Research and Design of Intelligent Riveting System for Railway Freight Cars
In order to ensure the reliability of freight car operation,riveting technology is adopted on the bogie.There is no obvious difference in the appearance of short-tail rivets before and after riveting.Operators in the installation also need to assemble other parts,which often causes riveting not in place,riveting omission and other operational problems,bringing serious safety hazards in practical application.In response to the problems of rivet omission and incomplete riveting during the assembly of the brake beam on the bogie,this article proposes a method for detecting the quality and position of the riveting.Flow sensor and pressure sensor signals are collected during the riveting process to indirectly obtain the riveting force and riveting displacement,and the relation curve of riveting force and displacement is drawed.The riveting curve is analyzed using the empirical threshold method to judge the quality of the riveting effect.At the same time,the background image of each riveted position is collected and the pixel point eigenvalues are extracted,and the eigenvalues are dimensionally reduced using principal component analysis(PCA).Finally,convolutional neural network(CNN)is used for training and recognition.The experimental results show that this method can correctly determine the riveting results according to the qualified curve,and accurately identify the riveting position,which can provide effective technical support for the driving safety of railway freight cars.
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维普
