Smart bricks for strain sensing and crack detection in masonry structures

The paper proposes the novel concept of smart bricks as a durable sensing solution for structural health monitoring of masonry structures. The term smart bricks denotes piezoresistive clay bricks with suitable electronics capable of outputting measurable changes in their electrical properties under changes in their state of strain. This feature can be exploited to evaluate stress at critical locations inside a masonry wall and to detect changes in loading paths associated with structural damage, for instance following an earthquake. Results from an experimental campaign show that normal clay bricks, fabricated in the laboratory with embedded electrodes made of a special steel for resisting the high baking temperature, exhibit a quite linear and repeatable piezoresistive behavior. That is a change in electrical resistance proportional to a change in axial strain. In order to be able to exploit this feature for strain sensing, high-resolution electronics are used with a biphasic DC measurement approach to eliminate any resistance drift due to material polarization. Then, an enhanced nanocomposite smart brick is proposed, where titania is mixed with clay before baking, in order to enhance the brick\u27s mechanical properties, improve its noise rejection, and increase its electrical conductivity. Titania was selected among other possible conductive nanofillers due to its resistance to high temperatures and its ability to improve the durability of construction materials while maintaining the aesthetic appearance of clay bricks. An application of smart bricks for crack detection in masonry walls is demonstrated by laboratory testing of a small-scale wall specimen under different loading conditions and controlled damage. Overall, it is demonstrated that a few strategically placed smart bricks enable monitoring of the state of strain within the wall and provide information that is capable of crack detection

Crack detection in RC structural components using a collaborative data fusion approach based on smart concrete and large-area sensors

Recent advances in the fields of nanocomposite technologies have enabled the development of highly scalable, low-cost sensing solution for civil infrastructures. This includes two sensing technologies, recently proposed by the authors, engineered for their high scalability, low-cost and mechanical simplicity. The first sensor consists of a smart-cementitious material doped with multi-wall carbon nanotubes, which has been demonstrated to be suitable for monitoring its own deformations (strain) and damage state (cracks). Integrated to a structure, this smart cementitious material can be used for detecting damage or strain through the monitoring of its electrical properties. The second sensing technology consists of a sensing skin developed from a flexible capacitor that is mounted externally onto the structure. When deployed in a dense sensor network configuration, these large area sensors are capable of covering large surfaces at low cost and can monitor both strain- and crack-induced damages. This work first presents a comparison of the capabilities of both technologies for crack detection in a concrete plate, followed by a fusion of sensor data for increased damage detection performance. Experimental results are conducted on a 50 50 5 cm3 plate fabricated with smart concrete and equipped with a dense sensor network of 20 large area sensors. Results show that both novel technologies are capable of increased damage localization when used concurrently

Experimental damage detection of wind turbine blade using thin film sensor array

Damage detection of wind turbine blades is difficult due to their large sizes and complex geometries. Additionally, economic restraints limit the viability of high-cost monitoring methods. While it is possible to monitor certain global signatures through modal analysis, obtaining useful measurements over a blade\u27s surface using off-the-shelf sensing technologies is difficult and typically not economical. A solution is to deploy dedicated sensor networks fabricated from inexpensive materials and electronics. The authors have recently developed a novel large-area electronic sensor measuring strain over very large surfaces. The sensing system is analogous to a biological skin, where local strain can be monitored over a global area. In this paper, we propose the utilization of a hybrid dense sensor network of soft elastomeric capacitors to detect, localize, and quantify damage, and resistive strain gauges to augment such dense sensor network with high accuracy data at key locations. The proposed hybrid dense sensor network is installed inside a wind turbine blade model and tested in a wind tunnel to simulate an operational environment. Damage in the form of changing boundary conditions is introduced into the monitored section of the blade. Results demonstrate the ability of the hybrid dense sensor network, and associated algorithms, to detect, localize, and quantify damage