Defect detection and recognition device and method based on deep learning algorithm

Abstract

The invention discloses a defect detection and recognition device based on a deep learning algorithm, which relates to the field of defect detection and identification. The device comprises a test bench, a detection system, a model-based reasoning system, The detection system is connected to the test bench, and the model-based reasoning system operates in the detecting system. The defect detectionand recognition device and method based on deep learning algorithm trains an effective neural network model to detect and recognize the processing defect image to be defected under the condition thatthe actual processing defect data sample is insufficient, and uses the deep learning algorithm to reduce the misdetection probability, and realizes the automatic detection of the decorative sheet tobe detected, and reduces the amount of manual work.

Description

technical field [0001] The present invention relates to the field of deep learning technology, in particular to a defect detection and identification device and method based on deep learning algorithms. Background technique [0002] As an important material for interior decoration, decorative panels are widely used in various indoor places, such as gymnasiums, hotels, residential buildings, etc. In the production process of decorative panels, quality inspection is a key link. In actual production, manufacturers usually employ several skilled and experienced inspectors to detect surface processing defects of decorative panels on the production line. However, the production quantity of decorative panels is huge, and there are many types of processing defects, such as: scratches, stains, plaques, wear, debris, etc., resulting in low efficiency of manual inspection, and it is easy to miss inspection due to fatigue of inspectors. The time and financial costs are high. It is an ...

AI Technical Summary

Problems solved by technology

[0006] In view of the above-mentioned defects in the prior art, the technical problem to be solved by the present invention is to provide a deep learning algorithm based on the complex texture of the decorative plate processing defect detection Identify the method and improve the robustness of the detection method, reduce the missed detection rate, and build an automatic detection and identification device based on this to make the detection process more intelligent

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