摘要
角向磨光机的工作环境复杂,由于机械冲击、过载、电动机等发热体散热不畅等原因,都对角磨的工作可靠性和安全性有重要的影响,影响了角磨的正常使用。我国的电动工具行业起点低、设计方法落后,在实际工作中常出现停机冷却时间过长、电动机易受损坏等问题,严重的制约了我国电动工具行业的发展。为此,结合国家自然科学基金,编号为50705083和实际要求,本文以角向磨光机为例,对其散热性能和对灰尘的防止与排出性能进行了深入的研究,开展了角向磨光机多学科相结合的优化设计等研究工作。
全文共分六章,第一章阐明了课题研究背景及其意义,系统地总结了国内外在多学科设计优化的研究工作,总结了灵敏度分析方法和代理模型的现状,确定了本文的主要研究内容;第二章对多学科设计优化进行了论述;第三章对角向磨光机进行三维建模,仿真分析了其散热性能和对灰尘的防止与排出性能,确定了对性能影响较大的设计变量;第四章论述了灵敏度分析法,并对各子学科的设计变量进行灵敏度分析,确定对各子系统影响较大的设计变量;第五章在系统级分析的基础上构造目标函数,运用代理模型技术,分析对比三种代理模型,确定精度最高的一种方法,用遗传算法寻找全局最优解;第六章作为本文的结尾,对整篇文章进行了总结,并提出下一步研究工作的展望。
For the complex working condition of the angle grinder, many factors may affect the operation reliability and safety about the angle grinder, such as mechanical shock, overload and the poor heating flow. As domestic manufacturing industry of electricity tools started late, the starting point is low, and the design method is backward. During practical using, it often occurs that the cooling down time is too long; the motor is vulnerable to damage.To the end, in conjunction with national natural science foundation of China and the practical requirements. This thesis studies the performance of heat dissipation and dust of angle grinding machine, and carries out relevant research about the multidisciplinary design optimization.
This thesis includes six chapters. Chapter one presents the research background and significance of the topic and sums up the research work about the MDO at home and abroad and the work of sensitivity analysis and surrogate models. And at last it makes the main research content of this thesis; Chapter two discusses the working steps to MDO. Chapter three builds 3-d model of angle grinder, and do the simulation analysis to its thermal and dust performance to identify the design variables which have greater influence. Chapter four discusses the methods of sensitivity analysis; analyze the design variables of sub-disciplines to determine the important impact factors. Chapter five, objective function is constructed based on system level analysis, then applied the surrogate model, analysis three models, determine the most accurate model, and search the global optimal solution of this models with genetic algorithm. Chapter six makes the conclusion and gives research work of the next step.
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