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Wind Turbine Gearbox Early Fault Detection Using Mel‐Frequency Cepstral Coefficients of Vibration Data

https://doi.org/10.1155/2024/7733730
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.ifacol.2022.11.276openalex-snapshot
Condition Monitoring in a Wind Turbine Planetary Gearbox Using Sensor Fusion and Convolutional Neural Network
inferredcites →https://doi.org/10.1016/j.isatra.2022.10.008openalex-snapshot
A deep capsule neural network with data augmentation generative adversarial networks for single and simultaneous fault diagnosis of wind turbine gearbox
inferredcites →https://doi.org/10.1016/j.measurement.2021.109094openalex-snapshot
Fault detection of wind turbine based on SCADA data analysis using CNN and LSTM with attention mechanism
inferredcites →https://doi.org/10.1016/j.oceaneng.2022.112920openalex-snapshot
A novel order spectrum-based Vold-Kalman filter bandwidth selection scheme for fault diagnosis of gearbox in offshore wind turbines
inferredcites →https://doi.org/10.1016/j.renene.2021.12.054openalex-snapshot
Improved adversarial learning for fault feature generation of wind turbine gearbox
inferredcites →https://doi.org/10.1016/j.renene.2022.05.085openalex-snapshot
A novel wind turbine fault diagnosis method based on compressed sensing and DTL-CNN
inferredcites →https://doi.org/10.1016/j.renene.2022.09.102openalex-snapshot
Condition monitoring of wind turbines based on spatial-temporal feature aggregation networks
inferredcites →https://doi.org/10.1016/j.wear.2023.204697openalex-snapshot
A novel vibration-based prognostic scheme for gear health management in surface wear progression of the intelligent manufacturing system
inferredcites →https://doi.org/10.1016/j.ymssp.2019.02.051openalex-snapshot
Vibration based condition monitoring and fault diagnosis of wind turbine planetary gearbox: A review
inferredcites →https://doi.org/10.1016/j.ymssp.2019.03.036openalex-snapshot
Time-Frequency demodulation analysis via Vold-Kalman filter for wind turbine planetary gearbox fault diagnosis under nonstationary speeds
inferredcites →https://doi.org/10.1016/j.ymssp.2022.109848openalex-snapshot
Fault diagnosis of rotating machinery based on graph weighted reinforcement networks under small samples and strong noise
inferredcites →https://doi.org/10.1049/icp.2021.2262openalex-snapshot
Condition Monitoring of Wind Turbine Converter based on a Two-stage Data Augmentation Scheme
inferredcites →https://doi.org/10.1088/1742-6596/2265/3/032067openalex-snapshot
Wind turbine gearbox fault prognosis using high-frequency SCADA data
inferredcites →https://doi.org/10.1109/appeec.2014.7066016openalex-snapshot
Investigation on vibration based CM technique for wind turbine gearbox
inferredcites →https://doi.org/10.1109/cca.2014.6981517openalex-snapshot
Frequency based wind turbine gearbox fault detection applied to a 750 kW wind turbine
inferredcites →https://doi.org/10.1109/eeeic.2019.8783233openalex-snapshot
Wind Turbine Fault Diagnosis with Generative-Temporal Convolutional Neural Network
inferredcites →https://doi.org/10.1109/iccss52145.2020.9336899openalex-snapshot
A GAN Based Fault Detection of Wind Turbines Gearbox
inferredcites →https://doi.org/10.1109/icebe.2018.00045openalex-snapshot
Fault Diagnosis of Wind Turbine Gearbox Based on Vibration Data
inferredcites →https://doi.org/10.1109/icicta.2009.375openalex-snapshot
Wind Turbine Gearbox Fault Diagnosis Using Adaptive Morlet Wavelet Spectrum
inferredcites →https://doi.org/10.1109/jsen.2022.3178137openalex-snapshot
Generative Adversarial Networks for Gearbox of Wind Turbine With Unbalanced Data Sets in Fault Diagnosis
inferredcites →https://doi.org/10.1109/jsen.2022.3213551openalex-snapshot
TempGNN: A Temperature-Based Graph Neural Network Model for System-Level Monitoring of Wind Turbines With SCADA Data
inferredcites →https://doi.org/10.1109/phm-chongqing.2018.00210openalex-snapshot
Fault Diagnosis of Wind Turbine Gearbox Based on Dual-tree Complex Wavelet and Information Entropy
inferredcites →https://doi.org/10.1109/tie.2017.2767520openalex-snapshot
Multiscale Filtering Reconstruction for Wind Turbine Gearbox Fault Diagnosis Under Varying-Speed and Noisy Conditions
inferredcites →https://doi.org/10.1109/tim.2017.2698738openalex-snapshot
Stacked Multilevel-Denoising Autoencoders: A New Representation Learning Approach for Wind Turbine Gearbox Fault Diagnosis
inferredcites →https://doi.org/10.1109/tim.2020.3025396openalex-snapshot
Fault Diagnosis of Bearing in Wind Turbine Gearbox Under Actual Operating Conditions Driven by Limited Data With Noise Labels
inferredcites →https://doi.org/10.1109/tmech.2017.2759301openalex-snapshot
Wind Turbine Fault Detection Using a Denoising Autoencoder With Temporal Information
inferredcites →https://doi.org/10.2307/843164openalex-snapshot
The Mel Scale
inferredcites →https://doi.org/10.23967/latam.2023.017openalex-snapshot
Wind Turbine Gearbox Condition Monitoring Using Vibration Data and Mel-Frequency Cepstral Coefficients
inferredcites →https://doi.org/10.2991/ijcis.d.201105.001openalex-snapshot
Dictionary Learning Approach to Monitoring of Wind Turbine Drivetrain Bearings
inferredcites →https://doi.org/10.3390/en10111904openalex-snapshot
Performance and Reliability of Wind Turbines: A Review
inferredcites →https://doi.org/10.3390/en14061728openalex-snapshot
Wind Turbine Fault Detection Using Highly Imbalanced Real SCADA Data
inferredcites →https://doi.org/10.5281/zenodo.591533openalex-snapshot
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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.5356458openalex-extracted
Neural Circuit Policy-Driven Spiking Neural Network: A Clustered and Lightweight Method for Wind Farm Condition Monitoring
inferred← citeshttps://doi.org/10.1007/978-3-031-96106-9_101openalex-snapshot
Pattern Recognition and Damage Detection in Wind Turbine Monitoring Using Cepstral Coefficients
inferred← citeshttps://doi.org/10.1007/978-3-031-96106-9_98openalex-snapshot
Wind Turbine Gearbox Fault Detection Under Distribution Shifts
inferred← citeshttps://doi.org/10.1007/s10010-025-00815-0openalex-snapshot
Robustness and transferability of an autoencoder based anomaly detection approach to detect gear damage
inferred← citeshttps://doi.org/10.1016/j.renene.2026.126182openalex-snapshot
Cepstral coefficients for real-time recognition of known and unknown wind turbine damage and power-generation states
inferred← citeshttps://doi.org/10.1016/j.rineng.2024.103791openalex-snapshot
Optimal feature selection for a weighted k-nearest neighbors for compound fault classification in wind turbine gearbox
inferred← citeshttps://doi.org/10.1049/tje2.70098openalex-snapshot
Fault Diagnosis and Dynamic Threshold Early Warning for Wind Turbines Using DBSCAN‐MAD Anomaly Cleaning and GA‐Optimized LightGBM
inferred← citeshttps://doi.org/10.1080/10589759.2025.2598291openalex-snapshot
LSC-VAE: a lightweight separable convolutional variational autoencoder for unsupervised and generalisable gearbox fault detection
inferred← citeshttps://doi.org/10.1109/cscwd68734.2026.11582751openalex-snapshot
Fault Detection Method for Wind Turbine Bearings Based on FCWT-GMRF-CNN
inferred← citeshttps://doi.org/10.1109/jsas.2025.3638975openalex-snapshot
Acoustic-Based Fault Detection for Robotic Arms
inferred← citeshttps://doi.org/10.1109/jsen.2025.3607962openalex-snapshot
Multidomain Health Indicator Construction for Wind Turbine Gearboxes Situational Awareness Under Generation–Grid–Load–Storage Integration
inferred← citeshttps://doi.org/10.1109/tii.2026.3673932openalex-snapshot
An Efficient Wind Farm Condition Monitoring Method Balancing Complexity and Performance
inferred← citeshttps://doi.org/10.1155/stc/4023580openalex-snapshot
Enhancing Wind Turbine Diagnostics With SCADA‐Vibration Fusion, Contrastive Learning, and Linear Predictive Coefficients
inferred← citeshttps://doi.org/10.1155/stc/6359435openalex-snapshot
Decoupling Machine and Operational Variances: A Spectral Attention Framework for Robust Few‐Shot Cross‐Machine Fault Diagnosis
inferred← citeshttps://doi.org/10.1155/stc/8787490openalex-snapshot
Hybrid Deep Learning for Gearbox Fault Diagnosis Using Raw Vibration Time‐Series Data
inferred← citeshttps://doi.org/10.3390/electronics14193948openalex-snapshot
Accurate Fault Classification in Wind Turbines Based on Reduced Feature Learning and RVFLN
inferred← citeshttps://doi.org/10.3390/pr13041239openalex-snapshot
Bearing Fault Diagnosis Based on Multiscale Lightweight Convolutional Neural Network
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