A Dynamic Dual Stiffness Sensor in Helicopter Health and Usage Monitoring

New sensors have the potential to bring about a radical improvement in prognostics and diagnostics of structures. This improvement leads to a reduction in maintenance costs and an improvement in the reliability of health and usage monitoring systems. The dual stiffness sensor proposes a new sensing idea, involving the implementation of nano-physics in macro structures. The idea of a mechanical multi-functional dual-stiffness sensor for in-situ real-time stiffness and energy density measurements, developed at the University of Maryland is motivated by Eshelby’s equivalent inclusion theorem. The present study shows the possibility of using the sensor to determine the stiffness of a the local area of a host material under dynamic loading conditions. Damaged structures are characterized by a reduction in their elastic stiffness. This reduction in stiffness evolves from microstructural defects. A local smart sensor can be developed to sense the local average properties on a host. In this paper, sensors are attached to a structure and a modified Eshelby’s equivalent inclusion method is used to derive the elastic properties of the host. An analytical derivation and a sensitivity analysis for the quasistatic application are given in papers by Majed, Dasgupta, Kelah and Pines. A summary of the derivation of the dynamic Eshelby tensor for the dynamic application is presented in this paper. This is of importance because damage detection in structures undergoing vibratory motion presents a greater challenge than those in quasistatic motion. An in-situ health monitoring active sensor system for an aluminum beam under fatigue loading conditions is developed. The detection of the onset of any damage to the structure and the subsequent monitoring of the growth of this damage constitute important goals of the system. Both experimental and numerical methods were applied.