FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3005221154> ?p ?o ?g. }

• W3005221154 endingPage "24575" @default.
• W3005221154 startingPage "24561" @default.
• W3005221154 abstract "The measurement of partial discharges (PD) in electrical equipment or machines subjected to high voltage can be considered as one of the most important indicators when assessing the state of an insulation system. One of the main challenges in monitoring these degradation phenomena is to adequately measure a statistically significant number of signals from each of the sources acting on the asset under test. However, in industrial environments the presence of large amplitude noise sources or the simultaneous presence of multiple PD sources may limit the acquisition of the signals and therefore the final diagnosis of the equipment status may not be the most accurate. Although different procedures and separation and identification techniques have been implemented with very good results, not having a significant number of PD pulses associated with each source can limit the effectiveness of these procedures. Based on the above, this research proposes a new algorithm of artificial generation of PD based on a Deep Convolutional Generative Adversarial Networks (DCGAN) architecture which allows artificially generating different sources of PD from a small group of real PD, in order to complement those sources that during the measurement were poorly represented in terms of signals. According to the results obtained in different experiments, the temporal and spectral behavior of artificially generated PD sources proved to be similar to that of real experimentally obtained sources." @default.
• W3005221154 created "2020-02-14" @default.
• W3005221154 creator A5011482611 @default.
• W3005221154 creator A5018659221 @default.
• W3005221154 creator A5039840422 @default.
• W3005221154 creator A5044087954 @default.
• W3005221154 creator A5053921091 @default.
• W3005221154 date "2020-01-01" @default.
• W3005221154 modified "2023-10-16" @default.
• W3005221154 title "Artificial Generation of Partial Discharge Sources Through an Algorithm Based on Deep Convolutional Generative Adversarial Networks" @default.
• W3005221154 cites W1689711448 @default.
• W3005221154 cites W1885185971 @default.
• W3005221154 cites W1968713868 @default.
• W3005221154 cites W1971038944 @default.
• W3005221154 cites W1982069957 @default.
• W3005221154 cites W1990432345 @default.
• W3005221154 cites W2002067674 @default.
• W3005221154 cites W2020865134 @default.
• W3005221154 cites W2076063813 @default.
• W3005221154 cites W2087347434 @default.
• W3005221154 cites W2088936587 @default.
• W3005221154 cites W2105998701 @default.
• W3005221154 cites W2116983999 @default.
• W3005221154 cites W2117457887 @default.
• W3005221154 cites W2119101698 @default.
• W3005221154 cites W2139870867 @default.
• W3005221154 cites W2143257327 @default.
• W3005221154 cites W2154425812 @default.
• W3005221154 cites W2157832308 @default.
• W3005221154 cites W2165790482 @default.
• W3005221154 cites W2280498816 @default.
• W3005221154 cites W2295071068 @default.
• W3005221154 cites W2335262272 @default.
• W3005221154 cites W2592630487 @default.
• W3005221154 cites W2593174029 @default.
• W3005221154 cites W2602034649 @default.
• W3005221154 cites W2742822006 @default.
• W3005221154 cites W2772263446 @default.
• W3005221154 cites W2789995919 @default.
• W3005221154 cites W2792190413 @default.
• W3005221154 cites W2794907702 @default.
• W3005221154 cites W2799870331 @default.
• W3005221154 cites W2804383999 @default.
• W3005221154 cites W2805310132 @default.
• W3005221154 cites W2883723049 @default.
• W3005221154 cites W2887808321 @default.
• W3005221154 cites W2919115771 @default.
• W3005221154 cites W2921736909 @default.
• W3005221154 cites W2953928707 @default.
• W3005221154 cites W2962949934 @default.
• W3005221154 cites W2964303615 @default.
• W3005221154 cites W4249619477 @default.
• W3005221154 doi "https://doi.org/10.1109/access.2020.2971319" @default.
• W3005221154 hasPublicationYear "2020" @default.
• W3005221154 type Work @default.
• W3005221154 sameAs 3005221154 @default.
• W3005221154 citedByCount "17" @default.
• W3005221154 countsByYear W30052211542020 @default.
• W3005221154 countsByYear W30052211542021 @default.
• W3005221154 countsByYear W30052211542022 @default.
• W3005221154 countsByYear W30052211542023 @default.
• W3005221154 crossrefType "journal-article" @default.
• W3005221154 hasAuthorship W3005221154A5011482611 @default.
• W3005221154 hasAuthorship W3005221154A5018659221 @default.
• W3005221154 hasAuthorship W3005221154A5039840422 @default.
• W3005221154 hasAuthorship W3005221154A5044087954 @default.
• W3005221154 hasAuthorship W3005221154A5053921091 @default.
• W3005221154 hasBestOaLocation W30052211541 @default.
• W3005221154 hasConcept C108583219 @default.
• W3005221154 hasConcept C11413529 @default.
• W3005221154 hasConcept C115961682 @default.
• W3005221154 hasConcept C116834253 @default.
• W3005221154 hasConcept C119599485 @default.
• W3005221154 hasConcept C124101348 @default.
• W3005221154 hasConcept C127413603 @default.
• W3005221154 hasConcept C130143024 @default.
• W3005221154 hasConcept C134306372 @default.
• W3005221154 hasConcept C151201525 @default.
• W3005221154 hasConcept C153180895 @default.
• W3005221154 hasConcept C154945302 @default.
• W3005221154 hasConcept C165801399 @default.
• W3005221154 hasConcept C2780009758 @default.
• W3005221154 hasConcept C2988773926 @default.
• W3005221154 hasConcept C33923547 @default.
• W3005221154 hasConcept C41008148 @default.
• W3005221154 hasConcept C59822182 @default.
• W3005221154 hasConcept C81363708 @default.
• W3005221154 hasConcept C86803240 @default.
• W3005221154 hasConcept C99498987 @default.
• W3005221154 hasConceptScore W3005221154C108583219 @default.
• W3005221154 hasConceptScore W3005221154C11413529 @default.
• W3005221154 hasConceptScore W3005221154C115961682 @default.
• W3005221154 hasConceptScore W3005221154C116834253 @default.
• W3005221154 hasConceptScore W3005221154C119599485 @default.
• W3005221154 hasConceptScore W3005221154C124101348 @default.
• W3005221154 hasConceptScore W3005221154C127413603 @default.
• W3005221154 hasConceptScore W3005221154C130143024 @default.
• W3005221154 hasConceptScore W3005221154C134306372 @default.

• next