Application of Dempster-Shafer theory in condition monitoring applications: a case study

Abstract This paper is concerned with the use of Dempster–Shafer theory in `fusion' classifiers. We argue that the use of predictive accuracy for basic probability assignments can improve the overall system performance when compared to `traditional' mass assignment techniques. We demonstrate the effectiveness of this approach in a case study involving the detection of static thermostatic valve faults in a diesel engine cooling system.

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