基于电压阻尼振荡的变压器故障绕组识别方法

doi:10.19595/j.cnki.1000-6753.tces.230314

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Abstract

The winding fault is a serious transformer fault. The voltage damping oscillation method is an effective method to diagnose the winding health state. However, this method still has the following problems: 1) The voltage damping oscillation of transformer winding continue to fluctuate slightly for a period of time before the end of charging and discharging. In this process, there are lot of irregular maximum points, minimum points and burrs. These invalid extreme points and burrs interfere with the subsequent characteristic processing and analysis of the oscillation wave. According to the existing literature, the oscillation ends when it attenuates to 5% of the maximum value, and all poles in this band are effective extreme points. Through a large number of experiments, it is observed that when the voltage damping oscillation is no longer attenuated, its stable value is far greater than 5% of the maximum value, which leads to the definition of the effective wave band of the above voltage damping oscillation is no longer applicable. 2) Due to the complexity of on-site testing and external interference, the two voltage damping oscillation signals measured at different time intervals on the same transformer may have small deviations. At present, the time-domain feature extraction of the oscillation wave applied to the transformer is distinguished only by a single curve feature, and the identifiable accuracy is low when diagnosing the fault location and degree. In order to eliminate the interference and obtain more status information of transformer windings , this paper presents a method of transformer winding fault analysis based on the selection of dynamic wave band of voltage damping oscillation: first, build a transformer winding fault simulation platform to obtain the winding oscillation wave data under four kinds of faults: axial displacement, inter disk capacitance, inter pie or inter turn short circuit; Secondly, By analogy with the effectiveness of mechanical system and electrical system, the characteristics of oscillation wave attenuation are analyzed from the perspective of energy conversion, selecting the effective wave band of oscillation wave through defined energy attenuation factor; Then, in the effective band of the oscillating wave test data: obtain the waveform Feature Correlation Degree (FCD) to identify the fault type, At the same time, taking into account the rich feature information between the extreme point and the waveform, construct the oscillating wave binary image based on mathematical morphology to eliminate the measurement interference and extract more stable Tamura texture features to identify the fault location and degree; Finally, based on the distribution rule of characteristic parameter combination, the application analysis is carried out through the actual transformer. The results show that the band interference information dynamically selected is less, the attenuation oscillation regularity is obvious and contains rich feature information. The oscillation wave under four types of faults have certain differences between each other, and exhibit significant variation patterns compared to normal windings. The use of waveform FCD is particularly effective in identifying winding fault types; The oscillation wave under the same fault type exhibit small differences in different fault areas and degrees. Different combinations of four Tamura texture features exhibit good classification performance in identifying fault degrees and types. In general, the waveform FCD and Tamura texture feature based on binarization values extracted under different faults have their obvious separation and clustering. It can realize the recognition and classification of fault type, fault degree and fault region.

Key words： Transformer Voltage damping oscillation Winding fault Dynamic band Waveform feature Texture feature

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TM614

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	ZHOU Lijun
	YUN Xiucheng
	WANG Dongyang
	ZHOU Meng
	ZHANG Jun

Cite this article:

ZHOU Lijun,YUN Xiucheng,WANG Dongyang等. Transformer Fault Winding Identification Method Based on Voltage Damped Oscillation[J]. Transactions of China Electrotechnical Society, 0, (): 8925-.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.230314 OR https://dgjsxb.ces-transaction.com/EN/Y0/V/I/8925

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