A set expansion type reliability optimization method, system and device and a medium

An optimization method and reliability technology, applied in special data processing applications, instruments, electrical and digital data processing, etc., can solve problems such as restricting the application of intelligent stochastic optimization methods, unable to provide search space, etc., to solve restrictive factors and facilitate solutions. , to ensure the effect of optimizing efficiency

Active Publication Date: 2019-06-14
NAVAL UNIV OF ENG PLA
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  • Abstract
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  • Application Information

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Problems solved by technology

The intelligent optimization methods developed in recent years are all stochastic optimization methods. The optimization search process must have a certain random search space, and (hype

Method used

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  • A set expansion type reliability optimization method, system and device and a medium
  • A set expansion type reliability optimization method, system and device and a medium
  • A set expansion type reliability optimization method, system and device and a medium

Examples

Experimental program
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Effect test

Embodiment 1

[0095] Embodiment one, as figure 1 As shown, an optimization method for set extended reliability includes the following steps:

[0096] S1: Establish a convex set model describing structural uncertainty, and perform standardized transformation on the convex set model to obtain a standardized convex set model;

[0097] S2: According to the standardized convex set model, construct a set-extended reliability optimization solution model with constraints, and convert the optimization solution model with constraints into a target unconstrained optimization solution model;

[0098] S3: Based on the particle swarm optimization method, optimize and solve the target unconstrained optimization solution model to obtain the extended reliability of the target set.

[0099] In this embodiment, the standardized convex set model is obtained after the standardized transformation of the convex set model, which is convenient for analysis according to the standardized variable space formed by the...

Embodiment 2

[0194] Embodiment two, such as Figure 7 As shown in , an optimization system that integrates extended reliability includes a modeling module, a constraint transformation module and an optimization solution module;

[0195] The modeling module is used to establish a convex set model describing structural uncertainty, and perform standardized transformation on the convex set model to obtain a standardized convex set model;

[0196] The constraint conversion module is used to construct a set-extended reliability optimization solution model with constraints according to the standardized convex set model, and convert the optimization solution model with constraints into a target unconstrained optimization solution model;

[0197] The optimization solution module is configured to optimize and solve the target unconstrained optimization solution model based on the particle swarm optimization method to obtain the extended reliability of the target set.

[0198] The present invention...

Embodiment 3

[0199]Embodiment 3. Based on Embodiment 1 and Embodiment 2, this embodiment also discloses an optimization device for integrated extended reliability, including a processor, a memory, and a memory stored in the memory and operable on the processor. A computer program on the computer program, when the computer program runs, it realizes as figure 1 The following steps are shown:

[0200] S1: Establish a convex set model describing structural uncertainty, and perform standardized transformation on the convex set model to obtain a standardized convex set model;

[0201] S2: According to the standardized convex set model, construct a set-extended reliability optimization solution model with constraints, and convert the optimization solution model with constraints into a target unconstrained optimization solution model;

[0202] S3: Based on the particle swarm optimization method, optimize and solve the target unconstrained optimization solution model to obtain the extended reliabi...

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Abstract

The invention relates to a set expansion type reliability optimization method, system and device and a medium, and the method comprises the steps of building a convex set model describing the uncertainty of a structure, and carrying out the standardized transformation of the convex set model, and obtaining a standardized convex set model; according to the standardized convex set model, constructing a constraint-containing optimization solution model with set expansion type reliability, and converting the constraint-containing optimization solution model into a target unconstrained optimizationsolution model; and based on a particle swarm optimization method, carrying out optimization solution on the target unconstrained optimization solution model to obtain the target set expansion type reliability. According to the method, a constraint-containing optimization solving problem is converted into an unconstrained optimization solving problem; the set expansion type reliability optimization method is combined with the particle swarm optimization method to optimize and solve the set expansion type reliability, so that the optimization efficiency is guaranteed, the restrictive factors in the particle swarm optimization method are solved, the method is rigorous in theory, and the accurate, efficient and high-operability set expansion type reliability optimization solution is achieved.

Description

technical field [0001] The present invention relates to the field of structural reliability measurement, in particular to an optimization method, system, device and medium of integrated extended reliability. Background technique [0002] In the structural reliability analysis and design, due to the complexity of the structural system itself and the limitations of people's understanding, there are many uncertainties, which often play a crucial role in the performance and response of the structure. Therefore, it is necessary to deal with these uncertainties reasonably and quantitatively. The traditional description of these uncertainties is based on probability theory, but due to the limitations of probability theory, non-probability reliability theory has been developed in recent years. The mathematical basis of non-probability reliability theory is the convex set model. Through the convex set The "worst case" of the combination of parameters in the model is used to predict ...

Claims

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Application Information

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IPC IPC(8): G06F17/50
Inventor 孙文彩杨自春杨立国王磊
Owner NAVAL UNIV OF ENG PLA
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