Load weight estimation on an excavator in static and dynamic motions

Abstract

Excavators are one of the commonly used types of hydraulic machines in earth moving operations. The material handled is often transferred by dump trucks having a payload capacity that should not be exceeded. Payload monitoring systems are needed in order to prevent the possible problems during the delivery, increase the work efficiency, reduce the cost, and obtain the product information automatically without the requirement of truck scales. In this study, we propose a novel approach to estimate the load weight in the bucket of the excavator when the machine links are in motion. We consider the excavator as a three-revolute joint manipulator in vertical plane with the boom, the stick, and the bucket links. We rewrite the dynamic torque equations in a decoupled form as the linear combination of dynamic parameters and functions of joint angles, velocities, and accelerations. We perform least squares estimation to identify these parameters allowing us to predict the no load joint torques for any configuration of the links. We show that the most accurate torque prediction is the difference between the boom torque and the stick torque. We then derive the relation between the joint torques with and without the load, which are functions of the dynamic parameters. Using these equations, we can estimate the load weight. The relation becomes simpler when the links are stationary, since only the gravitational parameters remain present in the torque equations. The relation in dynamic case requires the parameters of the polar coordinates for the center of gravity of the bucket and we show that these parameters can be estimated with the knowledge of the empty bucket mass. We summarize our findings on load weight estimation for different cases including stationary poses and dynamic trajectories on free space and discuss the results. Although the friction is neglected throughout the modeling, the results obtained indicate that the effect of the static friction plays an important role in the accuracy of the estimated payload mass. We show that our dynamic model based solution is very promising, and exhibit only 2% error for high enough velocities.