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RISVibration Characteristics Diagnosis of Roller Bearing Using the New Empirical Model
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Roller bearings are essential parts extensively used in many industries such as automobile, sugar factories, cement industries, weaving mills, chemical industries, and other process industries. The catastrophic failure of ...
Dynamic Response Analysis of Gearbox to Improve Fault Detection Using Empirical Mode Decomposition and Artificial Neural Network Techniques
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Since the last decade, gearbox systems have been requiring increasing power, and consequently, the complexity of systems has escalated. Inevitably, this complexity has resulted in the need for the troubleshooting of gearbox ...
A Novel Method to Classify Rolling Element Bearing Faults Using K-Nearest Neighbor Machine Learning Algorithm
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: A novel method is proposed in this work for the classification of fault in the ball bearings. Applications of K-nearest neighbor (KNN) techniques are increasing, which redefines the state-of-the-art technology for defect ...
Identification and Fault Diagnosis of Rolling Element Bearings Using Dimension Theory and Machine Learning Techniques
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The study presents the classification of bearing fault types occurring in rotating machines using machine learning techniques. Recent condition monitoring demands all-inclusive but precise fault diagnosis for industrial ...