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.
Thomas C, Parameswaran R, Kewal K S. Analysis of exposure of target activities in a sensornetwork with obstacles. SenSys, 2003
Lin M, Qing X L, Kumar A, Beard S J. Smart layerand smart suitcase for structural health monitoring application, smartstructure and materials. Proceedings ofSPIE, 2002, 4701: 167―176 doi: 10.1117/12.474698
Yao Y Y. Granular computing: basic issues and possible solutions, In: Paul P, ed. Proceedings of the 5th Joint Conferenceon Information Sciences. USA: Elsevier Publishing Company, 2000, 186―189
Pawlak. Rough sets. International Journal of Computer and Information Sciences, 1982, 11: 341―356 doi: 10.1007/BF01001956
Swiniarski R W, Andrzej S. Rough set methods in featureselection and recognition. Pattern RecognitionLetters, 2003, 24: 833―849 doi: 10.1016/S0167-8655(02)00196-4
Amitava R, Pa S K. Fuzzy discretization of featurespace for a rough set classifier. PatternRecognition Letters, 2003, 24: 895―902 doi: 10.1016/S0167-8655(02)00201-5
Liang I, Shi Z. The information entropy roughentropy and knowledge granulation in rough set theory. International Journal of Uncertainty, Fuzziness and Knowledge-BasedSystem, 2004, 12: 37―46 doi: 10.1142/S0218488504002631
Yao Y Y, Zhong N. Granular computing usinginformation 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 Softwareand 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 doi: 10.1016/S0925-2312(02)00605-7
