This study presents a non-invasive, compact, and cost-effective approach for pollutant detection in hydraulic oil in the industrial environment, addressing the critical need to effectively detect the presence of contamination. Hydraulic oils are essential to the operation of industrial machinery, but contamination poses significant risks to efficiency and reliability. Conventional methods for contaminant monitoring can be complex, invasive, and expensive. To address this challenge, this study introduces a monitoring solution capable of detecting the presence of pollutants, in particular water, from the measurement of fluid dielectric characteristics. Through an experimental analysis, the performance of the proposed system in the presence of different pollutant concentrations is evaluated. The research aims to help prevent mechanical failures and accidents, improve operational efficiency, and extend equipment life. This innovative approach offers a compact and cost-effective alternative to conventional methods, promising significant improvements in industrial predictive maintenance.

A non-invasive measurement system for pollutant detection in oil: a preliminary analysis

Tari, L.;Milano, F.;Ferrigno, L.;Lanni, D.;Erme, G.;Ficco, G.;
2024-01-01

Abstract

This study presents a non-invasive, compact, and cost-effective approach for pollutant detection in hydraulic oil in the industrial environment, addressing the critical need to effectively detect the presence of contamination. Hydraulic oils are essential to the operation of industrial machinery, but contamination poses significant risks to efficiency and reliability. Conventional methods for contaminant monitoring can be complex, invasive, and expensive. To address this challenge, this study introduces a monitoring solution capable of detecting the presence of pollutants, in particular water, from the measurement of fluid dielectric characteristics. Through an experimental analysis, the performance of the proposed system in the presence of different pollutant concentrations is evaluated. The research aims to help prevent mechanical failures and accidents, improve operational efficiency, and extend equipment life. This innovative approach offers a compact and cost-effective alternative to conventional methods, promising significant improvements in industrial predictive maintenance.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11580/108565
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