Artificial intelligence allows the textile industry to “intellect” in four directions

With the wide application of machine vision technology in the industry, artificial intelligence is also constantly maturing, especially in the fields of security and finance. In addition, more and more entrepreneurs are also trying to bring new breakthroughs in industries, manufacturing, and other related fields to reduce costs and improve efficiency, and gradually replace the traditional manual work methods.

Taking the textile industry as an example, in the textile process, it can generally be divided into spinning, weaving, printing and dyeing and finishing processes. The fabric defect detection is an important part of the weaving process. Glass fiber multi-axial fabrics often have some foreign matter and hairballs mixed in the weaving process. The detection of fabric defects is the key to quality control of fabrics in major textile mills. Link. At present, the detection of fiber fabric defects at many domestic companies still remains at the stage of manual inspection. Manual inspections have many disadvantages such as slow speed, limited output, high rate of missed inspections, and poor continuity of detection. Therefore, it is urgent to develop novel, fast and accurate fabric defects. Detection method.

Xi'an Kede is a high-tech enterprise in the field of artificial intelligence based on image recognition and machine vision software algorithms. It is mainly used for the surface quality inspection of textile glass fiber, textile, carbon fiber, chemical fiber, and non-woven fabrics. The difficulty in the detection of fabric defects mainly lies in the variety of texture and morphological structure of the fabrics, and in particular, the types of defects are very different. Xi'an has adopted a neural network algorithm using artificial intelligence algorithm and deep self-learning function. It can automatically adjust the algorithm for optimal performance for different varieties, weight, width, different cutting lines, light source attenuation or replacement of new light sources. Detect foreign objects and defects.

At the same time, continuous real-time detection is achieved through machine vision technology. Multiple high-speed industrial cameras and visual light sources fixed on top of a multi-axial fabric constantly take pictures of the moving cloth surface at high speed, acquire images, transmit real-time images to the computer, perform real-time image processing and analysis, and detect defects. Timely alarm or parking, prompting manual processing. From a practical point of view, compared to the traditional manual inspection, fabric defect detection equipment can quickly improve work efficiency; in terms of recognition rate, the detection rate is as high as 95%, and in terms of cost, it can replace half of the manual detection and save 50%. wage.

In the current market competition, there are generally quality guarantees, but efficiency cannot be improved quickly, and the willingness to iterate the technology is not enough to support the larger development costs. The high market share, but the lack of quality assurance, is not suitable for users who are increasingly concerned about quality issues. In contrast, Xi'an’s core advantages lie in the accumulation of actual experience and algorithms on the site, ie, artificial intelligence. Solve existing human problems, quality problems, and efficiency issues.

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Description:

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