The Effect of the Displacement Amplitude on the Fretting Wear of GCr15 Steel with a TiC Coating.

In the present paper, the effect of mechanical ball milling time on the fretting wear of GCr15 steel balls at different displacement amplitudes is investigated. TiC powder coating was fabricated on the surface of GCr15 steel balls using various process times, and the fretting wear tests were conducted on an AISI 52100 steel disk with the applied force of 80 N. Additionally, various displacement amplitudes (10 µm, 20 µm, and 60 µm) were selected. Specimen attributes and wear scars were characterized using an inverted metallographic microscope, a microhardness tester, an X-ray diffractometry analyzer, a white light interferometer, and a scanning electron microscope. The results showed that thick and continuous coatings could be obtained at the milling time of 18 h. The specimens processed for a longer milling time demonstrated better fretting wear resistance, which we attribute to higher microhardness of the surface layer. The coefficient of friction and wear volume of specimens at each different displacement amplitude significantly decreased with increasing milling time. As the displacement amplitude increased, the three fretting states were: partial slip coordinated by elastic deformation; partial slip state coordinated by plastic deformation; and gross slip condition. Our observations indicate that mechanical ball milling could be an efficient approach to improve the fretting wear resistance of GCr15 steel balls.

Enhanced Strength-Ductility Synergy Properties in Selective Laser Melted 316L Stainless Steel by Strengthening Grinding Process.

Selective laser melted (SLM) 316L stainless steel (SS) has been widely employed in the fields of designing and manufacturing components with complex shapes and sizes. However, the low yield strength, low ultimate tensile stress, and low hardness of SLM 316L SS components hinder its further application. In this work, the strengthening grinding process (SGP) was used to enhance the mechanical properties of SLM 316L SS. The microhardness, residual stress, microstructure, and tensile properties of all the samples were analyzed. The results demonstrate that the SGP induced higher compressive residual stress and microhardness, as well as higher tensile properties. The maximum hardness and residual stress reached 354.5 HV and -446 MPa, respectively, indicating that the SGP resulted in a plastic deformation layer over 150 µm. The possible mechanisms have been discussed in further detail. Compared to the untreated sample, the SGP sample shows a significant improvement in yield strength (YS), ultimate tensile stress (UTS), and elongation (EL), increasing 30%, 25.5%, and 99.1%, respectively. This work demonstrates that SGP treatment could be an efficient approach to simultaneously improving the strength and ductility of the SLM 316L SS, which makes it more suitable for engineering applications.

The Tribological Properties of 30CrMnSiA Bearing Steels Treated by the Strengthening Grinding Process under Lubrication Wear.

This study used the strengthening grinding process (SGP) to treat the surface of 30CrMnSiA bearing steels. The effect of the jet angle of SGP on the tribological properties of 30CrMnSiA bearing steels under lubrication was investigated. The principle of enhancing wear resistance of 30CrMnSiA bearing steel ascribed to SGP was discussed in detail. The results showed that the lubrication properties and surface hardness of the 30CrMnSiA steels were enhanced due to the formation of numerous microscale microscope oil pockets on the surface layer and the grain refinement of the surface microstructures, resulting in a significant improvement in wear resistance. With the jet angle of SGP increased from 0° to 90°, the friction coefficient, the wear volume, and the specific wear rate were exhibited to reduce rapidly first, then reduce slowly, and then rise slowly. With the optimal parameters at the jet angle of 60°, compared with the control sample, the average friction coefficient was reduced from 0.2235 to 0.1609, and the wear volume and specific wear rate were reduced from 9.04 × 10-3 mm3 to 3.82 × 10-3 mm3 and from 15.13 × 10-3 mm2/N to 6.36 × 10-3 mm2/N, respectively. When the jet angle was 90°, the reduced wear resistance was mainly attributed to the excessive roughness that caused the oil coating on the surface to be severely damaged.

A Domestic Trash Detection Model Based on Improved YOLOX.

Domestic trash detection is an essential technology toward achieving a smart city. Due to the complexity and variability of urban trash scenarios, the existing trash detection algorithms suffer from low detection rates and high false positives, as well as the general problem of slow speed in industrial applications. This paper proposes an i-YOLOX model for domestic trash detection based on deep learning algorithms. First, a large number of real-life trash images are collected into a new trash image dataset. Second, the lightweight operator involution is incorporated into the feature extraction structure of the algorithm, which allows the feature extraction layer to establish long-distance feature relationships and adaptively extract channel features. In addition, the ability of the model to distinguish similar trash features is strengthened by adding the convolutional block attention module (CBAM) to the enhanced feature extraction network. Finally, the design of the involution residual head structure in the detection head reduces the gradient disappearance and accelerates the convergence of the model loss values allowing the model to perform better classification and regression of the acquired feature layers. In this study, YOLOX-S is chosen as the baseline for each enhancement experiment. The experimental results show that compared with the baseline algorithm, the mean average precision (mAP) of i-YOLOX is improved by 1.47%, the number of parameters is reduced by 23.3%, and the FPS is improved by 40.4%. In practical applications, this improved model achieves accurate recognition of trash in natural scenes, which further validates the generalization performance of i-YOLOX and provides a reference for future domestic trash detection research.

Tribological Properties of Ti6Al4V Alloy Composite Texture Fabricated by Ultrasonic Strengthening Grinding and Laser Processing.

The Ti6Al4V alloy has been widely used in aerospace equipment and medical devices. However, the poor wear resistance of the Ti6Al4V alloy hinders its further engineering application. In this study, the ultrasonic strengthening grinding process (USGP) and laser texturing process were employed to enhance the wear resistance of Ti6Al4V alloy. The frictional behavior of all samples was determined via a ball-on-disc friction and wear tester under dry conditions. The worn surface morphology, cross-sectional hardness, surface roughness, and microstructure were analyzed. The results demonstrated that the USGP induced high hardness, high dislocation density, and grain refinement, as well as improvements in the wear resistance of Ti6Al4V. Moreover, laser texture could enhance the capacity to capture wear debris and reduce wear probability. When combining the USGP and laser texturing process for the surface treatment of Ti6Al4V alloy, the lowest and most stable friction coefficients were obtained, as well as the best wear resistance. Compared to the polished sample, the steady stage friction coefficient of the sample treated by USGP and laser texturing process was remarkably decreased by 58%. This work demonstrates that combining the USGP and laser texturing process could be a promising solution for improving the wear resistance properties of Ti6Al4V alloy, which makes it more suitable for various engineering applications.

Video tracking for high-similarity drug tablets based on reflective lightness intensity and fuzzy recognition system.

Video tracking of drug tablet exerts important influences on the efficiency and reliability of its mass production; this topic also becomes a difficult and targeted focus for pharmaceutical production monitory in the past several years due to the high similarity and random distribution of those objectives to be searched for. By measuring the reflective lightness intensity of illumination lightness on tablet surface, reflective lightness intensity matrix was established and demonstrated in the form of grey image, presenting its shape topology and topography details in return. On this basis, a series of mathematical properties for describing reflective lightness intensity images were proposed, thereafter a set of fuzzy recognition system and its identification rules can be employed to classify those moving tablets with inputted image properties, which facilitates the determination of their instantaneous coordinate positions on given image frame accordingly. By repeating identical operations on the next frame, the real-time motions of tablet objectives were traced successfully. Orthogonal tracking experiment and performance comparisons verified the accuracy and reliability of this new method in pharmaceutical industry. With original suggestions concerning imaging arrangements, tablet descriptions and video tracking, this article provides reliable references and new research ideas for tablet tracking performance in high-yielding production domain.

Image tracking for the high similarity drug tablets based on light intensity reflective energy and artificial neural network.

It is obvious that tablet image tracking exerts a notable influence on the efficiency and reliability of high-speed drug mass production, and, simultaneously, it also emerges as a big difficult problem and targeted focus during production monitoring in recent years, due to the high similarity shape and random position distribution of those objectives to be searched for. For the purpose of tracking tablets accurately in random distribution, through using surface fitting approach and transitional vector determination, the calibrated surface of light intensity reflective energy can be established, describing the shape topology and topography details of objective tablet. On this basis, the mathematical properties of these established surfaces have been proposed, and thereafter artificial neural network (ANN) has been employed for classifying those moving targeted tablets by recognizing their different surface properties; therefore, the instantaneous coordinate positions of those drug tablets on one image frame can then be determined. By repeating identical pattern recognition on the next image frame, the real-time movements of objective tablet templates were successfully tracked in sequence. This paper provides reliable references and new research ideas for the real-time objective tracking in the case of drug production practices.

Fuzzy performance between surface fitting and energy distribution in turbulence runner.

Because the application of surface fitting algorithms exerts a considerable fuzzy influence on the mathematical features of kinetic energy distribution, their relation mechanism in different external conditional parameters must be quantitatively analyzed. Through determining the kinetic energy value of each selected representative position coordinate point by calculating kinetic energy parameters, several typical algorithms of complicated surface fitting are applied for constructing microkinetic energy distribution surface models in the objective turbulence runner with those obtained kinetic energy values. On the base of calculating the newly proposed mathematical features, we construct fuzzy evaluation data sequence and present a new three-dimensional fuzzy quantitative evaluation method; then the value change tendencies of kinetic energy distribution surface features can be clearly quantified, and the fuzzy performance mechanism discipline between the performance results of surface fitting algorithms, the spatial features of turbulence kinetic energy distribution surface, and their respective environmental parameter conditions can be quantitatively analyzed in detail, which results in the acquirement of final conclusions concerning the inherent turbulence kinetic energy distribution performance mechanism and its mathematical relation. A further turbulence energy quantitative study can be ensured.