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dc.contributor.authorGalina Malykhina
dc.contributor.authorDmitry Tarkhov
dc.contributor.authorViacheslav Shkodyrev
dc.contributor.authorTatiana Lazovskaya
dc.contributor.otherHigh School of Cyber-Physical Systems and Control, Peter the Great St. Petersburg State Polytechnic University, 195251 Saint Petersburg, Russia
dc.contributor.otherScientific and Technological Centre (STC) “Mathematical Modelling and Intelligent Control Systems”, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
dc.contributor.otherHigh School of Cyber-Physical Systems and Control, Peter the Great St. Petersburg State Polytechnic University, 195251 Saint Petersburg, Russia
dc.contributor.otherScientific and Technological Centre (STC) “Mathematical Modelling and Intelligent Control Systems”, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
dc.date.accessioned2025-10-09T05:30:58Z
dc.date.available2025-10-09T05:30:58Z
dc.date.issued01-04-2021
dc.identifier.urihttps://www.mdpi.com/1424-8220/21/8/2891
dc.identifier.urihttp://digilib.fisipol.ugm.ac.id/repo/handle/15717717/41113
dc.description.abstractIt is impossible to effectively use light-emitting diodes (LEDs) in medicine and telecommunication systems without knowing their main characteristics, the most important of them being efficiency. Reliable measurement of LED efficiency holds particular significance for mass production automation. The method for measuring LED efficiency consists in comparing two cooling curves of the LED crystal obtained after exposure to short current pulses of positive and negative polarities. The measurement results are adversely affected by noise in the electrical measuring circuit. The widely used instrumental noise suppression filters, as well as classical digital infinite impulse response (IIR), finite impulse response (FIR) filters, and adaptive filters fail to yield satisfactory results. Unlike adaptive filters, blind methods do not require a special reference signal, which makes them more promising for removing noise and reconstructing the waveform when measuring the efficiency of LEDs. The article suggests a method for sequential blind signal extraction based on a cascading neural network. Statistical analysis of signal and noise values has revealed that the signal and the noise have different forms of the probability density function (PDF). Therefore, it is preferable to use high-order statistical moments characterizing the shape of the PDF for signal extraction. Generalized statistical moments were used as an objective function for optimization of neural network parameters, namely, generalized skewness and generalized kurtosis. The order of the generalized moments was chosen according to the criterion of the maximum Mahalanobis distance. The proposed method has made it possible to implement a multi-temporal comparison of the crystal cooling curves for measuring LED efficiency.
dc.language.isoEN
dc.publisherMDPI AG
dc.subject.lccChemical technology
dc.titleIntelligent LED Certification System in Mass Production
dc.typeArticle
dc.description.keywordsefficiency
dc.description.keywordsLED
dc.description.keywordsmulti-temporal comparison
dc.description.keywordscascade neural network
dc.description.keywordsgeneralized statistical moments
dc.description.doi10.3390/s21082891
dc.title.journalSensors
dc.identifier.e-issn1424-8220
dc.identifier.oaioai:doaj.org/journal:1769678a0e4d456ba17469ec934438c1
dc.journal.infoVolume 21, Issue 8


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