Frequency response analysis for transformer tap changer damage detection

Power utilities desire an alternate noninvasive test method for assessing the diagnostic status of power apparatus. The primary reason is to minimize the economic constraints and ensure lifetime and reliability of power apparatus within shorter duration. In this context, frequency response analysis (FRA) method is increasingly recommended. The underlying principle of fault diagnosis using FRA method focuses on correlating the insulation condition to the changes in the magnitude and phase frequency response function. Existing practices validates the usage of FRA method in ascertaining the insulation integrity of transformers. Further attempts to expand the potential of FRA in method in determining the insulation status of power apparatus other than transformers, lack scientific and experimental evidence. To fill this gap, a research on using FRA method in assessing the insulation condition of high voltage bushings and power cables is initiated. Initially, test samples of insulation materials that are commonly used in bushings and cables are selected. The chosen samples are prepared in such a way that they represent common defect conditions that inflict premature material degradation and failures. These samples are grouped accordingly, placed on test cells, subjected to nonconventional FRA tests and their diagnostic status are respectively ascertained through comparative analysis. Following this, the pertinent findings are validated on actual bushings and power cables installed on a power transformer. In summary, the findings of this studies not only validate the usage of FRA method but provides the missing scientific and technical evidences and indices that could be used for diagnosing power apparatus.

This paper examines a frequency response analysis (FRA) method which aims at obtaining an precise linear plant model for a controller design, for fast and precise positioning of mechatronic systems with nonlinear friction. As well known, friction generated at linear guideways and/or bearings shows nonlinear and complicated behaviors, which causes deterioration of the motion control performance. In addition, the frequency response of the plant system dynamically changes depending on the measurement condition such as displacement and/or excitation force in the frequency domain analysis. The dynamic change of the frequency response makes it difficult to identify the actual linear plant characteristic for design of a precise simulator and/or an effective compensator. In this study, therefore, effects of parameter identification errors due to the dynamic frequency property on the fine positioning performance are clarified by simulation analyses with a nonlinear friction model. Then, a fundamental friction model-based FRA method is introduced, and the effectiveness of the presented FRA and effects of the friction model errors are demonstrated by frequency-domain simulations.

Frequency response analysis (FRA) is considered as an accurate, fast, effective and sensitive method for detection of mechanical defects within power transformers, providing worthy information on active part structure. FRA measurement has been industrialized and employed since the last decade while FRA spectrum interpretation is still under development. The interaction of distributed resistances, series and shunt capacitances as well as self- and mutual-inductances in transformer winding leads to FRA spectrum oscillations. In fact, each and every parameter has its own impact on this spectrum. This study has concentrated on shunt capacitance influences on frequency response spectrum oscillations in Bode diagram. Shunt capacitance impacts on low-, mid- and high-frequency bands of FRA spectrum are discussed. A practical study on a single phase air-core glassy model transformer is carried out to explore the influence of shunt capacitances of HV and LV windings with respect to the transformer tank on FRA spectrum. In addition, a single phase 11/0.25 kV, 25 kVA core type distribution transformer is also tested to evaluate the shunt capacitance impacts on FRA fluctuations.

Frequency Response Analysis (FRA) is a test method used for assessment of mechanical condition of transformer active parts. Its biggest problem is the interpretation of test results, namely the relationship between scale of differences between compared curves and the decision for further operation of the given transformer. Very often visible differences between two FRA curves do not mean that there is a deformation in the winding. The cause of the curve shift may come from other elements of the transformer that influence inductive or capacitive parameters. This paper takes under consideration the influence of both capacitance and inductance changes on transformer frequency response (FR). The analysis is performed with the computer model of a transformer and also some experimental results are presented, showing the influence of capacitance and inductance changes on the FR of real transformers. The results of research showed that this influence may lead to misleading effects on the shape of FR characteristics. The paper presents an analysis that can be used in the assessment of FRA measurement, especially in the case of uncertain data comparison results.

This work studies the sensitivity of frequency response analysis (FRA) method in detecting different types of deformations on a 6.6 kV plain disc type transformer winding. Winding deformations such as axial displacements and inter-turn faults are experimentally simulated and the measured FRA results are presented. A high frequency transformer-winding model is developed to investigate the sensitivity of the FRA method for these winding deformations. A comparison is carried out and a good agreement is shown between measured and calculated FRA results.

A multimode perturbation method for frequency response analysis of nonlinearly vibrational beams with periodic distribution parameters is proposed. The partial differential equation with spatial varying parameters for nonlinear vibration of beams with periodic parameters under harmonic excitations is derived. The procedure of the multimode perturbation method includes three main steps: first, the nonlinear partial differential equation is transformed into linear partial differential equations with varying parameters by applying perturbation method; second, the linear partial differential equations are transformed into ordinary differential equations with multimode coupling by applying Galerkin method, where multiple vibration modes of the beams are used and the equations are suitable to nonlinear vibration of periodic structures with high parameter-varying wave in wide frequency band; third, the ordinary differential equations are solved by applying harmonic balance method to obtain vibration response of the nonlinear periodic beam, which is used for characteristics analysis of frequency response and spatial mode. Furthermore, the stability problem of nonlinear harmonic vibration as multidegree-of-freedom system with periodic time-varying parameters is solved by applying direct eigenvalue analysis approach. The proposed method can incorporate multiple vibration modes into response analysis of nonlinear periodic structures and consider mode-coupling effects due to structural nonlinearity and parametric periodicity. Finally, a nonlinear beam with periodic supports under harmonic excitations is studied. Numerical results on frequency response of the beam are given to illustrate an application of the proposed method, new frequency response characteristics, and influences of periodic parameters on structural response. The results have potential application to nonlinear structural vibration control and support damage detection of nonlinear structures with periodic supports.

In this paper, we first outline the original fuzzy expert AVQC (automatic voltage and reactive control) method that has been in use at Tohoku Electric Power Company. We then investigate the mechanism of the inadequate motion of a transformer's tap changer. We propose an improved fuzzy expert control method to prevent unnecessary tap changer action. In order to validate the improved method, simulations of tap changer behavior under various operating conditions are conducted. The results of the simulations and analyses are also presented. In the last section, we briefly recommend utilizing on-load tap changers under critical operating conditions in terms of transient stability of a power system.

ABSTRACTAmong the most expensive assets in power grids, power transformers are essential for the reliability of the power supply chain and the overall stability of the grid. Due to their permanent connection to the network, this equipment is exposed to all kinds of faults and phenomena, including short‐circuit faults and overvoltages caused by lightning and switching. Hence, ongoing monitoring of the transformer's condition is essential to prevent breakdowns and damage to the transformer. Among the different condition monitoring methods, the frequency response analysis (FRA) method is sensitive to the smallest functional changes of the transformer, as it is completely related to the physics and geometry of the transformer. This method stands out as one of the most effective and efficient approaches to transformer monitoring, especially for detecting mechanical faults. However, the FRA method faces an important challenge of interpretation: the correlation between the type of fault that occurred and the way the transformer's function changes is still not well‐known, and studies in this field are ongoing. One of the most widely used methods of interpreting frequency response results is the use of numerical indices, coil modelling, transformer function estimation, and artificial intelligence algorithms. This paper introduces these methods, and their advantages and disadvantages are discussed. Then, the most widely used artificial intelligence algorithms in transformer condition monitoring are presented and compared. Finally, future research directions are anticipated.

The short circuit fault detection practices of power-transformer winding are important to ensure its unfailing and proper operation. In this regard, Frequency response analysis (FRA) is a favourable tool that can be used to detect a such fault. The FRA method has four measurement configurations called: end-to-end; open circuit test, short circuit test, and inductive inter-winding test, capacitive inter-winding test. However, a method of detecting the short circuit fault using FRA end-to-end measurement is investigated. This paper aims on investigating the inductive inter-winding of short circuit faults by showing a bipolar signature. The FRA inductive inter-winding measurement has been obtained from 11/0.415 kV, 500kVA distribution transformer to interpret the characteristics of resonances indicating a bipolar signature. There is a different level of short circuit fault artificially applied to the transformer winding. The inductive inter-winding measurements show that the resonances showing the bipolar signature at the mid-frequency range can be employed to determine the short circuit fault in the transformer winding. Based on this finding, a process of identifying the short circuit fault of a transformer winding is proposed. The data of short circuit fault and normal data of FRA measurement are compared. The proposed method can add to improving the purpose of using the FRA method to detect short-circuit faults in power transformers.

Based on two-probe inductive coupling and two-port cascade network theorem, in-circuit impedance extraction of primary of operational transformer has been discussed and validated. The importance of this approach is to overcome drawbacks in existing on-line Frequency Response Analysis (FRA) which is used to monitor impedance of the transformer winding to detect movement or deformation of transformer winding and predict early sign of transformer failure. Hence, it can be used for on-line FRA on operational transformer without expensive outage of the system.

Topology optimization for fiber-reinforced plastic (FRP) composite for frequency responses

The Frequency Response Analysis (FRA) is an efficient tool to diagnosis mechanical defects in transformer windings. After measurement of frequency responses, they must be compared to find any defects in the winding. The lack of clarity in the interpretation of measured frequency responses is the main problem of this method. This paper tries to solve this problem via a dimensional reduction of frequency response traces by Principal Component Analysis (PCA) to diagnose any short circuits in the winding. The precise location of the fault in the transformer winding is considered to be the main index, the effectiveness of which is presented by the results. Based on the approved transformer model, a dimensionality reduction method and feature selection are implemented to transformer's frequency response traces to map it from its main high-dimensional vector space to a lower dimensional one. It was shown that frequency response traces of Turn-to-Turn faults were separated from each other and the exact location of each fault was determined.

This paper presents various types of windings in a power transformer, their FEM methods, frequency response analysis etc. Frequency response analysis (FRA) standards are used in all places. In frequency response, one reference spectrum is first done and after fault is done, spectrum is compared with reference one. A 3-D model of a transformer is considered to show the field distribution, inductance and capacitance matrices, force analysis etc. The forces developed in a transformer winding has also been explained and transient case has been studied.

Frequency response analysis (FRA) has gained attention as a reliable diagnostic tool, to assess the mechanical integrity of power transformers, due to standardised FRA measurement methods. However, the assessment of FRA results is still a challenge as it demands skilful personnel for diagnosis. Since there is no definitive and reliable code available for FRA interpretation. In this study, the three‐dimensional (3D) finite integration technique is used to simulate the physical geometrical dimensions of a three‐phase transformer which emulate the behaviour of real transformer and frequency response measurements. This novel method eliminates the need for lumped parameter circuit models, as it provides the ability to extract the FRA signatures directly from the 3D winding model. Axial displacement of different levels is simulated in several connection schemes. It was found that variation of the inter‐winding capacitance due to the axial displacement possesses a linear relationship with the degree of axial displacement fault. This provides the possibility for the quantitative determination of winding axial displacement fault using FRA. A simple mathematical relation is derived for calculating the variation of inter‐winding capacitance and a geometrical factor is introduced to generalise the method. Finally, lookup charts are introduced to diagnose axial displacement fault in different transformers.

Induction motors are indispensable in industrial systems, and their failure, especially from short circuit faults, can lead to substantial operational losses. This paper presents a novel application of Frequency Response Analysis (FRA), traditionally used in transformer diagnostics, for identifying short circuit faults in a 5.5 HP, delta-connected three-phase induction motor. Five fault types were artificially introduced: turn-to-turn (TT), coil-to-coil (CC), phase-to-phase (PP), phase-to-ground (PG), and open-circuit (OC) faults. FRA measurements were conducted before and after fault application, and deviations were analyzed across three frequency regions: low <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\text{2 0 ~ H z}-\text{1 ~ k H z})$</tex>, medium <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\text{1 ~ k H z}-\text{6 0}$</tex> kHz), and high (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$60 \text{kHz}-1 \text{MHz}$</tex>). The trapezoidal rule was employed to calculate area deviations between normal and faulty conditions. Results show the highest deviations in the high-frequency region for CC (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$2.08 \times 10^{6}$</tex> a.u.), followed by OC <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(9.07 \times 10^{5}$</tex> a.u.) and PG (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$7.95 \times 10^{5}$</tex> a.u.). TT and PP faults showed moderate deviations in the medium frequency range. These distinct numerical signatures demonstrate the high sensitivity and diagnostic potential of FRA for early-stage fault detection in delta-connected motors. The approach is non-invasive, cost-effective, and practical for predictive maintenance applications.