Abstract
Vehicle vibrations caused by poor haul road conditions create multiple negative effects for mines, including slower cycle times, increased maintenance, and operator injury. Vibration levels in vehicles result in part from road roughness. Mine roads are mainly constructed from in-pit materials that are more likely to deteriorate overtime and require frequent maintenance to maintain a smooth surface. The decision for when and where road maintenance is conducted is primarily based on visual inspections. This method can provide subjective, inaccurate, and delayed response to adverse conditions. The recent increase in vehicle telemetry data allows instant access to several types of data; mainly being used for haul fleet dispatching, collision avoidance, and geologic surveying, telemetry data has yet to see widespread use in road maintenance dispatching. This paper examines current road roughness characterization techniques and current telemetry data streams. An initial case study was conducted using vibration and Global Navigation Satellite System (GNSS) telemetry data to determine road roughness. Data from three haul trucks under normal operating conditions were collected over the course of a week. The results of this case study demonstrate localized vibration levels can be used to objectively identify rough roads. This can be further developed to dispatch road maintenance crews leading to overall reduced mining costs and increased operator health. The researches propose continuing to full scale test using data from an entire fleet and longer timeframe.
Dynamic habitat models: using telemetry data to project fisheries bycatch