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Bearing Fault Detection Using Multi-Scale Fractal Dimensions Based on Morphological Covers

https://doi.org/10.1155/2012/438789
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inferred← citeshttps://doi.org/10.2139/ssrn.4518298openalex-extracted
Vision-Based Vibration Frequency Measurement by Dna-Shaped Metamaterial Array
inferred← citeshttps://doi.org/10.2139/ssrn.4600359openalex-extracted
Vision-Based Vibration Frequency Measurement by Dna-Shaped Metamaterial Array
inferred← citeshttps://doi.org/10.1007/978-3-030-01132-1_5openalex-snapshot
Multilayer-Based HMM Training to Support Bearing Fault Diagnosis
inferred← citeshttps://doi.org/10.1007/978-3-030-05645-2_7openalex-snapshot
A New Hilbert-Huang Transform Technique for Fault Detection in Rolling Element Bearings
inferred← citeshttps://doi.org/10.1007/978-3-030-48021-9_74openalex-snapshot
Bearing Failure Prediction Technique Using Exponential Moving Average Crossover Threshold with Support Vector Regression and Kernel Regression
inferred← citeshttps://doi.org/10.1007/s12206-015-1206-7openalex-snapshot
Diagnosis of compound faults of rolling bearings through adaptive maximum correlated kurtosis deconvolution
inferred← citeshttps://doi.org/10.1016/j.chaos.2015.06.018openalex-snapshot
Early fault detection of rotating machinery through chaotic vibration feature extraction of experimental data sets
inferred← citeshttps://doi.org/10.1016/j.measurement.2021.109614openalex-snapshot
Rolling bearing fault diagnosis utilizing variational mode decomposition based fractal dimension estimation method
inferred← citeshttps://doi.org/10.1108/ilt-04-2023-0113openalex-snapshot
A new fault diagnosis of rolling bearing based on phase-space reconstruction and convolutional neural network
inferred← citeshttps://doi.org/10.1109/ccdc.2015.7161960openalex-snapshot
Fault diagnosis for rolling bearing based on lifting wavelet and morphological fractal dimension
inferred← citeshttps://doi.org/10.1109/icmic.2017.8321523openalex-snapshot
Early-stage monitoring and diagnosis on faults of rolling bearings based on fractal feature extraction
inferred← citeshttps://doi.org/10.1109/itnec.2017.8284932openalex-snapshot
Early-stage monitoring on faults of rolling bearings based on fractal feature extraction
inferred← citeshttps://doi.org/10.1109/tim.2016.2598019openalex-snapshot
A Morphological Hilbert-Huang Transform Technique for Bearing Fault Detection
inferred← citeshttps://doi.org/10.1142/s0218127425501123openalex-snapshot
Chaos-Based Fault Diagnosis: Methodologies and Practices
inferred← citeshttps://doi.org/10.1155/2014/717465openalex-snapshot
Bearing Degradation Process Prediction Based on the Support Vector Machine and Markov Model
inferred← citeshttps://doi.org/10.1155/2015/167902openalex-snapshot
Rolling Element Bearing Fault Diagnosis Based on Multiscale General Fractal Features
inferred← citeshttps://doi.org/10.1155/2016/4632562openalex-snapshot
Multifeatures Fusion and Nonlinear Dimension Reduction for Intelligent Bearing Condition Monitoring
inferred← citeshttps://doi.org/10.1155/2016/5467643openalex-snapshot
Multiple-Fault Detection Methodology Based on Vibration and Current Analysis Applied to Bearings in Induction Motors and Gearboxes on the Kinematic Chain
inferred← citeshttps://doi.org/10.1177/1077546314532859openalex-snapshot
Fault detection in rolling element bearings using wavelet-based variance analysis and novelty detection
inferred← citeshttps://doi.org/10.1541/ieejsmas.139.244openalex-snapshot
Vibration Analysis of Rotating Machine based on the Distribution of Fractal Dimension
inferred← citeshttps://doi.org/10.1541/ieejsmas.140.130openalex-snapshot
State Analysis for Pump using Its Sound based on Sampling Rate Dependence of Fractal-Dimension
inferred← citeshttps://doi.org/10.21595/jve.2016.16847openalex-snapshot
A rolling bearing fault diagnosis method based on VMD – multiscale fractal dimension/energy and optimized support vector machine
inferred← citeshttps://doi.org/10.3390/e19110607openalex-snapshot
Fault Detection for Vibration Signals on Rolling Bearings Based on the Symplectic Entropy Method
inferred← citeshttps://doi.org/10.36001/ijphm.2022.v13i2.3205openalex-snapshot
Methodology for Selection of Condition Monitoring Techniques for Rotating Machinery
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