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首页> 外文期刊>Mathematical Problems in Engineering >Tundish Cover Flux Thickness Measurement Method and Instrumentation Based on Computer Vision in Continuous Casting Tundish
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Tundish Cover Flux Thickness Measurement Method and Instrumentation Based on Computer Vision in Continuous Casting Tundish

机译：基于计算机视觉的连铸中间包中间包通量厚度测量方法与仪器

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摘要

Thickness of tundish cover flux (TCF) plays an important role in continuous casting (CC) steelmaking process. Traditional measurement method of TCF thickness is single/double wire methods, which have several problems such as personal security, easily affected by operators, and poor repeatability. To solve all these problems, in this paper, we specifically designed and built an instrumentation and presented a novel method to measure the TCF thickness. The instrumentation was composed of a measurement bar, a mechanical device, a high-definition industrial camera, a Siemens S7-200 programmable logic controller (PLC), and a computer. Our measurement method was based on the computer vision algorithms, including image denoising method, monocular range measurement method, scale invariant feature transform (SIFT), and image gray gradient detection method. Using the present instrumentation and method, images in the CC tundish can be collected by camera and transferred to computer to do imaging processing. Experiments showed that our instrumentation and method worked well at scene of steel plants, can accurately measure the thickness of TCF, and overcome the disadvantages of traditional measurement methods, or even replace the traditional ones.
机译：中间包保护层厚度（TCF）在连铸（CC）炼钢过程中起着重要作用。传统的TCF厚度测量方法是单/双线方法，存在一些问题，例如人身安全，容易受到操作员影响以及可重复性差。为了解决所有这些问题，在本文中，我们专门设计并建造了一种仪器，并提出了一种测量TCF厚度的新颖方法。仪器由测量杆，机械设备，高清工业相机，西门子S7-200可编程逻辑控制器（PLC）和计算机组成。我们的测量方法基于计算机视觉算法，包括图像去噪方法，单眼范围测量方法，尺度不变特征变换（SIFT）和图像灰度梯度检测方法。使用本发明的仪器和方法，CC中间包中的图像可以通过照相机收集并转移到计算机以进行成像处理。实验表明，我们的仪器和方法在钢厂现场工作良好，可以准确地测量TCF的厚度，克服了传统测量方法的弊端，甚至可以代替传统方法。

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  • 来源
    《Mathematical Problems in Engineering》 |2013年第9期|690948.1-690948.15|共15页
  • 作者

    Meng Lu; He Qing; Xie Zhi; Yang Weimin; Ci Ying; Zhang Chuanyi; Gao Hongliang;

  • 作者单位

    College of Information Science and Engineering, Northeastern University, Shenyang 110000, China;

    College of Information Science and Engineering, Northeastern University, Shenyang 110000, China;

    College of Information Science and Engineering, Northeastern University, Shenyang 110000, China;

    College of Information Science and Engineering, Northeastern University, Shenyang 110000, China;

    College of Information Science and Engineering, Northeastern University, Shenyang 110000, China;

    College of Information Science and Engineering, Northeastern University, Shenyang 110000, China;

    College of Information Science and Engineering, Northeastern University, Shenyang 110000, China;

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