XRF Condition Monitoring of Oil Lubricated Machines

Lead Research Organisation: University of Sussex
Department Name: Sch of Engineering and Informatics

Abstract

The technology (called LCM) to be developed in this project uses X-ray fluorescence spectroscopy (XRF) to measure the elemental composition and abundances of microscopic tribological debris caught in machine oil filters. It also measures the composition of the lubricant which also changes with wear. These data can be used to predict impending failure, target preventative maintenance, diagnose faults, and ensure optimum machine operation. LCM can be used on any oil lubricated machine with an oil filter.

This project will build a fully functional demonstrator version of LCM, prove that it can operate in situ in real time on real running machinery, and prepare to bring it to market.

Predicting impending failure and providing early warning of oil wear and machine wear enables operators to avoid downtime by targeting preventative maintenance. Optimum operation and preventing failure can be the difference between profit and loss. In safety critical systems detecting impending failures can save lives. As such, operators dedicate much time, money, and effort to condition monitoring.

LCM is a novel system invented in the UK.

Publications

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Lioliou G (2021) X-ray and ? -ray spectroscopy using a 2 × 2 GaAs p + -i-n + diode array in Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment