DEVELOPMENT OF INTELLIGENT SYSTEMS FOR PURIFYING THE WORKING FLUID IN EXCAVATOR HYDRAULIC DRIVES USING SENSOR MONITORING AND ADAPTIVE FILTRATION

This article examines the issue of improving the efficiency of cleaning the working fluid in excavator hydraulic systems as one of the key factors in ensuring the reliability and durability of construction machinery. The aim of the study is to develop an intelligent cleaning system based on the use of sensor-based monitoring of the working fluid’s condition and adaptive filtration methods. An approach is proposed for constructing a mathematical model of contamination processes, which takes into account the dynamics of particle accumulation, their particle size distribution and the influence of the hydraulic drive’s operating modes. Based on this model, a sensor monitoring system has been implemented, providing continuous real-time measurement of fluid parameters (contamination level, temperature, viscosity). An intelligent control algorithm has been developed that adapts the filtration parameters according to the current state of the system and predicted operating conditions. The scientific novelty of the work lies in the combination of sensor-based monitoring, adaptive filtration and intelligent control within a single system for purifying the working fluid of excavator hydraulic drives. The practical significance of the results obtained lies in the possibility of using them to modernise existing hydraulic systems and implement them in modern construction machinery.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-29
DOI
https://doi.org/10.5281/zenodo.21031905
Primary Topic
Hydraulic and Pneumatic Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DEVELOPMENT OF INTELLIGENT SYSTEMS FOR PURIFYING THE WORKING FLUID IN EXCAVATOR HYDRAULIC DRIVES USING SENSOR MONITORING AND ADAPTIVE FILTRATION

Ihor Pimonov, Yuriy Saliy, Oleksandr Yaryzhko, Tkachenko Mykhailo et al.
Zenodo (CERN European Organization for Nuclear Research)
Hydraulic and Pneumatic Systems
article

DEVELOPMENT OF INTELLIGENT SYSTEMS FOR PURIFYING THE WORKING FLUID IN EXCAVATOR HYDRAULIC DRIVES USING SENSOR MONITORING AND ADAPTIVE FILTRATION

Ihor Pimonov, Yuriy Saliy, Oleksandr Yaryzhko, Tkachenko Mykhailo, Andrii Yefymenko
article en

Abstract

This article examines the issue of improving the efficiency of cleaning the working fluid in excavator hydraulic systems as one of the key factors in ensuring the reliability and durability of construction machinery. The aim of the study is to develop an intelligent cleaning system based on the use of sensor-based monitoring of the working fluid’s condition and adaptive filtration methods. An approach is proposed for constructing a mathematical model of contamination processes, which takes into account the dynamics of particle accumulation, their particle size distribution and the influence of the hydraulic drive’s operating modes. Based on this model, a sensor monitoring system has been implemented, providing continuous real-time measurement of fluid parameters (contamination level, temperature, viscosity). An intelligent control algorithm has been developed that adapts the filtration parameters according to the current state of the system and predicted operating conditions. The scientific novelty of the work lies in the combination of sensor-based monitoring, adaptive filtration and intelligent control within a single system for purifying the working fluid of excavator hydraulic drives. The practical significance of the results obtained lies in the possibility of using them to modernise existing hydraulic systems and implement them in modern construction machinery.

Zenodo (CERN European Organization for Nuclear Research)
Kharkiv National Automobile and Highway University (UA)
Industry, innovation and infrastructure
Openalex Percentile: Top 13%
Hydraulic and Pneumatic Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.