Bio: Vince Jacob is an academic researcher from PDF Solutions. The author has contributed to research in topics: Bridge (interpersonal) & Structural health monitoring. The author has an hindex of 3, co-authored 6 publications receiving 49 citations.
TL;DR: The development of a large-scale wireless structural monitoring system for long-span bridges is reported; the system is entirely wireless which renders it low-cost and easy to install.
Abstract: A dense network of sensors installed in a bridge can continuously generate response data from which the health and condition of the bridge can be analyzed. This approach to structural health monitoring the efforts associated with periodic bridge inspections and can provide timely insight to regions of the bridge suspected of degradation or damage. Nevertheless, the deployment of fine sensor grids on large-scale structures is not feasible using wired monitoring systems because of the rapidly increasing installation labor and costs required. Moreover, the enormous size of raw sensor data, if not translated into meaningful forms of information, can paralyze the bridge manager's decision making. This paper reports the development of a large-scale wireless structural monitoring system for long-span bridges; the system is entirely wireless which renders it low-cost and easy to install. Unlike central tethered data acquisition systems where data processing occurs in the central server, the distributed network of wireless sensors supports data processing. In-network data processing reduces raw data streams into actionable information of immediate value to the bridge manager. The proposed wireless monitoring system has been deployed on the New Carquinez Suspension Bridge in California. Current efforts on the bridge site include: 1) long-term assessment of a dense wireless sensor network; 2) implementation of a sustainable power management solution using solar power; 3) performance evaluation of an internet-enabled cyber-environment; 4) system identification of the bridge; and 5) the development of data mining tools. A hierarchical cyber-environment supports peer-to-peer communication between wireless sensors deployed on the bridge and allows for the connection between sensors and remote database systems via the internet. At the remote server, model calibration and damage detection analyses that employ a reduced-order finite element bridge model are implemented.
TL;DR: This paper presents the implementation of the Finite Element (FE) model updating for a skewed highway bridge using real-time sensor data and provides modal results which are very consistent with the experimentally measured modal characteristics.
Abstract: This paper presents the implementation of the Finite Element (FE) model updating for a skewed highway bridge using real-time sensor data. The bridge under investigation is a I-275 crossing in Wayne County, Michigan. The bridge is instrumented with a wireless sensory system to collect the vibration response of the bridge under ambient vibrations. The dynamic characteristics of the bridge have been studied through the field measurements as well as a high-fidelity FE model of the bridge. The developed finite element model of the bridge is updated with the field measured response of the bridge so that the FE computed and field measured modal characteristics of the bridge match each other closely. A comprehensive sensitivity analysis was performed to determine the structural parameters of the FE model which affect the modal frequencies and modal shapes the most. A multivariable sensitivity-based objective function is constructed to minimize the error between the experimentally measured and the FE predicted modal characteristics. The selected objective function includes information about both modal frequencies and mode shapes of the bridge. An iterative approach has been undertaken to find the optimized structural parameters of the FE model which minimizes the selected objective function. Appropriate constraints and boundary conditions are used during the optimization process to prevent non-physical solutions. The final updated FE model of the bridge provides modal results which are very consistent with the experimentally measured modal characteristics.
TL;DR: Elements of the proposed two-tiered monitoring system architecture are validated upon an operational long-span suspension bridge and the ultra-low power Phoenix wireless sensor node whose design has been optimized to draw minimal power during standby is validated.
Abstract: Bridges are an important societal resource used to carry vehicular traffic within a transportation network. As such, the economic impact of the failure of a bridge is high; the recent failure of the I-35W Bridge in Minnesota (2007) serves as a poignant example. Structural health monitoring (SHM) systems can be adopted to detect and quantify structural degradation and damage in an affordable and real-time manner. This paper presents a detailed overview of a multi-tiered architecture for the design of a low power wireless monitoring system for large and complex infrastructure systems. The monitoring system architecture employs two wireless sensor nodes, each with unique functional features and varying power demand. At the lowest tier of the system architecture is the ultra-low power Phoenix wireless sensor node whose design has been optimized to draw minimal power during standby. These ultra low-power nodes are configured to communicate their measurements to a more functionally-rich wireless sensor node residing on the second-tier of the monitoring system architecture. While the Narada wireless sensor node offers more memory, greater processing power and longer communication ranges, it also consumes more power during operation. Radio frequency (RF) and mechanical vibration power harvesting is integrated with the wireless sensor nodes to allow them to operate freely for long periods of time (e.g., years). Elements of the proposed two-tiered monitoring system architecture are validated upon an operational long-span suspension bridge.
TL;DR: This paper presents an iterative uncoupled approach to obtain an accurate estimation of the vehicle/structure interaction and develops a reduced-order model of the bridge using a state-space model.
Abstract: Vehicle/structure interaction is extremely important in determining the structural performance of highway bridges. However, an accurate prediction of the generated vibrations and forces requires a high-fidelity nonlinear 3D model which is sufficiently representative of the actual vehicle and bridge structure. In spite of all the computational advancements, there are still many technical difficulties to obtain a converging solution from a coupled highly nonlinear and highly damped vehicle/structure models. This paper presents an iterative uncoupled approach to obtain an accurate estimation of the vehicle/structure interaction. The multi-axle vehicle is simulated using a nonlinear 3D multibody dynamics model. The bridge model also contains several nonlinear components to accurately model the bridge behavior. The vehicle/bridge interaction results are obtained through an iterative solution by exchanging the outputs of two uncoupled nonlinear models. A convergence criterion is selected to obtain a reliable solution after several of these iterations. Finally, a reduced-order model of the bridge is developed using a state-space model. The linear reduced-order model of the bridge is coupled with the nonlinear vehicle model to improve the solution time of the analysis. The results are in a very good agreement with the iterative uncoupled approach. Â© 2012 SPIE.
TL;DR: The results of the investigation showed that the local failure of pin and hanger assemblies can partially change the global modal response of the bridge, and the changes in flexibility method and the change in uniform load surface method yield better damage identification results compared to the other methods.
Abstract: Pin and hanger assemblies are among the traditional structural components that have been widely used in many conventional suspended plate girder bridge systems around the U.S. The failure of pin and hanger assemblies has been reported as the main reason for collapse of all or part of several bridges. This paper investigates the vulnerability of a skewed highway bridge using the pin and hanger assemblies, and evaluates the application of five different modally-based damage detection techniques in identifying the failure of a pin and hanger assembly in this specific type of bridge. A detailed high-fidelity nonlinear finite element (FE) model of a typical suspended bridge using pin and hanger system is developed to investigate the possible failure of pin and hanger assemblies. Different types of loadings were applied to identify a critical stress state in the hangers. The results show that the hangers could reach to a critical bending-torsion stress state when a combination of unsymmetrical truck loadings is added to the temperature-induced stresses. In the second part of the paper, five different vibration-based damage detection techniques were used to identify failure of pin and hanger assemblies on one of the exterior steel girders. The results of the investigation showed that the local failure of pin and hanger assemblies can partially change the global modal response of the bridge. Finally, the change in flexibility method and the change in uniform load surface method yield better damage identification results compared to the other methods.
TL;DR: In this article, an inertial power generator has been developed that can harvest traffic-induced bridge vibrations at only 2 Hz, and the generator is capable of operating over an unprecedentedly large acceleration (0.54 m s −2 ) and frequency range (up to 30 Hz) without any modifications or tuning.
Abstract: This paper discusses the development and testing of a renewable energy source for powering wireless sensors used to monitor the structural health of bridges. Traditional power cables or battery replacement are excessively expensive or infeasible in this type of application. An inertial power generator has been developed that can harvest traffic-induced bridge vibrations. Vibrations on bridges have very low acceleration (0.1‐0.5 m s −2 ), low frequency (2‐30 Hz), and they are non-periodic. A novel parametric frequency-increased generator (PFIG) is developed to address these challenges. The fabricated device can generate a peak power of 57 μW and an average power of 2.3 μW from an input acceleration of 0.54 m s −2 at only 2 Hz. The generator is capable of operating over an unprecedentedly large acceleration (0.54‐9.8 m s −2 ) and frequency range (up to 30 Hz) without any modifications or tuning. Its performance was tested along the length of a suspension bridge and it generated 0.5‐0.75 μW of average power without manipulation during installation or tuning at each bridge location. A preliminary power conversion system has also been developed. (Some figures in this article are in colour only in the electronic version)
TL;DR: The state of the art in WSNs-based bridge health monitoring systems is reviewed including wireless sensor, network topology, data processing technology, power management, and time synchronization.
Abstract: Structural health monitoring (SHM) systems have shown great potential to sense the responses of a bridge system, diagnose the current structural conditions, predict the expected future performance, provide information for maintenance, and validate design hypotheses. Wireless sensor networks (WSNs) that have the benefits of reducing implementation costs of SHM systems as well as improving data processing efficiency become an attractive alternative to traditional tethered sensor systems. This paper introduces recent technology developments in the field of bridge health monitoring using WSNs. As a special application of WSNs, the requirements and characteristics of WSNs when used for bridge health monitoring are firstly briefly discussed. Then, the state of the art in WSNs-based bridge health monitoring systems is reviewed including wireless sensor, network topology, data processing technology, power management, and time synchronization. Following that, the performance validations and applications of WSNs in bridge health monitoring through scale models and field deployment are presented. Finally, some existing problems and promising research efforts for promoting applications of WSNs technology in bridge health monitoring throughout the world are explored.
TL;DR: Reduced data collection, storage and communication requirements are found to lead to substantial reductions in the energy requirements of wireless sensor networks at the expense of modal accuracy.
Abstract: Compressed sensing (CS) is a powerful new data acquisition paradigm that seeks to accurately reconstruct unknown sparse signals from very few (relative to the target signal dimension) random projections. The specific objective of this study is to save wireless sensor energy by using CS to simultaneously reduce data sampling rates, on-board storage requirements, and communication data payloads. For field-deployed low power wireless sensors that are often operated with limited energy sources, reduced communication translates directly into reduced power consumption and improved operational reliability. In this study, acceleration data from a multi-girder steel-concrete deck composite bridge are processed for the extraction of mode shapes. A wireless sensor node previously designed to perform traditional uniform, Nyquist rate sampling is modified to perform asynchronous, effectively sub-Nyquist rate sampling. The sub-Nyquist data are transmitted off-site to a computational server for reconstruction using the CoSaMP matching pursuit recovery algorithm and further processed for extraction of the structure?s mode shapes. The mode shape metric used for reconstruction quality is the modal assurance criterion (MAC), an indicator of the consistency between CS and traditional Nyquist acquired mode shapes. A comprehensive investigation of modal accuracy from a dense set of acceleration response data reveals that MAC values above 0.90 are obtained for the first four modes of a bridge structure when at least 20% of the original signal is sampled using the CS framework. Reduced data collection, storage and communication requirements are found to lead to substantial reductions in the energy requirements of wireless sensor networks at the expense of modal accuracy. Specifically, total energy reductions of 10?60% can be obtained for a sensor network with 10?100 sensor nodes, respectively. The reduced energy requirements of the CS sensor nodes are shown to directly result in improved battery life and communication reliability.
TL;DR: In this paper, the authors investigated the potential for using dense arrays of relatively low-precision GPS sensors to achieve high precision displacement estimates and showed that dynamic response resolution as low as 20-30 cm can be achieved and that the resolution improves with the number of sensors used.
Abstract: SUMMARY Many of the available SHM approaches neither readily support displacement monitoring nor work in concert with one another to take advantage of displacement-based SHM for various long-period structures. Although survey-quality GPS technology offers the possibility of measuring such displacements with sub-centimeter precision, the associated cost is too high to allow for routine deployment. Low-cost GPS chips commonly found in mobile phones and automobile navigation equipment are attractive in terms of size, cost, and power consumption; however, the displacement accuracy of these GPS chips is on the order of several meters, which is insufficient for SHM applications. Inspired by sensory information processing strategies of weakly electric fish, this paper investigates the potential for using dense arrays of relatively low-precision GPS sensors to achieve high-precision displacement estimates. Results show that dynamic response resolution as low as 20–30 cm can be achieved and that the resolution improves with the number of sensors used. Copyright © 2012 John Wiley & Sons, Ltd.
TL;DR: In this paper, a new high-sensitivity accelerometer board (SHM-H) for the Imote2 wireless smart sensor (WSS) platform is presented for structural health monitoring.
Abstract: State-of-the-art smart sensor technology enables deployment of dense arrays of sensors, which is critical for structural health monitoring (SHM) of complicated and large-scale civil structures. Despite recent successful implementation of various wireless smart sensor networks (WSSNs) for full-scale SHM, the low-cost micro-electro-mechanical systems (MEMS) sensors commonly used in smart sensors cannot readily measure low-level ambient vibrations because of their relatively low resolution. Combined use of conventional wired high- sensitivity sensors with low-cost wireless smart sensors has been shown to provide improved spectral estimates of response that can lead to improved experimental modal analysis. However, such a heterogeneous network of wired and wireless sensors requires central collection of an enormous amount of raw data and off-network processing to achieveglobal time synchronization; consequently, many of the advantages of WSSNs for SHM are lost. In this paper, the development of a new high-sensitivity accelerometer board (SHM-H) for the Imote2 wireless smart sensor (WSS) platform is presented. The use of a small number of these high-sensitivity WSSs, composed of the SHM-H and Imote2, as reference sensors in the Natural Excitation Technique—based decentralized WSSN strategy is explored and is shown to provide a cost- effective means of improving modal feature extraction in the decentralized WSSN for SHM. DOI: 10.1061/(ASCE)EM.1943-7889 .0000352. © 2012 American Society of Civil Engineers. CE Database subject headings: Structural health monitoring; Probe instruments; Identification; Stochastic models. Author keywords: Structural health monitoring; Wireless smart sensor network; High-sensitivity sensor; System identification; Decentralized sensor network.