Online measurement method for dimensions of disk parts based on machine vision.

Online measurement of disk part dimensions by the standard industrial camera features low cost, high efficiency and good universality, but the impact of projection distortion and end face chamfer on measurement is needed to overcome. Present work presents a measurement method to resolve above issues based on machine vision. To improve the measurement accuracy, lower end face of a disk part is determined as calibration plane and the upper end face is measurement plane. To reduce the impact of projection distortion and chamfer on measurement, the measurement points are reconstructed on the measurement plane by re-projection. Then, the inner and outer diameters of disk parts are measured by circle geometric fitting, and the thickness is calculated by the measurement plane position. The experimental results show that the method can online measure disk part dimensions just by a single image, and accuracy meets the requirements of universal grade disk parts.

Vision measuring technology for the position degree of a hole group.

The hole is one of the most important geometric elements in mechanical parts. The center distance of a hole group measurement method based on machine vision is proposed for solving the influence of perspective distortion and improving the applicability of vision systems. In the method, the plane equation of the measured plane is obtained by the line structured light vision technology, and the process is free from the constraints of the calibration plate. In order to eliminate the effect of projection distortion on the measurement accuracy, a local coordinate system is established on the plane of the measured hole group, the hole diameter, and the center distance of the hole group, which could be calculated by the local coordinates of the hole edge points. In the experiment, the flange is taken as the measured object, the distances between the holes on the flange are obtained by the method proposed in this paper, and the measurement results compared with the data are obtained by a coordinate measuring machine (CMM). The experimental results show that the average measurement error of center distance is 0.0739 mm, and the standard deviation is 0.0489 mm.

Aperture measurement based on a conic invariant.

With the advantages of low cost, universal applicability, and in situ detection, the conic invariant of the tested aperture diameter was obtained by ellipse geometric fitting on the aperture surface. The world coordinate system was established, and the transformation relationship between the world coordinate system and the camera coordinate system was obtained by the calibration. The improved Candy algorithm and coordinate transformation relationship could be used to project the sub-pixel coordinates of the aperture edge onto the aperture surface. Then, the ellipse geometric fitting was performed on the aperture edge curve surface to obtain the conic invariant. Finally, the conic invariant was used to measure the aperture diameter on the test bench.

Vision measuring method for the involute profile of a gear shaft.

Since the involute profile error of a gear shaft influences its transmission performance, it is desirable to accurately and quickly measure its involute profiles. With the advantages of low cost, universal applicability and in situ detection, a vision measuring method for multiple involute profiles of a gear shaft is developed only using one image in this study. The base circle radius and initial position angle of the involute are obtained by geometrically fitting the involute profile. The correctness and reliability of the method are tested by measuring the pitch deviation of the gear shaft; a specialized experiment is carried out; and the factors affecting the measurement accuracy also are analyzed.

Shaft Diameter Measurement Using Structured Light Vision.

A method for measuring shaft diameters is presented using structured light vision measurement. After calibrating a model of the structured light measurement, a virtual plane is established perpendicular to the measured shaft axis and the image of the light stripe on the shaft is projected to the virtual plane. On the virtual plane, the center of the measured shaft is determined by fitting the projected image under the geometrical constraints of the light stripe, and the shaft diameter is measured by the determined center and the projected image. Experiments evaluated the measuring accuracy of the method and the effects of some factors on the measurement are analyzed.

A flexible calibration method using the planar target with a square pattern for line structured light vision system.

A flexible calibration approach for line structured light vision system is proposed in this paper. Firstly a camera model is established by transforming the points from the 2D image plane to the world coordinate frame, and the intrinsic parameters of camera can be obtained accurately. Then a novel calibration method for structured light projector is presented by moving a planar target with a square pattern randomly, and the method mainly involves three steps: first, a simple linear model is proposed, by which the plane equation of the target at any orientations can be determined based on the square's geometry information; second, the pixel coordinates of the light stripe center on the target images are extracted as the control points; finally, the points are projected into the camera coordinate frame with the help of the intrinsic parameters and the plane equations of the target, and the structured light plane can be determined by fitting these three-dimensional points. The experimental data show that the method has good repeatability and accuracy.

A planar-dimensions machine vision measurement method based on lens distortion correction.

Lens distortion practically presents in a real optical imaging system causing nonuniform geometric distortion in the images and gives rise to additional errors in the vision measurement. In this paper, a planar-dimensions vision measurement method is proposed by improving camera calibration, in which the lens distortion is corrected on the pixel plane of image. The method can be divided into three steps: firstly, the feature points, only in the small central region of the image, are used to get a more accurate perspective projection model; secondly, rather than defining a uniform model, the smoothing spline function is used to describe the lens distortion in the measurement region of image, and two correction functions can be obtained by fitting two deviation surfaces; finally, a measurement method for planar dimensions is proposed, in which accurate magnification factor of imaging system can be obtained by using the correction functions. The effectiveness of the method is demonstrated by applying the proposed method to the test of measuring shaft diameter. Experimental data prove that the accurate planar-dimensions measurements can be performed using the proposed method even if images are deformed by lens distortion.

Measurement of shaft diameters by machine vision.

A machine vision method for accurately measuring the diameters of cylindrical shafts is presented. Perspective projection and the geometrical features of cylindrical shafts are modeled in order to enable accurate measurement of shaft diameters. Some of the model parameters are determined using a shaft of known diameter. The camera model itself includes radial and tangential distortions terms. Experiments were used to measure the accuracy of the proposed method and the effect of the position of the camera relative to the shaft, as well as other factors.