This manuscript investigates one way sound propagation in Magnetorheological fluids (MRF) using spatio-temporal modulation of the applied magnetic field. One-way propagation of waves in a structure can have potential technological applications such as sound isolation, filtering and echo suppression. Several experimental works in the literature have shown that elastic properties of MRF’s (local speed of sound, in particular) are dependent on the applied magnetic field. Therefore, several fascinating possibilities regarding the manipulation of sound waves in MRF, by tailoring the applied magnetic field, exist. A effective medium approximation (previously used in literature) is used to analyze sound propagation in a MRF composed of hydrogen-reduced Iron particles suspended in pure glycerine. Floquet-Bloch theory is used to obtain a quadratic eigenvalue problem that gives the band structure as a function of the material and modulation parameters. When the applied magnetic field is allowed to vary only in space, regular bandgaps are obtained as a result of Bragg scattering. In contrast, the temporal variation of the magnetic field to induce a traveling wave like variation of the modulated parameters, breaks the symmetry of the Brilloouin zones and we obtain directional bandgaps. The theoretical band structure is validated by numerical band diagrams obtained using a Finite Element code. This research has important applications in active sound manipulation.

This paper presents the investigation of piezo-optical active sensing methodology for structural health monitoring (SHM). Piezoelectric wafer active sensors (PWAS) have emerged as one of the major structural health monitoring (SHM) technology; with the same installation of PWAS transducers, one can apply a variety of damage detection methods; propagating acousto-ultrasonic waves, standing waves (electromechanical impedance) and phased arrays. In recent years, fiber Bragg gratings (FBG) sensors have been investigated as an alternative to piezoelectric sensors for the detection of ultrasonic waves. FBG have the advantage of being durable, lightweight, and easily embeddable into composite structures as well as being immune to electromagnetic interference and optically multiplexed. In this paper, the investigation focused on the interaction of PWAS and FBG sensors with structure, and combining multiple monitoring and interrogation methods (AE, pitch-catch, pulse-echo, phased-array, thickness mode, electromechanical impedance). The innovative piezo-optical active sensing system consists of both active and passive sensing. PWAS and FBG sensors are bonded to the surface of the structure, or are integrated into structure by manufacturing process. The optimum PWAS size and excitation frequency for energy transfer was determined. The FBG sensors parameters (size, spectrum, reflectivity, etc.) for ultrasonic guided waves sensing were also evaluated. We focused on the optimum FBG length and design to improve the sensitivity, coverage, and signal to noise ratio. In this research, we built the fundamental understanding of different sensors with optimum placement. Calibration and performance improvements for the optical interrogation system are also discussed. The paper ends with conclusions and suggestions for further work.

Embedded smart actuators/sensors, such as piezoelectric types, have been used to conduct wave transmission and reception, pulse-echo, pitch-catch, and phased array functions in order to achieve in-situ nondestructive evaluation for different structures. By comparing to baseline signatures, the damage location, amount, and type can be determined. Typically, this methodology does not require analytical structural models and interrogation algorithm is carefully designed with little wave propagation knowledge of the structure. However, the wave excitation frequency, waveform, and other signal characteristics must be comprehensively considered to effectively conduct diagnosis of incipient forms of damage. Accurate prediction of high frequency wave response requires a prohibitively large number of conventional finite elements in the structural model. A new high fidelity approach is needed to capture high frequency wave propagations in a structure. In this paper, a spectral finite element method (SFEM) is proposed to characterize wave propagations in a beam structure under piezoelectric material (i.e., PZT) actuation/sensing. Mathematical models are developed to account for both Uni-morph and bi-morph configurations, in which PZT layers are modeled as either an actuator or a sensor. The Timoshenko beam theory is adopted to accommodate high frequency wave propagations, i.e., 20–200 KHz. The PZT layer is modeled as a Timoshenko beam as well. Corresponding displacement compatibility conditions are applied at interfaces. Finally, a set of fully coupled governing equations and associated boundary conditions are obtained when applying the Hamilton’s principle. These electro-mechanical coupled equations are solved in the frequency domain. Then, analytical solutions are used to formulate the spectral finite element model. Very few spectral finite elements are required to accurately capture the wave propagation in the beam because the shape functions are duplicated from exact solutions. Both symmetric and antisymmetric mode of lamb waves can be generated using bimorph or uni-morph actuation. Comprehensive simulations are conducted to determine the beam wave propagation responses. It is shown that the PZT sensor can pick up the reflected waves from beam boundaries and damages. Parametric studies are conducted as well to determine the optimal actuation frequency and sensor sensitivity. Such information helps us to fundamentally understand wave propagations in a beam structure under PZT actuation and sensing. Our SFEM predictions are validated by the results in the literature.

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 (pitch-catch 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.

We present a novel approach for optimal actuator and sensor placement for active sensing-based structural health monitoring (SHM). Of particular interest is the optimization of actuator-sensor arrays making use of Lamb wave propagation for detecting damage in thin plate-like structures. Using a detection theory framework, we establish the optimum configuration as the minimization of the expected percentage of the structure to show type I or type II error during the damage detection process. The detector incorporates a statistical model of the active sensing process which implements both pulse-echo and pitch-catch actuation schemes and takes into account line of site and non-uniform damage probabilities. The optimization space was searched using a genetic algorithm with a time varying mutation rate. We provide four example actuator/sensor placement scenarios and the optimal solutions as generated by the algorithm.