Diagnosis of Valves Using Entropy Indicators

Abidova, E.A.; Hegay, L.S.; Чернов, А. В.; Draka, O.E.; Pugachyova, O.J.

doi:10.26583/gns-2016-04-09

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определение набора диагностических признаков1

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2021

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Cited by 3 publications

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“…В работе [10] исследовались стохастические характеристики циклограмм (такие как энтропия) в зависимости от степени выраженности дефектов. В [10] теоретически по казана связь энтропии Шеннона с состоянием ЭПА и показана большая чувствительность энтропии Шеннона по отношению к отдельным видам дефектов.…”

Section: определение набора диагностических признаковunclassified

Expert Neural Network System for Diagnosing Еlectrically Actuated Valves

Trykov¹,

Trykova

Kotsoev

2021

YadEn

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Section: определение набора диагностических признаковunclassified

Expert Neural Network System for Diagnosing Еlectrically Actuated Valves

Trykov¹,

Trykova

Kotsoev

2021

YadEn

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Bearing defects diagnostics using the principal components analysis

Abidova

Lapkis

Чернов

2019

IOP Conf. Ser.: Mater. Sci. Eng.

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An expert neural system for diagnostics of motor-driven valves

Trykov¹,

Trykova²,

Kotsoyev³

2021

NUCET

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Trouble-free operation of motor-driven valves (MDV) is one of the key factors behind the operating safety of NPPs. As critical components, MDVs are a part of a safety system and a safety-related system. This imposes the highest possible requirements on the MDV reliability. MDVs are the most numerous category of the NPP components. Depending on design, one power unit contains 1500 to 3000 motor-driven valves alone. It follows from an analysis of the NPP failures that many of these are caused by failed motor-driven valves of safety and safety-related systems. The paper presents a description of an automated system for diagnostics of shutoff and control MDVs used in the NPP pipelines. The developed diagnostic algorithms make it possible to take into account the variability of the MDV technical parameters, while taking into account, at the same time, rated restrictions on diagnostic parameters, if any.

show abstract

Diagnosis of Valves Using Entropy Indicators

Cited by 3 publications

References 0 publications

Expert Neural Network System for Diagnosing Еlectrically Actuated Valves

Expert Neural Network System for Diagnosing Еlectrically Actuated Valves

Bearing defects diagnostics using the principal components analysis

An expert neural system for diagnostics of motor-driven valves

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