A new system that enables early detection of potential problems on conveyor systems was recently unveiled by Tru-Trac at Electra Mining Africa. The monitoring technology is used to identify and mitigate conveyor belt anomalies and damage, thereby minimising downtime and enhancing efficiency and productivity.

The Rip Prevent+ system allows mines to optimise the performance of conveyor lines by preventing costly interruptions as a result of anomalies or rip events. Using a data-driven model and AI, the system can detect rip events on any conveyor belt type, including metal cord, pipe and fabric belts.

The system is designed to eliminate the need for sensor elements inside the belt, making it suitable  for all conveyor systems. It analyses data from the conveyor belt using an AI-based model, which is combined with an algorithm to detect anomalies and rips, generating data and signals that allow customers to stop the conveyor line before significant damage occurs. The system's model is able to compute data 50 times a second and can generate a signal to the programmable logic controller within 0.2 seconds, reducing the impact of rip events.

By stopping the conveyor belt when a possible rip event is detected, the system minimises associated damage, potentially reducing downtime as well as belt replacement and cleanup costs. The system's data-driven model is said to offer a number of advantages over inductive, magnetic and laser-based systems including reduced wear risk, suitability for all conveyor types and lower investment costs.

The Rip Prevent+ system is Web-based and accessible using an ethernet network connection, featuring a user-friendly interface and dashboard. The system incorporates additional functions that align with predictive maintenance strategies, such as mass flow calculation, condition monitoring, drive or motor monitoring, energy efficiency and electrical network analysis, aligning with predictive maintenance strategies.

The system is designed to be easy to install and can be commissioned within hours, with minimal downtime required. In addition, a subscription model offers a more affordable alternative and minimises initial capital investment.