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The purpose of this paper is to study the application of advanced computer image processing techniques for flaw detection on flexible printed circuit (FPC) solder.

Texture directionality feature is obtained based on texture gradient, contour's position is extracted and directionality information obtained through analyzing the distribution of directionality. Contour similarity function is established to filter out false contour and keep proper contour, and the solder's location work is accomplished based on reversed contour. After that, a combination of grey and texture gradient's value deviation from reference value is utilized to reflect and describe texture on the solder's surface. Flaw can be distinguished from homogeneous texture background.

The method has been applied to the inspecting system and achieved a higher accuracy and a lower false defect rate. It demonstrates that the method can detect flaws efficiently and effectively.

Although the work on FPC solder's location and flaw detection is presented, defective classification is not involved that is also very important content for inspection.

The paper provides a new way to locate solder based on directionality. The method not only extracts contour feature but also gains directional parameters to help realize accurate location, especially for some solders that are deformed to some extent. Entropy statistic based on distribution of grey and texture gradient is proposed to describe and measure solder's surface texture. The new algorithm performs stably and efficiently and is fit for practical application.

The purpose of this paper is to propose a new inspecting algorithm for defect detection on PCB circuits.

PCB circuit images were processed by a radon transformation. A Radon histogram was formed and utilized to establish a texture directional characteristic similarity function. Then, a region of the image which contained the same texture directionality feature was segmented. Furthermore, a directionality estimation method is presented. As the circuit was damaged, the directionality was weakened correspondingly. According to principle, the concept of directional intensity was proposed and then used to measure directionality through analysis of the Radon histogram fluctuation. Finally, the defect was detected based on directional intensity.

The method has been applied to an inspecting system used in practice and it achieved a higher accuracy and efficiency in comparison with similar methods.

Although work on highly intensive PCB circuitry inspection and flaw detection is presented, defect classification was not involved although this is also a very important requirement of inspection.

The paper provides a new way to detect PCB circuitry defects based on texture directionality and proposes evaluating the similarity between image texture directionalities using a radon transformation to search the inspected area. As the inspected region was located, the concept of directional intensity was defined to measure texture directionality to identify defects. The new algorithm performs stably and efficiently and is fit for practical application.

This paper aims to enhance lubrication performance of the pitcher plant–like textured surface with various parameters.

A pitcher plant–like structure surface is fabricated on the copper alloy, and the lubrication performance of the pitcher plant–like structure with various parameters is evaluated. In addition, the pressure distribution and oil film load capacity of the pitcher plant–like surface are simulated based on Navier–Stokes equations.

When the direction of motion aligns with the pitcher plant–like structure, the friction coefficient remains lower than that of the nontextured surface, and it exhibits a decreasing trend with the increasing of the texture width and spacing distance; the lowest friction coefficient (0.04) is achieved with B = 0.3 mm, L = 1.0 mm and θ = 45°, marking a 75% reduction compared to the nontextured surface. Simulation results demonstrate that with the increase in texture width and spacing distance, the oil film load-bearing capacity demonstrates an increasing trend.

Bionic pitcher plants are prepared on the copper alloy to improve the lubrication performance and wear resistance.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0119/

This study aims to solve the premature failure of the rubber stator due to wear, reduce the frictional resistance moment of the screw pump to solve the problem of a model of Daqing oilfield screw pump oil recovery system shutdown after the difficult start.

For the first time, the rotor surface of a screw pump was treated with dot-matrix texture to study the effect of dot matrix texture on the tribological performance of the stator-rotor friction subsets of screw pump. Reciprocating friction tests with different texture morphologies (S-shape, double tongue) and angular parameters (0°, 45° and 90°) were conducted at 10% of the texture area and pump silicone grease.

When point texture was added to the surface of the rotor sample, the friction coefficient and wear quantity of the sample were lower than those of the surface without texture treatment, and the double tongue 0° combination showed the best tribological properties. At this time, the average coefficient of friction and wear is reduced by 22.8% and 62%, 28.6% and 64.8%.

The introduction of texture can effectively improve the tribological performance of progressive screw pumps, and this paper provides important theoretical and experimental support for the design of progressive screw pumps in practical applications.

The urban environment is perceived through multiple senses in parallel, which means that visual understanding of space is aided and complemented by auditory, basic-orienting, and haptic stimuli – although mainly unconsciously. Sensory conditions are inherent attributes of urban places, but are often overlooked in research. To include these aspects in any way in analysis of the urban landscape, they need to be understood as properties of urban space, to be translated from attributes of the perceiver to attributes of the perceived. Using the relation between a designed garden and its suburban context in Bad Oeynhausen (DE) as an example, I will explore an alternative analytical methodology that takes the first-hand perspective view of the subject moving through the city as the starting point. The human body explores space by moving through it; walking is the most direct way to access, study, and research the physical qualities of the (urban) landscape, involving not only visual experience but also sound, rhythm, kinaesthesia, balance, and so forth. A notation technique that discloses the interrelation between visual qualities and their perception over time is the technique of ‘scoring’. Scores are symbolisations of processes, which extend over time. They can objectively represent non-visual qualities of space, communicating the relation between such processes and their spatial context to others in other places and other moments. These representations of movement expose the qualities of the surroundings that change as one moves through them, thus communicating the experiential aspects of urban landscape.

Nowadays, most methods of illusion garment evaluation are based on the subjective evaluation of experienced practitioners, which consumes time and the results are too subjective to be accurate enough. It is necessary to explore a method that can quantify professional experience into objective indicators to evaluate the sensory comfort of the optical illusion skirt quickly and accurately. The purpose of this paper is to propose a method to objectively evaluate the sensory comfort of optical illusion skirt patterns by combining texture feature extraction and prediction model construction.

Firstly, 10 optical illusion sample skirts are produced, and 10 experimental images are collected for each sample skirt. Then a Likert five-level evaluation scale is designed to obtain the sensory comfort level of each skirt through the questionnaire survey. Synchronously, the coarseness, contrast, directionality, line-likeness, regularity and roughness of the sample image are calculated based on Tamura texture feature algorithm, and the mean, contrast and entropy are extracted of the image transformed by Gabor wavelet. Both are set as objective parameters. Two final indicators T1 and T2 are refined from the objective parameters previously obtained to construct the predictive model of the subjective comfort of the visual illusion skirt. The linear regression model and the MLP neural network model are constructed.

Results show that the accuracy of the linear regression model is 92%, and prediction accuracy of the MLP neural network model is 97.9%. It is feasible to use Tamura texture features, Gabor wavelet transform and MLP neural network methods to objectively predict the sensory comfort of visual illusion skirt images.

Compared with the existing uncertain and non-reproducible subjective evaluation of optical illusion clothing based on experienced experts. The main advantage of the authors' method is that this method can objectively obtain evaluation parameters, quickly and accurately obtain evaluation grades without repeated evaluation by experienced experts. It is a method of objectively quantifying the experience of experts.

The precise segmentation of brain tumors is the most important and crucial step in their diagnosis and treatment. Due to the presence of noise, uneven gray levels, blurred boundaries and edema around the brain tumor region, the brain tumor image has indistinct features in the tumor region, which pose a problem for diagnostics. The paper aims to discuss these issues.

In this paper, the authors propose an original solution for segmentation using Tamura Texture and ensemble Support Vector Machine (SVM) structure. In the proposed technique, 124 features of each voxel are extracted, including Tamura texture features and grayscale features. Then, these features are ranked using the SVM-Recursive Feature Elimination method, which is also adopted to optimize the parameters of the Radial Basis Function kernel of SVMs. Finally, the bagging random sampling method is utilized to construct the ensemble SVM classifier based on a weighted voting mechanism to classify the types of voxel.

The experiments are conducted over a sample data set to be called BraTS2015. The experiments demonstrate that Tamura texture is very useful in the segmentation of brain tumors, especially the feature of line-likeness. The superior performance of the proposed ensemble SVM classifier is demonstrated by comparison with single SVM classifiers as well as other methods.

The authors propose an original solution for segmentation using Tamura Texture and ensemble SVM structure.

Microstructure-sensitive design (MSD), for optimal performance of engineering components that are sensitive to material anisotropy, has largely been confined to the realm of theory. The purpose of this paper is to insert the MSD framework into a finite element environment in order to arrive at a practical tool for improved selection and design of materials for critical engineering situations.

This study applies the recently developed Hybrid Bishop-Hill (HBH) model to map the yield surface of anisotropic oxygen free electronic copper. Combining this information with the detailed local stresses determined via finite element analysis (FEA), a “configurational yield stress” is determined for the entire component. By varying the material choice/processing conditions and selecting the directionality of anisotropy, an optimal configuration is found.

The paper provides a new FEA-based framework for MSD for yield-limited situations. The approach identified optimal directionality and processing configurations for three engineering situations that are particularly sensitive to material anisotropy.

The microstructure design space for this study is limited to a selection of eight copper materials produced by a range of processing methods, but is generalizable to many materials that exhibit anisotropic behavior.

The introduction of MSD methodology into a finite element environment is a first step toward a comprehensive designer toolkit for exploiting the anisotropy of general materials (such as metals) in a way that is routinely undertaken in the world of fiber-based composite materials. While the gains are not as sizeable (due to the less-extreme anisotropy), in many applications they may be extremely important.

This paper aims to investigate the feasibility of adding macro-textures to triangle meshes for additive manufacturing (AM) focusing on possible time and quality issues in both software processing and part fabrication.

A demonstrative software tool was developed to apply user-selected textures to existing meshes. The computational procedure is a three-dimensional extension of the solid texturing method used in computer graphics. The tool was tested for speed and quality of results, considering also the pre- and post-processing operations required. Some textured meshes were printed by different processes to test build speed and quality.

The tool can handle models with realistic complexity in acceptable computation times. Parts are built without difficulties or extra-costs achieving a good aesthetic yield of the texture.

The tool cannot reproduce sample patterns but requires the development of a generation algorithm for different type of textures. Mesh processing operations may take a long time when very fine textures are added to large parts.

Direct texturing can help obtain parts with aesthetic or functional textures without the need for surface post-treatments, which can be especially difficult and expensive for plastic parts.

The proposed method improves the uniformity and consistency of textures compared to existing approaches, and can support future systematic studies on the detail resolution of AM processes.