Adaptive Tikhonov regularization for damage detection based on nonlinear model updating

摘要: This paper presents an adaptive regularization approach for solving the nonlinear model updating inverse problem. The discrimination of possible damaged elements and undamaged is done from results obtained in previous iterations via a new side condition which aims at (a) to limit local change structural each iteration; (b) force variation other close zero. A thirty-one bar plane truss structure with multiple damages studied. Results proposed method are greatly improved over those traditional Tikhonov even large noise contamination measurements.