Simulation and analysis of vibration signals generated by rolling element bearing with defects

Dynamic loading of a rolling element bearing structure is modeled by a computer program developed in Visual Basic programming language. The vibration response of the structure to the dynamic loading is obtained using a standard finite element package I-DEAS. A force model is proposed to model the localized rolling element bearing defects. Time and frequency domain analyses are performed for diagnostics of rolling element bearing structures. Statistical properties of the vibration signals for healthy and defected structures are compared. The envelope (HFRT) method is employed in the frequency domain analysis. The effect of the rotational speed on the diagnostics of rolling element bearing defects is investigated. An optimum sensor location on the structure is sought. Effect of the structure geometry on the monitoring techniques is studied. An optimum monitoring method can be employed by analyzing the rolling element bearing structure following the procedure proposed in this study. The present commercial computer aided engineering packages can be used in special engineering applications such as condition monitoring of rolling element bearings.     

起重机用滚动轴承有限元分析及故障检测

针对起重机用滚动轴承故障率高且难以检测的问题,首先采用Ansys软件对起重机用滚动轴承进行基于实际接触状态的有限元分析,然后采用基于小波包能量法和Hilbert变换方法对滚动轴承进行信号处理、分析以及故障检测。结果表明:滚动轴承的滚动体与内外圈接触部位存在较大应力集中,最易在此处首先发生破坏;根据轴承故障特征频率与内圈、外圈、滚动体三种故障类型所对应的频谱特征和能量谱相比较,可有效判断轴承故障类型。研究所采用的检测方法可为起重机用滚动轴承的故障预防和检测提供一定理论依据和指导作用。     

滚动轴承疲劳寿命数值仿真技术的研究

建立了滚动轴承疲劳寿命计算的数学模型,运用Monte-Carlo方法对其实验数据进行模拟,编制出相应的计算程序并建立了滚动轴承疲劳寿命预测系统.在计算机上完成滚动轴承寿命计算、数值模拟和滚动轴承的疲劳寿命的预测.     

Fault diagnosis of rolling element bearing using a new optimal scale morphology analysis method

Periodic transient impulses are key indicators of rolling element bearing defects. Efficient acquisition of impact impulses concerned with the defects is of much concern to the precise detection of bearing defects. However, transient features of rolling element bearing are generally immersed in stochastic noise and harmonic interference. Therefore, in this paper, a new optimal scale morphology analysis method, named adaptive multiscale combination morphological filter-hat transform (AMCMFH), is proposed for rolling element bearing fault diagnosis, which can both reduce stochastic noise and reserve signal details. In this method, firstly, an adaptive selection strategy based on the feature energy factor (FEF) is introduced to determine the optimal structuring element (SE) scale of multiscale combination morphological filter-hat transform (MCMFH). Subsequently, MCMFH containing the optimal SE scale is applied to obtain the impulse components from the bearing vibration signal. Finally, fault types of bearing are confirmed by extracting the defective frequency from envelope spectrum of the impulse components. The validity of the proposed method is verified through the simulated analysis and bearing vibration data derived from the laboratory bench. Results indicate that the proposed method has a good capability to recognize localized faults appeared on rolling element bearing from vibration signal. The study supplies a novel technique for the detection of faulty bearing.     

Predicting polygonal-shaped defects during hot ring rolling using a rigid-viscoplastic finite element method

We applied a rigid-viscoplastic finite element method to investigate polygonal-shaped defects that occur during ring rolling and developed an improved analysis model with relatively fine finite elements near the roll gap to reduce the computational time, along with a scheme to minimize the volume change. We also simulated the formation of a polygonal-shaped defect during hot ring rolling of a ball bearing outer race. The results were in good qualitative agreement with actual experimental phenomena.     

A weighted multi-scale morphological gradient filter for rolling element bearing fault detection

This paper presents a novel signal processing scheme, named the weighted multi-scale morphological gradient filter (WMMG), for rolling element bearing fault detection. The WMMG can depress the noise at large scale and preserve the impulsive shape details at small scale. Both a simulated signal and vibration signals from a bearing test rig are employed to evaluate the performance of the proposed technique. The traditional envelope analysis and a multi-scale enveloping spectrogram algorithm combining continuous wavelet transform and envelope analysis (WT-EA) are also studied and compared with the presented WMMG. Experimental results have demonstrated the effectiveness of the WMMG to extract the impulsive components from the raw vibration signal with strong background noise. We also investigated the classification performance on identifying bearing faults based on the WMMG and statistical parameters with varied noise levels. Application results reveal that the WMMG achieves the same or better performance as EA and WT-EA. Meanwhile, the WMMG requires low computation cost and is very suitable for on-line condition monitoring of bearing operating states.     

Faults diagnosis of rolling element bearings based on modified morphological method

In order to effectively smooth noise and extract the impulse components in the vibration signals of defective rolling element bearings, a new modified morphology analytical method has been proposed. In this method, average of the closing and opening operator has been used as the morphology operator. Being the flat and zero adopted as the shape and the height of structure element (SE), respectively, the optimized length of SE is defined by a new proposed criterion (called SNR criterion). The effect of the new method is validated by both simulated impulsive signal and vibration signal of three defective rolling bearings with an outer, an inner and a rolling element faults and compared with Nikolaou’s method. The result shows that the proposed method has the superior performance in extracting impulsive characteristics of vibration signals, especially for the high level noise signals, and can implement better in diagnosis of defective rolling element bearing.     

轧钢机械设备轴瓦的检修要点分析

轧钢机械设备是当前工业发展的重要设备之一,其运行效果、效率可以说直接关系着其性能的发挥,为了使轧钢机械设备能够正常运转,那么提高轧钢机械设备轴瓦的运转效果也是非常关键的。本次研究结合轧钢机械设备轴瓦的具体情况,对轧钢机械设备轴瓦检修存在的问题及检修要点进行分析,旨在提高轧钢机械设备的运行效果。     

橡胶-钢球支座非线性有限元分析

针对橡胶的大变形及接近不可压缩的特点,笔者对工程中常用的橡胶-刚球支座进行非线性有限元分析,得出支座受轴向拉伸时的刚度与轴向变形关系.此外,分析了泊松比对支座刚度和橡胶层中应力的影响,同时得出支座受轴向拉伸时最易失效的位置.     

滚动轴承的"跨步跳动"

经典轴承分析理论由于把滚动体载荷分布处理成连续变量,因而忽略了滚动体离散性所引起的轴承振动。当滚动体通过承载区时,由于受压滚动体数目的奇偶性变化而使轴承产生周期性振动,分析了这种振动的幅值和径向游隙的影响,并提出了"奇压"、"偶压"现象和"跨步跳动"概念。     

轧钢机械设备轴瓦的检修要点分析

轧钢机械设备是当前工业发展的重要设备之一,其运行效果、效率可以说直接关系着其性能的发挥,为了使轧钢机械设备能够正常运转,那么提高轧钢机械设备轴瓦的运转效果也是非常关键的。本次研究结合轧钢机械设备轴瓦的具体情况,对轧钢机械设备轴瓦检修存在的问题及检修要点进行分析,旨在提高轧钢机械设备的运行效果。     

基于改进谐波小波包分解的滚动轴承复合故障特征分离方法

为解决滚动轴承单通道振动信号中复合故障特征难以分离的问题,提出了基于改进谐波小波包分解的轴承复合故障特征分离方法。首先,改进了二进谐波小波包分解方法,提出了连续谐波小波包分解方法,克服了信号分解后子带个数和带宽范围受二进制划分的缺陷;然后,采用谐波窗分解提取信号中频率成分集中的频段,根据轴承各单点故障特征频率确定分解层数,进行连续谐波小波包分解,利用能量算子包络解调得到子带信号中各个单点故障的权重因子;最后,重构轴承各单点故障信号,实现复合故障的特征分离和提取。对仿真信号和实测轴承内、外圈复合故障信号分析的结果表明,该方法能将轴承单通道复合故障信号分解到不同的通道中,实现了复合故障特征的分离,具有一定的工程实用价值。     

基于应变的柴油机滚动轴承故障诊断方法研究

从简单的悬臂梁入手,建立了柴油机上滚动轴承的动力学模型,从理论上推导了梁上各点位移、速度、加速度和应变的响应解析表达式。通过仿真计算,发现上述四种参数对激振力都很敏感,而相对于其它三种响应而言,应变响应对其它激振源的加速度信号不敏感,得出了利用应变信号可以有效地避免柴油机上其它振动源的干扰的结论。并通过试验研究,验证了上述结论。     

Effects of extreme pressure additive chemistry on rolling element bearing surface durability

Lubricant additives have been known to affect rolling element bearing surface durability for many years. Tapered roller bearings were used in fatigue testing of lubricants formulated with gear oil type additive systems. These systems have sulfur- and phosphorus-containing compounds used for gear protection as well as bearing lubrication. Several variations of a commercially available base additive formulation were tested having modified sulfur components. The variations represent a range of “active” extreme pressure (EP) chemistries. The bearing fatigue test results were compared with respect to EP formulation and test conditions. Inner ring near-surface material in selected test bearings was evaluated on two scales: the micrometer scale using optical metallography and the nanometer scale using transmission electron microscopy (TEM). Focused-ion beam (FIB) techniques were used for TEM specimen preparation. Imaging and chemical analysis of the bearing samples revealed near-surface material and tribofilm characteristics. These results are discussed with respect to the relative fatigue lives.     

滚动轴承数据库设计及其在故障诊断中的应用

针对国内外滚动轴承种类繁多、编号复杂以及轴承故障特征频率难以获得的现状,利用Power Builder强大的数据库功能,设计出一套数据完整、查询快捷方便,并与瑞典SKF公司的轴承故障特征频率参数相吻合的数据库系统,同时举例说明该系统可广泛应用于设备状态监测、故障诊断和预知维修领域。     

An adaptive SK technique and its application for fault detection of rolling element bearings

In this paper, we propose an adaptive spectral kurtosis (SK) technique for the fault detection of rolling element bearings. The primary contribution is adaptive determination of the bandwidth and center frequency. This is implemented with successive attempts to right-expand a given window along the frequency axis by merging it with its subsequent neighboring windows. Influence of the parameters such as the initial window function, bandwidth and window overlap on the merged windows as well as how to choose those parameters in practical applications are explored. Based on simulated experiments, it can be found that the proposed technique can further enhance the SK-based method as compared to the kurtogram approach. The effectiveness of the proposed method in fault detection of the rolling element bearings is validated using experimental signals.     

An improved complementary ensemble empirical mode decomposition with adaptive noise and its application to rolling element bearing fault diagnosis

A novel time–frequency analysis method called complementary complete ensemble empirical mode decomposition (EEMD) with adaptive noise (CCEEMDAN) is proposed to analyze nonstationary vibration signals. CCEEMDAN combines the advantages of improved EEMD with adaptive noise and complementary EEMD, and it improves decomposition performance by reducing reconstruction error and mitigating the effect of mode mixing. However, because white noise mixed in with the raw vibration signal covers the whole frequency bandwidth, each mode inevitably contains some mode noise, which can easily inundate the fault-related information. This paper proposes a time–frequency analysis method based on CCEEMDAN and minimum entropy deconvolution (MED) for fault detection of rolling element bearings. First, a raw signal is decomposed into a series of intrinsic mode functions (IMFs) by using the CCEEMDAN method. Then a sensitive parameter (SP) based on adjusted kurtosis and Pearson’s correlation coefficient is applied to select a sensitive mode that contains the most fault-related information. Finally, the MED is applied to enhance the fault-related impulses in the selected IMF. The fault signals of high-speed train axle-box bearing are applied to verify the effectiveness of the proposed method. Results show that the proposed method can effectively reveal axle-bearing defects’ fault information. The comparisons illustrate the superiority of SP over kurtosis for selecting the sensitive mode from the resulted signal of CCEEMEDAN. Further, we conducted comparisons that highlight the superiority of our proposed method over individual CCEEMDAN and MED methods and over two other popular signal-processing methods, variational mode decomposition and fast kurtogram.     

Vibration analysis of rolling element bearings with various defects under the action of an unbalanced force

In this paper, a method based on the finite element vibration analysis is presented for defect detection in rolling element bearings with single or multiple defects on different components of the bearing structure using the time and frequency domain parameters. A dynamic loading model is proposed in order to create the nodal excitation functions used in the finite element vibration analysis as external loading. A computer code written in Visual Basic programming language with a graphical user interface is developed to create the nodal excitations for different cases including the outer ring, inner ring or rolling element defects. Forced vibration analysis of a bearing structure is performed using the commercial finite element package I-DEAS under the action of an unbalanced force transferred to the structure via a ball bearing. Time and frequency domain parameters such as rms, crest factor, kurtosis and band energy ratio for the frequency spectrum of the enveloped signals are used to analyse the effect of the defect location and the number of defects on the time and frequency domain parameters. The role of the receiving point for vibration measurements is also investigated. The vibration data for various defect cases including the housing structure effect can be obtained using the finite element vibration analysis in order to develop an optimum monitoring method in condition monitoring studies.     

Vibration response of spalled rolling element bearings: Observations, simulations and signal processing techniques to track the spall size

Fatigue in rolling element bearings, resulting in spalling of the races and/or rolling elements, is the most common cause of bearing failure. The useful life of the bearing may extend considerably beyond the appearance of the first spall and a premature removal of the bearing from service can be very expensive, but on the other hand chances cannot be taken with safety of machines or personnel. Previous studies indicated that there might be two parts to the defect vibration signal of a spalled bearing, the first part being originating from the entry of the rolling element into the fault (de-stress) and the second part being due to the departure of the rolling element from the fault (re-stress). This is investigated in this paper using vibration signatures of seeded faults at different speeds. The acceleration signals resulting from the entry of the rolling element into the spall and exit from it were found to be of different natures. The entry into the fault can be described as a step response, with mainly low frequency content, while the impact excites a much broader frequency impulse response. The latter is the most noticeable and prominent event, especially when examining the high pass filtered response or the enveloped signal. In order to enable a clear separation of the two events, and produce an averaged estimate of the size of the fault, two approaches are proposed to enhance the entry event while keeping the impulse response. The first approach (joint treatment) utilizes pre-whitening to balance the low and high frequency energy, then octave band wavelet analysis to allow selection of the best band (or scale) to balance the two pulses with similar frequency content. In the second approach, a separate treatment is applied to the step and the impulse responses, so that they can be equally represented in the signal. Cepstrum analysis can be used to give an average estimate of the spacing between the entry and impact events, but the latter can also be assessed by an arithmetic estimation of the mean and standard deviation of the event separation for a number of realizations, in particular for the second approach. In order to determine the effects of various simulations and signal processing parameters on the estimated delay times, the entry and exit events were simulated as modified step and impulse responses with precisely known starting times. The simulation was also found useful in pointing to artefacts associated with the cepstrum calculation, which affect even the simulated signals, and have thus prompted modifications of the processing of real signals. The results presented for the two approaches give a reasonable approximation of the measured fault widths (double the spacing between the entry and impact events) under different speed conditions, but the method of separate treatment is somewhat better and is thus recommended.     

减少滚动轴承车加工留量的分析与实践

实验分析滚动轴承车工各工序留量的减少,通过调整磨工工艺来提高劳动生产率。