Application and comparison of an ANN-based feature selection method and the genetic algorithm in gearbox fault diagnosis

References

Page 1

	Year	Citations
Time-frequency distributions-a review Leon Cohen Proceedings of the IEEE Spectral TheoryTime-frequency AnalysisEngineeringFundamental IdeasSpectral Analysis	1989	3.5K
Gear fault detection using artificial neural networks and support vector machines with genetic algorithms B. Samanta Mechanical Systems and Signal Processing Fault DiagnosisCondition MonitoringEngineeringGenetic AlgorithmsArtificial Neural Networks	2003	504
Intelligent condition monitoring of a gearbox using artificial neural network Javad Rafiee, Farid Arvani, Abbas Harifi, Mechanical Systems and Signal Processing Fault DiagnosisCondition MonitoringEngineeringIntelligent DiagnosticsIndustrial Engineering	2006	321
EARLY DETECTION OF GEAR TOOTH CRACKING USING THE RESONANCE DEMODULATION TECHNIQUE Wenyi Wang Mechanical Systems and Signal Processing EngineeringMechanical EngineeringStructural Health MonitoringGear Tooth CrackingEarly Detection	2001	274
Evolving an artificial neural network classifier for condition monitoring of rotating mechanical systems Abhinav Saxena, Saad Ashraf Applied Soft Computing Fault DiagnosisCondition MonitoringEngineeringMachine LearningIntelligent Diagnostics	2006	212
Early detection of gear failure by vibration analysis i. calculation of the time-frequency distribution W.J. Wang, P.D. McFadden Mechanical Systems and Signal Processing Condition MonitoringReliability EngineeringEngineeringTime-frequency DistributionMeasurement	1993	210
Interpolation techniques for time domain averaging of gear vibration P.D. McFadden Mechanical Systems and Signal Processing Modal AnalysisInterpolation TechniquesEngineeringMechanical EngineeringMechatronics	1989	114
Fault gear identification using vibration signal with discrete wavelet transform technique and fuzzy–logic inference Jian-Da Wu, Chuang-Chin Hsu Expert Systems with Applications Fault DiagnosisCondition MonitoringFuzzy LogicEngineeringFault Gear Identification	2008	74
Input variable selection for neural networks: application to predicting the U.S. business cycle Joachim Utans, John Moody, Steven Rehfuss, Forecasting MethodologyEngineeringMachine LearningBusiness IntelligenceBusiness Analytics	2002	61
Fault detection and location in gears by the smoothed instantaneous power spectrum distribution İsa Yeşilyurt NDT & E International Fault DiagnosisCondition MonitoringReliability EngineeringElectrical EngineeringEngineering	2003	40

Page 1