FEM based 3D modelling of partial discharge detection and localization in an oil-filled power transformer using piezoelectric acoustic sensor

Meitei, Sorokhaibam Nilakanta; Borah, Kunal; Chatterjee, Saibal

doi:10.1515/teme-2019-0159

Cited by 6 publications

(3 citation statements)

References 29 publications

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“…where V is the potential, v; c 0 is the vacuum dielectric constant, 10 −9 /36π F/m; and c r is the relative permittivity. Te propagation of ultrasonic waves in GIS enclosure is solved by using the transient pressure acoustic model, as formulated in equation (7), and the ultrasonic waves are coupled to the pMUT by using acoustic-structural boundary conditions, as formulated in equation ( 8) [21].…”

Section: Governing Equations and Computational Methodsmentioning

confidence: 99%

Numerical Study of Acoustic‐Electric Signal Conversion for GIS Discharge Detection and Structure Optimization for pMUT

Zhao

et al. 2023

Mathematical Problems in Engineering

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With the development of microelectromechanical technology, the piezoelectric micromechanical ultrasonic transducer (pMUT) for ultrasonic detection of gas-insulated switchgear (GIS) breakdown discharge has become possible. In this article, the ultrasonic-solid-pMUT coupling simulation model was established to investigate the propagation process of ultrasonic waves in GIS enclosure and the conversion between ultrasonic and electric signals through pMUT. The output electric signals for the unsimplified top electrode and simplified top electrode model were compared, and the structure of receiving pMUT was optimized according to the main ultrasonic frequency range of GIS breakdown discharge and the key performance parameters of pMUT. First, it is found that the simulation results of the ultrasonic-solid-pMUT coupling model are reliable, and the frequency of the output electric signal of receiving pMUT is consistent with the input signal, while the amplitude of output signal attenuates greatly. Second, simplifying the top electrode of pMUT may lead to relatively large errors in simulation results. The output response of simplified pMUT is obviously weakened, and the inherent frequency is higher. Furthermore, it is noted that the pMUT inherent frequency (f0) is inversely proportional to the radius (R) of the piezoelectric layer and directly proportional to the substrate thickness (dsi). When the coverage rate of the top electrode is between 30% and 80%, the pMUT effective electromechanical coupling coefficient ( K e f f 2 ) is high and has a maximum value. Finally, it is indicated that the pMUT with the optimum structure is suitable for the detection of GIS breakdown discharge ultrasonic signals, and the K e f f 2 can be improved by 106.7%.

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Section: Governing Equations and Computational Methodsmentioning

confidence: 99%

Numerical Study of Acoustic‐Electric Signal Conversion for GIS Discharge Detection and Structure Optimization for pMUT

Zhao

et al. 2023

Mathematical Problems in Engineering

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“…In the first, the behavior of the electric current is analyzed to identify the transients generated by PD activity [18][19][20]. In the second, piezoelectric transducers capture the acoustic waves emitted by the discharges [21][22][23]. More specifically, in the case of transformers with dry insulation, the failures can occur in the epoxy resin [24], which constitutes the device's external insulation, and it is directly in contact with the environment.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Analysis Applied to the Partial Discharges Identification in Dry-Type Transformers by Hall and Acoustic Emission Sensors

Castro

Santos

Lucas

et al. 2022

Sensors

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Dry-type insulated transformers stand out for their higher applicability in substations, high-voltage instrumentation systems, and electrical installations. In this machine, the insulation system is constituted of dielectric materials such as epoxy resin and Nomex paper. Some critical issues in the operation of this equipment, such as overload, moisture, or heat, can induce a slow degradation of the physical–chemical properties of the dielectric materials, which can culminate in the total failure of the transformer. However, before the transformer’s shutdown, it is common to detect discharge activity in the insulation system. Based on this issue, this work proposes an experimental and comparative analysis between acoustic emission and Hall-effect sensors, aiming at differentiating discharges in epoxy resin and Nomex paper, materials that constitute the insulation of the dry-type insulated transformers. Two signal processing techniques were studied: traditional frequency analysis and discrete wavelet transform. The objective is to develop signal processing techniques to differentiate each type of discharge since different discharges require different maintenance actions. The results obtained indicate that acoustic emission sensors and Hall sensors are promising in differentiating discharge in epoxy resin and Nomex paper. Furthermore, the pattern recognition tools presented by this work, which associated the wavelet levels energies and the energy of the full signals with the average band and the equivalent bandwidth, were effective to perform feature extraction of power transformer condition.

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“…For the early detection of these failures, some non-destructive methods have shown promising results [3][4][5][6][7]. The acoustic emission method consists in the frequency analysis of the acoustic signal behavior, provided by the machine and when combined with temporal data, it is possible to establish patterns of evolution in the degradation of the transformer [2,[8][9][10]. In the final stages of the total failure in the transformer, it is common to detect discharges (DPs), which are low energy ionization processes in dielectrics materials, composing the machine insulation [11,12].…”

Section: Introductionmentioning

confidence: 99%

An Application of Wavelet Analysis to Assess Partial Discharge Evolution by Acoustic Emission Sensor

Santos

Castro

Binotto

et al. 2020

7th International Electronic Conference on Sensors and Applications

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Under normal operation, insulation systems of high voltage electrical devices, like power transformers, are constantly subjected to multiple types of stresses (electrical, thermal, mechanical, environmental, etc.), which can lead to a degradation of the machine insulation. One of the main indicators of the dielectric degradation process is the presence of partial discharges (PD). Although it starts due to operational stresses, PD can cause a progressive insulation deterioration, since it is characterized by localized current pulses that emit heat, UV radiation, acoustic, and electromagnetic waves. In this sense, acoustic emission (AE) transducers are wildly applied in PD detection. The goal is to reduce maintenance costs by predictive actions and avoid total failures. Becasue of the progressive deterioration, the assessment of the PD evolution is crucial for improving the maintenance planning and ensure the operation of the transformer. Based on this issue, this article presents a new wavelet -based analysis in order to characterize the PD evolution. Three levels of failures were carried out in a transformer and the acoustic signals captured by a lead zirconate titanate piezoelectric transducer were processed by discrete wavelet transform. The experimental results revealed that the energy of the approximation levels increasing with the failure evolution. More specifically, levels 4, 6, 7, and 10 presented a linear fit to characterize the phenomena, enhancing the applicability of the proposed approach to transformer monitoring.

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FEM based 3D modelling of partial discharge detection and localization in an oil-filled power transformer using piezoelectric acoustic sensor

Cited by 6 publications

References 29 publications

Numerical Study of Acoustic‐Electric Signal Conversion for GIS Discharge Detection and Structure Optimization for pMUT

Numerical Study of Acoustic‐Electric Signal Conversion for GIS Discharge Detection and Structure Optimization for pMUT

A Comparative Analysis Applied to the Partial Discharges Identification in Dry-Type Transformers by Hall and Acoustic Emission Sensors

An Application of Wavelet Analysis to Assess Partial Discharge Evolution by Acoustic Emission Sensor

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