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Examination of Multivalent Diagnoses Developed by a Diagnostic Program with an Artificial Neural Network for Devices in the Electric Hybrid Power Supply System “House on Water”

Author

Listed:
  • Stanisław Duer

    (Department of Energy, Faculty of Mechanical Engineering, Technical University of Koszalin, 15–17 Raclawicka St., 75-620 Koszalin, Poland)

  • Konrad Zajkowski

    (Department of Energy, Faculty of Mechanical Engineering, Technical University of Koszalin, 15–17 Raclawicka St., 75-620 Koszalin, Poland)

  • Marta Harničárová

    (Department of Mechanical Engineering, Faculty of Technology, Institute of Technology and Business in České Budějovice, Okružní 10, 370 01 České Budějovice, Czech Republic)

  • Henryk Charun

    (Department of Energy, Faculty of Mechanical Engineering, Technical University of Koszalin, 15–17 Raclawicka St., 75-620 Koszalin, Poland)

  • Dariusz Bernatowicz

    (Faculty of Electronic and Informatic, Technical University of Koszalin, 2 Sniadeckich St., 75-620 Koszalin, Poland)

Abstract

This article presents the problem of diagnostic examination by the (DIAG) diagnostic system of devices of the House on Water (HoW) hybrid electric power system in the multi-valued (2, 3, and 4) state assessment. Forming the basis for the functioning of the (DIAG) diagnostic system is the measurement knowledge base of the object tested. For this purpose, the issues of building a diagnostic knowledge base for a hybrid power system for HoW are presented. The basis for obtaining diagnostic information for the measurement knowledge base is a functional and diagnostic analysis of the hybrid power system tested. The result of this analysis is a functional and diagnostic model of the research object. At the next stage of the work, on the basis of the model created, the sets of basic elements and the sets of measurement signals were determined together with the reference signals assigned. State classification in the (DIAG) system is based on an analysis of the value of the divergence metrics of the signal vectors tested. The purpose of the HoW diagnostic test is to assess an increase in the diagnoses developed by the intelligent diagnostic system (DIAG 2) in 4-valued logic in relation to the assessments in 3- and 2-valued logic.

Suggested Citation

  • Stanisław Duer & Konrad Zajkowski & Marta Harničárová & Henryk Charun & Dariusz Bernatowicz, 2021. "Examination of Multivalent Diagnoses Developed by a Diagnostic Program with an Artificial Neural Network for Devices in the Electric Hybrid Power Supply System “House on Water”," Energies, MDPI, vol. 14(8), pages 1-19, April.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:8:p:2153-:d:534802
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    References listed on IDEAS

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    1. Stanisław Duer, 2020. "Assessment of the Operation Process of Wind Power Plant’s Equipment with the Use of an Artificial Neural Network," Energies, MDPI, vol. 13(10), pages 1-17, May.
    2. Toshio Nakagawa, 2005. "Maintenance Theory of Reliability," Springer Series in Reliability Engineering, Springer, number 978-1-84628-221-8, June.
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    Cited by:

    1. Sungmok Hwang & Cheol Yoo, 2021. "Health Monitoring and Diagnosis System for a Small H-Type Darrieus Vertical-Axis Wind Turbine," Energies, MDPI, vol. 14(21), pages 1-18, November.

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