A kind of floor automatic sorting method

Abstract

The invention belongs to a sorting method, in particular to a floor automatic sorting method. An automatic floor sorting method, which includes the following steps: step 1: training phase; training artificial intelligence, so that the artificial intelligence can automatically identify the defects of the floor in black and white images and color images; step 2: use phase; 1. The artificial intelligence obtained by training is identified and randomly checked, and the artificial intelligence is continuously upgraded iteratively. The significant effects of the invention are: an effective identification algorithm is formed through artificial intelligence training, and then the algorithm is used for intelligent identification, the identification efficiency is high, the identification effect is good, the marginal cost is low, and the quality control of the finished floor product is beneficial. In addition, if other defects occur, the recognition algorithm can be upgraded as long as the training is supplemented. The upgrade iteration is convenient and fast, and the iteration cost is low.

Description

technical field [0001] The invention belongs to a sorting method, in particular to a floor automatic sorting method. Background technique [0002] Under the wave of Industry 4.0, industrial automation is the development trend. In the process of industrial automation, intelligent quality inspection occupies an important part and is a key step to ensure product quality. [0003] In the flooring industry, especially in the field of PVC flooring, the appearance directly affects the quality of the product and the willingness of consumers to buy. Therefore, almost all manufacturers attach great importance to the quality inspection of the appearance of the flooring. [0004] In the traditional technology, appearance quality inspection has always been done through manual visual screening, relying on experienced workers for visual identification. However, due to the many types of appearance defects of the floor, such as attached Figure 1-13 shown. These defects include but are no...

AI Technical Summary

Problems solved by technology

During manual identification, as the working hours go by, workers will inevitably experience work fatigue, lack of energy and other problems, so there may be missed detections

In addition, different workers have different judgment standards for the same defect. Some people think it is a defect, while others think it is a small defect, which does not affect subsequent sales and use, so the judgment standard is not uniform.

At the same time, the labor cost is extremely high, and the efficiency of manual detection is also low.

[0005] In summary, the traditional detection method has the following disadvantages: slow detection speed, unstable detection results, uncontrollable detection accuracy, high detection cost, etc.

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