Article

A Novel Bearing Fault Diagnosis Method Based on Singular Spectrum Decomposition and a Multi‐Strategy Enhanced Cuckoo Search–Optimized Extreme Learning Machine

2025-10-16

Abstract excerpt

Large background noise, difficulty in feature extraction, and low parameter‐optimization efficiency of diagnosis models are key challenges in rolling bearing fault diagnosis. To address these issues, this paper proposes a fault diagnosis framework that combines Singular Spectrum Decomposition (SSD) with a Multi‐Strategy Enhanced Cuckoo Search (MS-CS) algorithm to optimize an Extreme Learning Machine (ELM). First,...

Topics

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

Identifiers and source

Literature Corpus work: 48b1633b-6f32-5e41-bb50-c5cdcd3821b2
DOI: 10.20944/preprints202510.1308.v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

A Novel Bearing Fault Diagnosis Method Based on Singular Spectrum Decomposition and a Multi‐Strategy Enhanced Cuckoo Search–Optimized Extreme Learning MachineDOI 10.20944/preprints202510.1308.v1Read

Enhanced Mechanical Fault Diagnosis of High-Voltage Circuit Breakers Using a Multi-Strategy Improved Dung Beetle Algorithm and Support Vector MachineSemantic proximity Read

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

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

Wavelet machine learning model for condition monitoring of ball bearingsSemantic proximity Read

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

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

Spectral-Based Fault Diagnosis Methodology for Industrial Shot Blast Machinery Leveraging XGBoost and Feature ImportanceSemantic proximity Read

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

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

A Novel Hybrid Approach to the Diagnosis of Simultaneous Imbalance and Shaft-Bow in a Jeffcott Rotor-Bearing System.Semantic proximity Read

Crested Porcupine Optimized Long Short-Term Memory based Multi Fault Diagnosis of Wind TurbinesSemantic proximity Read

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