Structural Identification for Mobile Sensing with Missing Observations
Publication: Journal of Engineering Mechanics
Volume 142, Issue 5
Abstract
There are many occasions in structural health monitoring (SHM) on which collected data sets contain missing observations. Such instances may occur as a result of failed communications or packet losses in a wireless sensor network or as a result of sensing and sampling methods—for example, mobile sensing. By implementing modified expectation and maximization steps, structural identification using expectation maximization (STRIDE) is capable of processing data in these circumstances and is the first modal identification technique to formally accept data with missing observations. This paper presents the STRIDE algorithm, a statistical perspective of missing data, and new STRIDE equations that account for missing observations. Expectation step (E-step) equations are given explicitly for both partially observed time steps and those not fully observed. The maximization step (M-step) provides state-space parameter updates in terms of available observations and missing-data state-variable statistics. This paper also discusses the performance and convergence behavior of STRIDE with missing data. Finally, two applications are presented to exemplify common use in network reliability and mobile sensing, both using data collected at the Golden Gate Bridge. This paper proves that sensor network data containing a significant amount of missing observations can be used to achieve a comprehensive modal identification. A successful real-world identification with simulated mobile sensors quantifies the preservation of spatial information, establishing the benefits of this type of network and emphasizing a line of inquiry for future SHM implementations.
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Acknowledgments
Research funding for this work is partially provided by the National Science Foundation through Grant No. CMMI-1351537 through the Hazard Mitigation and Structural Engineering Program, and by a grant from the Commonwealth of Pennsylvania, Department of Community and Economic Development, through the Pennsylvania Infrastructure Technology Alliance (PITA).
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Published In
Journal of Engineering Mechanics
Volume 142 • Issue 5 • May 2016
Copyright
© 2016 American Society of Civil Engineers.
History
Received: Jul 3, 2014
Accepted: Oct 12, 2015
Published online: Feb 16, 2016
Published in print: May 1, 2016
Discussion open until: Jul 16, 2016
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