Introduction
In a previous blog post, we detailed our field-validation process on a Komatsu 930 haul truck, where we captured a 15-hour dataset by sampling a 6-axis IMU at 100 Hz. Following this validation, we embarked on a process of feature extraction to explore additional insights beyond road-condition monitoring and safety enhancement. This blog post delves into one such application: the automated detection of loading events on the haul truck by a dragline.
Feature extraction
To analyze loading events, we filtered the GPS dataset by delineating a square encompassing the dragline’s location. Subsequently, the vibration waveforms within this defined area were scrutinized to ascertain whether the loading of material into the bucket could be discerned through the readings of the accelerometers and gyroscopes.
Capturing and aggregation of loading events
The analysis revealed that loading events, characterized by the dragline filling the bucket with material, are distinctly captured by the accelerometers. This capability enables the counting of loading events, facilitating the aggregation of total materials excavated over time, on a truck-by-truck basis.
In conclusion, the successful detection of loading events by RoadGuard marks a significant advancement in production monitoring within mining operations. RoadGuard enables the accurate counting of loading events, providing valuable insights into material excavation rates on a truck-by-truck basis. This real-time production monitoring not only enhances operational efficiency but also empowers mine operators to make informed decisions for optimizing workflow and resource allocation. Excited to explore how RoadGuard can revolutionize production monitoring in your mining operation? Contact us today to learn more and take the next step toward maximizing your mine’s productivity and profitability.
