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In order to meet the demand of high position accuracy, many methods have been developed for measuring the thread profile features of ball screws. However, most of these efforts are limited to measuring a small number of ball screw features and therefore less efficient. In this study, an automatic, non-contact measuring system for the thread profile...
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... spindle motor and a feed motor were installed inside the left end of the bed (as shown in Fig. 2). The spindle motor is used to drive the tested ball screw and the feed motor is used to drive the feed ball screw. The air floating platform was connected with the nut of the feed ball screw. The feed motor drives the feed ball screw and the nut and the platform can move along the x 0 -axis with the rotated feed ball ...
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... At present, many relevant scholars at home and abroad have conducted research on this subject and have already formed a relatively complete thread detection system, as in [3]- [8], which can be described as follows: First, the original image of the thread profile by CCD or other optical camera is captured, then the features of thread profile based on image processing techniques such as filtering, boundary extraction and curve fitting are extracted, and finally the parameters are measured from the acquired features such as the thread profile, which are considered as the result of detection. Min and Zhao respectively designed a non-contact thread parameter measurement system based on machine vision to support efficient and accurate measurement of the thread contact angle, as in [9], [10]; Rao et al. summarized the image processing technology and computer vision algorithms currently used for external thread detection, as in [11]; Senthilnathan used a diffuse reflection light source to obtain a thread profile projection, and proposed a profile processing algorithm to estimate the thread parameters, as in [12]; Chen et al. integrated the photoelastic effect and an image processing algorithm to measure the contact angle of the ball screw, as in [13]; Li et al. proposed a Res Unet-based thread edge recognition method that eliminates the need for thread area calibration and identifies the thread edge in a complex environment, as in [14]; Chen took the possible thread shape distortion during CCD shooting into account, and gave a corresponding compensation algorithm for the image distortion on the optical angle, as in [15]. However, the above solutions are only applied to the detection of ordinary threads with a linear profile, while the Journal homepage: https://content.sciendo.com ...
... According to (9) and (10), must be optimized and it is assumed that = . From (10) it is evident that the search for the optimal value of is a typical One-Dimensional Optimization problem, as in [19], which can be solved by the Linear Search [20]. The Linear Search method can be divided into two stages: First, the search interval containing the optimal solution of the problem is determined. ...
The transmission accuracy of the ball screw depends on the processing quality of the thread profile. Traditional detection method of thread profile is complicated and inefficient. When shooting the thread profile of the ball screw in the normal section, the camera axis must be tilted to the lead angle, and adjustment errors are easily introduced from both the front view and the top view. When shooting in the axial section, the spiral lines block each other, so the actual thread profile cannot be captured for detection. In order to solve the above problems, a thread profile detection method is proposed: the theoretical equation of the ball screw thread profile in the axial section is derived based on the theoretical thread profile in the normal section, and the theoretical equation of the thread profile projection curve in the axial section is solved based on helix analysis, and the differential equation between them is obtained; then, the theoretical correction value of the thread profile projection curve is obtained by Linear Search to find the boundary value; the actual thread profile in both axial section and normal section is finally obtained with the theoretical correction value, which can support accurate measurement and detection of the key parameters of the thread profile. Experiments show that the proposed method can effectively improve the accuracy of the ball screw thread profile detection.
... According to the design principle, the center position and radius are indispensable. The least square method is a standard approach to the approximate solution of overdetermined systems; this means that the overall solution minimizes the sum of the squares of the errors made in the results of every single equation [28]. The general formula of the circular equation on the plane can be represented as: According to the least square theory, the objective function can be written as: ...
As a linear actuator, accurate dimension measurement is crucial to the transmission reliability and interchangeability of ball screws. However, most of the current approaches are ineligible for rapid ball screw in-situ inspections due to the installation condition requirement of the production line. In this research, a machine vision method is presented to achieve highly accurate measurements of crucial parameters (the center distance and raceway arcs) in ball screws using a curvature edge detection algorithm. To capture images of the immediate area surrounding the area of interest, a telecentric lens is used. Thereafter, the curvature-based edge detection algorithm is employed to extract the contours. The measurement location on the object is automatically chosen by using a shape-matching algorithm. Additionally, random noise is suppressed by using the multiple-measurement averaging technique. Based on the results of the experiments, it is concluded that the center distance and the two raceway arcs computed absolute errors are 0.0019 mm, 0.0055 mm, and 0.0059 mm, respectively.
The bending deflection of screw rod is an essential factor which affects the transmission accuracy and service life of the screw rod. However, existing researches haven’t proposed an effective and general method for measuring screw rod bending deflection. In this paper, a novel measurement method is proposed by using a laser edge detection sensor. The screw rod profile is approximated as its outer or inner cylinder by an algorithm based on cubic spline interpolation, and a rigorous mathematical model among eccentricity, initial phase angle and cross-section position is built. Then, extensive numerical simulations are conducted to analyze theoretical errors of proposed method, which provides guiding references for practices. Finally, the feasibility and reliability of proposed method are proved by comparing with measuring projector and repeatability and reproducibility analysis. In conclusion, the proposed method can realize continuous non-contact measurement of screw rod bending deflection and has strong practicability and generality.
Ball screws are crucial for improving the reliability and interchangeability of transmission mechanical systems; however, existing contact measurement methods that utilise stylus contact are not efficient, which precludes their use for rapid in-situ geometry evaluation. This paper presents a vision-based two-stage method for rapid measurement of key parameters (raceway arc radii and centre distance) of ball screws. The edge contour information is extracted from the acquired image using the dual-tree complex wavelet transform and non-maximal suppression. In the matching stage, a shape-matching algorithm is used for detecting approximate geometrical centres of raceway arcs. The refinement stage, on the other hand, is implemented for acquiring precise dimensional results. Furthermore, the method of averaging multiple measurements is performed to suppress random noise. A comparative experiment is presented to validate the robustness of the proposed method. Based on experimental results, the calculated mean absolute errors in the measurement of the two raceway arc radii and the centre distance are found to be 0.0082 mm, 0.0079 mm and 0.0055 mm, respectively. This study therefore paves the way for key parameter measurement without removing ball screws.
A new method using the screw thread edge image characteristics was proposed. A new template named improved Sobel templates, which had 67.5°and 112.5°direction templates, was used to obtain the edge of image after the image pretreatment. Different weighted values of the inner pixels in the template were proposed depending on the different distance from every pixel in the template to the center point. Comparing the edge of angle threads with different tooth type in edge extraction processing using the improve Sobel and the traditional Sobel operators, the improved Sobel operator had advantages of clearer edges and better continuity.
In order to achieve optimal control of the screw rotor process, a novel measurement method using laser triangulation under multi-factor constraints was introduced to achieve online measurement of the screw rotor profile. This method involved the integration of a 4-axis motion system, which is used to adjust the laser probe, with a laser displacement sensor (LDS), which is used to measure the screw rotor profile. Firstly, the effect of laser beam positioning on measurement accuracy was analyzed experimentally in conjunction with an improved LDS error compensation model. Then, according to the characteristics of rotor profiles, a laser-measurement trajectory planning algorithm for the rotor profile under multi-factor constraints was developed. Finally, the comparison study between the traditional contact measurement (P65) and the proposed measurement demonstrates that the proposed method has not only kept the advantages of traditional contact measurement, but also shown good performances and high measuring precision.
