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Item type:Publication, Access status: without files , An embedded computing approach for vibration-based system identification using reduced-order finite elementsSystem identification (SID) constitutes a focal point in experimental testing of civil infrastructure as well as in structural health monitoring (SHM). Conventional SID approaches have relied on creating finite element (FE) models of civil infrastructure assets and on calibrating the models against in-situ derived information from testing equipment or against SHM data. FE models are capable of providing valuable information on the structural condition. However, the equations governing the FE method are coupled, usually calling for centralized data collection, which may be unsuitable for modern wireless SHM systems that employ independently operating wireless sensor nodes. In this paper, a SID approach for making full use of FE models on board wireless sensor nodes is presented, based on embedded computing and on reduced-order finite elements. Specifically, FE models of civil infrastructure assets are reduced, using model-order reduction, and partitioned into partial models, which represent different substructures and are computationally efficient for embedment in wireless sensor nodes. Using the partial models and structural response data from the substructures, insights into the structural condition of the civil infrastructure assets are obtained. The proposed approach is suitable for vibration-based SID, applied as part of long-term SHM strategies, and implementable in wireless SHM systems. Validation tests using SHM data recorded from a real-world road bridge showcase the validity of the proposed SID approach.Publicationtype: Conference Paper14 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Frequency-domain synchronization of structural health monitoring data(2024-02-17); ; ; Since the advent of structural health monitoring (SHM), vibration analysis has been one of the most popular strategies for yielding modal information of structures, such as eigenfrequencies and mode shapes. As a result of the relatively high sampling rates adopted in vibration analysis, obtaining accurate modal information requires absolute synchronization of structural response data. Despite the advances in sensing technologies and synchronization protocols, synchronization discrepancies in structural response data may occur due to drifting in internal clocks of independent data acquisition units. Particularly in wireless SHM, in which each wireless sensor node essentially operates as an independent data acquisition unit, mitigating clock drifting has been an area of intensive research. This paper addresses the issue of data synchronization from a physics-based perspective, aiming to add an additional synchronization check at the post-sampling stage. Specifically, a frequency-domain synchronization approach is reported, which builds upon the relationship between time lags in structural response data and the cross spectral density phase angles. Validation tests are conducted using simulations of a multi-degree-of-freedom oscillator and data collected from a full-scale road bridge, demonstrating the capability of the approach to estimate time lags between SHM data even in the presence of non-proportional damping, thus overcoming a common limitation of other synchronization methods. The frequency-domain synchronization approach is intended to complement synchronization protocols in extracting accurate modal information.Publicationtype: Journal Article26 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Cross-spectrum-based synchronization of structural health monitoring data(2022-07); ; ; Synchronization discrepancies when measuring structural response may compromise the accuracy of information on the condition of structures, ex- tracted from structural health monitoring (SHM) systems. Loss of synchroniza- tion mostly concerns modern wireless SHM systems; however, synchronization discrepancies may also occur in cable-based systems in case multiple data ac- quisition units without global clock management are used. This paper presents the implementation and validation of a concept towards synchronizing SHM da- ta records containing structural response data, which is imperative for obtaining information valuable for accomplishing monitoring objectives. Specifically, the performance of a cross spectrum synchronization approach reported in a recent study, which builds upon cross spectral density phase angles of structural re- sponse data transformed into the frequency domain, is investigated with struc- tural response data from real structures. The cross spectrum synchronization approach is implemented into a wireless SHM system and into a cable-based SHM system, and it is validated through tests on a laboratory shear-frame struc- ture and through field tests on a pedestrian bridge, respectively. The validation test results prove that the cross spectrum synchronization approach is capable of complementing traditional clock synchronization protocols, thus enhancing the accuracy of SHM outcomes.Publicationtype: Conference Paper74 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , On-board data synchronization in wireless structural health monitoring systems based on phase lockingWireless sensor networks are prone to synchronization discrepancies, due to the lack of intrinsic global clock management from a centralized server. In wireless structural health monitoring (SHM) systems, synchronization discrepancies may lead to erroneous estimations of structural parameters of monitored structures. To avoid errors in the estimations of structural parameters, structural response data sets collected from a structure must be synchronized. Synchronization between structural response data sets can be achieved through offline processing. However, in wireless SHM systems, offline processing requires wireless communication of entire structural response data sets, which has been proven detrimental to the power autonomy of wireless sensor nodes. This paper presents an embedded synchronization algorithm for wireless SHM systems. The embedded synchronization algorithm functions as a module added to embedded algorithms performing peak picking, which is part of operational modal analysis, for ensuring accurate outcomes. The embedded synchronization algorithm enables wireless SHM systems to synchronize structural response data sets on board using the embedded computing capabilities of wireless sensor nodes. The synchronization is achieved by imposing the expected relationship between the phase angles of Fourier spectra of acceleration response data sets at peaks corresponding to vibration modes. Time lags are autonomously estimated by the wireless sensor nodes through collaborative analysis of the phase angle relationship between acceleration response data sets collected by different sensor nodes. The embedded synchronization algorithm is implemented into a prototype wireless SHM system with embedded peak picking algorithms and validated by laboratory tests and by ambient vibration tests on a pedestrian bridge.Publicationtype: Journal Article85