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Optimizing method for multi-flexible dynamic structure of bridge crane

A technology of bridge cranes and optimization methods, which is applied in the direction of neural learning methods, instruments, biological neural network models, etc., can solve problems such as difficult optimization of flexible components, and achieve the effect of small amount of calculation

Active Publication Date: 2016-12-07
NANJING UNIV OF SCI & TECH
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Problems solved by technology

[0005] The purpose of the present invention is to provide a multi-flexible-body dynamic structure optimization method for bridge cranes, which solves the problem that flexible components are difficult to optimize in the multi-flexible-body dynamics calculation and structural dynamics optimization of crane construction machinery

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  • Optimizing method for multi-flexible dynamic structure of bridge crane
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  • Optimizing method for multi-flexible dynamic structure of bridge crane

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Embodiment 1

[0058] combine Figure 1 to Figure 4 , the embodiment 1 of the present invention provides a kind of bridge crane multi-flexible body dynamic structure optimization method, the method steps are as follows:

[0059] Step S1, determine the optimization goal according to the optimization requirements. The design of the crane pursues the minimum mass, which is reflected in the calculation problem model as the minimum volume. The fifth-order common frequency is the maximum value as possible, so the volume of the bridge crane, the fifth-order natural frequency and its maximum stress are taken as the optimization objective function. Structural sensitivity analysis is performed on each structural parameter that affects the optimization objective, so as to select appropriate design variables. The research object of the present embodiment is the bridge crane structure system, so the main design variable is the section size of each girder. According to the results of structural sensitiv...

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Abstract

The invention discloses an optimizing method for a multi-flexible dynamic structure of a bridge crane. A multi-flexible dynamic technology, an optimal Latin hypercube algorithm, a neural network model optimized through particle swarm optimization, a NSGA-II algorithm and Maxi-min criterion are adopted for solving the problem of difficulty in optimizing the flexible part in the previous multi-flexible dynamic optimization process. According to the method, design variable values in a dynamic model are changed by altering a finite element parameter for changing modal neutral file information; a BP neural network optimized by the particle swarm optimization is introduced for establishing a surrogate model; the non-linear relationship between the design variable values of the flexible body and the optimized target value in the multi-flexible dynamic model is fit; the NSGA-II genetic algorithm is adopted for performing multi-target optimization on the surrogate model, thereby acquiring a Pareto solution set; the Maxi-min criterion is adopted for finding a feasible solution considering all the optimized targets.

Description

technical field [0001] The invention belongs to the field of structural dynamics optimization research, in particular to a multi-flexible dynamics structure optimization method of an overhead crane. Background technique [0002] Mechanical optimization design is to optimize the design parameters of a certain mechanical design under various specified design constraints, so that one or several design indicators can obtain the optimal value. The "optimum value" or "best value" in engineering design refers to the most satisfactory and appropriate value obtained under various design objectives and constraints. As one of the main equipment for lifting and aerial handling in material handling machinery, the bridge crane industry is also constantly improving its design mode with the development of the times. The traditional experience-based design mode has gradually faded out of the hoisting machinery industry. In the design scope of the industry, designers have begun to work towar...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06N3/08
CPCG06F30/17G06F30/367G06F2111/04G06N3/084G06N3/086
Inventor 萧辉杨国来孙全兆葛建立
Owner NANJING UNIV OF SCI & TECH
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