Compensation of environmental influences for damage detection using classification techniques

Proceedings of the 4th European Workshop on Structural Health Monitoring

Volumn , Issue , 2008, Pages 1080-1087

  Moll, Jochen ^a   Kraemer, Peter ^a   Fritzen, Claus Peter ^a  

^a UNIVERSITY OF SIEGEN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ALARM SYSTEMS; ALGORITHMS; DAMAGE DETECTION; ERRORS; HEALTH; IMAGE SEGMENTATION; PATTERN RECOGNITION; PROBABILITY DENSITY FUNCTION; PROBABILITY DISTRIBUTIONS; STRUCTURES (BUILT OBJECTS); WIND POWER; COMPUTER SIMULATION; STRUCTURAL HEALTH MONITORING;

BASIC IDEAS; BEAM MODELS; CLASSIFICATION TECHNIQUES; CLASSIFICATION TOOLS; DETECTION ALGORITHMS; ENVIRONMENTAL INFLUENCES; EXPECTATION-MAXIMIZATION ALGORITHMS; FALSE ALARMS; INPUT PARAMETERS; K-MEANS; LOW-FREQUENCY RANGES; NUMBER OF FALSE ALARMS; OFF-SHORE WIND ENERGIES; OPERATIONAL CHANGES; OPERATIONAL CONDITIONS; REAL-WORLD APPLICATIONS; REFERENCE STATE; SIMULATION MODELS; SIMULATION RESULTS; SIMULATION STUDIES; STATISTICAL PATTERN RECOGNITION;

STRUCTURAL HEALTH MONITORING; DAMAGE DETECTION;

BEAM MODEL; CLASSIFICATION TECHNIQUE; CLASSIFICATION TOOL; DETECTION ALGORITHM; ENVIRONMENTAL INFLUENCES; EXPECTATION-MAXIMIZATION ALGORITHMS; FALSE ALARMS; INPUT PARAMETER; K-MEANS; LOW FREQUENCY RANGE; NUMBER OF FALSE ALARMS; OFF-SHORE WIND ENERGY; OPERATIONAL CHANGES; OPERATIONAL CONDITIONS; REAL-WORLD APPLICATION; REFERENCE STATE; SIMULATION MODEL; SIMULATION STUDIES; STATISTICAL PATTERN RECOGNITION;

EID: 62949201701     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (16)

1. Sohn, H., K. Worden, and C.R. Farrar. 2002. "Statistical Damage Classification Under Changing Environmental and Operational Conditions," Journal of Intelligent Material Systems and Structures (Vol. 13), pp. 561-574.
2. Peeters, B., J. Maeck and G. De Roeck. 2001. "Vibration-based damage detection in civil engineering: excitation sources and temperature effects," Smart Materials and Structures (Vol. 10), pp. 518-527.
3. Hios, J.D. and S.D. Fassois. 2006. "Identification of a Global Model Describing the Temperature Effects on the Dynamics of a Smart Composite Beam," Proc. ISMA 2006, pp. 3279-3294.
4. Kullaa, J. 2005. "Damage Detection under a Varying Environment using the Missing Data Concept," Proc. 5th International Workshop on SHM, pp. 565-573.
5. Lämsä, V. and J. Kullaa. 2007. "Nonlinear Factor Analysis in Structural Health Monitoring to Remove Environmental Effects," Proc. 6th International Workshop on SHM, pp. 1092-1099.
6. Yan, A.-M., G. Kerschen, P. De Boe, and J.-C. Golinval. 2005. "Structural damage diagnosis under varying environmental conditions - part 2: local PCA for non-linear cases," Mechanical Systems and Processing (Vol. 19), pp. 865-880.
7. Zhou, H.F., Y.Q. Ni and J.M. Ko. 2007. "Eliminating Temperature Effect in Structural Damage Alarming Using Auto-Associative Neural Networks," Proc. 6th International Workshop on SHM, pp.539-548.
8. Sohn, H. 2007. "Effects of Environmental and Operational Variability on Structural Health Monitoring," Royal Society of London Transactions Series A (Vol. 365), pp. 539-560.
9. Mengelkamp, G. and C.-P. Fritzen. 2002. "Detection of Delaminations in Composite Materials Using a Smart Structure Concept," Proc. 1st European Workshop on SHM, pp. 237-244.
10. Fritzen, C.-P., G. Mengelkamp, and A. Güemes. 2003. "Elimination of Temperature Effects on Damage Detection within a Smart Structure Concept," Proc. 4th International Workshop on SHM, pp. 1530-1538.
11. Kraemer P., and C.-P. Fritzen. 2007. "Concept for Structural Damage Identification of Offshore Wind Energy Plants," Proc. 6th International Workshop on SHM, pp. 1881-1888.
12. Basseville, M., M. Abdelghani, and A. Benveniste. 2000. "Subspace-based fault detection algorithms for vibration monitoring," Automatica (Vol. 36), pp. 101-109.
13. Basseville, M., F. Bourquin, L. Mevel, H. Nasser, and F. Treyssède. 2006. "Merging sensor data from multiple temperature scenarios for vibration-based monitoring of civil structures," Proc. of the 3rd European Workshop on SHM, pp. 759-766.
14. Nair, K.K.. and A.S. Kiremidjian. 2007. 'Time Series Based Structural Damage Detection Algorithm Using Gaussian Mixtures Modeling," Journal of Dynamic Systems, Measurement and Control (Vol. 129), pp. 285-293.
15. Balageas, D., C.-P. Fritzen, and A. Güemes. 2006. Structural Health Monitoring. ISTE, London
16. Nelles, O. 2001. Nonlinear System Identification. Springer, Germany.