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EVT develops the graphical programming Machine Vision Software for 1D, 2D, 3D, Themal Imaging and Hyperspectral solutions.
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Quality Control of Cast Parts
POSTED 07/18/2014
During the production and processing of cast parts various defects on the surface of the part can occur. Among them are for example blowholes, scraches, edges, blowouts or pinholes. Defects of this kind can influence the functionality of the cast part and therefore have to be detected and separated from the production in an early stage.
It is well known that a large percentage of cast parts is produced for the automotive industry. But they are also produced for branches such as heating technology, sanitary engineering and electrical engineering. And due to the increasing demand of the customers for zero-defect quality, more and more manufacturers are adopting machine vision inspection, such as with vision sensors by EVT.
The various shapes and surface structures of the cast parts pose a challenge to machine vision developer. There are three main challenges: the first is that some surfaces of cast parts are reflecting. This can be solved with the correct illumination. Also e.g. scratches are best seen with a flat incident dark field light, while blowholes and pinholes need a diffuse reflected-light methode.
The second challenge is the complex outer contour, which usually is not linearly limited. And thirdly, due to the processing of the cast part with sandblasting, milling or polishing, etc. the surface structure is relatively “random”. Therefore it is quite difficult to distinguish between the regular texture and a defect.
The RazerCam in combination with the EyeVision software is providing a variety of commands for a broad range of cast parts. Additionally, the system works also on surfaces and contours, which due to their geometry and texture are known as difficult. Due to the free programmable FPGAs and the two ARM Cortex A9 processors of the RazerCam, the images can be preprocessed already during the image capture.
For the inspection a lineup of steps are carried out. The first step is to recognize the contour. This is useful for limiting the test range and to detect defects in the shape. The second step is to analyze the texture. The surfaces have a strong texture. To prevent defects, the texture is characterized in advance and therefore each difference is a potential error.
Thanks to the FPGAs of the camera, it is possible to detect even the tiniest error in real time and therefore even difficult surfaces can be inspected.
With the EyeVision software already integrated the system is offered as EyeCheck 4000 and contains the advantage of the drag-and-drop programming.