Crack identification using combined power flow and acceleration matching technique

Abstract

This article presents a multi-objective optimization (MO) formulation to detect cracks in structures using time-domain acceleration responses combined with power flow balance conditions. No additional sensors are required to ensure power flow balance. This is an application of inverse problem formulation whereby the unknown structural stiffnesses are estimated by minimizing the difference between the measured and theoretically predicted accelerations; simultaneously ensuring the net power flow balance in the substructure is zero. Numerical simulations are performed for identifying a lumped mass system and damage detection in a cantilever beam of 20 elements with single crack. Effects of noise are also taken into account by contaminating the measured responses with up to 5% Gaussian noise. The particle swarm approach is used as the optimization algorithm, and the objective function is defined to minimize the error with weighted contribution of both acceleration and power flow parameters. The effects of various weighting factors are studied. It is shown that significant improvement in accuracy of damage detection is achieved by the combined method, when compared to previous methods. The enhanced accuracy of identification could imply the use of fewer sensors for this method.