Development of a multi-channel classifier of rail line states
The article deals with the construction of a three-channel invariant classifier that has the properties of classifying the states of rail lines into a set of classes that are invariant to changes in the longitudinal resistance of the rail line and the transverse conductivity of the insulation of the...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2023-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/48/e3sconf_apecvi2023_01020.pdf |
| _version_ | 1797740333870612480 |
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| author | Tarasov Evgeny Tarasova Anna Zolkin Alexander Kunygina Liliya Burakova Anzhelika |
| author_facet | Tarasov Evgeny Tarasova Anna Zolkin Alexander Kunygina Liliya Burakova Anzhelika |
| author_sort | Tarasov Evgeny |
| collection | DOAJ |
| description | The article deals with the construction of a three-channel invariant classifier that has the properties of classifying the states of rail lines into a set of classes that are invariant to changes in the longitudinal resistance of the rail line and the transverse conductivity of the insulation of the ballast material. Invariance is achieved taking into account the change in the transverse conductivity of the insulation and the longitudinal resistance of the rail line while compiling systems of equations of state for rail lines, which are the decisive functions of the classifier. The article shows that the three-channel method allows for the correct recognition of all three classes of rail line states by three decision functions with arguments - voltages and currents at the input and output of the rail line. The block diagram of the operation algorithm of the three-channel classifier of the states of the rail lines allows to form the recognition process and the majority classification depending on the states of the channels. The feasibility of the algorithm is confirmed by simulation studies on a mathematical model and graphical results. |
| first_indexed | 2024-03-12T14:10:57Z |
| format | Article |
| id | doaj.art-b2b2c0cbebb14d6faeee1c8fe82783c8 |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-03-12T14:10:57Z |
| publishDate | 2023-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-b2b2c0cbebb14d6faeee1c8fe82783c82023-08-21T09:01:23ZengEDP SciencesE3S Web of Conferences2267-12422023-01-014110102010.1051/e3sconf/202341101020e3sconf_apecvi2023_01020Development of a multi-channel classifier of rail line statesTarasov Evgeny0Tarasova Anna1Zolkin Alexander2Kunygina Liliya3Burakova Anzhelika4Samara State Transport University (SSTU)Samara State Transport University (SSTU)Povolzhskiy State University of Telecommunications and InformaticsVoronezh branch of the Federal State-Funded Educational Institution Rostov State Transport UniversityVoronezh branch of the Federal State-Funded Educational Institution Rostov State Transport UniversityThe article deals with the construction of a three-channel invariant classifier that has the properties of classifying the states of rail lines into a set of classes that are invariant to changes in the longitudinal resistance of the rail line and the transverse conductivity of the insulation of the ballast material. Invariance is achieved taking into account the change in the transverse conductivity of the insulation and the longitudinal resistance of the rail line while compiling systems of equations of state for rail lines, which are the decisive functions of the classifier. The article shows that the three-channel method allows for the correct recognition of all three classes of rail line states by three decision functions with arguments - voltages and currents at the input and output of the rail line. The block diagram of the operation algorithm of the three-channel classifier of the states of the rail lines allows to form the recognition process and the majority classification depending on the states of the channels. The feasibility of the algorithm is confirmed by simulation studies on a mathematical model and graphical results.https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/48/e3sconf_apecvi2023_01020.pdf |
| spellingShingle | Tarasov Evgeny Tarasova Anna Zolkin Alexander Kunygina Liliya Burakova Anzhelika Development of a multi-channel classifier of rail line states E3S Web of Conferences |
| title | Development of a multi-channel classifier of rail line states |
| title_full | Development of a multi-channel classifier of rail line states |
| title_fullStr | Development of a multi-channel classifier of rail line states |
| title_full_unstemmed | Development of a multi-channel classifier of rail line states |
| title_short | Development of a multi-channel classifier of rail line states |
| title_sort | development of a multi channel classifier of rail line states |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/48/e3sconf_apecvi2023_01020.pdf |
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