Basic Technical Research On Micromanipulation /Microassembly System For Intelligent Manufacturing

Micromanipulation/Microassembly system for intelligent manufacturing, as the center of MEMS(Micro-Electro-Mechanical System), which is an important way to intelligent micro-manufacturing, has gained more and more attention and application. According to the survey on current available microassembly workstations and application requirements, a micromanipulation/microassembly system for intelligent micro manufacturing is contructed under the support by the key project (No. 59990470) and the project (No. 50275078) of National Nature Science Foundation of China. The main creativities and achievements of the dissertation are as follows: 1.An object recognition and localization algorithm based on local feature―turning angle between neighbouring tangent vectors, is presented. The primary localization of template on image is obtained by comparing the signatures, which are based on the turning angle between the neighbouring tangent vectors at the naturally parameterized edge curve, of image and template. By composing and minizing the object function, which is the function of the transformation parameters of template relative to image, subpixel localization accuracy is achieved. The occluded edge pixel of template is determined according to its distance to the nearest edge pixel of image and will not be taken into account in object function, so the localization accuracy will not be influenced by occlusion. To meet the need of observation of different depth features of 3D object, local autofocusing is added to microscopic vision system. 2.CMAC neural network and PD controller is combined to implement the transformation from the error signal in the image space to the control signal in the task space in order to avoid the iterative adjustment and complicated inverse solution of the image Jacobian. In this control scheme, the CMAC neural network gives the feedforward control and PD controller the feedback conrol. 3.According to the finite element method (FEM) analysis on the stress and strain distribution, a microgripper based on flexure hinge amplification mechanism is designed, which is actuated by piezoelectric ceramic stack. The micro displacement produced by piezoelectric ceramic stack is enlarged by the flexure hinge mechanism to form the large range, high precision motion of the finger. A peg-in-hole experiment is performed to validate the capability of microgripper. 4.A micromanipulation/microassembly system is constructed for intelligent micro manufacturing. Control software is realized with the developing environment Visual C++6.0 and MIL 7.5.