Tundish Cover Flux Thickness Measurement Method and Instrumentation Based on Computer Vision in Continuous Casting Tundish

Abstract

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.

Digital-Twin-Based Monitoring System for Slab Production Process

“…Han et al [30] introduced big data and Internet of Things (IoT) technologies into the field of steelmaking, enabling early detection of smelting equipment failures. Lu et al [31] created an instrument for measuring the thickness of thin slab continuous casting and rolling (TSCF) using various devices, such as measuring rods, mechanical devices, and high-definition industrial cameras. Liu et al [32] proposed a method based on flame image processing and pattern classification for end-point prediction in the basic oxygen furnace (BOF).…”