Diagnostics of low-capacity solar power station equipment with 2- and 3-valued logic
The paper outlines research issues relating to 2- and 3-valued logic diagnoses developed with the diagnostic system (DIA G 2) for the equipment installed at a low-capacity solar power station. The presentation is facilitated with an overview and technical description of the functional and diagnostic...
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| Format: | Article |
| Language: | English |
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Military University of Technology, Warsaw
2018-09-01
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| Series: | Biuletyn Wojskowej Akademii Technicznej |
| Subjects: | |
| Online Access: | http://biuletynwat.pl/gicid/01.3001.0012.6613 |
| _version_ | 1797711749464457216 |
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| author | Stanisław Duer Paweł Wrzesień Radosław Duer Dariusz Bernatowicz |
| author_facet | Stanisław Duer Paweł Wrzesień Radosław Duer Dariusz Bernatowicz |
| author_sort | Stanisław Duer |
| collection | DOAJ |
| description | The paper outlines research issues relating to 2- and 3-valued logic diagnoses developed
with the diagnostic system (DIA G 2) for the equipment installed at a low-capacity solar power station.
The presentation is facilitated with an overview and technical description of the functional and
diagnostic model of the low-power solar power station. A model of the low-power solar power station
(the tested facility, a.k.a. the test object) was developed, from which a set of basic elements and a set
of diagnostic outputs were determined and developed by the number of functional elements j of j.
The work also provides a short description of the smart diagnostic system (DIA G 2) used for the tests
shown herein. (DIA G 2) is a proprietary work. The diagnostic program of (DIA G 2) operates by comparing
a set of actual diagnostic output vectors to their master vectors. The output of the comparison
are elementary divergence metrics of the diagnostic output vectors determined by a neural network.
The elementary divergence metrics include differential distance metrics which serve as the inputs
for (DIA G 2) to deduct the state (condition) of the basic elements of the tested facility.
Keywords: technical diagnostics, diagnostic inference, multiple-valued logic, artificial intelligence. |
| first_indexed | 2024-03-12T07:10:40Z |
| format | Article |
| id | doaj.art-ec9188ce74c94995a68d4da09dee085e |
| institution | Directory Open Access Journal |
| issn | 1234-5865 |
| language | English |
| last_indexed | 2024-03-12T07:10:40Z |
| publishDate | 2018-09-01 |
| publisher | Military University of Technology, Warsaw |
| record_format | Article |
| series | Biuletyn Wojskowej Akademii Technicznej |
| spelling | doaj.art-ec9188ce74c94995a68d4da09dee085e2023-09-02T23:08:19ZengMilitary University of Technology, WarsawBiuletyn Wojskowej Akademii Technicznej1234-58652018-09-0167318519510.5604/01.3001.0012.661301.3001.0012.6613Diagnostics of low-capacity solar power station equipment with 2- and 3-valued logicStanisław Duer0Paweł Wrzesień1Radosław Duer2Dariusz Bernatowicz3Koszalin University of Technology, Faculty of Mechanical Engineering, 15-17 Raclawicka Str., 75-620 Koszalin, PolandVortex Energy Polska sp. z o.o., Department of Technical and Commercial Management, Rodła Square 8, 70-419 Szczecin, PolandKoszalin University of Technology, Faculty of Electronics and Computer Science, 2 Śniadeckich Str., 75-453 Koszalin, PolandKoszalin University of Technology, Faculty of Electronics and Computer Science, 2 Śniadeckich Str., 75-453 Koszalin, PolandThe paper outlines research issues relating to 2- and 3-valued logic diagnoses developed with the diagnostic system (DIA G 2) for the equipment installed at a low-capacity solar power station. The presentation is facilitated with an overview and technical description of the functional and diagnostic model of the low-power solar power station. A model of the low-power solar power station (the tested facility, a.k.a. the test object) was developed, from which a set of basic elements and a set of diagnostic outputs were determined and developed by the number of functional elements j of j. The work also provides a short description of the smart diagnostic system (DIA G 2) used for the tests shown herein. (DIA G 2) is a proprietary work. The diagnostic program of (DIA G 2) operates by comparing a set of actual diagnostic output vectors to their master vectors. The output of the comparison are elementary divergence metrics of the diagnostic output vectors determined by a neural network. The elementary divergence metrics include differential distance metrics which serve as the inputs for (DIA G 2) to deduct the state (condition) of the basic elements of the tested facility. Keywords: technical diagnostics, diagnostic inference, multiple-valued logic, artificial intelligence.http://biuletynwat.pl/gicid/01.3001.0012.6613technical diagnosticsdiagnostic inferencemultiple-valued logicartificial intelligence |
| spellingShingle | Stanisław Duer Paweł Wrzesień Radosław Duer Dariusz Bernatowicz Diagnostics of low-capacity solar power station equipment with 2- and 3-valued logic Biuletyn Wojskowej Akademii Technicznej technical diagnostics diagnostic inference multiple-valued logic artificial intelligence |
| title | Diagnostics of low-capacity solar power station equipment with 2- and 3-valued logic |
| title_full | Diagnostics of low-capacity solar power station equipment with 2- and 3-valued logic |
| title_fullStr | Diagnostics of low-capacity solar power station equipment with 2- and 3-valued logic |
| title_full_unstemmed | Diagnostics of low-capacity solar power station equipment with 2- and 3-valued logic |
| title_short | Diagnostics of low-capacity solar power station equipment with 2- and 3-valued logic |
| title_sort | diagnostics of low capacity solar power station equipment with 2 and 3 valued logic |
| topic | technical diagnostics diagnostic inference multiple-valued logic artificial intelligence |
| url | http://biuletynwat.pl/gicid/01.3001.0012.6613 |
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