Method for automatically detecting abnormal shape of injector part by using mechanical vision system

A machine vision system and automatic detection technology, which is applied in the direction of instruments, measuring devices, optical devices, etc., can solve the problems of inability to guarantee the quality of product qualification rate inspection, high labor intensity, and low monitoring speed, and achieve the goal of reducing the labor intensity of inspection Effect

Inactive Publication Date: 2012-01-04
WUXI ZHONGWANG 4D TECH
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0004] Aiming at the existing technology, the on-line detection of the abnormal shape of the syringe parts relies on manual detection, the workers are prone to visual fatigue, the labor intensity is high, the product qualification rate and detection quality cannot be guaranteed, and the monitoring speed is low. The invention provides a machine vision system for The automatic detection method of the abnormal shape of the syringe parts greatly reduces the labor intensity of the workers' detection, and the detection accuracy is high and the speed is fast, which can effectively ensure the qualified rate of the manufactured products

Method used

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  • Method for automatically detecting abnormal shape of injector part by using mechanical vision system
  • Method for automatically detecting abnormal shape of injector part by using mechanical vision system
  • Method for automatically detecting abnormal shape of injector part by using mechanical vision system

Examples

Experimental program
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Effect test

Embodiment 1

[0031] Example 1, the detection of qualified syringe parts (taking the syringe rubber piston as an example):

[0032] Such as figure 2 The profiled image of the syringe rubber plunger shown has a protruding profile in its upper portion.

[0033] Fix the Basler ACA640-100GM industrial camera on the side of the syringe part, the distance between the camera and the side of the syringe part is about 100mm, use the Schneider zoom lens, adjust the focal length to 8mm, adjust the aperture to the maximum value, and adjust the exposure time to 0.41 ms. The detection accuracy of component abnormality is set to 0.05mm, and the normal abnormality value of qualified products is set to a maximum of 0.5mm. A special white LED bowl light source is used to irradiate (positive light) from the same side of the camera relative to the syringe part, and a semi-closed metal frame is used to shield the influence of external stray light, so as to obtain a relatively stable visual image and reflect ...

Embodiment 2

[0039] Example 2, detection of abnormally shaped syringe parts (taking the rubber plunger of the syringe as an example):

[0040] Such as image 3 The profiled image of the rubber plunger of a syringe shown has a protruding profile in its lower portion.

[0041]Fix the Basler ACA640-100GM industrial camera above the straight side of the syringe part, the distance between the camera and the side of the syringe part is about 100mm, use the Schneider zoom lens, adjust the focal length to 8mm, adjust the aperture to the maximum value, and adjust the exposure time to 0.41ms. The detection accuracy of component abnormality is set to 0.05mm, and the normal abnormality value of qualified products is set to a maximum of 0.5mm. A special white LED bowl light source is used to irradiate (positive light) from the same side of the camera relative to the syringe parts, and a semi-closed metal frame is used to shield the influence of external stray light in order to obtain a relatively sta...

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Abstract

The invention provides a method for automatically detecting an abnormal shape of an injector part by using a mechanical vision system. The method comprises the following steps of: pre-shooting an image of a standard part as an abnormal shape standard image, and storing the image into a computer; setting a difference proportion of the abnormal shape standard image as a detection parameter; setting the detection accuracy and qualified range of different detection parameters according to a user requirement; starting a camera by using an external trigger and control signal to shoot the image of the abnormal shape of an on-line operating injector part in real time, and transmitting the shot image to the computer for detection; processing the image by using the computer with an image algorithm, and extracting the image of the abnormal shape of the injector part; calculating an abnormal shape difference value, and judging whether a product is a qualified product or a rejected product by using the calculated abnormal shape difference value; and eliminating the rejected product from an appointed discharge hole by using the external trigger and control signal. The method has the advantages that: the detection accuracy and speed of the abnormal shape of the injector part are high; and the yield of products can be effectively guaranteed.

Description

technical field [0001] The invention relates to the technical field of using a machine vision system for on-line detection, in particular to a method for automatically detecting whether a syringe part is abnormal by using a machine vision system at the production site of the syringe part. Background technique [0002] In the assembly workshop of the syringe parts in the assembly line of the assembly line, it is necessary to carry out online detection of whether each part of the syringe is abnormal. In the prior art, the on-line detection of the abnormal shape of the syringe parts relies on manual detection, and about 80 people are arranged beside the syringe parts production machine to detect and process the abnormal shapes of the syringe parts, and the products are classified into qualified products according to the detection results (such as the abnormal shape <0.5 mm) and unqualified products (such as special-shaped ≥ 0.5mm). Unqualified products are directly rejected...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01B11/24
Inventor 董仲伟
Owner WUXI ZHONGWANG 4D TECH
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