A. Ya. Grigoriev

Surface roughness and texture analysis in microscale

The capacity of various instruments in roughness measurements and analysis is compared. Review of various models of roughness is made and the models of contact mechanics are presented, when taking account the nanometer scale roughness and relating phenomena of adhesion and surface forces. The concept of multi-level models of roughness and contact area is presented. Analysis of surface topography as a spatial pattern is given, when using the approaches of image recognition theory operating with the 3D digital images processing. Qualitatively the spatial structure is often characterized in terms of texture features such as random, linear, wavy etc., and some national standards introduce spatial structure of machined surfaces. However, texture characteristics are not adequately investigated. AFM images of different surfaces were used as initial data and multi-dimensional scaling technique was used for the data analysis. The study has shown that there are at least four types surface textures on nanoscale level. The correlation was found between texture types and reasons of their formation.

Classification of wear debris using a neural network

Abstract In this work, an evaluation was made to prove the possibility of employing a neural net method for the classification of debris and monitoring of a lubricated contact pair. We trained a neural net to classify the severity of wear into two types from the morphological features of the wear debris. The following procedures were used. First, the shape of wear particles was characterized by Fourier descriptors. The Fourier descriptors were considered as coordinates of a point in multidimensional feature space. A set of points from a cluster, and the location and structure of the cluster depend on the morphology of the wear particles and the current conditions of the contact system. A distance distribution between the debris in the feature space was used to represent the location of the cluster. Second, we trained a back-propagation neural net. To train the neural net, we used the distance distribution corresponding to the different stages of the wear process as an input vector and encoded the wear rate as a desired response. The network was then further trained until the desired error goal was achieved. Finally, we tested the trained neural net. The ability of the neural net method to monitor wear is shown.

The use of color in wear debris analysis

A method and results of classification of metallic wear debris using their color features are presented. The color images of wear debris were used as initial data. The color features of the debris are specified by an HSI color model. Each particle is characterized by a set of statistical features derived from a distribution of HSI color model components. The initial feature set was optimized by principal component analysis. A multidimensional scaling procedure was used for definition of the classification plane. The selected features allow us to distinguish copper-based alloys, red and dark iron oxides and steel particles. A method was proposed of probabilistic decision of class assignment based on analysis of debris coordinates distribution in the classification plane. The obtained results have demonstrated the feasibility of using color features for automated wear particle analysis.

Quantitative analysis of surface topography using scanning electron microscopy

Abstract A supplement to the existing methods of studying topography is proposed, using methods based on analysis of the textural and morphological characteristics that are widely used in image processing theory. A survey of methods of studying roughness, allowing both the images of surfaces and a quantitative estimate of the surface properties to be obtained simultaneously, is presented. A method of evaluating topography using scanning electron microscopy and a personal computer is described.

Morphology: Texture, shape, and color of friction surfaces and wear debris in tribodiagnostics problems

Fundamentals and methods of morphological analysis of images of friction surfaces and wear debris are discussed in terms of practical problems of tribodiagnostics. A review of widespread approaches to the description of texture, shape, and color of tribological objects is presented. Their parametrical models and methods of classification of morphological types related to the mechanisms of operational degradation of the friction surface are considered. In addition, basic trends of development of morphological analysis methods in the investigation of friction and wear are discussed.

Reciprocating MTU-2K7 millitribometer

The design of the reciprocating tribometer for testing materials under the sphere-plane scheme in the millisize range of loads and speeds is discussed. The device enables elastic and elasto-plastic contact for nearly all materials for friction units. Wear measurements have been carried out in a system based on a Linnik micro interferometer. The modular design of the device enables it to be calibrated and certified in the laboratory.

Friction and wear of powder coatings of epoxy composites with alumosilicate nanoparticles

The paper studies the effect of alumosilicate nanofillers of tubular and lamellar shape on the friction and wear of epoxy composites. It is shown that the influence of concentration and shape of the fillers on the tribological behavior of the composites is due to variations in their viscoelastic properties and shielding of the contact area of the matrix material with the metallic counterbody by the filler particles. The data evidence that at equal concentrations of alumosilicate fillers in the epoxy matrix, the best tribological characteristics are provided in the case of tubular-shaped particles.

Analysis of Tribochemical Surface Damage by Image Processing (Analysis of Tribochemical Damages)

In the work, the problem of automated classification of tribochemical damage of metallic surfaces based on digital image processing was considered. Five types of tribochemical wear damage, including fretting, smearing damage, combinations of oxidation and erosion wear, and wear in corrosive media were investigated. Initial images were characterized by a set of texture features. The effectiveness of using the developed method for automated identification of tribochemical surface damage types was demonstrated.

Tribological behavior of thin electroplated and chemically deposited Ni-P coatings on copper substrates

The paper deals with the study of the tribological behavior of thin (1 and 5 μm thick) Ni-P coatings formed on plates made of electrotechnical copper by electroplating and chemical deposition. It has been found that after heat treatment, owing to diffusion processes, the coating components are capable of penetrating into the substrate material—to a depth of 15 μm for electroplated coatings and of 35 μm for chemically deposited coatings)—and influencing the mechanical properties of a specimen such as the hardness and friction coefficient. A correlation between the wear mode of the coating and the method of its deposition has been found. The results show that thin (one μm thick and lesser) Ni-P chemically deposited coatings are promising for being used in friction units of precise mechanical devices.

Friction of brushlike self-assembled monomolecular coatings

Friction modes of self-assembled monomolecular coatings (SAM) based on dodecyclophosphoric acid ester and its derivatives on a silicon substrate are investigated. The antifriction properties of the films are shown to be due to their ability to decrease the interfacial energy of friction contact. Models are suggested for friction force computation for single and multiple molecularly smooth contacts. They are based on consideration of the thermodynamic cycle of formation and break-off of the friction junction. On the example of composite coatings having different surface energy, a possible means of regulation of the tribological parameters of the silicon-SAM-silicon system is discussed.