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(a) Measurement setup, (b) aluminum defect Location 1, (c) aluminum defect Location 2, (d) carbon-fiber-reinforced polymer (CFRP) defect Location 1, and (e) CFRP defect Location 2.
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In this work, an approach for enabling miniaturized, low-voltage hardware for active structural health monitoring (SHM) based on ultrasonic guided waves is investigated. The proposed technique relies on S-parameter measurements instead of time-domain pulsing and thereby trades off longer measurement times with lower actuation voltages for improved...
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Citations
... Commonly used structural health monitoring methods include the acoustic emission method, electromechanical impedance method, Lamb wave method, etc. [6]. Lamb waves propagate in the measured structure with low signal attenuation, sensitivity to damage, and high accuracy, so the Lamb wave method is commonly used to image the damage of carbon fiber composite materials in monitoring [7,8]. The complex structure of carbon fiber composites and the dispersive, multimodal nature of Lamb waves lead to difficulty in obtaining accurate wave velocities, limiting the use of time-reversal imaging [9], time-delayed cumulative imaging [10], laminar imaging [11], phased array imaging, and other methods [12]. ...
Carbon fiber composites are commonly used in aerospace and other fields due to their excellent properties, and fatigue damage will occur in the process of service. Damage imaging can be performed using damage probability imaging methods to obtain the fatigue damage condition of carbon fiber composites. At present, the damage factor commonly used in the damage probability imaging algorithm has low contrast and poor anti-noise performance, which leads to artifacts in the imaging and misjudgment of the damaged area. Therefore, this paper proposes a fatigue damage probability imaging method for carbon fiber composite materials based on the sparse representation of Lamb wave signals. Based on constructing the Lamb wave dictionary, a fast block sparse Bayesian learning algorithm is used to represent the Lamb wave signals sparsely, and the definition of Lamb wave sparse representing the damage factor calculates the damage probability of the monitoring area and then images the fatigue damage of the carbon fiber composite materials. The imaging research was carried out using the fatigue monitoring experiment data of NASA’s carbon fiber composite materials. The results show that the proposed damage factor can clearly distinguish the damaged area from the undamaged area and has strong noise immunity. Compared with the energy damage factor and the cross-correlation damage factor, the error percentages are reduced by at least 58.63%, 28.11%, and 8.43% for signal-to-noise ratios of 6 dB, 3 dB, and 0.1 dB, respectively, after adding noise to the signal. The results can more accurately reflect the real location and area of fatigue damage in carbon fiber composites.
... In the last decades, numerous SHM methods have been proposed and were successfully tested on simple specimens relevant to aircraft design in laboratory environments [13][14][15][16][17][18]. Recently, scaled demonstrators equipped with multiple sensors have also been built to develop and test the applicability of promising SHM methodologies [19][20][21]. ...
An idealized 1:2 scale demonstrator and a numerical parameter optimization algorithm are proposed to closely reproduce the deformation shape and, thus, spatial strain directions of a real aerodynamically loaded civil aircraft spoiler using only four concentrated loads. Cost-efficient experimental studies on demonstrators of increasing complexity are required to transfer knowledge from coupons to full-scale structures and to build up confidence in novel structural health monitoring (SHM) technologies. Especially for testing novel sensor systems that depend on or are affected by mechanical strains, e.g., strain-based SHM methods, it is essential that the considered lab-scale structures reflect the strain states of the real structure at operational loading conditions. Finite element simulations with detailed models were performed for static strength analysis and for comparison to experimental measurements. The simulated and measured deformations and spatial strain directions of the idealized demonstrator correlated well with the numerical results of the real aircraft spoiler. Thus, using the developed idealized demonstrator, strain-based SHM systems can be tested under conditions that reflect operational aerodynamic pressure loads, while the test effort and costs are significantly reduced. Furthermore, the presented loading optimization algorithm can be easily adapted to mimic other pressure loads in plate-like structures to reproduce specific structural conditions.
Lightweight structures are optimized designs with minimal weight and with additional consideration of many boundary conditions. In different fields of engineering there are many reasons to reduce the weight of structures, e.g., to increase the payload of aircraft, to minimize the fuel consumption of vehicles, or to build larger bridges. However, an optimized design is usually accompanied by greater utilization of safety margins and thus increased susceptibility to fatal failures. By retaining the advantages of weight reduction structural health monitoring (SHM) promises to increase the operational safety of vehicles and buildings. SHM has been part of academic research for more than three decades, and yet there is no widespread commercial application of this technology.
In aerospace industry, structures are usually designed according to a building block approach that provides a hierarchical and structured development strategy (including numerical simulations and experimental tests) and is intended to ensure the quality and safety of newly built aircraft. In this thesis, such a building block approach is adopted for the development of SHM technology. The main objective is to provide a strategy to efficiently develop new sensors, measurement and evaluation methods to be used in reliable SHM systems. The proposed building block approach has a pyramidal shape, with a large number of models and experiments on the lowest layer and the validation of a well performing SHM system applied to a structure in-service on its peak. Essential to this strategy are idealized demonstrators. These representations (digital and/or physical objects) of in-service structures should be simplified to enable the investigation of a specific definable behavior of the structure. A sophisticated demonstrator provides an in-depth understanding of the functionality of applied sensors and SHM methods, i.e., boundary conditions, limitations, sensitivities and resolutions of adopted SHM technologies can be easily investigated.
The proposed approach to efficiently develop SHM technology is illustrated by double shear lugs and an idealized 1:2 scale spoiler demonstrator. The potential use of a SHM system is only given if there is a significant period of time in which damage (e.g., a crack) can grow under a given load without complete loss of structural integrity. Therefore, the damage tolerance of threaded connections and double shear lugs is investigated first by numerical simulations and experimental tests. A difference of 20 times the fatigue life was found for threaded connections with only slightly modified designs. Investigations on necked double shear lugs revealed a considerable crack propagation period in the range of 0.5% to 6% depending on the tested fatigue load level. Subsequently, the application of a small piezoelectric actor and sensor element was investigated to monitor the length of cracks in double shear lugs by the electro-mechanical impedance (EMI) method. The length of artificially introduced cracks in aircraft lugs could be estimated with a submillimeter error using a model-based approach. Finally, the full potential of the proposed building block approach is presented facilitating an idealized spoiler demonstrator, to develop a strain-based SHM method for an aircraft spoiler.
URL: https://resolver.obvsg.at/urn:nbn:at:at-ubl:1-53692
