Dynamic study of the Barqueta cable-stayed Bridge

Proceedings of a meeting held 30 January - 2 February 2006, St Louis, Missouri, USA. http://toc.proceedings.com/00102webtoc.pdf Vol. 1A theoretical and experimental research work of the Barqueta cable-stayed bridge is described in this paper. The Barqueta Bridge, across Guadalquivir river, links the city of Seville with the Scientific Park Cartuja 93. At jam hours cars may cover one half of the bridge lanes for more than one hour. Full-scale tests were carried out to measure the bridge dynamic response. The experimental program includes the dynamic study for both cases: the bridge with one half of it lanes full of cars, and empty. Modal parameters estimations were made based on the acquired data. Ten vibration modes have been identified in the frequency range of 0-6 Hz by different techniques, being two of these modes very close to each other. The traffic-structure interaction is also studied. The experimental results were compared with those obtained from a three-dimensional finite element model developed in this work. Both sets of results show very good agreement. Finally, a damage identification technique has been applied to determine the integrity of the structureMinisterio de Educación y Ciencia BIA2004-03955-C02-0

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

Dynamic analysis of a cable-stayed deck steel arch bridge

A theoretical and experimental research work in relation to Barqueta cable-stayed bridge is described in this paper. Barqueta Bridge, across Guadalquivir river, links the city of Seville with the Scientific Park Cartuja 93. At jam hours cars may cover one half of the bridge lanes for more than one hour. Full-scale tests were carried out to measure the bridge dynamic response. The experimental program included the dynamic study for two different live load conditions: the bridge with one half of it lanes full of cars, and the bridge empty of cars. Modal parameters estimations were made based on the acquired data. Ten vibration modes were identified in the fre-quency range of 0-6 Hz by different techniques, being two of these modes very close to each other. The traffic-structure interaction is also studied. Experimental results were compared with those obtained from a three-dimensional finite element model developed in this work. Both sets of results show very good agreement. Finally, a damage identification technique has been applied to determine the integrity of the structure. Results obtained from a test developed in July 2005 have been correlated to experimental results obtained in October 2006 using the damage index methodMinisterio de Educación y Ciencia BIA2004-03955-C02-01Ministerio de Foment

Cyber-Physical Codesign of Wireless Structural Control System

Structural control systems play a critical role in protecting civil infrastructure from natural hazards such as earthquakes and extreme winds. Utilizing wireless sensors for sensing, communication and control, wireless structural control systems provide an attractive alternative for structural vibration mitigation. Although wireless control systems have advantages of flexible installation, rapid deployment and low maintenance cost, there are unique challenges associated with them, such as wireless network induced time delay and potential data loss. These challenges need to be considered jointly from both the network (cyber) and control (physical) perspectives. This research aims to develop a framework facilitating cyber-physical codesign of wireless control system. The challenges of wireless structural control are addressed through: (1) a numerical simulation tool to realistically model the complexities of wireless structural control systems, (2) a codesign approach for designing wireless control system, (3) a sensor platform to experimentally evaluate wireless control performance, (4) an estimation method to compensate for the data loss and sensor failure, and (5) a framework for fault tolerance study of wireless control system withreal-time hybrid simulation. The results of this work not only provide codesign tools to evaluate and validate wireless control design, but also the codesign strategies to implement on real-world structures for wireless structural control

On anomaly-aware structural health monitoring at the extreme edge

© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Self-awareness has been successfully utilized to create adaptive behaviors in wireless sensor nodes. However, its adoption can be daunting in scenarios, such as structural health monitoring, where the monitored environment is too complex for it to be accurately modeled by a sensor node. This article addresses this challenge by proposing a novel and lightweight anomaly-aware monitoring method for structural health monitoring that can be directly executed by a sensor node. Instead of modeling the complete structure, the proposed anomaly-aware monitoring method uses the vibration measurements of the sensor node to identify local deviations in the dynamic response of the monitored structure. The self-awareness module can then use this information to guide the dynamic behavior of the sensor node, replacing more resource-intensive structural models. We use data from multiple public benchmark structures to evaluate different features and propose an unsupervised feature selection method. Additionally, we evaluate different anomaly detection algorithms comparing their ability to detect local structural damages, also taking into account their memory and energy cost. The proposed method has been implemented in a commercial sensor node, and deployed in a scaled structure where various damage scenarios were simulated to validate the proposed method, where it was able to successfully detect the presence of damages in over 88% of the cases. Finally, we showcase how the proposed method can enhance self-awareness through the use of a simulation, where the proposed monitoring method was able to extend the battery life of the sensor node by over 59%, without impacting the node’s ability to swiftly detect damages in the structure.This work was supported in part by the Industrial Doctorate Plan of the Department of Research and Universities of the Generalitat de Catalunya. The work of David Arnaiz was supported by Agència de Gestió d’Ajuts Universitaris de Recerca under Grant AGAUR 2019 DI 075.Peer ReviewedPostprint (published version

Hybrid structural health monitoring using data-driven modal analysis and model-based Bayesian inference.

Civil infrastructures that are valuable assets for the public and owners must be adequately and periodically maintained to guarantee safety, continuous service, and avoid economic losses. Vibration-based structural health monitoring (VBSHM) has been a significant tool to assess the structural performance of civil infrastructures over the last decades. Challenges in VBSHM exist in two aspects: operational modal analysis (OMA) and Finite element model updating (FEMU). The former aims to extract natural frequency, damping ratio, and mode shapes using vibrational data under normal operation; the latter focuses on minimizing the discrepancies between measurements and model prediction. The main impediments to real-world application of VBSHM include 1) uncertainties are inevitably involved due to measurement noise and modeling error; 2) computational burden in analyzing massive data and high-fidelity model; 3) updating structural coupled parameters, e.g., mass and stiffness. Bayesian model updating approach (BMUA) is an advanced FEMU technique to update structural parameters using modal data and account for underlying uncertainties. However, traditional BMUA generally assumes mass is precisely known and only updating stiffness to circumvent the coupling effect of mass and stiffness. Simultaneously updating mass and stiffness is necessary to fully understand the structural integrity, especially when the mass has a relatively large variation. To tackle these challenges, this dissertation proposed a hybrid framework using data-driven and model-based approaches in two sequential phases: automated OMA and a BMUA with added mass/stiffness. Automated stochastic subspace identification (SSI) and Bayesian modal identification are firstly developed to acquire modal properties. Following by a novel BMUA, new eigen-equations based on two sets of modal data from the original and modified system with added mass or stiffness are derived to address the coupling effect of structural parameters, e.g., mass and stiffness. To avoid multi-dimensional integrals, an asymptotic optimization method and Differential Evolutionary Adaptive Metropolis (DREAM) sampling algorithm are employed for Bayesian inference. To alleviate computational burden, variance-based global sensitivity analysis to reduce model dimensionality and Kriging model to substitute time-consuming FEM are integrated into BMUA. The proposed VBSHM are verified and illustrated using numerical, laboratory and field test data, achieving following goals: 1) properly treating parameter uncertainties; 2) substantially reducing the computational cost; 3) simultaneously updating structural parameters with addressing the coupling effect; 4) performing the probabilistic damage identification at an accurate level

Structural Health Monitoring With Emphasis On Computer Vision, Damage Indices, And Statistical Analysis

Structural Health Monitoring (SHM) is the sensing and analysis of a structure to detect abnormal behavior, damage and deterioration during regular operations as well as under extreme loadings. SHM is designed to provide objective information for decision-making on safety and serviceability. This research focuses on the SHM of bridges by developing and integrating novel methods and techniques using sensor networks, computer vision, modeling for damage indices and statistical approaches. Effective use of traffic video synchronized with sensor measurements for decision-making is demonstrated. First, some of the computer vision methods and how they can be used for bridge monitoring are presented along with the most common issues and some practical solutions. Second, a conceptual damage index (Unit Influence Line) is formulated using synchronized computer images and sensor data for tracking the structural response under various load conditions. Third, a new index, Nd , is formulated and demonstrated to more effectively identify, localize and quantify damage. Commonly observed damage conditions on real bridges are simulated on a laboratory model for the demonstration of the computer vision method, UIL and the new index. This new method and the index, which are based on outlier detection from the UIL population, can very effectively handle large sets of monitoring data. The methods and techniques are demonstrated on the laboratory model for damage detection and all damage scenarios are identified successfully. Finally, the application of the proposed methods on a real life structure, which has a monitoring system, is presented. It is shown that these methods can be used efficiently for applications such as damage detection and load rating for decision-making. The results from this monitoring project on a movable bridge are demonstrated and presented along with the conclusions and recommendations for future work

NSF/ESF Workshop on Smart Structures and Advanced Sensors, Santorini Island, Greece, June 26-28, 2005: Structural Actuation and Adaptation Working Group

This document is a result of discussions that took place during the workshop. It describes current state of research and development (R&D) in the areas of structural actuation and adaptation in the context of smart structures and advanced sensors (SS&AS), and provides an outlook to guide future R&D efforts to develop technologies needed to build SS&AS. The discussions took place among the members of the Structural Actuation and Adaptation Working Group, as well as in general sessions including all four working groups. Participants included members of academia, industry, and government from the US and Europe, and representatives from China, Japan, and Korea