The article discusses the technical vision system of a machine for mounting semiconductor crystals. The disadvantage of existing systems is that the moment of installation of a semiconductor crystal on the substrate is not recorded by a camera and is in no way controlled by the operator. This makes it impossible to manually control such installations and complicates the learning process.
The authors of the article eliminated this drawback by using two non-orthogonally located cameras, the focuses of which coincide with the location of the crystal on the working tool. The resulting two images are then processed. The contours of the reference marks on the substrate, already installed elements and the mounted crystal are highlighted. After geometric transformations of the selected contours, the operator receives a real-time map of elements and can adjust the position of the chip in the horizontal plane. All operations are performed in real time. This approach has been practically tested on industrial equipment developed with the direct participation of the authors.
Increasing demands for versatility, ease of deployment and operation, increasing the degree of automation and energy saving necessitate the use of new approaches to the design of manipulators for moving goods. The weight and cost of handling equipment are significantly reduced, as is the degree of protection of more advanced structures based on flexible mechanical connections.
One of the problems of machine that arises when carrying loads, is the impact of factors, such as pendulum fluctuations of the load, compression of suspension cables. In conventional manipulators, such as cranes, this is determined by the skill of the operator. This is not possible in fully controlled non-orthogonal manipulators with multiple actuators.
To solve these problems, the authors of the article use two stereo cameras, the data from which, through mathematical transformations, is fed into the control system. Using a stereo camera is the simplest way to go from object coordinates in pixels an image, in an actual offset expressed in units of length.
This paper presents an efficient algorithm for finding the location of legs on electronic components. The proposed method has a wide range of applications, including areas such as quality manufacturing, quality control, defect detection, and more.
The research described in this article demonstrates the significant potential for automation and optimization in the context of microchip analysis processes. Automated analysis systems can eliminate the need for manual labor, leading to increased efficiency, accuracy, and consistency.
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