Life Prediction of Naval Gun Barrel Based on Multi-source Information Fusion

Abstract

The performance of naval gun barrel highly influences the operational lifespan. During the firing process, it is a quite challenge to predict the life of the naval gun due to many unknown factors in the complex physical and chemical reactions that occur in the barrel inner surface. This paper presents an optimized life prediction model which considers the information difference of ablative and fatigue life.The model consists of three modules, heat transfer simulation model, fatigue finite element model, and data fusion based on D-S evidence theory. The heat transfer simulation model and fatigue finite element model are established by simulating the firing process of a naval gun, and the life distribution is calculated. On this basis, a life prediction model is improved taking into account the variability of erosion and fatigue life data. The result shows that the established model can predict the life of the barrel more accurately and correctly judge the state of the body tube and improve the reliability of the naval gun.