Safe Remote Drilling through Predictive Modeling of Hydraulic Hoses

Purpose and goal

This project is about modeling flexible hydraulic hoses attached to mining machines and has the goal of predicting hose states under different machine configurations in order to avoid damage during operations. For this, we will implement different modeling techniques from computational physics and machine learning and evaluate their efficacy for preventing hose damage under realistic use-case scenarios for heavy duty mining machines. By accurately modeling the motion of hydraulic hoses we aim at preventing hose damage and supporting remote and autonomous machine operation.

Expected results and effects

In this project we aim at deploying two different techniques: one analytic and one data-driven, for the task of modeling the behavior of hydraulic hoses. We will use these methods to predict where the hoses on a machine are situated and devise methodology to prevent collisions between machine and hoses. The modules developed in this project will allow an intelligent controller to avoid damage to the hydraulic fluid hoses powering the machine, thereby decreasing the need for machine maintenance and improving the reliability and cost-efficiency of remote and autonomous mining machines.

Planned approach and implementation

The project will be carried out by a consortium composed of one academic partner (Örebro University) and two industrial partners (Epiroc, Underground Rock Excavation division and Algoryx). The project will be coordinated by the academic partner.