Unless the sensors are closely located to a local defect, the change in the global strain field caused by the defect is very small, and may go faded by other environmental effects. Only when compared the strain readings at many points, some information about damage may be unveiled. Robust automated techniques are needed to do this comparison. Principal Component Analysis (PCA) is a well-known statistical technique that has been used as a pattern recognition technique by several years with excellent results. It allows obtaining pattern that often underlie from the data by calculating the principal components and re-expressing the information in a new space. Damage index are already available. An experimental validation of the technique is discussed in this paper, comparing damages of different sizes and positions, under a set of combined loads, both under static and dynamic conditions. Strains were measured at several points by bonded FBGs (Fiber Bragg Gratings), and also along continuous lines by optical fiber distributed sensing (OBR, Optical Backscatter Reflectometer). The sensitivity of the approach and the influence of parameters (number of sensors, distance to the damage) are quantified.
|Title of host publication||Structural Health Monitoring 2013|
|Subtitle of host publication||A Roadmap to Intelligent Structures - Proceedings of the 9th International Workshop on Structural Health Monitoring, IWSHM 2013|
|Number of pages||12|
|State||Published - 2013|
|Event||9th International Workshop on Structural Health Monitoring: A Roadmap to Intelligent Structures, IWSHM 2013 - Stanford, United States|
Duration: 10 Sep 2013 → 12 Sep 2013
|Name||Structural Health Monitoring 2013: A Roadmap to Intelligent Structures - Proceedings of the 9th International Workshop on Structural Health Monitoring, IWSHM 2013|
|Conference||9th International Workshop on Structural Health Monitoring: A Roadmap to Intelligent Structures, IWSHM 2013|
|Period||10/09/13 → 12/09/13|
Bibliographical noteFunding Information:
The financial support of Deutsche Forschungsgemeinschaft for the Sonderforschungsbereich Transregio 63 (SFB/TR 63) is gratefully acknowledged. The authors would like to thank all coworkers in InPROMPT for their contributions to the knowledge base that led to the definition of the superstructure of the hydroformylation process and for the contribution of models of the different production steps.