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题名: An artificial immune pattern recognition approach for damage classification in structures
作者: Zhou Y(周悦) ; Tang S(唐世) ; Zang CZ(臧传治) ; Zhou, Rui
作者部门: 工业信息学研究室
会议名称: 2nd International Conference of Electrical and Electronics Engineering, ICEEE 2011
会议日期: December 1-2, 2011
会议地点: Macau, China
会议主办者: International Industrial Electronics Center
会议录: Lecture Notes in Electrical Engineering
会议录出版者: Springer Verlag
会议录出版地: Heidelberg, Germany
出版日期: 2011
页码: 11-17
收录类别: EI
ISSN号: 1876-1100
ISBN号: 978-3642260001
关键词: Damage detection ; Electronics engineering ; Electronics industry ; Industrial applications ; Information technology ; Learning algorithms ; Pattern recognition ; Research
摘要: Structural Health Monitoring (SHM) is one of the research topics that have received growing interest in research communities. While a lot of efforts have been made in detecting damages in structures, very few researches have been conducted for the structure damage classification problem. This paper presents an artificial immune pattern recognition (AIPR) approach for the damage classification in structures. An AIPR-based Structure Damage Classifier (AIPR-SDC) has been developed, which incorporates several novel characteristics of the natural immune system. The immune learning algorithm can remember various data patterns by generating a set of memory cells that contain representative feature vectors for each pattern, which are extracted from the compressed data using the auto regression exogenous (ARX) algorithm. The AIPR-SDC approach has been tested using a benchmark structure proposed by the IASC-ASCE Structural Health Monitoring Task Group. The test results show the feasibility of using the AIPR-SDC method for the structure damage classification. © 2012 Springer-Verlag.
产权排序: 2
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/9893
Appears in Collections:工业信息学研究室_会议论文

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