Structural damage assessment under external loading, such as earthquake excitation, is an important issue in structural safety evaluation. In this regard, an appropriate data analysis and system identification technique is required to interpret the measured data and to identify the state of the structure. Generally, the recursive system identification algorithm is used. In this study, the recursive subspace identification (RSI) algorithm based on the matrix inversion lemma algorithm with oblique projection technique (RSI-Inversion-Oblique) is applied to investigate the time-varying dynamic characteristics. The user-defined parameters used in the RSI-Inversion-Oblique technique are carefully discussed, which include the size of the data Hankel matrix (i), model order to extract the physical modes, and forgetting factor (FF) to detect the time-varying system modal frequencies. Response data from the Northridge earthquake from the Sherman Oaks building (CSMIP) is used as an example to examine a systematic method to determine the suitable user-defined parameters in RSI. It is concluded that the number of rows in the data Hankel matrix significantly influences the identification of the time-varying fundamental modal frequency of the structure. An algorithmic model order selection method using the eigenvalue distribution of RSI-Inversion can detect the system modal frequencies at each appending data window without causing any abnormality.

The objective of this study is to design and validate distributed strain field monitoring using a patterned nanocomposite “sensing mesh” that is coupled with an electrical impedance tomography (EIT) measurement strategy and algorithm. Although EIT has been used in other studies and in conjunction with a piezoresistive thin film for spatial damage detection, different strain components cannot be directly extracted from reconstructed EIT conductivity maps. Therefore, this study seeks to address this issue by patterning piezoresistive graphene-based thin films to form a mesh-like pattern. The high aspect ratio of each nanocomposite grid interconnect acts as a linear distributed strain sensor, capable of resolving strains along the entire length and direction of the element. This study first began with the design, fabrication, and characterization of the strain sensing response of a graphene-based thin film of high strain sensitivity. Second, the strain-sensitive film was spray-coated onto patterned polymer substrates to form the sensing meshes, which were then subjected to load tests. Upon validating distributed strain field monitoring through EIT, its applicability for field implementation and damage characterization was also demonstrated by instrumenting sensing meshes in the column of a seven-story reinforced-concrete building subjected to shaking table earthquake excitations. The large-scale shaking table test results successfully validated distributed damage detection.

This study aims to validate a piezoelectric driven-rod scour monitoring system that can sense changes in scour depth along the entire rod at its instrumented location. The proposed sensor is a polymeric slender rod with a thin strip of polyvinylidene fluoride that runs through its midline. Extraction of the fundamental frequency allows the direct calculation of the exposed length (or scour depth) of the slender rod undergoing fluid flow excitation. First, laboratory validation in dry conditions is presented. Second, hydrodynamic testing of the sensor system in a soil-bed flume is discussed. Each rod was installed using a three-dimensional-printed footing designed for ease of installation and stabilization during testing. The sensors were installed in a layout designed to capture symmetric scour conditions around a scaled pier. In order to analyze the system out of steady-state conditions, water velocity was increased in stages during testing to induce different degrees of scour. As ambient water flow excited the portion of the exposed rods, the embedded piezoelectric element outputted a time-varying voltage signal. Different methods were then employed to extract the fundamental frequency of each rod, and the results were compared. Further testing was also performed to characterize the relationship between frequency outputs and flow velocity, which were previously thought to be independent. In general, the proposed driven-rod scour monitoring system successfully captured changing frequencies under varied flow conditions.