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This article presents a practical method for an electro-mechanical impedancebased wireless structural health monitoring (SHM), which incorporates the principal component analysis (PCA)-based data compression and k-means clustering-based pattern recognition. An on-board active sensor system, which consists of a miniaturized impedance measuring chip (AD5933) and a self-sensing macro-fiber composite (MFC) patch, is utilized as a next-generation toolkit of the electromechanical impedance-based SHM system. The PCA algorithm is applied to the raw impedance data obtained from the MFC patch to enhance a local data analysis-capability of the on-board active sensor system, maintaining the essential vibration characteristics and eliminating the unwanted noises through the data compression. Then, the root-mean square-deviation (RMSD)-based damage detection result using the PCA-compressed impedances is compared with the result obtained from the raw impedance data without the PCA preprocessing. Furthermore, the k-means clustering-based unsupervised pattern recognition, employing only two principal components, is implemented. The effectiveness of the proposed methods for a practical use of the electromechanical impedance-based wireless SHM is verified through an experimental study consisting of inspecting loose bolts in a bolt-jointed aluminum structure.

This paper presents the results of experimental studies on piezoelectric lead-zirconate-titanate (PZT)-based active damage detection techniques for nondestructive evaluations (NDE) of steel bridge components. PZT patches offer special features suitable for real-time in situ health monitoring systems for large and complex steel structures, because they are small, light, cheap, and useful as built-in sensor systems. Both impedance and Lamb wave methods are considered for damage detection of lab-size steel bridge members. Several damage-sensitive features are extracted: root mean square deviations (RMSD) in the impedances and wavelet coefficients (WC) of Lamb waves, and the times of flight (TOF) of Lamb waves. Advanced signal processing and pattern recognition techniques such as continuous wavelet transform (CWT) and support vector machine (SVM) are used in the current system. Firstly, PZT patches were used in conjunction with the impedance and Lamb waves to detect the presence and growth of artificial cracks on a 1/8 scale model for a vertical truss member of Seongsu Bridge, Seoul, Korea, which collapsed in 1994. The RMSD in the impedances and WC of Lamb waves were found to be good damage indicators. Secondly, two PZT patches were used to detect damage on a bolt-jointed steel plate, which was simulated by removing bolts. The correlation of the Lamb wave transmission data with the damage classified by in and out of the wave path was investigated by using the TOF and WC obtained from the Lamb wave signals. The SVM was implemented to enhance the damage identification capability of the current system. The results from the experiments showed the validity of the proposed methods.

The active sensing methods using piezoelectric materials have been extensively investigated for the efficient use in structural health monitoring (SHM) applications. Relying on high frequency structural excitations, the methods showed the extreme sensitivity to minor defects in a structure. Recently, a sensor self-diagnostic procedure that performs in situ monitoring of the operational status of piezoelectric (PZT) active sensors and actuators in SHM applications has been proposed. In this investigation, previously developed impedance models were revisited in order to investigate the effects of sensor and/or bonding defects on the admittance measurement. New parameters for sensor quality assessment of a PZT and coupling degradation effects between a PZT and bonding layer were incorporated into the traditional electromechanical impedance model for better estimation of the electromechanical impedance signatures and sensor diagnostics. The feasibility of the modified impedance model for sensor self-diagnosis using the admittance measurements was demonstrated by a series of parametric studies using a simple example of PZT-driven single degree of freedom spring-mass-damper system. This paper summarizes the description of the proposed modified electromechanical impedance model, parametric studies for impedance-based sensor diagnostics, and several issues that can be used as a guideline for future investigation.