Identification of corrosion factors in blast furnace gas pipe network with corrosion big data online monitoring technology

Abstract

To mitigate the accelerated corrosion of blast furnace gas pipelines induced by severe environmental conditions, this study has established an extensive high-throughput sensor system in the field. It leverages corrosion big data technology to investigate the corrosion factors affecting industrial gas pipelines and to precisely analyze the influence of related variables. The results indicated that temperature reduction is the driving factor that causes increased pipeline corrosion. On one hand, temperature fluctuations impact the evaporation and condensation of moisture in the tube. On the other hand, temperature fluctuations, in conjunction with corrosive gases, exhibit significant coupling effects, resulting in more severe corrosion. In addition, critical points for relative humidity and temperature are evident. When humidity exceeds 50%, corrosion in the pipe begins to increase, reaching its peak at 70%. The increase in temperature has a slowing effect on pipeline corrosion, reaching a peak value at 40°C. The response of corrosion rate to the concentration of corrosive gases follows a linear pattern. Based on these observations, we propose an effective corrosion control scheme.