桁架式桥梁检测车臂架系统结构分析及优化设计
发布时间：2018-11-03 14:40
【摘要】：桥梁检测车是一种装备有桥梁检测仪器,为桥梁检测人员在检测过程中提供检测作业平台,用于流动检测和维修作业的专用汽车。臂架结构轻量化可以改善桥梁检测车整车液压工作系统的动力特性,降低车载平衡配重以及提高桥梁检测车整车系统安全性。平行底座结构是由板材焊接而成的框架结构,其在实际工作过程中受到臂架系统相关机构的空间限制,受力情况较为复杂,选取危险工况,对其进行疲劳寿命计算和优化设计对提高桥架检测车的使用寿命具有重要意义。 论文以某16m桁架式桥梁检测车上车臂架结构系统为研究对象,结合有限元法、神经网络与遗传算法,完成对臂架系统中的桁架检测臂结构的轻量化设计；根据疲劳可靠性理论,试验设计以及响应面近似模型等方法,借助ISIGHT软件集成自动化手段,完成了臂架结构的中关键部件平行底座的结构改善疲劳寿命的优化设计。 1.在ANSYS Workbench中建立桥梁检测车上车臂架系统结构有限元仿真模型,通过静力分析对转台机构各组件和桁架检测臂部分进行强度与刚度校核； 2.在ANSYS中建立桁架检测臂结构的参数化有限元仿真模型,采用正交试验法建立样本数据,完成对BP神经网络的训练,建立设计参数与目标向量之间的映射关系,以结构重量最轻为优化目标,利用遗传算法进行全局寻优。 3.以平行底座结构作为疲劳分析关键部件,借助ANSYS Workbench中的疲劳分析模块Fatigue Module对平行底座进行应力寿命分析,计算结构疲劳寿命,初步确定结构中容易发生疲劳关键部位。 4.在疲劳分析基础上,运用试验设计与响应面模型方法,建立结构设计变量空间内的样本点对结构自重和疲劳寿命的响应面模型,借助ISIGHT优化软件的自动集成功能搭建结构优化流程,采用多岛遗传算法在响应面模型上进行寻优计算。 通过对桥梁检测车臂架结构的轻量化研究以及关键部件的抗疲劳优化设计,可以改善桥梁检测车的工作性能及其使用寿命,降低设计以及制造过程中的成本,提高了产品设计的效率和质量,对于类似结构的的设计与研发具有一定的参考价值。
[Abstract]:Bridge detection vehicle is a kind of special vehicle equipped with bridge detection instrument, which provides detection platform for bridge detection personnel in the detection process, and is used for mobile detection and maintenance work. The light weight of the arm structure can improve the dynamic characteristics of the hydraulic working system of the whole vehicle of the bridge detection vehicle, reduce the balance weight of the vehicle and improve the safety of the whole vehicle system of the bridge detection vehicle. Parallel base structure is a frame structure which is welded by sheet metal. It is limited by the space of the relevant mechanism of the boom system in the actual working process, and the stress situation is more complex, so the dangerous working condition is selected. It is of great significance to calculate and optimize the fatigue life of the bridge detection vehicle. In this paper, a 16m truss bridge detection vehicle boom structure system is taken as the research object, combining finite element method, neural network and genetic algorithm, the lightweight design of the truss detection arm structure in the boom system is completed. Based on fatigue reliability theory, experimental design and response surface approximation model, and with the help of ISIGHT software integrated automation, the optimization design for improving fatigue life of the parallel base of the key components of the boom structure is completed. 1. The finite element simulation model of the bridge detection vehicle boom system is established in ANSYS Workbench, and the strength and stiffness of the components of the turntable mechanism and the truss detection arm are checked by static analysis. 2. The parameterized finite element simulation model of truss detection arm structure is established in ANSYS. The orthogonal test method is used to establish the sample data, to complete the training of BP neural network, and to establish the mapping relationship between design parameters and target vectors. Taking the least weight of structure as the optimization objective, the genetic algorithm is used for global optimization. 3. Taking the parallel base structure as the key component of fatigue analysis, the stress life of parallel base is analyzed with the help of the fatigue analysis module Fatigue Module in ANSYS Workbench, and the fatigue life of the structure is calculated, and the fatigue key parts of the structure are preliminarily determined. 4. On the basis of fatigue analysis, the response surface model of structural weight and fatigue life of sample points in structural design variable space is established by means of test design and response surface model. With the help of the automatic integration function of the ISIGHT optimization software, the structure optimization process is built, and the multi-island genetic algorithm is used for the optimization calculation on the response surface model. Through the lightweight research of the bridge detection vehicle's arm structure and the anti-fatigue optimization design of the key parts, the working performance and service life of the bridge detection vehicle can be improved, and the cost in the design and manufacture process can be reduced. It improves the efficiency and quality of product design, and has a certain reference value for the design and development of similar structures.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U446.3
本文编号：2308087
[Abstract]:Bridge detection vehicle is a kind of special vehicle equipped with bridge detection instrument, which provides detection platform for bridge detection personnel in the detection process, and is used for mobile detection and maintenance work. The light weight of the arm structure can improve the dynamic characteristics of the hydraulic working system of the whole vehicle of the bridge detection vehicle, reduce the balance weight of the vehicle and improve the safety of the whole vehicle system of the bridge detection vehicle. Parallel base structure is a frame structure which is welded by sheet metal. It is limited by the space of the relevant mechanism of the boom system in the actual working process, and the stress situation is more complex, so the dangerous working condition is selected. It is of great significance to calculate and optimize the fatigue life of the bridge detection vehicle. In this paper, a 16m truss bridge detection vehicle boom structure system is taken as the research object, combining finite element method, neural network and genetic algorithm, the lightweight design of the truss detection arm structure in the boom system is completed. Based on fatigue reliability theory, experimental design and response surface approximation model, and with the help of ISIGHT software integrated automation, the optimization design for improving fatigue life of the parallel base of the key components of the boom structure is completed. 1. The finite element simulation model of the bridge detection vehicle boom system is established in ANSYS Workbench, and the strength and stiffness of the components of the turntable mechanism and the truss detection arm are checked by static analysis. 2. The parameterized finite element simulation model of truss detection arm structure is established in ANSYS. The orthogonal test method is used to establish the sample data, to complete the training of BP neural network, and to establish the mapping relationship between design parameters and target vectors. Taking the least weight of structure as the optimization objective, the genetic algorithm is used for global optimization. 3. Taking the parallel base structure as the key component of fatigue analysis, the stress life of parallel base is analyzed with the help of the fatigue analysis module Fatigue Module in ANSYS Workbench, and the fatigue life of the structure is calculated, and the fatigue key parts of the structure are preliminarily determined. 4. On the basis of fatigue analysis, the response surface model of structural weight and fatigue life of sample points in structural design variable space is established by means of test design and response surface model. With the help of the automatic integration function of the ISIGHT optimization software, the structure optimization process is built, and the multi-island genetic algorithm is used for the optimization calculation on the response surface model. Through the lightweight research of the bridge detection vehicle's arm structure and the anti-fatigue optimization design of the key parts, the working performance and service life of the bridge detection vehicle can be improved, and the cost in the design and manufacture process can be reduced. It improves the efficiency and quality of product design, and has a certain reference value for the design and development of similar structures.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U446.3
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