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A platform for research: civil engineering, architecture and urbanism
Damage localization on reinforced concrete slab structure using electromechanical impedance technique and probability-weighted imaging algorithm
Abstract Damage localization plays a key role in structural damage identification and health monitoring. This paper proposed a new damage localization approach using electromechanical impedance/admittance (EMI/EMA) technique integrated with probability-weighted imaging algorithm based on Gaussian distribution. The proposed approach comprises five steps namely measurement of the EMA signature from an array of piezoelectric ceramic lead zirconate titanate (PZT) transducers, computation of statistic damage indicator, establishment of regression model for the indicator, damage visualization via Gaussian distribution and final damage localization. Experimental validation of the approach was conducted on a reinforced concrete (RC) slab with artificial crack damages detected by using an array of surface-bonded PZT patches. Comparative studies on localization accuracy were performed by utilizing root mean square deviation (RMSD), baseline-changeable RMSD namely RMSDk, mean absolute percentage deviation (MAPD) and correlation coefficient (CC). Experimental results demonstrated that the proposed approach could achieve precise localization of concrete crack with error as small as 0 mm, and that using RMSDk index exhibited the highest localization accuracy in average. The proposed approach promoted the capability of the EMI technique in characterization of concrete structural damages.
Highlights A new damage localization approach using electromechanical impedance technique. Probability-weighted imaging algorithm based on Gaussian distribution was introduced. Experimental validation of the approach on a reinforced concrete slab with crack damages. Comparative studies on localization accuracy were performed by different damage indicators. Baseline-changeable RMSD namely RMSDk exhibited the highest localization accuracy.
Damage localization on reinforced concrete slab structure using electromechanical impedance technique and probability-weighted imaging algorithm
Abstract Damage localization plays a key role in structural damage identification and health monitoring. This paper proposed a new damage localization approach using electromechanical impedance/admittance (EMI/EMA) technique integrated with probability-weighted imaging algorithm based on Gaussian distribution. The proposed approach comprises five steps namely measurement of the EMA signature from an array of piezoelectric ceramic lead zirconate titanate (PZT) transducers, computation of statistic damage indicator, establishment of regression model for the indicator, damage visualization via Gaussian distribution and final damage localization. Experimental validation of the approach was conducted on a reinforced concrete (RC) slab with artificial crack damages detected by using an array of surface-bonded PZT patches. Comparative studies on localization accuracy were performed by utilizing root mean square deviation (RMSD), baseline-changeable RMSD namely RMSDk, mean absolute percentage deviation (MAPD) and correlation coefficient (CC). Experimental results demonstrated that the proposed approach could achieve precise localization of concrete crack with error as small as 0 mm, and that using RMSDk index exhibited the highest localization accuracy in average. The proposed approach promoted the capability of the EMI technique in characterization of concrete structural damages.
Highlights A new damage localization approach using electromechanical impedance technique. Probability-weighted imaging algorithm based on Gaussian distribution was introduced. Experimental validation of the approach on a reinforced concrete slab with crack damages. Comparative studies on localization accuracy were performed by different damage indicators. Baseline-changeable RMSD namely RMSDk exhibited the highest localization accuracy.
Damage localization on reinforced concrete slab structure using electromechanical impedance technique and probability-weighted imaging algorithm
Ai, Demi (author) / Zhang, Duluan (author) / Zhu, Hongping (author)
2024-03-12
Article (Journal)
Electronic Resource
English
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