An interpretable fault diagnosis method for aeroengine bearings based on belief rule based with a dynamic power set

Nature·Dec 28

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Researchers are exploring various methods for fault diagnosis and prediction in aircraft engines and related components, such as bearings and gearboxes. Different approaches are being investigated, including the use of belief rule bases, deep learning models, and hybrid sampling techniques. The goal of these efforts appears to be the development of effective and interpretable tools for predicting and managing engine health and remaining service life.

Full coverage

A bearing fault diagnosis method for complex system based on improved extended belief rule base

Nature·Mar 24

Bearing fault diagnosis based on multi-branch enhanced GhostNet with adaptive focal loss

Nature·Apr 21

Fault diagnosis using ISMA to optimize SVM parameters for aircraft engine damage repair

Nature·Nov 26

Prediction of aero engine remaining service life using a bidirectional GRU model with self attention mechanism

Nature·Apr 19

A novel intelligent fault diagnosis method for gearbox based on multi-dimensional attention denoising convolution

Nature·Oct 21

Deep learning based approaches for intelligent industrial machinery health management and fault diagnosis in resource-constrained environments

Nature·Jan 7

Fault prediction of aircraft engine based on adaptive hybrid sampling and BiLSTM