含污染物油润滑条件下的磨粒磨损研究

概述了含污染物油润滑条件下的磨损试验方法，分析了磨粒尺寸、磨粒含量；材料硬度和材料表面粗糙度等试验参数对含污染物油润滑条件下材料的磨损性能的影响，结果表明其磨损机理主要是点蚀、犁削和熔着磨损，并提出了解决措施。     

润滑油磨粒浓度的时序分析与在线建模

润滑油中的磨粒通过其浓度,尺寸,形状等特征反映出丰富的来自相对运动表面的摩擦学信息。因而,磨粒分析一直是人们进行机器工况监测和故障诊断的一个重要领域,其中,润滑油中磨粒的浓度作为机器磨损状态最为敏感的因子而成为在线铁谱仪进     

成形砂轮磨削齿轮表面形貌特征及摩擦学特性分析

为了揭示成形砂轮磨削齿轮表面形貌的分布特征及其对摩擦学特性的影响机制,开展了磨削表面不同角度方向的纹理特征、粗糙度评定参数、摩擦磨损性能的对比分析试验。研究表明:随着角度θ在0°～90°增长时,表面形貌的粗糙度微观不平高度、沟纹深度、均匀性与规则性均先逐渐增大,直至45°时表面纹理最为复杂且表面粗糙程度最大,然后又略有所改善;凸峰形态尖峭程度先减弱,直至15°纹理方向达到最小,然后再逐渐增大;粗糙度微观不平间距逐渐减小。在流体润滑摩擦状态下,微观不平高度特性Ra越大,动压润滑效应减弱,边界润滑效应越显著。摩擦磨损机制是塑性变形与微切削作用,以及磨粒磨损、粘着磨损、疲劳磨损等的耦合作用。     

基于铁谱分析的颗粒分类识别方法与应用

铁谱颗粒分析是机器磨损状态监测与维修决策制定最有效的油液分析方法。通过近年来开展工业企业机器油液监测积累的大量铁谱磨粒图像,进行基于不同的颗粒特征的分类识别探究,并基于不同颗粒形成机制与原因提出切合工业现场的润滑管理维保策略。应用实践表明,铁谱分析方法在机器磨损状态监测、润滑磨损诊断机制判别以及企业润滑管理提升活动中仍发挥着积极作用。     

海水润滑赛龙材料磨损机制分析

试验研究海水润滑条件下赛龙材料的摩擦磨损性能,借助表面形貌仪、扫描电镜分析磨痕表面形貌,分析海水润滑条件下赛龙材料的磨损机制,并与干摩擦、湿润滑条件下的磨损机制进行比较。结果表明:干摩擦条件下表现为黏着磨损和磨粒磨损特征;湿润滑条件下磨损表现为微切削(磨粒磨损);海水润滑条件下的磨损中有气蚀磨损、磨粒磨损共同存在。     

不同磨损形式下的滑动轴承磨损表面及其磨粒特征

为了对其实现快速和准确的诊断,在试验机上模拟了滑动轴承的各个典型磨损过程,收集各阶段产生的磨粒信息,观察磨损表面形貌,研究了磨粒和磨损表面特征及其对应关系.结果表明通过检测润滑油中的磨粒信息可以间接获得滑动轴承的磨损表面特征,进而进行滑动轴承的状态诊断.     

基于在线铁谱图像的磨损机理智能辨识

基于状态的维护(Condition based maintenance,CBM)理念为机器健康状态维护提出了实时监测的新挑战。现有研究由于缺乏在线信息获取手段,磨损状态监测逐渐成为CBM的技术瓶颈。基于特征磨粒的磨损机理判断方法已经被广泛应用在离线磨损分析中,但是在线磨损机理的表征依然是一个很大的问题。针对基于在线铁谱图像的磨损机理开展研究。为了在一副在线铁谱图像中获得分离的磨粒图像,研究磨粒在在线铁谱传感器中的沉积机理。研究结果表明,磨粒链是图像中的主要形态,这是由于先前沉积的磨粒产生的局部磁场所致。设计一种依靠自适应调节沉积时间的在线磨粒沉积方法。运用该方法可以在在线铁谱图像中获得分离的磨粒,为特征磨粒的特征辨识提供了便利。参考分析铁谱知识,提取特征磨粒的4种形态学特征(当量尺寸、长径比、形状因子和分形维数)以综合表征4种典型磨损机理,包括正常、切削、疲劳、严重滑动磨损。采用反馈式人工神经网络构建自动磨损机理辨识模型。采用离线铁谱图像样本验证所建模型,结果表明该模型可以识别在线磨粒图像中的特征磨粒。对在线磨损机理表征方法进行了有意义的探索,所得研究成果将为在线磨损状态表征提供可行方法。     

新型油液在线监测集成装置

油液在线监测是目前装备润滑磨损状态监测技术发展的重要方向,而监测仪器的开发是这一监测诊断技术研究热点。针对现代远洋船舶流动性工作特点及机械润滑磨损状态监测实时性要求,开发一套集油液磨粒监测和黏度检测的在线监测装置。装置具有结构紧凑、尺寸小、安装方便等特点。调试试验分析表明,该集成装置具有良好的稳定性,能快速实现油液磨粒含量、黏度趋势分析及超限报警。该油液在线监测装置的集成实现,为后续集成如水分、颗粒计数指标以及温度、压力等状态参数提供了研发基础。     

超声辅助磨削碳化硅陶瓷的工具磨损试验研究

为探究超声辅助磨削过程中不同工具的磨损特征,采用电镀和钎焊两种金刚石磨头对碳化硅陶瓷进行了超声辅助磨削和普通磨削对比试验,研究了超声振动作用、工具类型对磨粒磨损形式及其变化过程的影响,在此基础上分析了磨粒磨损形式对工件表面质量的影响.试验结果表明:对于电镀磨头,普通磨削和超声辅助磨削过程中的磨粒磨损形式均以磨耗磨损和宏观破碎为主,超声振动作用可有效改善加工表面质量;而对于钎焊磨头,普通磨削的磨粒磨损形式主要是磨耗磨损和宏观破碎,超声辅助磨削的磨粒磨损形式主要是磨耗磨损和微破碎,初始阶段超声振动作用可改善表面质量,但随着磨削行程的增加,微破碎形式的占比增高,超声辅助磨削时的工件表面粗糙度值高于普通磨削时的工件表面粗糙度值.     

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。     

Analysis for Wear Behaviors of Oxidative Wear

Sliding wear tests were performed for H13 steel and a cast steel under atmospheric conditions of 25, 200, and 400°C. XRD results identify that oxidative wear prevailed for the steels during sliding at 200–400°C. However, the oxidative wear at 200°C presented entirely different wear behaviors from the one at 400°C. With an increase of load, the oxidative wear at 200°C exhibited slowly increased and lower wear rates, despite relatively less tribo-oxides. On the contrary, although there were more tribo-oxides, the oxidative wear at 400°C presented rapidly increased and higher wear rates. The former oxidative wear could be classified into mild wear; the latter one fell beyond mild wear. The two types of oxidative wear universally existed; their discrepancies were mainly attributed not to the tribo-oxides, but to the extent of softening and deformation of substrate. Hence, we suggested that the two types of oxidative wear should be distinguished in the coming research, and were termed oxidative mild wear and oxidative wear, respectively.     

磨粒均匀涂布制谱方法研究

磨损微粒分离和收集是各种铁谱检测仪器的关键技术，文中提出了一种全新的均匀涂布制谱方法，磨粒不受挤压和碾磨作用，保持颗粒的原始信息。为此设计了磨粒制谱装置，并对样品制备，实验结果进行了分析和讨论。     

On Prediction of Wear Coefficients in Sliding Wear

The wear rates and wear coefficients of metals are analytically predicted based on the delamination theory of wear when the wear rates are controlled by the subsurface crack propagation rate. The wear rate and the wear coefficient are predicted to be directly proportional to the depth of crack location and the crack growth rate. The numerical values of wear coefficients are obtained through finite element analysis of crack propagation in elastoplastic solids. The agreement between typical experimental results and theoretical prediction is excellent.     

Transition of Mild Wear to Severe Wear in Oxidative Wear of H21 Steel

Under atmospheric conditions at 400 °C, we studied the wear mechanism of H21 steel with different tempering states as a function of normal load. Typical oxidative wear was identified by X-ray diffraction patterns with predominant tribo-oxides of Fe₃O₄ and Fe₂O₃. Under loads of 50–100 N, mild oxidative wear prevailed for all samples, such that the wear losses of H21 steel with various tempering states showed no significant differences with characteristics of a slight plastic deformation of the substrate and single-layer oxide. In this case, the wear rate was lower, and the tribo-oxide was decisive factor in determining wear rate. Under loads of 150–200 N, the transition of mild wear to severe wear occurred in H21 steel and was characterized by: (1) a significant difference of wear losses for steel with various tempering states; (2) wear loss that started to increase faster and reached a relatively high level; (3) the appearance of significant plastic deformation in the oxide underneath the substrate and multi-layer tribo-oxide. Under a load of 200 N for the steel tempered at 700 °C, plastic extrusion prevailed with a mixed metal-oxide layer.     

Prediction of Steady-State Wear Coefficients in Adhesive Wear

With an integrated adhesive wear model, Yang's second wear coefficient equation was previously found suitable for modeling the standard wear coefficients for both the transient wear and the steady-state wear of MMC-A, MMC-B, and MMC-C, which are aluminium-based matrix composites containing 10%, 15%, and 20% alumina particles, respectively. In this study, Yang's third wear coefficient equation was used to predict the standard wear coefficient and the net steady-state wear coefficient, respectively, for MMC-D, an aluminium alloy matrix composite containing 20% spherical alumina particles, and an aluminium alloy A6061-T6. As compared with the wear data obtained previously, the average deviations were found to be about 23% and 15%, respectively, for the predicted standard wear coefficients and about 20% and 65% for the predicted net steady-state wear coefficients for the two materials respectively. The high deviation of about 65% obtained for the aluminium alloy was due to the very low wear rate obtained during wear testing with a long sliding distance, with the presence of powdery debris.     

可共享的磨粒识别及磨损诊断系统

针对当前铁谱分析技术存在的不足 ,将计算机图像处理技术、数据库技术、网络通信技术相结合 ,提出了以人工智能、神经网络为核心的设计思想。介绍了基于本思想所建立的可共享的磨粒识别及磨损诊断系统WPRWDS,分析了其系统结构、实现机制、硬软件设计、功能和特点等。     

Modeling Wear State Evolution Using Real-Time Wear Debris Features

Because wear is one of the most typical causes of decreasing performance in running machines, monitoring wear is regarded as a crucial technology in maintaining the health of machines. However, monitoring wear is not a fully mature process because quantifying the development of wear in real time is a challenging task because there is no universal indicator. To meet this need, wear-oriented dynamic modeling with online ferrographic images was used to investigate and then describe a real-time wear state. This investigation was carried out by combining three wear indices to describe the wear rate, the wear mechanism, and the severity of wear. A binary classifier method is also proposed to classify these wear stages in the three extracted indices. A strategy to identify the dynamic transition of wear states with adaptive parameters is also developed and then a four-ball wear test is carried out to verify the method. The results indicate that this modeling strategy can accurately identify a developing wear state that is characterized by stages. This proposed method is better at monitoring the health evolution of a machine system than just detecting faults.     

柴油机主要摩擦副磨损型式的识别

本文首先提出了柴油机磨损型式识别的重要性,进而阐述了磨损型式模糊模式识别的过程,即：模糊模式识别原理,建立磨损型式的标准样板库,隶属函数的确定等等,最后给出了结论。     

Characteristics of Extrusive Wear and Transition of Wear Mechanisms in Elevated-Temperature Wear of a Carbon Steel

The dry sliding wear of a medium carbon steel with different microstructures was measured under the normal load range of 50–150 N at 400°C by a pin-on-disc high-temperature wear setup. The wear behavior and wear mechanism were systematically studied; in particular, the characteristics of extrusive wear and the transition of wear mechanisms were investigated. Under low normal loads, the wear is oxidative type wear. Once the normal load reached a critical value, a mild-to-severe wear transition occurred, and subsequently an extrusive wear prevailed. The mild-to-severe wear transition depended on the microstructure of matrix; the critical normal load of the transition was 112.5 N for tempered sorbite, 125 N for lamellar pearlite, and 137.5 N for tempered martensite and tempered troostite. As oxidative wear prevailed, a thick oxide layer about 20–30 μ m and a plate-like wear debris with regular outline were recognized. However, as the extrusive wear occurred, the wear rate abruptly increased but the friction coefficient was reduced. The extrusive wear predominated due to thermal softening of the matrix and presented a superthin oxide layer (less than 0.5 μ m) and low oxide content on worn surfaces, accompanied by the appearance of ribbon-like wear debris.     

摩擦磨损试验磨痕检测新方法的研究

介绍了一种基于图像处理技术的摩擦磨损试验磨痕测量新方法,即磨损量的数字图像测量法.该方法与传统的磨损量测量方法(如:称重法、测量直径法、表面形貌法、光干涉法等)相比较,能在一定程度上实现磨痕的在机检测和磨损量的快速计算,从而达到磨痕测量手段的非接触、快速及自动化.