Rusted beam model correction and damage identification method

Abstract

A rusted beam model correction and damage identification method relates to the technical field of safety risk assessment, and comprises the following steps: step 1, establishing a finite element model, performing sensitivity analysis on to-be-corrected parameters, and determining final corrected parameters according to a sensitivity analysis result; step 2, correcting the finite element model step by step according to an extreme learning machine algorithm improved based on a sparrow search algorithm; and step 3, according to the corrected finite element model, carrying out damage identification on the rusted beam according to an extreme learning machine algorithm improved based on a sparrow search algorithm. According to the method, the extreme learning machine algorithm improved based on the sparrow search algorithm is adopted to carry out model correction and model damage identification after corrosion on the model before corrosion, and the accuracy of finite element model correction output parameters and damage identification results is greatly improved.

Description

technical field [0001] The invention relates to the technical field of safety risk assessment, in particular to a corroded beam model correction and damage identification method. Background technique [0002] The main cause of failure of concrete structures is the corrosion of steel bars. Chloride ions in the external environment seriously threaten the durability of its structure, making the structure vulnerable to damage and even collapse, which has become a major hidden danger to life and property safety. With the continuous development of my country's sea-crossing bridges and coastal buildings and other building structures, many bridges and coastal buildings have been in the marine environment for a long time. At the same time, chlorine salt is widely used as a deicing agent in my country on winter roads in severe cold areas. There are a large number of corrosion phenomena of steel bars caused by chloride ion corrosion in China. [0003] The pre-corrosion model correctio...

AI Technical Summary

Problems solved by technology

[0006] 1. The process of this technical solution is relatively cumbersome and has high requirements for test equipment. The judgment of the feature points of the corrosion fatigue damage identification map still requires a certain learning cost, and the sensor needs to be buried inside the component to be tested along with the construction. Not suitable for existing monitoring methods without built-in sensor components

[0007] 2. For model correction before corrosion, usually all the parameters to be corrected are corrected at the same time, ignoring the sensitivity difference between parameters, which may cause the correction result to deviate from the real value; the suggested criterion for damage evaluation after corrosion is based on the post-disaster bearing capacity The degree of reduction determines the damage level. At this time, the determination result is more accurate and the reliability is higher. However, the acquisition of the post-disaster bearing capacity will inevitably cause certain damage or even destruction to the components, and there will be a certain degree of uncertainty if only one indicator is used to determine it. chance

[0008] 3. Although the literature also gives a set of simple reduction evaluation system for each factor through objective parameters such as bearing capacity, stiffness and corrosion rate after corrosion, there is no specific solution method, and the determination of the indicators has a certain degree of complexity

Images