Condition monitoring studies on spindle bearing of a lathe

In modern industry, machinery must become increasingly flexible and automatic. In order to increase productivity, enhance quality and reduce cost, machine tools have to work free of any failure. When a failure occurs in a machine tool, it is necessary to identify the causes as early as possible. Machine tool condition monitoring is very important to achieve this goal. Condition monitoring is generally used on the critical subsystem of any machine tool. This paper endeavors to focus on the condition monitoring aspects on the machine tool element. In the present study, a critical subsystem has been identified based on the failure data analysis. Condition monitoring techniques like vibration monitoring, acoustic emission, Shock Pulse Method (SPM) and surface roughness have been successfully used for fault identification.     

Influence of operational variables in a hydrodynamic bearing on the generation of acoustic emission

Detecting mechanical faults of rotating machines particularly in hydrodynamic bearings has been recognised as important for preventing sudden shut downs. This technical note presents an experimental investigation that is aimed at understanding the influence of operational variables (speed, load, etc) on generation of acoustic emission in a hydrodynamic bearing. It is concluded that the power losses of the bearing are directly correlated with acoustic emission levels.     

Sifting process of EMD and its application in rolling element bearing fault diagnosis

Among the vibration-based fault diagnosis methods for rolling element bearing, the shock pulse method (SPM) combined with the demodulation method is a useful quantitative technique for estimating bearing running state. However, direct demodulation often misestimates the shock value of characteristic defect frequency. To overcome this disadvantage, the vibration signal should be decomposed before demodulation. Empirical mode decomposition (EMD) can be an alternative for preprocess bearing fault signals. However, the trouble with this method’s application is that it is time-consuming. Therefore, a novel method that can improve the sifting process’s efficiency is proposed, in which only one time of cubic spline fitting is required in each sifting process. As a consequence, the time for EMD analysis can be evidently shortened and the decomposition results simultaneously maintained at a high precision. Simulations and experiments verify that the improved EMD method, combined with SPM and demodulation analysis, is efficient and accurate and can be effectively applied in engineering practice. This paper was recommended for publication in revised form by Associate Editor Eung-Soo Shin Hongbo Dong was born in Chaoyang, China, in 1979. He received the B.E. and M.E. degree from Northwestern Polytechnical University in Mechanical Engineering in 2002 and 2005 respectively and received the Ph.D degree from Xi’an Jiaotong University in Mechanical Engineering in 2009. His research interests include fault diagnosis of rotor and bearing system. Bing Li was born in Xuzhou, China, in 1976. He received the B.E. and M.E. degree from Northwestern Polytechnical University in Mechanical Engineering in 1999 and 2002 respectively and received the Ph.D degree from Xi’an Jiaotong University in Mechanical Engineering in 2005. After graduating from Xi’an Jiaotong University, he works as a lecturer in Xi’an Jiaotong University. His research interests include wavelet finite element theory and its application in fault diagnosis.     

The possibility of evaluating turbo-set bearing misalignment defects on the basis of bearing trajectory features

This paper presents the results of computer simulation of bearing misalignment defects in a power turbogenerator. This malfunction is typical for great multi-rotor and multi-bearing rotating machines and very common in power turbo-sets. Necessary calculations were carried out by the computer code system MESWIR, developed and used at the IFFM in Gdansk for calculating dynamics of rotors supported on oil bearings. The results are presented in the form of a set of journal and bush trajectories of all turbo-set bearings. Our analysis focuses on the vibrational effects of displacing the two most vulnerable machine bearings in horizontal and vertical directions by the maximum acceptable range calculated with regard to bearing vibration criterion. This assumption required preliminary assessment of the maximum values for the permissible bearing dislocations. We show the relations between the attributes of the particular bearing trajectories and the bearing displacements in relation to their base design position. The shape and dimensions of bearing trajectories are interpreted based on the theory of hydrodynamic lubrication of oil bearings. It was shown that the relative journal trajectories and absolute bush trajectories carry much important information about the dynamic state of the machine, indicating also the way in which bearings are loaded. Therefore, trajectories can be a source of information about the position and direction of bearing misalignments. This article indicates the potential of using trajectory patterns for diagnosing misalignment defects in rotating machines and suggests including sets of trajectory patterns to the knowledge base of a machine diagnostic system.     

A method for detecting tool wear on a CNC lathe using a doppler radar detector

Installing a non-contact in-process tool wear detection system on a computer numerical control lathe can help prevent product defects and improve product quality without impacting product cycle time. Many methods have been proposed for non-contact in-process tool wear detection. In particular, a recent international patent application describes a method for measuring the torque in a rotating axle using a high-frequency wireless transmitter/receiver and a vibrating string. The method has reportedly been used to detect cutting on a manual lathe. The authors present a new method for measuring tool wear using a high-frequency wireless transmitter/receiver alone, without a vibrating string. The high-frequency transmitter/receiver apparently responds to metal-metal contact noise rather than, or more strongly than, to signals generated by a vibrating string. The findings could help bring automated tool wear monitoring systems closer to the level of performance needed for practical use in industry.     

The combined use of vibration, acoustic emission and oil debris on-line monitoring towards a more effective condition monitoring of rotating machinery

The monitoring of progressive wear in gears using various non-destructive technologies as well as the use of advanced signal processing techniques upon the acquired recordings to the direction of more effective diagnostic schemes, is the scope of the present work. For this reason multi-hour tests were performed in healthy gears in a single-stage lab scale gearbox until they were seriously damaged. Three on-line monitoring techniques are implemented in the tests. Vibration and acoustic emission recordings in combination with data coming from oil debris monitoring (ODM) of the lubricating oil are utilized in order to assess the condition of the gears. A plethora of parameters/features were extracted from the acquired waveforms via conventional (in time and frequency domain) and non-conventional (wavelet-based) signal processing techniques. Data fusion was accomplished in the level of integration of the most representative among the extracted features from all three measurement technologies in a single data matrix. Principal component analysis (PCA) was utilized to reduce the dimensionality of the data matrix whereas independent component analysis (ICA) was further applied to identify the independent components among the data and correlate them to different damage modes of the gearbox. Finally heuristic rules based on characteristic values of the resulted independent components were set, realizing thus a health monitoring scheme for gearboxes.The integration of vibration, AE and ODM data increases the diagnostic capacity and reliability of the condition monitoring scheme concluding to very interesting results. The present work summarizes the joint efforts of two research groups towards a more reliable condition monitoring of rotating machinery and gearboxes specifically.     

The application of spectral kurtosis on Acoustic Emission and vibrations from a defective bearing

The application of Acoustic Emission (AE) technology for machine health monitoring is gaining ground as power tool for health diagnostic of rolling element bearing. This paper provides an investigation that compares the applicability of AE and vibration technologies in monitoring a naturally degraded roller bearing. This research is the first known attempt investigating the comparative effectiveness of applying the Kurtogram to both vibration and AE data from a defective bearing.     

The implementation of optimum MRR on digital PC-based lathe system

Optimizing the profit of an individual cutting tool is crucial to the computer numerically controlled (CNC) machining industry. In this paper, the mathematical modeling, the dynamic solution, and the decision criteria through calculus of variations are introduced to achieve the optimal material removal rate (MRR) control of a cutting tool under the fixed tool life. To realize the optimum MRR, a commercialized lathe system with a digital processor controller (DSP) and a man-machine interface is developed. Additionally, the implementation of dynamic MRR control for a real-world industrial case is experimentally performed on our proposed digital PC-based lathe system. It is found that the surface roughness (R _a ) of all machined work-pieces not only stabilizes as the tool consumed, but also accomplishes the recognized standard for finish turning. In this study, the adaptability of the dynamic control of optimum MRR as well as the realization of the digital PC-based lathe system are absolutely guaranteed.     

Bearing load distribution studies in a multi bearing rotor system and a remote computing method based on the internet

A model in the form of a Bearing Load Distribution (BLD) matrix in the Muiti Bearing Rotor System (MBRS) is established by a transfer matrix equation with the consideration of a bearing load, elevation and uniform load distribution. The concept of Bearing Load Sensitivity (BLS) is proposed and matrices for load and elevation sensitivity are obtained. In order to share MBRS design resources on the Internet with remote customers, the basic principle of Remote Computing (RC) based on the Internet is introduced ; the RC of the BLD and BLS is achieved by Microsoft Active Server Pages (ASP) technology.     

基于BP神经网络的表面粗糙度声发射预测

介绍了BP神经网络的原理、算法和公式,在对Matlab及其神经网络工具箱介绍的基础上,采用声发射信号有效值、FFT峰值和标准差作为输入,工件表而粗糙度作为输出,用BP神经网络的方法对高效深磨加工工程陶瓷Al2O3的工件表面粗糙度进行了训练、预测和分析.创新的研究方法是直接从磨削声发射信号中提取磨削表面粗糙度信息.结果表明,该方法可以实现高效深磨加工工程陶瓷工件表面粗糙度的监测.     

The use of SESK as a trend parameter for localized bearing fault diagnosis in induction machines

A critical work of bearing fault diagnosis is locating the optimum frequency band that contains faulty bearing signal, which is usually buried in the noise background. Now, envelope analysis is commonly used to obtain the bearing defect harmonics from the envelope signal spectrum analysis and has shown fine results in identifying incipient failures occurring in the different parts of a bearing. However, the main step in implementing envelope analysis is to determine a frequency band that contains faulty bearing signal component with the highest signal noise level. Conventionally, the choice of the band is made by manual spectrum comparison via identifying the resonance frequency where the largest change occurred. In this paper, we present a squared envelope based spectral kurtosis method to determine optimum envelope analysis parameters including the filtering band and center frequency through a short time Fourier transform. We have verified the potential of the spectral kurtosis diagnostic strategy in performance improvements for single-defect diagnosis using real laboratory-collected vibration data sets.     

Experimental investigation of the effect of lead errors on helical gear and bearing vibration transmission characteristics

The characteristics of gear meshing vibration undesgo change as the vibration is transmitted from the gear to the housing. Therefore, vibration transmission characteristics of helical gear systems must be understood before the effective methods of reducing gear noise can be found. In this work, using a helical gear with different lead errors, the gear vibration in the rotational direction and the bearing vibration are measured. The frequency characteristics of gear and bearing vibration are investigated and a comparson is also provided.     

Combined effects of surface roughness and viscosity variation due to additives on long journal bearing

Abstract

The combined effects of surface roughness and viscosity variation due to additives on long journal bearing are analytically studied. The variation in viscosity along the film thickness is considered. The presence of solid particles in the lubricant is an increased effective viscosity, which increases the load carrying capacity and decreases the frictional coefficient, whereas the viscosity variation tends to decrease both the load carrying capacity and coefficient of friction for non-micropolar fluid case. The modified Reynolds type equation for surface roughness has been derived on the basis of Eringen’s micropolar fluid theory. The generalised stochastic random variable with non-zero mean, variance and skewness is assumed to mathematically model the surface roughness on the bearing surface. Numerical results were obtained for the fluid film pressure, load carrying capacity and the coefficient of friction. It is observed that the combined effect is to increase the load carrying capacity and to decrease the coefficient of friction, which improves the performance of the bearing.     

小波再分配尺度谱在声发射信号特征提取中的应用

在分析典型声发射(Acoustic emission, AE)信号特征的基础上,根据机械故障或损伤引发的AE信号的故障特征提取原理和特点,首次提出AE信号的小波再分配尺度谱分析法.将小波尺度谱和再分配尺度谱同时用于AE信号的特征提取,再分配尺度谱能提高尺度图的聚集性,减少干扰项,更准确地表征AE信号中的特征信息.通过理论研究和仿真,确定了小波再分配尺度谱基函数及其参数的选择,克服了小波再分配尺度谱的时、频分辨率不能同时达到最好的缺陷.将小波再分配尺度谱用于声发射检测的滚动轴承损伤类型及部件的识别,诊断结果十分直观、清晰、准确.仿真分析和试验研究均表明了小波再分配尺度谱能有效应用于基于声发射技术的状态监测和故障诊断.     

Effect of surface roughness on the static characteristics of inclined plane slider bearing: Rabinowitsch fluid model

In this paper, a theoretical study of the effect of surface roughness on the static characteristics of inclined plane slider-bearing lubricated with Rabinowitsch fluid is analysed. Christensen’s stochastic theory for the lubrication of rough surfaces has been used for the derivation of generalised stochastic Reynolds-type equation. The two types of one-dimensional roughness patterns (Longitudinal and Transverse) are considered. Expressions for pressure, load carrying capacity, frictional force and coefficient of friction are obtained. It is found that the presence of transverse roughness pattern on the bearing surface increases pressure and load carrying capacity. Results are well agreement with smooth case.     

A neural-network-based methodology for the prediction of surface roughness in a turning process

A neural-network-based methodology is proposed for predicting the surface roughness in a turning process by taking the acceleration of the radial vibration of the tool holder as feedback. Upper, most likely and lower estimates of the surface roughness are predicted by this method using very few experimental data for training and testing the network. The network model is trained using the back-propagation algorithm. The learning rate, the number of neurons in the hidden layer, the error goal, as well as the training and the testing dataset size, are found automatically in an adaptive manner. Since the training and testing data are collected from experiments, a data filtration scheme is employed to remove faulty data. The validation of the methodology is carried out for dry and wet turning of steel using high speed steel and carbide tools. It is observed that the present methodology is able to make accurate prediction of surface roughness by utilising small sized training and testing datasets.     

干摩擦条件下载荷动特性对摩擦面粗糙度的影响

在自行研制的环 -块磨损试验装置上研究了干摩擦状态下矩形波载荷特性对摩擦面粗糙度的影响 ,结果表明 :1随着磨程的进行 ,摩擦面粗糙度将达到一个稳定值—平衡粗糙度 ,其大小与摩擦面初始形貌无关 ;2当载荷波形占空比 φ较小时 ,平衡粗糙度 Rsq 对φ的变化敏感 ,且随 φ的增加而增加。当 φ足够大时 ,Rsq 几乎不随 φ而变化     

FEM analysis of the vibrational motion of oblique piezoelectric microcantilever in the vicinity of a sample surface in liquid

This article examines an oblique Microcantilever (MC) with an extended piezoelectric layer in liquid. The study of hydrodynamic force in MC which has been floated in viscous fluid is considered as paramount importance. To model the Vibrational motion, the Hamilton's principle has been used. For this purpose, the Vibrational motion equation has been modeled by considering the continuous beam based on the Euler–Bernoulli beam theory in liquid. Furthermore, using the Galerkin method and the Newmark algorithm, the differential equations of the MC has been solved. In this modeling, the inter-atomic forces between the MC tip and the sample surface have been considered in addition to the hydrodynamic and squeeze forces. The simulation results illustrate a reduction in the sensitivity of the vibrational motion under the effect of the squeeze force during the angularization of the MC. Moreover, the results illustrate that by reducing the MC distance from the sample surface, the Vibration amplitude decreases due to the increase in the fluid squeeze force. At the end, it has been shown that the time delay in sample surface topography in liquid substantially decreases in comparison with the air.     

空间飞轮轴承滚道氮离子注入改性工艺研究

针对空间飞轮轴承工作特性,为改善轴承摩擦磨损性能,采用等离子体浸没离子注入(PIII)技术,对轴承内外滚道进行氮离子注入改性处理.对比改性前后轴承主要几何尺寸和形位公差,精度变化量在(1～2)μm;改性前后陪试件表面粗糙度量级相同,Ra值均小于0.04μm;装配后轴承旋转精度为2μm,基本无变化.摩擦学性能对比测试表明:改性后陪试件的摩擦系数为基体的1/5;空间飞轮轴承组件精密装配后,反映其摩擦性能的跑合电流由改性前的196mA降为162mA.     

Monitoring of Ball Bearing Operation under Grease Lubrication Using a New Compound Diagnostic System Detecting Vibration and Acoustic Emission

Our new compound diagnostic system comprised of a compound sensor, a signal processor, and a personal computer installed signal processing software. The compound sensor made by an advanced sensor fusion technique was able to detect simultaneously the vibration acceleration and the acoustic emission by itself. The signal processor received a signal from the sensor and separated it into the vibration acceleration signal and the acoustic emission signal. The signal processor and the personal computer processed the acceleration signal and acoustic emission signal for diagnostic information. The rolling contact fatigue process of a ball bearing under grease lubrication was monitored using the compound system. The system outputs diagnostic information, for example, the means, the variance, the skewness, and the kurtosis of the vibration acceleration signal and the acoustic emission signal. In diagnosing the rolling contact fatigue failure, the root mean square (rms) value of the vibration acceleration was most effective, and the mean of the demodulated acoustic emission was second to the rms value of the acceleration in effectiveness. From the result of the evaluation, it became clear that the system was useful for diagnosing rolling contact bearings under grease lubrication.