Detection of Partial Discharges in Transformers Using Acoustic Emission Techniques

Howells, E.; Norton, Edward T.

doi:10.1109/tpas.1978.354646

Cited by 78 publications

(16 citation statements)

References 11 publications

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“…Deheng et al (1988) show that the main frequency band for the magnetoacoustic emission phenomenon in investigations of transformers is 20-65 kHz, whereas the total band for the phenomena associated with the magnetization of transformer core sheets (HEB + MAE) is 10-65 kHz. Howells et al (Howells, Norton, 1978) determine the frequency range of magnetic noise as 30-60 kHz. In (Bengtsson et al, 1997), extend the band of signals associated with noises in the core up to 80 kHz.…”

Section: Magnetic Phenomena In Ferromagnetic Materialsmentioning

confidence: 99%

Identification of Acoustic Emission Signals Originating from the Core Magnetization of Power Oil Transformer

Olszewska

Witos

2016

Archives of Acoustics

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In this paper, the properties of AE signals originating from phenomena occurring during magnetization of ferromagnetic materials which are used to construct power transformer cores are presented. The AE signals in a selected power oil transformer were recorded and analyzed. The analysis included, i.e., time, frequency, and time-frequency analyses, calculations of amplitude distributions of the signals and defined AE descriptors, determination of the descriptor map on the side walls of transformers, as well as a detailed analysis of selected part of the signals.The maps of descriptors were analyzed in the frequency bands of 20-70 kHz, 70-100 kHz, and 100-200 kHz. The analysis of the properties of the signals was performed in time and frequency domains. Based on the analysis, there were identified the AE signals originating from the phenomena occurring during the core magnetization of a power oil transformer. To identify those phenomena, the maps of the ADC descriptor calculated in the band of 20-70 kHz when selecting the measurement points in which there were no AE sources from partial discharges were used.An analysis of magnetoacoustic emission signals in the bands of 70-100 kHz and 100-200 kHz was also performed. The analysis of the signal properties in such an extended frequency range allowed determining the properties of the magnetoacoustic signals coming from core sheets of power oil transformers.Keywords: power oil transformers; magnetization of transformers cores; magnetoacoustic emission. Magnetic phenomena in ferromagnetic materialsPhenomena in ferromagnetic materials are one of the sources of acoustic signals in power oil transformers. During the magnetization of ferromagnetic materials which are used to construct transformer core laminations, there occurs the reversible movement of domain boundaries (the so-called Bloch walls), irreversible movement of domain boundaries (Barkhausen effect), and rotation of magnetization vectors in the direction of the external magnetic field. Within these processes, there occur processes of creation of domain boundaries, movement of these boundaries, and their annihilation.The Barkhausen jump results in (i) the generation of an electromagnetic wave (Barkhausen field effect -HEB), (ii) a local change of the magnetization and defects in the crystal lattice and (iii) the generation of an acoustic wave (magnetoacoustic emission effect).The phenomenon of magnetoacoustic emission (MAE) consists in generating a sound wave by a jump motion of a 90• domain wall in a material with nonzero magnetostriction (Augustyniak, 1999). A MAE signal depends not only on the microstructure, stresses or the magnetization frequency, but also on the geometry of the sample and its demagnetization. MAE has a relatively short history. It was first reported by A.E. Lord in the middle 1970 -s (Lord,1975. He called that effect "the acoustic Barkhausen effect" by analogy with "the classic Barkhausen effect". Elastic waves generated during MAE are caused by changes in magnetostrictive stresses during t...

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Section: Magnetic Phenomena In Ferromagnetic Materialsmentioning

confidence: 99%

Identification of Acoustic Emission Signals Originating from the Core Magnetization of Power Oil Transformer

Olszewska

Witos

2016

Archives of Acoustics

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“…This method, first applied in [17] to transformers, is not subject to the electrical noise problems of the IEC method because the measurable ultrasonic wave emission is not affected by strong electric fields, however piezoelectric sensors can also be subject to large amounts of environmental noise within substations [5].…”

Section: A Pd Measurementmentioning

confidence: 99%

Compositional Modeling of Partial Discharge Pulse Spectral Characteristics

Baker

Stephen

Judd

2013

IEEE Trans. Instrum. Meas.

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This version is available at https://strathprints.strath.ac.uk/41327/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Strathprints administrator: strathprints@strath.ac.ukThe Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output. A number of different approaches to PD defect diagnosis have been developed to extract defect-specific information from PD pulse data in both the time and frequency domains. Frequency based PD pulse analysis has previously been demonstrated to offer a low-power approach to PD defect identification, where a mixture of passive and active analog electronics can be used to generate diagnostic features in a low-power device suited to wireless sensor network operation.This paper examines approaches to implementing diagnostic methods for frequency-based PD pulse diagnosis targeted at compositional frequency spectrum features in a computationally efficient manner. Dirichlet and Gaussian distributions are used to demonstrate the complex probabilistic form of fault class decision surfaces, which motivates the proposed application of the log ratio transform to frequency composition data.The results demonstrate that PD defects can be differentiated using these frequency-based methods and that employing the log ratio transform to the compositional frequency content data yields increases in classification accuracy without necessarily resorting to more complex classifiers.

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“…When a PD appears (about picocoulombs) it shows by different ways: as electrical pulse, through the residual compounds, the light emission, and as generation of ultrasonic pulses because of the high instantaneous dissipation energy [1,2]. Once the event of a PD is detected, its most important characteristics are its pulse amplitude (and duration) and the point or region it was produced from (the location of its source site through the ultrasounds time-of-flight).…”

Section: Requirements For Pd Measurementmentioning

confidence: 99%

“…PD in oil cause, in addition to the measurable electrical pulses, acoustic waves in the ultrasonic range (20 kHz-1 MHz) [2]. PD detection using acoustic methods has several advantages over electrical methods such as detection capability from outside of apparatus, no susceptibility to EM interference, high sensitivity, and capability of localizing the PD source site [1,5,6].…”

Section: Requirements For Pd Measurementmentioning

confidence: 99%

Electrical and ultrasonic measurement system for nondestructive testing

Pastoriza

Machado

Mariño

et al. 2009

2009 3rd International Conference on Signals, Circuits and Systems (SCS)

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The goal of this research work was the design and implementation of a measurement system that will be used for the partial discharge (PD) characterization in order to assess the condition of paper-oil (PO) insulation systems. In addition, this measuring instrument can be used to achieve a deeper understanding of the PD phenomena and their basis. This instrument integrates PD signals simultaneously measured using electric and ultrasonic sensors for making PD detection easier. The post-processing of the data captured from theses sensors allows a PD characterization based on the identification of the PD root cause and the localization of its source site. The performance of the proposed instrument was evaluated by sessions of controlled PD tests in the laboratory.

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Detection of Partial Discharges in Transformers Using Acoustic Emission Techniques

Cited by 78 publications

References 11 publications

Identification of Acoustic Emission Signals Originating from the Core Magnetization of Power Oil Transformer

Identification of Acoustic Emission Signals Originating from the Core Magnetization of Power Oil Transformer

Compositional Modeling of Partial Discharge Pulse Spectral Characteristics

Electrical and ultrasonic measurement system for nondestructive testing

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