Influence of Sensor Statistics on Piezoelectric and Magneto-Elastic Damage Detection (original) (raw)
2012, Volume 1: Development and Characterization of Multifunctional Materials; Modeling, Simulation and Control of Adaptive Systems; Structural Health Monitoring
Increasing complexity of aerospace structures facilitates a growing need for structural health monitoring (SHM) systems capable of real-time active damage detection. A variety of sensing approaches have been demonstrated using embedded ultrasonic sensors such as piezoelectric wafer active sensors (PWAS) and magneto-elastic active sensors (MEAS). Common methodologies consider wave propagation (pitchcatch or pulse-echo) and standing wave (vibration or impedance) techniques with damage detection capabilities dependent upon structural geometry, material characteristics, distance to damage and damage size/orientation. While recent studies have employed damage detection and classification approaches that are dependent on cumulative statistics, this study explores the contribution of sensor parameters and experimental setup variability on the damage detection scheme. The impact of variability in PWAS and MEAS are considered on sensor use in ultrasonic and magneto-mechanical impedance damage detection. In order to isolate sensor parameters, measurements were conducted with PWAS in free-free boundary conditions. Variability of PWAS parameters was evaluated by measuring the sensors impedance response. An analytical model of PWAS was used to estimate sensor parameters and to determine their variability. Additionally, experiments using MEAS were performed that demonstrate variation of magneto-mechanical impedance during structural dynamic tests. From these experiments the importance of sensor setup is discussed and its contribution into the overall detection scheme is explored.
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