Sensitivity study of dynamic features to monitor the condition of vibrating screen isolators

Abstract

Vibrating screens form an integral part in the processing of bulk materials. The major components of a vibrating screen are purposefully designed and selected to contribute to the operational parameters required. The monitoring of each components function is essential to guarantee optimal performance and reduce downtime through predictive maintenance. This is the premise of a condition-based maintenance strategy which is becoming increasingly popular with the advent of new, affordable technology and advanced signal processing and classification algorithms. For vibrating screen components such as motors, gearboxes, and bearings there exist several validated monitoring strategies. However, for components such as vibrating screen isolators very few working strategies exist. The isolators are a notoriously difficult component to monitor due to the operating environment, limited access, isolator geometry and material composition. Each of these factors restrict the use of conventional non-destructive testing (NDT) and visual inspection. Another monitoring strategy is a static compression or displacement technique which suffers practical relevance for very large vibrating screens with numerous isolators. The most promising techniques for isolator condition monitoring are vibration-based approaches. One such approach is the evaluation of modal parameters by experimental modal analysis (EMA) and modal parameter extraction. The premise for this approach is that a deterioration of isolator condition will manifest as a change in stiffness which directly influences modal natural frequencies, particularly for the rigid body modes (RBM). Another approach is the use of signal processing to extract features directly from operational vibration measurements. These features need to be sensitive to faults such that their change will be indicative of a fault developing. The difficulty of the latter approach is that the evaluation of feature sensitivity is expensive when done experimentally. It is therefore common to use a model-based approach for feature evaluation. This implies the use of simulated measurements from which the feature sensitivity can be established. However, this does not excuse the use of some experiments to validate both the numerical model as well as the feature sensitivity results. The purpose of this dissertation is to evaluate the sensitivity of identified features to known faults in isolators using both numerically simulated and experimentally obtained measurements. The same premise as for an EMA approach is used to evaluate isolator deterioration (i.e. as a change in stiffness only). A numerical model of a vibrating screen is developed which uses linear approximations for the exciters and isolators. However, the experiments were performed on a vibrating screen with different isolator types considered (spring steel and rubber-based isolators). This was done to demonstrate the generic use of the features for isolators condition monitoring in that they are not coupled to only one ii isolator type. The features identified for this study are exploratory as research has yet to identify the most appropriate features for isolator condition monitoring. The entire operating envelope (startup, steady operation and coast down) of a vibrating screen, with no material on the deck, is considered. An EMA is also conducted to evaluate the behaviour of modal parameters for changes in isolator condition. The sensitivity results from both the simulated and experimental measurements are compared to one another. It was found that the features that undergo the highest percentage change and are the most sensitive to changes in isolator stiffness are those obtained from the transient startup and coast down envelopes. The steady operating orbit features underwent considerably smaller changes. The rigid body mode natural frequencies obtained by EMA and those extracted from the transient startup and coast down envelopes are comparable in magnitude and behaviour. However, from the experimental results the features and how they change are dependent on the type of isolator used, the temperatures of the isolators and exciters as well as the sensor locations.