Stochastic iterative modal identification algorithm and application in wireless sensor networks

摘要

Computational capability of wireless sensor network (WSN) significantly facilitates application of dense sensorynarrays, which is increasingly important in health monitoring of large-scale structural systems. As the wirelessnsensor technology improves, more complicated tasks can be assigned to sensing units, and the communicationnbetween sensing nodes and their base station can be minimized, utilizing in-network processing. This strategynshould be used to address WSN challenges, such as limited communication bandwidth and prohibitive powernconsumption, associated with wireless communication and battery power. An iterative modal identificationnalgorithm is proposed in this paper, which uses the on-board processors for estimation of system parametersnthrough iteration cycles. The iterative algorithm was originally developed such that each individual sensor, havingnan initial estimate of the system parameters, its local measurement, and the excitation signal, updates the estimatednmodel and passes it through the network until convergence. This study further improves the algorithm to eliminatenits limitations in need for availability of excitation load and initial estimate of the system parameters. As a result,nthe algorithm is applicable for modal identification of structural systems under ambient loading without need fornprior information about the system parameters. The development of the algorithm is presented in this paper andnvalidated through implementation on a numerically simulated example and a laboratory experiment. Furthermore,nits performance is evaluated using data from an ambient vibration test of the Golden Gate Bridge using a WSN.nResults of these implementations verify the functionality of the algorithm in monitoring of real-life structuralnsystems. Copyright © 2012 John Wiley & Sons, Ltd.