| The positioning platform with large workspace and high precision plays a critical role in many cutting-edge fields, such as themanufacturing and detectingof large scale integrated circuit, the microelectronics manufacturing, the bio-chip technologies, and the lead-free mounted of the printed circuit board. The key theory and technique of the above fields are mainly including the areas of precision driving, accuracy positioning and precise detecting. Considering the beneficial characteristics of the parallel structure of high precision and high speed, and the advantages of the linear ultrasonic motors of large stroke, high resolution and direct drive, a are developed to meet the requirements of the large workspace and the high precision. The key technologies, including the precision control method of the linear ultrasonic motor, the auto-focus algorithm of micro vision, the image processing algorithm of detecting the artificial circle and the precision positioning of the parallel manipulator, are investigated based on the developed system. The theoretical prototype has achieved the large workspace of 20 mm and the precision positioning of ±5μm through the experimental detection and evaluation, which meets the basic requirements of the advanced electronic manufacturing equipments. The main research contents and achievements in this paper including:1. All of the existing 3-dof planar parallel structures are analyzed, and two different projects, namely the guiderail is triangle layout or square layout, are chosen to design the parallel manipulator. The two different projects are compared and analyzed based on the kinematic and dynamic simulation results, and the conclusion that the driving forces in the triangle layout scheme are less than that in the square layout is obtained. Hence, a prototype of 3-PRR planar parallel manipulator actuated by linear ultrasonic motors are designed and manufactured based on the triangle layout analysis, and a computer vision based detection and feedback system is also developed to provide the feedback of the pose of the moving platform.2. Based on the 3-PRR parallel manipulator driven by linear ultrasonic motors, the PID, fuzzy control, neural network and so on are summarized and analyzed. To deal with the non-linearity, time-varying of linear ultrasonic motors,, a new control method based on the normal distribution theory combined with the technology of fuzzy logic approach is proposed.The experimental results show that the positioning error is in the ±0.5μm range when the stroke is 5mm.3. A new auto-focusing function was proposed based on DWT and Sobel-Tenengrad. Then, the defocused and focused sample pictures were used to unsupervised training the self-organizing map algorithm, and the Particle Swarm Optimization was used to accelerate the training process. The auto-focusing experiment was carried out using the trained SOM controller. The experimental results show that the new auto-focusing function has the characters of single steep peak, and strong robustness to different samples and objective lenses. The results also indicate that the SOM based controller only took 7.6 steps for auto-focusing process on average, and the focusing speed and stability has been greatly improved.4. The kinematic model of the manipulator is developed. A charge coupled device camera is adopted to measure the output of the manipulator, namely the 3 degrees of freedom of the manipulator. By using the technologies of image processing, the center of the artificial features fixed on the moving platform is located to realize the pose measurement of the moving platform. Based on the error evaluation function, particle swarm optimization algorithm is employed to optimize the kinematic parameters of the manipulator. Calibration experiments show that: the max trajectory error of the desired ellipse motion is greater than 800μm before calibration experiment, but the trajectory error is reduced to within 20μm after the calibration experiment.5. The Kalman fitter is adopted since the image processing time is up to 189 ms while detecting the position of the circles. The region of interest of the image can be reduced to 32X32 size using the proposed Kalman fitter to predict the location of the object and the total calculation time can been reduced to less than 4ms.The experiments from the prototype reveal that the tracking error of X-Y axes is within ±10μm and the range of θ is within ±0.1o, when tracking a circle with 2mm diameter, and the visual alignment system can achieve a higher precision range within ±5μm by repeated the alignment process when performing point position task. |
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