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CONTENTS
Volume 14, Number 1, July 2014
 

Abstract
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Key Words
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Address
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Abstract
In this work, we address the so-called sensor reachback problem for Wireless Sensor Networks, which consists in collecting the measurements acquired by a large number of sensor nodes into a sink node which has major computational and power capabilities. Focused on applications such as Structural Health Monitoring, we propose a cooperative communication protocol that exploits the spatio-temporal correlations of the sensor measurements in order to save energy when transmitting the information to the sink node in a non-stationary environment. In addition to cooperative communications, the protocol is based on two well-studied adaptive filtering techniques, Least Mean Squares and Recursive Least Squares, which trade off computational complexity and reduction in the number of transmissions to the sink node. Finally, experiments with real acceleration measurements, obtained from the Canton Tower in China, are included to show the effectiveness of the proposed method.

Key Words
spatio-temporal correlated data; sensor reachback; adaptive predictor; wireless sensor network; structural health monitoring

Address
Nikola Bogdanovic, Dimitris Ampeliotis, Kostas Berberidis,
and Jorge Plata-Chaves: Department of Computer Engineering and Informatics, University of Patras & C.T.I RU-8,
26500, Rio - Patra, Greece
Fabio Casciati: Department of Civil Engineering and Architecture, University of Pavia,Via Ferrata 1, 27100 Pavia, Italy

Abstract
In this study, four widely accepted and used variants of Evolution Strategies (ES) are adapted and applied to the output–error state-space identification problem. The selection of ES is justified by prior strong indication of superior performance to similar problems, over alternatives like Genetic Algorithms (GA) or Evolutionary Programming (EP). The ES variants that are being tested are (i) the (1+1)–ES, (ii) the (u/p+y)–o–SA–ES, (iii) the (ui,y)–o–SA–ES, and (iv) the (uw,y)–CMA–ES. The study is based on a six–degree–of–freedom (DOF) structural model of a shear building that is characterized by light damping (up to 5%). The envisaged analysis is taking place through Monte Carlo experiments under two different excitation types (stationary / non–stationary) and the applied ES are assessed in terms of (i) accurate modal parameters extraction, (ii) statistical consistency, (iii) performance under noise–corrupted data, and (iv) performance under non–stationary data. The results of this suggest that ES are indeed competitive alternatives in the non–linear state-space estimation problem and deserve further attention.

Key Words
structural identification; evolution strategy;optimization; state–space

Address
Vasilis K. Dertimanis: Department of Civil Engineering and Geomatics, Faculty of Engineering and Technology,
Cyprus University of Technology, Limassol 3603, Cyprus, P.O. Box 50329


Abstract
Node layout optimization of structural wireless systems is investigated as a means to prolong the network lifetime without, if possible, compromising information quality of the measurement data. The trade-off between these antagonistic objectives is studied within a multi-objective layout optimization framework. A Genetic Algorithm is adopted to obtain a set of Pareto-optimal solutions from which the end user can select the final layout. The information quality of the measurement data collected from a heterogeneous WSN is quantified from the placement quality indicators of strain and acceleration sensors. The network lifetime or equivalently the network energy consumption is estimated through WSN simulation that provides realistic results by capturing the dynamics of the wireless communication protocols. A layout optimization study of a monitoring system on the Great Belt Bridge is conducted to evaluate the proposed approach. The placement quality of strain gauges and accelerometers is obtained as a ratio of the Modal Clarity Index and Mode Shape Expansion values that are computed from a Finite Element model of the monitored bridge. To estimate the energy consumption of the WSN platform in a realistic scenario, we use a discrete-event simulator with stochastic communication models. Finally, we compare the optimization results with those obtained in a previous work where the network energy consumption is obtained via deterministic communication models.

Key Words
SHM; WSN; multi-objective layout optimization; energy estimation; discrete-event simulation

Address
Khash-Erdene Jalsan, Kallirroi Flouri and Glauco Feltrin: Structural Engineering Research Laboratory, Empa, Swiss Federal Laboratories for Materials Science and Technology, Ueberlandstrasse 129, 8600 Dübendorf, Switzerland
Rohan N. Soman, Marios A. Kyriakides and Toula Onoufriou: Department of Civil Engineering and Geomatics, Cyprus University of Technology, 2-8 Saripolou Street, Achilleos Building 1, 1st floor, 3036 Limassol, Cyprus


Abstract
The paper presents a multi-objective optimization strategy for a multi-type sensor placement for Structural Health Monitoring (SHM) of long span bridges. The problem is formulated for simultaneous placement of strain sensors and accelerometers (heterogeneous network) based on application demands for SHM system. Modal Identification (MI) and Accurate Mode Shape Expansion (AMSE) were chosen as the application demands for SHM. The optimization problem is solved through the use of integer Genetic Algorithm (GA) to maximize a common metric to ensure adequate MI and AMSE. The performance of the joint optimization problem solved by GA is compared with other established methods for homogenous sensor placement. The results indicate that the use of a multi-type sensor system can improve the quality of SHM. It has also been demonstrated that use of GA improves the overall quality of the sensor placement compared to other methods for optimization of sensor placement.

Key Words
long span bridge; sensor placement optimization; mode shape expansion; modal identification; modal clarity index; genetic algorithm

Address
Rohan N. Soman, Toula Onoufriou, Marios A. Kyriakides, Renos A. Votsis and Christis Z. Chrysostomou: Department of Civil Engineering and Geomatics, Faculty of Engineering and Technology, Cyprus University of Technology, Limassol 3603, Cyprus, P.O. Box 50329



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