应用复小波变换检测突发短路时的电力变压器绕组状态

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摘要突发短路时电力变压器箱壁的振动信号与绕组的运行状态密切相关。考虑到突发短路时变压器振动信号的强时变性和非平稳性,为了进一步提高振动分析法检测变压器绕组状态的准确性,本文引入复数小波变换法即Morlet小波对突发短路时变压器的实测振动信号进行时频分析,根据振动信号中的频域特征变化来判断变压器的绕组状态。结果表明：复小波变换算法能够准确地展示突发短路时变压器振动信号的频谱特性,时频图中100Hz分量和冲击总能量的大幅增加预示了绕组的松动,而高频分量的出现敏锐地反映出绕组变形的开始。与短路电抗法相比,振动分析法更能灵敏地反映出变压器绕组的变形故障。

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	张坤
	王丰华
	廖天明
	金之俭

关键词 ：电力变压器, 复小波变换, 突发短路, 绕组变形, 振动分析法

Abstract：The vibration signals of power transformer tank under sudden short-circuit impact are closely related to the winding operation condition. In order to improve the accuracy of vibration analysis method, a complex wavelet transformer algorithm was proposed and applied to extract the time-frequency feature of the non-stationary and strong time-varying measured vibration signals while power transformer under sudden short-circuit impact. The results show that the complex wavelet transformer algorithm is capable of analyzing the transformer vibration signal effectively and accurately. The substantial increase of 100Hz frequency component and the energy imply the loosening of the winding. The beginning of winding deformation can be indicated clearly by the occurrences of the high frequency components. In addition, the vibration analysis method is more sensitive to the transformer winding deformations than that of short-circuit reactance method.

Key words： Power transformer complex wavelet transformer sudden short-circuit winding deformation vibration analysis method

收稿日期: 2012-09-20 出版日期: 2014-11-05

PACS:

TM41

基金资助:国家自然科学基金（51207090）和上海市科学委员会（09dz1205900）资助项目

作者简介: 张坤女,1989年生,硕士研究生,研究方向为变压器在线监测与故障诊断；王丰华女,1973年生,博士,讲师,研究方向为电力设备在线监测与故障诊断、电力系统过电压和接地技术。

引用本文:

张坤, 王丰华, 廖天明, 金之俭. 应用复小波变换检测突发短路时的电力变压器绕组状态[J]. 电工技术学报, 2014, 29(8): 327-332. Zhang Kun, Wang Fenghua, Liao Tianming, Jin Zhijian. Detection of Transformer Winding Deformation under Sudden Short-Circuit Impact Based on Complex Wavelet Algorithm. Transactions of China Electrotechnical Society, 2014, 29(8): 327-332.

链接本文:

http://dgjsxb.ces-transaction.com/CN/Y2014/V29/I8/327

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