Chemical fiber product line
Silk cake appearance inspection
Based on artificial intelligence, machine vision, computer technology, professional optical technology, and automation technology, and using customized lenses and light sources, a high-performance fully automatic inspection line, the HD-FDY-I chemical fiber cake appearance inspection system, has been developed. It can meet the stringent requirements of the chemical fiber industry and the industrial production environment. By using artificial intelligence deep learning technology and with the help of a large number of defect data samples, it can learn the multidimensional features of defects and accurately identify and classify various defects.

Function:
1. With artificial intelligence technology at its core, combined with cutting-edge technologies such as machine vision, optical imaging, and electrical automation, a fully automated silk cake appearance inspection system was finally realized through their collaboration.
2. Defect Classification: Utilizing artificial intelligence deep learning technology based on a large number of defect data samples, the system learns multidimensional defect features to accurately classify various defects.
3. By using a large number of defect samples detected later, a defect classification model can be trained through deep learning parameter tuning, thereby accurately classifying and identifying defect types. This allows for more precise grading of the silk cake quality and provides a data interface for connection with the packaging system.
4. The human-computer interaction interface (HCI) is a comprehensive embodiment of the system's functions, serving as the central control and data center for system implementation. It primarily includes functions such as real-time detection, statistical analysis, product management, user management, camera settings, and system settings. Detection data is stored in a local database, and statistical analysis functions are used to trace defects and products and conduct big data analysis, providing managers with production data.
5. Quality grading and automatic packaging interface
6. Can provide data interfaces for ERP or MES big data systems.
Applicable scenarios: Composite materials industry / Textile industry / Detection of appearance defects in various chemical fiber filament cakes such as polyester, spandex, nylon, aramid, and PE fibers.
Inquiry Hotline 400-8800-716
Product Features
01
Can complete testing items
(1) It can detect all defects of various chemical fiber filament cakes, including the upper and lower surfaces, 360° circumferential surface, and paper tubes. (2) It can detect fuzz, accompanying filaments, oily filaments, and wrapped filaments on all surfaces of the filament cake, as well as the upper and lower end faces and cylindrical surfaces. (3) It can detect poor filament cake forming, including the upper and lower surfaces and the circumference. (4) It can detect stains on the outer surface of the filament cake. (5) It can identify the color of the paper tube. It can successfully detect abnormal colors and detect them stably. (6) It can detect paper tube defects. Since the burrs on the paper tube have a great influence on the formation of fuzz in the fiber filaments, we can achieve high-precision detection of paper tube defects. (7) We can also complete the detection of the integrity of the filament cake after peeling.
02
Detection efficiency
6 seconds/piece.
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