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확률신경망에 기초한 교량구조물의 손상평가

Title
확률신경망에 기초한 교량구조물의 손상평가
Other Titles
Probabilistic Neural Network-Based Damage Assessment for Bridge Structures
Author
조효남
Keywords
Probabilistic Neural Network; Damage Assessment; Mode Shape
Issue Date
2002-10
Publisher
한국구조물진단유지관리공학회
Citation
한국구조물진단유지관리공학회 논문집, v. 6, issue. 4, page. 169-179
Abstract
This paper presents an efficient algorithm for the estimation of damage location and severity in structure using Probabilistic Neural Network (PNN). Artificial neural network has been being used for damage assessment by many researchers, but there are still some barriers that must be overcome to improve its accuracy and efficiency. The major problems with the conventional neural network are the necessity of many training data for neural network learning and ambiguity in the relation of neural network architecture with convergence of solution. In this paper, PNN is used as a pattern classifier to overcome those problems in the conventional neural network. The basic idea of damage assessment algorithm proposed in this paper is that modal characteristics from a damaged structure are compared with the training patterns which represent the damage in specific element to determine how close it is to training patterns in terms of the probability from PNN. The training pattern that gives a maximum probability implies that the element used in producing the training pattern is considered as a damaged one. The proposed damage assessment algorithm using PNN is applied to a 2-span continuous beam model structure to verify the algorithm.
URI
https://www.koreascience.or.kr/article/JAKO200217061964135.pagehttps://repository.hanyang.ac.kr/handle/20.500.11754/157715
ISSN
2234-6937; 2287-6979
Appears in Collections:
COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > CIVIL AND ENVIRONMENTAL ENGINEERING(건설환경공학과) > Articles
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