齿轮传动系统断齿故障的机理研究

研究了含断齿故障的4自由度齿轮系统的动力学机理。考虑了断齿故障会引起齿轮系统微小的不平衡,及断齿故障对系统啮合刚度的影响,综合建立了齿轮—转子—轴承模型。数值仿真了故障信号,并通过时域图、相轨迹、Poincaré截面图及频谱分析研究了断齿故障引起的响应,及断齿故障的演化对系统动力响应的影响。最后实验模拟了齿轮断齿故障,通过实测振动信号的振动特征能够验证理论分析的结果,从而说明断齿故障理论模型的合理性,能为齿轮系统断齿故障的诊断提供理论依据。     

基于EMD小波阈值去噪和时频分析的齿轮故障模式识别与诊断

建立了齿轮故障系统试验装置,对齿轮传动系统在各种转速与故障状态下进行测试分析,获取了有关振动信号,对齿轮系统的无故障、齿根裂纹、分度圆裂纹、齿面磨损四种状态信号进行特征提取,并对提取的信号进行基于经验模态EMD分解的小波阈值去噪处理,然后对预处理后的信号进行时频分析与诊断。结果表明,采用基于EMD的小波阈值去噪方法比单纯采用小波阈值去噪对测试信号进行预处理,能提高信噪比,并更加有效的提取出故障特征,而在EMD的小波阈值去噪的基础上,再与时频分析方法相结合能够较好的识别不同运转状况下不同种类的故障,如齿根裂纹、分度圆裂纹、齿面磨损等,可用于对实际工程工作的齿轮系统进行故障诊断。     

Influence of Crack on Structure Vibration of Gear Tooth

This paper presents a theoretical model for analyzing the dynamic characteristic such as natural frequencies and vibration mode shapes of cracked gears. The influence of crack position and crack size on the dynamic characteristic of gears is thoroughly investigated using the proposed theoretical model as well as the finite element method (FEM) for the sake of model validation. The theoretical analysis and numerical simulation show that the influence of crack size and crack position on the dynamic responses of cracked gears is significant and that the influence of crack position is larger than that of crack size. The natural frequencies drop with the increase of crack size and the low order natural frequencies drop more notably. The natural frequencies drop more significantly when crack is located at tooth root than at tooth tip. The vibration mode shapes of cracked gear tooth are very different from those of gear tooth without crack, and the vibration amplitude increases significantly in crack neighborhood. These observations are very valuable for damage detection and fault diagnosis of gear system.     

基于扭振分析方法的齿轮传动系统故障辨识

通过分析齿轮啮合过程的数学模型及典型故障,论证了扭振分析方法在齿轮系统故障诊断上的优越性,并提出一种测量齿轮轴上扭振信息的新方法。在此基础上搭建了齿轮传动系统,通过采用永磁旋转(角)加速度传感器检测齿轮系统各个运行状态下不同轴上的扭振信号;然后,分别对齿轮传动系统轴上的扭振信号和平台的振动信号采用小波包分解,提取各个节点的能量作为特征向量;最后,结合以径向基函数(RBF)为核函数的支持向量机(SVM)分别进行故障的辨识。实验结果表明:轴上的扭振信号在齿轮系统故障诊断上的效果要优于平台振动信号的诊断效果。     

A Comparative Study of Various Methods of Gear Faults Diagnosis

Investigating gear damages using vibration signal is a subject of a high interest, because gears vibration signals are complex and difficult to understand. A failure diagnosis of gearbox based on Fourier analysis of the vibration produced by speed reducers has shown its limits in terms of spectral resolution. In the present paper, a comparative study of the performances of various different methods of fault diagnosis of helicopter gearbox gear is carried out. The results are highlighted on the basis of real data recorded during a helicopter flight and have showed that cepstral analysis is most effective technique in detecting gearbox gear faults.     

四分位偏差分形维及其在齿轮故障识别中的应用

介绍了用于非平稳、非线性信号的四分位偏差分形维算法，并通过仿真实例验证了此计算方法的准确性。针对齿轮振动信号的非平稳、非高斯、非线性特点，将四分位偏差分形维用于齿轮故障分类，结果表明此方法能很好地区分齿轮故障模式。以四分位偏差与相应的截距为特征量进行聚类，能更好地区分齿轮的各种故障模式。可将其用于在线故障识别。     

基于包络S变换时频图像提取齿轮故障特征

齿轮故障振动信号中调幅和调频现象同时存在,其频谱包括以啮合频率及其谐波为载频,齿轮所在轴转频及其谐波为调制频率产生的调制边频带。针对齿轮故障振动信号特征提取困难的问题,提出一种基于包络分析和S变换时频图像相结合的故障特征提取方法。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,然后对包络信号进行S变换,得到包络的时频图像的等高线灰度图像,计算图像的灰度共生矩阵及其统计特征量,提取齿轮故障特征。试验结果表明：该方法能有效提取齿轮故障特征。     

全矢小波包-包络分析方法及其在齿轮故障诊断中的应用

在旋转机械故障诊断中,针对传统单源信息采集的不全面性,提出了一种基于全矢谱技术的小波包-包络分析方法。首先对同源双通道信息分别采用小波包分解,根据需要选择频段的信息,并对提取的信号进行重构。然后采用全矢Hilbert解调分析方法对重构信号实现包络解调,并与两单源信息的包络解调相比较,说明了仅以单源信息为诊断依据的不足。利用全矢谱技术进行融合的全矢小波包-包络解调技术,不仅继承了小波包-包络分析方法的优势,而且更加全面地反映出了信号的真实性。最后通过仿真信号对其算法的可行性进行了验证,同时又以齿轮的故障振动信号为例,进一步表明了该方法在故障诊断中的有效性。     

基于倒阶次谱分析的齿轮故障诊断研究

针对齿轮箱升速过程中振动信号非平稳的特点，将常规的倒谱分析技术与阶次谱结合，提出了倒阶次谱的齿轮箱故障诊断方法。首先对齿轮箱升降速瞬态信号进行时域同步采样，再对时域信号实行等角度重采样，转化为角域平稳信号，最后对角域重采样信号进行倒谱分析，就可提取齿轮的故障特征。通过对齿轮齿根裂纹和齿面磨损故障实验信号的分析，表明该方法能有效地诊断齿轮的故障。     

扩大分度盘加工齿坯齿数范围的精密磨齿工艺

分度盘式分度系统广泛应用于高精度标准齿轮、插齿刀和剃齿刀的磨齿中,然而传统的磨齿工艺限制了分度盘加工齿坯齿数的种类.为扩大分度盘的加工范围,提出了一种应用分度盘分组多次加工齿坯的精密磨齿工艺方法.首先精加工出一组齿数等于分度盘工作槽数的同名齿面为基准齿面;然后根据待加工齿面与基准齿面单一齿距偏差代数和的平均差值或径向跳动偏差代数的平均差值来确定同名齿面中另一组齿面的加工余量,或根据公法线测量跨齿数的奇偶性和公法线的加工余量确定并完成异名齿面的精加工;最后,用上述方法选择已精加工的、误差源较少的齿面为基准齿面依次完成剩余齿面的精加工.设计一组利用工作槽数为20的分度盘,分两组加工齿数为40的标准齿轮试件的精密磨齿实验,采用"差动进给磨齿法"实现了齿面渐开线法向0.2μm量级的微量进给.最终被磨试件的单一齿距偏差不超过0.8μm,齿距累积总偏差不超过1.3μm,均达到齿轮国际标准ISO 1328-1∶1995和国家标准GB/T 10095.1——2008中的最高级精度(0级).精密磨齿实验验证了该磨齿工艺方法的可行性.分度盘分组加工齿坯的磨齿工艺扩大了分度盘加工齿坯齿数的范围,具有重要的工程应用价值.     

重合度对人字齿轮非线性系统振动特性的影响分析

由轮齿接触分析以及轮齿承载接触分析计算出考虑安装误差的轮齿综合啮合刚度和单齿啮合刚度,提出了考虑齿轮啮合重合度的啮合冲击计算模型,建立了考虑时变啮合刚度、啮入冲击、齿侧间隙的人字齿轮十二自由度啮合型弯—扭—轴耦合非线性振动模型。以某船用单级人字齿轮副为实例,通过改变轮齿高度变位系数调整重合度进行验证计算,将本文提出的线外啮合冲击模型冲击力计算结果与文献[8]中模型计算结果进行比较,验证了本文提出模型的有效性。通过实例计算,结果表明在负载一定的情况下,轮齿啮合周向及小轮轴向振动随着重合度的增大而减小;而当轮齿啮合重合度增大到4.07时,系统振动呈增大趋势。     

Wavelet analysis for gear crack identification

There are many typical damages and faults that can cause problems in relation to gear unit operation, a crack in the tooth root being probably the least desirable among them. It often results in failure of gear unit operation. Fault analyses presented in this article are based on gear units with real damages or faults, produced on the basis of real operating conditions. A test plant has been used. A possible damage can be identified by monitoring vibrations. The influences of a crack in a single-stage gear unit on produced vibrations are presented. A fatigue crack in the tooth root causes significant changes in tooth stiffness, whereas, in relation to other faults, changes of other dynamic parameters are more expressed. Different methods are used to analyse signals acquired by experiments. Signal analysis has been carried out in relation to a non-stationary signal, using the family of Time Frequency Analysis tools, such as Wavelets Analyses. Typical spectrogram and scalogram patterns resulting from reactions to faults or damages indicate the presence of damages in a very reliable way.     

A Method for Gear Fault Diagnosis Based on the Empirical Mode Decomposition

According to the characteristics of gear fault vibration signals, a method for gear fault diagnosis based upon the empirical mode decomposition (EMD) is proposed in this paper. By using EMD, any complicated signal can be decomposed into a finite and often small number of intrinsic mode functions ( IMFs) , which are based upon the local characteristic time scale of the signal. Thus, EMD is perfectly suitable for non-stationary signal processing and fault characteristics extracting. It is well known that a gear vibration signal consists of a number of frequency family components, each of which is a modulated signal. Thus, we can use EMD to decompose a gear fault vibration signal into a number of lMF components, some of which correspond to the frequency families, and the others are noises. Therefore, the frequency families can be separated and the noise can be decreased at the same time. The proposed method has been applied to gear fault diagnosis. The results show that both the sensitivity and the reliability of this method are satisfactory.     

Effects of gear center distance variation on time varying mesh stiffness of a spur gear pair

Gear center distance variation is one of the most common defects of gear transmission systems. The changes in the gear center distance as well as other faults (e.g. tooth crack, pitting) have a direct influence on the Time Varying Mesh Stiffness (TVMS) which further modifies gear vibration behaviors. Accurately estimating gear TVMS under fault conditions is crucial in gear vibration dynamic simulation. Common methods used to evaluate TVMS are generally based on the assumption that the gear pair is perfectly mounted and that all mesh points are at their theoretical positions. This assumption prevents these methods from modeling deviations in gear center distance. To address this shortcoming, this paper proposes a new gear mesh kinematic model that can evaluate the actual contact positions of tooth engagement with time varying gear mesh center distance. With the proposed kinematic model, the actual TVMS of both healthy and cracked gear teeth are computed under conditions of perfect mounting, constant gear center distance deviation, and also time-varying gear center distance. Numerical simulations indicate that gear center distance variation has a significant effect on gear TVMS. Comparison between the effect of multiple faults and summed individual effects on TVMS indicates that the TVMS modification due to multiple-faults do not appear to combine in a linear manner. The proposed model for actual TVMS enables gear system dynamic models to be used to study the effects of assembly errors, gear run-out errors, shaft bending, and bearing deformation on the vibration behavior of gear transmission systems.     

齿轮传动系统损伤检测与多故障分类研究

研究了数据挖掘的支持向量机的智能故障检测与诊断方法。通过对齿轮系统在不同的运转状态下的工作状况进行试验测试分析,获取了有关的测试信号,并对不同的故障振动特征信号进行了特征提取与分析研究。在此基础上将支持向量机引入到齿轮传动的损伤检测与诊断之中,建立了两分类和多分类分类器,研究了支持向量机的两分类和多类分类算法。通过分析处理、训练和测试仿真数据以及齿轮振动特征信号,对齿轮系统在各种不同转速下不同故障进行了预测、分类和诊断。研究表明, 支持向量机能够很好的区分不同运转状况下各种典型齿轮损伤与故障,低转速下识别率更高,为95%,特别是对各种复合类故障具有较高的识别精度、识别率在81%以上。它在齿轮故障诊断中具有较好诊断识别能力与发展前景,是一种有效地损伤检测与诊断新方法。     

齿轮振动的边带分布特征与故障诊断实例

从理论上讨论了齿轮集中缺陷和分布缺陷的频域特征,特别是边带分布特点。集中故障的边带数目多,强度起伏小;而对于分布故障,若调制波为单频,则理论上只在啮合频率ｆ ｍ 和它的 ２ 倍频２ｆｍ 两侧各形成 １ 个边带;若调制波含有２ 次谐波,则在啮合频率ｆｍ 和它的２ 倍频２ｆｍ 两侧各形成２ 个边带。还结合测试实例,提出了运用振动信号诊断齿轮故障所应注意的问题     

张力拉矫机的二自由度行星齿轮减速箱故障诊断研究

张力拉矫机是生产带钢非常重要的关键性设备,某钢厂冷轧酸洗线的张力拉矫机主减速箱是二自由度差动轮系结构,行星包中的太阳轮、行星轮和大齿圈、行星架都同时运转,其运行轨迹复杂。为研究1#锥齿减速箱和主减速箱振动大的原因,对其进行振动信号测试和频谱分析,分析结论得出,引起主减速箱和1#锥齿减速箱振动大的主要原因是主减速箱中行星包中齿轮啮合不良,并且推测出行星轮有严重损伤。实际检测结果表明,基于传统的频谱分析能够识别出行星齿轮箱的故障。     

Determining cracks in gears using adaptive wavelet transform approach

A new family of biorthogonal wavelets used to identify fault in gears is dealt with. The fault detection analyses and methods presented in this paper are based on signals created by a faultless gear and by a gear with a crack in the tooth root, caused through operating conditions. The new wavelets are a generalization of biorthogonal wavelet systems. In the analysis, smoothness is controlled independently and discrete finite variation is used to optimise the synthesis bank. The procedure measure dispenses with a measure of differentiability, requiring a large number of vanishing wavelet moments in favour of a smoothness measure that is based on the fact that, in most practical applications, only a finite depth of the filter bank tree is involved.     

Differential diagnosis of spall versus cracks in the gear tooth fillet region

This paper presents a technique to differentially diagnose two localized gear tooth faults: a spall and a crack in the gear tooth fillet region. These faults could have very different prognoses, but existing diagnostic techniques only indicate the presence of local tooth faults without being able to differentiate between a spall and a crack. The effects of spalls and cracks on the behavior/response of gear assemblies were studied using static and dynamic simulation models. Changes in the kinematics of a pair of meshing gears due to a gear tooth root crack and a tooth flank spall were compared using a static analysis model. The difference in the variation of the transmission error caused by the two faults reveals their characteristics. The effect of a tooth crack depends on the change in stiffness of the tooth, while the effect of a spall is predominantly determined by the geometry of the fault. The effect of the faults on the gear dynamics was studied by simulating the transmission error in a lumped parameter dynamic model. A technique had previously been proposed to detect spalls, using the cepstrum to detect a negative echo in the signal (from entry into and exit from the spall). In the authors’ simulations, echoes were detected with both types of fault, but their different characteristics should allow differential diagnosis. These concepts are presented prior to experimental validation in hopes that the diagnostic techniques will be useful in the failure analysis community prior to the validation by ongoing experimental testing of the concepts and the evaluation of how metallurgical defects may influence fault development and detection.     

基于时间-小波能量谱的齿轮故障诊断

振动信号中的冲击现象及其频率特征是诊断齿轮局部损伤故障的重要依据之一。针对齿轮故障特征提出了一种时间-小波能量谱信号处理方法,它能够有效提取振动信号中冲击成分的时域和频域特征。利用时间-小波能量谱方法分析了正常、磨损、断齿等三种状态的齿轮箱振动信号,并与传统频谱分析方法进行相比。结果表明：时间-小波能量谱不仅可以有效提取故障特征,识别出齿轮箱的故障存在,而且可以清晰地分辨出故障类型及故障元件。