Phát triển hệ thống nhận diện màu sắc tự động cho bề mặt ván gỗ công nghiệp trong máy dán cạnh bằng công nghệ laser


Các tác giả

  • Trong Tuan Nguyen College of Mechanical Engineering Northeast Forestry University, Harbin 150040, China
  • Trong Tuan Nguyen College of Mechanical Engineering Northeast Forestry University, Harbin 150040, China
  • Jun Hua College of Mechanical Engineering Northeast Forestry University, Harbin 150040, Chin
  • Bei Long Zhang College of Mechanical Engineering Northeast Forestry University, Harbin 150040, Chin
  • Quoc Huy To Vietnam Academy of Forest Sciences, Hanoi 11956, Vietnam
  • Cong Chi Tran Vietnam National University of Forestry, Hanoi 156200, Vietnam
  • Van Tuu Nguyen Vietnam National University of Forestry, Hanoi 156200, Vietnam
  • Tat Thang Nguyen Vietnam National University of Forestry, Hanoi 156200, Vietnam

Từ khóa:

Arduino UNO, cảm biến TCS3200;, nhận dạng màu sắc, máy dán cạnh Laser

Tóm tắt

Automatic color recognition is an important factor to achieve high levels of automation for laser edge banding system in furniture manufacturing. In this article, a color recognition system was designed and evaluated based on the Arduino UNO mainboard and TCS3200 sensor. The TCS3200 sensor was used to detect the color of the product, and the Arduino mainboard was used to read the output frequency and analyze the color result. Eight-panel surfaces with different colors were used to validate the accuracy of the designed system. The results showed that the design system had the ability to accurately identify colors with high stability. Therefore, this result might be applied for developing automatic color recognition systems in the next generations of laser-based edge sealing machine.

Tài liệu tham khảo

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04-04-2024

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[1]
Nguyen, T.T., Nguyen, T.T., Hua, J., Zhang, B.L., To, Q.H., Tran, C.C., Nguyen, V.T. và Nguyen, T.T. 2024. Phát triển hệ thống nhận diện màu sắc tự động cho bề mặt ván gỗ công nghiệp trong máy dán cạnh bằng công nghệ laser. TẠP CHÍ KHOA HỌC LÂM NGHIỆP. 3 (tháng 4 2024).

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