Methods of Springs Failures Diagnostics in Ore Processing Vibrating Screens

Abstract

Abstract Large-scale vibrating screens are widely used in minerals processing industry. One of main components in any vibrating screen is a set of springs supporting the main body of machine with sieving material inside. These springs are subjected to cyclic loading and fatigue. Changing of their stiffness and subsequent failures have influence on the sieving efficiency and are difficult to predict, hence, online condition monitoring is required. Visual inspection and non-destructive diagnostic methods are not sufficient in this case. Noisy signals from vibration sensors installed on bearings supports of rotating unbalanced exciters are preferably used for diagnostics of spring failures. In this research, vibrating screen motion is represented by multi-DOF (degree-of-freedom) dynamic model, which accounts stochastic disturbances from incoming material and impacts on sieving decks. Specific features of vibration signals are analysed to identify springs deterioration modelled as the bilinear stiffness characteristics. Phase space plots (PSP) are considered as the promising method to recognise nonlinear behaviour of system under the presence of spring damage. Advantages are assessed of spring stiffness change and failures diagnostics as compared with other methods.