A Multivariate Cumulative Sum Method for Continuous Damage Monitoring with Lamb-wave Sensors
##plugins.themes.bootstrap3.article.main##
##plugins.themes.bootstrap3.article.sidebar##
Published
Nov 3, 2020
Spandan Mishra
O. Arda Vanli
Chiwoo Park
Abstract
This paper proposes a new damage monitoring method based on a multivariate cumulative sum test statistic applied to Lambwave sensing data for health monitoring in composites. The
CUSUM monitoring method applied to the features extracted with Principal Components Analysis was studied to improve robustness of detection and sensitivity to small damages. The method is illustrated with measured sensor data from fatigue loading and impact tests of carbon fiber materials and the performance of the proposed CUSUM approach was compared with existing Mahalanobis distance based monitoring techniques commonly applied in the health monitoring literature. It was shown that the CUSUM approach can significantly improve the misdetection rate for monitoring gradually developing damages.
##plugins.themes.bootstrap3.article.details##
Keywords
Structural Health Monitoring, Principal Components Analysis, Multivariate Cumulative Sum, Hotellings T2
References
Bogdanoff, J. L., & Kozin, F. (1985). Probabilistic models of cumulative damage. New York: John Wiley.
Crosier, R. (1988). Multivariate generalizations of cumulative sum quality-control schemes. Technometrics, 30(3), 291–303.
Cross, E. J., Manson, G.,Worden, K., & Pierce, S. G. (2012). Features for damage detection with insensitivity to environmental and operational variations. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Science, 468(2148), 4098–4122.
Deraemaeker, A., Reynders, E., De Roeck, G., & Kullaa, J. (2008). Vibration-based structural health monitoring using output-only measurements under changing environment. Mechanical systems and signal processing, 22(1), 34–56.
Diamanti, K., Hodgkinson, J. M., & Soutis, C. (2004). Detection of low-velocity impact damage in composite plates using lamb waves. Structural Health Monitoring, 3(1), 33–41.
Gertsbackh, I. B., & Kordonskiy, K. B. (1969). Models of failure. New York: Springer-Verlag.
Giurgiutiu, V. (2005). Tuned lamb wave excitation and detection with piezoelectric wafer active sensors for structural health monitoring. Journal of intelligent material systems and structures, 16(4), 291–305.
Ihn, J. B., & Chang, F. K. (2004). Detection and monitoring of hidden fatigue crack growth using a built-in piezoelectric sensor/actuator network: I. diagnostics. Smart Materials and Structures, 13(3), 609.
Jackson, J. E. (2005). A user’s guide to principal components (Vol. 587). John Wiley & Sons.
Kessler, S. S., & Agrawal, P. (2007). Application of pattern recognition for damage classification in composite laminates. In Proceedings of the 6th international workshop on structural health monitoring, stanford university.
Kessler, S. S., Spearing, S. M., & Soutis, C. (2002). Damage detection in composite materials using lamb wave methods. Smart Materials and Structures, 11(2), 269.
Kullaa, J. (2003). Damage detection of the z24 bridge using control charts. Mechanical Systems and Signal Processing, 17(1), 163–170.
Lowry, C. A., & Montgomery, D. C. (1995). A review of multivariate control charts. IIE transactions, 27(6), 800–810.
Lu, C. J., & Meeker, W. O. (1993). Using degradation measures to estimate a time-to-failure distribution. Technometrics, 35(2), 161–174.
MacGregor, J. F., & Kourti, T. (1995). Statistical process control of multivariate processes. Control Engineering Practice, 3(3), 403–414.
Montgomery, D. C. (2007). Introduction to statistical quality control. John Wiley & Sons.
Mujica, L. E., Rodellar, J., Fernandez, A., & Guemes, A. (2010). Q-statistic and t2-statistic pca-based measures for damage assessment in structures. Structural Health Monitoring, 1475921710388972.
Pavlopoulou, S., Worden, K., & Soutis, C. (2013). Structural health monitoring and damage prognosis in composite repaired structures through the excitation of guided ultrasonic waves. In Spie smart structures and materials+ nondestructive evaluation and health monitoring (pp. 869504–869504).
Pignatiello, J. J., & Runger, G. C. (1990). Comparisons of multivariate cusum charts. Journal of quality technology, 22(3), 173–186.
Pullin, R., Eaton, M. J., Hensman, J. J., Holford, K. M., Worden, K., & Evans, S. L. (2008). A principal component analysis of acoustic emission signals from a landing gear component. Applied Mechanics and Materials, 13, 41–47.
Raghavan, A., & Cesnik, C. (2007). Review of guided-wave structural health monitoring. Shock and Vibration Digest, 39(2), 91–116.
Saxena, A., Goebel, K., Larrosa, C. C., & Chang, F. K. (2015). CFRP Composites dataset, NASA Ames Prognostics Data Repository. http://ti.arc.nasa.gov/project/ prognostic-data-repository. Accessed Jan 18, 2015. NASA Ames, Moffett Field, CA.
Sohn, H., Czarnecki, J. A., & Farrar, C. R. (2000). Structural health monitoring using statistical process control. Journal of Structural Engineering, 126(11), 1356–1363.
Su, Z., Ye, L., & Lu, Y. (2006). Guided lamb waves for identification of damage in composite structures: A review. Journal of sound and vibration, 295(3), 753–780.
Viktorov, I. A. (1967). Rayleigh and lamb waves. physical theory and applications. Plenum Press.
Wang, W. (2000). A model to determine the optimal critical level and the monitoring intervals in condition-based maintenance. International Journal of Production Research, 38(6), 1425–1436.
Woodall, W. H., & Ncube, M. M. (1985). Multivariate cusum quality-control procedures. Technometrics, 27(3), 285–292.
Worden, K., Manson, G., & Fieller, N. R. J. (2000). Damage detection using outlier analysis. Journal of Sound and Vibration, 229(3), 647–667.
Crosier, R. (1988). Multivariate generalizations of cumulative sum quality-control schemes. Technometrics, 30(3), 291–303.
Cross, E. J., Manson, G.,Worden, K., & Pierce, S. G. (2012). Features for damage detection with insensitivity to environmental and operational variations. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Science, 468(2148), 4098–4122.
Deraemaeker, A., Reynders, E., De Roeck, G., & Kullaa, J. (2008). Vibration-based structural health monitoring using output-only measurements under changing environment. Mechanical systems and signal processing, 22(1), 34–56.
Diamanti, K., Hodgkinson, J. M., & Soutis, C. (2004). Detection of low-velocity impact damage in composite plates using lamb waves. Structural Health Monitoring, 3(1), 33–41.
Gertsbackh, I. B., & Kordonskiy, K. B. (1969). Models of failure. New York: Springer-Verlag.
Giurgiutiu, V. (2005). Tuned lamb wave excitation and detection with piezoelectric wafer active sensors for structural health monitoring. Journal of intelligent material systems and structures, 16(4), 291–305.
Ihn, J. B., & Chang, F. K. (2004). Detection and monitoring of hidden fatigue crack growth using a built-in piezoelectric sensor/actuator network: I. diagnostics. Smart Materials and Structures, 13(3), 609.
Jackson, J. E. (2005). A user’s guide to principal components (Vol. 587). John Wiley & Sons.
Kessler, S. S., & Agrawal, P. (2007). Application of pattern recognition for damage classification in composite laminates. In Proceedings of the 6th international workshop on structural health monitoring, stanford university.
Kessler, S. S., Spearing, S. M., & Soutis, C. (2002). Damage detection in composite materials using lamb wave methods. Smart Materials and Structures, 11(2), 269.
Kullaa, J. (2003). Damage detection of the z24 bridge using control charts. Mechanical Systems and Signal Processing, 17(1), 163–170.
Lowry, C. A., & Montgomery, D. C. (1995). A review of multivariate control charts. IIE transactions, 27(6), 800–810.
Lu, C. J., & Meeker, W. O. (1993). Using degradation measures to estimate a time-to-failure distribution. Technometrics, 35(2), 161–174.
MacGregor, J. F., & Kourti, T. (1995). Statistical process control of multivariate processes. Control Engineering Practice, 3(3), 403–414.
Montgomery, D. C. (2007). Introduction to statistical quality control. John Wiley & Sons.
Mujica, L. E., Rodellar, J., Fernandez, A., & Guemes, A. (2010). Q-statistic and t2-statistic pca-based measures for damage assessment in structures. Structural Health Monitoring, 1475921710388972.
Pavlopoulou, S., Worden, K., & Soutis, C. (2013). Structural health monitoring and damage prognosis in composite repaired structures through the excitation of guided ultrasonic waves. In Spie smart structures and materials+ nondestructive evaluation and health monitoring (pp. 869504–869504).
Pignatiello, J. J., & Runger, G. C. (1990). Comparisons of multivariate cusum charts. Journal of quality technology, 22(3), 173–186.
Pullin, R., Eaton, M. J., Hensman, J. J., Holford, K. M., Worden, K., & Evans, S. L. (2008). A principal component analysis of acoustic emission signals from a landing gear component. Applied Mechanics and Materials, 13, 41–47.
Raghavan, A., & Cesnik, C. (2007). Review of guided-wave structural health monitoring. Shock and Vibration Digest, 39(2), 91–116.
Saxena, A., Goebel, K., Larrosa, C. C., & Chang, F. K. (2015). CFRP Composites dataset, NASA Ames Prognostics Data Repository. http://ti.arc.nasa.gov/project/ prognostic-data-repository. Accessed Jan 18, 2015. NASA Ames, Moffett Field, CA.
Sohn, H., Czarnecki, J. A., & Farrar, C. R. (2000). Structural health monitoring using statistical process control. Journal of Structural Engineering, 126(11), 1356–1363.
Su, Z., Ye, L., & Lu, Y. (2006). Guided lamb waves for identification of damage in composite structures: A review. Journal of sound and vibration, 295(3), 753–780.
Viktorov, I. A. (1967). Rayleigh and lamb waves. physical theory and applications. Plenum Press.
Wang, W. (2000). A model to determine the optimal critical level and the monitoring intervals in condition-based maintenance. International Journal of Production Research, 38(6), 1425–1436.
Woodall, W. H., & Ncube, M. M. (1985). Multivariate cusum quality-control procedures. Technometrics, 27(3), 285–292.
Worden, K., Manson, G., & Fieller, N. R. J. (2000). Damage detection using outlier analysis. Journal of Sound and Vibration, 229(3), 647–667.
Section
Technical Papers