A New Evidential Reasoning Rule Considering Evidence Correlation with Maximum Information Coefficient and Application in Fault Diagnosis DOI Creative Commons
Shanshan Liu, Guanyu Hu, Shaohua Du

и другие.

Sensors, Год журнала: 2025, Номер 25(10), С. 3111 - 3111

Опубликована: Май 14, 2025

The evidential reasoning (ER) rule has been widely adopted in engineering fault diagnosis, yet its conventional implementations inherently neglect evidence correlations due to the foundational independence assumption required for Bayesian inference. This limitation becomes particularly critical practical scenarios where heterogeneous collected from diverse sensor types exhibits significant correlations. Existing correlation processing methods fail comprehensively address both linear and nonlinear inherent such systems. To resolve these theoretical constraints, this study develops MICER-a novel ER framework that incorporates analysis based on maximum mutual information coefficient (MIC). proposed methodology advances theory by systematically integrating interdependencies, thereby expanding boundaries of rules their applicability real-world diagnosis. Flange ring loosening diagnosis flywheel system cases are experimentally verified effectiveness method is demonstrated.

Язык: Английский

A New Evidential Reasoning Rule Considering Evidence Correlation with Maximum Information Coefficient and Application in Fault Diagnosis DOI Creative Commons
Shanshan Liu, Guanyu Hu, Shaohua Du

и другие.

Sensors, Год журнала: 2025, Номер 25(10), С. 3111 - 3111

Опубликована: Май 14, 2025

The evidential reasoning (ER) rule has been widely adopted in engineering fault diagnosis, yet its conventional implementations inherently neglect evidence correlations due to the foundational independence assumption required for Bayesian inference. This limitation becomes particularly critical practical scenarios where heterogeneous collected from diverse sensor types exhibits significant correlations. Existing correlation processing methods fail comprehensively address both linear and nonlinear inherent such systems. To resolve these theoretical constraints, this study develops MICER-a novel ER framework that incorporates analysis based on maximum mutual information coefficient (MIC). proposed methodology advances theory by systematically integrating interdependencies, thereby expanding boundaries of rules their applicability real-world diagnosis. Flange ring loosening diagnosis flywheel system cases are experimentally verified effectiveness method is demonstrated.

Язык: Английский

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