Simon Laflamme

Dynamic Characterization of a Soft Elastomeric Capacitor for Structural Health Monitoring

AbstractStructural health monitoring of civil infrastructures is a difficult task, often impeded by the geometrical size of the monitored systems. Recent advances in conducting polymers enabled the fabrication of flexible sensors capable of covering large areas, a possible solution to the monitoring challenge of mesoscale systems. The authors have previously proposed a novel sensor consisting of a soft elastomeric capacitor (SEC) acting as a strain gauge. Arranged in a network configuration, the SECs have the potential to cover very large surfaces. In this paper, understanding of the proposed sensor is furthered by evaluating its performance at vibration-based monitoring of large-scale structures. The dynamic behavior of the SEC is characterized by subjecting the sensor to a frequency sweep, and detecting vibration modes of a full-scale steel beam. Results show that the sensor can be used to detect fundamental modes and dynamic input. Also, a network of SECs is used for output-only modal identification of...

Robust Flexible Capacitive Surface Sensor for Structural Health Monitoring Applications

Early detection of possible defects in civil infrastructure is vital to ensuring timely maintenance and extending structure life expectancy. The authors recently proposed a novel method for structural health monitoring based on soft capacitors. The sensor consisted of an off-the-shelf flexible capacitor that could be easily deployed over large surfaces, the main advantages being cost-effectiveness, easy installation, and allowing simple signal processing. In this paper, a capacitive sensor with tailored mechanical and electrical properties is presented, resulting in greatly improved robustness while retaining measurement sensitivity. The sensor is fabricated from a thermoplastic elastomer mixed with titanium dioxide and sandwiched between conductive composite electrodes. Experimental verifications conducted on wood and concrete specimens demonstrate the improved robustness, as well as the ability of the sensing method to diagnose and locate strain.

Novel nanocomposite technologies for dynamic monitoring of structures: a comparison between cement-based embeddable and soft elastomeric surface?sensors

The authors have recently developed two novel solutions for strain sensing using nanocomposite materials. While they both aim at providing cost-effective solutions for the monitoring of local information on large-scale structures, the technologies are different in their applications and physical principles. One sensor is made of a cementitious material, which could make it suitable for embedding within the core of concrete structures prior to casting, and is a resistor, consisting of a carbon nanotube cement-based transducer. The other sensor can be used to create an external sensing skin and is a capacitor, consisting of a flexible conducting elastomer fabricated from a nanocomposite mix, and deployable in a network setup to cover large structural surfaces. In this paper, we advance the understanding of nanocomposite sensing technologies by investigating the potential of both novel sensors for the dynamic monitoring of civil structures. First, an in-depth dynamic characterization of the sensors using a uniaxial test machine is conducted. Second, their performance at dynamic monitoring of a full-scale concrete beam is assessed, and compared against off-the-shelf accelerometers. Experimental results show that both novel technologies compare well against mature sensors at vibration-based structural health monitoring, showing the promise of nanocomposite technologies for the monitoring of large-scale structural systems.

Soft Elastomeric Capacitor Network for Strain Sensing Over Large Surfaces

Field applications of existing sensing solutions to structural health monitoring (SHM) of civil structures are limited. This is due to economical and/or technical challenges in deploying existing sensing solutions to monitor geometrically large systems. To realize the full potential of SHM solutions, it is imperative to develop scalable cost-effective sensing strategies. We present a novel sensor network specifically designed for strain sensing over large surfaces. The network consists of soft elastomeric capacitors (SECs) deployed in an array form. Each SEC acts as a surface strain gage transducing local strain into changes in capacitance. Results show that the sensor network can track strain history above levels of 25 με using an inexpensive off-the-shelf data acquisition system. Tests at large strains show that the sensors sensitivity is almost linear over strain levels of 0-20%. We demonstrate that it is possible to reconstruct deflection shapes for a simply supported beam subjected to quasi-static loads, with accuracy comparable to resistive strain gages.

Strongly enhanced sensitivity in elastic capacitive strain sensors

Strain sensors based on dielectric elastomer capacitors function by the direct coupling of mechanical deformations with the capacitance. The coupling can be improved by enhancing the relative permittivity of the dielectric elastomer. Here, this is carried out through the grafting of conducting polymer (poly-aniline) to the elastomer backbone, leading to molecular composites. An enhancement in capacitance response of 46 times is observed. This could help to extend the possible range of miniaturization towards even smaller device features.

Electromechanical modelling of a new class of nanocomposite cement-based sensors for structural health monitoring

This work focuses on the analysis of a new nanocomposite cement-based sensor (carbon nanotube cement-based sensor), for applications in vibration-based structural health monitoring of civil engineering structures. The sensor is constituted of a cement paste doped with multi-walled carbon nanotubes, so that mechanical deformations produce a measurable change of the electrical resistance. Prior work of some of the authors has addressed the fabrication process, dynamic behaviour and implementation to full-scale structural components. Here, we investigate the effectiveness of a linear lumped-circuit electromechanical model, in which dynamic sensing is associated with a strain-dependent modulation of the internal resistance. Salient circuit parameters are identified from a series of experiments where the distance between the electrodes is parametrically varied. Experimental results indicate that the lumped-circuit model is capable of accurately predicting the step response to a voltage input and its steady-state response to a harmonic uniaxial deformation. Importantly, the model is successful in anticipating the presence of a superharmonic component in sensor’s output.

Smart sensing skin for detection and localization of fatigue cracks

Fatigue cracks on steel components may have strong consequences on the structure’s serviceability and strength. Their detection and localization is a difficult task. Existing technologies enabling structural health monitoring have a complex link signal-to-damage or have economic barriers impeding large-scale deployment. A solution is to develop sensing methods that are inexpensive, scalable, with signals that can directly relate to damage. The authors have recently proposed a smart sensing skin for structural health monitoring applications to mesosystems. The sensor is a thin film soft elastomeric capacitor (SEC) that transduces strain into a measurable change in capacitance. Arranged in a network configuration, the SEC would have the capacity to detect and localize damage by detecting local deformation over a global surface, analogous to biological skin. In this paper, the performance of the SEC at detecting and localizing fatigue cracks in steel structures is investigated. Fatigue cracks are induced in steel specimens equipped with SECs, and data measured continuously. Test results show that the fatigue crack can be detected at an early stage. The smallest detectable crack length and width are 27.2 and 0.254 mm, respectively, and the average detectable crack length and width are 29.8 and 0.432 mm, respectively. Results also show that, when used in a network configuration, only the sensor located over the formed fatigue crack detect the damage, thus validating the capacity of the SEC at damage localization.

Wavelet Network for Semi-Active Control

This paper proposes a wavelet neurocontroller capable of self-adaptation and self-organization for uncertain systems controlled with semiactive devices that are ideal candidates for control of large-scale civil structures. A condition on the sliding surface for cantilever-like structures is defined. The issue of applicability of the control solution to large-scale civil structures is made the central theme throughout the text, as this topic has not been extensively discussed in the literature. Stability and convergence of the proposed neurocontroller are assessed through various numerical simulations for harmonic, earthquake, and wind excitations. The simulations consist of semiactive dampers installed as a replacement for the current viscous damping system in an existing structure. The controller uses only localized measurements. Results show that the controller is stable for both active and semiactive control using limited measurements and that it is capable of outperforming passive control strategies for earthquake and wind loads. In the case of wind loads, the neurocontroller is found to also outperform a linear quadratic regulator (LQR) controller designed using full knowledge of the states and system dynamics.

Damage Detection and Localization from Dense Network of Strain Sensors

Structural health monitoring of large systems is a complex engineering task due to important practical issues. When dealing with large structures, damage diagnosis, localization, and prognosis necessitate a large number of sensors, which is a nontrivial task due to the lack of scalability of traditional sensing technologies. In order to address this challenge, the authors have recently proposed a novel sensing solution consisting of a low-cost soft elastomeric capacitor that transduces surface strains into measurable changes in capacitance. This paper demonstrates the potential of this technology for damage detection, localization, and prognosis when utilized in dense network configurations over large surfaces. A wind turbine blade is adopted as a case study, and numerical simulations demonstrate the effectiveness of a data-driven algorithm relying on distributed strain data in evidencing the presence and location of damage, and sequentially ranking its severity. Numerical results further show that the soft elastomeric capacitor may outperform traditional strain sensors in damage identification as it provides additive strain measurements without any preferential direction. Finally, simulation with reconstruction of measurements from missing or malfunctioning sensors using the concepts of virtual sensors and Kriging demonstrates the robustness of the proposed condition assessment methodology for sparser or malfunctioning grids.

Smart cement paste with carbon nanotubes

Abstract Carbon nanotubes can be added to cementitious materials to create a multifunctional nanocomposite with excellent piezoresistive and strain-sensing properties. The use of carbon nanotubes provides high strain sensitivity and signal-to-noise ratio, which are ideal for fabricating self-sensing nanocomposite cement paste for applications to structural health monitoring of concrete structures. The authors have recently developed an innovative sensor, the carbon nanotube cement-based sensor (CNTCS), made from a nanocomposite cement paste. This CNTCS is durable because it is fabricated with a material that has a life expectancy similar to the one of the monitored structure, and provides a natural strong mechanical bond with structural concrete. These characteristics enable embedded and spatially distributed sensing. The CNTCS was conceived to conduct vibration-based structural health monitoring. This chapter presents an overview of the sensing properties of cement pastes doped with multiwalled carbon nanotubes. After introducing the topic, including a brief state of the art on multifunctional cement-based materials, the fabrication process of the CNTCSs is discussed. Then, unstrained and strained electrical responses of the nanocomposite sensors are discussed and interpreted in light of a lumped electromechanical circuit model used to characterize both the polarization effects and the sensing capability of the CNTCSs. Finally, a proof-of-concept laboratory application consisting of vibration monitoring and modal identification of a full-scale concrete beam is presented, where outputs of CNTCSs are benchmarked against mature off-the-shelf sensing technologies.