For a rolling bearing fault that has nonlinearity and nonstationary characteristics, it is difficult to identify the fault category. A rolling bearing clustering fault diagnosis method based on ensemble empirical mode decomposition (EEMD), permutation entropy (PE), linear discriminant analysis (LDA), and the Gath–Geva (GG) clustering algorithm is proposed. Firstly, we decompose the vibration signal using EEMD, and several inherent modal components are obtained. Then, the permutation entropy values of each modal component are calculated to get the entropy feature vector, and the entropy feature vector is reduced by the LDA method to be used as the input of the clustering algorithm. The data experiments show that the proposed fault diagnosis method can obtain satisfactory clustering indicators. It implies that compared with other mode combination methods, the fault identification method proposed in this study has the advantage of better intra-class compactness of clustering results.

Aeronautical thin-walled frame workpieces are usually obtained by milling aluminum alloy plates. The residual stress within the workpiece has a significant influence on the deformation due to the relatively low rigidity of the workpiece. To accurately predict the milling-induced residual stress, this paper describes an orthogonal experiment for milling 7075 aluminum alloy plates. The milling-induced residual stress at different surface depths of the workpiece, without initial stress, is obtained. The influence of the milling parameters on the residual stress is revealed. The parameters include milling speed, feed per tooth, milling width, and cutting depth. The experimental results show that the residual stress depth in the workpiece surface is within 0.12 mm, and the residual stress depth of the end milling is slightly greater than that of the side milling. The calculation models of residual stress and milling parameters for two milling methods are formulated based on regression analysis, and the sensitivity coefficients of parameters to residual stress are calculated. The residual stress prediction model for milling 7075 aluminum alloy plates is proposed based on a back-propagation neural network and genetic algorithm. The findings suggest that the proposed model has a high accuracy, and the prediction error is between 0–14 MPa. It provides basic data for machining deformation prediction of aluminum alloy thin-walled workpieces, which has significant application potential.

Aluminum alloy 7075 is one of the materials widely used in the manufacture of structural components used by aviation industries. High precision is required in producing the shapes of such components due to shape stability and dimensional accuracy being difficult to maintain throughout the different stages of manufacturing. In this work, an experimental study of the effect of VSR (Vibratory Stress Relief) on the deformation and residual stresses of aluminum alloy 7075 thin-walled components is presented. It was concluded that VSR improved the shape and size stability of the material to a significant level by relieving induced residual stresses in the thin-walled parts. Finally, more uniform residual stress distribution was obtained after the VSR treatment, compared to before the VSR treatment. This proved that VSR has a significant influence on improving the shape stability of the thin-walled aluminum alloy 7075 components.

Welding is one of the essential stages in the manufacturing process of mechanical structures. Friction stir welding structure of aluminum alloy has been used as a primary supporting member in aerospace equipment. However, friction stir welding inevitably generates residual stress that promotes the initiation and propagation of cracks, threatening the performance of the welded structure. Shot peening can effectively change the distribution of residual stress and improve the fatigue properties of materials. In this paper, friction stir welding and shot peening are performed on 2219 aluminum alloy plates. The residual stress fields induced by friction stir welding and shot peening are measured by using the X-ray diffraction method and incremental center hole drilling method, and the distribution characteristics of residual stress fields are analyzed. The effect of the pellet diameters and pellet materials used in shot peening on the redistribution of welding residual stress field are investigated. The pellet diameter used in the experiment is in the range of 0.6–1.2 mm, and the pellet material includes glass, steel, and corundum. This study provides guidance for the application of shot peening in friction stir welding structure of 2219 aluminum alloy.

Relieving the residual stress in components is essential to improve their service performance. In this study, a roll-bending process was proposed to reduce the quenching residual stress in a large-size 2219 Al alloy ring. The roll-bending effect on quenching residual stress was evaluated via the finite element method (FEM) combined with experiment. The effect of radial feed quantity, friction coefficient, and roller rotational speed during the roll-bending process on quenching residual stress was analyzed. A set of optimized roll-bending parameters with radial feed quantity, friction coefficient, and roller rotational speed was obtained. The results reveal that the best reduction rates of circumferential and axial residual stress reached 61.72% and 86.24%, respectively. Furthermore, the difference of the residual stress reduction effect between the roll-bended ring and the three-roller bended beam was analyzed.