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Damage Identification Method for Stochastic Structures Based on Genetic Algorithm and Static Measurement Data

A technology of structural damage and genetic algorithm, applied in the direction of electrical digital data processing, special data processing applications, calculations, etc., can solve problems such as non-optimal results and misjudgment, so as to reduce misjudgment, increase stability and reliability , the effect of fast convergence speed

Active Publication Date: 2016-01-06
WUHAN UNIV OF TECH
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  • Abstract
  • Description
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  • Application Information

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Problems solved by technology

However, this method also has the following disadvantages: (1) sometimes misjudgment occurs; (2) the obtained results are often not optimal

Method used

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  • Damage Identification Method for Stochastic Structures Based on Genetic Algorithm and Static Measurement Data
  • Damage Identification Method for Stochastic Structures Based on Genetic Algorithm and Static Measurement Data
  • Damage Identification Method for Stochastic Structures Based on Genetic Algorithm and Static Measurement Data

Examples

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Embodiment 1

[0071] Example 1: Damage identification for a simply supported beam structure

[0072] a. The first step: through the random structure damage identification method based on static measurement data, the statistical characteristics of the random structure damage index are initially obtained α 0 , α 1 , α 2

[0073] Such as figure 1 For the simply supported beam with rectangular cross-section shown, the parameters of the given material are: beam length l=5.0m, cross-sectional area A=0.3m×0.8m, moment of inertia I=0.0128m 4 , density ρ=2.5×10 3 Kg / m 3. The simply supported beam is discretized into 10 equally spaced planar beam units, each unit node has two degrees of freedom of vertical deflection and rotation angle, and there are 20 degrees of freedom in total. Assume that the randomness of the stiffness in the initial model of simply supported beams is caused by the uncertainty of the elastic modulus, and the mean value of the elastic modulus is E=2.8×10 10 Pa, and assum...

Embodiment 2

[0090] Example 2: Damage identification for a continuous beam structure

[0091] Such as Figure 5 For the three-span continuous beam with rectangular section shown, the parameters of the given material are: beam length l=15.0m, cross-sectional area A=0.3m×0.8m, moment of inertia I=0.0128m 4 , density ρ=2.5×10 3 Kg / m 3 . The beam is discretized into 30 equally spaced planar beam units, each unit node has two degrees of freedom of vertical displacement and rotation angle, a total of 62 degrees of freedom, and then the influence of the degree of freedom of rotation angle can be removed by the agglomeration method. Assume that the elastic modulus of the initial stiffness of the continuous beam is random, and assume that the elastic modulus of each span unit of the continuous beam is a random variable, a total of three independent random variables.

[0092] Working condition one: the modulus of elasticity of the beam unit 16 is reduced by 20%; only considering the initial mode...

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Abstract

The invention relates to an identification method of random structural damage based on genetic algorithm and static force measurement data. The identification method of the random structural damage based on the genetic algorithm and the static force measurement data comprises the following steps: (1) preliminarily obtaining statistical properties of random structural damage indexes; (2) defining the probability of unit damage as the random rigidity before occurrence of the damage or the probability that an elastic modulus Kai is larger than Kdi; (3) introducing damage probability indexes, determining several units of the damage probability indexes as non-damage units, and conducting corresponding adjustment on the statistical properties of the damage indexes; (5) going back to the governing equation of the initial damage identification in the step (1), and obtaining the objective function of the structural damage indexes after rearranging; and (6) solving the minimum value of the objective function in the step (5) by means of the genetic algorithm, and obtaining the statistical properties of the damage indexes. The identification method of the random structural damage based on the genetic algorithm and the static force measurement data has the advantages that multiple damage identification of different damage degrees can be carried out due to the fact that the genetic optimized algorithm has little limit on the type, the quantity and the size of the parameter.

Description

technical field [0001] The invention belongs to building structure detection technology, in particular to a random structure damage identification method based on genetic algorithm and static force measurement data. Background technique [0002] With the rapid development of housing and bridge construction in our country, large-span, high-rise and complex engineering structures continue to emerge. Due to the continuous adoption of new materials and new processes, the safety and durability of these structures have attracted great attention from relevant departments and researchers. In order to ensure the normal operation, safety and reliability of these important projects, a complete monitoring and maintenance mechanism must be established. In addition, natural or man-made disasters such as earthquakes, typhoons, and fires will cause major damage to engineering structures, and it is also very important to evaluate the residual bearing capacity of structures after disasters a...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/00G06N3/12
Inventor 张衡黄斌张林林朱芙蓉舒星王广李伟
Owner WUHAN UNIV OF TECH
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