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UBC Theses and Dissertations

Dynamic modeling, parameter identification, payload estimation, and non-contact arm geometry sensing of the mining cable shovel Rasuli, Abdol Rasul

Abstract

This thesis presents the application of the least squares estimation technique in identification of the cable shovel parameters and monitoring its payload. Both detailed and simplified dynamic models of the cable shovel are derived by modeling the DC motors and analyzing such nonlinear effects as inertia, Coriolis, centripetal, and friction. Mathematical methods, including the interactive Newton-Euler technique, have been used to obtain the kinematic and dynamic equations of the shovel, and establish the relationship between the shovel parameters and the payload inside the bucket. The cable shovel bucket is also referred to as “dipper”. An on-line parameter identification scheme was developed and experimentally verified in order to estimate the cable shovel parameters. A data acquisition system was installed on a P&H2100 cable shovel in the Sarcheshmeh Copper mine, located in Iran, where it logged the cable shovel data for several loading cycles. The payload was dynamically estimated using the simplified dynamic cable-shovel model developed in this thesis. The accuracy and repeatability of the algorithm has been verified based upon the cable-shovel data logged during its normal operation at the mine. In the course of this thesis project, I also devised a novel approach for non-contact sensing of the dynamic arm-geometry of the cable-shovel. A prototype sensor apparatus was designed and assembled that measures the dipper handle angle, the swing angle, and the dipper handle length. Different sensors such as gyroscopes, magnetometers, accelerometers, and a laser sensor are integrated into Arm Geometry Sensor (AGS) apparatus. The AGS apparatus is installed on the saddle block and measures all cable shovel joint variables without having direct physical contact with the links or joints. The AGS apparatus was employed during field trials on the on P&H2100 cable shovel and verified to effectively sense the shovel joint variables with acceptable accuracy.

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Attribution-NonCommercial-NoDerivatives 4.0 International