Sensor Fault Diagnosis for Impedance Monitoring Using a Piezoelectric-Based Smart Interface Technique

Abstract

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 impedance-based SHM using the piezoelectric interface technique. Firstly, the piezoelectric interface-based 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 interface-driven 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 shear-lag 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.

Piezoelectric Sensor-Embedded Smart Rock for Damage Monitoring in a Prestressed Anchorage Zone

“…For the 3-DOF impedance model, the governing equation of the motion under a harmonic excitation F p at the PZT driving point can be formulated as the following: where ; ; and are the accelerations, the velocities, and the displacements corresponding to the motions of masses m p , m r , and m s , respectively. The coupling structural–mechanical (SM) impedance, the Z s of the protected layer, the concrete block, and the host structure are determined as follows [ 36 ]: where the terms K mn ( m,n = 1–3) are the dynamic stiffness coefficients that contain the structural parameters of the protective layer, the concrete block, and the monitored structure [ 36 ].…”

Bolt-Loosening Monitoring Framework Using an Image-Based Deep Learning and Graphical Model

“…While the sensor-based SHM often requires expensive data acquisition systems [ 8 , 9 , 10 , 11 , 12 , 13 ], the vision-based approach requires only simple and low-cost setup and operation. Besides this, vision sensors are non-contact, while traditional sensors must be contacted to a target structure, causing degradations in the sensor’s quality under environmental effects [ 14 , 15 ]. Furthermore, the structural information obtained from a vision sensor is not affected by environmental variation, while the signals obtained from a contacted sensor can be significantly affected by environmental changes, which is the main cause of false detections [ 16 , 17 , 18 , 19 ].…”

Piezoelectric Transducer-Based Diagnostic System for Composite Structure Health Monitoring

“…Schematic representation of boundary conditions is presented in Figure 4 a. The application of piezoelectric sensors in damages or different type of defect detection was used by other authors [ 20 , 21 , 31 ]; as for a structural health monitoring (SHM) system, this method is of great significance [ 32 ].…”