Research On Key Technology Of Dual Camera Brinell Hardness Tester

As one of the most important parameters of the material,hardness can reflect the strength characteristics of the material to a certain extent.Hardness testing is an important means to know the mechanical properties of the material.Due to its simple operation and easy implementation,it is often used to check the quality of the product An important tool.Among them,Brinell hardness is one of the earliest methods for testing hardness,which has been widely used due to its high accuracy and good stability.However,most of the domestic Brinell hardness testers obtain the hardness value by using an optical scale microscope to measure the hardness value.On the one hand,this measurement method requires a lot of work,the measurement personnel are easily fatigued,and on the other hand,it introduces artificial measurement errors.The measurement results are greatly discounted.Therefore,according to a domestic measurement grade micro-Brinell hardness tester,the original single-use microscope measurement method is changed to the machine vision measurement method,and the large-field camera is used as the guiding camera.With the small-field camera as an accurate measurement camera,the measurement scheme is obtained by the large-field camera first obtaining new pressure marks,and then the small-field camera to measure,forming a dual-camera Brinell hardness measurement system.According to the functional characteristics of the existing dual-camera Brinell hardness tester,the key technology of which is the function of the large-field camera as a guide camera is analyzed and studied.Aiming at the problem of large distortion of the introduced large-field camera after acquiring the image,through a certain analysis of the camera's imaging process,on the basis of studying the classic Zhang's calibration algorithm,it is proposed to introduce an optimized camera parameter The calibration algorithm is described in detail,and the calibration of the large-field camera is completed through the design of reasonable experiments.The feasibility of the optimization algorithm is proved by calculating the projection error.After the new supercharging mark image is obtained by the large field of view camera,the image quality is poor,the noise is more complicated,and some of the indentation is smaller,it is not easy to identify.A filtering method based on adaptive fuzzy mixed noise is proposed,which uses the method to denoise the image to improve the image quality and retain the indentation information.Then it is proposed to use the Random Hough transform algorithm based on MeanShift clustering to identify the new supercharging marks and The principle was verified,and finally the new supercharging marks were accurately identified through experiments.For the recognition of new supercharging marks with a large-field camera,small-field cameras need to be accurately measured,which involves the mutual conversion problem.Based on the analysis of the general coordinate conversion theory and the use of mathematical models to establish transformation A method of direct positioning using the affine transformation matrix,and on this basis,a corresponding error compensation mathematical model is established.The model is used to correct the positioning effect.Finally,the correctness of the model is confirmed through experiments.Finally,there are still some errors in the existing structure and measurement characteristics of the currently improved metrological grade Brinell hardness tester.After a detailed analysis of the source and type of the error,combined with this measurement system,it is given The specific errors and corresponding solutions are provided to provide guarantee for the subsequent measurement link.