A micro-computed tomography investigation of the breakdown paths in mica/epoxy machine insulation

Saxén, Carl; Gamstedt, E. Kristofer; Afshar, R.; Paulsson, Goran; Sahlén, F.

doi:10.1109/tdei.2018.007083

Cited by 9 publications

(4 citation statements)

References 5 publications

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“…Electrical discharges may ensue. An experimental validation of the above comes from a recent study on mica/epoxy machine insulation with the aid of micro computed tomography (μCT), which allows for 3-D reconstruction of the test object [41]. It was clearly shown that defects may coalesce into larger ones.…”

Section: Electrical Trees and Their Naturementioning

confidence: 96%

Propagation of Electrical Trees under the Influence of Mechanical Stresses: A Short Review

Danikas

Papadopoulos

Morsalin

2019

Eng. Technol. Appl. Sci. Res.

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The present paper deals with the phenomenon of electrical treeing in solid insulation, under the influence of mechanical stresses. In this short review, it is indicated that mechanical stressing can affect the propagation of electrical trees and –depending on whether it is tensile or compressive- it can facilitate (or render more difficult) the breakdown. In aged insulating materials, electrical trees can appear very quickly and can lead to breakdown.

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Section: Electrical Trees and Their Naturementioning

confidence: 96%

Propagation of Electrical Trees under the Influence of Mechanical Stresses: A Short Review

Danikas

Papadopoulos

Morsalin

2019

Eng. Technol. Appl. Sci. Res.

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“…Thermal stress results in hightemperature differentials, overload, and hot spots. Electrical stress [10] is related to the thickness of the electrical insulation of EMs.. It can lead to partial discharges (PD), which are small electric sparks that occur within air pockets of the insulation or on the surface of coils.…”

Section: Standard Diagnostic Proceduresmentioning

confidence: 99%

Perspective Chapter: Data Mining in Electrical Machine Maintenance Reports

Athanasios¹,

Falekas²,

Verginadis³

et al. 2023

New Trends in Electric Machines - Technology and Applications

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Industrial electrical machine maintenance logs pertinent information, such as fault causality and earlier indications, in the form of a semi-standardized report, previously written and now in digital form. New practices in predictive maintenance, state-of-the-art condition monitoring, include increasing applications of machine learning. Reports contain a large volume of natural text in various languages and semantics, proving costly for feature extraction. This chapter aims to present novel techniques in information extraction to enable literature access to this untapped information reserve. A high level of correlation between text features and fault causality is noted, encouraging research for extended application in the scope of electrical machine maintenance, especially in artificial intelligence indication detection training. Furthermore, these innovative models can be used for decision-making during the repair. Information from well-trained classifiers can be extrapolated to advance fault causality understanding.

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“…concentration caused by internal defects, the insulation degradation process can be accelerated, and a rapid failure fault can decrease the reliability of electrical equipment [8][9][10] . With improvements in the voltage level, capacity, and integration of electrical equipment, the failure rate of epoxy insulation components is rapidly increasing, which presents higher requirements and challenges to the insulation performance of epoxy resin [11][12][13] . In recent years, statistics on electrical equipment accidents, both domestically and internationally, indicate that incidents of electrical tree breakdown in epoxy resin insulation components have frequently occurred under the combined effects of mechanical stress and temperature gradient fields.…”

mentioning

confidence: 99%

Characterization of Electrical Tree Degradation of Epoxy Resin under Thermal and Temperature Stresses by Photoelastic Effect

Aung,

Wang,

et al. 2024

Chin. J. Electr. Eng.

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Epoxy resin is widely used in the support, insulation, and packaging components of electrical equipment owing to their excellent insulation, thermal, and mechanical properties. However, epoxy-resin insulation often suffers from thermal and mechanical stresses under extreme environmental conditions and a compact design, which can induce electrical tree degradation and insulation failure in electrical equipment. In this study, the photoelastic method is employed to investigate the thermal-mechanical coupling stress dependence of the electrical treeing behavior of epoxy resin. Typical electrical tree growth morphology and stress distribution were observed using the photoelastic method. The correlation between the tree length and overall accumulated damage with an increase in mechanical stress is determined. The results show that compressive stress retards the growth of electrical trees along the electric field, while tensile stress has accelerating effects. This proves that the presence of thermal stress can induce more severe accumulated damage.

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A micro-computed tomography investigation of the breakdown paths in mica/epoxy machine insulation

Cited by 9 publications

References 5 publications

Propagation of Electrical Trees under the Influence of Mechanical Stresses: A Short Review

Propagation of Electrical Trees under the Influence of Mechanical Stresses: A Short Review

Perspective Chapter: Data Mining in Electrical Machine Maintenance Reports

Characterization of Electrical Tree Degradation of Epoxy Resin under Thermal and Temperature Stresses by Photoelastic Effect

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