Advanced transformer winding deformation diagnosis: moving from off-line to on-line

Bagheri, Mehdi; Naderi, Mohammad Salay; Blackburn, T.R.

doi:10.1109/tdei.2012.6396941

Cited by 158 publications

(59 citation statements)

References 42 publications

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“…Winding mechanical faults, namely winding deformation (such as tilting, forced bulking, free buckling, hoop tension, telescoping, etc. ), are difficult to detect at an early stage because they have limited impact on the normal operation of power transformers [4]. However, as the transformer continues to operate and suffers the external short circuit current, the minor winding mechanical fault would eventually develop catastrophic failure if no steps are taken.…”

Section: Introductionmentioning

confidence: 99%

Identification of Power Transformer Winding Mechanical Fault Types Based on Online IFRA by Support Vector Machine

et al. 2017

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Abstract:A transformer is the most valuable and expensive property for power utility, thus ensuring its reliable operation is a major task for both operators and researchers. Online impulse frequency response analysis has proven to be a promising technique for detecting transformer internal winding mechanical deformation faults when a power transformer is in service. However, as so far, there is still no reliable standard code for frequency response signature interpretation and quantification. This paper tries to utilize a machine learning method, namely the support vector machine, to identify and classify the winding mechanical fault types, based on online impulse frequency response analysis. Actual transformer fault data from a specially manufactured model transformer are collected and analyzed. Two feature vectors are proposed and the diagnostic results are predicted. The diagnostic results indicate the satisfied classifying accuracy by the proposed method.

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Section: Introductionmentioning

confidence: 99%

Identification of Power Transformer Winding Mechanical Fault Types Based on Online IFRA by Support Vector Machine

et al. 2017

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“…Transformer is one of the most important electrical equipment in power system, its safe and stable operation is of great significance to ensure the safe operation of the entire power grid [1][2]. In recent years, the transformer fault arises along with the increase of the power system capacity and load.…”

Section: Introductionmentioning

confidence: 99%

“…There is a variety of methods to detect the winding deformation developed at home and abroad [2], divideding into non electric measurement such as vibration analysis method [3], ultrasonic method [4], divergent coefficient method and electrometric method such as short circuit impedance method [5]and frequency response analysis [6].…”

Section: Introductionmentioning

confidence: 99%

Simulation study on the frequency response curve of the winding in different kinds of failure

Liu¹,

Wang²,

Yang³

2016

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

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Abstract. The equivalent circuit model is established to reflect the physical characteristics of the inner winding of the transformer, and then the parameters of the equivalent circuit model are calculated by using the finite element simulation software Maxwell ANSYS. Based on the establishment of the transformer winding equivalent circuit model and the distribution of resistance, capacitance, inductance calculation results, the variation of the distribution parameters of different winding faults is obtained. Use circuit analysis software PSpice and data analysis software MATLAB to simulate and set up the deformation of different types and degrees of transformer winding, such as winding axis shift, winding radial deformation, change of pitch of winding. According to the variation of the distribution parameters, the variation of the frequency response curve of the transformer winding is obtained.

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“…To realize condition based maintenance, the accuracy of equipment condition assessment is very important [1][2][3][4]. Therein, the detection of transformer winding deformation is one piece.…”

Section: Introductionmentioning

confidence: 99%

A transformer winding deformation detection method based on the analysis of leakage inductance changes

Li¹,

Tao²,

Wei³

et al. 2015

Archives of Electrical Engineering

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Abstract:The detection of transformer winding deformation caused by short-circuit current is of great significance to the realization of condition based maintenance. Considering the influence of environment and measurement errors, an online deformation detection method is proposed based on the analysis of leakage inductance changes. First, the operation expressions are derived on the basis of the equivalent circuit and the leakage inductance parameters are identified by the partial least squares regression algorithm. Second, the amount of the leakage inductance samples in a detection time window is determined using the Monte Carlo simulation thought, and then the samples in the confidence interval are obtained. Last, a criteria is built by the mean value changes of the leakage inductance samples and the winding deformation is detected. The online detection method considers the random fluctuation characteristics of the leakage inductance samples, adjust the threshold value automatically, and can quantify the change range to assess the severity. Based on the field data, the distribution of the leakage inductance samples is analyzed to obey the normal function approximately. Three deformation experiments are done by different sub-winding connections and the detection results verify the effectiveness of the proposed method.

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Advanced transformer winding deformation diagnosis: moving from off-line to on-line

Cited by 158 publications

References 42 publications

Identification of Power Transformer Winding Mechanical Fault Types Based on Online IFRA by Support Vector Machine

Identification of Power Transformer Winding Mechanical Fault Types Based on Online IFRA by Support Vector Machine

Simulation study on the frequency response curve of the winding in different kinds of failure

A transformer winding deformation detection method based on the analysis of leakage inductance changes

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