A literature review of next-generation smart sensing technology in structural health monitoring

This paper studies the trajectory tracking problem of flapping-wing micro aerial vehicles &#x0028 FWMAVs &#x0029 in the longitudinal plane. First of all, the kinematics and dynamics of the FWMAV are established, wherein the aerodynamic force and torque generated by flapping wings and the tail wing are explicitly formulated with respect to the flapping frequency of the wings and the degree of tail wing inclination. To achieve autonomous tracking, an adaptive control scheme is proposed under the hierarchical framework. Specifically, a bounded position controller with hyperbolic tangent functions is designed to produce the desired aerodynamic force, and a pitch command is extracted from the designed position controller. Next, an adaptive attitude controller is designed to track the extracted pitch command, where a radial basis function neural network is introduced to approximate the unknown aerodynamic perturbation torque. Finally, the flapping frequency of the wings and the degree of tail wing inclination are calculated from the designed position and attitude controllers, respectively. In terms of Lyapunov&#x02BC s direct method, it is shown that the tracking errors are bounded and ultimately converge to a small neighborhood around the origin. Simulations are carried out to verify the effectiveness of the proposed control scheme.

Modeling and trajectory tracking control for flapping-wing micro aerial vehicles

In this work a methodology for impact identification on composite stiffened panels using piezoceramic sensors has been presented. A large number of impacts covering a wide range of energies (corresponding to small and large mass impacts) at various locations of a composite stiffened panel have been simulated using the finite element (FE) method. To predict the impact location, artificial neural networks have been established using the data generated from FE analyses. A number of sensor signal features have been examined as inputs to the neural network and the effect of noise on the predictions has been investigated. The results of the study show that the trained network is capable of locating impacts with different energies at different locations (e.g. in the bay, over/under the stringer and on the foot of the stringer) in a complicated structure such as a composite stiffened panel.

https://iopscience.iop.org/article/10.1088/0964-1726/21/10/105026/pdf

Determination of impact location on composite stiffened panels

Arthropod pest outbreaks are unpredictable and not uniformly distributed within fields. Early outbreak detection and treatment application are inherent to effective pest management, allowing management decisions to be implemented before pests are well-established and crop losses accrue. Pest monitoring is time-consuming and may be hampered by lack of reliable or cost-effective sampling techniques. Thus, we argue that an important research challenge associated with enhanced sustainability of pest management in modern agriculture is developing and promoting improved crop monitoring procedures. Biotic stress, such as herbivory by arthropod pests, elicits physiological defense responses in plants, leading to changes in leaf reflectance. Advanced imaging technologies can detect such changes, and can, therefore, be used as noninvasive crop monitoring methods. Furthermore, novel methods of treatment precision application are required. Both sensing and actuation technologies can be mounted on equipment moving through fields (e.g., irrigation equipment), on (un)manned driving vehicles, and on small drones. In this review, we focus specifically on use of small unmanned aerial robots, or small drones, in agricultural systems. Acquired and processed canopy reflectance data obtained with sensing drones could potentially be transmitted as a digital map to guide a second type of drone, actuation drones, to deliver solutions to the identified pest hotspots, such as precision releases of natural enemies and/or precision-sprays of pesticides. We emphasize how sustainable pest management in 21st-century agriculture will depend heavily on novel technologies, and how this trend will lead to a growing need for multi-disciplinary research collaborations between agronomists, ecologists, software programmers, and engineers.

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Drones: Innovative Technology for Use in Precision Pest Management

This paper reports on a novel metamodel for impact detection, localization and characterization of complex composite structures based on Convolutional Neural Networks (CNN) and passive sensing. Methods to generate appropriate input datasets and network architectures for impact localization and characterization were proposed, investigated and optimized. The ultrasonic waves generated by external impact events and recorded by piezoelectric sensors are transferred to 2D images which are used for impact detection and characterization. The accuracy of the detection was tested on a composite fuselage panel which was shown to be over 94%. In addition, the scalability of this metamodelling technique has been investigated by training the CNN metamodels with the data from part of the stiffened panel and testing the performance on other sections with similar geometry. Impacts were detected with an accuracy of over 95%. Impact energy levels were also successfully categorized while trained at coupon level and applied to sub-components with greater complexity. These results validated the applicability of the proposed CNN-based metamodel to real-life application such as composite aircraft parts.

https://www.mdpi.com/1424-8220/19/22/4933/pdf

A convolutional neural network for impact detection and characterization of complex composite structures

Bird strike event monitoring in a composite UAV wing using high speed optical fiber sensing system

Bird-mimetic Wing System of Flapping-wing Micro Air Vehicle with Autonomous Flight Control Capability

Laser ultrasonic scanning in combination with contact or non-contact sensors provides new paradigms in structural health management (SHM) and non-destructive in-process quality control (IPQC) for large composite structures. Wave propagation imaging technology based on laser ultrasonic scanning and fixed-point sensing shows remarkable advantages, such as minimal need for embedded sensors in SHM, minimum invasive defect visualization in IPQC and general capabilities of curved and complex target inspection, and temporal reference-free inspection. However, as with other SHM methods and non-destructive evaluation based on ultrasound, the signal-to-noise ratio (SNR) is a prevalent issue in real structural applications, especially with non-contact thin-composite sensing or with thick and heterogeneous composites. This study proposes a high-speed repeat scanning technique for laser ultrasonic propagation imaging (UPI) technology, which is realized with the scanning speed of 1 kHz of a Q-switched continuous wave laser, and precise control of the laser beam pulses for identical point scanning. As a result, the technique enables the achievement of significant improvement in the SNR to inspect real-world composite structures. The proposed technique provides enhanced results for impact damage detection in a 2 mm thick wing box made of carbon-fiber-reinforced plastic, despite the low sensitivity of non-contact laser ultrasonic sensing. A field-applicable pure laser UPI system has been developed using a laser Doppler vibrometer as the non-contact ultrasonic sensor. The proposed technique enables the visualization of the disbond defect in a 15 mm thick wind blade specimen made of glass-fiber-reinforced plastic, despite the high dissipation of ultrasound in the thick composite.

https://iopscience.iop.org/article/10.1088/0957-0233/24/8/085201/pdf

Repeat scanning technology for laser ultrasonic propagation imaging

A new approach of monitoring low-velocity impact events on composite structures was presented and experimentally evaluated. In this approach, impact strain histories of a composite plate were measured with optical fiber sensors. The recorded signals were used to estimate locations and forces of low-velocity impact events. For experimental validation, four-sensor heads were surface mounted at the four corners of a composite panel. The optical sensors caught dynamic strain due to impacts on the panel, and the optical cables transmitted wavelength changes of the sensors. The multiplexed wavelength changes were measured using a high-speed fiber Bragg grating interrogator for the determination of impact location. The locations of impact events were estimated using a neural network program and measured signals. The estimated locations and converted strain signals were taken as the inputs to the process of reconstructing impact forces. Even though the current study is an initial investigation on a simple impact ...

Localizations and force reconstruction of low-velocity impact in a composite panel using optical fiber sensors

A radome must not only withstand various forces during operation, but also provide a window for electromagnetic signals. A radome is generally a composite sandwich structure. Much of the damage to radomes is barely visible to the naked eye on the outer surface, but is severe internally. In this study, a radome health management strategy consisting of in-flight damage event detection and ground damage evaluation processes is proposed. A radome health management system, composed of an on-board subsystem and a ground subsystem, was developed to realize the strategy. An in-flight event detection system was developed based on acoustic emission (AE) technology. A built-in amplifier-integrated PZT sensor was used, and the minimum impact energy that the on-board subsystem can detect was determined. The AE sensor was then switched to an ultrasonic receiver. A scanning laser ultrasonic technology was combined with the ultrasonic receiver to develop a ground nondestructive evaluation subsystem. For in situ damage visualization, laser ultrasonic frequency tomography and wavelet-transformed ultrasonic propagation imaging algorithms were developed in this study. To demonstrate the robustness of the ground subsystem, a damage was generated by 5.42 J impact in a glass/epoxy radome with honeycomb core, and the impact image of 25 mm in diameter invisible outside could be visualized with the combination of ultrasonic spectral imaging (USI) and wavelet-transformed ultrasonic propagation imaging (WUPI), which made the propagation of only the damage-related ultrasonic modes visible.

Radome health management based on synthesized impact detection, laser ultrasonic spectral imaging, and wavelet-transformed ultrasonic propagation imaging methods

Chan Yik Park

Papers

Bird strike event monitoring in a composite UAV wing using high speed optical fiber sensing system

Bird-mimetic Wing System of Flapping-wing Micro Air Vehicle with Autonomous Flight Control Capability

Repeat scanning technology for laser ultrasonic propagation imaging

Localizations and force reconstruction of low-velocity impact in a composite panel using optical fiber sensors

Radome health management based on synthesized impact detection, laser ultrasonic spectral imaging, and wavelet-transformed ultrasonic propagation imaging methods