With the increasing frequency of Arctic shipping activities, structural safety issues of polar ships operating in complex ice-covered environments have become increasingly critical. To address this challenge, this study proposes an intelligent operation-oriented method 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 monitoring system, fatigue damage evolution and fracture risk analyses are carried out for typical nodes. Using the rainflow counting method combined with Miner’s linear cumulative damage theory, the fatigue life of nodes is predicted, and results indicate that the foremost column is the fatigue-susceptible component. Furthermore, by applying the modified Mohr–Coulomb criterion, the critical fracture strain under extreme ice loads is calculated, revealing that the 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, offering practical significance for enhancing their operational safety and reliability in Arctic navigation.