Fault detection and diagnosis of linear bearing in auto core adhesion mounting machines based on condition monitoring
Prathan Chommuangpuck, Thanasak Wanglomklang, Jiraphon Srisertpol
Abstract
This study aims to increase machine reliability thereby preventing product defects from adhesive dispense and slider attachment by a fault detection and diagnostic technique. The experiment was set up to investigate the vibration signal and motor current. Six fault conditions of a linear bearing were set up. The approaches, including spectrum analysis, crest factor, and analysis of variance, are used for data analysis. It was found that the spectrum analysis was suitable for classifying the frequency domains and the statistics tool was successful in measuring the current. Fault detection and diagnosis results can forecast the status of the linear bearings.
Topics & Concepts
Fault detection and isolationCondition monitoringBearing (navigation)Core (optical fiber)Fault (geology)EngineeringComputer scienceArtificial intelligenceGeologySeismologyElectrical engineeringTelecommunicationsActuatorGear and Bearing Dynamics AnalysisMachine Fault Diagnosis TechniquesControl Systems in Engineering