Journal of Chemistry and Chemical Research

During prolonged operation, chemical equipment is susceptible to corrosion media that cause structural degradation and failure, posing serious threats to industrial safety and production efficiency. Given the multi-factor coupling characteristics of corrosion-induced failures, developing a scientific safety life prediction model has become crucial for enhancing equipment reliability and safety. This study investigates corrosion mechanisms, failure mode identification, and predictive methodologies, proposing a framework that integrates multi-source data-driven approaches with physical mechanism modeling for life prediction. The proposed framework provides theoretical foundations and technical support for lifecycle management and risk control in chemical equipment systems.

Chemical equipment; Corrosion failure; Life prediction; Data-driven; Reliability assessment