Method for classification and online defect visual detection of blister drugs on production line

A visual inspection and production line technology, applied in the field of medical inspection, can solve the problems of high labor intensity, false detection, poor reliability, etc., and achieve the effect of low missed detection and false detection rate, high detection efficiency, and low labor intensity.

Inactive Publication Date: 2017-12-29
FOSHAN NANHAI GUANGDONG TECH UNIV CNC EQUIP COOP INNOVATION INST +1
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Problems solved by technology

This detection method is labor-intensive, has poor reliability and low efficiency, and it is difficult to achieve the speed required for assembly line production and meet production needs.
And it is very harmful to the eyesight of the inspectors
Moreover, this manual selection method is greatly affected by human subjective factors, and is prone to fatigue, and cannot maintain a good condition during working hours, resulting in defects in packaging, missed inspections, false inspections, etc. of blister drugs.

Method used

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  • Method for classification and online defect visual detection of blister drugs on production line
  • Method for classification and online defect visual detection of blister drugs on production line
  • Method for classification and online defect visual detection of blister drugs on production line

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Embodiment Construction

[0048] The present invention will be further described below in conjunction with specific embodiment:

[0049] See attached Figure 1-2 As shown, a method for classification of blister drugs on a production line and an online visual inspection method for defects described in this embodiment includes the following steps:

[0050] S1. Obtain and store the standard threshold value of the blister drug size, color component, drug particle circularity, drug particle area and the standard value of the number of drug particles, so as to be used as a reference for the subsequent blister drug to be tested. The specific steps are:

[0051] S11. collecting images of standard blister medicines;

[0052] S12. Preprocessing the collected images: selecting a 5*5 window for median filtering to remove salt and pepper noise and pollution on the surface;

[0053] S13. Measure the size of the aluminum-plastic panel, and set the standard threshold of the size of the aluminum-plastic panel accordi...

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Abstract

The invention relates to a method for classification and online defect visual detection of blister drugs on a production line. The method comprises the following steps: S1, acquiring and storing the reference standards of all characteristics of the blister drugs; S2, acquiring images of the blister drugs to be detected; S3, carrying out detection of the different types of blister drugs on the blister drugs to be detected according to the standard threshold values of all the characteristics of the blister drugs; S4, carrying out defect detection of the same type of blister drugs on the blister drugs to be detected according to the standard threshold values of all the characteristics of the blister drugs; S5, obtaining the same type of blister drugs without defects. The method replaces the traditional artificial blister drug quality inspection with a machine vision inspection technology, and has the advantages of being low in labor intensity, not susceptible to subjective factors, high in reliability and detection efficiency, low in loss detecting rate and false detecting rate, and the like.

Description

technical field [0001] The invention relates to the technical field of medical detection, in particular to a method for classification of blister medicines on a production line and an online visual detection method for defects. Background technique [0002] At present, most domestic pharmaceutical companies mainly use manual quality inspection to detect defects in blister drugs. This method requires workers to monitor the aluminum-plastic packaging drug boards on the assembly line in real time, and immediately reject unqualified blister drugs. This detection method is labor-intensive, has poor reliability and low efficiency, and it is difficult to achieve the speed required for assembly line production and meet production needs. And it is very harmful to the eyesight of the inspectors. Moreover, this manual selection method is greatly affected by human subjective factors, is prone to fatigue, and cannot maintain a good condition during working hours, resulting in missed ins...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/88G06T5/00G06T7/00
CPCG01N21/8851G01N2021/8887G06T5/002G06T7/0012
Inventor 张美杰
Owner FOSHAN NANHAI GUANGDONG TECH UNIV CNC EQUIP COOP INNOVATION INST
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