PCA-Data Compression for Impedance-Based Wireless Structural Health Monitoring Framework

This paper presents a practical method for an electro-mechanical impedance-based wireless structural health monitoring (SHM) framework, which employs the principal component analysis (PCA)-based data compression. 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 electro-mechanical 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. The effectiveness of the proposed methods for a practical use of the electro-mechanical impedance-based wireless SHM was verified through an experimental study inspecting loose bolts in a bolt-jointed aluminum structure.