A New Testing Method for the Diagnosis of Winding Faults in Transformer
09 Jun 2020-IEEE Transactions on Instrumentation and Measurement (Institute of Electrical and Electronics Engineers (IEEE))-Vol. 69, Iss: 11, pp 9203-9214
TL;DR: The proposed testing method for the diagnosis of winding faults based on the resonant frequency of the transformer can conduct the test of winding and insulation in one test for a short time, which proves a reference in the field.
Abstract: In this article, a new testing method for the diagnosis of winding faults based on the resonant frequency of the transformer is proposed. The system that consists of the high-voltage dc power and high-voltage insulated gate bipolar transistor (IGBT) could charge the transformer periodically. The response measured from the bushing of the winding is the oscillating wave that can be used for evaluating the status. Carrying out the new test on a 220-kV three-winding, three-phase transformer in the field, the tests of insulation and the winding have been completed in one test. The calculated frequency verifies the feasibility and applicability of the method in theory and the voltage does not affect the resonant frequency in the test. The three-winding, three-phase model transformer was built to simulate the various parameters of the power supply, which proves that the features of the oscillating waves are brought about by the properties of the transformer. Also, the new testing method provides a new opportunity to do parameter identification of axial displacement and short-circuit (SC) fault. The abovementioned research shows that the proposed method can conduct the test of winding and insulation in one test for a short time, which proves a reference in the field.
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TL;DR: Fault detection and diagnosis (FDD) has been recently the center of attention in both industrial and academic studies as discussed by the authors , where the main advantage of FDD is that it prevents costly repairs, costly downtimes, putting human into danger, and destruction of the equipment nearby.
22 citations
TL;DR: A model for predicting the frequency domain spectroscopy (FDS) of the transformer OPI including the effect of nonuniform aging is expected to provide.
Abstract: The influence of nonuniform aging has not been considered in the prediction of the frequency domain spectroscopy (FDS) of the transformer oil-paper insulation (OPI) when using the finite element method (FEM). Given this issue, the modified simulation model was constructed based on the XY model and FEM. In the current work, the dielectric response property of the pressboards with different aging conditions in the modified model was characterized by its dielectric response parameters measured in the lab. Then the modified simulation model constructed in a 3-D system would be applied to study the effect of both nonuniform aging and the axial geometry on the FDS of OPI. Finally, the feasibility of the proposed models was verified by comparing the measured FDS and the predicted FDS. This article is expected to provide a model for predicting the FDS of the transformer OPI including the effect of nonuniform aging.
22 citations
Cites background from "A New Testing Method for the Diagno..."
...ACCURATELY monitoring the insulation condition of the transformer solid insulation is of great significance to the stable operation of the power system [1]–[3]....
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TL;DR: In this article, an alternative model including the aging effect is proposed using frequency-domain spectroscopy (FDS) and intelligent algorithm, where the feature parameters of FDS data are used to build the databases for characterizing the aging degree and moisture, and the moisture estimation models are developed using the weighted K-NN algorithm.
Abstract: Moisture accumulates with the growing aging progress of oil-paper insulation and further shortens the remaining life of the transformer The frequency-domain spectroscopy (FDS) technique can be used to realize the moisture estimation However, the moisture estimation results would be unreliable once the aging effect on FDS was ignored Given this issue, an alternative model including the aging effect is thus proposed using FDS and intelligent algorithm In this work, the feature parameters of FDS data are used to build the databases for characterizing the aging degree and moisture Then, the moisture estimation models are developed using the weighted K-nearest neighbor (K-NN) algorithm The accuracy and applicability of the proposed models are finally discussed in laboratory and field conditions In that respect, the findings reveal that the reported model is available for moisture estimation of transformer oil-paper insulation under various aging degrees and test temperatures
22 citations
TL;DR: In this paper , a technique for interpreting frequency responses based on image processing and a deep learning method called graph convolutional neural network (CNN) is presented, which transfers frequency responses into 2D images through a visualization technique.
Abstract: Frequency response analysis (FRA) suffers from the interpretation of results despite its potential ability to detect faults related to the power transformer windings. This article presents a technique for interpreting frequency responses, which is based on image processing and a deep learning method called graph convolutional neural network (CNN). The proposed procedure transfers frequency responses into 2-D images through a visualization technique. The resulting images are aggregated into a dataset to be used as the CNN input. The proposed technique is applied on frequency responses of two different winding models with short circuit (SC) faults. The SC faults with different intensities are applied on different sections of a simulated ladder model winding and a 20 kV winding of a 1.6 MVA distribution transformer. After determining the frequency response for each faulty case and applying the visualization technique, the precise locating of the SC faults is performed by the CNN. Then, the results are analyzed by performance evaluation metrics. At this stage, the high performance of the CNN in the use of 2-D images instead of the conventional method is observed. Finally, by testing the high impedance SC faults in different sections of the simulated winding model and applying the suggested method step by step, early detection of the SC fault is also performed in this article. It should be noted that the suggested technique, in addition to its accuracy and high detection speed, can be considered as an important step in automatic interpretation of frequency responses for online monitoring of transformers.
13 citations
TL;DR: A unified framework of intelligent algorithms for transformer condition assessment is presented and a survey of new findings in this rapidly-advancing field are presented, including differentiated evaluation, uncertainty methods, and big data analysis.
Abstract: Transformers are playing an increasingly significant part in energy conversion, transmission, and distribution, which link various resources, including conventional, renewable, and sustainable energy, from generation to consumption. Power transformers and their components are vulnerable to various operational factors during their entire life cycle, which may lead to catastrophic failures, irreversible revenue losses, and power outages. Hence, it is crucial to investigate transformer condition assessment to grasp the operating state accurately to reduce the failures and operating costs and enhance the reliability performance. In this context, comprehensive data mining and analysis based on intelligent algorithms are of great significance for promoting the comprehensiveness, efficiency, and accuracy of condition assessment. In this article, in an attempt to provide and reveal the current status and evolution of intelligent algorithms for transformer condition assessment and provide a better understanding of research perspectives, a unified framework of intelligent algorithms for transformer condition assessment and a survey of new findings in this rapidly-advancing field are presented. First, the failure statistics analysis is outlined, and the developing mechanism of the transformer internal latent fault is investigated. Then, in combination with intelligent demands of the tasks in each stage of transformer condition assessment under big data, we analyze the data source in-depth and redefine the concept and architecture of transformer condition assessment. Furthermore, the typical methods widely used in transformer condition assessment are mainly divided into rule, information fusion, and artificial intelligence. The new findings for intelligent algorithms are also elaborated, including differentiated evaluation, uncertainty methods, and big data analysis. Finally, future research directions are discussed.
10 citations
References
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TL;DR: In this article, an extensive review is given of diagnostic and monitoring tests, and equipment available that assess the condition of power transformers and provide an early warning of potential failure, which is a very important issue for utilities.
Abstract: As transformers age, their internal condition degrades, which increases the risk of failure. To prevent these failures and to maintain transformers in good operating condition is a very important issue for utilities. Traditionally, routine preventative maintenance programs combined with regular testing were used. The change to condition-based maintenance has resulted in the reduction, or even elimination, of routine time-based maintenance. Instead of doing maintenance at a regular interval, maintenance is only carried out if the condition of the equipment requires it. Hence, there is an increasing need for better nonintrusive diagnostic and monitoring tools to assess the internal condition of the transformers. If there is a problem, the transformer can then be repaired or replaced before it fails. An extensive review is given of diagnostic and monitoring tests, and equipment available that assess the condition of power transformers and provide an early warning of potential failure.
834 citations
"A New Testing Method for the Diagno..." refers background in this paper
...6% of transformer failures are connected with the winding [3]....
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...and the other is the short-circuit impedance test [3]....
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TL;DR: In this article, a frequency response analysis (FRA) method was used to measure wind deformation in power transformers, and the results indicated that benchmark reference data was not always necessary to identify certain kinds of mechanical damage.
Abstract: Winding deformation in power transformers can be measured externally using a new frequency response analysis (FRA) method Field experience since 1975, on five separate transformers up to 550 MVA rating, 230kVclassindicatesthatthismethod hasadvantagesover the low voltage impulse (LVI) method as a practical maintenance tool. Results on suspect transformers indicate that benchmark reference data is not always necessary to identify certain kinds of mechanical damage.
314 citations
"A New Testing Method for the Diagno..." refers methods in this paper
...The frequency response analysis is generally considered to be effective among the three methods [11]....
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01 Jul 1996
TL;DR: In this article, a survey of the most important methods for on-line monitoring and off-line diagnostics is given, and the area of life assessment is discussed, and in particular the difference between end-of-life of the insulating material and of the transformer is emphasized.
Abstract: A manufacturer's view on transformer monitoring is presented. Based on a review of the changes occurring on the electricity market, monitoring of transformers is discussed emphasizing its commercial aspects. Definitions of the words "monitoring" and "diagnostics" are proposed, and it is stressed that the key issues related to on-line monitoring are reliability and low cost. A survey of the most important methods for on-line monitoring and off-line diagnostics is given. The area of life assessment is discussed, and in particular, the difference between end-of-life of the insulating material and of the transformer is emphasized.
196 citations
"A New Testing Method for the Diagno..." refers background in this paper
...TRANSFORMER is the core equipment of the power system, and its security is very important for the safe and reliable operation of the power system [1], [2]....
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TL;DR: In this paper, the transfer function (TF) is used to detect different types of mechanical damage in power transformers, such as disc-space variation, radial deformation, and axial displacement.
Abstract: The transfer function (TF) these days is a well-known method to detect different types of mechanical damage in power transformers. The most important mechanical faults mentioned by the authors and researchers, which are most likely to be detected using the TF and occur frequently in transformers, are disc-space variation, radial deformation, and axial displacement. These faults are investigated in this paper using three different similar-size test objects. Since the TF method is a comparative method and the measured results should be compared with the reference results, some mathematical methods are studied to compare different TFs. A complete fault detection, which means determining the type, location, and level of the faults by using TF analyses is the main aim of this paper.
137 citations
"A New Testing Method for the Diagno..." refers methods in this paper
...According to the IEEE standard and other research [2], [12],...
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...Some features extracted from the FRA could be used in the identification of transformer status, such as statistical indexes [12], which describes the overall change of FRA in each frequency band, and would provide the reference for the fault diagnosis [2], [13]....
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TL;DR: In this paper, a complete mathematical model of the 2 × 27.5kV ac railway system, by means of the nodal admittance matrix, is presented to attain equal modeling of TPSS and modern train for harmonic studies.
Abstract: High-frequency harmonic resonance has occurred frequently in the traction power-supply system (TPSS) when high-speed trains that are equipped with pulsewidth-modulation converters were serviced in the China High-Speed Railway (HSR). This phenomenon can result in serious voltage distortion, overheating of electrical components, and electromagnetic interference (EMI) of communication circuits. In order to address this issue, a complete mathematical model of the 2 × 27.5-kV ac railway system, by means of the nodal admittance matrix, is presented to attain equal modeling of TPSS and modern train for harmonic studies in this paper. The impact of the train on resonance behavior of TPSS by employing resonance-mode assessment and modal sensitivity analysis are investigated. Finally, numerical simulation results using the presented model are compared to measurements results of the China HSR to verify the accuracy of the TPSS model and Norton model of the train, and proved that the method of resonance frequency shifts described is doable. The comparison results illustrate that the proposed model and harmonic resonance assessment can be useful for determining and mitigating the harmonic resonance problems in TPSS as well as the power system.
131 citations
"A New Testing Method for the Diagno..." refers background in this paper
...For example, in the traction power supply system, sometimes only 30 min is allowed for the entire maintenance time [21], [22], of which the test of transformer insulation and winding takes quite a few, thus leaving insufficient time for other tests....
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