It has been over two decades since the publication of pioneer works about the power transformer diagnostics based on monitoring of their acoustic fingerprints. Since then, there has been great progress in this field and the methods used are as complex as ever. Any unnecessary intervention on a power transformer implies its temporary disconnection from the power grid. The inability to supply electricity to the customer means not only financial loss for the utility but also generates a non-material loss, e.g., the loss of reputation to the customer. Faster, more accurate, more reliable, and less invasive diagnosis is the main reason behind development and improvement in this field. The main goal of this paper is to categorize and review state-of-the art of vibro-acoustic diagnostic methods for power transformers. This paper opens with a brief note about continuous condition monitoring, after which we overview the causes of transformer vibrations as well as the collection and preprocessing of diagnostic data. Then, we review and categorize works related to the acoustic condition assessment of power transformers considering both: feature extraction in the time, frequency, time-frequency domain, and mathematical modeling and system identification of dynamic systems.

/pdf/vibro-acoustic-methods-in-the-condition-assessment-of-power-596hhz2h8b.pdf

Vibro-Acoustic Methods in the Condition Assessment of Power Transformers: A Survey

This paper describes a differential algorithm for the protection of a three-phase transformer to differentiate transient phenomena, such as inrush currents and external faults from solid and turn-to-turn faults. This algorithm is based on the behavior of the second central moment (SCM) to identify the kind of event. Instantaneous differential currents are used as input signals to the algorithm once they are filtered and normalized. The algorithm compares the magnitude of the SCM with an established threshold based on the binomial distribution to achieve a successful identification of the event. If the magnitude of the SCM is above the limit, the algorithm identifies the event as a fault condition. Otherwise, the event is determined as a transient event or a steady-state condition. The threshold is setting-free if the transformer parameters are changed or if the harmonic content of the differential current varies. Also, the threshold does not have to be recalculated if the power system is modified. The D index was introduced to improve the fault-detection time when the current transformers experience saturation. This index uses the magnitude of the SCM as a basis and is compared with an established limit to detect the fault current. Both indices run in parallel, and if any of them does cross its respective threshold, a fault condition is determined. The algorithm is tested in a real-time digital simulator and is implemented in MATLAB. The algorithm was compared against the conventional differential protection with harmonic restraint to evaluate the performance of both indices in critical conditions. The results validate the performance of the algorithm and indicate that it can be the basis of a new algorithm to protect power transformers.

A Setting-Free Differential Protection for Power Transformers Based on Second Central Moment

Computational intelligence for preventive maintenance of power transformers

A fuzzy inference-based approach for estimating power transformers risk index

Transition to a low carbon emission transport is supported in all European countries, including Latvia. In this paper, a specific case of converting diesel bus into electric bus is analyzed. During its processing and development, real ready-made porotypes with field tests, and computer evaluation models are used.

Investigation of electrical bus traction motor dynamic using methods of physical and computer simulation

Technical condition of large power transformers has large impact on reliability of a power system since they are the connection points for generators and distribution system. Power transformers can experience various faults that can disrupt their reliable operation such as mechanical defects caused by magnetostriction or electrodynamic forces. Magnetostriction is a phenomenon occurring in transformer core in normal operation mode, yet in time it can cause the delamination of magnetic core resulting in higher vibrations and noise. Mechanical defects are complicated to detect with indirect measurements. Therefore, modelling elastic deformations of the magnetic core caused by magnetostriction combined with vibration measurements on the tank surface would create a more beneficial approach to mechanical defect diagnosis. The aim of this paper is to create model for magnetic core elastic deformation simulation and provide a case study. Authors developed this model in Matlab and COMSOL software.

Magnetostriction model of large power transformer magnetic core

Abstract Magnetostriction process creates vibrations within magnetic core of a power transformer. This effect can cause delamination of magnetic core layers and increase the vibration amplitudes on the surface of transformer tank. In this paper, a magnetostrictive vibration model is proposed for improved evaluation of the mechanical integrity of magnetic core and the finding of possible mechanical defects. This model is based on the simulation of magnetostrictive vibrations by replacing the magnetic core with mass and spring system, and application of a dynamic genetic algorithm in order to find the necessary system configuration. A case study is provided structurally modelling magnetic core in Matlab and Matlab Simulink with the analysis of simulated vibrations that indicate a possible mechanical defect.

/pdf/magnetostrictive-vibration-model-for-evaluation-of-591qcr77rb.pdf

Magnetostrictive Vibration Model for Evaluation of Mechanical Integrity of Power Transformer Magnetic Core

Power transformers are vital components of the power system. These electrical devices can experience multiple types of faults within them. Mechanical defects are relatively difficult to detect since they occur inside the structure of the power transformer. Magnetostriction can create this type of faults in magnetic core and electrodynamic forces can cause them in windings. Diagnostic methods mainly use vibration information from the surface of transformer. This is an indirect approach and causes additional errors since vibrations need to propagate transformer structure before sensors receive them. However, it is possible to calculate the mechanical situation in windings by modelling this part of the transformer as a mass and spring system with forces acting upon it and applying dynamic genetic algorithm. This paper describes a model created in COMSOL and Matlab software and a case study for a segment of windings displays the acquired results.

Dynamic genetic algorithm in model for vibrations of power transformer windings

A R T I C L E I N F O A B S T R A C T Article history: Received: 15 November, 2017 Accepted: 08 January, 2018 Online: 30 January, 2018 Reliable operation of a power transformer with a certain load depends on the technical condition of individual construction parts and the ability to prevent defects that can cause a failure. During the lifecycle of a transformer, valuable data is constantly accumulated, which forms the basis for technical or risk assessment of the equipment. Therefore it also serves as a ground for the decisions on further operation, or repairs, or replacement. To achieve this goal, data need to be systematized. Since technical condition indexing allows combining various types of data including results of diagnostic tests is used within the framework of this research. As part of a larger risk assessment methodology, algorithms for two indicators are proposed in this paper, and they are based on results of electrical measurements and analysis of oil parameters, respectively. The novelty of the algorithms for indicators introduced in this paper is based on analysis of features specific to the power system in Latvia such as large proportion of aged transformers, low loading level, significant variation in oil volumes, and statistics on typical faults. Proposed limits of parameters are verified with data from operation history. Taking into account the differences in the measurement periodicity, the indicator that is based on electrical measurements assesses the individual constructive parts of the transformer (windings and core, bushing and onload tap changer) separately, whereas the other, indicator combines the results of oil parameters into a single assessment. These indicators were verified by using 30 transformers from the Latvian power system and the obtained results coincide well with the operation history.

/pdf/development-of-indicators-for-technical-condition-indexing-rppuib5a8v.pdf

Development of Indicators for Technical Condition Indexing of Power Transformers

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