Machine vision in food & beverages
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Explains about how the Machine vision system works in the food and beverages industry. Detail descriptive animation of machine vision system
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This paper aims to connect the trope of the human imprisoned and isolated by media as it is expressed in dystopic science fiction to its expressions in mainstream discourse. I draw upon theories of immersion and digital dualism, while analyzing the trope across science fiction literature and films as well as in popular media. Works discussed include Fahrenheit 451 (1953), The Matrix (1999), Wall-E (2008), Ready Player One (2011), Divergent (2013) and I Forgot My iPhone (2013). I find that media is frequently seen as a threat that dehumanizes its user, and that this is expressed by showing the human user as a corpse, as a fetus, as motionless or as zombie-like. Even works that show the human as in control of media occasionally make use of this trope, and understanding this cultural imaginary of humans and media can help us understand contemporary media use and discourse.Viewers also liked (20)
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- 1. MACHINE VISION SYSTEM IN By: Mechatronics
- 2. Machine vision Block diagram:
- 3. What is Machine Vision? Lighting Techniques to make part look its best Components of a MachineVision System Field ofView Communications Send decisions to other devices Part: Good # Caps: 1 Image Acquisition Camera taking a picture VisionTools Evaluate the picture
- 4. ImageAcquisition: Imager Microchip that converts light energy into a digital information (pixels) CCD & CMOS are most common imager types Pixels The smallest piece of a digital image Camera Resolution is measured in pixels – 640 x 480 or 0.3 Megapixels – 1600 x 1200 or 2.5 Megapixels Field ofView Parts
- 5. 480 1200 640 1600 Pixel Resolution: 0.3 Megapixel 640 X 480 2.5 Megapixel 1600 X 1200
- 6. Factors affecting Image: Light Intensity Direction Focal length Object distance Imager type (CCD or CMOS) Dark Image calibration Image filtering
- 8. 1.Part arrives at inspection station 2.Proximity or Photo sensor detects part & sends trigger to vision sensor 3.Part is illuminated 4.Image is acquired and digitized 5.Vision software processes image and analyzes part as Good or Bad 6.Discrete output activates reject diverter if part is Bad 7.Display shows operator rejected parts and production statistics GoodBad
- 10. Applications of MV in food and beverages
- 12. 1. Quality Control: - Food Problems: - Wrong pie in wrapper - Damaged pies Solution: - Color vision sensors installed - Quality inspection for damaged pies Good Pie Coated with gaps in shell Coated with gap in shell Uncoated with holes
- 13. Beverages:- Problems: - Liquid in bottles not consistent in color - Matched labels Solution: - DVT color vision sensor - Color monitoring of liquid color
- 14. 2. Bottling, labeling & thread inspection: Problem: - Need to verify cap & tightened correctly - Check safety ring Solution: - Gauging tool in vision sensor measures distance from neck to top of the cap - Verifies safety ring
- 15. Computes dimensions of: - Hole diameter - Label length - Distance and angle
- 16. 3. Product Safety: Label Quality check Problem: - Label missed or torn - Label might have ‘flag’, if not applied fully Solution: - Measure label to check for torn, missing or skew labels - Elimination of ‘flag’
- 17. PC Vision Sees the Entire Product: Verify Product Size Read Bar Code Inspect Label Seam
- 18. 4. Product traceability: -Can code verification -Can Code verification system installed. - For no cans should be mislabeled.
- 19. BAR code reading and grading 2D matrix code reading OCR/ OCV - Optical Character recognition - Optical character verification
- 20. 5. Material Handling: - Locating the product conveyer and placing into the boxes - Vision sensor provides robotic guidance
- 21. Advantages: Lower capital costs Increased productivity Faster time to market Lower production costs Reduced scrap / rework Increased customer satisfaction Improved brand image
- 22. Animation of machine vision:
- 23. Thank You