Research on Elimination of Electric Power System Fault Based on Electrical Engineering Automatic Control Technology

Article Preview

Abstract:

In this paper we introduce the computer software fault analysis system to the power fault detection system, and design power fault elimination system of electrical engineering automatic control, and do simulation and experimental study on the performance. When using the turbine blade of electric machinery to detect fault, we can get the automated troubleshooting displacement curve, and using computer simulation to get the electric mechanical stress distribution nephogram. To further verify the effectiveness of the algorithm, we test the frequencies for eight different units, and obtain eight different sets of five order fault diagnosis frequency, and draw the frequency spectrum distribution of frequency response. It provides the theory reference for the automation of power system fault exclusion.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

771-774

Citation:

Online since:

February 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Fan Xiaoxia, Gu Xiaoping. Analysis of gas turbine fuzzy fault tree failure air in the compressor station [J]. Natural gas and oil, 20 10, 28 (6): 10-14.

Google Scholar

[2] Cui Xuanming. Application of fuzzy logic diagnosis technology in the gasoline engine fault diagnosis [J]. Journal of Changsha Traffic College, 2011, 24 (3): 81-83.

Google Scholar

[3] Hu Jianrong. Study of the structural damage diagnosis of based on modal analysis [D]. Chengdu: Southwest Jiao Tong University, 2010: 1-7.

Google Scholar

[4] Yang Jian. Analysis of centrifugal compressor impeller vibration characteristics based on ANSYS [D]. Dalian: Dalian University of Technology, 2011: 2-11.

Google Scholar

[5] Long Ying, Teng Zhaojin, Zhao Fushui. Finite element modal analysis current situation and development trend [J]. Hunan agricultural machinery, 2010, 36(4): 27-29.

Google Scholar

[6] Zhang Jian, Fang Fengyang, Jin Youlin. Analysis of the gravitation training facility mode based on LMS Test. Lab [J]. Helicopter technology, 2010 (1): 89-90.

Google Scholar

[7] Xie Zhiming. Application research on blind source separation technology in the aero engine fault diagnosis [D]. Changsha: South University, 2011: 1-9.

Google Scholar

[8] Fan Xiaoxia, Gu Xiaoping. Analysis of the air compressor station gas turbine fuzzy fault tree failure [J]. Natural gas and oil, 2010, 28 (6): 10-14.

Google Scholar

[9] Zhou Haichao, Zuo Yanyan, Bao Xiaolin. Four cylinder diesel engine crankshaft free modal [J]. Noise and vibration control, 2010, 12 (6): 63-66.

Google Scholar