Abstract
Optical systems for automatic visual inspections are of increasing importance in the field of automation in the industrial domain. A new application is the determination of steering wheel angles during wheel track setting of the final inspection of car manufacturing. The camera has to be positioned outside the car to avoid interruptions of the processes and therefore, oblique images of the steering wheel must be acquired. Three different approaches of computer vision are considered in this paper, i.e. a 2D shape-based matching (by means of a plane to plane rectification of the oblique images and detection of a shape model with a particular rotation), a 3D shape-based matching approach (by means of a series of different perspectives of the spatial shape of the steering wheel derived from a CAD design model) and a point-to-point matching (by means of the extraction of significant elements (e.g. multifunctional buttons) of a steering wheel and a pairwise connection of these points to straight lines). The HALCON system (HALCON, 2016) was used for all software developments and necessary adaptions. As reference a mechanical balance with an accuracy of 0.1° was used. The quality assessment was based on two different approaches, a laboratory test and a test during production process. In the laboratory a standard deviation of ±0.035° (2D shape-based matching), ±0.12° (3D approach) and ±0.029° (point-to-point matching) could be obtained. The field test of 291 measurements (27 cars with varying poses and angles of the steering wheel) results in a detection rate of 100% and ±0.48° (2D matching) and ±0.24° (point-to-point matching). Both methods also fulfil the request of real time processing (three measurements per second).
Highlights
In the industrial environment quality control has become an essential part of the production process
It has to be taken into account that those balances have a certain accuracy, i.e. the differences between the steering wheel angles extracted by the computer vision system and the mechanical balance contain a component caused by the balance itself
The obtained results have shown that computer vision systems based on automatic image analysis can fulfil the requirements of accuracy, contact-free measurements and real time analysis, indispensable preconditions for fully automatic inspection processes in the industrial production environment
Summary
In the industrial environment quality control has become an essential part of the production process. Automatic visual inspections based on digital imagery allow contact-free real time measurements of high accuracy in dynamic production processes. More complex challenges can be met by image analysis One of such new applications in this field is the determination of steering wheel angles during car alignment in the context of the final inspection of manufacturing. During wheel track setting the current steering wheel angle needs to be determined and subsequently aligned to a horizontal position (rotation angle = 0°). In this research a steering wheel balance of manufacturer DSA (DSA, 2016) was used with an operation area of ±20° This balance delivers an accuracy of 0.1° (Dürr, 2016a).
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