设备材料表面粗糙度的分形表征及其对界面粘附强度的影响
发布时间：2018-08-19 17:47
【摘要】：设备开车前或中间检修过程都需要对设备进行清洗,确保设备安全、高效运行。设备材料的表面特性对污垢颗粒界面粘附力的影响较大,表面粗糙程度是其中尤为关键的要素。定量、准确的描述设备材料的表面粗糙程度,并建立其与污垢颗粒界面粘附性能之间的关系将有助于深入了解污垢颗粒与设备材料粗糙表面的相互作用,为设备表面除污提供基础理论。由于材料的粗糙表面具有自相似性,故分形理论可以实现表面形貌的有效表征。而分形参数的精确求解依赖于无标度区间的准确识别,为此,本文基于密度峰聚类算法首先提出一种识别无标度区的新方法。通过铣削、刨削和研磨工艺对新方法加以验证,方法适用性强、精确度高,对大数据量高密度的数据运行时间短,辨识效果较好。传统指标在理论上具有尺度相关性的特征,而分形指标理论上具有尺度无关的特性。然而在实际粗糙表面表征中,二者的尺度独立性是否与理论相一致有待实验验证。本文以铣削加工、刨削加工和研磨加工的粗糙表面为研究对象,考察两种指标的尺度独立性,结果发现传统指标在任何条件下均不具有尺度独立性,与理论相符;分形指标在多数条件下也不具有尺度独立性,与理论有出入。进一步研究分形指标尺度独立性的过程中发现,分形指标随尺度的变化分为不稳定分形区和稳定分形区。本文在对二维表面轮廓线的过程中,将临界点的求取转化为取样长度和夹角α值的定量关系求解,通过实验得出其定量关系,用于确定稳定分形区。采用原子力显微镜测颗粒在不同粗糙表面的粘附力,结合固体污垢清除机理分析,发现表面的粗糙程度对界面粘附力的影响较大。研究表明Ra0.4627μm时,随着表面粗糙度增加,粘附力减小;1.3461μmRa2.9755μm时,粘附力逐渐增大;Ra3μm时,粘附力保持稳定。粘附力随着分形指标的变化而变化,其变化趋势与传统指标正好相反。随着分形维数的增大,粘附力先是保持稳定,后逐渐增大,随着加工工艺的改变,表面粗糙程度有个剧烈的变化,分维值锐减,后逐渐增大。
[Abstract]:The equipment must be cleaned before or during maintenance to ensure the safe and efficient operation of the equipment. The surface characteristic of the equipment material has a great influence on the adhesion force of the dirt particle interface, and the surface roughness is the most important factor. The quantitative and accurate description of the surface roughness of the equipment material and the establishment of its relationship with the adhesion property of the dirt particle interface will help to understand the interaction between the dirt particle and the rough surface of the equipment material. Provides the basic theory for the equipment surface decontamination. Because the rough surface of the material has self-similarity, fractal theory can effectively characterize the surface morphology. The exact solution of fractal parameters depends on the accurate identification of scale-free interval. Therefore, based on the density peak clustering algorithm, a new method to identify scale-free region is proposed in this paper. The new method is verified by milling, planing and grinding technology. The method has strong applicability, high accuracy, short running time for data with high data density and good identification effect. The traditional index has the characteristic of scale correlation in theory, while the fractal index has the characteristic of scale independent in theory. However, in the actual rough surface characterization, whether the scale independence of the two is consistent with the theory needs to be verified by experiments. Taking the rough surface of milling, planing and grinding as the research object, this paper investigates the scale independence of the two indexes. The results show that the traditional indexes do not have the scale independence under any condition, which is consistent with the theory. The fractal index does not have scale independence under most conditions, which is different from the theory. It is found that the fractal index can be divided into unstable fractal region and stable fractal region with the change of scale. In this paper, in the process of 2-D surface contours, the critical point is transformed into a quantitative relationship between the sampling length and the angle 伪, and the quantitative relationship is obtained through experiments, which is used to determine the stable fractal region. The adhesion force of particles on different rough surfaces was measured by atomic force microscope (AFM). Combined with the analysis of solid dirt removal mechanism, it was found that the roughness of the surface had a great influence on the adhesion force of the interface. The results show that when the surface roughness increases with the increase of Ra0.4627 渭 m, when the adhesion force decreases by 1.3461 渭 mRa2.9755 渭 m, the adhesion force increases gradually with Ra3 渭 m, and the adhesion force remains stable. The adhesion force changes with the change of fractal index, and the change trend is opposite to that of traditional index. With the increase of fractal dimension, the adhesion force keeps stable at first, then increases gradually. With the change of processing technology, the roughness of the surface changes dramatically, the fractal dimension decreases sharply, and then increases gradually.
【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TQ050.4
[Abstract]:The equipment must be cleaned before or during maintenance to ensure the safe and efficient operation of the equipment. The surface characteristic of the equipment material has a great influence on the adhesion force of the dirt particle interface, and the surface roughness is the most important factor. The quantitative and accurate description of the surface roughness of the equipment material and the establishment of its relationship with the adhesion property of the dirt particle interface will help to understand the interaction between the dirt particle and the rough surface of the equipment material. Provides the basic theory for the equipment surface decontamination. Because the rough surface of the material has self-similarity, fractal theory can effectively characterize the surface morphology. The exact solution of fractal parameters depends on the accurate identification of scale-free interval. Therefore, based on the density peak clustering algorithm, a new method to identify scale-free region is proposed in this paper. The new method is verified by milling, planing and grinding technology. The method has strong applicability, high accuracy, short running time for data with high data density and good identification effect. The traditional index has the characteristic of scale correlation in theory, while the fractal index has the characteristic of scale independent in theory. However, in the actual rough surface characterization, whether the scale independence of the two is consistent with the theory needs to be verified by experiments. Taking the rough surface of milling, planing and grinding as the research object, this paper investigates the scale independence of the two indexes. The results show that the traditional indexes do not have the scale independence under any condition, which is consistent with the theory. The fractal index does not have scale independence under most conditions, which is different from the theory. It is found that the fractal index can be divided into unstable fractal region and stable fractal region with the change of scale. In this paper, in the process of 2-D surface contours, the critical point is transformed into a quantitative relationship between the sampling length and the angle 伪, and the quantitative relationship is obtained through experiments, which is used to determine the stable fractal region. The adhesion force of particles on different rough surfaces was measured by atomic force microscope (AFM). Combined with the analysis of solid dirt removal mechanism, it was found that the roughness of the surface had a great influence on the adhesion force of the interface. The results show that when the surface roughness increases with the increase of Ra0.4627 渭 m, when the adhesion force decreases by 1.3461 渭 mRa2.9755 渭 m, the adhesion force increases gradually with Ra3 渭 m, and the adhesion force remains stable. The adhesion force changes with the change of fractal index, and the change trend is opposite to that of traditional index. With the increase of fractal dimension, the adhesion force keeps stable at first, then increases gradually. With the change of processing technology, the roughness of the surface changes dramatically, the fractal dimension decreases sharply, and then increases gradually.
【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TQ050.4
【参考文献】
相关期刊论文 前10条
1 张怀亮;邹佰文;肖雷;;一种辨识磨粒群分形无标度区的新算法[J];中国机械工程;2014年03期
2 王文健;汪洪;郭俊;刘启跃;朱e，
本文编号：2192369
本文链接：https://www.wllwen.com/kejilunwen/huagong/2192369.html
