On the novel approach to the On Load Tap Changer (OLTC) diagnostics based on the observation of fractal properties of recorded vibration fingerprints

Secic, Adnan; Kuzle, Igor

doi:10.1109/eurocon.2017.8011205

Cited by 7 publications

(4 citation statements)

References 14 publications

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“…Secic and Kuzle [43] proposed a diagnostic method based on signal fractal properties. Higuchi's algorithm was used on a signal envelope of a simulated OLTC vibration model from [44] to estimate the fractal dimension of the signal.…”

Section: ) Oltcmentioning

confidence: 99%

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

2019

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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.

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Section: ) Oltcmentioning

confidence: 99%

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

2019

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“…There are many methods to determine the technical condition of power switches, which are based on vibration measurement, arcing or motor current/voltage signal analysis, dynamic resistance measurement, and acoustic emission (AE) signal measurement [2,[5][6][7]. In [8], the authors investigated the possibility of using fractal analysis for damage detection in OLTC, while, in [9], a description of the dynamic resistance measurement (DRM) DV test method is given. In [10], a joint vibration and arcing measurement were applied for interpretation of events occurring during OLTC operation.…”

Section: Introductionmentioning

confidence: 99%

Study on the Influence of Measuring AE Sensor Type on the Effectiveness of OLTC Defect Classification

Wotzka

Cichoń

2020

Sensors

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The principal objective of this study is to improve the diagnostics of power transformers, which are the key element of supplying electricity to consumers. On Load Tap Changer (OLTC), which is the object of research, the results of which are presented in this article, is one of the most important elements of these devices. The applied diagnostic method is the acoustic emission (AE) method, which has the main advantage over others, that it is considered as a non-destructive testing method. At present, there are many measuring devices and sensors used in the AE method, there are also some international standards, according to which, measurements should be performed. In the presented work, AE signals were measured in laboratory conditions with various OLTC defects being simulated. Five types of sensors were used for the measurement. The recorded signals were analyzed in the time and frequency domain and using discrete wavelet transformation. Based on the results obtained, sets of indicators were determined, which were used as features for an autonomous classification of the type of defect. Several types of learning algorithms from the group of supervised machine learning were considered in the research. The performance of individual classifiers was determined by several quality evaluation measures. As a result of the analyses, the type and characteristics of the most optimal algorithm to be used in the process of classification of the OLTC fault type were indicated, depending on the type of sensor with which AE signals were recorded.

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“…The most frequent failures of a regulator occur due to low insulation or defects in the positioning system of the contact-changer. The switch is the most vulnerable part of failures, as it is an electromechanical switching mechanism, it undergoes mechanical and electrical stresses [8]. Generally, defects in the contacts or switch positioning mechanism are the most frequent causes of failures [9].…”

Section: Introductionmentioning

confidence: 99%

“In Situ” Evaluation of Mechanical Wear of Mobile Contacts of Electricity Voltage Regulator

et al. 2020

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This in situ study presents an analysis of the wear of mobile contacts of switching in an automatic line voltage regulator, regarding the surface wear of the contacts. It is interesting to analyze the contacts of this equipment due to the friction and wear generated during the contact change, in order to predict and contain mechanical operation failures. The contacts were evaluated for mass loss, profilometry, and analysis in a scanning electron microscope, after remaining in operation in the regulator for about one year and switching the contacts almost 2500 times. This study aims to evaluate the performance of the contacts, in terms of surface wear, correlating the number of switching and the effects generated on the contacts in terms of loss of mass and surface damage. With the results obtained, it is possible to conclude that with each switching maneuver the mobile contact loses about 0.002895% of its initial mass. In addition, there was a change in the topography of the sample, associated with its wear, suggesting that the wear is different along the surface of the regulator contacts studied.

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On the novel approach to the On Load Tap Changer (OLTC) diagnostics based on the observation of fractal properties of recorded vibration fingerprints

Cited by 7 publications

References 14 publications

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

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

Study on the Influence of Measuring AE Sensor Type on the Effectiveness of OLTC Defect Classification

“In Situ” Evaluation of Mechanical Wear of Mobile Contacts of Electricity Voltage Regulator

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