Damage Detection Using Flexibility Proportional Coordinate Modal Assurance Criterion
In the recent years, vibration-based identification techniques have attracted the attention of the civil engineering community, as these methods can be naturally incorporated into automated continuous structural health monitoring procedures. It is a generally accepted approach to model the damage and deterioration of a structural element through stiffness reduction. For this reason, a feature tailored so as to be well correlated to the expected differences between the undamaged and damaged flexibility matrices, such as the recently proposed Flexibility Proportional Coordinate Modal Assurance Criterion (FPCOMAC), is ideally suited to be exploited as damage sensitive feature. We present a statistical pattern recognition based damage detection method that employs FPCOMAC as damage sensitive feature. The proposed methodology is executed according to the training and testing phases typical of the pattern recognition framework. Particular effort is devoted to test the ability of the method to correctly identify the damage when response time histories used in the training are measured in different environmental conditions. The formulation is derived considering a shear-type structural system. Results obtained by considering a 7 DOFs shear-type system prove the efficiency of the method in detecting and locating the damage, irrespective of damage severity and environmental effects, under the conditions that the damage amount is greater than the structural variations caused by the external factors and the amount of data is reasonably large.
KeywordsStatistical pattern recognition Structural damage detection FPCOMAC
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