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  • Sciforum conference paper
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In Proceedings of the 4th Int. Electron. Conf. Sens. Appl. 15-30 November 2017; MDPI AG , 2017,
doi: 10.3390/ecsa-4-04889

Structural Health Monitoring is aimed at transforming civil structures into self-diagnosing systems able to automatically reveal the occurrence of a fault or a damage after a critical event such as an earthquake. While data science is presently experiencing a tremendous development, leading to the availability of powerful tools and algorithms that extract relevant information by effectively fusing data provided by different types of sensors, one of the main bottlenecks still limiting the development of SHM in the filed of civil engineering is the general lack of reliable sensing technologies that are effectively applicable to the large scale. A very promising solution to such a large scale challenge would be using the same construction materials for strain sensing and direct damage detection. In this view, the authors have recently proposed smart concretes and smart bricks that are piezoresistive concretes and clay bricks obtained by doping traditional construction materials with conductive nano- or micro inclusions. These novel multifunctional materials have the ability to provide measurable electrical output under application of a mechanical load and to provide information useful for damage detection, localization and quantification. The paper introduces both technologies, discusses their potentials and illustrates their application to paradigmatic structural elements arranged in the laboratory. The presented results contribute to showing the revolutionary impact that smart concretes and smart bricks may have in the near future on SHM of concrete and masonry structures.

  • Sciforum conference paper
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In Proceedings of the 4th Int. Electron. Conf. Sens. Appl. 15-30 November 2017; MDPI AG , 2017,
doi: 10.3390/ecsa-4-04890

Ordinary solar cell is too hard to bend or be squashed by compression, and to be extended by tensile strength. Because it is generally made of plastic polymer. However, if the one has elastic, flexible and extensible property as well as sensing of piezoelectricity, it is useful and effective on the artificial skin installed over a human-like robot as a husk which generates electric power in itself by solar and perceives any forces or temperature. Or other varied engineering applications will be feasible. In addition, such hybrid functions of both photovoltaics and piezoelectricity does not need any power supply or battery to be equipped. The solar cell with sensing developed in the present paper is novel in solar cell and sensor fields. For the realization of the elastic solar cell, it was made of natural rubber and electrolytically polymerized with configuration of magnetic clusters of metal particles by aiding a magnetic field, corresponding to the MCF rubber which the present author had developed as an elastic, flexible and extensible sensor made of natural rubber. The principle of photovoltaics and piezoelectricity was elucidated. The photo-voltage and current were measured under the photo-excitation based on the p- and n-type semiconductor resulted from the electrolytic polymerization of MCF rubber or from the doping, or on the dye. For clarifying piezoelectricity the compressive sensing was measured under compression.

  • Sciforum conference paper
  • 0 Reads
  • 0 Citations
In Proceedings of the 4th Int. Electron. Conf. Sens. Appl. 15-30 November 2017; MDPI AG , 2017,
doi: 10.3390/ecsa-4-04891

Structural health monitoring (SHM) is aimed to obtain information about the structural integrity of a system, e.g. via the estimation of its mechanical properties through observations
collected with a network of sensors. In the present work, we provide a method to optimally design sensor networks in terms of spatial configuration, number and accuracy of sensors. The utility of the sensor network is quantified through the expected Shannon information gain of the measurements with respect to the parameters to be estimated. At assigned number of sensors to be deployed over the structure, the optimal sensor placement problem is ruled by the objective function computed and maximized by combining surrogate models and stochastic optimization algorithms. For a general case, two formulations are introduced and compared: (i) the maximization of the information obtained through the measurements, given the appropriate constraints (i.e. identifiability, technological and budgetary ones); (ii) the maximization of the utility efficiency, defined as the ratio between the information provided by the sensor network and its cost. The method is applied to a large-scale structural problem, and the outcomes of the two different approaches are discussed.

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