Using the simplest neural network as a tool for fault location in power lines

Славутский, Л. А.; Ivanova, Nadezhda N.

doi:10.1063/5.0074926

Cited by 2 publications

(1 citation statement)

References 18 publications

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“…To process the data, the analytical platform "Deductor" was used, which includes the capabilities of preprocessing data, algorithms construction and the results graphical visualization. Two methods were used: the direct propagation ANN in the form of a multilayer perceptron with two hidden layers [20] and the "decision tree" method. The general scheme of data processing and analysis is shown in Figure 1.…”

Section: Attribute/mentioning

confidence: 99%

Machine learning techniques combination for selective and hierarchical analysis of psycho diagnostic data

Slavutskaya

Grigoryeva²,

Grigoryeva

et al. 2023

International Conference on Digital Transformation: Informatics, Economics, and Education (DTIEE2023)

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The research is devoted to the use of the decision tree method and artificial neural networks for the analysis of psycho diagnostic data. The possibility of applying these two data mining tools together to obtain additional information is explored. The analysis is carried out on the example of the psychological testing results of preschoolers' parents. Two widely known tests were used, which allow to assess the relationship between 27 psychological indicators having different numerical scales. The sample consisted of 496 respondents. It is shown that the combined use of the indicated processing techniques allows for the selective and hierarchical assessment of the interrelationships of multidimensional heterogeneous data. The proposed approach is available to a wide range of specialists from different fields of knowledge, since the tools used are included in widespread software.

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Section: Attribute/mentioning

confidence: 99%

Machine learning techniques combination for selective and hierarchical analysis of psycho diagnostic data

Slavutskaya

Grigoryeva²,

Grigoryeva

et al. 2023

International Conference on Digital Transformation: Informatics, Economics, and Education (DTIEE2023)

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Emergency Modes Modeling in a Complex Load Node: High-Frequency Components of Signals

Slavutskiy

2023

Vestn. Čuv. univ.

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The purpose of the study is to show the features of the occurrence of high–frequency components in current and voltage signals in various elements of the electrical complex by the example of modeling emergency modes in power lines and a complex load node and to analyze their mutual influence. Materials and methods. The signals of currents and voltages during transients in a power line and the load node with a three-winding transformer were modeled using the author’s software. The calculations are based on the method of synthetic circuits (Dommel’s algorithm). The main attention is paid to the occurrence of high-frequency components of current and voltage during short circuits and switching. Results. Modeling of the three-phase short circuit in a 110 kV transmission line when it is divided into P-sections demonstrates how significantly the level of high-frequency components differs in each of the three phases. This is manifested primarily in voltage signals. In a complex load node with a 110/35/10 kV transformer, short circuits and switching on the 35 kV side significantly affect the currents and voltages on the 10 kV side. It is shown that a higher level of high-frequency components of current signals corresponds to energy recovery modes in case of imbalance and run-out of the powerful asynchronous motor on the 10 kV side. The possibility of using the obtained results for the classification of faults in electrical systems is discussed. Conclusions. The level and spectral composition of the currents and voltages high-frequency components in transient modes depends on the initial phase and is of interest for the faults analysis and classification. The nature of these oscillations is determined by the resonant frequencies of the electrical circuits that occur during switching and short circuits.

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Using the simplest neural network as a tool for fault location in power lines

Cited by 2 publications

References 18 publications

Machine learning techniques combination for selective and hierarchical analysis of psycho diagnostic data

Machine learning techniques combination for selective and hierarchical analysis of psycho diagnostic data

Emergency Modes Modeling in a Complex Load Node: High-Frequency Components of Signals

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