Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

Damage localization map using electromechanical impedance spectrums and inverse distance weighting interpolation: Experimental validation on thin composite structures

Piezoelectric sensors are widely used for structure health monitoring technique. In particular, electromechanical impedance techniques give simple and low-cost solutions for detecting damage in composite structures. The purpose of the method proposed in this article is to generate a damage localization map based on both indicators computed from electromechanical impedance spectrums and inverse distance weighting interpolation. The weights for the interpolation have a physical sense and are computed according to an exponential law of the measured attenuation of acoustic waves. One of the main advantages of the method, so-called data-driven method, is that only experimental data are used as inputs for our algorithm. It does not rely on any model. The proposed method has been validated on both one-dimensional and two-dimensional composite structures

Design of Wireless Sensor Nodes for Structural Health Monitoring applications

Enabling low-cost distributed monitoring, wireless sensor networks represents an interesting solution for the implementation of structural health monitoring systems. This work deals with the design of wireless sensor networks for health monitoring of civil structures, specifically focusing on node design in relation to the requirements of different structural monitoring application classes. Design problems are analysed with specific reference to a large-scale experimental setup (the long-term structural monitoring of the Basilica S. Maria di Collemaggio, L’Aquila, Italy). Main limitations emerged are highlighted, and adopted solution strategies are outlined, both in the case of commercial sensing platform and of full custom solutions

Damage identification in structural health monitoring: a brief review from its implementation to the Use of data-driven applications

The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.Peer ReviewedPostprint (published version

Low weight additive manufacturing FBG accelerometer: design, characterization and testing

Structural Health Monitoring is considered the process of damage detection and structural characterization by any type of on-board sensors. Fibre Bragg Gratings (FBG) are increasing their popularity due to their many advantages like easy multiplexing, negligible weight and size, high sensitivity, inert to electromagnetic fields, etc. FBGs allow obtaining directly strain and temperature, and other magnitudes can also be measured by the adaptation of the Bragg condition. In particular, the acceleration is of special importance for dynamic analysis. In this work, a low weight accelerometer has been developed using a FBG. It consists in a hexagonal lattice hollow cylinder designed with a resonance frequency above 500 Hz. A Finite Element Model (FEM) was used to analyse dynamic behaviour of the sensor. Then, it was modelled in a CAD software and exported to additive manufacturing machines. Finally, a characterization test campaign was carried out obtaining a sensitivity of 19.65 pm/g. As a case study, this paper presents the experimental modal analysis of the wing of an Unmanned Aerial Vehicle. The measurements from piezoelectric, MEMS accelerometers, embedded FBGs sensors and the developed FBG accelerometer are compared.Ministerio de Economía y Competitividad BIA2013-43085-P y BIA2016-75042-C2-1-

Structural health monitoring of offshore wind turbines: A review through the Statistical Pattern Recognition Paradigm

Offshore Wind has become the most profitable renewable energy source due to the remarkable development it has experienced in Europe over the last decade. In this paper, a review of Structural Health Monitoring Systems (SHMS) for offshore wind turbines (OWT) has been carried out considering the topic as a Statistical Pattern Recognition problem. Therefore, each one of the stages of this paradigm has been reviewed focusing on OWT application. These stages are: Operational Evaluation; Data Acquisition, Normalization and Cleansing; Feature Extraction and Information Condensation; and Statistical Model Development. It is expected that optimizing each stage, SHMS can contribute to the development of efficient Condition-Based Maintenance Strategies. Optimizing this strategy will help reduce labor costs of OWTs׳ inspection, avoid unnecessary maintenance, identify design weaknesses before failure, improve the availability of power production while preventing wind turbines׳ overloading, therefore, maximizing the investments׳ return. In the forthcoming years, a growing interest in SHM technologies for OWT is expected, enhancing the potential of offshore wind farm deployments further offshore. Increasing efficiency in operational management will contribute towards achieving UK׳s 2020 and 2050 targets, through ultimately reducing the Levelised Cost of Energy (LCOE)

Colloidal quantum dots enabling coherent light sources for integrated silicon-nitride photonics

Integrated photoniccircuits, increasingly based on silicon (-nitride), are at the core of the next generation of low-cost, energy efficient optical devices ranging from on-chip interconnects to biosensors. One of the main bottlenecks in developing such components is that of implementing sufficient functionalities on the often passive backbone, such as light emission and amplification. A possible route is that of hybridization where a new material is combined with the existing framework to provide a desired functionality. Here, we present a detailed design flow for the hybridization of silicon nitride-based integrated photonic circuits with so-called colloidal quantum dots (QDs). QDs are nanometer sized pieces of semiconductor crystals obtained in a colloidal dispersion which are able to absorb, emit, and amplify light in a wide spectral region. Moreover, theycombine cost-effective solution based deposition methods, ambient stability, and low fabrication cost. Starting from the linear and nonlinear material properties obtained on the starting colloidal dispersions, we can predict and evaluate thin film and device performance, which we demonstrate through characterization of the first on-chip QD-based laser

Low-authority control synthesis for large space structures

The control of vibrations of large space structures by distributed sensors and actuators is studied. A procedure is developed for calculating the feedback loop gains required to achieve specified amounts of damping. For moderate damping (Low Authority Control) the procedure is purely algebraic, but it can be applied iteratively when larger amounts of damping are required and is generalized for arbitrary time invariant systems

On-demand Aerodynamics in Integrally Actuated Membranes with Feedback Control

This paper is a numerical investigation on model reduction and control system design of integrally actuated membrane wings. A high-fidelity electro-aeromechanical model is used for the simulation of the dynamic fluid-structure interaction between a low-Reynolds-number flow and a dielectric elastomeric wing. Two reduced-order models with different levels of complexity are then derived. They are based on the projection of the fullorder discretisation of fluid and structure on modal shapes obtained from eigenvalue analysis and Proper Orthogonal Decomposition. The low-order systems are then used for the design of Proportional-Integral-Derivative and Linear Quadratic Gaussian feedback schemes to control wing lift. When implemented in the full-order model, closed-loop dynamics are in very good agreement with the reduced-order model for both tracking and gust rejection, demonstrating the suitability of the approach. The control laws selected in this work were found to be effective only for low-frequency disturbances due to the large phase delay introduced by the fluid convective time-scales, but results demonstrate the potential for the aerodynamic control of membrane wings in outdoor flight using dielectric elastomers