Characterization of Distributed Microfabricated Strain Gauges on Stretchable Sensor Networks for Structural Applications

Electromechanical Properties of Smart Vitrimers Reinforced with Carbon Nanotubes for SHM Applications

The Structural Health Monitoring (SHM) capabilities of a well-studied self-healing epoxy resin based on disulfide bonds, through the addition of carbon nanotubes (CNTs), are studied. Since these materials demonstrated, in recent works, a high dependency of the dynamic hardener content on the repair performance, this study aimed to analyze the effect of the vitrimeric chemistry on the electromechanical properties by studying different 2-aminophenyl disulfide (2-AFD) hardener and CNT contents. The electrical conductivity increases with both the CNT and AFD contents, in general. Moreover, an excess of AFD close to the stoichiometric ratio with a low CNT content improved the tensile strength by 45%, while higher AFD contents promoted its detriment by 41% due to a reduced crosslinking density. However, no significant difference in the mechanical properties was observed at a higher CNT content, regardless of the AFD ratio. The developed materials demonstrate a robust electromechanical response at quasi-static conditions. The sensitivity significantly increases at higher AFD ratios, from 0.69 to 2.22 for the 0.2 wt.%. CNT system, which is advantageous due to the enhanced repair performance of these vitrimeric materials with a higher hardener content. These results reveal the potential use of self-healing vitrimers as integrated SHM systems capable of detecting damages and self-repairing autonomously.

Study of Pressure Distribution in Floor Tiles with Printed P(VDF:TrFE) Sensors for Smart Surface Applications

Pressure sensors integrated in surfaces, such as the floor, can enable movement, event, and object detection with relatively little effort and without raising privacy concerns, such as video surveillance. Usually, this requires a distributed array of sensor pixels, whose design must be optimized according to the expected use case to reduce implementation costs while providing sufficient sensitivity. In this work, we present an unobtrusive smart floor concept based on floor tiles equipped with a printed piezoelectric sensor matrix. The sensor element adds less than 130 µm in thickness to the floor tile and offers a pressure sensitivity of 36 pC/N for a 1 cm² pixel size. A floor model was established to simulate how the localized pressure excitation acting on the floor spreads into the sensor layer, where the error is only 1.5%. The model is valuable for optimizing the pixel density and arrangement for event and object detection while considering the smart floor implementation in buildings. Finally, a demonstration, including wireless connection to the computer, is presented, showing the viability of the tile to detect finger touch or movement of a metallic rod.

Design of a Robust Tool for Deploying Large-Area Stretchable Sensor Networks from Microscale to Macroscale

An investigation was conducted to develop an effective automated tool to deploy micro-fabricated stretchable networks of distributed sensors onto the surface of large structures at macroscale to create "smart" structures with embedded distributed sensor networks. Integrating a large network of distributed sensors with structures has been a major challenge in the design of so-called smart structures or devices for cyber-physical applications where a large amount of usage data from structures or devices can be generated for artificial intelligence applications. Indeed, many "island-and-serpentine"-type distributed sensor networks, while promising, remain difficult to deploy. This study aims to enable such networks to be deployed in a safe, automated, and efficient way. To this end, a scissor-hinge controlled system was proposed as the basis for a deployment mechanism for such stretchable sensor networks (SSNs). A model based on a kinematic scissor-hinge mechanism was developed to simulate and design the proposed system to automatically stretch a micro-scaled square network with uniformly distributed sensor nodes. A prototype of an automatic scissor-hinge stretchable tool was constructed during the study with an array of four scissor-hinge mechanisms, each belt-driven by a single stepper motor. Two micro-fabricated SSNs from a 100 mm wafer were fabricated at the Stanford Nanofabrication Facility for this deployment study. The networks were designed to be able to cover an area 100 times their manufacturing size (from a 100 mm diameter wafer to a 1 m2 active area) once stretched. It was demonstrated that the proposed deployment tool could place sensor nodes in prescribed locations efficiently within a drastically shorter time than in current labor-intensive manual deployment methods.

A New Payload Swing Angle Sensing Device and Its Accuracy

Measuring the swing angle of a crane load is a relatively well-known but unsatisfactorily solved problem in technical practice. This measurement is necessary for the automatic stabilization of load swing without human intervention. This article describes a technically simple and new approach to solving this problem. The focus of this work is to determine the accuracy of the measuring device. The focus of this work remains on the design, the principle of operation of the equipment, and the determination of accuracy. The basic idea is to apply the strain gauge on an elastic, easily deformable component that is part of the device. One part of the elastic component is fixedly connected to the frame; the other part is connected to the crane rope by means of pulleys close to the rope. In this way, the bending of the elastic component in proportion to the swing angle of the payload is ensured.

Monitoring the Impact of the Large Building Investments on the Neighborhood

The article presents the concept of monitoring buildings and infrastructure elements located near large construction investments (the construction of high-rise buildings of the Oak Terraces housing estate in Katowice and the construction of a tunnel under the roundabout in Katowice along the intercity express road DTŚ). The impacts include deep excavation, lowering of the groundwater level over a large area, and dynamic influences related to the use of impact methods of soil improvement. The presented monitoring includes observation of the groundwater level with the use of piezometers, geodetic measurements of settlement and inclinations, as well as the measurement of vibration amplitudes generated during the works involving shocks and vibrations. It was also important to observe the development of cracks on the basis of a previously made inventory of damage. The results of the monitoring allow corrections to be made in the technology of works (e.g., reduction of vibration amplitudes, application of additional protections at excavations, etc.) or the use additional safety measures. Currently, there are also monitoring systems used during the operation of completed facilities.

Practical Evaluation of Printed Strain Sensors Based on Long-Term Static Strain Measurements

Recent progress in printable electronics has enabled the fabrication of printed strain sensors for diverse applications. These include the monitoring of civil infrastructure, the gradual aging of which raises concerns about its effective maintenance and safety. Therefore, there is a need for automated sensing systems that provide information on the performance and behavior of engineering structures that are subjected to dynamic and static loads. The application of printed strain sensors in structural health monitoring is of growing interest owing to its large-area and cost-effective fabrication process. Previous studies have proven the suitability of printable strain sensors for dynamic strain measurements on bridges; however, the analysis of the long-term stability of printed sensors during static strain measurements is still lacking. Thus, this study aims to assess the long-term stability of printed strain sensor arrays and their suitability for the static strain analysis of large civil structures. The developed sensors and a dedicated wireless data acquisition system were deployed inside a gravity dam, which was selected as the field test environment. This test environment was chosen owing to the relatively stable temperature inside the dam and the very slow static strain changes associated with periodic water level changes. The results exhibited an average signal drift of 20 μϵ over 127 days. One of the sensor arrays was installed on a small crack in the dam structure; it showed that the sensors can track static strain changes owing to variations in the crack opening, which are related to the water level changes in the dam. Overall, the results of the developed sensors exhibit good strain sensitivity and low signal drift. This indicates the potential suitability of printed sensors for applications in the static strain analysis of engineering structures.

Static Tactile Sensing for a Robotic Electronic Skin via an Electromechanical Impedance-Based Approach

Tactile sensing is paramount for robots operating in human-centered environments to help in understanding interaction with objects. To enable robots to have sophisticated tactile sensing capability, researchers have developed different kinds of electronic skins for robotic hands and arms in order to realize the ‘sense of touch’. Recently, Stanford Structures and Composites Laboratory developed a robotic electronic skin based on a network of multi-modal micro-sensors. This skin was able to identify temperature profiles and detect arm strikes through embedded sensors. However, sensing for the static pressure load is yet to be investigated. In this work, an electromechanical impedance-based method is proposed to investigate the response of piezoelectric sensors under static normal pressure loads. The smart skin sample was firstly fabricated by embedding a piezoelectric sensor into the soft silicone. Then, a series of static pressure tests to the skin were conducted. Test results showed that the first peak of the real part impedance signal was sensitive to static pressure load, and by using the proposed diagnostic method, this test setup could detect a resolution of 0.5 N force. Numerical simulation methods were then performed to validate the experimental results. The results of the numerical simulation prove the validity of the experiments, as well as the robustness of the proposed method in detecting static pressure loads using the smart skin.

Design and Integration of a Wireless Stretchable Multimodal Sensor Network in a Composite Wing

This article presents the development of a stretchable sensor network with high signal-to-noise ratio and measurement accuracy for real-time distributed sensing and remote monitoring. The described sensor network was designed as an island-and-serpentine type network comprising a grid of sensor “islands” connected by interconnecting “serpentines.” A novel high-yield manufacturing process was developed to fabricate networks on recyclable 4-inch wafers at a low cost. The resulting stretched sensor network has 17 distributed and functionalized sensing nodes with low tolerance and high resolution. The sensor network includes Piezoelectric (PZT), Strain Gauge (SG), and Resistive Temperature Detector (RTD) sensors. The design and development of a flexible frame with signal conditioning, data acquisition, and wireless data transmission electronics for the stretchable sensor network are also presented. The primary purpose of the frame subsystem is to convert sensor signals into meaningful data, which are displayed in real-time for an end-user to view and analyze. The challenges and demonstrated successes in developing this new system are demonstrated, including (a) developing separate signal conditioning circuitry and components for all three sensor types (b) enabling simultaneous sampling for PZT sensors for impact detection and (c) configuration of firmware/software for correct system operation. The network was expanded with an in-house developed automated stretch machine to expand it to cover the desired area. The released and stretched network was laminated into an aerospace composite wing with edge-mount electronics for signal conditioning, processing, power, and wireless communication.

A New Frontier of Printed Electronics: Flexible Hybrid Electronics

The performance and integration density of silicon integrated circuits (ICs) have progressed at an unprecedented pace in the past 60 years. While silicon ICs thrive at low-power high-performance computing, creating flexible and large-area electronics using silicon remains a challenge. On the other hand, flexible and printed electronics use intrinsically flexible materials and printing techniques to manufacture compliant and large-area electronics. Nonetheless, flexible electronics are not as efficient as silicon ICs for computation and signal communication. Flexible hybrid electronics (FHE) leverages the strengths of these two dissimilar technologies. It uses flexible and printed electronics where flexibility and scalability are required, i.e., for sensing and actuating, and silicon ICs for computation and communication purposes. Combining flexible electronics and silicon ICs yields a very powerful and versatile technology with a vast range of applications. Here, the fundamental building blocks of an FHE system, printed sensors and circuits, thinned silicon ICs, printed antennas, printed energy harvesting and storage modules, and printed displays, are discussed. Emerging application areas of FHE in wearable health, structural health, industrial, environmental, and agricultural sensing are reviewed. Overall, the recent progress, fabrication, application, and challenges, and an outlook, related to FHE are presented.

Artificial Neural Network for Vertical Displacement Prediction of a Bridge from Strains (Part 2): Optimization of Strain-Measurement Points by a Genetic Algorithm under Dynamic Loading

Bridge displacements are one of the most important physical values in evaluating the health of bridges. However, the direct measurement of bridge displacements is not easy due to various factors, such as installation location and cost. For that reason, in a previous study (part 1), a method for predicting bridge displacements from strains was proposed using an artificial neural network (ANN), which has a strong ability in data mapping. In this paper, to predict the overall displacements from a small number of strains more efficiently, a method to optimize the number and locations of strain-measurement points was proposed using the genetic algorithm (GA), which is widely used for global optimization. To verify the proposed methods, two cases, a simple beam under sinusoidal loads and a girder bridge under vehicle loads, are carried out through numerical analysis. Also, a laboratory experiment is carried out with a vibrating cantilever beam. The results indicate that the predicted displacements from at least two strains at the optimized locations show good agreements with displacements by numerical analysis and measurements. The results suggest that the proposed method (optimization of strain-measurement points) is very efficient and can be applied in the actual field.