Papers by Keyword: Image Analysis

Abstract: Conventional (CCT) and accelerated (ACT) creep tests of a weld joint made of COST F and COST FB2 steels were carried out over a temperature range from 550 °C to 650 °C. Fracturing of the crept specimens was located in the heat affected zone (HAZ) of the F steel. Two specimens were selected after CCT and ACT for quantitative evaluation of the precipitates and compared to the weld joint in as-received conditions. Scanning and transmission electron micrographs were used to measure the precipitate size. Both methods were compared and the accuracy of the results was discussed. It was concluded that ACT can simulate the precipitation of chromium carbides and structure recovery during long term creep exposures. However, precipitation of Laves phase during CCT was not recorded after ACT. Therefore, it is difficult to use ACT in this experiment for estimating the long term creep strength.

Abstract: Anodization is an electrochemical process that converts the metal surface into a decorative, durable, corrosion-resistant, anodic oxide coatings. The thickness of the resulting layer depends on the process parameters (voltage, current, type of electrolyte, concentration and temperature of the electrolyte). In this work, the preparation of zinc metallographic samples with anodic layer is described. Samples prepared by anodic oxidation on the zinc substrate are rather brittle and porous. During the mounting, cutting, grinding and polishing the layer can be deformed which can affect the layer thickness measurements. The problem is to determine the boundary between anodic layer and resin. The cross-sectional micrographs were observed by scanning electron microscopy with the aim to improve anodic layers thickness measurements by means of digital image analysis.

Abstract: The present research was aimed to study the porosity in some powder metallurgy (P/M) alloys using an image analysis software. The porosity in P/M parts is an important parameter because is affecting the mechanical properties. Also, porosity is in correlation with processing parameters such as green density, alloying elements, particle size. The conventional method for porosity measurements of powder metallurgy products is using the density technique. Another method for porosity measurements was using an image processing software and by applying filters and adjustments the detection of the pores (black areas) was done. Two types of powders obtained by water amotization were subjected to analyze. To obtain the green compacts, the powders were pressed at 600 MPa using a single die action. The green compacts were sintered in a laboratory furnace at 1150o C for 30 and 120 minutes. A metallographic analysis was performed for porosity measurements. The pore’s shape and porosity fraction were measured using both conventional and image analysis techniques. The porosity measurements for sitnered specimens obtained from image analysis was slightly higher than that from density technique.

Abstract: The purpose of this paper is to investigate the fracture modes of the crack propagation of fourteen sandstone samples under Cracked Chevron Notch Brazilian Disc (CCNBD) test conditions through the use of image analysis and the high speed camera. The fracture mode is characterized by the displacement of 0.5mm glass beads placed on the sandstone surface relative to the approximate orientation of the fracture propagation. Using a Phantom v2011 High Speed Camera the fracture generation and propagation of the samples are recorded and processed for image analysis. ImageJ with Multi-Tracker and Manual Tracker, as well MATLAB® software were used to analyze the movement of particles during fracture propagation. It was found that the ImageJ software was able to track the movement of the particles and the output of the MATLAB® script was able to plot vector trajectories of the particles. For the analysis of samples tested under different orientations it was found that both shear mode and mixed-mode were evident in the fracture propagation.

Abstract: Coal mining raises a number of environmental and operational challenges, including the impact of changing groundwater levels and flow patterns on adjacent aquifer and surface water systems. Therefore it is of paramount importance to fully understand the flow of water and gases in the geological system on all scales. Flow in coal seams takes place on a wide range of scales from large faults and fractures to the micro-structure of a porous matrix intersected by a characteristic cleat network. On the micro-scale these cleats provide the principal source of permeability for fluid and gas flow. Description of the behaviour of the flow within the network is challenging due to the variations in number, sizing, orientation, aperture and connectivity at a given site. This paper presents a methodology to simulate flow and investigate the permeability of fractured media. A profound characterization of the geometry of the cleat network in micrometer resolution can be derived by CT-scans. The structural information is fed into a Lattice Boltzmann Method (LBM) based model that allows the implementation of virtual flow experiments. With the application of suitable hydraulic boundary conditions the full permeability tensor can be calculated in 3D.

Abstract: The identification and measuring of geometrical dimensions of very small objects including textile is the biggest achievement of the image processing techniques. Not only the analysis of the basic structure of yarn like hairiness, thickness and number of twist but also the external structural analysis like twist parameters and linear density co-efficient is possible with outstanding approach of image analysis new techniques. Dyed polyester samples by using different dyestuffs were examined with the polarized light with the help of optical light microscopy. It was observed that the dyestuffs possess strong dichroism and the relationship between dichroism and the concentration of dyestuff was examined. Dark field and Bright field illuminations together with imaging polarimetry are compared in terms of depth of field tolerance and image quality. Experiments show that passive imaging polarimetry illumination is superior in terms of depth of field tolerance and contrast allowing significant improvement of textile structure investigation.

Abstract: Determining the content of fly ash (FA) in hardened cement concrete is very difficult at present. In this paper, samples were prepared with water/binder ratio (0.4), different FA/binder ratios and different curing ages, the backscattered electron imaging and image analysis technology are used to study the dosage of FA in the hardened cement mortar. The results show that the backscattered electron imaging and image analysis technology can comparable accurately test the dosage of FA in hardened cement mortar; this method doesn't need to know the chemical composition of raw materials or prepare the standard reference samples.

Abstract: Wastewater originated from domestic or industry use need to be treated before discharge it to the environment. Particle size is one of the parameter that determine efficient operation of wastewater treatment plant. The present work conducts a comparative study of non-imaging and imaging based particle size analysis tools to analyze the limitations and advantages of using such equipment. The study utilizes particle size analyzer (PSA) as non-imaging tool and light microscope as imaging tool to determine particle sizes in various waste water samples. For this analysis domestic wastewater influent and effluent are analyzed with both techniques. In addition, palm oil mill effluent (POME) has also been analyzed after Fenton process to compare the particle size using these tools. PSA shows most of the particles in the influent and effluent are in the size range of 100 to 700 μm, while microscopy shows additional information of aggregates structure in POME sample showing promising possibility of identifying complex structure of aggregates present in the sample.

Abstract: In order to separate wool from cashmere efficiently, an identification method based on texture analysis was proposed in this paper. The microscopic images captured by CCD digital camera were preprocessed as the texture image. Improved Tamura texture feature were employed to analyzing the final texture images and to attaining the texture parameters. Through a large number of samples, the mathematical modeling was completed by using neural network. Experiment results indicate that texture analysis can be a feasible method to identify cashmere and wool.

Abstract: The article presents a developed orginal model designed to increase the efficiency of the processes of the design of adaptive image analysis methods used for detection of surface defects in materials. The model was created as part of activities related to the Strategic Program – Specialized knowledge bases and expert systems for the simulation of complex processes. The methods presented in this paper make it possible to accelerate design process, including testing of algorithms developed for a wide range of surface defects, such as: cracks, discoloration, loss of materials, geometric distortion, or even the presence of defect agglomerations caused by corrosion, without the need for the acquisition of the physical image of the actual objects. This in many cases can be a significant problem for engineers who design automatic optical inspection systems, because the acquisition of test objects with specified defects which are characterized by a fixed range of values of selected parameters is not always possible. This paper presents a formal model designed to generate material defects on the surface of three-dimensional virtual objects, which is equivalent to the acquisition of actual data from vision systems. The model takes into account various surface characteristics such as their texture or roughness by using mapping by the Blinn method. The results of the use of the system developed for the classification of products represented in digital images for which image analysis algorithms have been based on so-called artificial intelligence in the form of dedicated neural networks are presented. As described in this paper, artificial neural networks are an example of adaptive models, and provide the ability to solve problems for which there are no deterministic models. The models, however, require the use of learning processes (training) with the use of extensive data sets, which in this case were generated with the use of the developed solution model.