Computer-vision-based gob inspection system for monitoring and control in the glass industry

Eskarne Laizola; Antonio Ramon Jimenez; Fernando Morgado; Mar Calvache; Fernando Seco

doi:10.1117/12.474025

22 May 2003 Computer-vision-based gob inspection system for monitoring and control in the glass industry

Eskarne Laizola, Antonio Ramon Jimenez, Fernando Morgado, Mar Calvache, Fernando Seco

Proceedings Volume 5011, Machine Vision Applications in Industrial Inspection XI; (2003) https://doi.org/10.1117/12.474025
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States

Abstract

This paper presents a computer vision system for measuring the weight of gobs during a glass forming process, and a control strategy to correct automatically any weight deviation from a given set-point. During the formation of molten glass gobs, several noise sources can cause a deviation in the weight from a predefined reference value. Among them, there is a random white-noise disturbance caused by the lack of synchronisation of mechanical devices, the periodic disturbances due to changes in the spinning direction of the tube inside the feeder, and some long-term drifts caused by variations in temperature and viscosity of the raw glass material. The gob weight measurement system developed is based on a monochrome CCD high-resolution camera and photo-detector for synchronizing the frame acquisition. The molten glass provides the illumination, so a high contrast image is obtained with a bright object and dark background. Several image-processing algorithms are presented for reliable area estimation. Assuming that the gob is a symmetric geometry of revolution and uniform mass density, the proposed system estimates the weight of gobs with an accuracy better than ±0.75%. A learning weight control strategy is proposed based on a PI-repetitive control scheme. The weight deviation from a set point is used as a control signal to adjust the glass flow into the feeder. This regulation scheme allows effective weight control, canceling mid and long-term effects. The tracking error, ±1.5%, means a reduction of 40% when compared with a traditional PI controller.

Citation Download Citation

Eskarne Laizola, Antonio Ramon Jimenez, Fernando Morgado, Mar Calvache, and Fernando Seco "Computer-vision-based gob inspection system for monitoring and control in the glass industry", Proc. SPIE 5011, Machine Vision Applications in Industrial Inspection XI, (22 May 2003); https://doi.org/10.1117/12.474025

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