Morphological covering based generalized dimension for gear fault diagnosis

This investigation presents a new generalized dimension estimation method based on morphological covering (MC) technique for characterizing the nonlinearity and complexity of vibration signals measured from gearbox. A synthetic fractal signal is employed to evaluate and compare the proposed MC technique with the traditional box-counting (BC) method and a similar approach developed in literature. Results revealed that the presented MC method is the one providing the most reliable generalized dimension estimation results. Furthermore, we applied this scheme to analyze the vibration signals from a gearbox with three operation states. The estimated general dimensions are used as the input feature vector for classifiers to the gear working states. Experimental results showed that our presented scheme achieves the best performance on discriminating the gear conditions. We also explore the calculational efficiency of the MC method. Results demonstrated that the MC method requires much less computational cost than BC method and seems to be more suitable for on-line condition monitoring of gearboxes.     

Simulating the dynamic behavior of planetary gearbox based on improved Hanning function

Planetary gearboxes are widely used in industrial machines. They usually work in harsh environments giving rise to damages and high maintenance costs. Condition monitoring is a key action allowing one to detect the presence of such damage ensuring healthy running conditions. The knowledge of the dynamic behavior of such a gearbox can be achieved using modeling tools as a primary step before conditioning the monitoring subject. In addition, modeling a gear set can help in the stage of design in order to optimize physical and geometric parameters of the system. Therefore, in this work, a two-dimensional lumped parameter model is adopted to build all vibration sources. The time-varying mesh stiffness is approximated as a square wave form. A novel mathematical formulation is proposed to model the amplitude modulation phenomenon due to the rotational motion of the planets around the center of the gearbox. Finally, the overall vibration signal is concluded as a summation of all vibration components influenced by the modulation function.     

Modelling of gearbox dynamics under time-varying nonstationary load for distributed fault detection and diagnosis

Fault detection and diagnosis in mechanical systems during their time-varying nonstationary operation is one of the most challenging issues. In the last two decades or so researches have noticed that machines work in nonstationary load/speed conditions during their normal operation. Diagnostic features for gearboxes were found to be load dependent. This was experimentally confirmed by a smearing effect in the spectrum.In order to better understand the involved phenomena and to ensure agreement between simulation and experimental results, two models of gearboxes (a fixed-axis two-stage gearbox and a planetary gearbox) operating under varying load conditions are proposed. The models are based on two mechanical systems used in the mining industry, i.e. the belt conveyor and the bucket wheel excavator. An original transmission error function expressing changes in technical condition and load variation is presented.Energy based parameters (the signal RMS value or the arithmetic sum of the amplitudes of spectral gearmesh components) are adopted as the diagnostic features. Simulation results show a strong correlation between load values, changes in condition and the diagnostic features. The findings are key to condition monitoring. Thanks to the use of the models one can better understand the phenomena identified through an analysis of vibration signals captured from real machines.     

基于时频变换的激波风洞天平信号分析与处理

在激波风洞中开展测力试验时,测力系统在风洞流场起动瞬间会受到冲击激励,从而对天平的输出信号产生惯性干扰.天平输出信号中叠加有动态气动力信号和惯性振动信号,有可能无法直接分辨出气动力信号的规律性,信号处理结果与真实气动力之间会产生较大的误差,导致处理结果不可靠.由于模型测力天平系统结构的复杂性,在极短的有效试验时间(毫秒...     

循环神经网络在智能天平研究中的应用

激波风洞地面试验对高超声速飞行器高焓气动特性研究至关重要, 而高精度气动力测量是其中的关键技术. 在脉冲型激波风洞中进行测力试验时, 风洞起动时流场瞬间建立, 对测力系统会产生较大的冲击. 测力系统在瞬时冲击作用下受到激励, 系统的惯性振动信号在短时间内无法快速衰减, 天平的输出信号中会包含惯性振动干扰量, 导致脉冲型风洞测力试验精准度的进一步提高遇到瓶颈. 为了解决短试验时间内激波风洞快速准确测力问题, 发展高精度的动态校准技术是提升受惯性干扰天平性能的关键方法. 因此, 本文采用循环神经网络对天平动态校准数据进行训练和智能处理, 旨在消除输出动态信号中的振动干扰信号. 本文对该方法进行了误差分析, 验证了该方法的可靠性, 并将该方法应用于激波风洞测力试验中, 切实有效降低了惯性振动对天平输出信号的干扰影响. 根据智能模型的样本验证分析, 各分量载荷相对误差比较小, 其中高频轴向力分量处理结果的相对误差约1%. 在风洞试验数据验证中, 也得到了比较理想的结果, 同时与卷积神经网络模型处理的结果进行了对比分析.      

Evaluation of the fatigue life of a tractor’s transmission spiral bevel gear

Conventional tractor transmission spiral bevel gears are designed and evaluated based on the engine rated load, which is significantly higher than the load conditions in the field. In this study, the fatigue life of a spiral bevel gear is evaluated to obtain data for design optimization. The equivalent load was calculated using the field load data, and the integrated equivalent load was calculated based on the annual usage of major field operations in Korea. The fatigue life of three spiral bevel gear samples was evaluated using the accelerated life test (ALT) under an engine rated load condition of 120%. It was also evaluated under engine rated, plow equivalent, and integrated equivalent load. Fatigue life was estimated using the ALT results and the fatigue damage exponent based on the ALT equation. We observed that the fatigue life of the spiral bevel gear under the plow equivalent and integrated equivalent loads is higher than that under the rated load by 214 and 9,400 times, respectively. The results of this study can provide useful information for the design optimization of tractor transmission spiral bevel gears considering the field equivalent load.     

Application of energy operators for detection of failures in gearboxes

The paper presents the possibility of detection of early stages of local faults in gears using energy operators. During operation of gearbox, the local faults, such as pitting or tooth base fracture, are causing disturbances in the teeth contacts resulting in creation of local and transient anomalies in a vibration signal. Analysis performed on the diagnostic signal are focused on, as early as possible, detection of such anomalies but also on assess localization of defects and remaining useful life of gears. Methods of signal analysis presented in the paper allow detection of local nonstationarities in the time-domain vibration signal. It is assumed that such transient events are linked to the fatigue tooth damages. Described methods use energetic operators for obtaining diagnostically useful information.     

Near-wall imaging using toluene-based planar laser-induced fluorescence in shock tube flow

A quantitative thermometry technique, based on planar laser-induced fluorescence (PLIF), was applied to image temperature fields immediately next to walls in shock tube flows. Two types of near-wall flows were considered: the side wall thermal boundary layer behind an incident shock wave, and the end wall thermal layer behind a reflected shock wave. These thin layers are imaged with high spatial resolution (15μm/pixel) in conjunction with fused silica walls and near-UV bandpass filters to accurately measure fluorescence signal levels with minimal interferences from scatter and reflection at the wall surface. Nitrogen, hydrogen or argon gas were premixed with 1–12% toluene, the LIF tracer, and tested under various shock flow conditions. The measured pressures and temperatures ranged between 0.01 and 0.8 bar and 293 and 600 K, respectively. Temperature field measurements were found to be in good agreement with theoretical values calculated using 2-D laminar boundary layer and 1-D heat diffusion equations, respectively. In addition, PLIF images were taken at various time delays behind incident and reflected shock waves to observe the development of the side wall and end wall layers, respectively. The demonstrated diagnostic strategy can be used to accurately measure temperature to about 60 μm from the wall.     

The application of pattern recognition techniques in fault diagnosis of machinery equipment

In this paper,the characteristics of vibration signal of machinery in different runningconditions are statistically analysed,and some moments of statistical distribution of signalsare selected as the eigenvector to condense the state information.Here,we divide the statesof machinery into two:‘good’and‘aulty’,and the pattern recognition techniques are usedto classify the running conditions of machinery.At the end of this paper,the authors presentsome test data,and from the results obtained,it’s verified that the eigenvector selected isreliable and sensible to faults.And the results also show the effectiveness of classificationrule.     

On steady,inviscid shock waves at continuously curved,convex surfaces

An accurate and efficient numerical method for steady, two-dimensional Euler equations is applied to study steady shock waves perpendicular to smooth, convex surfaces. The main subject of study is the flow near both ends of the shock wave: the shock-foot and shock-tip flow. A known analytical model of the inviscid shock-foot flow is critically investigated, analytically and numerically. The results obtained agree with those of the existing analytical model. For the inviscid shock-tip flow, two existing analytical solutions are reviewed. Numerical results are presented which agree with one of these two solutions. Good numerical accuracy is achieved through a monotone, second-order accurate, finite-volume discretization. Good computational efficiency is obtained through iterative defect correction iteration and a multigrid acceleration technique which employs local grid refinement.This work was performed as part of a BRITE/EURAM Area 5 project, under Contract No. AERO-0003/1094.     

The effects of Coulomb friction on the performance of centrifugal pendulum vibration absorbers

We investigate analytically and experimentally the effects of Coulomb friction on the performance of centrifugal pendulum vibration absorbers (CPVAs), which are used to reduce torsional vibrations in rotating machinery. The analysis is based on perturbation methods applied to the nonlinear equations of motion for a rotor subjected to an engine order applied torque and equipped with a circular path CPVA with viscous and Coulomb damping. The experimental work is based on quantifying parameters for the damping model using free vibration measurements with a viscous and Coulomb damping identification scheme that is enhanced to better handle measurement noise, and running tests for steady-state operation under a range of loading conditions. The level of Coulomb damping is varied by adjusting the friction of the absorber connection bearing. Good agreement is found between the analytical predictions and the experimental data. It is shown that the absorber sticks up to a level of excitation that allows it to release, after which the Coulomb damping acts in the expected manner, resulting in lowered response amplitudes. The results obtained are of general use in assessing absorber performance when dry friction is present in absorber suspensions.     

基于小波变换的爆破振动信号能量分布特征分析

为了深入研究爆破地震波特性,应用小波变换方法对具有短时非平稳特点的爆破振动信号进行了能量分布特征分析。根据小波变换的时-频特性和分层分解展开关系,将爆破振动时间历史信号用分层重构信号进行扫描,应用这些信号得到了不同频率带上爆破振动的相对能量分布和振动强度的时间变化规律。爆破振动信号实测结果分析表明,基于小波变换的能量分布特征分析可以更准确地给出爆破振动信号的细节信息。研究结果为分析爆破振动结构安全性提供了新的途径。     

一种基于领域自适应的跨工况滚动轴承故障诊断新方法

机械设备在运转时,不同状态下滚动轴承监测数据存在较大分布差异且难以获取带标签的数据,导致现有模型在跨工况条件下故障诊断准确率低.针对滚动轴承跨工况诊断难题,论文提出一种基于领域自适应的跨工况滚动轴承故障诊断方法,该方法首先提取振动信号故障敏感特征,并将其嵌入Grassmann流形空间,避免直接进行特征变换导致特征失真;...     

The Application of Advanced Signal Processing Techniques to Induction Motor Bearing Condition Diagnosis

Four approaches based on bispectral and wavelet analysis of vibration signals are investigated as signal processing techniques for application in the diagnosis of a number of induction motor rolling element bearing faults. The bearing conditions considered are a normal bearing and bearings with cage and inner and outer race faults. The vibration analysis methods investigated are based on the bispectrum, the bispectrum diagonal slice, the summed bispectrum and wavelets. Singular value decomposition (SVD) is used to extract the most significant features from the vibration signatures and the features are used as inputs to an artificial neural network trained to identify the bearing faults. The results obtained show that the diagnostic system using a supervised multi-layer perceptron type neural network is capable of classifying bearing condition with high success rate, particularly when applied to summed bispectrum signatures.     

振动台数字控制系统中的多微机并行处理技术

本文在深入分析振动台对数字振动控制系统要求的基础上，提出了在数字振动控制系统中采用多微机主从式并行处理的方法，并阐述了ＰＣ３８６微机分别与ＴＭＳ３２０Ｃ２５信号处理器和Ｚ８０微机系统实现数据通讯的控制策略。     

爆破震动信号模极大值小波消噪方法的改进

针对模极大值小波消噪方法不利于所有信号特征的识别这一缺点,对该算法进行了改进,采用自适应的小波尺度来替换二进小波尺度,以更好地适应测试信号消噪的要求。应用改进前、后的消噪算法分别对实测爆破震动信号进行了分析,并将分析结果进行了比较。比较结果说明:改进后的算法消噪效果更好,消噪后信号同轴清晰、连续性好,信噪比由17.25提高到20.16,可以更好地实现爆破震动信号消噪的目的。     

振动信号检测技术研究及其在故障诊断中的应用

针对复杂机械系统异常振动信号的检测,提出一种新的无混叠指数双线性时间-频率变换探测方法,新变换方法可以避免常用双线性变换中的频率混叠和信息丢失等问题,能够有效的抑制交叉项,具有较高的时频分辨率,给出新的双线性时-频变换的离散算法,通过仿真实验与齿轮箱早期故障检测,对新的时频变换的检测效果进行了验证。     

Spectral simulation and shock absorber identification

In vehicle dynamics shock absorbers are used for the optimization of driving comfort and driving safety. Therefore, it is necessary to identify characteristics of shock absorbers under real conditions. This paper introduces the use of hardware-in-the-loop simulations for the identification of shock absorbers involving stochastic models of the road roughness. For this purpose a dynamic hydraulic test stand is used replacing the classical mechanical test stands which allow only sinusoidal excitation. For the Monte Carlo simulation with a real shock absorber in the loop, the random excitation of ground roughness is generated using a modified spectral representation method based on the famous contributions of Shinozuka. Motion and force of the shock absorber are measured and fed back to the Monte Carlo simulation of a car model in real time. The characteristic of the shock absorber is identified using the classical least squares method and a correlation-based method. A piecewise linear model for the characteristic relating the damping force and the velocity of the piston is applied for the shock absorber identification.     

爆炸冲击振动下人体抛离问题的分析

采用单自由度模型研究了爆炸冲击振动下人体抛离问题。提出了人体抛离的飞离条件,推导了人体飞离时刻和飞离速度计算公式,为定量研究爆炸冲击振动下人员冲击伤和碰撞伤及人员隔冲问题提供了参考。     

Free transverse vibration analysis of a toothed gear

Analysis of transverse vibration of the gear found in a high-speed gearbox considered as an annular plate reflecting gear geometry is the subject of this paper. How gear angular velocity affects the deformation of normal modes of transverse vibration of the system under consideration is analysed. Models considered were discretized by the finite elements method. Numerical computations have been performed in the ANSYS environment. The algorithm to identify the proper distorted mode shapes is presented. The Campbell diagram for the system under consideration is elaborated. The problems discussed here can be useful for engineers dealing with dynamics of rotating machine systems.