Appliance of stereoscopy for bath level detection of steel casting pans

Christian Rittenschober; Kurt S. Niel; Roman Rössler

doi:10.1117/12.713107

17 February 2007 Appliance of stereoscopy for bath level detection of steel casting pans

Christian Rittenschober, Kurt S. Niel, Roman Rössler

Proceedings Volume 6503, Machine Vision Applications in Industrial Inspection XV; 65030C (2007) https://doi.org/10.1117/12.713107
Event: Electronic Imaging 2007, 2007, San Jose, CA, United States

Abstract

For an automatic tapping of a steel converter and for further processing steps it is necessary to measure the bath level of the steel casting pans (charging ladles). The harsh environment and the properties of molten steel avoid applications of standard bath level detection systems like based on laser, micro wave or super sonic. Instead of these methods within this paper a stereoscopic camera system is introduced which acquires pictures of the molten steel surface. It is possible to detect the bath level without complex equalization of the perspective by geometric calculations. To know which deformations can make the system defective is essential on designing the mechanical bodywork. Simulations with Matlab allow showing the influences of variations to the stereoscopic standard geometry and the boundaries of the system accuracy. Out of these calculations inaccuracies of camera angle appears to be the main parameter for failures. But a developed algorithm is possible to affect that angle after a tapping automatically. Furthermore different parameters have been analyzed to optimize the accuracy of the stereoscopic algorithm. Generally the investigations of the stereo system have shown which specifications including certain tolerances have to be fulfilled by the designer of the mechanical construction to get accurate and reliable results for the automation process.

Citation Download Citation

Christian Rittenschober, Kurt S. Niel, and Roman Rössler "Appliance of stereoscopy for bath level detection of steel casting pans", Proc. SPIE 6503, Machine Vision Applications in Industrial Inspection XV, 65030C (17 February 2007); https://doi.org/10.1117/12.713107

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