APPLICATION OF WAVELET PACKET ANALYSIS IN TURBINE FAULT DIAGNOSIS

摘要：

Experimental platform is used to simulate typical faults of turbine. Based on the frequency domain feature, energy eigenvector of frequency domain is presented in the wavelet packet analysis method, and the way of best tree is used to choose symptom. Finally, the fault states are recognized using neural network, and the simulations show that it makes a good performance with the method.

关键词： Fault diagnosis symptom extraction wavelet packet analysis best tree neural networks

作者: YUE-HUI PENG XIAO-GANG XU HE-XIANG ZHAO

作者单位: Department of Science and Technology, North China Electric Power University, Baoding 071003, China Department of Power, North China Electric Power University, Baoding 071003, China

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 2897-2900

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）