J. Christian

Bio: J. Christian is an academic researcher from Siemens. The author has contributed to research in topics: Distribution transformer & Current transformer. The author has an hindex of 1, co-authored 1 publications receiving 158 citations.

Procedures for detecting winding displacements in power transformers by the transfer function method

Abstract: The paper investigates three different ways of using the transfer function method for detecting mechanical winding displacements in power transformers. The most reliable approach is time-based comparison , which requires finger print data from a previous measurement. Such information is, however, usually not available. For multilegged transformers without zigzag-connected windings the results of separately tested legs can be used as mutual references (construction-based comparison ). A third approach is to compare the transfer functions with those obtained from an identically constructed transformer ( type-based comparison). However, for a transformer with given nominal specification data, the winding design may over time undergo changes which causes changes to the transfer function. It is proposed to solve this problem by calculating tolerance bands using transfer functions from a big group of the same-type transformers. A novel statistical algorithm for this purpose is presented. The approach is demonstrated for a set of 28 specified identically 200-MVA power transformers.

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

Abstract: On-line monitoring and diagnosis of transformers have been investigated and discussed significantly in last decade. This study has concentrated on issues arising while on-line transformer winding deformation diagnosis is going to be applied on transformers with various kinds of techniques. From technical perspective, before replacing off-line methods by on-line methods and eventually by intelligent approaches, practical challenges must be addressed and overcome. Hence, available off-line transformer winding deformation diagnosis methods are discussed precisely. Mathematical calculation in on-line short circuit impedance measurement is investigated. On-line transformer transfer function measurement setup is presented. A profound insight to the problems pertaining on-line transformer winding deformation recognition methods, characterizes existing online methods, explains the concepts behind online measurements and striving to open the discussion doors towards challenges are discussed. In the end a 400 MVA step up transformer has been taken as a case in order to clarify the capability of Frequency Response Analysis (FRA) method in fault detection while short circuit impedance could only demonstrate some rough understanding about transformer condition.

Mathematical Comparison Methods to Assess Transfer Functions of Transformers to Detect Different Types of Mechanical Faults

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.

Interpretation of Transformer FRA Responses— Part I: Influence of Winding Structure

Abstract: Frequency-response analysis (FRA) has been accepted as one of the most sensitive tools to detect mechanical faults of power transformers. Correct interpretation of FRA responses is crucial when assessing the integrity of a transformer. Transformer FRA responses have distinctive frequency regions which are predominated by core, windings, and measuring setup. This paper addresses one of the major factors that affect the FRA responses: the winding structure itself. In terms of the structures of single winding, they can be categorized into windings with either high- or low-series capacitance in proportion to the shunt capacitance. Correspondingly, the FRA responses of windings of high series capacitance exhibit the increasing trend of magnitude, while windings of low series capacitance display a steady magnitude trend with the features of resonances and quasi-antiresonances or antiresonances. For a winding made of two concentric winding coils, the pattern of alternating resonances and antiresonances would be exhibited on its FRA response.

Transformer winding faults classification based on transfer function analysis by support vector machine

Abstract: This study presents an intelligent fault classification method for identification of transformer winding fault through transfer function (TF) analysis. For this analysis support vector machine (SVM) is used. The required data for training and testing of SVM are obtained by measurement on two groups of transformers (one is a classic 20 kV transformer and the other is a model transformer) under intact condition and under different fault conditions (axial displacement, radial deformation, disc space variation and short circuit of winding). Two different features extracted from the measured TFs are then used as the inputs to SVM classifier for fault classification. The accuracy of proposed method is compared with the accuracy of past well-known works. This comparison indicates that the proposed method can be used as a reliable method for transformer winding fault recognition.

Improved power transformer winding fault detection using FRA diagnostics – part 1: axial displacement simulation

Abstract: Frequency response analysis (FRA) has become a widely accepted tool to detect power transformer winding deformation due to the development of FRA test equipment. Because FRA relies on graphical analysis, interpretation of its signature is a very specialized area that calls for skilled personnel, as so far, there is no reliable standard code for FRA signature identification and quantification. Many researchers investigated the impact of various mechanical winding deformations on the transformer FRA signature using simulation analysis by altering particular electrical parameters of the transformer equivalent electrical circuit. None of them however, investigated the impact of various physical fault levels on the corresponding change in the equivalent circuit parameters. In this paper, the physical geometrical dimension of a single-phase transformer is simulated using 3D finite element analysis to emulate the real transformer operation. A physical axial displacement of different fault levels is simulated in both low voltage and high voltage windings. The impact of each fault level on the electrical parameters of the equivalent circuit is investigated. A key contribution of this paper is the charts it introduces to correlate various axial displacement levels with the percentage change of all transformer equivalent circuit parameters due to the axial displacement fault. In contrary with other researchers who only considered mutual inductance between low voltage and high voltage windings, simulation results shown in this paper reveal that other circuit parameters should be changed by a particular percentage to accurately simulate particular fault level of transformer winding axial displacement. Results of this paper aid to precisely simulating winding axial displacement using transformer equivalent circuit that facilitates accurate qualitative and quantitative analysis of transformer FRA signatures.