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An artificial immune pattern recognition approach for damage classification in structures
Zhou Y(周悦); Tang S(唐世); Zang CZ(臧传治); Zhou, Rui
Department工业信息学研究室
Conference Name2nd International Conference of Electrical and Electronics Engineering, ICEEE 2011
Conference DateDecember 1-2, 2011
Conference PlaceMacau, China
Author of SourceInternational Industrial Electronics Center
Source PublicationLecture Notes in Electrical Engineering
PublisherSpringer Verlag
Publication PlaceHeidelberg, Germany
2011
Pages11-17
Indexed ByEI
EI Accession number20120414714539
Contribution Rank2
ISSN1876-1100
ISBN978-3-642-26000-1
KeywordDamage Detection Electronics Engineering Electronics Industry Industrial Applications Information Technology Learning Algorithms Pattern Recognition Research
AbstractStructural 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.
Language英语
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/9893
Collection工业信息学研究室
Affiliation1.Faculty of Information and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China
2.No. 3 Laboratory, Shenyang Institute of Automation, Chinese Academy of Sciendes, Shenyang 110016, China
Recommended Citation
GB/T 7714
Zhou Y,Tang S,Zang CZ,et al. An artificial immune pattern recognition approach for damage classification in structures[C]//International Industrial Electronics Center. Heidelberg, Germany:Springer Verlag,2011:11-17.
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