Reformation Design Of The Health Monitoring System And Development Of A Structural Damage Identification Method For A Sea-crossing Suspension Bridge

The bridge health monitoring system is a comprehensive intelligent platform system integrating structural monitoring,condition assessment,safety early warning and maintenance planning.It is an effective means to obtain and process data from the bridge operation status,and evaluate the structural status and safety,so as to formulate an economic,reasonable,safe and reliable maintenance plan.However,most of the systems only focus on data collection,and do not deal with the massive data collected.The user interface is not clear,so it is difficult to provide help for bridge maintenance.At the same time,using the health monitoring results to identify structural damage and accurately and effectively evaluate the structural health status is another important task of bridge maintenance and management.In order to solve the above problems,this paper takes a cross-sea suspension bridge as the engineering background,analyzes the problems of the original health monitoring system of a sea-crossing suspension bridge on the basis of the existing health monitoring system,and optimizes the design of the health monitoring system of a sea-crossing suspension bridge.Build a modern and high-level health monitoring cloud platform to solve the problems of low data application efficiency and non intuitive user interface of a sea-crossing suspension bridge monitoring system.On the other hand,in view of the difficulty of applying the traditional damage identification theory in various health monitoring systems,this paper proposes a structural damage identification method based on vehicle bridge coupling analysis and neural network.This method can use the acceleration response collected by the health monitoring system to identify the bridge damage,and solve the problem that the traditional damage identification method is difficult to apply to the health monitoring system.This paper mainly includes the following six parts:(1)The first chapter summarizes the research status of bridge health monitoring system,summarizes the research status of structural damage identification and its development status at home and abroad,and discusses the current research direction and hot spots.(2)The second chapter analyzes the health monitoring system of a sea-crossing suspension bridge before reconstruction,and finds the direction of improvement.(3)In the third chapter,the bridge health monitoring system of a sea-crossing suspension bridge is improved in both hardware and software.In the hardware,the hardware equipment that fails or fails is overhauled,upgraded and replaced.In terms of software,the system can only realize the real-time collection and storage of sensor monitoring data,and can not be visually inspected and utilized in time.It is inefficient and can not meet the requirements of efficient and reliable monitoring.A modern high-level health monitoring cloud platform is developed.(4)The fourth chapter summarizes the basic theory and formula of vehicle bridge coupling,and the basic principle and formula of neural network.A structural damage identification method based on vehicle bridge coupling analysis and neural network is proposed.Using Python language to program neural network algorithm.(5)In Chapter five,a simple supported beam bridge model is established to test the feasibility of structural damage identification method based on vehicle bridge coupling analysis and neural network.Considering the influence of noise,the noise resistance of this method is tested.A finite element model of a sea-crossing suspension bridge is established to test the damage identification effect of this method for complex models.(6)The sixth chapter summarizes the full text and puts forward conclusions and prospects.