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A Method for Detecting Surface Defects in Railhead by Magnetic Flux Leakage

Yinliang Jia, Shicheng Zhang, Ping Wang, Kailun Ji

2021Applied Sciences20 citationsDOIOpen Access PDF

Abstract

With the rapid development of the world’s railways, rail is vital to ensure the safety of rail transit. This article focuses on the magnetic flux leakage (MFL) non-destructive detection technology of the surface defects in railhead. A Multi-sensors method is proposed. The main sensor and four auxiliary sensors are arranged in the detection direction. Firstly, the root mean square (RMS) of the x-component of the main sensor signal is calculated. In the data more significant than the threshold, the defects are determined by the relative values of the sensors signal. The optimal distances among these sensors are calculated to the size of a defect and the lift-off. From the finite element simulation and physical experiments, it is shown that this method can effectively suppress vibration interference and improve the detection accuracy of defects.

Topics & Concepts

Magnetic flux leakageAcousticsLeakage (economics)Lift (data mining)VibrationFinite element methodRoot mean squareSIGNAL (programming language)Structural engineeringMaterials scienceEngineeringMechanical engineeringElectrical engineeringComputer sciencePhysicsMagnetMacroeconomicsEconomicsProgramming languageData miningNon-Destructive Testing TechniquesGeophysical Methods and ApplicationsWelding Techniques and Residual Stresses
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