Diagnostics of hydraulic drive reliabilityusing neural networks
Abstract
An approach to the development of an intelligent system for diagnosing the technical condition of hydraulic drives using big data analysis methods and neural networks is presented. The system allows you to automatically detect malfunctions during the operation of equipment, calculating reliability and residual resource indicators based on probabilistic models. The implementation of the proposed methodology improves diagnostic accuracy, minimizes the risk of failures and reduces maintenance costs by offering automated solutions for controlling and correcting hydraulic system parameters.
About the Author
M. L. Khaziev
Naberezhnye Chelny Institute of the Kazan (Volga Region) Federal University
Russian Federation
Russian Federation
Senior lecturer
References
1. IEEE 1451.1-1999 [Электронный ресурс] // IEEE Standard for a Smart Transducer Interface for Sensors and Actuators - Network Capable Application Processor Information Model. URL http://standards.ieee.org/findstds/standard/1451.1-1999.html (дата обращения 07.02.2025)
2. IEEE 1451.2-1997 [Электронный ресурс] IEEE Standard for a Smart Transducer Interface for Sensors and Actuators -Transducer to Microprocessor Communication Protocols and Transducer Electronic Data Sheet (TEDS) Formats. URL http://standards.ieee.org/findstds/standard/1451.2-1997.html (дата обращения 07.02.2025)
3. IEEE 1451.3-2003 [Электронный ресурс] IEEE Standard for a Smart Transducer Interface for Sensors and Actuators-Digital Communication and Transducer Electronic Data Sheet (TEDS) Formats for Distributed Multidrop Systems. URL http://standards.ieee.org/findstds/standard/1451.3-2003.html (дата обращения 07.02.2025)
4. IEEE 1451.4-2004 [Электронный ресурс] Standard for a Smart Transducer Interface for Sensors and Actuators- Mixed-Mode Communication Protocols and Transducer Electronic Data Sheet (TEDS) Formats. URL http://standards.ieee.org/findstds/standard/1451.4-2004.html (дата обращения 07.02.2025)
5. Патент РФ № 2016111021/11; 24.03.201 Зубков Е.В., Хазиев М.Л. Способ расширения диапазона регулирования АСР без потери устойчивости// Патент России № 2619746. 2017. Бюл. №14.
6. Сырицын Т.А. Эксплуатация и надежность гидро- и пневмоприводов: Учебник для Студентов вузов по специальности «Гидравлические машины, гидроприводы и гидропневмоавтоматика» / Т.А. Сырицын// М.: Машиностроение, 1990. – 248 с.: ил.
7. Хазиев Э.Л., Хазиев М.Л. Нечеткое управление пневмоприводом подачи фрезерно-расточного станка с применением спецификации XML // Современные наукоемкиетехнологии. – 2016. – № 9-1. – С. 84-88.
Review
For citations:
Khaziev M.L. Diagnostics of hydraulic drive reliabilityusing neural networks. Social-economic and technical systems: research, design and optimization. 2025;(1):114-122. (In Russ.)
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