Payload estimation in AC electric mining shovels using drive signals

Shovels play a key role in surface mining operations. Keeping the shovel payload inside the limits defined by manufacturers will reduce mechanical components wear and overheating of electric drive train components. This paper presents and evaluates two online estimation algorithms of shovel payload based exclusively on shovel drive signals. Proposed algorithms use a model reference adaptive system (MRAS) structure based on a 3-dof integrated mechanical-electrical model of an ac drive rope shovel. The developed estimators based on the hoist and swing drives signals are evaluated first using an idealized truck loading cycle, and then using field signals of a production mining shovel, showing fast and accurate cross checked values. Having this information, operators will be able of operating their equipments inside the safety boundaries and avoid overloading the mining trucks.