Challenges in Mass Flow Estimation on Conveyor Belts in the Mining Industry: A Case Study

This paper presents a case study in indirect mass flow estimation of bulk material on conveyor belts, based on measuring the electric net energy demand of the drive motor. The aim is to replace traditional expensive measurement hardware, which results in benefits such as lowering overall costs as well as the possibility of working under harsh environmental conditions, such as dust, vibrations, weather, humidity, or temperature fluctuations. The data-driven model uses a dynamic estimation of the idle power in order to take into account time-varying influences. The case study has been developed in close collaboration between industry and scientific partners. Experiences gained from a first field prototype were used and incorporated to create an improved prototype setup, including a modular software infrastructure for automatically capturing all relevant measurement data. We discuss some of the challenges in development, like data quality, as well as our experiences in academia-industry collaboration. The presented case study showcases the importance to bring research into real-world applications for generating technology innovations.