Data gathered from multiple sensors can be effectively fused for accurate monitoring of many engineering applications. In the last few years, one of the most sought after applications for multisensor fusion has been fault diagnosis. Dempster-Shafer Theory of Evidence along with Dempster's Combination Rule is a very popular method for multisensor fusion which can be successfully applied to fault diagnosis. But if the information obtained from the different sensors shows high conflict, the classical Dempster's Combination Rule may produce counter-intuitive result. To overcome this shortcoming, this paper proposes an improved combination rule for multisensor data fusion. Numerical examples have been put forward to show the effectiveness of the proposed method. Comparative analysis has also been carried out with existing methods to show the superiority of the proposed method in multisensor fault diagnosis.

iDCR: Improved Dempster Combination Rule for multisensor fault diagnosis

Rourab Paul
Ultimo
Supervision
2021-01-01

Abstract

Data gathered from multiple sensors can be effectively fused for accurate monitoring of many engineering applications. In the last few years, one of the most sought after applications for multisensor fusion has been fault diagnosis. Dempster-Shafer Theory of Evidence along with Dempster's Combination Rule is a very popular method for multisensor fusion which can be successfully applied to fault diagnosis. But if the information obtained from the different sensors shows high conflict, the classical Dempster's Combination Rule may produce counter-intuitive result. To overcome this shortcoming, this paper proposes an improved combination rule for multisensor data fusion. Numerical examples have been put forward to show the effectiveness of the proposed method. Comparative analysis has also been carried out with existing methods to show the superiority of the proposed method in multisensor fault diagnosis.
2021
Ghosh, Nimisha; Saha, Sayantan; Paul, Rourab
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1219318
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