| Electrohydraulic servo valve, the key component of electro-hydraulic control system, is a device in which electrical signal is converted to hydraulic signal to take control of pressure or flow. Torque motor is the front end of servo valve, where the input electrical signal is converted to torque by means of the designed structure, and the assembly accuracy of air-gaps in the torque motor has a significant influence on the performance of the servo valve. As its small dimension and high assembly accuracy, the air-gaps were usually measured by manual operation in microscope. Therefore, the measurement efficiency and accuracy both were low, which greatly affect the stability and reliability of servo valve in the use. Based on machine vision, the measurement system for air-gaps in torque motor was developed in this paper. A series of researches on measurement technique from two aspects of autofocus and image processing were carried out.Aiming at micro size of the air-gaps and high assembly accuracy of torque motor, the microscopic vision inspection equipment was built, which includes the key part microscopic vision unit, transfer unit, power supply unit, and the assembly unit. The control system of the equipment was also developed to gain control of these units. Multi thread technology was utilized to achieve two microscopic units detecting simultaneously in order to shorten the measurement period. The visual interface is designed to display the data of the air-gaps in the form of curve.The imaging principle of the optical system is described briefly, and the mathematical character of the focused image is demonstrated. The autofocusing technology of microscopic vision is studied from two angles of image sharpness evaluation function and autofocus search strategy. Firstly, in order to select the optimal sharpness evaluation function, two characteristic parameters of the function and five function performance evaluation indexes were designed. Sequence images were sampled, and a dozen of functions were listed, calculated, and compared. Variance Function and Brenner Function are chosen as sharpness function in coarse focusing stage and fine focusing stage respectively. Secondly, based on the analysis of mountain climbing method and two characteristic parameters of optimization definition function, the modified mountain climbing method was put forward. Through the experiments on the other platform which enables to measure autofocus location, Fibonacci method, mountain climbing method, and modified mountain climbing method were compared.The experimental results testified the comprehensive performance of focus accuracy and efficiency.After autofocusing, the image was sampled and processed. The static distance and the variation of the air-gap were measured, which was the basis for the adjustment of the later precise assembly of torque motor. Firstly, to deal with region of interest(ROI) in one image, an adaptive ROI recognition method based on contour edge was developed. Bilateral blurring method was used to remove noise. Get the gray threshold for image segmentation with Otsu threshold method. The morphological opening algorithm was used to separate fine burrs on the edge of the part. Then the position of air-gap edges was extracted, and the target edge will be gained through the edge filter. Linear fitting of edge on least square method was carried out to find the optimization line, and the distance between two edges of air-gaps was calculated. The precision of the proposed distance calculation algorithm is similar to the universal tool microscope, while the stability and efficiency were superior to the microscope. Based on the image match-template algorithm and serial communication of the precision power supply, measurement of the vibration of air-gaps motion is realized. Five experiments guaranteed that the maximum fluctuation of measured mean variation of air-gap is 1.4 um /mA. At last, analysis of measuring results of four air-gaps was carried out, which provided basis for later precise micro-assembly. |
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