In this study, the tribological properties of three AISI 1045 steel samples were investigated. Two samples were treated with ultrasonic shot peening (USP) and ultrasonic strengthening grinding process (USGP), respectively, while the other one was only treated with a polishing process. Sample properties, such as surface morphology, roughness, microhardness, elastic modulus, frictional coefficient, and phase structures were analyzed. Results show that the sample treated with USGP had the best tribological properties. It realized the highest surface roughness, microhardness, and elastic modulus. Compared with a polished sample, the roughness of the sample treated with USGP increased by 157%, and the microhardness and elastic modulus improved by 32.8% and 21.3%, respectively. Additionally, USGP provided an average frictional coefficient of 0.4, decreasing approximately 45% compared to polishing. The possible mechanisms of USGP surface texturing were discussed. The findings denote that USGP could be an efficient approach to improve the fatigue life of some mechanical components.

Soil determines the degree of water infiltration, crop nutrient absorption, and germination, which in turn affects crop yield and quality. For the efficient planting of agricultural products, the accurate identification of soil texture is necessary. This study proposed a flexible smartphone-based machine vision system using a deep learning autoencoder convolutional neural network random forest (DLAC-CNN-RF) model for soil texture identification. Different image features (color, particle, and texture) were extracted and randomly combined to predict sand, clay, and silt content via RF and DLAC-CNN-RF algorithms. The results show that the proposed DLAC-CNN-RF model has good performance. When the full features were extracted, a very high prediction accuracy for sand (R² = 0.99), clay (R² = 0.98), and silt (R² = 0.98) was realized, which was higher than those frequently obtained by the KNN and VGG16-RF models. The possible mechanism was further discussed. Finally, a graphical user interface was designed and used to accurately predict soil types. This investigation showed that the proposed DLAC-CNN-RF model could be a promising solution to costly and time-consuming laboratory methods.

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.

In this paper, the corrosion resistance of four GCr15 steel samples has been investigated. Three samples were initially surface-treated by ultrasonic shot peening (USP), a dry ultrasonic strengthening grinding process (DUSGP), and a wet ultrasonic strengthening grinding process (WUSGP), respectively, while another one was only polished. Then, all the processed samples were subjected to salt spray corrosion. Sample properties, such as capacitance arc, self-corrosion potential (E_corr), self-corrosion current density (I_corr), corrosion morphology, and corrosion products were analyzed. Results show that the sample treated by WUSGP has the best corrosion resistance, which can be attributed to the high dislocation density, small grain size, needle-like and lath-like shape of martensite content formed in the treatment, which hinders Cl⁻ from eroding the matrix. The obtained corrosion pits and cracks in Sample WUSGP show a width of approximately 1.4 µm and 2.1 µm, respectively, degrading 78% and 75% compared to polishing. The possible corrosion mechanism of the samples has been discussed. The findings denote that the treatment fused ceramic balls, strengthened liquid, and corundum in USP could be an efficient method to improve the corrosion resistance of some mechanical parts.