رویکرد به کنترل کیفیت به وسیله ی کامپیوتر بر اساس 3D مختصات اندازه گیری دقیق
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|4571||2000||15 صفحه PDF||سفارش دهید||5168 کلمه|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Materials Processing Technology, Volume 107, Issues 1–3, 22 November 2000, Pages 96–110
The quality of manufactured products usually needs to be verified. This paper presents an advanced CAQ approach to compare manufactured objects with reference data from underlying CAD models. First, an overview about the current state-of-the-art in optical 3D measurement techniques is given. After that the research method adopted in this paper is discussed. Furthermore, a software prototype of the presented approach in which a stripe projection system with combined gray-code and phase shifting is described. With this equipment, 3D shapes of objects or manufactured products can be measured. In order to compare the 3D data (represented in sensor coordinate system) a registration to the CAD coordinate system is needed. At first, the selection of a starting point for the orientation parameters is described. For the registration process different numerical algorithms are used to minimize a distance function. To achieve a better performance, an optimization process based on 3D voxel arrays is introduced. After the registration process, several parameters for the kind of geometric displacement can be calculated and visualized. For objects that cannot be measured from one direction, a pair-wise registration as well as a global registration have been developed. Furthermore, some rapid prototyping examples to which our CAQ approach has been applied are presented. Those examples show that our method works well in practice. Finally, some application fields for the CAQ approach presented here are outlined.
In recent years the entire process from computer-aided product design to manufacture has reached an almost ultimate perfection. However, nominal/actual value comparisons show that there are always deviations between a manufactured product and its underlying CAD model. Reasons for that are, e.g. tool wear, thermal expansion, material defects, etc., things that are due to the nature of mechanical engineering, of course. In the range of computer-aided quality control the above-mentioned deviations have to be verified to detect part variations or to make tolerance conformance decisions. Today, there are powerful state-of-the-art coordinate measurement systems available that have provided industry with outstanding tools for expecting complex parts. Meanwhile, the majority of these systems is based on 3D metrology that has brought a significant change in modern coordinate measurement. The major difference to traditional measurement methods is that 3D metrology systems generate surface coordinates of a measured part instead of measuring its geometric dimensions. Having a collection of digitized surface points, details concerning part variation can be observed. Furthermore, various sections of different geometric features can be measured in a single process. Once a set of measurement data is collected, an independent numerical analysis must be performed to find a basis for a subsequent comparison between the measured feature and the corresponding reference data from its CAD models counterpart. This is the main goal of the approach presented in this paper. A more comprehensive introduction to 3D metrology as well as an overview about related work in this field can be found in . This paper presents a non-contact metrology approach that can be used for various tasks in computer-aided quality control and rapid prototyping. It will be discussed throughout the whole paper and can be summarized as follows. Manufactured objects are measured by a stripe projector system based on a coded light approach combined with phase shifting. For image acquisition a standard video camera is employed. The sampled surface points measured in sensor coordinate system, typically 200.000–400.000 per image, are transferred into a CAD coordinate system. After selecting a rough orientation, either in an interactive manner or by a priori knowledge (automatic orientation without a priori knowledge can also be achieved by using fixed marks on the object’s surface), a sophisticated numerical optimization process is started to determine the exact orientation that means to align the CAD model and the measured data set. A problem that occurs whenever objects cannot be captured from a single 3D sensor within one image has been solved by applying an additional orientation process. Measured data sets captured from different directions can either be orientated relatively to each other or transformed into a common coordinate system. For a nominal/actual value comparison, the distance from the data set to the underlying CAD model can be calculated point by point. The evaluated results can be visualized in many statistical ways, e.g. as difference per measured point, minimum, mean or maximum difference within a CAD element (e.g. an STL triangle). The approach proposed in this paper has been successfully applied to several stereo-lithographic rapid prototyping objects and produced remarkable results. It supports quality control for all kinds of rapid prototyping and/or NC manufactured objects and is especially suited for an integration of CAQ into CAM processes. In that way two essential independently performed processes can be combined to make the overall process of product development more efficient.
نتیجه گیری انگلیسی
In this paper, an advanced CAQ approach for comparing manufactured objects with reference data from underlying CAD models has been presented. The related methods have been discussed, examples have been shown and application fields have been outlined. The suggested method has been implemented in a software prototype and the first test results are promising. Big effort has been made on the implementation of the visualization parts of these software tools. The 3D images shown in the examples above have all been rendered with OpenGL.