Bridge Damage Identification Based On Dynamic Parameters And BP Neural Network

With the development of China's national economy,the country's construction of bridges has also been greatly enhanced under the current "One Belt,One Road" joint construction of the strategic guidelines for safe and efficient transportation and the demand for transportation.As the bridge structure is subject to frequent loads,external environment and human factors,damage will occur inside the bridge structure,which poses a great threat to the safe operation of the bridge and the safety of people's lives and property.Therefore,the identification of bridge structure damage has become a research hotspot for engineers and technicians.Based on the existing theory of structural damage identification,this paper collects the actual project materials of bridge structure damage and collapse in China and abroad,and summarizes the damage identification methods currently applied in engineering practice,and summarizes the advantages and disadvantages of each method.In addition,this paper proposes a bridge structure step-by-step identification technology to effectively identify the damage location and damage degree of the simply supported beam bridge and arch bridge suspension,and verify the feasibility and effectiveness of the technology.Based on the dynamic characteristics of the bridge structure and the BP neural network,the location and damage degree of the bridge structure are effectively identified.This article is divided into four chapters.The first chapter introduces the background and significance of the damage identification research of bridge structure.Then the current research status of damage identification at home and abroad is introduced.Finally,the research work of this thesis is summarized.The second chapter introduces the theory of damage identification based on the dynamic characteristics of bridge structure and BP neural network.How to theoretically calculate the structural dynamic characteristic data obtained by finite element software,and extract the indicators for structural damage identification.At the same time,the appropriate dynamic parameters are selected as the input samples of BP neural network for network training.The third chapter introduces the theoretical derivation of these dynamic parameters based on the natural frequency,vibration mode and vertical displacement of the bridge structure,and obtains the damage indexes such as frequency difference,vibration modedifference and displacement difference curvature.At the same time,the three indicators are applied to the damage of the suspension beam of the simply supported beam bridge and the lower arch bridge.The results show that the damage identification based on the structural displacement difference curvature can accurately identify the damage location of the structure,but the degree of damage to the structure cannot be quantitatively determined.The fourth chapter introduces the basic principle of BP neural network and proposes a bridge step identification technology.Firstly,according to the damage index of structural displacement difference,the structure is identified for damage location.Then a MATLAB software is used to establish a three-layer BP neural network to identify the damage degree of the structure.The structural displacement difference curvature is used as the input vector of the network.The trained network effectively identifies the damage level of the boom damage location.