Arc Fault Protections for Aeronautic Applications: A Review Identifying the Effects, Detection Methods, Current Progress, Limitations, Future Challenges, and Research Needs

Riba, Jordi-Roger; Moreno-Eguilaz, Manuel; Ortega, Juan Antonio

doi:10.1109/tim.2022.3141832

Cited by 22 publications

(8 citation statements)

References 92 publications

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“…While deep CNNs were initially used for image classification tasks, they have since been used for video analysis and recognition. However, the use of 1D sequence data for classification and prediction is relatively new [ 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 ]. The corona and non-corona categories can be seen as a sequential modeling effort, making 1D CNNs a suitable choice.…”

Section: Theoretical Study and Methodsmentioning

confidence: 99%

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Detection of Corona Faults in Switchgear by Using 1D-CNN, LSTM, and 1D-CNN-LSTM Methods

Alsumaidaee

Yaw

Koh

et al. 2023

Sensors

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The damaging effects of corona faults have made them a major concern in metal-clad switchgear, requiring extreme caution during operation. Corona faults are also the primary cause of flashovers in medium-voltage metal-clad electrical equipment. The root cause of this issue is an electrical breakdown of the air due to electrical stress and poor air quality within the switchgear. Without proper preventative measures, a flashover can occur, resulting in serious harm to workers and equipment. As a result, detecting corona faults in switchgear and preventing electrical stress buildup in switches is critical. Recent years have seen the successful use of Deep Learning (DL) applications for corona and non-corona detection, owing to their autonomous feature learning capability. This paper systematically analyzes three deep learning techniques, namely 1D-CNN, LSTM, and 1D-CNN-LSTM hybrid models, to identify the most effective model for detecting corona faults. The hybrid 1D-CNN-LSTM model is deemed the best due to its high accuracy in both the time and frequency domains. This model analyzes the sound waves generated in switchgear to detect faults. The study examines model performance in both the time and frequency domains. In the time domain analysis (TDA), 1D-CNN achieved success rates of 98%, 98.4%, and 93.9%, while LSTM obtained success rates of 97.3%, 98.4%, and 92.4%. The most suitable model, the 1D-CNN-LSTM, achieved success rates of 99.3%, 98.4%, and 98.4% in differentiating corona and non-corona cases during training, validation, and testing. In the frequency domain analysis (FDA), 1D-CNN achieved success rates of 100%, 95.8%, and 95.8%, while LSTM obtained success rates of 100%, 100%, and 100%. The 1D-CNN-LSTM model achieved a 100%, 100%, and 100% success rate during training, validation, and testing. Hence, the developed algorithms achieved high performance in identifying corona faults in switchgear, particularly the 1D-CNN-LSTM model due to its accuracy in detecting corona faults in both the time and frequency domains.

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Section: Theoretical Study and Methodsmentioning

confidence: 99%

“…Breakdowns in switchgear can be classified into several types, including arcing, tracking, surface discharge, and mechanical failure [ 6 ]. Corona discharge is a common issue that occurs in switchgear [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Detection of Corona Faults in Switchgear by Using 1D-CNN, LSTM, and 1D-CNN-LSTM Methods

Alsumaidaee

Yaw

Koh

et al. 2023

Sensors

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“…Moreover, once electrical discharges and high voltage arcing events appear it is very difficult to mitigate them, leading to catastrophic results. For this reason, the modelling of the electrical insulation of the conductors within the motor is particularly important, e.g., in [100], some limitations of existing arcing protections for aircraft applications are described.…”

Section: Safety and High Voltage At High Altitudementioning

confidence: 99%

Review of High Power and High Voltage Electric Motors for Single-Aisle Regional Aircraft

et al. 2022

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This paper presents a review of the state of the art in electric propulsion for regional aircraft in the MW range. The implications surrounding the implementation of this technology, such as the need of high-power density or the use of high-voltage at high-altitude, are presented. Along with the challenges, the available technologies to face them are reviewed. Those are, as follows, the emerging new motor topologies for this purpose, the winding technologies, the materials employed for electric motors for aircraft propulsion and the ground-breaking use of high-temperature superconductors (HTS) as a high-power density enabler. Finally, a conclusion is presented gathering the main ideas of the paper.INDEX TERMS Aircraft propulsion, electric motor, high-power, high-temperature superconductor, high-voltage.

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“…It is well known that low-pressure operation significantly reduces the dielectric strength of air [3][4][5], and thus, surface discharges tend to initiate at lower voltages compared to the voltages at which they initiate at sea-level. The reduction of the dielectric strength of atmospheric air at low pressure presents several disadvantages related to premature insulation degradation, insulation lifetime reduction and finally complete electrical breakdown [6] with the consequent risk of fire [7,8] and disconnection of circuits, which can lead to emergency landings, aborted operations or severe accidents [9].…”

Section: Introductionmentioning

confidence: 99%

Measurement of Corona Discharges under Variable Geometry, Frequency and Pressure Environment

Bas-Calopa

Riba

Moreno-Eguilaz

2022

Sensors

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Aeronautical industry is evolving towards more electric aircrafts (MEA), which will require much more electrical power compared to conventional models. To satisfy this increasing power demand and stringent weight requirements, distribution voltages must be raised, which jointly with the low-pressure environment and high operating frequencies increase the risk of electrical discharges occurrence. Therefore, it is important to generate data to design insulation systems for these demanding applications. To this end, in this work a sphere-to-plane electrode configuration is tested for several sphere geometries (diameters ranging from 2 mm to 10 mm), frequencies of 50 Hz, 400 Hz and 800 Hz and pressures in the 20–100 kPa range, to cover most aircraft applications. The corona extinction voltage is experimentally determined by using a gas-filled tube solar blind ultraviolet (UV) sensor. In addition, a CMOS imaging sensor is used to locate the discharge points. Next, to gain further insight to the discharge conditions, the electric field strength is calculated using finite element method (FEM) simulations and fitted to equations based on Peek’s law. The results presented in this paper could be especially valuable to design aircraft electrical insulations as well as for high-voltage hardware manufacturers, since the results allow determining the electric field values at which the components can operate free of surface discharges for a wide altitude range.

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Arc Fault Protections for Aeronautic Applications: A Review Identifying the Effects, Detection Methods, Current Progress, Limitations, Future Challenges, and Research Needs

Cited by 22 publications

References 92 publications

Detection of Corona Faults in Switchgear by Using 1D-CNN, LSTM, and 1D-CNN-LSTM Methods

Detection of Corona Faults in Switchgear by Using 1D-CNN, LSTM, and 1D-CNN-LSTM Methods

Review of High Power and High Voltage Electric Motors for Single-Aisle Regional Aircraft

Measurement of Corona Discharges under Variable Geometry, Frequency and Pressure Environment

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