Modeling and Monitoring of the Dynamic Response of Railroad Bridges using Wireless Smart Sensors

Railroad bridges form an integral part of railway infrastructure in the USA, carrying approximately 40 % of the ton-miles of freight. The US Department of Transportation (DOT) forecasts current rail tonnage to increase up to 88 % by 2035. Within the railway network, a bridge occurs every 1.4 miles of track, on average, making them critical elements. In an effort to accommodate safely the need for increased load carrying capacity, the Federal Railroad Association (FRA) announced a regulation in 2010 that the bridge owners must conduct and report annual inspection of all the bridges. The objective of this research is to develop appropriate modeling and monitoring techniques for railroad bridges toward understanding the dynamic responses under a moving train. To achieve the research objective, the following issues are considered specifically. For modeling, a simple, yet effective, model is developed to capture salient features of the bridge responses under a moving train. A new hybrid model is then proposed, which is a flexible and efficient tool for estimating bridge responses for arbitrary train configurations and speeds. For monitoring, measured field data is used to validate the performance of the numerical model. Further, interpretation of the proposed models showed that those models are efficient tools for predicting response of the bridge, such as fatigue and resonance. Finally, fundamental software, hardware, and algorithm components are developed for providing synchronized sensing for geographically distributed networks, as can be found in railroad bridges. The results of this research successfully demonstrate the potentials of using wirelessly measured data to perform model development and calibration that will lead to better understanding the dynamic responses of railroad bridges and to provide an effective tool for prediction of bridge response for arbitrary train configurations and speeds.National Science Foundation Grant No. CMS-0600433National Science Foundation Grant No. CMMI-0928886National Science Foundation Grant No. OISE-1107526National Science Foundation Grant No. CMMI- 0724172 (NEESR-SD)Federal Railroad Administration BAA 2010-1 projectOpe

Smart FRP Composite Sandwich Bridge Decks in Cold Regions

INE/AUTC 12.0

A high-throughput multi-hop WSN for structural health monitoring

Two major challenges with existing multi-hop WSNs used for structural health monitoring (SHM) are how to increase the data transmission rate (DTR) for large amounts of sampling data and enlarge the data transmission range without degrading link quality. To handle these issues, this paper proposes a new design method of a multi-hop WSN with multi-radio sink node (M-RSN) and double-radio relay node (D-RRN) which can increase the data transfer ability at the sink and extend the monitoring distance without degrading wireless link quality. Additionally, a tight scheduled approach and multi-radio time synchronization method are designed for the stable implementation of the proposed network. To evaluate the effectiveness and robustness of the proposed network designing method, experiments in outdoor environment and for aircraft composite wing boxes monitoring are carried out. The evaluation results have shown the advantages of the proposed methods

Decentralized identification and multimetric monitoring of civil infrastructure using smart sensors

Wireless Smart Sensor Networks (WSSNs) facilitates a new paradigm to structural identification and monitoring for civil infrastructure. Conventionally, wired sensors and central data acquisition systems have been used to characterize the state of the structure, which is quite challenging due to difficulties in cabling, long setup time, and high equipment and maintenance costs. WSSNs offer a unique opportunity to overcome such difficulties. Recent advances in sensor technology have realized low-cost, smart sensors with on-board computation and wireless communication capabilities, making deployment of a dense array of sensors on large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized data acquisition and processing are common practice, WSSNs require decentralized algorithms due to the limitation associated with wireless communication; to date such algorithms are limited. This research develops new decentralized algorithms for structural identification and monitoring of civil infrastructure. To increase performance, flexibility, and versatility of the WSSN, the following issues are considered specifically: (1) decentralized modal analysis, (2) efficient decentralized system identification in the WSSN, and (3) multimetric sensing. Numerical simulation and laboratory testing are conducted to verify the efficacy of the proposed approaches. The performance of the decentralized approaches and their software implementations are validated through full-scale applications at the Irwin Indoor Practice Field in the University of Illinois at Urbana-Champaign and the Jindo Bridge, a 484 meter-long cable-stayed bridge located in South Korea. This research provides a strong foundation on which to further develop long-term monitoring employing a dense array of smart sensors. The software developed in this research is opensource and is available at: http://shm.cs.uiuc.edu/.NSF Grant No. CMS-060043NSF Grant No. CMMI-0724172NSF Grant No. CMMI-0928886NSF Grant No. CNS-1035573Ope

Smart-antenna techniques for energy-efficient wireless sensor networks used in bridge structural health monitoring

Abstract: It is well known that wireless sensor networks differ from other computing platforms in that 1- they typically require a minimal amount of computing power at the nodes; 2- it is often desirable for sensor nodes to have drastically low power consumption. The main benefit of the this work is a substantial network life before batteries need to be replaced or, alternatively, the capacity to function off of modest environmental energy sources (energy harvesting). In the context of Structural Health Monitoring (SHM), battery replacement is particularly problematic since nodes can be in difficult to access locations. Furthermore, any intervention on a bridge may disrupt normal bridge operation, e.g. traffic may need to be halted. In this regard, switchbeam smart antennas in combination with wireless sensor networks (WSNs) have shown great potential in reducing implementation and maintenance costs of SHM systems. The main goal of implementing switch-beam smart antennas in our application is to reduce power consumption, by focusing the radiated energy only where it is needed. SHM systems capture the dynamic vibration information of a bridge structure in real-time in order to assess the health of the structure and to predict failures. Current SHM systems are based on piezoelectric patch sensors. In addition, the collection of data from the plurality of sensors distributed over the span of the bridge is typically performed through an expensive and bulky set of shielded wires which routes the information to a data sink at one end of the structure. The installation, maintenance and operational costs of such systems are extremely high due to high power consumption and the need for periodic maintenance. Wireless sensor networks represent an attractive alternative, in terms of cost, ease of maintenance, and power consumption. However, network lifetime in terms of node battery life must be very long (ideally 5–10 years) given the cost and hassle of manual intervention. In this context, the focus of this project is to reduce the global power consumption of the SHM system by implementing switched-beam smart antennas jointly with an optimized MAC layer. In the first part of the thesis, a sensor network platform for bridge SHM incorporating switched-beam antennas is modelled and simulated. where the main consideration is the joint optimization of beamforming parameters, MAC layer, and energy consumption. The simulation model, built within the Omnet++ network simulation framework, incorporates the energy consumption profiles of actual selected components (microcontroller, radio interface chip). The energy consumption and packet delivery ratio (PDR) of the network with switched-beam antennas is compared with an equivalent network based on omnidirectional antennas. In the second part of the thesis, this system model is leveraged to examine two distinct but interrelated aspects: Gallium Arsenide (GaAs) based solar energy harvesting and switched-beam antenna strategies. The main consideration here is the joint optimization of solar energy harvesting and switchedbeam directional antennas, where an equivalent network based on omnidirectional antennas acts as a baseline reference for comparison purposes.Il est bien connu que les réseaux de capteurs sans fils diffèrent des autres plateformes informatiques étant donné 1- qu’ils requièrent typiquement une puissance de calcul minimale aux noeuds du réseau ; 2- qu’il est souvent désirable que les noeuds capteurs aient une consommation d’énergie dramatiquement faible. La principale retombée de ce travail réside en la durée de vie allongée du réseau avant que les piles ne doivent être remplacées ou, alternativement, la capacité de fonctionner indéfiniment à partir de modestes sources d’énergie ambiente (glânage d’énergie). Dans le contexte du contrôle de la santé structurale (CSS), le remplacement de piles est particulièrement problématique puisque les noeuds peuvent se trouver en des endroits difficiles d’accès. De plus, toute intervention sur un pont implique une perturbation de l’opération normale de la structure, par exemple un arrêt du traffic. Dans ce contexte, les antennes intelligentes à commutation de faisceau en combinaison avec les réseaux de capteurs sans fils ont démontré un grand potentiel pour réduire les coûts de réalisation et d’entretien de systèmes de CSS. L’objectif principal de l’intégration d’antennes à commutation de faisceau dans notre application réside dans la réduction de la consommation énergétique, réalisée en concentrant l’énergie radiée uniquement là où elle est nécessaire. Les systèmes de CSS capturent l’information dynamique de vibration d’une structure de pont en temps réel de manière à évaluer la santé de la structure et prédire les failles. Les systèmes courants de CSS sont basés sur des senseurs piézoélectriques planaires. De plus, la collecte de données à partir de la pluralité de senseurs distribués sur l’étendue du pont est typiquement effectuée par le biais d’un ensemble coûteux et encombrant de câbles blindés qui véhiculent l’information jusqu’à un point de collecte à une extremité de la structure. L’installation, l’entretien, et les coûts opérationnels de tels systèmes sont extrêmement élevés étant donné la consommation de puissance élevée et le besoin d’entretien régulier. Les réseaux de capteurs sans fils représentent une alternative attrayante, en termes de coût, facilité d’entretien et consommation énergétique. Toutefois, la vie de réseau en termes de la durée de vie des piles doit être très longue (idéalement de 5 à 10 ans) étant donné le coût et les problèmes liés à l’intervention manuelle. Dans ce contexte, ce projet se concentre sur la réduction de la consommation de puissance globale d’un système de CSS en y intégrant des antennes intelligentes à commutation de faisceau conjointement avec une couche d’accès au médium (couche MAC) optimisée. Dans la première partie de la thèse, une plateforme de réseau de capteurs sans fils pour le CSS d’un pont incorporant des antennes à commutation de faisceaux est modélisé et simulé, avec pour considération principale l’optimisation des paramètres de sélection de faisceau, de la couche MAC et de la consommation d’énergie. Le modèle de simulation, construit dans le logiciel de simulation de réseaux Omnet++, incorpore les profils de consommation d’énergie de composants réels sélectionnés (microcontrôleur, puce d’interface radio). La consommation d’énergie et le taux de livraison de paquets du réseau avec antennes à commutation de faisceau est comparé avec un réseau équivalent basé sur des antennes omnidirectionnelles. Dans la deuxième partie de la thèse, le modèle système proposé est mis à contribution pour examiner deux aspects distrincts mais interreliés : le glânage d’énergie à partir de cellules solaire à base d’arséniure de Gallium (GaAs) et les stratégies liées aux antennes à commutation de faisceau. La considération principale ici est l’optimisation conjointe du glânage d’énergie et des antennes à commutation de faisceau, en ayant pour base de comparaison un réseau équivalent à base d’antennes omnidirectionnelles

Design And Evaluation of Flexibility-Based Structural Damage Localization Using Wireless Sensor Networks

The health of civil structures is very important and sometimes life-critical. While there are different ways to monitor their health, wireless sensor network: WSN) has the advantage of easy deployment and low cost, which make it feasible for most structures. We designed and implemented a system to localize damages on structures with a WSN by detecting the change in structure flexibility. This method has been validated to work well on bridges like a cantilever beam and a truss. It is also possible to be extended to other type of structures. Different from other systems, in network data processing was applied to lower the bandwidth requirement of large amount of raw sensing data. Only the intermediate computation results, that capture the flexibility related information, were transmitted back to the base station. We also divide the detection and localization into multiple levels. Lower level acts as the sentinel to detect the existence of damage; and higher levels, which consume more energy, are then triggered when necessary to get a higher resolution of localization. This design helps to further extend the lifetime of the system

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

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

Development of a wireless displacement measurement system using acceleration responses

Displacement measurements are useful information for various engineering applications such as structural health monitoring (SHM), earthquake engineering and system identification. Most existing displacement measurement methods are costly, labor-intensive, and have difficulties particularly when applying to full-scale civil structures because the methods require stationary reference points. Indirect estimation methods converting acceleration to displacement can be a good alternative as acceleration transducers are generally cost-effective, easy to install, and have low noise. However, the application of acceleration-based methods to full-scale civil structures such as long span bridges is challenging due to the need to install cables to connect the sensors to a base station. This article proposes a low-cost wireless displacement measurement system using acceleration. Developed with smart sensors that are low-cost, wireless, and capable of on-board computation, the wireless displacement measurement system has significant potential to impact many applications that need displacement information at multiple locations of a structure. The system implements an FIR-filter type displacement estimation algorithm that can remove low frequency drifts typically caused by numerical integration of discrete acceleration signals. To verify the accuracy and feasibility of the proposed system, laboratory tests are carried out using a shaking table and on a three storey shear building model, experimentally confirming the effectiveness of the proposed system.open3