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Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/11065

Title: 機率神經網路之渦輪發電機故障診斷
Probabilistic Neural Network for Turbine Generator Fault Diagnosis
Authors: 魏忠必;邱裕豐;陳家湧
Contributors: 電機工程系
Keywords: 類神經網路;機率神經網路;渦輪發電機;故障診斷
Neural network;Probabilistic neural network;Turbine generator;Fault diagnosis
Date: 2006-06
Issue Date: 2012-06-05T03:53:35Z
Publisher: 中華民國自動化科技學會;建國科技大學創新育成研發中心
Abstract: 本文提出以機率神經網路(Probabilistic Neural Network, PNN)應用於渦輪發電機組故障診斷(Turbine Generator Fault Diagnosis)之研究。利用機率神經網路之特性,用已知的故障數據對類神經網路進行訓練後,即可對渦輪發電機組的故障型態進行診斷。為驗證本文所提之PNN對渦輪發電機故障診斷之準確性,使用MATLAB撰寫PNN程式,並經過訓練後診斷新的樣本資料,分辨出故障型態,證明所提方法之準確性可達到100%。
This paper presents a Probabilistic Neural Network (PNN) for turbine generator fault diagnosis. Using the known data to train the neural network. Then, input the new samples to diagnose the fault type. In order to prove the accuracy of the PNN for turbine generator fault diagnosis, using MATLAB to develop PNN program. The simulation can prove the proposed method is effective and accurate.
Relation: 第十四屆全國自動化科技研討會, 建國科技大學, 2006年6月2-3日
Appears in Collections:[電機工程學系] 會議論文

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