Optical Radiation from an Electric Arc at Different Frequencies

Nagi, Łukasz; Kozioł, Michał; Zygarlicki, Jarosław

doi:10.3390/en13071676

Cited by 11 publications

(9 citation statements)

References 25 publications

(30 reference statements)

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“…When analyzing the influence of interferences, it is also important to stress the importance of external electromagnetic type interferences, which include own noise of preamplifiers, amplifiers, and data recording systems [39][40][41][42]. In the case of a small maximum value of the signal measured with the noise of the measuring equipment, there are analytical difficulties related to the extraction of relevant information from the recorded signal.…”

Section: Measurement Disturbancesmentioning

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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Section: Measurement Disturbancesmentioning

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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“…There is no work that would analyze the spectra for AC and DC in such a wide range. Arc power supply for different frequencies gives surprising results and is presented in our previous article [9]. The main aim of the research presented in this article was to determine and analyze the spectrum of optical radiation emitted by an electric arc in air for DC and different AC voltage frequencies.…”

Section: Introductionmentioning

confidence: 97%

“…A comprehensive review of the knowledge and needs concerning arc tracking is presented in the article [8]. In the paper [9], the authors analyzed the electric arc spectrum for alternating current (AC). In the earlier mentioned article [1], the research on CD spectra were related to direct current (DC).…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Optical Radiation Emitted by Electric Arc Generated at AC and DC Voltage

2020

Self Cite

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The article presents a comparison of the spectra of electromagnetic radiation emitted by an electric arc. The spectrum ranges from ultraviolet through visible light to near infrared. Spectra from electric arcs were compared for different frequencies of generating current and for direct current. Characteristic peaks for each measurement were described, and the percentage of individual components of light emitted through the arc was presented. An electric arc is an undesirable phenomenon in many areas, and its detection and control depends largely on its source. There are also areas where an electric arc is used. A better understanding of the physical phenomena involved in different arcs can help optimize the use of the electric arc. Safety and economy through the elimination of parasitic energy shares i.e., in the welding arc can be based on the control of the arc by controlling its optical spectrum. The optical method used in this study is one of the methods of electrical discharge detection in electrical devices and systems.

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“…Electric arcs generate noises at very different frequencies, which can be detected by various sensors [45]. If the place of the arc presence is known, magnetic sensors [23], radio antennas [24,25], IR, visual light, or UV [36,44,46,47] sensors can be used; otherwise, the current and voltage in the protected system can be measured. Then, the measured data need to be processed.…”

Section: Introductionmentioning

confidence: 99%

A Novel Algorithm for Fast DC Electric Arc Detection

Dołęgowski

Szmajda

2021

Energies

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Electric arcing is a common problem in DC power systems. To overcome this problem, the electric arc detection algorithm has been developed as a faster alternative to existing algorithms. The following issues are addressed in this paper: The calculation of the proposed algorithm of incremental decomposition of the signal over time; the computational complexity of Fast Fourier Transform (FFT) and the incremental decomposition; the test bench used to measure electric arcs at given parameters; the analysis of measurements using FFT; and the analysis of measurements using incremental decomposition. The parameters are the DC voltage, electric load, and width of the gap between electrodes. The results showed that the proposed algorithm allows for a faster calculation—about seven times faster than FFT—and cheaper implementation in electric arc detection devices than FFT.

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Optical Radiation from an Electric Arc at Different Frequencies

Cited by 11 publications

References 25 publications

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

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

Comparative Analysis of Optical Radiation Emitted by Electric Arc Generated at AC and DC Voltage

A Novel Algorithm for Fast DC Electric Arc Detection

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