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动力卡瓦的结构设计及其参数优化
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摘要
在目前国内修井作业过程中,井口操作还是以手工操作为主,此种作业工人劳动强度大,容易造成重大工程和人身事故。因此,国内出现了大量的自动化井口设备,动力卡瓦是自动化修井作业设备的重要组成部分。
     首先,介绍了国内外卡瓦的现状以及发展过程,总结了动力卡瓦结构设计要点。其次,建立单轴载荷下金属的应力—应变特征及其理想化模型,讨论了金属典型基本应力—应变关系;根据建立的模型推出一般应力状态的初始屈服条件,Tresca准则和Von Mises准则;推出了屈服条件的函数,提出了三种描述强化材料的加载面形成方法。
     介绍了概率法机械设计特点,两种可靠度的一般表达式,即应力强度为指数分布和正态分布,以及受不稳定变应力疲劳强度的计算。
     最后,本文对卡瓦主要部件进行了有限元分析和动力学分析。讨论了卡瓦牙的几个重要几何参数与卡紧效果的关系,其中包括:卡牙张角、卡牙高度、卡牙间距、吃入深度;讨论了卡瓦体、卡瓦座的失效形式以及影响卡瓦工作可靠性的因素;利用正交优化法进行了各种组合的优化,并得出较为理想的优化组合。
In the current domestic workover operations process, the Wellhead operations is mainly manual operations, the labor intensity of workers is too large, easily lead to major projects and personal accident. Thus, in China appeared a large number of automated wellhead equipments. Power Slip is an important part of the device.
     Firstly, This paper introduces the status of Slips, and the development process, summarizes the design features of the power slips.
     Secondly, establish of the metal under uniaxial loading the stress - strain characteristics and idealized models, and discuss a typical basic metal stress - strain relationship; according to the established model ,reach the general state of stress the initial yield condition,Tresca criterion and Von Mises criterion; Introduced a function of subsequent yield condition, and proposed three kinds of loading method that describing the formation of reinforced materials.
     Describes the features of probability method mechanical design,two kinds of reliability of the general expression, the stress intensity for the exponential distribution and normal distribution, and the calculation of affected by the unstable alternating stress fatigue strength.
     Finally, This paper analyzes the main parts of Power Slips, using the finite element analysis and Msc.Adams,including: slips tooth angle, slips tooth height, slips tooth spacing, eating into the pipe’s depth; discussed the slip body, slip seat invalidation modality and factors affecting the reliability of slip work; optimize a variety of combination using Orthogonal optimization method.
引文
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