A Bayesian approach of structural health monitoring based on identified parameter from nondestructive test

Abstract

Structural health monitoring is important to assess the condition of existing structures, particularly to ensure efficient delivering of its functional utility with adequate safety. Visual inspection and non-destructive tests are existing practices to assess the structural health. But often the inference is drawn in a subjective manner based on the experts’ opinion. The uncertainties associated with the inspection data, model assumed and environmental variations are generally not properly addressed. A Bayesian approach is adopted to update the identified structural parameter associated with the non-destructive testing data. The subjective judgment based on intuition, experience or indirect information may be systematically incorporated with observed data to obtain a balanced estimation. The condition of the structure can be continuously updated with the advancement of inspection information as available. The structural health may be monitored at regular interval with the Bayesian updating. The proposed method is demonstrated with few practical examples of structural health monitoring using non-destructive test data.