A novel method for impact force estimation in composite plates under simulated environmental and operational conditions

Abstract

Abstract During its lifetime, an aircraft structure is subjected to various impacts from various sources such as tool drops, hail, ground service equipment, etc. In modern composite structures, these impacts have a significant chance of generating barely visible damage (BVID) which may lead to catastrophic failure of a structure if left undetected to grow. However, BVID is difficult to detect during routine visual inspection without specialised non-destructive inspection and thus there is large interest in developing monitoring systems for estimating the location and severity of impact events. Currently, most systems and methods have been developed for controlled lab conditions and do not consider the wide range of impact parameters in real life operation (environmental conditions, vibration, impactor stiffness, angle, etc) which may severely compromise the accuracy of these methods. In this study we have explored two methods for maximum impact force estimation, deconvolution and a novel gradient method, for the purpose of reliable severity assessment in composite aircraft structures under simulated environmental and operational conditions. It is shown that both methods allow accurate and robust estimation of the maximum impact force from various cases of impacts (variation of impact energy, mass, stiffness, angle, temperature, source) using minimum initial data from a single impact case. From further testing it is demonstrated that the gradient method is robust towards the effects of impact localisation errors and noise. The gradient method also has much less computational and storage requirements and is thus more feasible to integrate with current data acquisition systems being developed for structural health monitoring. Thus, we conclude that the proposed gradient method is suitable for impact force monitoring and severity assessment in composite aircraft structures in the simulated environmental and operational conditions.