Detection Of Steel Ball Surface Defect Based On Motion Vision

Bearing is basic part in mechanical equipment, which is used widely. To a large extent, bearing's precision, motility and service life depend on the quality of steel ball in bearing. Research is very important task for detection surface defect of steel ball. In order to inspect and classify effectively surface defects of steel ball, an automatic measurement system was researched with dynamic vision technology. The main content of this thesis includes the following parts:The whole design scheme and the main module of detection mechanism were described in detail. The thesis also integrally analyzed the control circuit design of automatic detection of steel ball's surface defect. The motion vision experimental platform was developed for steel ball surface defect detection.Aiming at the distortion of steel ball vision experimental system, the improved traditional camera calibration method was designed based on multi distortion model. First of all, the characteristic of steel ball image sequence distortion was synthetically analyzed, and then the conclusion was got that there were two distortions: the camera installation distortion and the geometric distortion. Then the correctional matrix was established according to various kinds of distortions. The thesis calculated the transformation of coordinate system and the inner and outer parameters of the camera with correction. Finally the mathematic model of system calibration was derived.The problems of noise-removing and restoration of steel ball image sequence were studied.On analyzing the function characteristic of noise-fielded and rule of steel ball motion obscuration, the thesis put forward to the steel ball degradation model and designed the wiener filtering method based on parameter estimation to restore image. The experimental results indicated that restoration algorithm has obvious advantage for articulation in this paper. The thesis also analyzed their optical causes and investigated two possible solutions aiming at the reflection of steel ball and its normal line halo phenomenon .Combined lighting scheme were designed to weaken the reflection of steel ball and the normal line halo.Aiming at tracing image sequence of several motion steel balls in scene, the thesis designed the immunity self-adaptive tracing algorithm based on Kalman. First of all, the initial original template was determined by steel ball gray centroid. Then using Kalman arithmetic, the thesis obtained the estimation of every steel ball motion parameter and the position information. The matching template was numbered. Finally, the problem of tracing point drift was solved based on the weighted self-adaptive template updating arithmetic. The thesis put forward to the dynamic contour model based on the ant colony algorithm to realize the strategy of automatic extraction. On the first step, based on the expanded joint edge of the circular arc neighborhood, we designed the improved Canny arithmetic to obtain the initial profile of the steel ball Snake model.Second, we designed the ant colony algorithm which was based on time model to obtain the best solution of Greedy evolvement and gain the best profile.The thesis studied the judgment whether the steel ball has defect or not and the defect classification.First of all, the surface images texture feature of steel ball was analyzed. Based on the research of energy feature, entropy feature, contrast feature, partially-homogeneous feature and relativity parameter, the synthesis entropy parameter was designed to judge. Then the fast algorithm for Otsu was designed to get the defect area of steel ball surface. The thesis also proposed that by the shape factor F combined with three moment invariants the four-dimensional eigenvector was constructed to sign the feature of steel ball surface curve area. Finally, the thesis put forward the AdaBoost classifier algorithm based on the verification update strategy to classify the defect type of steel ball surface.