Preliminary Study on Estimating the High-temperature Particles Concentration from Smoke Images in Industrial Sites

¹ State Key Laboratory of Green Building, Xi’an University of Architecture and Technology, China
² School of Building Services Science and Engineering, Xi’an University of Architecture and Technology, China

^* Corresponding author: huangyanqiu@xauat.edu.cn

Abstract

Understanding the spatio-temporal variation of high-temperature particle concentration is crucial for refining ventilation systems during industrial operations. However, it is unlikely to apply existing particle concentration measurements to the above scenarios due to constraints and limitations at high temperatures. This study proposes a novel approach, the Estimation of Particle Concentration from Smoke Images (EPCSI), leveraging on-site smoke imagery and the qualitative Ringelmann smoke chart. The principles and post-processing of EPCSI were introduced in detail. Additionally, EPCSI is employed to analyze the spatiotemporal distribution of particle concentration during coke oven charging operations, both instantaneously and over time. The results show that the inter-frame difference method can accurately segment smoke from a pure background. The EPCSI can capture the transient development process, spatial distribution area, and period of particle concentration. During the coke oven charging, the concentration in different height sections follows a Gaussian distribution. The period of high concentration occurs 300 seconds after the charging starts. A promising tool was introduced for high-temperature particle concentration measurement and smoke control.