基于多平台测向及全局搜索的局部放电超声阵列定位方法

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (899 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract PD locating detection is a key project in electrical equipment insulation mechanism research and quality control. Emphasized much by the power department, it is an important foundation in transformer’s condition maintenance. Based on the errors of “noncoplanar disjoint line” and the “cumulative errors”in the method of “locating cross”, and the principle of multi-platform locating principle and global search with cloud optimization, a novel method to locate the PD in transformer is presented. According to the direction angle and elevation angle of multiple locating lines and the known coordinates of sensors, the PD source is referred to the point from which the sum of distance in space to all the locating lines is the minimum value. Then global search the min-distance function with cloud theory optimization algorithm (CTOA) to obtain the accurate geometric space coordinates of PD source. Finally, a PD ultrasonic array location experimental system is build, and extensive experiment research are conducted, the results of the research verify the accuracy and superiority of the method.

Key words： Partial discharge(PD) ultrasonic array location multi-platform measuring direction cloud optimization algorithm

Received: 29 July 2010 Published: 07 March 2014

PACS:

TM835

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors

Cite this article:

URL:

http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2011/V26/I11/217

[1] IEC 270. High-voltage test techniques-partial discharge measurements[S]. 2000.
[2] Kemp J. Partial discharge plant-monitor technology: present and future developments[J]. IEE Proceedings of Science, Measurement and Technology, 1995, 142(1): 4-10.
[3] Pedrsen A, Crichton G C, Mcallister I W. The theory and measurement of partial discharge transients[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 1991, 26(3): 487-496.
[4] Pedrsen A, Crichton G C, Mcallister I W, The theory and measurement of partial discharge transients[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 1991, 26(3): 487-496.
[5] 卢毅, 楼樟达, 王大忠. 用模式识别法进行油中放电超声定位的研究[J]. 电工技术学报, 1999, 14(3): 51-53.
[6] 李燕青, 陈志业, 律方成, 等. 超声波法进行变压器局部放电模式识别的研究[J]. 中国电机工程学报, 2003, 23(2): 108-111.
[7] Tolkachev A A, Levitan B A, Solovjev G K, et al. A meawatt power millimeter-wave phased-array radar[J]. IEEE AES Systems Magzine, 2000, 15(7): 25-31.
[8] Stocia P, Sharman K C. Maximum likelihood methods for direction-of-arrival estimation[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1990, 38(7): 1132-1143.
[9] 唐志国, 李成榕, 黄兴泉, 等. 基于辐射电磁波检测的电力变压器局部放电定位研究[J]. 中国电机工程学报, 2006, 26(3): 96-101.
[10] 谢庆, 李燕青, 律方成, 等. 超声相控阵与宽带阵列信号处理相结合的油中局部放电定位方法[J]. 中国电机工程学报, 2009, 29(28): 13-17.
[11] 罗勇芬, 李彦明, 刘丽春. 基于超高频和超声波相控接收原理的油中局部放电定位法的仿真研究[J]. 电工技术学报, 2004, 19(1): 35-39.
Luo Yongfen, Li Yanming, Liu Lichun. Simulation of PD location method in oil based on UHF and ultrasonic phased array receiving theory[J]. Transactions of China Electrotechnical Society, 2004, 19(1): 35-39.
[12] Luo Yongfen, Ji Shengchang, Li Yanming. Phased ltrasonic receiving planar array transducer for partial discharge location in transformer[J]. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 2006, 53(3): 614-622.
[13] 刘云鹏, 律方成, 李成榕, 等. 基于多导体传输线模型的单相变压器绕组中放电的距离函数法定位[J]. 电工技术学报, 2006, 21(1): 115-120.
[14] 罗日成, 李卫国, 李成榕.基于阵列信号处理的变压器内局部放电源多目标定位方法[J]. 电网技术, 2006, 30(1): 65-69.
[15] 罗日成. 基于阵列信号处理的大型变压器局部放电多目标定位方法研究[D]. 武汉: 武汉大学, 2006, 4.
[16] 李德毅, 杜鹢. 不确定性人工智能[M]. 北京: 国防工业出版社, 2005.
[17] Tian Yongqing, Weng Yingjun, Zhu Zhongying. Mining association rules based on cloud model and application in prediction [C]. Proceedings of the 4th World Congress on Intelligent Control and Automation, Shanghai, China, 2002.
[18] 李德仁, 王树良, 李德毅, 等. 论空间数据挖掘和知识发现的理论与方法[J]. 武汉大学学报: 信息科学版, 2002, 27(3): 221-233.
[19] Wang Hanjun, Deng Yu. Spatial clustering method based on cloud model [C]. Proceedings of the 4th International Conference on Fuzzy Systems and Knowledge Discovery, Jinan, China, 2007.
[20] Miranda V, Ranito J V, Proenco L M. Genetic algorithms in optimal multistage distribution network planning[J]. IEEE Transactions on Power System, 1994, 9(11): 1927-1933.
[21] Skrlec D, Krajcar S, Pribicevic B, et al. Exploiting the power of genetic algorithm in optimization of distribution networks[C]. Proceedings of the 8th Meditarranean Electrotechnical Conference, 1996: 1607-1610