Monitoring of winding faults is of great significance for the assessment of the transformer maintenance status. In this study, the time series analysis is combined with frequency response analysis (FRA) for better interpretation and analysis of FRA results. Here, healthy baseline residual data are modeled using the time series analysis for faults detection of the transformer winding. Different statistical software, such as R 4.0.2 and ITSM2000, are used to analyze measured data. To detect the transformer’s winding faults, various analyses, such as the autocorrelation and partial autocorrelation functions plot, the Box–Pierce test, the Ljung–Box test, the McLeod–Li test, the turning points test, the Wallis and Moore phase–frequency test, and the Jarque–Bera test, and the order of minimum corrected Akaike’s information criteria are used. The simulation results show that the suggested method is able to classify and discriminate mechanical and electrical faults of the transformer’s winding with good accuracy.

Transformer Winding Faults Detection Based on Time Series Analysis

Fault detection and diagnosis in power transformers: a comprehensive review and classification of publications and methods

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

FDS Measurement-Based Moisture Estimation Model for Transformer Oil-Paper Insulation Including the Aging Effect

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.

A Modified Simulation Model for Predicting the FDS of Transformer Oil-Paper Insulation Under Nonuniform Aging

Efficient prediction and classification for cirrhosis disease using LBP, GLCM and SVM from MRI images

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.

A New Testing Method for the Diagnosis of Winding Faults in Transformer

Autotransformer (AT) is the most core power supply equipment, and overvoltage and short circuit (SC) fault may lead to winding deformation, which will have a negative impact on its insulation and even affect the operation of a train. The frequency response analysis (FRA) is widely used for detecting winding faults in a transformer. However, the direct measure of FRA for each split winding fails because the split windings are adopted to satisfy the impedance requirement of a high-speed railway, where the windings are connected inside the tank. A novel fault interpretation method based on image features and binary tree support vector machine (SVM) is proposed, which can get the condition of three windings in one measurement. Winding faults caused by different windings are simulated, including SC defect, axial deformation, and series capacitance variation, and the FRA curves are measured under various faults. Then, the features of the gray-level gradient co-occurrence matrix and the gray-level difference statistics are got from the polar plot of FRA. Finally, the image features are used as the inputs to the binary tree SVM for fault type and faulty winding classification. The results show that the proposed method has high accuracy for identifying fault type and faulty winding in AT.

Detection of Winding Faults Using Image Features and Binary Tree Support Vector Machine for Autotransformer

Frequency response analysis (FRA) is a widely used approach for detecting winding faults in a transformer. Appropriate and quantitative FRA features will help to improve the accuracy of fault diagnosis. In this study, a novel FRA interpretation including new image features is proposed based on the image processing technique. First, winding faults of different windings are simulated in a test autotransformer and the FRA curves are measured under various faults. Then frequency region division method and image processing technique are first applied to the measured FRA curves. The area ratio and centroid deviation in different frequency regions are calculated through a novel algorithm. Finally, the image features are used as the inputs to support vector machine model. Additionally, three different parametric optimisation algorithm are compared during the training process. The results show that the particle swarm optimisation and image feature exhibit best performance for identifying winding faults.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-epa.2019.0933

Detection of transformer winding faults using FRA and image features

The primary objective of evaluation of eddy-current losses is to provide a guide for optimized design of tractive transformer. It is not sensible to directly create the detailed laminations of a transformer core for analyzing the eddy-current field because of sophisticated modeling procedure and incredible computational cost. As a result, in this article, a series of original formulas to describe the equivalent electromagnetic parameters of multilevel-circle-section wound core under various frequencies, including anisotropic conductivity and permeability, are proposed to serve for finite-element analysis, on which the core model is considered to be a continuum with homogeneous material property. The experiment of core losses on practical wound core with the characteristic of multilevel-circle section is taken to verify the availability of the proposed model, where the modified extrapolation method is applied to obtain the eddy-current components separated from total core losses. Finally, there are satisfactory precisions on simulated results of eddy-current losses at a wide range of frequency and magnetic flux density; hence, this homogenization method is effectively applicable for engineering. This article can also provide reference for analysis of the other electromagnetic problems in tractive power supply equipment.

A Homogeneous Model for Estimating Eddy-Current Losses in Wound Core of Multilevel-Circle Section

The invention discloses a frequency response test platform under transformer winding radial deformation and an evaluation method thereof. The frequency response test platform under radial deformationmainly comprises an insulating screw (3), an insulating stay (2), a transmission motor (5), a motor control platform (6), and a transmission chain (12). The transmission motor (5) drives the insulating screw (3) to work so that a transformer winding carries out radial deformation. Under different radial deformation degrees, a frequency response tester (10) is used for testing, and frequency response data is obtained through interaction between a computer (11) and the frequency response tester (10). For frequency response curves under a normal state and different fault degrees, an area of a frequency response is calculated according to an intersection point of curves in frequency bands through using a Gaussian integral formula and an area difference is obtained. Finally, a standard deviation coefficient delta of area offset is obtained, and the transformer winding state is evaluated.

Lin Tong

Papers

A New Testing Method for the Diagnosis of Winding Faults in Transformer

Detection of Winding Faults Using Image Features and Binary Tree Support Vector Machine for Autotransformer

Detection of transformer winding faults using FRA and image features

A Homogeneous Model for Estimating Eddy-Current Losses in Wound Core of Multilevel-Circle Section

Frequency response test platform under transformer winding radial deformation and evaluation method thereof