Improved algorithm for calculating contributions to D-statistic

Abstract

D-statistic contribution analysis has been frequently used in practice for fault diagnosis. Existing algorithms for computing contributions to D-statistic tend to distribute cross-term contribution equally between two correlated variables. This leads to increased variance in contribution estimation and hence poor separability of faulty and normal variables. A new method for contribution calculation to D-statistic is proposed here which introduces a weighting scheme capable of distinguishing the contributions of two correlated variables. Simulation examples show that the proposed approach achieves improved resolution for distinguishing faulty and normal conditions.

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