Market-based frequency domain decomposition for automated mode shape estimation in wireless sensor networks

Zimmerman, Andrew T.; Lynch, Jerome P.

doi:10.1002/stc.415

Cited by 15 publications

(22 citation statements)

References 11 publications

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“…The FDD provides more reliable and robust model shape estimation compared to PP, while this approach requires a linear network topology and may result in substantial accumulation of errors in the global mode shapes. Subsequently, a market-based frequency domain decomposition (MBFDD) technique derived from free-market principles is developed by Zimmerman and Lynch [91] through which an agentbased WSN can autonomously and optimally shift emphasis between improving the accuracy of its mode shape calculations and reducing its dependency on any of the physical limitations of a wireless network, namely, processing time, storage capacity, wireless bandwidth, or power consumption. In contrast to the FDD method, which uses a predefined chain-like topology through which computational tasks are distributed, the MBFDD technique creates an ad hoc treelike topology through which a set of SVD calculations of varying sizes can be distributed.…”

Section: Wireless Txmentioning

confidence: 99%

Recent Developments on Wireless Sensor Networks Technology for Bridge Health Monitoring

Zhou

2013

Mathematical Problems in Engineering

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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. WSNs-Based Bridge Health Monitoring SystemAs a new concept in the field of SHM, the WSNs-based bridge health monitoring system, which eliminates the high Submit your manuscripts at

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Section: Wireless Txmentioning

confidence: 99%

Recent Developments on Wireless Sensor Networks Technology for Bridge Health Monitoring

Zhou

2013

Mathematical Problems in Engineering

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“…Each Narada wireless sensor is programmed with DAA algorithm, and asked to autonomously form computational clusters with varying values of n. The root of the tree is randomly selected in each experiment. In a manner similar to [33], the weight of an edge e is set to w e = 1−p CF 1+e −0.4(40+RSSI) , where RSSI is the radio signal strength indicator reported by the radio and p CF is the probability that a communication link with perfect RSSI fails due to unforeseen circumstances and is set to 0.1 for the Narada platform.…”

Section: Simulation and Experimentationmentioning

confidence: 99%

Networked Computing in Wireless Sensor Networks for Structural Health Monitoring

Jindal

Liu

2012

IEEE/ACM Trans. Networking

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This paper studies the problem of distributed computation over a network of wireless sensors. While this problem applies to many emerging applications, to keep our discussion concrete we will focus on sensor networks used for structural health monitoring. Within this context, the heaviest computation is to determine the singular value decomposition (SVD) to extract mode shapes (eigenvectors) of a structure. Compared to collecting raw vibration data and performing SVD at a central location, computing SVD within the network can result in significantly lower energy consumption and delay. Using recent results on decomposing SVD, a well-known centralized operation, into components, we seek to determine a near-optimal communication structure that enables the distribution of this computation and the reassembly of the final results, with the objective of minimizing energy consumption subject to a computational delay constraint. We show that this reduces to a generalized clustering problem; a cluster forms a unit on which a component of the overall computation is performed. We establish that this problem is NPhard. By relaxing the delay constraint, we derive a lower bound to this problem. We then propose an integer linear program (ILP) to solve the constrained problem exactly as well as an approximate algorithm with a proven approximation ratio. We further present a distributed version of the approximate algorithm. We present both simulation and experimentation results to demonstrate the effectiveness of these algorithms.

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“…The collected data on the laptop were then transferred to a database located in University of Michigan via a 3G sprint wireless connection. The modal frequencies and modal shapes were identified using a Frequency Domain Decomposition (FDD) [18]. The first six extracted modal frequencies of the bridge are plotted in Table 2.…”

Section: Field Measurementsmentioning

confidence: 99%

Finite Element model updating of a skewed highway bridge using a multi-variable sensitivity-based optimization approach

et al. 2012

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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.

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Market-based frequency domain decomposition for automated mode shape estimation in wireless sensor networks

Cited by 15 publications

References 11 publications

Recent Developments on Wireless Sensor Networks Technology for Bridge Health Monitoring

Recent Developments on Wireless Sensor Networks Technology for Bridge Health Monitoring

Networked Computing in Wireless Sensor Networks for Structural Health Monitoring

Finite Element model updating of a skewed highway bridge using a multi-variable sensitivity-based optimization approach

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