Near Real-time Adaptation of DAS Conveyor Monitoring

This project describes the fourth phase of the Condition Conveyor Monitoring System (CCMS) using Distributed Acoustic Sensing (DAS) methodology. The previous research phases were Phase 1 [C24014] which demonstrated the feasibility of the system. Phase 2 [C25054] demonstrated proof of concept on site. Phase 3 [C27075] used advanced data analysis and feature detection to improve the classifier of the system. Finally this work Phase 4 [C28025], focused on optimising the system and developing it to be able to run continuously.

Industry feedback during a previous research phases suggested that continuous monitoring would result in the highest impact from a commercial product. The objective of this project was to develop a near-real-time system to handle the data in a continuous manner.

The key result was the implementation of novel algorithms that changed the processing methods from batch process to continuous process mode. This was done by exploring and testing different algorithms followed by optimisation of the code base. The algorithms were tested and explored extensively to be able to get theoretical response times for the system. Building on those results theoretical models for processing times were built. By analysing the theoretical models further bottlenecks were discovered and solved. The final output is a system that can run continuously and in near-real-time.