【作者】 袁成清；

【导师】 严新平；

【作者基本信息】 武汉理工大学 ， 载运工具运用工程， 2005， 博士

【摘要】 磨损状态的确定以及磨损过程中的磨损机理的判定都依赖于对摩擦副表面形貌和磨损过程中生成的磨粒的分析研究。对正在运行的机器设备,磨粒比较容易获得,但磨损表面形貌往往无法直接获取,因此,研究磨损表面与磨粒表面之间的相互关系具有重要的意义。 本文针对现今摩擦学测试手段的不足,开发了基于激光共焦扫描显微镜和图像处理技术的三维表面数字化描述的新方法,运用该方法能够获得精确的磨粒和磨损表面的三维表面形貌,然后用小波理论分离磨损表面和磨粒表面的表面粗糙度、波纹度和形状误差,并用计算机图像分析技术来获得磨粒的二维特征参数以及磨粒和磨损表面的三维表面特征参数,进而开展摩擦副系统中磨粒表面和磨损表面的研究。在此基础上以矿山和港口机械为研究背景,针对这类机械的运行环境,在摩擦磨损试验机上模拟这类机械摩擦副中广泛存在的滑动磨损形式,考察污染物、高温、润滑状况等因素影响下的磨损过程,综合运用开发的三维表面数字化描述方法、铁谱、磨粒分析仪、激光共焦扫描显微镜等技术和手段,研究磨损进程中磨损颗粒和磨损表面的变化情况及其相互关系,深入探讨磨损机理。 对于矿山和港口机械,一些硬颗粒如二氧化硅和低硬度颗粒污染物不可避免地存在于这些机械的润滑系统中。在销盘磨损试验机上通过模拟试验研究了高硬度的二氧化硅颗粒和低硬度的铁粉颗粒存在润滑油中时的滑动磨损过程,分析了不同磨损阶段中的磨损表面和磨粒表面特征,探讨了二氧化硅颗粒和铁粉颗粒的单独作用和协同效应;研究了当污染物颗粒存在于润滑油中时,润滑油温度对滑动磨损过程的影响,结果表明,温度严重影响着粘着和氧化磨损发生的概率和程度,这充分说明外来污染物在磨损过程中起着重要作用。可以相信从这些研究中获取的知识将有助于加深理解高温且污染物存在于润滑系统中更多还原

【Abstract】 The recognition of wear condition as well as wear mechanism in wear process depends on the analysis of surface topographies of wear components and wear debris generated in the wear process. For a machine in operation, it is very convenient to collect wear particles generated in wear process for conducting wear debris analysis. However, it is definitely difficult to access to study the surface of wear components. Therefore, it is very crucial and significant to study the relationship between the surface of wear components and the surface of wear particles.This paper has proposed a set of methods and techniques to acquire appropriate images using confocal laser scanning microscopy, to separate roughness, waviness, and form using wavelet theory, and to calculate 2D & 3D surface parameters of wear particles and engineering surfaces for quantifying surface characterization of engineering surfaces and surfaces of small particles using computerized image analysis techniques. The use of the approaches for 3D surface parameters developed in this paper will play a great role in studying surfaces of wear particles and surfaces of wear components. Benefited from the above approaches, this project focused on the sliding wear mode in mining and port machinery and conducted a series of wear tests to study the effects of contaminants, temperature and lubricant condition on wear process and the surface evolutions of wear particles and wear components as wear progresses.For all mining and port machinery, their lubricants are very likely to be polluted by contaminants such as silica and other metallic debris such as iron and nickel. In order to seek a deeper understanding of the effects of different contaminants on wear process, this project conducted sliding wear processes using pin-on-disc tester when silica powder and iron powder exist in N32 lubricant to study the surface characterization of wear particles and wear components in different wear stages. The independent and dependent role of silica and iron powder in sliding wear processes was also analyzed based on experimental results. Furthermore, sliding wear tests have been conducted to investigate the effects of temperature on sliding wear processes when the iron particle contaminants were existent or non-existent in the SAE40lubricant. The experimental results clearly showed that the temperature of the S AE40 lubricating oil has a significant influence on the wear processes. The increase in the temperature of the SAE40 lubricant increases the probability and the degree of adhesion and oxidation. It is very clear that containments and lubricant temperature did play an important role in wear process. It is believed that the knowledge gained in this study is significant for a deeper understanding of the wear mechanisms and wear characteristics as well as for controlling wear rates.Surface characterization, particularly roughness analysis, is very important for a wide range of applications involved with the control of friction, lubrication, and wear. Sliding wear tests were conducted on the tester at room temperature to investigate the surface roughness evolutions of both wear components and the wear particles generated from tests as wear progresses under proper lubrication and improper lubrication conditions. The results showed that there is good correlation of the surface morphology of wear particles and the surface morphology of the wear components. In order to seek a further correlation of surfaces of wear particles and surfaces of wear components, more surface parameters were adopted to describe the surface characteristics. Subsequently, information fusion technology was used to investigate the mapping relationship between surface topographies of wear particles and those of corresponding wear components. Firstly, appropriate parameters of wear particles are selected to recognize types of wear particles using neural network to determine the main representative types of wear particles generated in the wear process. Then, the surface characterization of these representative wear particles was gained to conduct the relationship between surface characteristics of wear particles and those of wear components. The demonstrated case has showed that the surface characteristics of wear components can be assessed through studying the surface characteristics of the wear particles. It is believed that the surface characteristics of wear components can be predicted according to the surface characteristics of wear particles, which will contribute to machine condition monitoring.更多还原