Sensor network based damage detection of structures using weight function in electromechanical impedance method

Shishir Singh; Rohan Soman; Pawel Malinowski

doi:10.1117/12.2612785

19 April 2022 Sensor network based damage detection of structures using weight function in electromechanical impedance method

Shishir Singh, Rohan Soman, Pawel Malinowski

Author Affiliations +

Proceedings Volume 12048, Health Monitoring of Structural and Biological Systems XVI; 1204813 (2022) https://doi.org/10.1117/12.2612785
Event: SPIE Smart Structures + Nondestructive Evaluation, 2022, Long Beach, California, United States

Abstract

The electromechanical impedance (EMI) method is a high frequency based local structural damage detection technique. The recent advances in sensor network study have led to study of direct-coupled mechanical impedance (DCMI) signals based damage indices using a modified probability weight function for damage imaging in the structure. Further, a novice fused data which combines the information of sensor resistance (R) and conductance (G) is also studied in robust damage detection in structural health monitoring (SHM) due to its capabilities of extracting multiple information. RMSD is the popular damage metrics in describing the behaviour of signal in damage quantification in the frequency domain based EMI method. This work implements a modified probability weight function using the optimal radius of sensing region for the large and small steps/intervals of radius. Further, a comparative damage imaging study done among F, DCMI and filtered detrend (FD) data based RMSD damage index. The proposed methodology is implemented for the glass fiber reinforced polymer (GFRP) composite material with impact damage.

Conference Presentation

Citation Download Citation

Shishir Singh, Rohan Soman, and Pawel Malinowski "Sensor network based damage detection of structures using weight function in electromechanical impedance method", Proc. SPIE 12048, Health Monitoring of Structural and Biological Systems XVI, 1204813 (19 April 2022); https://doi.org/10.1117/12.2612785

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