Missing Detection of The Clutch-Driven Disc Spring Assembly

Abstract

A detection system for the missing assembly of clutch-driven plate springs is established. The algorithms used in this system, such as point cloud data preprocessing, spring area positioning, and spring missing detection, are studied. Firstly, according to the characteristics of the clutch-driven plate spring point cloud, the Gaussian statistical method is used to eliminate the outliers incurred by system error and other reasons, and the two-sided filtering is performed on the clutch-driven plate spring point cloud that eliminates the outliers to eliminate the noise points with small ups and downs. Then, the theoretical division area is constructed by using the theoretical width between the clutch-driven plate springs and the theoretical width of the springs. Compared with actually recorded positions, the theoretical area is expanded so that the real spring point cloud data are in the corresponding positioning area; finally, the spring in the region is identified by using the characteristics of an inconsistent number of point clouds in different assembly conditions, so as to detect the missing assembly of the clutch-driven plate spring. The experimental results show that the detection accuracy of the clutch-driven plate spring assembly is as high as 100%. It can basically meet the detection requirements for the missing assembly of clutch-driven plate springs.