电子齿轮箱系统的研究与应用

论述了电子齿轮箱的概念、基本结构与运动特征 ,并就实现电子齿轮箱的方法以及电子齿轮箱的控制策略进行了分析与研究 ,最后列举了电子齿轮箱传动在机床内联传动与连续生产系统中的若干应用。     

Determination of Turboprop Reduction Gearbox System Fatigue Life and Reliability

Two computational models to determine the fatigue life and reliability of a commercial turboprop gearbox are compared with each other and with field data. These models are (1 Zaretsky, E. V. 1992. “STLE Life Factors for Rolling Bearings,”, STLE SP–34 Park Ridge, IL: STLE.  [Google Scholar]) Monte Carlo simulation of randomly selected lives of individual bearings and gears comprising the system and (2 Weibull, W. 1939. “A Statistical Theory of the Strength of Materials,”. In Ingenioersvestenskapsakademiens. Handl. 151 [Google Scholar]) two-parameter Weibull distribution function for bearings and gears comprising the system using strict-series system reliability to combine the calculated individual component lives in the gearbox. The Monte Carlo simulation included the virtual testing of 744,450 gearboxes. Two sets of field data were obtained from 64 gearboxes that were first-run to removal for cause, were refurbished and placed back in service, and then were second-run until removal for cause. A series of equations were empirically developed from the Monte Carlo simulation to determine the statistical variation in predicted life and Weibull slope as a function of the number of gearboxes failed. The resultant L ₁₀ life from the field data was 5,627 h. From strict-series system reliability, the predicted L ₁₀ life was 774 h. From the Monte Carlo simulation, the median value for the L ₁₀ gearbox lives equaled 757 h. Half of the gearbox L ₁₀ lives will be less than this value and the other half more. The resultant L ₁₀ life of the second-run (refurbished) gearboxes was 1,334 h. The apparent load-life exponent p for the roller bearings is 5.2. Were the bearing lives to be recalculated with a load-life exponent p equal to 5.2, the predicted L ₁₀ life of the gearbox would be equal to the actual life obtained in the field. The component failure distribution of the gearbox from the Monte Carlo simulation was nearly identical to that using the strict-series system reliability analysis, proving the compatibility of these methods.     

Rotary regenerative shock absorbers for automotive suspensions

The increasingly strict limits on pollutant emissions are pushing the car industry towards the electrification of the powertrain and chassis. This scenario has driven the automotive field to the use of energy harvesters. Among these, regenerative shock absorbers are mechatronic devices that enable the energy recovery from road irregularities, thus yielding benefits in terms of fuel saving and ride quality. The state of the art proposes different technologies for regenerative dampers. In this context, rotary dampers represent an unexplored field from the scientific point of view. These devices feature a linkage and a gearbox to convert the suspension linear motion into rotation of an electric machine. This work proposes a novel system-level design methodology for rotary regenerative shock absorbers and explores their performance from an experimental perspective. The design is focused in yielding a compact solution able to fulfill a given damping specification. Hence, the integrated definition of electric machine, gearbox and linkage is addressed by the proposed method. To support the methodology, a case study is presented. A fully functional prototype is produced and successfully validated in terms of damping capability, total conversion efficiency and acoustic behavior. The obtained results demonstrate the validity of the proposed methodology and the advantageous features of rotary dampers with respect to other regenerative suspension solutions.     

齿轮箱振动源信号分离与故障诊断研究

对齿轮的运行状态进行监测能够有效消除设备的潜在故障,避免大的事故发生.然而由于工作条件恶劣,很难采集到齿轮箱真实可靠的振动信号.由此,提出了一种基于独立分量分析（ICA）和支持向量机（SVM）相结合的齿轮故障诊断方法.首先利用ICA从被噪声污染的齿轮箱振动信号中分离出真实振动源信号,以提取可靠的齿轮状态高阶统计特征信息;而为了准确监测设备运行状态,采用支持向量机（SVM）对所提取的特征进行学习与智能分类,以检测齿轮早期故障.结果表明,通过齿轮箱故障实验分析,所提出的方法能够有效提取齿轮振动源信号,准确识别与诊断齿轮裂纹、点蚀以及断齿等故障状态,且精度比未进行源分离高10%,具有较好工业应用价值.     

非定比传动机械的计算阶次分析

研究非定比传动旋转机械非稳态信号的分析方法。由于可以避免传统频谱分析的“频率模糊”现象,阶次分析方法常被用来分析转速不稳定的机械信号。对传动比不确定的机械系统进行信号分析时,由于系统中存在不同的轴频,单一的阶次分析将难以满足要求,需进行多轴阶次分析。文中介绍多轴阶次分析的计算方法,对等时间间隔采样的信号,利用插值算法实现角域重采样,并在此基础上实现计算阶次分析。实例证明该方法可以在阶次域内将与不同轴频相关的信号进行分离,有效识别系统工况。     

小波包和BP神经网络在齿轮箱故障诊断中的应用

研究如何采用处理非平稳性的实用方法以提高监测诊断效率及水平是国内外专家一直研究的课题之一。小波包技术将信号中不同的分量无冗余、无疏漏、正交地分解到独立的频带内,这些频带里的信号能量守衡,每个频带里信号的能量对于状态监测和故障诊断都是十分有用的信息。本文对齿轮箱振动信号应用小波包分解提取故障特征向量,进一步用特征向量训练前向传播BP人工神经网络,建立齿轮运行状态分类器,对齿轮故障进行识别。实验结果表明,本文方法对齿轮箱故障诊断十分有效。     

风电齿轮箱轴承寿命计算方法研究

介绍了滚动轴承最新寿命理论和计算方法,讨论了这些计算方法的特点,并结合风电齿轮箱的特点详细分析了影响轴承寿命的几种主要因素。     

高速动车组列车齿轮箱的故障树分析与仿真

齿轮箱是高速动车组列车驱动系统中的关键零部件,在高速列车运行过程中容易出现故障导致安全隐患。以可靠性理论中的故障树方法为基础,深入分析了高铁齿轮箱的运行特点和故障模式,建立了高铁列车齿轮箱系统失效的故障树模型,进行了定性分析和定量计算,采用蒙特卡罗仿真方法得出了齿轮箱系统的平均寿命,采用框架表示法和规则表示法融合的方式设计出了适于故障树数据处理的知识数据库,有效提高了高铁齿轮箱故障诊断系统的灵敏度和可靠性。     

基于信息融合的齿轮箱故障诊断技术研究

对齿轮箱的故障诊断和信息融合进行了简要概述,将信息融合技术和D-S证据推理运用于齿轮箱的故障诊断中,提出了一种可行有效的融合方法.     

基于核函数的SOM网络在齿轮箱状态监测中的应用

基于支持向量机用内积运算实现非线性变换的思想，提出基于核函数的自组织映射方法。该方法借助于核函数在原输入空间构造非线性映像空间的自组织竞争评价函数及权值调整方法，从而更好地解决输入向量的聚类问题。研究该方法在齿轮箱状态监测中的应用，分析表明，它可以清楚地将齿轮箱不同状态区分开，并且特征数据映象点在网络输出层的轨迹变化趋势直观反映齿轮箱工作状态的变化，便于及时监测到齿轮箱早期故障及变化趋势，与标准self-or-ganizing maps(SOM)相比，该方法性能更稳定，效果更好。