期刊刊名：管理科學與統計決策 　 卷期：7卷1期

篇名出版日期：2010年3月1日

作者：Yanbin Li,Kailin Ji,Yan He,Yun Li,Pengyu Zhang

語言：English

關鍵字：RBF nueral network,PSO,fault diagnosis,Condition-based maintenance,voltage transformer

被點閱次數：0次

閱讀時間：0sec

摘要：
In this paper, an improved neural network algorithm is used in the fault diagnosis for transmission and transformation equipments. In the process of model building, Particle Swarm Optimization (PSO) algorithm is used to optimize the Radial Bases Function (RBF) neural network. By controlling the bias of diagnosis results, the network parameters are adjusted dynamically and then the network structure is optimized and the diagnostic accuracy is raised. The correctness and effectiveness of this algorithm are proved by means of practical example in voltage transformer DGA fault diagnosis. It can also be used in fault diagnosis among kinds of other transmission and transformation equipments.

　　　　　[全文下載]