Research On Automatic Detection Method For Measuring Blocks And Rods

Measuring blocks and rods,as common measuring and testing tools,have the advantages of simple structure,convenient use,and accurate measurement values,and are widely used in scientific research and industrial production.Measuring blocks and rods are physical standards for the transmission of measurement values,so regular testing is necessary to ensure the reliability of measurement values.Due to the significant impact of the pose accuracy of gauge blocks and rods on measurement accuracy,and the manual correction of pose depends on the experience of calibration personnel,with significant subjective differences,enterprises urgently need a practical and feasible method to improve the accuracy and efficiency of gauge block and rod measurement.In response to the above issues,this article conducts research on the auxiliary automatic detection method for measuring blocks and rods.The main research content of this article is as follows:Firstly,this article provides a detailed analysis of the impact of pose errors on the measurement accuracy of gauge blocks and rods.Based on the actual task requirements,the existing technical difficulties are analyzed,and an overall solution is provided.The overall design of the gauge block and rod assisted automatic detection system is completed.Secondly,the imaging model of the camera is analyzed in detail,and the conversion relationship between the four coordinate systems is studied.The pixel coordinates of the image coordinate system are linked to the spatial coordinates of the world coordinate system,and the main parameters of the camera are determined based on the camera distortion situation.According to the overall plan,a binocular camera imaging model is constructed,and the calibration of the binocular camera is completed using the Zhang Zhengyou calibration method.The internal and external parameters of the camera are solved,and the calibration accuracy is verified using the re projection error.In addition,research is conducted on the identification methods for measuring blocks and rods.Based on actual needs,the collected images are preprocessed and template matching methods based on SURF are analyzed.In response to the problem of high mismatch rate in traditional SURF algorithms,an optimization method based on feature point matching geometric relationships is proposed.At the same time,the RANSAC algorithm improved based on disparity gradient is used to further eliminate mismatch points and improve matching accuracy.Simulating different scenarios and using matching accuracy as the evaluation criterion,the effectiveness of the optimization algorithm is verified through experiments.Then,after successfully identifying the gauge blocks and rods,in order to calculate accurate pose information,an improvement is made to address the issue of poor performance of the traditional Census transform stereo matching algorithm.In the cost calculation stage,a judgment before modification approach is adopted,and the cross domain aggregation method was introduced into the cost aggregation calculation.The experiment shows that the improved algorithm has better matching performance.A feature matching based pose calculation method is proposed for the gauge block.On the one hand,the centroid of the gauge block in the target image is obtained by affine transformation,on the other hand,the vertical slope of the gauge block is calculated by using the feature matching points and the centroid,and the spatial vector of the vertical line is obtained by stereo matching and 3D reconstruction,and then the spatial pose information of the gauge block is obtained.In addition,edge fitting is performed on the identified measuring rod,and the disparity value obtained by the stereo matching algorithm is used to reconstruct the edge points on the surface of the measuring rod in 3D,in order to fit a spatial circle.The pose information of the measuring rod is calculated based on the center coordinates and normal vectors of the spatial circle,and the pose calculation methods of the measuring block and the measuring rod are evaluated and analyzed.Finally,establish a system platform and conduct experimental verification.According to the overall plan design,the corresponding hardware selection is completed,and the hardware platform of the system is built.Based on the Visual Studio development environment,the system software is designed and developed,mainly including image processing module,communication module,measurement and detection module,and data management module.Use the experimental platform to complete robot hand eye calibration,and use the error evaluation function to evaluate and analyze the calibration results.Design experiments for verification,use the method proposed in this article to calculate the spatial pose of the gauge block and gauge rod,correct the target pose through a robot,control the detection instrument for measurement,and compare the measurement data with standard data.The results show that the proposed automatic detection method for gauge blocks and gauge rods is feasible.