Jig Washer Bed Status-of-Loose Estimation Based on Knowledge Discovering

In the separating process with jig washer bed, an accurate online measurement of status-of-loose is essential for automatic control of jig washer. Via knowledge discovering, the model of fuzzy inference system (FIS) is built to evaluate status-of-loose offline, based on the relationship between status-of-loose and separation effect of jig washer bed. Separation effect is mainly described by imperfection and total misplaced material. Online estimation model of status-of-loose based on radial basis function neural network (RBFNN) is proposed due to its great advantages over multi-layer perception on the approximation and classification and its better abilities of learning and generalization. This model is trained by evaluating results of FIS and outputs of the buoy sensor. Simulation and application results indicate that the method is reasonable and effectual