CO2压缩机增速齿轮箱断齿故障分析

通过对齿轮断口的形貌、振动原因及裂纹源分析、并结合对原齿轮设计承裁能力的校核，找到了GN-25增速齿轮箱断齿的原因，提出了防止故障发生措施。     

提升机齿轮箱振动频谱诊断中边频分析方法

提升机齿轮箱的振动频谱中存在丰富的低频边频带。讨论了通过频谱细化技术提高特征频率分辨率,并联合使用倒频谱分析技术对低频边频成分进行分离提取,从而提高了故障诊断准确性。     

紧凑式轧机主传动复合减速箱转化设计

本文简述了紧凑式连轧机组中的立式主传动复合减速箱箱体结构的改进，曲线齿锥齿轮几何参数和齿制的变化以及全部主传动复合减速箱的齿轮结构、材质、热处理和齿轮润滑方面的转化设计要点。探讨了用中硬齿面齿轮代替硬齿面齿轮的可能性。     

应用Hilbert变换和ZFFT提取变速器齿轮故障特征

变速器故障齿轮振动信号,调幅现象和调频现象同时存在,其频谱中包括啮合频率及其谐波、调制产生的耦合频率。Hilbert变换无法提供足够高的频率分辨率解调低频调制信号,为此提出复调制细化谱分析方法。通过变速器齿轮故障模拟实验,采集齿轮正常、轻微磨损和严重磨损时的稳态振动信号,对其进行Hilbert变换得到信号的包络,对包络信号进行复调制细化谱分析,得到齿轮轴转频基波及其谐波幅值。随着齿轮磨损程度的增加,齿轮轴转频基波及其谐波幅值明显增大,可作为齿轮磨损故障特征参数。     

粒子群优化的神经网络在故障诊断中的应用

为提高齿轮箱故障诊断性能，建立了以齿轮箱振动信号的时频域特征为输入，以齿轮箱的主要故障形式为输出的神经网络。采用粒子群优化算法代替反向传播算法来训练神经网络的权重和阈值，利用训练后的神经网络对齿轮箱进行了故障诊断，并比较了基于粒子群优化算法与BP算法的诊断结果。结论是基于粒子群优化算法神经网络具有较好训练性能，收敛速度快，迭代步数少，诊断精度高，具有良好的故障识别率。     

基于HHT的齿轮箱复合故障诊断研究

提出一种基于HHT的齿轮箱复合故障诊断方法。该方法将齿轮箱故障振动信号进行Hilbert-Huang变换,得到信号的Hilbert能量谱,通过谱分析实现齿轮箱复合故障的识别。齿轮箱故障实验信号的研究结果表明:该方法能有效诊断齿轮箱的复合故障。     

Gearbox fault diagnosis using adaptive zero phase time-varying filter based on multi-scale chirplet sparse signal decomposition

When used for separating multi-component non-stationary signals, the adaptive time-varying filter(ATF) based on multi-scale chirplet sparse signal decomposition(MCSSD) generates phase shift and signal distortion. To overcome this drawback, the zero phase filter is introduced to the mentioned filter, and a fault diagnosis method for speed-changing gearbox is proposed. Firstly, the gear meshing frequency of each gearbox is estimated by chirplet path pursuit. Then, according to the estimated gear meshing frequencies, an adaptive zero phase time-varying filter(AZPTF) is designed to filter the original signal. Finally, the basis for fault diagnosis is acquired by the envelope order analysis to the filtered signal. The signal consisting of two time-varying amplitude modulation and frequency modulation(AM-FM) signals is respectively analyzed by ATF and AZPTF based on MCSSD. The simulation results show the variances between the original signals and the filtered signals yielded by AZPTF based on MCSSD are 13.67 and 41.14, which are far less than variances (323.45 and 482.86) between the original signals and the filtered signals obtained by ATF based on MCSSD. The experiment results on the vibration signals of gearboxes indicate that the vibration signals of the two speed-changing gearboxes installed on one foundation bed can be separated by AZPTF effectively. Based on the demodulation information of the vibration signal of each gearbox, the fault diagnosis can be implemented. Both simulation and experiment examples prove that the proposed filter can extract a mono-component time-varying AM-FM signal from the multi-component time-varying AM-FM signal without distortion.     

基于有限元的履带车辆变速箱体强度分析

建立了履带车辆变速箱体的力学模型,对其载荷和结构特点进行了分析,同时根据边界条件,引入特定的约束,通过有限元方法对履带车辆变速箱体进行了结构强度分析,计算得到了等效位移和等效应力云图,分析得出了箱体结构位移和应力的分布及其数值,从而找出了原设计的薄弱环节,可为进一步改进履带车辆变速箱体的结构设计提供一定的参考和借鉴。     

锅炉炉排调速机动态转矩测试系统的研发

针对链条炉排牵引力设计时缺乏可靠依据、制造时缺乏定量检测的现状,采用转矩测量钳和电磁加载器,研制了炉排牵引力及其调速机动态转矩测试系统,可满足其从静止到高速的宽调速范围的转矩测量。     

基于EMD和非线性峭度的齿轮故障诊断

采用经验模式分解(empirical mode decomposition,简称EMD)和非线性峭度的统计特性对振动加速度传感器获取的齿轮箱振动响应信号进行特性分析。利用EMD分解获得振动响应信号的本征模式函数,用非线性Tea-ger能量算子计算每个本征模式函数的瞬时能量,并对本征模式函数进行系数的非线性峭度计算,提取系统的特征信息。仿真结果表明,用经验模式分解和非线性峭度可实现在线监测齿轮运转工作状态,及时发现齿轮的早期故障,提高了故障检测的可靠性。