Abstract:
Equipment failures lead to unexpected downtimes that often result in a significant capital and productivity loss. A condition monitoring system (CMS) is critical in alleviating such equipment downtime and to ensure reliability by providing real-time analytics on condition monitoring (CM) data. However, many small and medium enterprises find CM data inaccessible due to the requirement of expensive hard-wired data acquisition system and the difficulty to install the additional hardware and sensors within the existing plant set-up. In this regard, Internet of Things (IoT) brings a new opportunity to CMS, increasing the system's ability to collect and analyze data with more flexibility. This paper presents a proof-of-concept prototype of an IoT-enabled CMS that utilizes edge-devices to remotely collect various measurements from industrial equipment and carry out real-time CM. Moreover, the system leverages a cloud, where history of machinery health state is stored. The cloud also enables real-time access of machinery health status either on demand or push notifications. This cloud service can be further expanded to facilitate the integration of advanced data analytic tools for predictive maintenance. The effectiveness of the implemented system is presented by demonstrating remote data acquisition and spectral analysis of CM signals from a rotating machinery test-rig