A damage classification technique for impedance-based health monitoring of helicopter blades

One of the most sensitive problems regarding the application of SHM (Structural Health Monitoring) is found in the aeronautical segment. This field presents the necessity of monitoring small structural changes representing damage, due both to economic aspects and safety. In this contribution two helicopter blade structures (pertaining to a civil and a military helicopter) are studied. In both cases, two types of damage are inserted, namely holes and cracks. Through the impedance-based structural health monitoring method, an identification procedure using cluster analysis techniques was performed aiming at distinguishing these two types of damage. Then, a meta-model based on a probabilistic neural network was built for fault position identification.

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