应能力强等优点,但是一旦发生故障,其造成的损失也是无法想象的。由于光纤出现故障后影响比较大,光纤故障诊断又是网络故障管理的难点和关键,所以光纤故障管理技术被国内外学者广为研究。目前,数据挖掘应用于故障诊断已经有许多成功的例子。BP神经网络是数据挖掘研究中的一个重要课题,选取BP神经网络技术来实现光纤故障诊断预测功能,可把具有复杂因果关系的物理量在经过适当数量的训练之后较准确地反映出来。本文的主要工作体现在以下几个方面:(1)基于VS2003平台,开发了光纤自动切换保护系统,实现了对通信光纤的实时监测,将光功率值上报给系统的主控模块,并存入历史记录表中,为之后的数据挖掘做好数据采集工作。主控模块对上报的数据与预设门限进行比较,实现自动控制。(2)实时绘制光功率变化曲线,直观地显示传输系统中光纤的光功率变化情况,通过观察光纤光功率曲线变化,用户可以判断光纤运行的稳定性。(3)在研究BP算法的基础上,对BP算法进行改进,对实际的网络模型进行样本选择,构造训练样本;对所选择的样本进行规范化预处理;选择三层神经网络,确定网络的输入输出结点数及隐含层结点数;确定合适的学习率。构造合适的BP神经网络后,对光功率值进行挖掘预测,并对预测结果进行分析。经实验表明,采用BP神经网络对光纤故障诊断进行数据挖掘是可行的。 【英文摘要】With the rapid development of computer and network techniques, people’s social activities become more dependent on communication network. This requires the network platform which provides and supports datas exchange to be more dependable and stable. The carrier of communications is optical-fiber, it has many advantages, such as communication capacity, long-distance relay, security performance, adaptability, etc; but in the event of failure, the loss is beyond imagination. As the impact of fiber failure is relatively large, the fault diagnosis of fiber-optic is also difficult and critical in the Network Fault Management, so fiber-optic fault management technology is widely studied by foreign scholars.Currently, there are many successful data mining application examples at home and abroad in fault diagnosis. BP neural network is an important issue of data mining. Selecting BP neural network technology to realize fault diagnosis capabilities of fiber, some physical quantity with complex causal relationship can be accurately reflected after the training of appropriate times.The main job of this paper is as following: (1) Develope an automatic switching protection system of optical-fiber based on VS2003 platform, it achieves real-time monitoring of optical-fiber communication, then sends opti