A WeighinMotion Characterization Algorithm for Smart Pavements Based on Conductive Cementitious Materials Smart materials are promising technologies for reducing the instrumentation cost required to continuously monitor road infrastructures, by transforming roadways into multifunctional elements capable of selfsensing. This study investigates a novel algorithm empowering smart pavements with weighinmotion (WIM) characterization capabilities. The application domain of interest is a cementitiousbased smart pavement installed on a bridge over separate sections. Each section transduces axial strain provoked by the passage of a vehicle into a measurable change in electrical resistance arising from the piezoresistive effect of the smart material. The WIM characterization algorithm is as follows. First, basis signals from axles are generated from a finite element model of the structure equipped with the smart pavement and subjected to given vehicle loads. Second, the measured signal is matched by finding the number and weights of appropriate basis signals that would minimize the error between the numerical and measured signals, yielding information on the vehiclexe2x80x99s number of axles and weight per axle, therefore enabling vehicle classification capabilities. Third, the temporal correlation of the measured signals are compared across smart pavement sections to determine the vehicle weight. The proposed algorithm is validated numerically using three types of trucks defined by the Eurocodes. Results demonstrate the capability of the algorithm at conducting WIM characterization, even when two different trucks are driving in different directions across the same pavement sections. Then, a noise study is conducted, and the results conclude that a given smart pavement section operating with less than 5% noise on measurements could yield good WIM characterization results.

Sensor Fault Diagnosis for Impedance Monitoring Using a PiezoelectricBased Smart Interface Technique For a structural health monitoring (SHM) system, the operational functionality of sensors is critical for successful implementation of a damage identification process. This study presents experimental and analytical investigations on sensor fault diagnosis for impedancebased SHM using the piezoelectric interface technique. Firstly, the piezoelectric interfacebased impedance monitoring is experimentally conducted on a steel bolted connection to investigate the effect of structural damage and sensor defect on electromechanical (EM) impedance responses. Based on the experimental analysis, sensor diagnostic approaches using EM impedance features are designed to distinguish the sensor defect from the structural damage. Next, a novel impedance model of the piezoelectric interfacedriven system is proposed for the analytical investigation of sensor fault diagnosis. Various parameters are introduced into the EM impedance formulation to model the effect of shearlag phenomenon, sensor breakage, sensor debonding, and structural damage. Finally, the proposed impedance model is used to analytically estimate the change in EM impedance responses induced by the structural damage and the sensor defect. The analytical results are found to be consistent with experimental observations, thus evidencing the feasibility of the novel impedance model for sensor diagnosis and structural integrity assessment. The study is expected to provide theoretical and experimental foundations for impedance monitoring practices, using the piezoelectric interface technique, with the existence of sensor faults.