Radiation in the Optical and UHF Range Emitted by Partial Discharges

Next generation aircrafts will use more electrical power to reduce weight, fuel consumption, system complexity and greenhouse gas emissions. However, new failure modes and challenges arise related to the required voltage increase and consequent rise of electrical stress on wiring insulation materials, thus increasing the risk of electrical arc appearance. This work performs a critical and comprehensive review concerning arc tracking effects in wiring insulation systems, underlying mechanisms, role of materials and possible mitigation strategies, with a special focus on aircraft applications. To this end an evaluation of the scientific and technological state of the art is carried out from the analysis of theses, research articles, technical reports, international standards and white papers. This review paper also reports the limitations of existing insulation materials, standard test methods and mitigation approaches, while identifying the research needs to comply with the future demands of the aircraft industry.

Section: Arc Tracking Detection Methodsmentioning

confidence: 99%

Arc Tracking Control in Insulation Systems for Aeronautic Applications: Challenges, Opportunities, and Research Needs

Riba

Gómez-Pau

Moreno-Eguilaz

et al. 2020

“…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

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.

“…An important part of the radiation is associated with corona falls within the ultraviolet spectrum [5] and the blue visible spectrum, so special care must be taken to detect this effect, particularly at the very early stage. A corona effect is often detected by means of specialized techniques, which often are very expensive, comprising electromagnetic radiation or audible noise [6], such as radio interference voltage (RIV) receivers, PD (partial discharges) detectors, UHF (Ultra High Frequency) sensors [7], optical spectrophotometers [8], or sound level meters [9]. However, by using such sensors, it is not always easy to locate the exact corona points.…”

Section: Introductionmentioning

confidence: 99%

Experimental Study of Visual Corona under Aeronautic Pressure Conditions Using Low-Cost Imaging Sensors

Riba

Gómez-Pau

Moreno-Eguilaz

2020

Visual corona tests have been broadly applied for identifying the critical corona points of diverse high-voltage devices, although other approaches based on partial discharge or radio interference voltage measurements are also widely applied to detect corona activity. Nevertheless, these two techniques must be applied in screened laboratories, which are scarce and expensive, require sophisticated instrumentation, and typically do not allow location of the discharge points. This paper describes the detection of the visual corona and location of the critical corona points of a sphere-plane gap configurations under different pressure conditions ranging from 100 to 20 kPa, covering the pressures typically found in aeronautic environments. The corona detection is made with a low-cost CMOS imaging sensor from both the visible and ultraviolet (UV) spectrum, which allows detection of the discharge points and their locations, thus significantly reducing the complexity and costs of the instrumentation required while preserving the sensitivity and accuracy of the measurements. The approach proposed in this paper can be applied in aerospace applications to prevent the arc tracking phenomenon, which can lead to catastrophic consequences since there is not a clear protection solution, due to the low levels of leakage current involved in the pre-arc phenomenon.