Diagnosis of Technical Condition of Power Transformers Based on the Analysis of Vibroacoustic Signals Measured in Transient Operating Conditions

Borucki, S.

doi:10.1109/tpwrd.2012.2185955

Cited by 88 publications

(52 citation statements)

References 23 publications

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“…In [2][3][4], the researchers from the theoretical modelling of the vibration characteristics of the transformer windings are studied, and got some meaningful results. ; In [5][6], the researchers have studied the a Corresponding author : 41037504@qq.com International Conference on Advanced Electronic Science and Technology (AEST 2016) development and application of the transformer vibration monitoring system, and got some meaningful results; In [7][8], the researchers have studied the method of detecting the state of the transformer winding based on the vibration signal, and got some meaningful results. Among them, in [9][10], the Spanish scholars put forward according to the transformer vibration model of the calculated results and the measured results are compared to the change of the threshold of the winding state detection.…”

Section: Introductionmentioning

confidence: 99%

Condition detection of transformer winding based on entropy weight correlation theory

Qian¹,

Yin²,

Zou³

2016

Proceedings of the 2016 International Conference on Advanced Electronic Science and Technology (AEST 2016)

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Abstract.To effectively detect the hidden fault of transformer winding, the combination of grey correlation analysis and entropy weight theory is proposed to detect the winding condition of power transformer based on the inherent relations of vibration frequency response (VFR) curves of several measured points. The vibration frequency response experiment is made on a real 220kV transformer winding both in normal and loosened conditions. The grey correlation degree and grey area correlation degree of VFR curves in each measured point. Then the entropy weight correlation degree is defined to determine the weight value of all the obtained features. The results have shown that the detection results based on the proposed method are agreed well with the preset condition of transformer winding, which is better illustrated the loosened degree of transformer winding. Compared with the existed FRA method, the vibration frequency response method is more sensitive to the variations of winding condition and has high application value.

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Section: Introductionmentioning

confidence: 99%

Condition detection of transformer winding based on entropy weight correlation theory

Qian¹,

Yin²,

Zou³

2016

Proceedings of the 2016 International Conference on Advanced Electronic Science and Technology (AEST 2016)

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“…Previous work has demonstrated that this method provides an option for assessing the mechanical integrity of a transformer. [6][7][8][9][10][11][12] Unlike the DGA and FRA methods, it relies on changes in the vibration response of the transformer under both steady-state and transient processes. For an example, Berler found that looseness in the winding clamping force might cause variations at twice the operating frequency and its harmonics.…”

Section: Introductionmentioning

confidence: 99%

Changes to the Vibration Response of a Model Power Transformer with Faults

Yuxing¹

2016

IJAV

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Current vibration-based techniques for transformer condition monitoring mostly rely on the vibration response caused by operating excitations, which consist of electrical excitations from the core and winding. Therefore, it is worthwhile to study the electrically-excited frequency response function (FRF), as it carries information of transformer mechanical and electromagnetic properties. This paper includes a sensitivity analysis of the mechanically and electrically excited FRFs of a model transformer to the reasons behind its failures. A model power transformer is used as an example to demonstrate the variation of its vibration response to a couple of causes of transformer faults, such as looseness of clamping forces in winding and core. Experimental evidence is presented to show the quantitative description of the causes of artificial faults and to extract features of variations of FRFs that might be useful to the vibration-based detection of the causes of transformer faults in general.

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“…Hence, it's fairly required to conduct research involving mechanism or so of such vibration phenomenon of transformers and so far some certain achievements have been reported already by literature from both in and abroad [4,5]. A kind of novel approach to identify the condition of cores the windings employing acoustic-vibration method was stated in [6] that the mechanical faults like screw looseness were detected via time-frequency domain analysis of acquired transient vibration signal from a transformer. Another method to identify the characteristic frequency of transformer vibration is stated in [7] that the vibration of the core and structure deformation of transformers was analyzed utilizing magnetostriction characteristics.…”

Section: Introductionmentioning

confidence: 99%

Multi-field Coupling Simulation and Experimental Study on Transformer Vibration Caused by DC Bias

Wang¹,

Gao²,

Xu³

et al. 2015

Journal of Electrical Engineering and Technology

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-DC bias will cause abnormal vibration of transformers. Aiming at such a problem, transformer vibration affected by DC bias has been studied combined with transformer core and winding vibration mechanism use multi-physical field simulation software COMSOL in this paper. Furthermore the coupling model of electromagnetic-structural force field has been established, and the variation pattern of inner flux density, distribution of mechanical stress, tension and displacement were analyzed based on the coupling model. Finally, an experiment platform has been built up which was employed to verify the correctness of model.

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Diagnosis of Technical Condition of Power Transformers Based on the Analysis of Vibroacoustic Signals Measured in Transient Operating Conditions

Cited by 88 publications

References 23 publications

Condition detection of transformer winding based on entropy weight correlation theory

Condition detection of transformer winding based on entropy weight correlation theory

Changes to the Vibration Response of a Model Power Transformer with Faults

Multi-field Coupling Simulation and Experimental Study on Transformer Vibration Caused by DC Bias

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