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
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