Application of Statistical Process Control for Structural Health Monitoring of a Historic Building
Publication: Journal of Infrastructure Systems
Volume 20, Issue 1
Abstract
The authors apply a statistical process control framework to support structural health monitoring of the Grace Church building in Charleston, South Carolina. Specifically, they conduct a post-hoc analysis of displacement data acquired via remote monitoring of delamination between two wythes of brick in a clerestory wall. The framework consists of formulation and estimation of statistical models to explain the progression of the measurements under ordinary conditions and use of control charts to detect unusual events. One such event was excessive displacement in September 2011 that led the engineer of record to close the building to public access and order immediate repairs. The analysis also reveals a few unusual events that were not apparent from visual interpretation of the data, including a possible precursor to the aforementioned event.
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Acknowledgments
The authors gratefully acknowledge the cooperation of Bennett Preservation Engineering PC of Charleston, South Carolina, and the Grace Church vestry in making structural health monitoring data available for this analysis. The research was partially funded by the Infrastructure Technology Institute at Northwestern University with a grant awarded to the corresponding author.
References
Alwan, L., and Roberts, H. (1988). “Time-series modeling for statistical process control.” J. Bus. Econ. Stat., 6(1), 87–95.
Balageas, D., Fritzen, C.-P., and Güemes, A. (2006). Structural health monitoring, ISTE, London.
Brockwell, P., and Davis, R. (2002). Introduction to time series and forecasting, Springer, New York.
Fennell, E. (2011). “Lowcountry feels earthquake centered in Va.” The Post and Courier, Charleston, SC.
Chen, Y., Corr, D., and Durango-Cohen, P. (2014). “Analysis of common and special causes of variation in the deterioration of transportation infrastructure: A field application of statistical process control for structural health monitoring.” Transport. Res. B Method.
Chu, C.-Y., and Durango-Cohen, P. (2007). “Estimation of infrastructure performance models using state-space specifications of time series models.” Transport. Res. C Emerg. Tech., 15(1), 17–32.
Chu, C.-Y., and Durango-Cohen, P. (2008). “Estimation of dynamic performance models for transportation infrastructure using panel data.” Transport. Res. B Method., 42(1), 57–81.
Deming, W. (1975). “On probability as a basis for action.” Am. Stat., 29(4), 146–152.
Fritzen, C.-P. (2005). “Vibration-based structural health monitoring—concepts and applications.” Key Eng. Mater., 293–294(3), 3–20.
Fugate, M., Sohn, H., and Farrar, C. (2001). “Vibration-based damage detection using statistical process control.” Mech. Syst. Signal Process., 15(4), 707–721.
Gendreau, M., and Soriano, P. (1998). “Airport pavement management systems: An appraisal of existing methodologies.” Transport. Res. A, 32(3), 197–214.
Hudson, W., Haas, R., and Uddin, W. (1997). Infrastructure management, McGraw-Hill, New York.
Johnson, E. H. L., Katafygiotis, L., and Beck, J. (2004). “Phase I IASC–ASCE structural health monitoring benchmark problem using simulated data.” J. Eng. Mech., 3–15.
Kiremidjian, A. (2009). “Statistical pattern recognition.” Health monitoring of bridges, H. Wenzel, ed., Wiley, West Sussex, U.K.
Kutner, M., Nachtsheim, C., and Neter, J. (2004). Applied linear regression models, 4th Ed., McGraw-Hill/Irwin, New York.
McNeil, S., Markow, M., Neumann, L., Ordway, J., and Uzarski, D. (1992). “Emerging issues in transportation facilities management.” J. Transp. Eng., 477–495.
Montgomery, D. (2009). Introduction to statistical quality control, Wiley, Hoboken, NJ.
Nair, K., and Kiremidjian, A. (2007). “Time series based structural damage detection algorithm using Gaussian Mixture Modeling.” J. Dynam. Syst. Measure. Control, 129(3), 285–293.
National Climatic Data Center. (2012). National oceanic and atmospheric administration, U.S. Dept. of Commerce, 〈http://www.ncdc.noaa.gov〉 (Apr. 15, 2013).
National Strong-Motion Project. (2012). U.S. Geological Survey, U.S. Dept. of the Interior, 〈http://nsmp.wr.usgs.gov/〉 (Apr. 15, 2013).
Nelson, L. (1984). “The Shewhart control chart—tests for special causes.” J. Quality Tech., 16(4), 237–239.
Shewhart, W. (1931). Economic control of quality of manufactured products, Van Nostrand, New York.
Sohn, H., Farrar, C., Hemez, F., and Czarnecki, J. (2002). “A review of structural health monitoring literature 1996–2001.”, Los Alamos National Laboratory.
Sohn, H., Fugate, M., and Farrar, C. (2000). “Damage diagnosis using statistical process control.” Conf. Recent Advances in Structural Dynamics, Los Alamos National Laboratory.
van Noortwijk, J., and Frangopol, D. (2004). “Deterioration and maintenance models for insuring safety of civil infrastructures at lowest life-cycle cost.” Life-cycle performance of deteriorating structures: assessment, design and management, D. M. Frangopol, E. Brühwiler, M. H. Faber, and B. Adey, eds., ASCE, Reston, VA, 384–391.
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© 2013 American Society of Civil Engineers.
History
Received: Sep 12, 2012
Accepted: Apr 17, 2013
Published online: Apr 25, 2013
Published in print: Mar 1, 2014
Discussion open until: May 26, 2014
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