铝合金车轮侧向刚度影响因素分析

使用CATIA开展铝合金车轮参数化设计,通过调整轮心结构、轮辐结构、轮辋结构、轮缘结构、窗口结构得到不同的铝合金车轮三维数据;使用Hypermesh划分网格、Nastran求解,得到不同结构铝合金车轮的侧向刚度;分析车轮侧向刚度随车轮结构参数变化的敏感程度,结果显示轮心厚度、轮心直径、轮心根部圆角、轮辐内侧厚度、轮心减重窝深度、轮辐内侧宽度对车轮刚度影响较大,且影响呈现递减趋势;综合车轮侧向刚度和质量要求,给出一种较优的车轮设计方案。该方案能够大幅提升车轮刚度,且质量增加不多。     

考虑磨损的直齿轮啮合刚度计算与分析

基于能量法和Archard磨损模型,提出了一种考虑磨损的齿轮啮合刚度数值计算方法。根据展成法原理,建立了精确的齿廓曲线方程。利用能量法计算齿轮单齿啮合刚度,并通过分段1阶傅里叶级数拟合获得齿轮总啮合刚度。以Archard磨损模型为基础,计算得到齿面法向磨损量与啮合点处压力角的关系。计算分析了不同磨损量对齿轮啮合刚度的影响。结果表明,磨损量在齿根、齿顶处较大,在节点处的理论磨损量为0 mm,随着压力角的逐渐增加,磨损量先减小后增大;齿面非均匀磨损会降低齿轮啮合刚度,随着磨损量的逐渐增加,啮合刚度逐渐减小。该方法为考虑磨损的齿轮系统动力学建模提供了理论基础。     

轨道不平顺影响下高速列车齿轮传动系统的振动特性分析

为了分析高速列车齿轮传动系统在轨道不平顺激励影响下的振动特性变化规律,利用动力学软件SIMPACK建立包含齿轮传动系统的整车动力学模型,分别在大、小齿轮内部布置测点,进行无轨道不平顺和有轨道不平顺工况下的动力学仿真实验,获得高速列车时速250 km/h时大、小齿轮的振动加速度。对大、小齿轮横向、纵向和垂向振动加速度幅值进行频域分析,并对比分析了齿轮传动系统在有、无轨道不平顺工况的振动幅值、频谱分布。结果表明,由于轨道不平顺激励的影响,高速列车齿轮传动系统的横向、纵向和垂向振动加强,振动加速度均增幅明显,其中,垂向振动加速度变化幅值最大。齿轮传动系统的振动频率主要集中在0~400 Hz,小齿轮和大齿轮横向振动受轨道不平顺的影响规律一致,但小齿轮受到纵向振动的影响略小于大齿轮,小齿轮受到垂向振动的影响略大于大齿轮。     

基于振动与流场耦合齿轮泵困油现象分析

为了解决困油现象的历程和困油压力对齿轮泵工作状态的影响,根据困油条件下齿轮泵齿轮的振动模型,由内部流场数值分析,将困油压力作为耦合的条件,建立了困油条件下的齿轮副振动和内部流场耦合的动态模型,并通过对模型解耦,分析困油压力对齿轮副振动的影响以及困油压力的具体表现形式。通过齿轮泵内部流场进行仿真,和对通过传感器采集的振动信号处理分析,明确了困油压力的大小及位置和困油产生冲击的程度,表明所建耦合模型正确可靠,能够用于困油压力预测、振动冲击分析与困油历程的仿真分析。     

成形铣齿切削载荷与加工精度的分析

错齿盘铣刀可用于齿轮的成形铣齿加工,具有多刃断续切削和变切屑厚度等特点,属于非自由强力铣削。切削载荷、加工精度逐渐成为切削机制的主要内容。通过试验方法,测量获得铣齿加工的典型载荷,可知切入、切中、切出三个阶段具有不同的特征。通过三坐标测量加工精度,分析得出齿向呈现了倒锥形的结果。其中切中阶段,加工精度为正并逐渐提高;而切出阶段,加工精度为负。基于对三向切削载荷及机床主轴箱体的悬伸对加工精度的直接影响分析,解释了"收口"现象的主要原因。该类实时的切削数据可用于现场分析与控制,进而实现精度补偿。     

磁力传动齿轮泵结构设计及分析

针对系统要求,为使齿轮泵达到高可靠性、零泄漏的要求,设计一种特殊的齿轮泵结构。采用磁力传动使齿轮泵和电机以非接触式进行连接,取消了传统结构上的轴封,摩擦力小,使电机的输入功率减少;将动密封转换为静密封,使该齿轮泵实现零泄漏的指标。     

基于粒子群算法的RBF神经网络齿轮磨损预测

针对机械设备磨损难以预测问题,提出RBF神经网络预测模型,并结合粒子群算法优化模型参数。利用变速箱型号为SG135-2系列的K727840ZW齿轮磨损实验输入-输出数据,通过基于粒子群算法的RBF神经网络建立输出预测模型,并与传统的AR模型、BP神经网络模型及Hermite神经网络模型预测作比较。仿真结果表明,基于粒子群算法的RBF神经网络模型结构简单、预测精度高,验证了所提方法的有效性和实用性。     

A new fault diagnosis algorithm for helical gears rotating at low speed using an optical encoder

Helical gears are widely used in gearboxes due to its low noise and high load carrying capacity, but it is difficult to diagnose their early faults based on the signals produced by condition monitoring systems, particularly when the gears rotate at low speed. In this paper, a new concept of Root Mean Square (RMS) value calculation using angle domain signals within small angular ranges is proposed. With this concept, a new diagnosis algorithm based on the time pulses of an encoder is developed to overcome the difficulty of fault diagnosis for helical gears at low rotational speeds. In this proposed algorithm, both acceleration signals and encoder impulse signal are acquired at the same time. The sampling rate and data length in angular domain are determined based on the rotational speed and size of the gear. The vibration signals in angular domain are obtained by re-sampling the vibration signal of the gear in the time domain according to the encoder pulse signal. The fault features of the helical gear at low rotational speed are then obtained with reference to the RMS values in small angular ranges and the order tracking spectrum following the Angular Domain Synchronous Average processing (ADSA). The new algorithm is not only able to reduce the noise and improves the signal to noise ratio by the ADSA method, but also extracts the features of helical gear fault from the meshing position of the faulty gear teeth, hence overcoming the difficulty of fault diagnosis of helical gears rotating at low speed. The experimental results have shown that the new algorithm is more effective than traditional diagnosis methods. The paper concludes that the proposed helical gear fault diagnosis method based on time pulses of encoder algorithm provides a new means of helical gear fault detection and diagnosis.     

Design and validation of a grinding wheel optical scanner system to repeatedly measure and characterize wheel surface topography

This paper describes the design and validation of an upgraded grinding wheel scanner system that controls the position of a Nanovea CHR-150 Axial Chromatism sensor along the x- and y-directions of the wheel surface to measure and characterize wheel surface topography. The scanner features a novel homing system that enables the wheel to be removed from the scanner, used on a grinding machine and then re-mounted and re-homed so that the same location on the wheel surface can be repeatedly measured and monitored. The average standard deviation for homing was 27.6 μm and 19.3 μm in the x- and y-directions, respectively, which is more than adequate for typical area scans of 25 mm². After homing, the scanner was able to repeatedly measure features that were similar in size to an abrasive grain (∼200 μm diameter) with an average error of 9.3 μm and 5.9 μm in the x- and y-directions, respectively. The resulting topography measurements were compared with Scanning Electron Microscope images to demonstrate the accuracy of the scanner. A custom particle filter was developed to process the resulting data and a novel analysis technique involving the rate of change of measured area was proposed as a method for establishing the reference wheel surface from which desired wheel topography results can be reported such as the number of cutting edges, cutting edge width and cutting edge area as a function of radial depth.     

Pitch deviation measurement and analysis of curve-face gear pair

The curve-face gear pair is proposed as a new type of gear pair which was put forward in recent years. It can achieve variable ratio transmission of motion and power between the intersection axes. In the matter of the inspection of the pitch deviations of this gear pair, there is no practical possibility for a reliable metrological traceability to national or international measurement standards can be provided. Hence, a new method was proposed in this article, which was based on the CNC gear measuring center, aimed at the gear artefacts processed by the five-axis machining center. With the coordinate data which were obtained by the gear measuring center, the pitch deviations of the gear pair were obtained. In addition, based on the values of the pitch deviations, the angular deviations of curve-face gear pair can be worked out, and the results turn out that the measurement method is feasible.