复杂工况齿轮传动轴微动磨损机理及其预测方法研究

发布时间：2018-03-14 17:44

本文选题：复杂工况　切入点：齿轮传动　出处：《湖南大学》2014年博士论文　论文类型：学位论文

【摘要】：齿轮组件作为动力机械中传递功率的主要部件，主要起到支承转动零件并传递运动、扭矩或弯矩的作用。由于齿轮啮合力的周期性变化导致齿轮轴产生扭转振动，从而导致齿轮轴肩与轴承内圈之间的粘着-滑动摩擦失稳现象。随着动力机械的持续运转，进而导致齿轮轴肩产生微动磨损。微动磨损普遍存在于各种机械装备的运行中，经常使零件的材料疲劳极限降低，是关键零部件失效的重要原因之一。在齿轮轴运转过程中，齿轮轴与轴承构成的运动系统具有内部参数变化、外加负载干扰、传动系统中的摩擦干扰和模型的不确定性以及非线性的复杂特点。其扭振具有转速低、承载大和干摩擦作用的典型特征，因此，齿轮轴在运转过程中不可避免地出现扭振幅值和噪声都大幅度增加的现象。以上影响因素导致齿轮轴运转的均匀性差，容易使齿轮轴与轴承之间的接触面产生微动，引起齿轮轴肩的微动磨损，严重的微动磨损造成齿轮轴的疲劳断裂，从而使复杂动力设备产生机械故障。因此，本文以国家“863”项目[2008AA11A116]、武器装备预研重点基金项目[9140A2011QT4801]和校企合作项目“减速器传动齿轮组件性能分析及优化设计研究”为依托，对复杂工况下齿轮传动机构中的齿轮轴肩与轴承接触面之间的微动磨损现象进行了机理与数值计算相结合的研究，主要研究工作如下：（1）建立了复杂工况齿轮组件有限元仿真模型，对齿轮轴肩微动现象进行了有限元仿真分析，得到齿轮轴肩的应力场、应变场和温度场的变化规律。仿真结果表明，接触应力随轴肩高度的增加而增大；轴向变形量和径向变形量随轴肩高度的增加而增大；齿轮轴肩的温度场和热应力场随着齿轮转速的增加而增大。（2）建立了复杂工况齿轮轴肩微动摩擦失稳模型和运动学方程，引入了摩擦失稳阻尼比，得到齿轮轴肩微动摩擦失稳的判别条件。在此基础上建立了齿轮轴肩微观扭振数值计算模型，分析了齿轮轴肩微观扭振随主要影响因素的变化规律。计算结果表明，载荷和转速是导致齿轮轴肩微动摩擦失稳的主要因素，并且齿轮轴肩的微动摩擦失稳是造成齿轮轴肩表面微动磨损的主要原因。（3）在复杂工况下齿轮传动机构中的齿轮轴肩与轴承接触特性和扭振摩擦运动特性分析的基础上，研究了复杂工况齿轮轴肩微动磨损机理并建立了齿轮轴肩微动磨损数学模型。在复杂工况齿轮轴肩微动磨损数值计算的基础上，，分析了预紧力矩、传递功率、过盈量、摩擦因数以及转速等主要因素对齿轮轴肩微动磨损的影响。（4）建立了复杂工况齿轮轴肩微动磨损影响因素模糊灰色关联分析模型，以多载荷工况下齿轮轴肩微动磨损量为模型的参考序列，多载荷工况下特征性能指标为模型的比较序列，对影响复杂工况齿轮轴肩微动磨损性能的特征指标重要性程度进行了模糊灰色关联度的研究。结果表明，即各主要因素对复杂工况齿轮传动轴微动磨损的影响程度为传递功率＞转速＞预紧力矩＞过盈量＞摩擦因数。（5）构建了复杂工况齿轮轴肩微动磨损量支持向量机预测方法，并采用自适应变权重粒子群优化算法对其进行优化。仿真与计算结果一致表明，基于自适应变权重粒子群优化算法支持向量机的复杂工况齿轮轴肩微动磨损预测方法的均方根误差为0.103%、平均相对误差为2.06%，表明该预测方法精度较高，并对其进行了分析和实验验证。
[Abstract]:The main components of the gear assembly as power machinery in power transmission, mainly to support the rotating parts and transfer movement, torque or bending moment. Due to cyclical changes in force in gear meshing gear shaft torsional vibration, resulting in adhesion gear shaft shoulder and the inner ring of the bearing between the sliding friction with continued instability phenomenon. Operation of power machinery, which led to the gear shaft shoulder to produce fretting. Fretting wear exists in all kinds of machinery and equipment operation, often make the fatigue limit of material parts is reduced, is one of the important reasons for the failure of key parts in the gear shaft. During the operation, the movement system of gear shaft and bearing which has internal parameter variations. Load disturbance, friction disturbance and model characteristics of complex transmission system's uncertainty and nonlinear. The torsional vibration with low speed, large bearing capacity and dry friction The typical characteristics of rubbing functions so the gear shaft in the process of operation inevitably greatly increased torsional vibration amplitude and noise phenomenon. These factors lead to the uniformity of gear shaft is poor, easy to make the contact surface between the gear shaft and bearing the fretting induced fretting wear of gear shaft shoulder, serious the fretting wear caused by fatigue fracture of the gear shaft, so that the complicated power equipment from mechanical failure.
Therefore, based on the national "863" project [2008AA11A116], "and the school enterprise cooperation project [9140A2011QT4801] weapon equipment pre Research Foundation reducer gear assembly performance analysis and optimization research is based on the design research on the fretting wear phenomenon between the gear shaft shoulder between the bearing and gear transmission mechanism under complicated working conditions in the calculated mechanism with the combination of numerical, the main research work is as follows:
(1) a complex working gear assembly finite element simulation model of gear shaft fretting phenomenon finite element simulation analysis was carried out, get the gear shaft shoulder of the stress field, strain field and temperature field were studied. The simulation results show that the contact stress increases with the increase of the height of the shoulder; the increase of axial deformation and the radial deformation of the shaft shoulder height with increasing; the temperature field and thermal stress field of the gear shaft with increasing gear speed increases.
(2) a complex working gear shaft shoulder fretting friction instability model and kinematics equation, introduced friction instability damping ratio, get the gear shaft shoulder fretting friction loss criterion. Stability is established based on the numerical calculation model of gear shaft micro torsional vibration analysis of the gear shaft torsional vibration change with micro shoulder law of the main factors. The calculation results show that the load and speed is the cause of gear shaft fretting friction loss of the main factors of instability, and the fretting friction gear shaft shoulder instability is caused by the gear shaft shoulder surface fretting wear is the main reason.
(3) based on the complex condition of gear transmission of the gear shaft shoulder and the bearing contact characteristics and torsional vibration of friction motion characteristics, study the complex condition of gear shaft shoulder fretting wear mechanism and establishes the mathematical model of the gear shaft. The fretting wear based on complicated gear shaft fretting wear numerical calculation on the shoulder and analysis of the pre tightening torque, transmission power, the amount of interference, the main factor affecting the friction factor and the rotational speed of the gear shaft shoulder of fretting wear.
(4) a complex working gear shaft shoulder and the influence factors of fretting wear of fuzzy grey correlation analysis model, with the reference sequence of gear shaft shoulder fretting wear volume model under multi load cases, sequence comparison of performance characteristics of multi load model, influence on the complex working condition of gear shaft shoulder fretting wear performance indicators the importance of fuzzy grey correlation. The results showed that the main factors influence on the fretting wear of complicated gear transmission shaft for power transmission > > > speed tightening torque interference, friction factor.
(5) the construction of complex working gear shaft shoulder fretting wear volume support vector machine prediction method, and the adaptive weight particle swarm optimization to optimize the algorithm. The simulation and calculation results show that the adaptive weight particle swarm optimization algorithm for support vector machine complex conditions of gear shaft fretting wear prediction method of RMS based on the error is 0.103%, the average relative error is 2.06%, indicating that the forecasting method has higher accuracy, and has carried on the analysis and experimental verification.

【学位授予单位】：湖南大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TH132.41;TH117

【参考文献】