DeepImpact: a deep learning model for whole body vibration control using impact force monitoring

Large capacity shovels are matched with large capacity dump trucks for gaining economic advantage in surface mining operations. These high impact shovel loading operations (HISLO) result in large dynamic impact force at truck bed surface. This impact force generates high-frequency shockwaves which expose the operator to whole body vibrations (WBVs). These WBVs cause serious injuries and fatalities to operators in mining operations. The present work focuses on developing solution technology for minimizing impact force on truck bed surface, which is the cause of these WBVs. The proposed technology involves modifying the truck bed structural design through the addition of synthetic rubber. Detailed experiments, with the technology implementation, showed a reduction of impact force by 22.60% and 23.83%, during the first and second shovel passes, respectively, which in turn reduced the WBV levels by 25.56% and 26.95% during the first and second shovel passes, respectively, at the operator's seat. To make the smart implementation of the technology feasible, a novel state-of-the-art deep learning model, 'DeepImpact,' is designed and developed for impact force real-time monitoring during a HISLO operation. DeepImpact showed an exceptional performance, giving anR(2), RMSE, and MAE values of 0.9948, 10.750, and 6.33, respectively, during the model validation. This smart and intelligent real-time monitoring system with design and process optimization would minimize the impact force on truck surface, which in turn would reduce the level of vibration on the operator, thus leading to a safer and healthier working environment at mining sites.

Automated summary

The research aims to reduce serious injuries caused by vibrations to operators in surface mining operations by modifying truck bed structural design through the addition of synthetic rubber to minimize impact force, and designing an intelligent monitoring system. Experiments showed a significant reduction in impact force and vibration levels, enhancing safety and health in the work environment.