滑动轴承轴心轨迹测试及控制算法研究

发布时间：2018-02-11 18:50

本文关键词： 滑动轴承轴承系统测试 xPC物理仿真　出处：《山东大学》2012年硕士论文　论文类型：学位论文

【摘要】：非圆异型截面结构可以显著提高零件的性能及其使用寿命,所以其加工在机械制造行业中占据着一个很重要的地位,但零件的加工是难点所在。本文以四油腔动静压混合轴承系统的主轴运动轨迹控制为出发点,研究了转子运动轨迹的主动控制技术,以期为非圆异型机械零件的加工提供一种新方法,并相应的进行了实验设计与搭建、测试,相关理论的模型分析、仿真以及实验验证。本文通过控制轴颈的主动运动,为实现非圆异型机械零件的加工开辟新的新途径。其实现思路是通过主动伺服节流控制技术,实时调节流入动静压混合轴承油腔的流量和压力,并影响轴承封油面上的油膜压力分布,得到可控的油膜合力以达到控制主轴定轨迹运动的目的。对轴承系统进行了研究,推导出了静压时含有回油槽的四油腔轴承油膜压力分布Reynolds方程,推导了油膜厚度方程。并用差分方法对油膜压力分部进行了计算,并在不同偏心率下,计算了合力,做出了压力分布图形。设计了轴颈位移测试试验台,实验中涉及到了多个模块：液压模块,滑动轴承模块测试,计算机数据采集模块。完成了对电容位移传感器的标定、Endevco8150B-2000型压阻传感器9针连线的焊接,及其实验台的搭建。通过实验采集了轴颈在不同转速下的位移,及其不同转速下的油腔压力,对所采集的电信号进行了傅里叶分析及其滤波处理,并给出了处理后信号的时域和频域图形。研究了动静压混合轴承系统的控制方法,对一些控制理论进行了详细讲述,并在simulink中搭建了PID模型,编写了基于BP神经网络的PID控制算法,对系统模型进行仿真实验。仿真实验表明,基于BP神经网络的PID控制算法,在动静压轴承的仿真实验中,有着较好的效果,精度大于相应的PID控制。在本文的最后一章,设计了滑动轴承液压主动控制的系统图形,采用基于xPCTarget的硬件在回路的仿真实验,对滑动轴承转子轨迹实时控制进行了设计。搭建了xPC Target仿真实验平台,提出了xPC启动盘的多种制作方法。
[Abstract]:Non circular cross-section structure of parts can significantly improve the performance and service life, so the machining in the mechanical manufacturing industry plays a very important role, but the part machining is difficulty. Spindle motion trajectory control the bearing system with four oil cavity movement as the starting point, the research of active control technology the rotor trajectory, for noncircular machining to provide a new method, and the corresponding to experimental design and build, test, correlation analysis model, simulation and experimental verification.
By controlling the active movement of the journal, opened up a new method for the realization of noncircular machining. The idea is that through active throttle servo control technology, real-time adjustment into the hybrid bearing oil cavity flow and pressure, and the influence of oil film pressure bearing oil seal surface on the distribution of oil film the ability to control the controllable spindle fixed trajectory. We studied the bearing system, four oil bearing oil film pressure distribution of Reynolds equation is derived for the static pressure containing oil return tank, oil film thickness equation is deduced. On the oil film pressure segment was calculated using the differential method, and under different eccentricity, calculate the force, make the pressure distribution graph.
The design of the axial displacement experiment test platform of neck, involves multiple modules: Hydraulic module, sliding bearing module test, the computer data acquisition module. Complete calibration of the capacitive displacement sensor, Endevco8150B-2000 type welding pressure resistance sensor 9 pin connection, and build the experimental platform. Through the experiment collected the displacement of the shaft neck at different speeds, and different speed of the oil cavity pressure, the electrical signal collected by Fourier analysis and filtering, and gives the time domain and frequency domain graph signal processing.
Research on the control method of the hybrid bearing system, the control theory in detail, and set up the PID model in Simulink, preparation of the BP neural network PID control algorithm based on the simulation model of the system. Simulation results show that based on BP neural network PID control algorithm in the simulation experiment bearing, has good effect, accuracy is higher than the corresponding PID control.
In the last chapter of this paper, the design of active control of sliding bearing hydraulic system graphics, using xPCTarget based hardware in the loop simulation, real-time control of the sliding bearing rotor trajectory is designed. Set up the xPC Target simulation platform, proposed a variety of production methods for xPC boot disk.

【学位授予单位】：山东大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TH133.31

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