Depolarization diagnosis of PWAS used for EMI based structural health monitoring system for composite plates

Document Type : Original Article

Authors

1 Assoc. Prof., Civil Eng. Dep., Military Technical College, Egypt.

2 Msc, Civil Eng. Dep., Military Technical College, Egypt.

10.1088/1757-899X/610/1/012018

Abstract

Implementation of Electromechanical Impedance (EMI) as a technique to carry out Structural Health Monitoring (SHM) has been proved to be such effective tool in the last two decades, especially for structures made of composite material. EMI technique is the revolutionary evolution of the conventional Vibrational Based Damage Identification (VBDI) techniques. Unlike VBDI techniques, EMI technique has the privilege of employment tinny permanent piece of equipment which is known as Piezoelectric Wafer Active Sensor (PWAS). Although it has such advantage, it brings the necessity of continuous and robust diagnosis process of the PWAS used in the SHM system to ensure that output signals are caused by real variation of the modal parameters for the host structure rather than being occurred due to degradation and-or physical damage of the PWAS system itself. The study presented in this paper is focused on the self-diagnosis of PWAS used to carry out SHM via implementation of EMI technique. The main concern of this research is to study the ability of EMI technique to determine depolarization of PWAS and its influence on the performance of EMI based SHM system employed for structures made of composite plates. The used specimen (s) is / are underwent controlled excitation over desired frequency range, the imaginary part of admittance is plotted over desired frequency range. The whole process is then repeated for different levels of depolarization for the same specimen (s). The modeling process is carried out using a finite element commercial package, ANSYS v.15.0 in which multi-physics-based modeling can be used for such coupling field of piezoelectricity. MATLAB code is written to process the output data received from numerical simulations into counterpart spectrum and to calculate the statistical damage index Root Mean Square deviation (RMSD) that is used in damage detection. The calculated RMSD found to be non-zero values, which means false prediction. These results shows how important to have self-diagnosis for PAWS used in SHM system for further reliable measurements and data interrogation using EMI technique.

Keywords

International Conference on Aerospace Sciences and Aviation Technology
Volume 18, Issue 18
18th International Conference on Aerospace Sciences & Aviation Technology 9–11 April 2019
April 2019
Pages 1-11

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