Classifying transformer winding deformation fault types and degrees using FRA based on support vector machine
- Authors: Liu, Jiangnan , Zhao, Zhongyong , Tang, Chao , Yao, Chenguo , Li, Chengxiang , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 112494-112504
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- Description: As an important part of power system, power transformer plays an irreplaceable role in the process of power transmission. Diagnosis of transformer's failure is of significance to maintain its safe and stable operation. Frequency response analysis (FRA) has been widely accepted as an effective tool for winding deformation fault diagnosis, which is one of the common failures for power transformers. However, there is no standard and reliable code for FRA interpretation as so far. In this paper, support vector machine (SVM) is combined with FRA to diagnose transformer faults. Furthermore, advanced optimization algorithms are also applied to improve the performance of models. A series of winding fault emulating experiments were carried out on an actual model transformer, the key features are extracted from measured FRA data, and the diagnostic model is trained and obtained, to arrive at an outcome for classifying the fault types and degrees of winding deformation faults with satisfactory accuracy. The diagnostic results indicate that this method has potential to be an intelligent, standardized, accurate and powerful tool.
Detection of power transformer winding deformation using improved FRA based on binary morphology and extreme point variation
- Authors: Zhao, Zhongyong , Yao, Chenguo , Li, Chengxiang , Islam, Syed
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Transactions on Industrial Electronics Vol. 65, no. 4 (2018), p. 3509-3519
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- Description: IEEE Frequency response analysis (FRA) has recently been developed as a widely accepted tool for power transformer winding mechanical deformation diagnosis, and has proven to be effective and powerful in many cases. However, there still exist problems regarding the application of FRA. FRA is a comparative method in which the measured FRA signature should be compared with its fingerprint. Small differences of FRA signatures in certain frequency bands might be produced by external disturbance, which hinders fault diagnosis. Additionally, the existing correlation coefficient indicator recommended by power industry standards cannot reflect key information of signatures, namely the extreme points. This paper proposes an improved FRA based on binary morphology and extreme point variation. Binary morphology is first introduced to extract the certain frequency bands of signatures with significant difference. A composite indicator of extreme point variation is adopted to realize the diagnosis of fault level. A ternary diagram is constructed by the area proportions of the binary image to identify winding faults, which has a potential to realize cluster analysis of fault types.
Determination of nanosecond pulse parameters on transfer function measurement for power transformer winding deformation
- Authors: Zhao, Zhongyong , Yao, Chenguo , Hashemnia, Naser , Islam, Syed
- Date: 2016
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 23, no. 6 (2016), p. 3761-3770
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- Description: Transfer function method is now a widely acceptable tool to diagnose transformer winding deformations. A sweep frequency sine wave generator is often used to excite the different modes of resonance and anti-resonances. However, it is time consuming. Nanosecond square wave pulse signal offers an alternative that can serve the same objective. However, as so far, there is no certain criterion for selecting pulse parameters. This paper provides a comprehensive method for the determination of nanosecond square wave pulse parameters for transfer function evaluation of power transformer for winding deformation studies.
Diagnosing transformer winding deformation faults based on the analysis of binary image obtained from FRA signature
- Authors: Zhao, Zhongyong , Yao, Chenguo , Tang, Chao , Li, Chengxiang , Yan, Fayou , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 40463-40474
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- Description: Frequency response analysis (FRA) has been widely accepted as a diagnostic tool for power transformer winding deformation faults. Typically, both amplitude-frequency and phase-frequency signatures are obtained by an FRA analyzer. However, most existing FRA analyzers use only the information on amplitude-frequency signature, while phase-frequency information is neglected. It is also found that in some cases, the diagnostic results obtained by FRA amplitude-frequency signatures do not comply with some hard evidence. This paper introduces a winding deformation diagnostic method based on the analysis of binary images obtained from FRA signatures to improve FRA outcomes. The digital image processing technique is used to process the binary image and obtain a diagnostic indicator, to arrive at an outcome for interpreting winding faults with improved accuracy.
Impact of capacitive coupling circuit on online impulse frequency response of a power transformer
- Authors: Zhao, Zhongyong , Yao, Chenguo , Zhao, Xiaozhen , Hashemnia, Naser , Islam, Syed
- Date: 2016
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 23, no. 3 (2016), p. 1285-1293
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- Description: Detecting the early signs of mechanical failures of power transformer winding is necessary and is possible with online monitoring techniques. Online impulse frequency response analysis (IFRA) is a promising diagnostic method when a transformer is in service. This paper examines the unrevealed problem existing in the method, namely, the impact of bushing capacitive coupling circuit on online impulse frequency response. An equivalent electrical model of capacitive coupling circuit and transformer winding is established. The frequency response of the capacitive coupling circuit is obtained to study its influence on online impulse frequency response. The parameter variations of capacitive coupling circuit caused by coupling capacitance variation and bushing dielectric breakdown are simulated to investigate their influence on online impulse frequency response signatures. A few experiments are eventually performed to verify the theoretical analysis and simulation results. This paper contributes to the application of online IFRA.
Improved method to obtain the online impulse frequency response signature of a power transformer by multi scale complex CWT
- Authors: Zhao, Zhongyong , Tang, Chao , Yao, Chenguo , Zhou, Qu , Xu, Lingna , Gui, Yingang , Islam, Syed
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 48934-48945
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- Description: Online impulse frequency response analysis (IFRA) has proven to be a promising method to detect and diagnose the transformer winding mechanical faults when the transformer is in service. However, the existing fast Fourier transform (FFT) is actually not suitable for processing the transient signals in online IFRA. The field test result also shows that the IFRA signature obtained by FFT is easily distorted by noise. An improved method to obtain the online IFRA signature based on multi-scale complex continuous wavelet transform is proposed. The electrical model simulation and online experiment indicate the superiority of the wavelet transform compared with FFT. This paper provides guidance on the actual application of the online IFRA method.
Interpretation of transformer winding deformation fault by the spectral clustering of FRA signature
- Authors: Zhao, Zhongyong , Tang, Chao , Chen, Yu , Zhou, Qu , Yao, Chenguo , Islam, Syed
- Date: 2021
- Type: Text , Journal article
- Relation: International Journal of Electrical Power and Energy Systems Vol. 130, no. (2021), p.
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- Description: Frequency response analysis (FRA) has been accepted as a widely used tool for the power industry. The interpretation of FRA can be achieved by the conventional mathematical indicators-based method, which is mostly used in the past. The newly developing artificial intelligence (AI)-based method also provides an alternative interpretation. However, in most reported AI techniques, the features of FRA signatures are directly input into the AI model to obtain the classification results. Few studies have concentrated on the separability of winding deformation faults. In this context, a spectral clustering algorithm is studied to aid in FRA interpretation. The electrical model simulation and experimental tests are performed. The FRA data processing results verify the feasibility, effectiveness and superiority of the proposed method. © 2021 Elsevier Ltd
Understanding online frequency response signatures for transformer winding deformation: Axial displacement simulation
- Authors: Zhao, Zhongyong , Islam, Syed , Hashemnia, Naser , Hu, Di , Yao, Chenguo
- Date: 2016
- Type: Text , Conference proceedings , Conference paper
- Relation: 2016 International Conference on Condition Monitoring and Diagnosis, CMD 2016; Xi'an, China; 25th-28th September 2016 p. 404-407
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- Description: The power transformer is considered as the most critical and expensive device in substation, however, the irreversible transformer winding mechanical deformation can eventually develop into catastrophic failure if no further steps are taken in a proper way, which would cause the outage of transformer and the significant economic losses. Online frequency response analysis (FRA) has been proven to be a promising tool for condition monitoring and diagnosing of winding deformation. Online FRA relies on graphic comparison of signatures, but up to now, there is no standard and practical interpretation code for signatures classification and quantification. This paper particularly studies the characteristic of online FRA signatures under the winding axial displacement mode, in which the 3D finite element electromagnetic analysis and online transformer equivalent high frequency electrical model are established as auxiliary tools to precisely emulate winding axial displacement. Results of this simulation will provide guidance on understanding online frequency response signatures.