Abstract

This paper studies how a particular variation in a wireless mobile sensor configuration can influence modal identification accuracy. A mobile sensor network simultaneously measures vibration data in time while scanning over a large set of points in space. Previous research has demonstrated that such data can be specified under the dynamic sensor network (DSN) data class and examined using the truncated physical state-space model (TPM). The extended structural dentification using expectation maximization (STRIDEX) algorithm is applied to determine maximum likelihood estimates of the TPM model parameters, which are related to structural modal properties. With this approach, numerous mode shape ordinates can be extracted from each sensor, exemplifying the advantageous spatial information provided by mobile sensors as well as DSN data in general.

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