一种基于磁力测量的油液铁磁性磨粒监测新方法

针对润滑油中铁磁性磨粒常用监测方法存在的缺点,提出采用磁力测量方法来进行油液铁磁性磨粒的总量监测。分析该方法的测量原理,设计相应的实验装置。实验结果表明,在强磁场作用下,油液中铁磁性磨粒含量与产生的磁力有很好的线性关系,用磁力法监测油液中铁磁性磨粒量是可行的。磁力法对油液中铁磁性颗粒的含量非常敏感,且不受磨粒大小的影响,是一种快速有效的油液铁磁性磨粒监测新方法。     

颗粒污染的双离合变速箱磨粒分析与故障评估

对发生液压阀卡滞的双离合变速箱油液进行磨粒分析，利用铁谱分析仪收集分析油液中磨粒特征，发现铁谱片收集的磨粒尺寸较小，对非铁磁性磨粒的收集能力较弱。为了实现对油液中大粒径磨粒和非铁磁性磨粒的分析，提出一种油液磨粒的综合检测方法。该方法首先利用激光粒度分析方法得到磨粒粒径分布图，从而判断油液中是否存在异常粒径颗粒，再通过滤膜谱片技术收集大粒径磨粒，并通过光学显微镜初步判断颗粒的磨损类型和种类，最后通过X射线荧光光谱分析和扫描电镜-能谱分析方法确定磨粒的具体元素成分，确定磨粒的种类。实例分析结果表明，该方法可有效判断双离合变速箱油液中引起液压阀卡滞的异常粒径磨粒的来源、零部件的磨损类型和磨损程度，也能确定磨粒的物质成分，为变速箱故障预防和产品改进提出了新方法。     

用于铁谱分析技术磁化液的研制及其应用

在利用旋转式铁谱仪生成谱片时，非铁磁性磨屑不能沉积于谱片上，但对于滑动轴承等部件的状态监测，必须利用非铁磁性磨屑来判断其状态。本文利用一种能使非铁磁性磨屑可以磁化的磁流体-磁化液，成功地将非铁磁性磨屑按铁磁性磨屑在谱片上的沉积规律沉积于谱片上，据此，对滑动轴承的磨损成功地进行了预报。同时，本文还提供了适合于不同材料的非铁磁性磨屑的磁化液及其使用规范。     

油液监测分析应用系统数据库的研究

针对油液测试和分析的过程中，所产生的大量原始数据及一系列中间结果数据，为油燃监测技术的实施带来困难这一问题。本文建立了完整的油液监测数据库构架，并在数据库维护实践中，着重介绍了铁谱磨粒图像的采集、存储及提取磨粒图谱特征的方法。     

重型车辆齿轮油污染度和铁谱磨粒含量的关联分析

利用灰色关联分析方法对重型车辆变速箱齿轮油油样监测实验数据进行了分析,探讨了铁谱磨粒浓度和油液污染度之间的关联性.结果表明:重型车辆的齿轮传动系中,铁系颗粒的磨粒含量和大磨粒含量与油液污染度的关联性较强,可利用铁谱磨粒含量的变化趋势来估算润滑油的污染度等级.     

基于巨磁电阻传感器的油液铁磁性磨粒检测研究

针对油料原子发射光谱仪对大于10μm的磨粒检测效率不高,不能有效反映油液磨粒浓度的问题。通过检测经特定磁场磁化和聚集后油样中铁磁性磨粒剩余磁场的大小,来反映油样中铁磁性磨粒浓度大小的方法,利用巨磁电阻磁场传感器,设计一种油液铁磁性磨粒检测装置。该检测装置对同一油样的检测具有较好的重复性;对浓度和尺寸分布均不同的铁磁性磨粒油样,其检测结果并没有因尺寸分布的不同而出现明显的差别。该油液磨粒检测装置可以克服原子发射光谱仪对铁磁性大磨粒检测效率不高,不能有效反映油样铁磁性磨粒浓度的缺点。     

电感式油液磨粒传感器系统设计

油液中的磨粒可反映发动机等设备的磨损状况,为实现油液金属磨粒的在线监测,基于电磁感应原理建立了三线圈传感器的数学模型,通过仿真分析传感器最佳结构参数(内径、间隙、宽度等),利用相干解调模型提取磨粒信号,并分析磨粒信号产生原理.系统采用多层屏蔽结构,可有效减少外部的磁场干扰,设计的传感器检测系统接入风机齿轮箱油路进行相关试验.试验结果表明,本系统可对磨粒信号进行有效提取,且磨粒信号同时受磨粒速度及磨粒尺寸的影响,可在流量为1～18 L/min的工况下实现187 μm铁磁性金属磨粒和578 μm非铁磁性金属磨粒的检测,后续可结合BP神经网络对油液金属磨粒各特征参数进行自适应判别,对今后油液磨粒在线监测设备的开发提供了理论支撑及技术支持,为机械设备故障诊断提供重要依据.     

基于GMR磁传感器的油液铁磁性磨粒在线监测实验研究

为实现对油液中铁磁性磨粒的在线监测,设计搭建一套在线监测装置;基于GMR磁传感器芯片可有效检测微弱磁场的特点,利用GMR磁传感器监测单个铁磨粒被磁化后的剩余磁场;采取"模拟在线"的形式,从GMR磁传感器输出的磁场信号中获取磨粒信息。通过优化装置和试验参数,研究温度、磨粒运动速度对测试系统输出结果的影响,探讨传感器的磨粒检出能力及检出结果的一致性。试验结果显示:在95℃以内的温度和5 cm/s以内的磨粒运动速度条件下,传感器的输出值基本不受影响;运动速度一定时,装置对不同粒度的磨粒输出一致性良好。试验初步表明了GMR磁传感器可用于油液铁磁性磨粒的在线监测,可有效检测出尺寸在75μm以上的铁磨粒。     

一种基于微流体制备的电阻电感式磨粒传感器

为了实现油液金属磨粒的高精度测量,基于微流体制备了一种可检测电阻电感参数的磨粒传感器。通过仿真获得了金属颗粒在时谐磁场中的磁化和涡流效应特征,并通过实验研究了电阻电感检测的电压特性和频率特性。高频激励可以增强金属颗粒内部的涡流效应,而激励电压对传感器检测结果的影响不大。研究表明电感参数对铁磁性金属的检测能力强,电阻参数对非铁磁性金属的检测能力强。采用2.0 V、2.0 MHz的激励,通过比较分析电阻和电感检测结果,该传感器可有效识别直径60 μm的铜颗粒和直径16 μm的铁颗粒。这种基于线圈电阻参数检测非铁磁性金属磨粒的方法为增强磨粒传感器的综合测量性能提供了新思路。     

非铁磁性磨屑在铁谱分析中的磁化机制及力学模型研究

阐述磁化液对非铁磁性磨屑的磁化机制以及非铁磁性磨屑在制谱中的沉积过程.对磁化后的非铁磁性磨屑在梯度磁场中的受力进行分析,结果表明磁化液可以使非铁磁性磨屑有效地沉积在铁谱仪的谱片上,从而能够收集到更加全面的磨损信息.最后通过实验对理论分析结果加以证明.     

Application of magnetization measurements to wear debris analysis

Spectrometric oil analysis for total wear metal amounts is often used to monitor lubricated machinery. In many cases iron is the dominant wear metal, and spectrometric analysis gives good results for total iron. However, iron may be present in several forms such as metal particles, oxides, carbides, sulfates and dissolved ions. A breakdown of total iron into the amounts and forms of iron present should give further valuable insight into wear phenomena taking place inside the machine.In this paper the use of magnetization measurements on samples of used oils and oil filters to obtain information on the forms of iron present in wear debris from lubricated machines is introduced. The measurement technique is described and the magnetic properties of some iron species that might be expected in wear debris are reviewed. This technique provides information on both ferromagnetic and paramagnetic species through the observation of various magnetic properties. Several illustrative examples are included. The ability of this technique to detect the paramagnetic as well as the ferromagnetic components is important because it is often found that the majority of the iron in wear debris is paramagnetic. A correspondence between the measured ferromagnetic component and ferrography is also shown for some cases.     

融合颜色与形状信息的铁谱磨粒链分割方法研究

为了对铁谱图像中的磨粒链进行有效分割,提高磨粒特征提取的精度,通过分析铁谱磨粒链图像不同区域的特点,提出一种融合铁谱图像颜色、形状特征信息的磨粒链分割方法。该方法首先基于形态学运算对磨粒链分割方法,对异常大磨粒进行提取并断开磨粒链黏连部分,然后利用标记分水岭与灰色聚类的方法对磨粒链进行分割,最后考虑到不同磨粒链颜色信息存在差异,结合自适应阈值法对灰色聚类进行改进,从而实现磨粒链的自适应分割。结果表明,相较于传统分割方法,提出的方法能有效避免过分割与欠分割,分割效果较好,适用性高,操作简单。     

Advances in quantitative analytical ferrography and the evaluation of a high gradient magnetic separator for the study of diesel engine wear

Several sources of variation in quantitative analytical ferrography are investigated. A standard ferrography analysis procedure is developed. Normalization of ferrographic data to account for the amount of oil used to make the Ferrograms is discussed. Procedures to minimize the errors involved in calculating three quantitative ferrography parameters, i.e. the area A_L (% (ml of oil)⁻¹) covered by the large particles, the area A_S (% (ml of oil)⁻¹) covered by the small particles and the area under the curve (millimeters per cent per milliliter of oil) are outlined. Ferrographic data are presented which show that the volume and dilution ratio of the oil sample being analyzed have a major effect on the accuracy of the analysis. Several variables which influence the area-covered readings of the particle deposit on a Ferrogram are discussed. The accuracy of quantitative analytical ferrography is assessed.

Quantitative analytical ferrography is used to evaluate a high gradient magnetic separator (HGMS), both as a tool for engine wear research and as an oil filter. Laboratory tests indicate that the HGMS is an order of magnitude more efficient than conventional paper oil filters in removing magnetic wear debris from the lubricating oil.     

The development of ferrography in China—some personal reflections

Ferrography was first introduced into China over 20 years ago. Since then, academic research on wear debris formation mechanisms, intelligent identification of wear particle and other aspects have been carried out. Successful application of ferrography to machine condition monitoring in industry has been achieved with attendant cost benefits. Academic research has accelerated the development of ferrography, in which British scientists have made a considerable contribution to it. The future of ferrography is encouraging.     

齿轮磨损状态的在线铁谱监测试验研究

对ＯＬＦ１在线铁谱仪用于齿轮磨损状态的监测进行了研究。试验数据分析表明，ＯＬＦ－１在线铁谱仪对大磨粒有很强的敏感性，其采样值的大小和变化反映了齿面状态的变化。在正常磨损情况下，采样值曲线比较平稳；而一旦采样值出现无规律波动，则意味着不正常磨损的开始。与分析铁谱仪数据对比，也显示出非常近似的变化趋势。因而，ＯＬＦ－１在线铁谱仪用于齿轮磨损状态的实时和连续监测具有良好的性能。本文同时指出，ＯＬＦ－１在线铁谱与其它油液分析技术相结合，可以更准确地进行齿轮磨损状态的监测和诊断     

磨损颗粒的模糊神经网络识别研究

在传统的模式识别技术中，模式分类的基本方法是利用判别函数来划分不同的类别，然而如何选择有效的判别函数以及在识别过程中如何对判别函数的参数进行修正，对于以往的模式识别技术是比较困难的。针对油液铁谱分析中磨损颗粒的识别问题，讨论了一般机械设备的磨损颗粒的特征，分析了神经网络技术和模糊数学相结合的模式，提出了基于模糊神经网络的铁谱图象分类和识别方法，分析结果表明，提出的方法对铁谱分析的智能化和快速化提供一种有效的途径。     

用于铁谱分析磁化液使用规范的研究

本文简述了铁谱分析技术和磁化液的基本原理。在大量试验的基础上，建立了用于铁谱分析技术磁化液的使用规范。     

Ferrography—then and now

Since 1971, when ferrography was first introduced, there have been many developments in the techniques used to process samples and also the way in which debris is analysed and interpreted in relation to the underlying causes that produced them. The science and application of ferrography embraces both the engineering and medical fields and this has led to new and exciting ways of understanding the associated phenomena and how to extract the best information for the advancement of the subject matter.The purpose of this special issue is to provide an overview of some of the principal developments that have taken place over the past three decades, thereby placing on record what is widely acknowledged to be one of the most significant developments in the field of wear debris technology.     

基于油样分析技术的钻井泵寿命预测

通过跟踪3台不同运行时间钻井泵的油样的铁谱和光谱分析数据,发现随着使用时间的增多,设备磨损加大,油样中Al、Cu、Fe等金属元素含量明显增加,在泵接近损坏时,铁谱显示油液中存在严重滑动磨粒和球形磨粒,磨粒链加密并伴有疲劳剥离磨屑;光谱显示铁质含量陡增。分析了磨损产生的机制并提出了减少磨损的方法,提出了将金属磨屑增长的速率作为状态考察的重要判断指标。分析结果表明,通过油样检测分析可预报泵动力端轴承等摩擦副的运行状态,为泵的大修时间的确定以及提高泵的工作寿命提供了科学的依据。