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

Towards the Internet of Smart Trains: A Review on Industrial IoT-Connected Railways

[Abstract] Nowadays, the railway industry is in a position where it is able to exploit the opportunities created by the IIoT (Industrial Internet of Things) and enabling communication technologies under the paradigm of Internet of Trains. This review details the evolution of communication technologies since the deployment of GSM-R, describing the main alternatives and how railway requirements, specifications and recommendations have evolved over time. The advantages of the latest generation of broadband communication systems (e.g., LTE, 5G, IEEE 802.11ad) and the emergence of Wireless Sensor Networks (WSNs) for the railway environment are also explained together with the strategic roadmap to ensure a smooth migration from GSM-R. Furthermore, this survey focuses on providing a holistic approach, identifying scenarios and architectures where railways could leverage better commercial IIoT capabilities. After reviewing the main industrial developments, short and medium-term IIoT-enabled services for smart railways are evaluated. Then, it is analyzed the latest research on predictive maintenance, smart infrastructure, advanced monitoring of assets, video surveillance systems, railway operations, Passenger and Freight Information Systems (PIS/FIS), train control systems, safety assurance, signaling systems, cyber security and energy efficiency. Overall, it can be stated that the aim of this article is to provide a detailed examination of the state-of-the-art of different technologies and services that will revolutionize the railway industry and will allow for confronting today challenges.Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; ED431C 2016-045Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; ED341D R2016/012Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; ED431G/01Agencia Estatal de Investigación (España); TEC2013-47141-C4-1-RAgencia Estatal de Investigación (España); TEC2015-69648-REDCAgencia Estatal de Investigación (España); TEC2016-75067-C4-1-

Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

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

Mobile Coordinated Wireless Sensor Networks with Fault-Tolerance for Structural Health Monitoring

This paper introduces the Structural health monitoring (SHM) using Mobile Access Coordinated Wireless Sensor Network (MA-WSN) energy - efficient scheme for time sensitive applications. In Sensor Networks with Mobile Access points (SENMA), the mobile access points (MAs) traverse the network to collect information directly from each sensor. To organize disjoint nodes forming into small groups in high energy level, sensors are used in clustering methods, where each cluster has a coordinator referred as Cluster Head (CH). Early detection of failure CHs will reduce the data loss and provide possible minimal recovery efforts. Failure CHs are unable to connect to automatically organized another cluster head of access node and this access node collect and transfer data directly. So a new technique has been proposed in this paper which improves the life time of sensor nodes or it minimizes the maximum energy used by the sensor for transmitting data to the base station and also ensures monitoring quality. The performance of the proposed placement method has been tested by NS2 simulations and the result is compared with the sensor placement using effective independence method. This method obtains almost the same placement quality as that provided by using effective independence method, but with improvement in system life time

Indirect structural health monitoring (iSHM) of transport infrastructure in the digital age

Workshop reportCopyright © Joint Research Centre (European Commission). The existing European motorway infrastructure network is prone to ageing and subject to natural events (e.g. climate change) and hazards (e.g. earthquakes), necessitating immediate actions for its maintenance and safety. Within this context, the structural health monitoring (SHM) framework allows a quantitative assessment of the structural integrity, serviceability and performance, facilitating better-informed decisions for the management of the existing infrastructure. The European Commission Joint Research Centre (JRC) established the exploratory research project MITICA (Monitoring Transport Infrastructures with Connected and Automated vehicles) to investigate the opportunity to use novel methods for infrastructure motoring, aiming at the efficient maintenance of the European aging road infrastructure. This report summarizes the discussion and the outcomes of a workshop held at the JRC in Ispra (Italy) on June 6-7 2022, as part of the MITICA project. Considering the EU priority “A Europe fit for the digital age”, the workshop was dedicated to SHM and its application to civil infrastructure, focusing on innovative indirect structural health monitoring (iSHM) approaches that rely on the vehicle-bridge interaction and the deployment of sensor-equipped vehicles for the monitoring of the existing bridge infrastructure. The report aims to become a reference document in the area of iSHM using passing vehicles, for both scholars and policy makers

D5.1 SHM digital twin requirements for residential, industrial buildings and bridges

This deliverable presents a report of the needs for structural control on buildings (initial imperfections, deflections at service, stability, rheology) and on bridges (vibrations, modal shapes, deflections, stresses) based on state-of-the-art image-based and sensor-based techniques. To this end, the deliverable identifies and describes strategies that encompass state-of-the-art instrumentation and control for infrastructures (SHM technologies).Objectius de Desenvolupament Sostenible::8 - Treball Decent i Creixement EconòmicObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i InfraestructuraPreprin

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

A Review of Current Research Trends in Power-Electronic Innovations in Cyber-Physical Systems.

In this paper, a broad overview of the current research trends in power-electronic innovations in cyber-physical systems (CPSs) is presented. The recent advances in semiconductor device technologies, control architectures, and communication methodologies have enabled researchers to develop integrated smart CPSs that can cater to the emerging requirements of smart grids, renewable energy, electric vehicles, trains, ships, internet of things (IoTs), etc. The topics presented in this paper include novel power-distribution architectures, protection techniques considering large renewable integration in smart grids, wireless charging in electric vehicles, simultaneous power and information transmission, multi-hop network-based coordination, power technologies for renewable energy and smart transformer, CPS reliability, transactive smart railway grid, and real-time simulation of shipboard power systems. It is anticipated that the research trends presented in this paper will provide a timely and useful overview to the power-electronics researchers with broad applications in CPSs.post-print2.019 K

Phase Space Dissimilarity Measures for Structural Health Monitoring

A novel method for structural health monitoring (SHM), known as the Phase Space Dissimilarity Measures (PSDM) approach, is proposed and developed. The patented PSDM approach has already been developed and demonstrated for a variety of equipment and biomedical applications. Here, we investigate SHM of bridges via analysis of time serial accelerometer measurements. This work has four aspects. The first is algorithm scalability, which was found to scale linearly from one processing core to four cores. Second, the same data are analyzed to determine how the use of the PSDM approach affects sensor placement. We found that a relatively low-density placement sufficiently captures the dynamics of the structure. Third, the same data are analyzed by unique combinations of accelerometer axes (vertical, longitudinal, and lateral with respect to the bridge) to determine how the choice of axes affects the analysis. The vertical axis is found to provide satisfactory SHM data. Fourth, statistical methods were investigated to validate the PSDM approach for this application, yielding statistically significant results