A New On-Line Visual Ferrograph

An on-line visual ferrograph (OLVF) characterized by direct reading and on-line analysis was developed based on magnetic deposition and image analysis. A digital sensor was integrated with a CMOS image sensor to obtain images of deposited wear debris under illumination conditions. An electromagnetic instrument was designed to deposit the wear debris flowing through an oil flow channel. The oil flow channel, fixed on the electromagnet, was arranged parallel to the magnetic flux in the air gap between two electromagnet poles. The deposition effect on wear debris was analyzed theoretically. The result shows that the wear debris in different sizes can be deposited in the same zone by controlling the oil flow rate and magnet field intensity. Corresponding application software for image sampling and processing was developed. An index of relative wear debris concentration, IPCA (Index of Particle Coverage Area), is given as an output in addition to wear debris images. Finally, two kinds of experiments were specified to assess the effect and validity of the OLVF. The results show that the OLVF has effective deposition and identification for both relatively large and small wear debris with rational control parameters. The validity examinations with the commercial particle quantifier (PQ) and direct reading ferrograph (DR) show that the OLVF has an approaching trend to the reference instruments in both heavily and lightly contaminated oil.     

图像可视在线铁谱传感器的图像数字化处理技术

为实现图像可视在线铁谱传感器的磨粒图像自动辨识,建立数字图像获取系统,探讨铁谱图像数字化处理方法。研究了铁谱图像的预处理方法,对比在RGB和YUV颜色空间对铁谱图像的灰度化处理效果,采用不同的微分模板对平滑后图像进行锐化处理;探讨减背景法和自动阈值法在铁谱图像磨粒分割中的应用效果;给出适用于在线铁谱图像的定量描述方法。研究表明,采用YUV颜色空间的明视度分量可以得到平滑的灰度图像,合理的模板选择可以使微分法在锐化磨粒边缘的同时保持整体图像的平滑;铁谱图像的磨粒分割结果表明,减背景法由于采用人工选取门限值而难以适用于在线铁谱图像的处理,而自动阈值法可以根据铁谱图像自动选取合适的阈值以达到良好的分割效果;采用磨粒百分覆盖面积作为定量指标可反应良好分割的铁谱图像中的磨粒统计质量分数。     

透平机减速齿轮箱的在线铁谱监测

在线铁谱技术是一种由分析铁谱技术发展而来的磨损状态实时监测技术，对于连续运行的关键设备的主要摩擦付实施在线铁谱监测是十分必要的。它可以避免离线铁谱监测的取样、制样等繁杂过程和长间隔采样漏掉故障信息等缺点。利用在线铁谱技术对透平机减速齿轮箱的磨损状态监测结果表明，即使在正常磨损状态下，齿轮摩擦付的磨损速率并不是恒定的。它既受磨粒在摩擦付附近的不均匀造成的随机误差影响，又受齿轮载荷变化的影响。而磨损趋     

油液在线监测系统中磨粒识别技术研究

针对磨损状态监测要求,构建了基于显微图像分析的油液在线监测系统。根据系统光路特点,对磨粒图像进行了基于彩色特征的转换,并通过与背景图像的差值处理来快速提取磨粒目标。基于最小二乘支持向量机设计了磨粒两类分类器,并利用粒子群优化算法对最小二乘支持向量机模型中的参数进行了优化选取;根据磨粒识别体系,设计了基于最小二乘支持向量机的磨粒综合分类器。最后,利用铁谱分析技术对系统性能和识别效果进行了检验,结果表明本系统具有较高的检测精度和识别效果。     

Watershed-Based Morphological Separation of Wear Debris Chains for On-Line Ferrograph Analysis

Separation and characterization of wear debris from ferrograph images are demanded for on-line analysis. However, particle overlapping issue associated with wear debris chains has markedly limited this technique due to the difficulty in effectively segmenting individual particles from the chains. To solve this bottleneck problem, studies were conducted in this paper to establish a practical method for wear debris separation for on-line analysis. Two conventional watershed approaches were attempted. Accordingly, distance-based transformation had a problem with oversegmentation, which led to overcounting of wear debris. Another method, by integrating the ultimate corrosion and condition expansion (UCCE), introduced boundary-offset errors that unavoidably affected the boundary identification between particles, while varying the corrosion scales and adopting a low-pass filtering method improved the UCCE with satisfactory results. Finally, together with a termination criterion, an automatic identification process was applied with real on-line wear debris images sampled from a mineral scraper gearbox. With the satisfactory separation result, several parameters for characterization were extracted and some statistics were constructed to obtain an overall evaluation of existing particles. The proposed method shows a promising prospect in on-line wear monitoring with deep insight into wear mechanism.     

Advances in research on a multi-channel on-line ferrograph

This paper introduces the basic principle, functions and test results of a multi-channel on-line ferrograph. The instrument catches wear debris with an electromagnet, detects wear debris with a photoelectric sensor, and controls sampling and data processing with an 8098 single-chip microprocessor which can communicate with a master computer. The instrument has four sampling channels, which can monitor not only one machine but also four machines one by one. The software of the instrument includes five modules which are a main program, a keyboard control program, a floating point operation program, a serial communication program and a self-checking program. The results of experiments on a gear box show that increasing average values detected by the instrument correspond to increasing load, so the instrument can meet the need for on-line monitoring of the wear condition of machines.     

油液在线监测系统中的磨粒识别

针对机械设备磨损状态监测要求,构建了基于显微图像分析的油液在线监测系统.根据系统的光路特点,对磨粒图像进行了基于彩色特征的转换,并通过与背景图像的差值处理来快速提取磨粒目标.基于最小二乘支持向量机设计了两类磨粒分类器,并利用粒子群优化算法对最小二乘支持向量机模型中的参数进行了优化选取.在此基础上,根据磨粒识别体系,设计了磨粒综合分类器.最后,利用铁谱分析技术对系统性能和识别效果进行了检验,结果表明,系统的识别精度达到95%以上,满足磨粒在线监测要求.     

A Hybrid Method for the Segmentation of a Ferrograph Image Using Marker-Controlled Watershed and Grey Clustering

Aimed at the correct segmentation of wear particles in ferrograph images, a new method combining marker-controlled watershed and an improved grey clustering algorithm is proposed in this article. First, the marker-controlled watershed is applied to ferrograph images to efficiently obtain the initial segmentation of wear particles. Then, an improved grey clustering algorithm utilizing color characteristics and relative position information is applied to merge the oversegmented regions after the watershed segmentation. This new algorithm is tested for ferrograph images and the results are compared with those of other algorithms. The experimental results show that the proposed method is effective for the segmentation of large wear particles and fine wear debris deposited as chains on the ferrograph, and it is proven to be a practical method for segmenting wear particles quickly and accurately.     

基于拓展有限元的齿轮点蚀磨粒形态学特征模拟

疲劳点蚀是齿轮摩擦副的典型固有磨损特征,其产生的点蚀磨粒已经被用于理解疲劳磨损的发生和发展机理,由于缺乏理论模拟,基于磨粒特征的疲劳磨损机理判断还停留在经验分析层面。为此,拟通过齿轮接触疲劳点蚀的数值模拟,研究点蚀磨粒形态特征,为在线磨粒特征表征磨损状态的方法提供理论探索。在考虑弹流润滑的条件下,建立齿轮副局部接触模型,并采用拓展有限元法(Extended finite element method,XFEM)模拟表面萌生裂纹的拓展过程。进一步分析工况与点蚀磨粒形态特征的关系,结果表明,点蚀磨粒长轴尺寸随初始萌生裂纹的长度增加而增大,随载荷的增加而减小;点蚀磨粒的厚度随初始萌生裂纹的深度增加而增大。通过与已发表的试验结果进行对比,该模型所得到的点蚀形貌尺寸和形状与试验得到的点蚀形貌基本一致,从而验证了该模型的有效性。     

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。     

Wear Condition Monitoring and Working Pattern Recognition of Piston Rings and Cylinder Liners Using On-Line Visual Ferrograph

This study applies stepped loading and stepped velocity approaches to simulate the actual working conditions of gasoline engines. Accelerated wear tests were conducted for piston rings and cylinder liners under different lubricating conditions by using a self-made pin-on-disc wear machine equipped with an on-line visual ferrograph (OLVF) for wear monitoring. The wear coefficients for oil monitoring were extracted to distinguish between constant conditions and stepped changing conditions. A similarity model for oil monitoring was constructed and the monitoring data sets of similar working conditions were grouped together. Results show that the OLVF monitoring system can be used to obtain the real-time variation in debris concentration. The index of particle coverage area (IPCA) of OLVF increases abruptly after the load or speed changes. The similarity model can evaluate the similarity of the variation trend of IPCA under different operating conditions. The relationship between IPCA and working conditions was examined in this study and provides an essential support to wear monitoring and life prediction of engines.     

An oil monitoring method of wear evaluation for engine hot tests

Abnormal wear of a piston ring-cylinder liner pair may happen after 9 min hot tests of internal combustion engines, while the engine performance parameters were within predetermined threshold ranges. Few differences were observed among oil samples from the engines with or without abnormal wear in the spectrometric and Kittiwake Analex PQ analysis. Therefore, a manual confirmation by disassembling the oil pan was often required. In this work, an oil monitoring method for wear evaluation of the engines was proposed. The oil samples were rapidly analyzed on site by on-line visual ferrograph (OLVF). For the abnormal engines, it was found that the index of particle coverage area (IPCA), characterizing the wear debris concentration, was low. Moreover, large debris was rarely observed on OLVF ferrograms, which was consistent with the results obtained from analytical ferrography, and the reason was analyzed and discussed. In addition, an on-site abnormal wear evaluation procedure for the 9 min hot tests was proposed based on a trained Naive Bayes Classifier. As observed from the results of 27 engines, 4 abnormal engines were found. Among one of them, longitudinal scratches were found on the cylinder wall, which were evaluated as abnormal wear by the classifier. This method can cut down the quantity of disassembly inspection and is more efficient.     

在线图像可视铁谱成像系统的像面照度均匀性

为了定量评价在线图像可视铁谱(OLVF)成像系统的像面照度均匀性,建立了一种像面照度模型。以像方参数及放大倍率表征物方视场,将物方视场区域离散化,采用朗伯余弦理论建立入瞳模式的像面照度模型,实现了像面照度的计算与均匀性评价。利用Matlab进行了物面照度仿真分析,确定了OLVF成像系统环形阵列光源的发光二极管(LED)数量,基于像面照度分析确定了最佳成像焦距和放大倍率。计算了油腔通油情况下成像系统中的光能量损耗以及磨粒沉积面的照度分布,建立了油液吸光系数与CCD像面轴上像点照度的关系。结果显示:LED发光强度已知时,仿真计算的像面不均匀度约为5.60%,实际测试的像面不均匀度为8%~9%,满足不均匀度≤10%的要求。开展了磨粒铁谱图像采集实验,结果表明:图像中磨粒清晰可辨,便于图像分割与视觉特征提取。提出的模型可定量描述OLVF成像系统的像面照度,可作为优化系统结构,提高系统成像性能的依据。     

Engine Wear Monitoring with OLVF

In this article, an on-line visual ferrograph (OLVF) was used to monitor the wear condition of a vehicle engine during a bench test. A quantitative index of particle coverage area (IPCA) and wear debris ferro-image were obtained via OLVF to characterize wear degrees. On-line ferrograph analysis indicated some problems with the engine from about the 17th hour. A linear threshold value method to identify running condition of engines with the OLVF data was proposed. The OLVF data were in a fault zone after running for 25 h, when a base bolt broke and the engine stopped working during the test. The engine was disassembled and inspected after the test. Several wear scars were found on the cylinder walls as well as on the bearing surfaces. The oil was added at the 26th and 55th hours, which was also reflected by the variation of IPCA. Moreover, several off-line analyses were carried out in parallel. Off-line ferrograph data did not give any information about the abnormality and only showed stable wear debris content. Spectrometric oil analysis showed that there was no significant change in contents of metal elements.     

钢芯铝绞线磨损微粒特性分析

在自制导线微风振动模拟试验机上,于8%拉断张力下,对LGJ150/25型钢芯铝绞线完成了3种不同振动周次下的微风振动磨损试验。在线夹出口89mm处采集了磨损微粒,利用铁谱仪、扫描电镜和能谱仪对磨粒表面微观形貌、成分和尺寸进行了分析。结果表明,钢芯铝绞线铝线股的磨损主要为磨料磨损和氧化腐蚀磨损;随着振动周次的增加,磨粒尺寸迅速减小,几何长短轴比逐渐趋于1,棱角逐渐变得平滑,形成粒度较小,数量较多,且分布均匀的磨损微粒;在1×107振动周次下,试验导线的钢芯线发生较为明显的磨损现象。     

全视场在线图像可视铁谱磨粒显微成像特性分析

为了评估全视场在线图像可视铁谱磨粒显微成像特性,提出了一种反射光显微成像模型。首先,基于朗伯余弦与小角度散射理论建立了全视场(OLVF)的反射光辐照度模型,实现了磨粒显微成像清晰度定量评价。然后,仿真计算磨粒显微成像的反差透视比,确定了最优光学倍率和适用于全视场OLVF探测的油液衰减系数范围,明确了光学参数对磨粒显微成像质量的影响规律。结果显示：光学倍率为2.0×且油液衰减系数≤2.0条件下,磨粒沉积于物方视场的主光轴附近,全视场OLVF可获得最佳磨粒显微成像清晰度。最后,开展了磨粒显微成像实验测试,结果表明：全视场OLVF能够从油液衰减系数小于2.0的在用液压油和齿轮油中获取反射光谱片图像,并提取磨粒视觉信息进行磨损在线监测。