Abstract
The objective of this work is to develop a new structural health monitoring system for composite aerospace structures based on dynamic response strain measurements and experimental modal analysis techniques. Fiber Bragg grating (FBG) optical sensors were used for monitoring the dynamic response of the composite structure. The structural dynamic behavior has been numerically simulated and experimentally verified by means of vibration testing. The hypothesis of all vibration tests was that actual damage in composites reduces their stiffness and produces an eigenfrequency shifting to lower values in the same sense as mass increase produces. Thus, damage was simulated by slightly varying locally the mass of the structure at different zones. The correlation between the simulated damage and the loss of stiffness was analytically defined. Experimental modal analysis based on the strain responses was conducted and the extracted strain mode shapes were the input for the damage detection expert system. A feed-forward back propagation neural network was the core of the damage detection system. The features-input to the neural network consisted of the strain mode shapes, extracted from the experimental modal analysis. Dedicated training and validation activities were carried out based on the experimental results. The system showed high reliability, confirmed by the ability of the neural network to recognize the size and the position of damage on the structure. The experiments were performed on a real structure i.e. a lightweight antenna sub-reflector, manufactured and tested at EADS CASA ESPACIO. An integrated FBG sensor network, based on the advantage of multiplexing, was mounted on the structure with optimum topology. Numerical simulation was used as a support tool at all the steps of the work. Potential applications for the proposed system are during ground qualification extensive tests of space structures and during the mission as modal analysis tool on board, being able via the FBG responses to identify a potential failure.
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