Raw silk defect detection equipment

Abstract

The invention discloses raw silk defect detection equipment. An analog-type photoelectric sensor and a camera are arranged near a raw silk traction path; the analog-type photoelectric sensor continuously tests an individual filament and is used for finding defects, determining the positions of the defects and preliminary determining the sizes and the types of the defects; the analog-type photoelectric sensor is connected with a first data acquisition card, and transmits data to the first data acquisition card; the first data acquisition card is connected with a computer and a control card; thecamera is connected with a second data acquisition card, and transmits data to the second data acquisition card; the second data acquisition card is connected with the computer and the control card;after the analog-type photoelectric sensor detects the defects, the camera is triggered by the control card to shoot pictures of the defects, and the defect images are processed by the computer so asto judge the types of the defects, so that the defects are graded according to the types, the shapes and the sizes of the defects. Based on the photoelectric sensor and machine vision, the raw silk defect detection equipment can completely replace blackboard inspection.

Description

technical field [0001] The invention relates to a raw silk defect detection device. Background technique [0002] As a natural raw material, cocoon silk has attracted much attention in high-end textile and clothing products due to its excellent performance. China is the world's largest cocoon and silk production and trade country, and raw silk is one of the few resource-based commodities in my country that dominates the international market. Haimen, with the cocoon and silk industry as its pillar industry, is known as the "Hometown of Cocoon and Silk". Its cocoon and silk industry chain has an annual output value of more than 10 billion yuan, and its cocoon production and purchase volume rank first in the province at the county (city) level for many years. The number, type, shape, and size of raw silk defects directly affect the quality and appearance of silk fabrics, and are important indicators of raw silk quality. For a long time, the defect detection of raw silk in va...

AI Technical Summary

Problems solved by technology

In 2015, Fang Hua et al. proposed a machine vision-based raw silk defect detection algorithm, but this algorithm only extracted the outline of raw silk defects, and did not further classify raw silk defects

It can be inferred that the post-processing of such equipment takes a long time and is inefficient, making it difficult to enter the stage of practical application.

[0011] In general, photoelectric / capacitive defect detection equipment has fast detection speed, low equipment cost and high efficiency, but it cannot accurately identify the type of defect, and cannot replace the traditional blackboard inspection of raw silk defects with artificial eyes. It can only be a supplement to the existing blackboard inspection. Test method

Although image-based raw silk defect detection equipment can theoretically determine the type of defect and has good detection repeatability, this type of equipment has high requirements for image acquisition equipment and image processing equipment, cumbersome preparation work, low detection efficiency, high equipment cost, and recognition. The error is large, and it is difficult to enter the stage of practical application and promotion

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