Fuzzy Logic Applied to Damage Characterization through SHM Techniques

Fuzzy Logic is an Artificial Intelligence technique that is dedicated to the construction of meta-models based on the human comprehension of a specific phenomenon. When a person is capable to understand such a phenomenon, it is possible to determine the response of the plant based on subjective rules associated to the system under study. This contribution focus on the use of fuzzy logic techniques for damage prediction as applied to flat structures under corrosion conditions, by using a SHM (Structural Health Monitoring) approach, which is based on electro-mechanic impedance. Representative indexes for each technique are obtained and five different locations and two depths of corrosion are taken into account. Finally, a fuzzy based meta-model is built and used for prediction purposes when the signatures corresponding to impedance-based SHM technique are known. With this contribution the authors expect to demonstrate that in various cases of damage detection experimentation can be avoided or the number of tests can be reduced by the prior elaboration of fuzzy rules. For this aim, the appropriate knowledge of the structure is mandatory so that the fuzzy rules can be drawn accordingly.