Simplified flow rate estimation by decentralization of Kalman filters in automatic pouring robot

We describe here a method for estimating the pouring flow rate for tilting-ladle-type automatic pouring robot used in casting industries. To precisely pour molten metal into the mold, controlling the flow rate of liquid flowing out of the ladle is mandatory. However, it is difficult to directly measure the pouring flow rate by using a conventional flow meter, because the flow meter is damaged by the high temperature molten metal. Thus, the pouring flow rate estimation system using a state estimation theory has been proposed recently. In previous studies, the extended or the unscented Kalman filters have been applied to the pouring flow rate estimation. The flow rate estimation by the extended Kalman filter can be applied only the ladle with smooth shape. On the other hand, the flow rate estimation by the unscented Kalman filter can be applied to the ladles with complicated shape. However, it is difficult to perform a real-time computation of the unscented Kalman filter by the industrial controller. In this paper, the simplified flow rate estimation in which the Kalman filters are decentralized to the motor systems and the pouring process is proposed. The effectiveness of the proposed flow rate estimation method is demonstrated through simulations and experiments.