Real-time defect identification system and method for optical fiber braided layer

Abstract

The invention discloses a real-time defect identification system and method for an optical fiber braided layer. The system comprises an imaging module, a computer control module, an image preprocessing module, a defect detection module and a defect classification module. The system is applied to operation in a factory in which n defect detectors, a host and n braiding machines are used for optical fiber braiding, and carries out real-time defect detection on an optical fiber braided layer in the optical fiber braiding process. The defects of high subjectivity, high misjudgment rate, high omission ratio, low efficiency, high labor intensity, high cost and the like of manual detection can be overcome, so that real-time defect detection, classification and alarm in the braiding process of an optical fiber braided layer can be realized.

Description

technical field [0001] The invention belongs to the field of image recognition and quality detection of optical fiber braiding layers, in particular to a real-time defect recognition system and method for optical fiber braiding layers. Background technique [0002] The 21st century is the information age. Computer and network technologies are further popularized and developed rapidly. The traditional industrial inspection industry is undergoing reforms, and intelligent inspection has gradually entered our sight. At present, during the production and use of optical fibers, the outer braid layer Faults may occur due to improper use or maintenance of production equipment, resulting in damage to the braid layer, resulting in surface defects in different forms such as exposed fibers, hairs, small pitches, foreign objects, oil stains, etc. These defects will bring unpredictable problems to the normal use of optical fibers Therefore, defects should be detected early, and problems i...

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Problems solved by technology

[0002] The 21st century is the information age. Computer and network technologies are further popularized and developed rapidly. The traditional industrial inspection industry is undergoing reforms, and intelligent inspection has gradually entered our sight. At present, during the production and use of optical fibers, the outer braid layer Faults may occur due to improper use or maintenance of production equipment, resulting in damage to the braid layer, resulting in surface defects in different forms such as exposed fibers, hairs, small pitches, foreign objects, oil stains, etc. These defects will bring unpredictable problems to the normal use of optical fibers hazards, so defects should be detected early, timely locate and solve problems in the production process, and eliminate hidden dangers

[0003] At present, the conventional detection methods for surface defects of optical fiber braiding layer rely on manual sampling inspection and visual inspection, which are easily affected by human subjective factors, resulting in misjudgment of defects, missed inspections, etc., and the efficiency of manual inspection is low and the cost is high.

[0004] At present, the intelligent detection method for the surface defect of the optical fiber braid is to use the neural network model to detect and classify the defects of the optical fiber braid, but when only using the neural network model to detect defects, due to the real-time There are a lot of fiber optic images taken. In the case of little difference in recognition accuracy, the amount of parameters and calculations is large, the detection time is too long, and the model is not easy to modify

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