Low-Cost Industrial IoT System for Wireless Monitoring of Electric Motors Condition

Abstract

Condition monitoring of industrial equipment has become a critical aspect in Industry 4.0. This paper shows the design, implementation and testing of a low-cost Industrial Internet of Things (IIoT) system designed to monitor electric motors in real-time. This system can be used to detect operating anomalies and paves the way for building predictive maintenance models. The system is built using low-cost hardware components (wireless multi-sensor modules and single-board computers as gateways), open-source software and open cloud services, where all the relevant information is stored. The module collects real-time vibration data from electric motors. Vibration analyses in the temporal and frequency domains were carried out in both modules and gateways to compare their capabilities. This approach is also a springboard to using edge/fog computing to save cloud resources. A system prototype has been tested in the laboratory and in an industrial dairy plant. The results show that the proposed system can be used for continuous monitoring of any rotatory machine with similar accuracy to professional monitoring devices but at a significantly lower cost.

A Compact IIoT System for Remote Monitoring and Control of a Micro Hydropower Plant

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