35,567 research outputs found

    Structural health monitoring of wind turbine blades: acoustic source localization using wireless sensor networks

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    Structural health monitoring (SHM) is important for reducing the maintenance and operation cost of safety-critical components and systems in offshore wind turbines. This paper proposes an in situ wireless SHM system based on an acoustic emission (AE) technique. By using this technique a number of challenges are introduced due to high sampling rate requirements, limitations in the communication bandwidth, memory space, and power resources. To overcome these challenges, this paper focused on two elements: (1) the use of an in situ wireless SHM technique in conjunction with the utilization of low sampling rates; (2) localization of acoustic sources which could emulate impact damage or audible cracks caused by different objects, such as tools, bird strikes, or strong hail, all of which represent abrupt AE events and could affect the structural health of a monitored wind turbine blade. The localization process is performed using features extracted from aliased AE signals based on a developed constraint localization model. To validate the performance of these elements, the proposed system was tested by testing the localization of the emulated AE sources acquired in the field

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

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    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

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

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    INE/AUTC 10.0

    Energy harvesting from earthquake for vibration-powered wireless sensors

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    Wireless sensor networks can facilitate the acquisition of useful data for the assessment and retrofitting of existing structures and infrastructures. In this perspective, recent studies have presented numerical and experimental results about self-powered wireless nodes for structural monitoring applications in the event of earthquake, wherein the energy is scavenged from seismic accelerations. A general computational approach for the analysis and design of energy harvesters under seismic loading, however, has not yet been presented. Therefore, this paper proposes a rational method that relies on the random vibrations theory for the electromechanical analysis of piezoelectric energy harvesters under seismic ground motion. In doing so, the ground acceleration is simulated by means of the Clough-Penzien filter. The considered piezoelectric harvester is a cantilever bimorph modeled as Euler-Bernoulli beam with concentrated mass at the free-end, and its global behavior is approximated by the dynamic response of the fundamental vibration mode only (which is tuned with the dominant frequency of the site soil). Once the Lyapunov equation of the coupled electromechanical problem has been formulated, mean and standard deviation of the generated electric energy are calculated. Numerical results for a cantilever bimorph which piezoelectric layers made of electrospun PVDF nanofibers are discussed in order to understand issues and perspectives about the use of wireless sensor nodes powered by earthquakes. A smart monitoring strategy for the experimental assessment of structures in areas struck by seismic events is finally illustrated

    Smart FRP Composite Sandwich Bridge Decks in Cold Regions

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    INE/AUTC 12.0

    Acoustic energy transmission in cast iron pipelines

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    In this paper we propose acoustic power transfer as a method for the remote powering of pipeline sensor nodes. A theoretical framework of acoustic power propagation in the ceramic transducers and the metal structures is drawn, based on the Mason equivalent circuit. The effect of mounting on the electrical response of piezoelectric transducers is studied experimentally. Using two identical transducer structures, power transmission of 0.33 mW through a 1 m long, 118 mm diameter cast iron pipe, with 8 mm wall thickness is demonstrated, at 1 V received voltage amplitude. A near-linear relationship between input and output voltage is observed. These results show that it is possible to deliver significant power to sensor nodes through acoustic waves in solid structures. The proposed method may enable the implementation of acoustic - powered wireless sensor nodes for structural and operation monitoring of pipeline infrastructure

    Open-source digital technologies for low-cost monitoring of historical constructions

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    This paper shows new possibilities of using novel, open-source, low-cost platforms for the structural health monitoring of heritage structures. The objective of the study is to present an assessment of increasingly available open-source digital modeling and fabrication technologies in order to identify the suitable counterparts of the typical components of a continuous static monitoring system for a historical construction. The results of the research include a simple case-study, which is presented with low-cost, open-source, calibrated components, as well as an assessment of different alternatives for deploying basic structural health monitoring arrangements. The results of the research show the great potential of these existing technologies that may help to promote a widespread and cost-efficient monitoring of the built cultural heritage. Such scenario may contribute to the onset of commonplace digital records of historical constructions in an open-source, versatile and reliable fashion.Peer ReviewedPostprint (author's final draft
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