ArticleSensors (Basel, Switzerland)2022
Gearbox Fault Diagnosis Based on Improved Variational Mode Extraction.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Strong Interference Elimination in Seismic Data Using Multivariate Variational Mode Extraction.Sensors (Basel, Switzerland) · 2024Article
- Seismic Signal Analysis Based on Variational Mode Decomposition and Hilbert Transform for Ground Intrusion Activity Classification.Sensors (Basel, Switzerland) · 2023Article
- Gearbox Fault Identification Model Using an Adaptive Noise Canceling Technique, Heterogeneous Feature Extraction, and Distance Ratio Principal Component Analysis.Sensors (Basel, Switzerland) · 2022Article
- Rolling Bearing Fault Diagnosis Based on Successive Variational Mode Decomposition and the EP Index.Sensors (Basel, Switzerland) · 2022Article
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Authors and funding
5 authors.
Funding
Abstract
Gearboxes are widely used in drive systems of rotating machinery. The health status of gearboxes considerably influences the normal and reliable operation of rotating machinery. When a gearbox experiences tooth failure, a vibration signal with impulse features is excited. However, these impulse features tend to be relatively weak and difficult to extract. To solve this problem, a novel approach for gearbox fault feature extraction and fault diagnosis based on improved variational mode extraction (VME) is proposed. Since the initial value of the desired mode center frequency and the value of the penalty parameter in VME must be assigned, a short-time Fourier transform (STFT) was performed, and a new index, the standard deviation of differential values of envelope maxima positions (SDE), is proposed. The feasibility and effectiveness of the proposed approach was verified by a simulation signal and two datasets associated with a gearbox test bench. The results demonstrate that the VME-based approach outperforms the variational mode decomposition (VMD) approach.
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Registered trials
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