Dissertation > Industrial Technology > Radio electronics, telecommunications technology > Wireless communications > Lightwave communications, laser communications > Optical fiber communication

Application and Research of Data Mining in Fiber Optic Fault Diagnosis

Author ZhaoFen
Tutor HuChaoJu
School North China Electric Power University
Course Applied Computer Technology
Keywords Fault Diagnosis Fiber failure Data Mining BP neural network
CLC TN929.11
Type Master's thesis
Year 2011
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With the rapid development of computer and network technology , people's social activities are increasingly dependent on the communication network . This need to provide and support these data interaction network platform has a higher reliability and stability . The communications carrier optical fiber communication capacity , long distance relay performance of confidentiality , adaptability advantages , but in the event of failure , caused by the loss but also can not imagine . The impact fiber failure , fiber failure diagnosis is the difficulty of network fault management and key , so the the fiber fault management technology scholars widely studied . Currently, data mining applied to fault diagnosis have many success stories . BP neural network is an important topic in the data mining research , select BP neural network technology to predict fiber fault diagnosis function , the complex causal physical quantities , after the appropriate number of training more accurately reflected . The main work is reflected in the following aspects : (1) based on VS2003 platform developed optical fiber protection system automatically switches to achieve real-time monitoring of communication optical fiber optical power value is reported to the system 's main control module , and stored in good data acquisition , data mining after work history table . Master module to compare the reported data with the preset threshold , to achieve automatic control . (2 ) real-time rendering of the curve of changes in the optical power , to visually display the optical power of the optical fiber transmission system changes , the user can determine the stability of the fiber runs through the observation of the power curve of the fiber optical . (3) on the basis of the study BP algorithm , BP algorithm improvements, a sample selection of the actual network model , constructed training samples ; standardization pretreatment of the sample selected ; select a three - layer neural network to determine the network's input output nodes and hidden layer nodes ; determine the appropriate learning rate . Constructing appropriate BP neural network , the optical power value forecast mining , analysis and prediction results . The experiments show that the BP neural network of optical fiber fault diagnosis data mining is feasible .

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