Intelligent operation-oriented safety monitoring and fracture early warning method for structural nodes of polar ships

With the increasing frequency of Arctic shipping activities, structural safetyissues of polar ships operating in complex ice-covered environments have become increasinglycritical. To address this challenge, this study proposes an intelligent operation-orientedmethod for safety monitoring and fracture early warning of polar ship structural nodes. Based on ice load time-history data acquired from an onboard structural health monitoringsyst em, fatigue damage evolution and fracture risk analyses are carried out for typical nodes. Using the rainflow counting method combined with Miner’s linear cumulative damagetheory, the fatigue life of nodes is predicted, and results indicate that the foremost columnist he fatigue-susceptible component. Furthermore, by applying the modified Mohr–Coulombcriterion, the critical fracture strain under extreme ice loads is calculated, revealingthat t he crucial node exhibits a relatively high fracture risk. On this basis, a node safety assessment and fracture early warning framework is developed through the integration of real-time monitoring data. The proposed method provides state diagnosis and maintenance decision support for the intelligent operation and maintenance of polar ships, of ering practical si gnificance for enhancing their operational safety and reliability in Arctic navigation.