Advantages Of Model-Based Fault Detection Approach

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Model-Based Approach The model-based fault detection approach employs a mathematical model of the system under observation, by assuming that a fault in the system will lead to deterministic changes in the model parameters. The model-based approach relies on comparing the model outputs with the actual system outputs to generate a residual signal, and based upon the properties of the generated residual signal, potential fault conditions are identified and useful information is extracted (Ding 2008). The basic concept of a typical model-based fault detection approach is illustrated in Fig. As indicated in Fig., there are two main stages in this approach, the first of which generates the residual which is then passed to the residual evaluation stage. Throughout the fault-free operation, the magnitude of the residual signal should be approximately zero, indicating that the proposed model is accurately describing the current behavior of the system. If, however, the value of the residual signal diverges from zero, appropriate processing and analysis techniques are applied to it in …show more content…

In such models since they are usually derived from first principles, using ordinary differential equations, different elements of the model are related to actual physical properties. Therefore, the main advantage of model-based techniques is the capability of detecting unanticipated faults as well as the replacement of hardware redundancy by analytical redundancy (Vachtsevanos et al. 2006). However, in many real world applications it is almost impractical to apply model-based diagnostic approaches, since many physical processes are too complex to develop accurate model. This will cause mismatch between the process and model outputs which, in turn, lead to large error signals usually giving rise to false alarms (Ding

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