Numerical and experimental study of circular disc electromechanical impedance spectroscopy signature changes due to structural damage and sensor degradation

Abstract

The article describes a study on the use of the electromechanical impedance spectroscopy method for crack-damage detection with piezoelectric wafer active sensors bonded to thin-walled structures. The study combines analytical, finite element method, and experimental methods. The specimens under consideration consisted of circular plates with circular piezoelectric wafer active sensors bonded at the center. Some of the plates were pristine, and others were damaged. The damage consists of simulated cracks (thin laser-machined slits) placed at various locations away from the center. For pristine plates, the electromechanical impedance spectroscopy spectrum was predicted with two numerical methods: (a) analytically using closed-form solutions and (b) Comsol 4.3 Multi-physics software using two-dimensional axisymmetric elements. The results were compared with experimental measurements performed with an HP 4194 impedance analyzer. This comparison allowed us to tune the model parameters. For plates with simulated cracks, the electromechanical impedance spectroscopy spectrum was predicted with three-dimensional finite element method models and then compared with experiments. Overall, the effect of crack damage on electromechanical impedance spectroscopy signature was found to consist of frequency shifts, peak splitting, and appearance of new peaks. These effects were predicted by the numerical models and confirmed by experiments. Modeshapes were also measured using a scanning laser Doppler vibrometer and compared with finite element method predictions. Interesting new modeshape features (local high-frequency modes) were observed near the crack. These features tend to explain some of the new peaks appearing in the electromechanical impedance spectroscopy spectrum. Further refining of the finite element method model was performed to capture variability effects associated with plate thickness, piezoelectric wafer active sensors thickness, adhesive layer thickness, and imperfect adhesive layer. The effect on the piezoelectric wafer active sensors asymmetrically placed electrodes and soldering points was also studied. It was found that these variations modify the electromechanical impedance spectroscopy signatures, but much less than the changes induced by the presence of the crack. Hence, it was concluded that the capability of the electromechanical impedance spectroscopy method to detect actual damage was not affected by these variations. A proper physics-based analysis and interpretation of the electromechanical impedance spectroscopy spectral changes are performed.

New results concerning structural health monitoring technology qualification for transfer to space vehicles

“…The analytic models, which are easy to apply for the pristine DS, and the numerical models, which provide solutions for the damaged specimens, fit well with the experimental records in terms of both the resonance frequency values and the resonance peaks. [11,19] Thus, Table 2 [21] shows that the theoretically (analytically) determined resonance frequencies (noted by ν t ), including both flexural and axial, are confirmed by the experimental results corresponding to the pristine specimens (noted with ν exp1 ) and the specimens with the damage arcs at 7 mm (ν exp2 ). The frequency values obtained using the experimental methods are close to the theoretical ones.…”

“…[1] To detect the damage and to monitor the health of the structure, numerous sensing and methodology paradigms have been developed in recent years including fibre optic sensors, [2,3] active and passive acoustic sensors, [4][5][6] microelectromechanical systems (MEMS), [7] wireless sensor systems, [8] vibration-based method, [9] and the electromechanical impedance spectroscopy (EMIS) method. [10][11][12] However, a quick foray into the technical literature reveals that very few references are dedicated to space applications of Structure Health Monitoring technologies. [4,5,[13][14][15][16] The importance of the SHM methodology in space disaster prevention is carefully discussed in the paper [14] through an analysis of the Space Shuttle Columbia disaster.…”

Qualification of PWAS-Based SHM Technology for Space Applications

“…These travel along the mechanical structure, are reflected by different structural abnormalities, or boundary edges, and they are recaptured by the same sensor in a pulse-echo configuration or by other sensors of same or different type, even passive sensors, and in pitch-catch configuration. If the structural damage or boundary edges are in the close vicinity of the active sensor, their reflections overlap the incident transient wave, and making impossible the interpretation [14]. One of the active SHM sensing techniques is based on standing waves, in the so-called EMIS method; by sweeping the frequency of the input signals to PWAS, some changes appear in the impedance measured by an impedance analyzer connected to the PWAS terminals.…”

“…The EMIS method uses PWAS high-frequency active sensors and bonded to the structure. The presence of damage in a neighboring zone of the sensor is signaled as its EMIS "signature," respectively, as a modification of the electromagnetic impedance spectrum Z (ω), recorded and online processed, and in principle [10][11][12][13][14]. The pioneering work on using EMIS in SHM technology is considered [10] (see [11]).…”

“…The sensors used to damage detection belong to a wide range, such as optical fiber sensors [2,3], acoustic active and passive sensors [4][5][6], microelectromechanical systems (MEMS) [7], and wireless sensor systems [8]. The basic SHM methods are the method based on a modal modification of structure dynamic vibrations in a relatively low-frequency register [9] and the electromechanical method of impedance spectroscopy (EMIS) in the high-frequency register, using the active piezo sensors [10][11][12][13][14]. It should be added that SHM methodology has been strongly related during its development to predictive maintenance [15] and fault detection [16] techniques due to safety demands in all areas of activity, especially in aerospace applications, chemical industry, nuclear power plants, and so on.…”