Algorithms for time synchronization of wireless structural monitoring sensors
Abstract
Dense networks of wireless structural health monitoring systems can effectively remove the disadvantages associated with current wire-based sparse sensing systems. However, recorded data sets may have relative time-delays due to interference in radio transmission or inherent internal sensor clock errors. For structural system identification and damage detection purposes, sensor data require that they are time synchronized. The need for time synchronization of sensor data is illustrated through a series of tests on asynchronous data sets. Results from the identification of structural modal parameters show that frequencies and damping ratios are not influenced by the asynchronous data; however, the error in identifying structural mode shapes can be significant. The results from these tests are summarized in Appendix A. The objective of this paper is to present algorithms for measurement data synchronization. Two algorithms are proposed for this purpose. The first algorithm is applicable when the input signal to a structure can be measured. The time-delay between an output measurement and the input is identified based on an ARX (auto-regressive model with exogenous input) model for the input–output pair recordings. The second algorithm can be used for a structure subject to ambient excitation, where the excitation cannot be measured. An ARMAV (auto-regressive moving average vector) model is constructed from two output signals and the time-delay between them is evaluated. The proposed algorithms are verified with simulation data and recorded seismic response data from multi-story buildings. The influence of noise on the time-delay estimates is also assessed. Copyright © 2004 John Wiley & Sons, Ltd.
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Lei et al. found that non-simultaneous sampling primarily affects mode shape identification rather than natural frequencies and damping ratios.
“Lei et al. [12] examined time delays caused by different triggering times, radio transmission interference, and internal sensor clock errors, highlighting that non-simultaneous sampling primarily affects mode shape identification rather than natural frequencies and damping ratios.”
Prior findings indicate that natural frequencies remain reasonably unaffected, while damping values tend to be significantly overestimated.
“Their findings indicate that natural frequencies remain reasonably unaffected, while damping values tend to be significantly overestimated.”
Mode shapes are the modal quantities most affected by lack of synchronization and require corrections for reliable use in SHM applications.
“Mode shapes are the modal quantities most affected by lack of synchronization and require corrections for reliable use in SHM applications.”
Previous works using different identification strategies arrived at the same conclusions: synchronization errors significantly affect mode shape estimation but have limited impact on frequency and damping estimates.
“Notably, previous works based on different identification strategies, such as [12] (using ARMAV models) and [13] (using SSI with corrective actions), arrived at the same conclusions: synchronization errors significantly affect mode shape estimation but have limited impact on frequency and damping estimates.”
Previous works [12,13] suggested that natural frequencies and damping ratios are generally more robust to sampling variability.
“Since previous works [12,13] suggested that natural frequencies and damping ratios are generally more robust to sampling variability, convergence analysis on those parameters is reported in Figure 6.”
Previous findings in the literature [12,13] attribute such degradation to the loss of physical phase consistency between sensor nodes.
“This trend aligns with previous findings in the literature [12,13], which attribute such degradation to the loss of physical phase consistency between sensor nodes.”
Previous studies [12,18] pointed out that even a tiny time misalignment is sufficient to lose the physical phase relationship between sensorized DOFs.
“As already mentioned, previous studies [12,18] pointed out that even a tiny time misalignment is sufficient to lose the physical phase relationship between sensorized DOFs.”
The use of digital sensor networks in OMA-based SHM applications is known to be affected by non-deterministic sampling, which occurs at both intra-node and inter-node levels.
“The use of digital sensor networks in OMA-based SHM applications is known to be affected by non-deterministic sampling, which occurs at both the intra-node and the inter-node levels.”
There is still a lack of a comprehensive methodology capable of systematically accounting for the sources of clock misalignment on the final modal parameters.
“Although the behavior of operational modal parameters in the presence of timing-uncertain conditions has been documented in a few seminal studies (e.g., [12,18]), there is still a lack of a comprehensive methodology capable of systematically accounting for the sources of clock misalignment on the final modal parameters.”
Even minimal misalignment is sufficient to degrade mode shapes, making them unreliable for damage detection.
“whereas even minimal misalignment is sufficient to degrade mode shapes, making them unreliable for damage detection.”
Natural frequencies are generally robust to lack of synchronization.
“Results align with findings by Lei [12] and Bernal [13]: natural frequencies are generally robust to lack of synchronization”
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- Authors
- Lei, Y., Kiremidjian, A. S., Nair, K. K., Lynch, J. P., & Law, K. H.
- Affiliations
- Stanford University (US)
- Corresponding author
- Kiremidjian, Anne S.
- Venue
- Earthquake Engineering & Structural Dynamics
- Publisher
- Wiley
- Published
- 2005
- Volume
- 34
- Issue
- 6
- Pages
- 555-573
- ISSN
- 0098-8847 (ISSN-L)
- 1096-9845
- OpenAlex
- W2148120189
- Cited by
- 50
- References
- 28
- Citations by year
- 2026: 4 · 2024: 1 · 2023: 2 · 2022: 3 · 2021: 4 · 2020: 2 · 2019: 4 · 2018: 5 · 2017: 4 · 2016: 1 · 2015: 1 · 2014: 1 · 2013: 1 · 2012: 3
- FWCI
- 9.66
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Earthquake Engineering & Structural Dynamics (publishedVersion)
- Funders
- National Science Foundation
- Topics
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
- Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
- Physical Sciences › Engineering › Civil and Structural Engineering › Bladed Disk Vibration Dynamics
- Keywords
- clock synchronization, wireless structural health monitoring, sensor data synchronization, time delay estimation, ARX model, modal parameter identification, mode shape identification, ambient excitation, seismic response, multi-storey buildings, damage detection, asynchronous data
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