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Evaluation of Bridge Condition Based on Fuzzy-neural Network

Author: CaoZhen
Tutor: HanQingHua
School: Tianjin University
Course: Structural Engineering
Keywords: Rural roads and bridges Technical state Fuzzy Neural Network MATLAB Blur Tool Box function ANFIS Assessment
CLC: U441
Type: Master's thesis
Year: 2009
Downloads: 82
Quote: 1
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Abstract


Tianjin most of the rural road bridge construction time earlier , simple structure , increasing degradation in the natural environment and the overload traffic load , aging and other factors of concrete structures under the action of their health status , the use of functional decline , serious affect driving security . In this context , the assessment on the situation of rural roads and bridges is particularly important. Fuzzy neural network fuzzy control and neural network -bound form , it can overcome the fuzzy control algorithm selection, degree of membership to determine the participating personnel subjective uncertainty and randomness , but also can avoid neural network weights are often not practical significance. In recent years , fuzzy neural network intelligent control the development of a hot spot , has been successfully used in aircraft, automobiles, engineering and other fields . This article is based on fuzzy neural network theory, Tianjin rural highway bridge condition assessment , do the following : 1 ) with the help of rural roads and bridges Tianjin rural highway departments to carry out investigation work , in-depth bridge survey the scene , summed Tianjin City, rural roads and bridges cracks , abutments irregularity, cracks in the superstructure , substructure cracks and other major diseases , and the cause of the disease were analyzed ; 2) from the Department of the bridge deck , superstructure , substructure , and subsidiary structure , combination of disease characteristics , select four aspects subsystem indicators , the establishment of a two - level bridge condition assessment model ; 3) on the basis of the present bridges assessment hierarchical model proposed in this paper based on fuzzy neural network bridge state of the art assessment methods . Adaptive fuzzy neural network simulation characteristics as input to the evaluation score the subsystem evaluation model , and then used as an input to the technical state of the assessed value of each subsystem to establish a bridge state of the art integrated assessment models , thus draw bridge state of the art results, and according to the given criteria to determine the level of the technical state of the bridge .

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CLC: > Transportation > Road transport > Bridges and Culverts > Structural principles, structural mechanics
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