Abstract
Using an optic fiber self-diagnosing system in health monitoring has become an important direction of smart materials and structure research. The buried optic fiber sensor can be used to test the parameters of the composite material. The granular computing method can reach the requirement of damage detection by analyzing digital signals and character signals of the smart structure at the same time. The paper investigates an optic fiber smart layer and presents a method for realizing optic fiber smart structure monitoring and damage detection by using granular computing. After the analysis, it is presumed that optic fiber smart structure monitoring based on granular computation can identify the damage from complex signals.
Similar content being viewed by others
References
Thomas C, Parameswaran R, Kewal K S. Analysis of exposure of target activities in a sensor network with obstacles. SenSys, 2003
Lin M, Qing X L, Kumar A, Beard S J. Smart layer and smart suitcase for structural health monitoring application, smart structure and materials. Proceedings of SPIE, 2002, 4701: 167–176
Yao Y Y. Granular computing: basic issues and possible solutions, In: Paul P, ed. Proceedings of the 5th Joint Conference on Information Sciences. USA: Elsevier Publishing Company, 2000, 186–189
Pawlak. Rough Sets: Theoretical Aspects of Reasoning about Data. Boston, MA: Kluwer Academic Publishers, 1991
Pawlak. Rough sets. International Journal of Computer and Information Sciences, 1982, 11: 341–356
Swiniarski RW, Andrzej S. Rough set methods in feature selection and recognition. Pattern Recognition Letters, 2003, 24: 833–849
Amitava R, Pa S K. Fuzzy discretization of feature space for a rough set classifier. Pattern Recognition Letters, 2003, 24: 895–902
Liang I, Shi Z. The information entropy rough entropy and knowledge granulation in rough set theory. International Journal of Uncertainty, Fuzziness and Knowledge-Based System, 2004, 12: 37–46
Yao Y Y, Zhong N. Granular computing using information table. In: Lin T Y, Yao Y Y, Zadeh L A, eds. Data Mining, Rough Sets and Granular Computing. Physica-Verlag, Heidelberg, 2000, 102–124
Yao Y Y. Modeling data mining with granular computing. In: Proceedings of the 25th Annual International Computer Software and Applications Conference, 2001, 638–643
Basak J, Das A. Hough transform network: a class of networks for identifying parametric structures. Neurocomputing, 2003, 51: 125–145
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Lu, G., Liang, D. Smart optical-fiber structure monitoring based on granular computing. Front. Mech. Eng. China 4, 462–465 (2009). https://doi.org/10.1007/s11465-009-0073-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11465-009-0073-2