Glass bottle defect detection system

Abstract

The invention provides a glass bottle defect detection system. A bearing unit, a defect detection unit, a judgment unit, an information processing unit, an adjusting and supporting unit and a controlunit are arranged in an inspection device. According to the defect detection device, optics and camera shooting analysis are combined; a sensor unit and the control unit are arranged, the convenienceof glass bottle defect detection work and the accuracy of defect detection can be effectively improved, and the yield of glass products is further improved; and the judgment unit and the information processing unit are arranged, the defect type of a glass bottle can be effectively analyzed, reference significance is provided for glass bottle production, and the problems that in the prior art, themanual detection effect is slow, the detection effect is poor, the detection cost is high, defect detection in glass bottle production is inaccurate, and production reference significance cannot be provided for a glass production process are solved.

Description

technical field [0001] The invention relates to the field of glass bottle defect detection systems, in particular to a glass bottle defect detection system. Background technique [0002] In the production process of glass bottles, the limitations of hot-end equipment, machinery and production precision instability of the production process will lead to defects such as cracks, bubbles, fried edges, etc. at the glass bottle mouth. These defects not only affect the appearance of the product, but also cause cause safety hazards. At present, the defect detection of industrially produced glass bottles is mainly manual quality inspection, that is, through random inspection, to detect the defects of glass bottles. Due to the fact that random inspection relies too much on the test results of random samples, the results of random inspection are often unsatisfactory, and The defects of the glass bottle mouth cannot be found comprehensively, which indirectly leads to the increase of th...

AI Technical Summary

Problems solved by technology

[0002] In the production process of glass bottles, the limitations of hot-end equipment, machinery and production precision instability of the production process will lead to defects such as cracks, bubbles, fried edges, etc. at the glass bottle mouth. These defects not only affect the appearance of the product, but also cause cause safety hazard

At present, the defect detection of industrially produced glass bottles is mainly manual quality inspection, that is, through random inspection, to detect the defects of glass bottles. Due to the fact that random inspection relies too much on the test results of random samples, the results of random inspection are often unsatisfactory, and The defects of the glass bottle mouth cannot be found comprehensively, which indirectly leads to the increase of production cost

Moreover, some cracks can only be seen clearly under certain reflective conditions. Due to individual visual differences, detecting glass bottle defects with the naked eye will affect the detection effect

In addition, the glass bottle detection in the prior art cannot obtain the glass bottle defect type more accurately, and cannot provide positive reference significance for the production of glass bottles, and the glass bottle detection in the prior art has low intelligence and convenience And the accuracy needs to be improved. How to effectively solve the above problems and realize the defect detection of the glass bottle mouth based on machine vision is a technical problem that needs to be solved urgently in this field.

[0003] For example, the patent No. CN107607549A discloses a glass bottle defect detection system, which can detect glass defects, but cannot specifically analyze the type of the defect

Another example is that the patent No. CN208155890U discloses a glass defect detection device, but its detection process is complicated

[0004] In summary, in the field of glass defect detection devices, there are still many practical problems that need to be dealt with in practical applications, and no specific solutions have been proposed.

Images