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Improvements To Single-Fault Isolation Using Estimated Parameters
Samantaray, A. K.
Ghoshal, S. K.
Article from Journal - ilmiah internasional
Simulation vol. 81 no. 12 (Dec. 2005)
fault detection and isolation
A method for finer fault isolation or localization in the model-based fault detection and isolation (FDI) paradigm is developed using parallely computed bond graph models. Many of the existing modelbased FDI methods are based on the evaluation of model consistency expressed in terms of analytical redundancy relations (ARR). These evaluations lead to residuals, and a number of sensors are to be installed in the plant to generate independent signatures needed for fault isolation. However, all the possible faults may not be isolable with the available instrumentation, and it is sometimes expensive or technically impossible to install necessary sensors in the plant to physically measure each and every state. In such situations, all component faults may not be uniquely isolated. However, a unique fault parameter subspace can be identified. One of the possible solutions, as proposed in this article, is to estimate parameters of that subspace from the ARR by assuming a single-fault hypothesis and then to incorporate the estimated values in separate models to run parallel with the plant during the fault. Thereafter, comparison of model behaviors leads to localization of the faulty parameters. This method is applied to an example system.
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