A new damage identification approach based on impedance-type measurements and 2D error statistics

Abstract

The electro-mechanical impedance (EMI) technique makes use of surface-bonded lead zirconate titanate (PZT) patches as impedance transducers measuring impedance variations monitored on host structural components. The present experimental work further evaluate an alternative to the conventional EMI technique which performs measurements of the variations in the output voltage of PZT transducers rather than computing electromechanical impedance (or admittance) itself. This paper further evaluates a variant of the EMI approach presented in a previous work of the present authors, suitable, for low-cost concrete structures monitoring applications making use of a credit card-sized Raspberry Pi single board computer as core hardware unit. This monitoring approach is also deployed by introducing a new damage identification index based on the ratio between the area of the 2-D error ellipse of specific probability of EMI-based measurements containment over that of the 2-D error circle of equivalent probability. Experimental results of damages occurring in concrete cubic and beam specimens are investigated under increasing loading conditions. Results illustrate that the proposed technique is an efficient approach for identification and early detection of damage in concrete structures.

Residual Force Method for damage identification in a laminated composite plate with different boundary conditions

“…Wand et al [4] Suggested a neural network technique for damage identification refinement in the case of a suspension bridge. And Providakis et al [5] used impedance-type measurements and error statistics to present a new damage identification approach in composite structures. Vahedian et al [6] considered the case of multi-storey timber buildings and presented an improvement on the damage assessment by SFRP.…”

Structural damage identification based on gray cloud rule generator algorithm

“…However, the uncertain damage identification method based on probability and statistics focus on the nature of uncertainty of the damage problems 2 such as structural damage detection following the Bayesian approach and the statistics theory. 3 It is still necessary to utilize dynamic characteristics in the uncertain damage identification method.…”

“…. The material properties of the structure are as follows: r = 2800 kg/ m3 , E = 72 GPa, and A = 0.001 m 2 . The truss model consists of 31 bar elements, 14 nodes, and 25 degrees of freedom.…”