Surrogate Models for Diagnostics of Electrical Equipment

被引：0
|
作者：
Kilin G.A. [1 ]
Kavalerov B.V. [1 ]
Suslov A.I. [1 ]
Shcherbinin D.A. [1 ]
机构：
[1] Perm National Research Polytechnic University, Perm
来源：
Russian Electrical Engineering | 2023年 / 94卷 / 11期
基金：
俄罗斯科学基金会;
关键词：
artificial neural networks; diagnostics; electrical equipment; neural network model; predictive analytics; surrogate models;
D O I：
10.3103/S1068371223110056
中图分类号：
学科分类号：
摘要：
Abstract: The possibility of using modern contactless methods of diagnostics and control of electrical equipment is considered. One such method is the use of artificial neural networks to assess the current state of electrical equipment, which allow timely detection of various malfunctions, assess its condition and prevent possible failures. © 2023, Allerton Press, Inc.
引用
收藏
页码：801 / 805
页数：4
相关论文
共 50 条
  • [1] THE NOISE DIAGNOSTICS OF MARITIME TRANSPORT ELECTRICAL EQUIPMENT
    Viktorovich, Klokov Vladimir
    Lazarevich, Losev Valeriy
    Igorevich, Ignatev Nikolay
    Vitalevich, Silin Nikolay
    MARINE INTELLECTUAL TECHNOLOGIES, 2015, 1 (03): : 144 - 149
  • [2] Intelligent Decision Support in the Electrical Equipment Diagnostics
    Eltyshev, D. K.
    Boyarshinova, V. V.
    PROCEEDINGS OF THE XIX IEEE INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND MEASUREMENTS (SCM 2016), 2016, : 157 - 160
  • [3] Residuals and Diagnostics for Ordinal Regression Models: A Surrogate Approach
    Liu, Dungang
    Zhang, Heping
    JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2018, 113 (522) : 845 - 854
  • [4] Diagnostics of electromechanical equipment by electrical power consumption parameters
    Gordeev, O., I
    Zakharenko, V. A.
    IV INTERNATIONAL SCIENTIFIC AND TECHNICAL CONFERENCE MECHANICAL SCIENCE AND TECHNOLOGY UPDATE (MSTU-2020), 2020, 1546
  • [5] Condition diagnostics of energized electrical equipment: Case studies
    Livshitz, Albert
    Chudnovsky, Bella H.
    2006 POWER ENGINEERING SOCIETY GENERAL MEETING, VOLS 1-9, 2006, : 4429 - 4434
  • [6] Exploitation stresses and challenges in diagnostics of electrical industrial equipment
    Florkowski, Marek
    2011 IEEE INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS (ISIE), 2011,
  • [7] Diagnostics of High Voltage Electrical Equipment in Power Engineering
    Khrennikov, Alexander Yu.
    Aleksandrov, Nikolay M.
    PROCEEDINGS OF THE 10TH INTERNATIONAL SCIENTIFIC SYMPOSIUM ON ELECTRICAL POWER ENGINEERING (ELEKTROENERGETIKA 2019), 2019, : 183 - 188
  • [8] Process equipment optimisation using CFD and surrogate models
    Stephens, D. W.
    Fawell, P. D.
    PROGRESS IN COMPUTATIONAL FLUID DYNAMICS, 2015, 15 (02): : 102 - 113
  • [9] Diagnostics of Industrial Electrical Equipment Using Modern Information Technologies
    Kolodenkova, Anna
    Vereshchagina, Svetlana
    2019 INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING, APPLICATIONS AND MANUFACTURING (ICIEAM), 2019,
  • [10] Partial discharge diagnostics and electrical equipment insulation condition assessment
    Stone, GC
    IEEE TRANSACTIONS ON DIELECTRICS AND ELECTRICAL INSULATION, 2005, 12 (05) : 891 - 904
12345