As the “flagship” unit of the petrochemical industry, the operational status of ethylene cracking furnaces directly impacts the stability and efficiency of the entire production chain. During long-term operation under extreme temperatures and complex reaction environments, cracking furnace tubes face core bottlenecks primarily related to thermal and coking effects, such as coke deposition, tube metal overheating, and associated creep damage, which restrict the long-term, safe, and efficient operation of the unit. This paper systematically reviews the key technologies for condition monitoring of cracking furnace tubes, providing an in-depth analysis of various monitoring methods—from traditional infrared thermometry and acoustic emission to emerging optical fiber sensing—covering their working principles, application status, and inherent limitations. Furthermore, it elaborates on the evolution from mechanism-based “white-box” models to data-driven “black-box” models, and further to “gray-box” intelligent diagnostic models that integrate expert knowledge. Industrial application cases of integrated monitoring and diagnostic systems are also introduced. Finally, the paper critically addresses the current severe challenges in data fusion, model generalization, real-time performance, and cost-effectiveness, while outlining future development trends toward digital twins, cross-modal fusion, edge intelligence, and self-evolving systems. The aim is to provide valuable references for technological innovation and engineering applications in this field.
Ren et al. (Mon,) studied this question.