Centrifugal pumps represent 70% of all kinds of pumps and are ubiquitous in the industrial world especially in heating, air conditioning and sewage applications. Although modern pumps can last for many years, their sudden failure can lead to undesirable or catastrophic disruptions.

The purpose of this project is to develop a low-cost IoT based predictive maintenance solution to continuously monitor the pump health using motor current signature analysis (MCSA) and predict failures using a combination of signal processing and machine-learning algorithms.An MCSA monitoring system is deployed by attaching current clamps, used as transducers, to power supply wires without requiring direct physical access to the pump itself. The proposed system consists of custom hardware modules that stream the pump data to the cloud, and a back-end for storage, visualisation and intelligent analysis.

The project is a collaboration with Uptime Systems Ltd and was funded by Innovate UK (2019-2023).

More details on the Early Detection of Electric Pump Failures project page

This project was funded internally under the England Call fund scheme  to use innovative models and methodologies for participatory research. One of the project aims was to start a new research theme within the engineering cluster, around the filtration of industrial sludge. This is now one of the active themes of research activities within IRESE, and continues to expand collaboration with industrial partners through new investigation, bid writing and consultancy work.