Intelligent detection method of tablet capsule filling omission based on machine vision
A machine vision and intelligent detection technology, applied in sorting and other directions, can solve the problems of reducing the efficiency of the assembly line, only using, medicine or health care products, etc.
Active Publication Date: 2021-03-16
NANTONG UNIVERSITY
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Problems solved by technology
However, in the filling stage, the current machine vision technology is only used for counting grains, and there is no solution to the problem of filling omissions
The problem of filling omission refers to that when a large number of medicines or health products are filled at the same time, there may be a small amount of medicines or health products spinning in the filling funnel and not falling into the bottle within the specified time, resulting in the bottle not being filled with medicines or Health products
If you increase the filling time, it will reduce the efficiency of the line
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[0063] The technical solution of the present invention will be described in further detail below in conjunction with specific embodiments and accompanying drawings.
[0064] In the present invention, a transparent extension funnel is arranged at the bottom of the original filling funnel, and an industrial camera is aligned with the extension funnel to construct a machine vision detection station, and at the same time, a special light source is used to perform environmental supplementary light on the area of interest (transparent funnel) to be detected below , collect the image information of the region of interest, and transmit the collected image information to the image processing system, and the processing system outputs a control signal after performing image processing on the region of interest, judges whether the bottle is full, and drives the action of the rejecting device unit at the same time, Reject unfilled bottles.
[0065] At the same time, a machine vision insp...
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The invention discloses a machine vision-based intelligent detection method for tablet and capsule filling omissions, which comprises the following steps: respectively attaching two high-speed industrial cameras to the right side of the bottle packaging conveyor belt of the automatic filling production line and above the funnel; the camera above the funnel Real-time video recording of tablet capsule filling, positioning of tablet capsules by block matching of consecutive video frames. The displacement vector of the positioned tablet capsule is monitored in real time, and when the displacement vector is greater than a certain value, it is defined as a filling fault. For the fault phenomenon, we use the SVM prediction model to predict the specific time when the tablet capsule leaves the funnel based on the fault occurrence time, the displacement and angle characteristics of the tablet capsule at the fault when the fault occurs. In this way, it can be judged whether the qualified filling can be completed within the specified time when there is a fault.
Description
technical field [0001] The invention relates to a machine vision intelligent detection method, in particular to a machine vision-based intelligent detection method for tablet capsule filling omissions. Background technique [0002] At present, the demand for industrial automation and intelligent technology using machine vision has begun to appear widely in all walks of life in China. For example, in the bottle packaging line of the pharmaceutical and health care products industry, the processes of bottle feeding, filling, desiccant filling, cap locking, aluminum foil sealing, and labeling all need to be detected online by machine vision technology, and most of the processes have already adopted machine vision technology. However, in the filling stage, the current machine vision technology is only used for counting grains, and there is no solution to the problem of filling omissions. The problem of filling omission refers to that when a large number of medicines or health c...
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IPC IPC(8): B07C5/34
CPCB07C5/3408
Inventor 张堃姜朋朋华亮吴建国张培建王震付君红李子杰
Owner NANTONG UNIVERSITY