Article

Intelligent Diagnosis Model for Rolling Bearing Faults Based on Multi-Modal Data Fusion

2026-05-18

Abstract excerpt

<title>Abstract</title> <p>The rolling bearings of high-speed trains are in long-term service under high-speed, variable-load and intense noise conditions, and the collected vibration signals exhibit prominent non-stationarity and non-linearity. This makes it difficult for fault diagnosis methods based on a single feature or single modality to stably characterize fault information. To address the above issues, th...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 9de8f1d0-b108-5028-ba5e-0fd26dcd4583
DOI: 10.21203/rs.3.rs-9473421/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Intelligent Diagnosis Model for Rolling Bearing Faults Based on Multi-Modal Data FusionDOI 10.21203/rs.3.rs-9473421/v1Read

MSE-NERSPPNet: A Multi-Channel Framework for Bearing Fault Diagnosis in the Presence of Imbalanced SamplesSemantic proximity Read

Research on Mechanical Fault Diagnosis under Complex Working Conditions Based on Improved YOLOv8Semantic proximity Read

An Intelligent diagnosis method for rolling bearings based on Ghost module and adaptive weighting moduleSemantic proximity Read

ETNeXt: Integrated feature engineering and classification framework for BLDC motor fault detectionSemantic proximity Read

Robust-GSR driven lightweight CNN framework for intelligent fault diagnosis under variable-speed conditionsSemantic proximity Read

An Energy-Efficient Fault Diagnosis Method for Subsea Main Shaft BearingsSemantic proximity Read

A novel meta-learning method based on relation network for train bearing fault diagnosisSemantic proximity Read

Rolling bearing fault detection of rotary machine using a novel adaptive sparse representationSemantic proximity Read

Research on Few-Shot Fault Diagnosis and Feature Extraction Mechanism Based on ADPCW-ELCNNSemantic proximity Read

Adaptive Graph Construction and Feature-Enhanced Graph Neural Network for Few-Shot Bearing Fault Diagnosis under Variable ConditionsSemantic proximity Read

A Functional Deep Learning Framework for Rotary Machines Fault DetectionSemantic proximity Read

Wind Turbine Gearbox Fault Diagnosis Based on PNCC-STFT Voiceprint Feature Extraction and GDC- ResNetSemantic proximity Read