A method for implementing performance monitoring on deep-level mine bulk air coolers

Abstract

Deep-level mining faces significant ventilation challenges, primarily due to increased heating effects from auto-compression and geothermal heat. To address these challenges and to maintain a safe and productive working environment, tertiary spot coolers like Finned Tube Bulk Air Coolers (FBACs) are employed to cool the ventilation air before it reaches the working areas. However, FBACs become less efficient over time, leading to higher temperatures in the working areas and adversely affecting mining safety, sustainability, and productivity. Monitoring the condition of these FBACs proves challenging due to remote installation locations and off-design operating conditions among others. Additionally, existing literature lacks effective methods to implement condition monitoring on these FBACs, with the majority of existing literature focussing mainly on heat exchangers operating at design conditions to detect fouling. This dissertation presents an innovative condition monitoring method tailored for FBACs operating under these challenging conditions to address the identified gap in literature. The method involves using a normalised prediction model and original equipment manufacturer (OEM) data to forecast the FBAC's outlet temperature based on inlet conditions. By comparing the forecasted and measured temperatures, the condition of the FBACs can be inferred.