To overcome the difficulty in early fault diagnosis with weak fault characteristics of rolling bearings that are easily drowned out by noise in the complex operation environment, an early fault diagnosis method was proposed by integrating the improved artificial gorilla troops optimizer (IGTO) algorithm, the optimized resonance-based sparse signal decomposition (RSSD), multi-parameter and sparse maximum harmonics-to-noise-ratio deconvolution (SMHD) method. Firstly, taking the squared envelope spectrum correlated kurtosis (SE-SCK) negative value of the low resonance component as the objective function, IGTO was used to simultaneously optimize the quality factor Q, weight coefficient λ and Lagrange multiplier μ of RSSD, for the achievement of the optimal matching of wavelet basis function and dissipation function. Secondly, the obtained optimal low resonance component was inputed into SMHD for filtering processing. Finally, the fault features were extracted by the perform envelope spectrum analysis. The algorithm comparison experiments show that the proposed IGTO algorithm has significantly improved optimization performance. The results of simulation and XJTU-SY bearing full life cycle fault signal test show that the proposed method is more useful in extracting early weak fault characteristics of bearings.

To explore the penetration resistance of aluminum alloy tubes under spherical steel projectile impact, focusing on the effects of varying tube radii and wall thicknesses on ballistic limit velocity, providing a foundation for tube protection design. A finite element model of spherical steel projectile penetration into 2024-T42 aluminum alloy targets was established using Ansys/Workbench software and the Johnson-Cook material model, which was then verified. Simulations of the response characteristics of aluminum alloy tubes with different radii and wall thicknesses under normal impact of spherical steel projectiles were conducted, along with an analysis of tube deformation and damage. The study found that the penetration resistance of the upper and lower walls of aluminum alloy tubes differs, with the upper convex structure outperforming the lower concave structure. A smaller tube radius enhances the penetration resistance of the upper wall, while for tubes of the same radius,increasing the wall thickness leads to a roughly linear increase in the ballistic limit velocity of both upper and lower walls.

Gear’s Circular plot is a result presentation method which needs to be combine with time synchronous averaging (TSA), which can clearly display gear meshing vibration waveform extracted by TSA. Aiming at the problem of parameter setting of gear’s Circular plot and lack of the quantitative index, F_i index for waveform edge recognition and Y_i index based on Hu-moments were proposed. Firstly, TSA algorithm was used to extract the gear meshing vibration signal, and the upper and lower edges of the vibration signal waveform were determined by calculating the minimum F_i index. Secondly,Circular plot of gears were drawn by the upper and lower edge parameters. Then, the Circular plot of the gear was divided into four parts, and Y_i index of the Circular plot was obtained by calculating Hu-moments of the picture after segmentation. Finally,based on the Y_i and F_i indices extracted from the gear Circular plot, a K-nearest neighbors (KNN) classifier was utilized to classify the gear vibration signals. The results show that there is a significant difference between the Y_i and F_i indices of the vibration signals of normal gears and those of abnormal gears. By combining with the KNN classifier，it is possible to distinguish between normal and abnormal gear signals，which proves the effectiveness of this method.

In order to study the mechanical properties of high volume fraction ratio metal particle reinforced resin matrix composites, the elastic modulus of the composites was predicted based on the micromechanics theory and the meso-finite element method. Firstly, standard specimens of the composites were prepared, and their macroscopic elastic moduli were tested by uniaxial tensile experiments, and the microscopic properties were observed. Secondly, the elastic modulus of the composites was predicted by using Voigt, Reuss, Mori-Tanaka and Generalized means based on the micromechanics theory.Then, based on the microscopic particle size statistics of the specimens, the gradation of the metal particle size and its quantity were determined by using the Gaussian distribution law, and the random particle placement program was written by Python language to construct a two-dimensional representative volume element (RVE) finite element model consisting of the particles,the resin matrix, and the interface. Finally, the elastic modulus of resin matrix composites reinforced with high volume fraction metal particles was predicted by theoretical and finite element simulations. The analysis results show that the generalized means and finite element models predict the elastic modulus with less error from the experimental test results, and the elastic modulus of the composites increases with the increase of the volume fraction of the metal particles.

In order to solve the problem of difficult to accurately extract early faults of solar wheels under the strong noise background, an improved grey wolf algorithm (newGWO) was proposed to optimize and improve the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and the maximum correlated kurtosis deconvolution (MCKD) for early fault feature extraction of solar wheels.NewGWO was used to optimize the selection of parameters of the white noise amplitude weight and noise addition times that affected the decomposition effect.The fault vibration signal was decomposed by newGWO-ICEEMDAN, and the minimum envelope entropy was selected as the fitness function to obtain several related modal components.Then, the envelope spectrum peak factor was selected as the best modal component index. MCKD signals optimized by newGWO were enhanced for the selected optimal intrinsic mode function（IMF）components. Finally, an envelope demodulation analysis was performed on the obtained signals to extract the solar wheel fault characteristic frequency and multiple frequency components. Simulation signals and experiments show that this method can make the early fault impact characteristics more obvious, and realize the early fault characteristic frequency extraction of solar wheels.

The main purpose was to study the local cyclic plastic behavior of 3D printed titanium alloy notched parts. Firstly, the local stress and strain field near the 3D printed titanium alloy notch was analyzed in detail by finite element method，and the evolution of stress and strain field was deeply investigated. Then, the experimental study was carried out and the influence of the forming direction on the results was analyzed. The results show that ratcheting deformation occurs at the notch root, with the maximum ratcheting strain rate in the L₃ direction and the minimum ratcheting strain rate in the L₁ direction. The influence of the forming direction on the stress triaxiality is not too obvious. The elastic strain energy of different forming directions is almost no difference. However, the forming direction has a great influence on the plastic strain energy. With the increase of the number of cycles, the difference of plastic strain energy results for different notch radii also becomes larger.

In order to improve the mechanical properties of three-dimensional negative Poisson ratio materials, and expand the application of negative Poisson ratio materials. A new unit cell of negative Poisson ratio structural material was proposed by introducing internal concave angles into the edges of tetrahedral porous structures, and 7 kinds of orthogonal isotropic and orthogonal anisotropic enhancement designs were carried out on it. The influence of cell geometry parameters on the dimension one equivalent elastic modulus and Poisson ratio of new and enhanced cells was studied by using the homogenized finite element method and periodic boundary conditions，and the 3D printed resin sample was used for experimental verification. Compared with the existing negative Poisson ratio unit cells, the novel unit cell can save 50% of materials while maintaining the negative Poisson ratio characteristics. The three reinforcement schemes in x-direction, y-direction and xy-direction can significantly improve the bearing-load capacity while improving the negative Poisson ratio characteristics.

In response to the problem of the gearbox fault diagnosis and analysis based on multi-sensor data under dataset imbalanced conditions, a gearbox fault diagnosis method based on a kurtosis index data fusion and a generative adversarial neural networks (GAN) was proposed. This method weighted the fusion of multiple sensor data based on signal kurtosis,highlighting the fault sensitive components of the gearbox in the fused signal. Then, a wavelet packet transform was used to extract the energy coefficients of each frequency band of the signal as signal features. Finally, the classification and recognition of signal features were implemented based on a back propagation (BP) neural network. Due to the fact that in actual working conditions, fault signals were more difficult to obtain than normal signals, GAN was used to expand the fault data section of the dataset, and the expanded dataset was used to train BP neural network. Through test analysis, it is shown that the fault accuracy of the described method is as high as 98%, which verifies the correctness of the proposed method and provides new ideas and methods for multi-sensor data fusion and fault diagnosis problems.

In order to reveal the nonlinear dynamics behavior of the marine rotor-bearing system under complex transport motions (heaving, swaying, yawing and pitching), the dynamical model of the rotor-bearing system with the nonlinear oil film force and transport inertial forces was built based on, Lagrange’s equation.The effects of the rotating speed and transport motion parameters on the nonlinear dynamics behaviors of the system were mainly analyzed. The results show that the amplitude and oil film whirl interval of the system are larger when considering the coupling motion of heaving, swaying,yawing and pitching than those when not considering this motion. Affected by the coupled transport motion, the rotor will deflect obviously at a lower speed. At a certain rotational speed, with the increase of heaving amplitude, swaying frequency or swaying amplitude, the amplitude jump phenomenon caused by the oil whirl appears in the vibration response of the system，and the motion state of the system undergoes quasi-periodic and chaos. With the increase of swaying frequency, yawing amplitude, yawing frequency, pitching amplitude or pitching frequency, the system is always in a quasi-periodic vibration state,but the vibration amplitude of the rotor increases in varying degrees.

Abnormal vibration in the pipeline associated with large synchronous condensers not only reduces the lifespan of the pipeline but also affects the supply of the lubricating oil and coolant for the synchronous condenser, posing a serious risk of major safety accidents and jeopardizing the stability of the power system. The lubricating oil supply pipeline of a specific ultra-high voltage converter station synchronous condenser was taken as the research object. Multiple methods, including field measurements, fluid-structure coupling, and harmonic response analysis, were used to investigate the causes and mechanisms of the pipeline vibration. The results indicate that the periodic excitation force generated by the synchronous condenser itself is the main cause of pipeline vibration. Furthermore, a pipeline vibration reduction measure based on a tuned mass damper(TMD) was proposed. Experimental and simulation data shows that installing a TMD at the intermediate positions between suspension supports 4 and 5, as well as 6 and 7 in the lubricating oil supply pipeline system, yields the best vibration reduction effect. This approach can reduce the vibration acceleration of the pipeline system by over 90% and exhibits the excellent vibration reduction performance.