Systems Engineering and Electronics ›› 2023, Vol. 45 ›› Issue (5): 1277-1285.doi: 10.12305/j.issn.1001-506X.2023.05.03

• Electronic Technology • Previous Articles    

Scattering characteristics modeling and imaging of blast furnace burden surface in dusty environment

Qing YU1,2, Qingwen HOU1,2, Xianzhong CHEN1,2,*   

  1. 1. School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
    2. Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, University of Science and Technology Beijing, Beijing 100083, China
  • Received:2021-08-23 Online:2023-04-21 Published:2023-04-28
  • Contact: Xianzhong CHEN

Abstract:

In harsh industrial environments, radar imaging is subject to low contrast and blurred target outlines. The affected quality of the radar imaging can interfere the results of computer vision tasks and cause errors in the results of parameter inversion. In this paper, the back-scattering characteristics of blast furnace burden surface are modeled, and an imaging algorithm based on attenuation compensation and scatter correction is proposed to improve the image quality of random rough surface in a dense dust environment. Considering the propagation loss of microwave along the path, environmental factors are added to the echo model. The attenuation coefficient and the back-scattering coefficient are obtained by Rayleigh scattering and integral equation methods. Based on the transmission loss and scattering mechanism, the target pixel values are compensated, so that the contrast between the target and the background is improved. Differences in pixel values due to the imaging environment, objects at different distances, and the degree of surface inclination are reduced by the prposed algorithm, which is verified by the No. 3 blast furnace radar data of Nanjing Iron and Steel. The target pixel brightness difference is reduced by 4.33 dB on average, and the object imaging is more uniform and clearer.

Key words: scattering characteristics, random rough surface, loss compensation, blast furnace burden surface imaging

CLC Number: 

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