Research on Measurement Method of High Temperature Slag Flow Rate Based on Image Identification

Chong Wang, Hong Wang, Xun Zhu, Xianyan He, TYu Tan, Bin Ding, Yudong Ding


A method for the measurements of the flow rate of high temperature molten slag using image identification was proposed. Image of molten slag could be acquired by high-speed camera. The flow rate of molten slag was calculated by the diameter, which was obtained by the edge detection, and the velocity of the feature points obtaining by threshold segmentation. Feature points could be found on the liquid column of molten slag by photo graphing, which showed that the method is feasible. Then glycerite was used to study the influences of different shooting parameters on the measurement accuracy. The effects of exposure time, frame rate and focal length on measurement accuracy were obtained. At the same time, it was found that the selection of location and length of feature region would also have a significant impact on the measurement accuracy.



Flow; Measurement; Algorithm; High Temperature Molten Slag; Image Identification

Full Text:



Wang Wenwen ,Efficiency-based Study on the Impact of China's Iron and Steel Industry Policy,[D] Nanjing: Nanjing University of Technology.2016.

Tan Y, Zhu X, Wang H, et al. Centrifugal granulation characteristics of molten blast furnace slag and performance of the granulated particles[J]. Applied Thermal Engineering, 2018, 142: 683-694.

Li Q H, Meng A H, Zhang Y G. Recovery status and prospect of low-grade waste energy in China[C]// International Conference on Sustainable Power Generation & Supply. 2009: 1-6.

Comprehensive Utilization of Blast Furnace Slag [J]. Iron and Steel Research, 2010, 38(2): 53-56.

Zhang H, Wang H, Zhu X, et al. A review of waste heat recovery technologies towards molten slag in steel industry[J]. Applied Energy, 2013, 112: 956-966.

Tan Y, Zhu X, He X Y, et al. Granulation characteristics of molten blast furnace slag by hybrid centrifugal-air blast technique[J]. Powder Technology, 2018, 323: 176-185.

Yang yinkai. Numerical simulation of blast furnace slag dry centrifugal granulation [D]. Wuhan.

Ding B, Wang H, Zhu X, et al. Crystallization Behaviors of Blast Furnace (BF) Slag in a Phase-Change Cooling Process[J]. Energy & Fuels, 2016, 30(4): 3331-3339.

Ding B, Zhu X, Wang H, et al. Experimental study on phase change heat transfer characteristics of alloys[J]. International Journal of Heat and Mass Transfer, 2017, 105: 261-269.

Qiu Yongjun, Zhu Xun, Wang Hong, et al. Three-dimensional Numerical Simulation of Air Cooling.

Wang H, Ding B, Zhu X, et al. Influence of Al2O3 content on crystallization behaviors of blast furnace slags in directional solidification process[J]. International Journal of Heat and Mass Transfer, 2017, 113: 286-294.

Memon S A, Lo T Y, Barbhuiya S A, et al. Development of form-stable composite phase change material by incorporation of dodecyl alcohol into ground granulated blast furnace slag[J]. Energy and Buildings, 2013, 62:360-367.

Du Bin, Zhang Yanguo. Experimental Study on Centrifugal Granulation of Liquid Blast Furnace Slag by Rotating Disk [J]. Metallurgical Energy, 2013, 32(4): 29-32.

Sun Qiang, Gui Weihua, Li Yonggang, et al. A new method for on-line detection of high temperature fluid flow [J]. Computing Technology and Automation, 2001, 20(4).10-13.

Fife S , Andereck C D, Rahal S. Ultrasound thermometry in transparent and opaque fluids[J]. Experiments in Fluids, 2003, 35(2):152-158.

Bizjan B, Širok B, Chen J. Optical measurement of high-temperature melt flow rate[J]. Applied Optics, 2018, 57(15): 4202-4210.

Liu Junjie. Study on dynamic vertical velocity detection of molten iron with infrared radiation time difference [D]. Shenyang: Northeastern University.2010.

Qu Ningning, Cai Xiaoshu, Zhou Zhi, et al. Experimental measurement of coherent structure of turbulent boundary layer by moving single frame image method [J]. Journal of Chemical Engineering, 2017(11):104-110.

Yan Z Y, Yan M, Hao S, et al. Cloud and Cloud Shadow Detection Using Multilevel Feature Fused Segmentation Network[J]. IEEE Geoscience and Remote Sensing Letters, 2018, 15(99): 1600-1604.

Sun Peng, Chai Tianyou, Zhou Xiaojie, et al. Flame Image Recognition System in Alumina Rotary Kiln [J]. Journal of Chemical Engineering, 2008, 59(7).

Romdhani S, Blanz V, Vetter T. Face Identification by Fitting a 3D Morphable Model Using Linear Shape and Texture Error Functions[C]// Computer Vision - ECCV 2002. Springer Berlin Heidelberg, 2002: 3-19.

Jassim E W, Newell T A, Chato J C. Probabilistic determination of two-phase flow regimes in horizontal tubes utilizing an automated image recognition technique[J]. Experiments in Fluids, 2007, 42(4): 563-573.

Anthonys G, Wickramarachchi N. An image recognition system for crop disease identification of paddy fields in Sri Lanka[C]2009 International Conference on Industrial and Information Systems (ICIIS). 2009: 403-407.

Figueiredo M M F, Goncalves J L, A. M. V. Nakashima, et al. The use of an ultrasonic technique and neural networks for identification of the flow pattern and measurement of the gas volume fraction in multiphase flows[J]. Experimental Thermal and Fluid Science, 2016, 70: 29-50.

Yin X X, Hadjiloucas S, Zhang Y, et al. Pattern identification of biomedical images with time series: Contrasting THz pulse imaging with DCE-MRIs[J]. Artificial Intelligence in Medicine, 2016, 67: 1-23.

Tong Jianjun, Zou Mingfu. Vehicle Speed Measurement Based on Surveillance Video Images [J]. journal of image and graphics, 2005, 10(2): 192-196.

Shi Lilian, Zhou zekui, ren shapu. image detection method of gas-liquid two-phase flow parameters in vertical pipeline [J]. fluid machinery, 2004, 32(9): 4-6.

Shi Lilian, Cai Jinhui, Zhou Zekui. Identification of gas-liquid two-phase flow patterns based on image processing [J]. Journal of Zhejiang University (Engineering Edition), 2005, 39(8). 1128-1131.

He X Y, Zhu X, Wang H, et al. Experimental visualization and theoretical analysis of the dynamic impact behavior of a molten blast furnace slag droplet on different surfaces[J]. Applied Thermal Engineering, 2019, 147: 1-9.

Wu Junjun, Wang Hong, Zhu Xun, et al. Filamentous granulation characteristics in rotary centrifugal granulation [J]. Journal of Chemical Engineering, 2015, 66(7): 2474-2480.

DOI: http://dx.doi.org/10.18282/pef.v9i1.849


  • There are currently no refbacks.