A data-driven simulation and Gaussian process regression model for hydraulic press condition diagnosis-Reference-Cited by-同舟云学术

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A data-driven simulation and Gaussian process regression model for hydraulic press condition diagnosis

Published:2024-01 Issue: Volume:59 Page:102276
ISSN:1474-0346
Container-title:Advanced Engineering Informatics
language:en
Short-container-title:Advanced Engineering Informatics

Author:

Jankovič Denis,Šimic Marko,Herakovič Niko

Funder

Javna Agencija za Raziskovalno Dejavnost RS

Ministrstvo za Izobraževanje, Znanost in Šport

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems,Building and Construction

Reference57 articles.

1. Bench testing of sensors utilized for in-line monitoring of lubricants and hydraulic fluids properties;Pochi;Sensors,2021

2. Research and experimental analyses of hydraulic cylinder position control mechanism based on pressure detection;Zhou;Machines,2022

3. Experimental investigation of friction behaviours for double-acting hydraulic actuators with different reciprocating seals;Pan;Tribol. Int.,2021

4. Acoustic emission-based condition monitoring and remaining useful life prediction of hydraulic cylinder rod seals;Pedersen;Sensors.,2021

5. Erosion behavior and influence of solid particles in hydraulic spool valve without notches;Liu;Eng. Fail. Anal.,2020

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Fractional-order transfer Q-learning based on modal decomposition and convolutional neural networks for voltage control of smart grids;Advanced Engineering Informatics;2024-10

2. A comparative study of machine learning regression models for production systems condition monitoring;Advances in Production Engineering & Management;2024-03-29

3. A preliminary investigation on DDPSS requirements to provide process quality as a service: example on laboratory scale;IFAC-PapersOnLine;2024

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