Identification of Corrosion Factors in Blast Furnace Gas Pipe Network with Corrosion Big Data Online Monitoring Technology
Authors: Liu Chao , Wang Bingqin , Cheng Xuequn , Li Xiaogang 
Published: December 2024

The production of blast furnace gas plays a crucial role in steel manufacturing, as the processing of raw materials can result in the generation of potentially harmful substances such as benzene, toluene, and xylene, known for their toxicity and carcinogenic properties. Moreover, blast furnace gas, primarily composed of harmful gases like SO2, reacts with moisture to form a highly acidic corrosive solution, hastening the corrosion of pipeline materials upon contact.

To mitigate the accelerated corrosion of blast furnace gas pipelines due to adverse environmental conditions, this study developed a high-throughput sensor system. Leveraging big data technology and the Internet of Things (IoT), we achieved real-time corrosion monitoring and rapid analysis of influential factors. The research followed a threefold approach: Firstly, we conducted field tests using an advanced corrosion electrochemical sensing system alongside six environmental sensors. This method effectively addressed issues related to data continuity, stability, and comprehensiveness. Secondly, we identified the most effective machine learning models and delved deeper into the data using them, along with data analysis techniques such as Spearman correlation analysis and partial dependency analysis. This allowed for a thorough exploration and interpretation of the large-scale corrosion data collected. Subsequently, we performed simulated condensate corrosion tests to comprehensively evaluate how environmental fluctuations in various states affect pipeline material corrosion.

The study findings reveal that temperature reduction is the primary factor driving increased pipeline corrosion. Temperature fluctuations impact water evaporation and condensation within the tube, exhibiting a high negative correlation with relative humidity (-0.92). Additionally, temperature fluctuations, combined with corrosive gases, result in significant coupling effects, leading to more severe corrosion. Furthermore, the study determined the dose-response relationship between relative humidity, temperature, and corrosion, identifying critical points. Corrosion intensifies when humidity exceeds 50%, peaking at 70%, while rising temperature initially slows down corrosion, peaking at 40°C. However, further temperature increases do not continue to mitigate corrosion. Conversely, the relationship between corrosive gas concentration and corrosion rate follows a linear pattern.

These observations underscore the significant enhancement in proactive management of blast furnace gas piping corrosion through advanced sensor technology and comprehensive corrosion data analysis. The proposed data-driven corrosion failure analysis method offers several advantages: (i) Enhanced data continuity with high-frequency data collection capabilities at one-minute intervals, enabling real-time insight into corrosion conditions and subtle changes that traditional methods might overlook. (ii) Comprehensive environmental data collection, including temperature, humidity, and gas concentrations, facilitating multidimensional correlation analysis and a deeper understanding of corrosion phenomena. (iii) Leveraging IoT for timely collection, transmission, and analysis of pipeline corrosion data, thereby improving the timeliness of corrosion control measures.

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