Elbows are an important component of oil and gas pipelines. The force state and the medium flow state are more complex than that of the straight pipe. Once the defect occurs at the elbow, the elbow pipe is more prone to fail. The high steel grade pipeline is the development trend of the long distance oil and gas pipeline construction, and it is urgent to evaluate the residual strength of the high steel grade bending pipe. Through the establishment of the finite element model, the defect size, relative position, bending radius, pipe parameters and pipe performance influence were studied on the ultimate internal pressure of the elbow, and finally the prediction formula of the bending was established. The results show that with the increase of defect length and defect depth, the ultimate internal pressure of the elbow is significantly reduced. The trench defect affects the ultimate internal pressure when the trench defect is located in the inner arch of the elbow. The bending radius, the wall thickness and the pipe material will affect the ultimate internal pressure. The error analysis shows that the prediction formula is more accurate, which can provide the basis for the residual strength evaluation of high steel grade elbows with trench defects.

Surface texture design is an effective way to achieve small leakage, long life and highly reliable operation of mechanical end seals. To investigate the characteristics of the interface film of guide groove texture, through the design and preparation of semi-circular, herringbone and E-shaped guide groove textures, experiments and theoretical research under high-speed operation conditions were carried out, the influence of different guide groove textures on the tribological properties of end face seals was explored. The results show that the existence of the guide groove can effectively improve the bearing capacity of the interface film and improve the tribological performance. In numerical calculations, the results show that the frictional performances of face seals varied with the configuration of guide groove. The herringbone textures and E-type ones show an obvious guide-aggregation effect. When the lubricant in E-type texture after being guide-aggregation through the groove, the pressure accumulates at the textured tail barrier, and fluid in the face seal clearance cannot escape from the guide groove boundary. As a result，the low energy loss in system, and an optimal liquid film bearing capacity achieves. Under different depths, the existence of guide groove promotes the hydrodynamic pressure. With the increase in depth, the bearing capacity of the liquid film increases first and then decreases. For the E-shape texture, the optimum bearing capacity of liquid film P_av=0.527 5 MPa is obtained at h₁=10 μm. The bearing capacity of fluid film of E-shape texture has a 51.2% increase in comparison to the common grooved texture, the value of frictional torque has a 53.5% decrease. The analysis show that, the configuration of guide groove results in an accumulation of lubricant on the top of texture, which enhances the pressure convergence, thereby improving the bearing capacity of the lubricating fluid film and reducing friction（‘guide⁃aggregation effect’）. The geometric parameters of the guide groove have a significant impact on the fluid dynamic pressure in the end face sealing pair，which will influence the tribological performances of face seal. The research result provides theoretical support for the design of non-contact end face seal material surface texture in future.

When the gear system starts or stops in non-stationary working conditions, a sharp change of the speed can cause it to exhibit complex vibration characteristics which has a significant impact on the performance and lifespan of the gear. Considering the influence of time-varying meshing stiffness, backlash and gear meshing error, a dynamics model of spur gear system was established. The influence of external load and angular acceleration on the vibration characteristics of the start-stop process was studied. At the same time, the time-frequency analysis of the non-stationary vibration signal of the gear system was carried out by using the short-time Fourier transform. The results show that increasing the load and angular acceleration during the start and stop processes will exacerbate the degree of vibration and impact of the gear pair, and both will make the unstable motion process in the early start period end earlier, and the unstable motion process in the late stop period appear later, but the impact components in the late start period (the early stop period) will increase (decrease). In the frequency domain, increasing the external load will enhance the energy of the harmonic component of the gear system’s meshing frequency, but it has no effect on the fundamental energy of the meshing frequency. However, increasing the angular acceleration will enhance the energy of both the fundamental and harmonic components of the meshing frequency.

To improve the accuracy and efficiency of load identification and structural response reconstruction, an improved Tikhonov regularization method that simultaneously considers transfer matrix error and measurement error was proposed. Firstly, the state space equation and transfer matrix were constructed through the structural dynamics model to obtain the reconstruction equation of the structural load and response. Secondly, the truncated randomized singular value decomposition method was used to calculate the approximate transfer matrix at the locations of the measurement points, while the total least squares method (TLSM) and the traditional Tikhonov regularization method were combined to identify the load,and then the unknown response was reconstructed by the transfer matrix at the locations. Finally, a numerical simulation and an experimental analysis were carried out for two-dimensional truss and simply supported beam to verify the proposed method. The results show that compared with the traditional Tikhonov regularization method, the proposed method can improve the reconstruction efficiency while guaranteeing the reconstruction accuracy.

To address the problem that it is difficult to label variable working condition gearbox fault samples and the significant data distribution discrepancies in practical engineering, which result in reduced accuracy of fault diagnosis models,a semi-supervised gearbox fault diagnosis method based on masked contrastive learning is proposed. Firstly, a random mask was used to hide part of the information in the unlabeled dataset, generating two different masked instances for each unlabeled sample. Secondly, a dynamic convolutional neural network was employed to dynamically weight and aggregate the masked instances, enabling discriminative feature modeling of different masked instances. Then, a contrastive learning framework was constructed with the optimization goal of maximizing the similarity between features of different masked instances. By enhancing the consistency of feature representations of masked instance pairs, the model's dependency on labels was reduced. Finally, during the fine-tuning phase, a domain-conditioned feature correction strategy was introduced to generate target domain feature corrections. By aligning source domain features and target domain corrected features according to the metric of minimizing domain feature distribution discrepancies, the method explicitly reduces the domain distribution differences caused by varying working conditions. Validation on a variable working condition gearbox fault dataset demonstrates the effectiveness of the proposed method.

In response to challenges such as large sampling data, extended diagnosis time, and subjective fault feature selection in traditional bearing fault diagnosis, based on compressed sensing (CS) and deep multi-kernel extreme learning machine (D-MKELM) theory, a CS-DMKELM intelligent diagnosis model for rolling bearings was proposed. Firstly, sparse signals were obtained through threshold processing of transformed domain signals. A Gaussian random matrix was employed as the measurement matrix to compress the processed data. Secongly, the compressed data was used as the input signal for the D-MKELM. Particle swarm optimization (PSO) algorithm was applied to optimize critical parameters, enabling intelligent fault diagnosis. Results demonstrate that the proposed method, using only a small amount of bearing diagnostic data,automatically extracts feature information of bearings from a limited number of measurement signals through the D-MKELM.The proposed method enables rapid fault diagnosis of bearings. With a diagnostic time of 0.55 s, a final recognition accuracy of 99.29% was achieved. The proposed method reduces the diagnostic time and exhibits the high diagnostic accuracy,providing a new approach for handling massive bearing data in the fault diagnosis.

Aiming at the problem of structural vibration modeling and characteristic analysis of rectangular sheets under arbitrary boundary conditions, an improved Fourier series method was proposed.Based on the Rayleigh-Ritz method, the allowable function of vibration displacement of thin plates was expressed as a linear combination of double Fourier cosine series function and auxiliary series function, which effectively avoided the possible discontinuities or singularities of the traditional Fourier series at the boundary. Firstly, the variational equation of the sheet vibration model was established by using the Hamilton energy variational principle, and the energy expressions in the equation were calculated and the displacement tolerance function was brought in. Secondly, the variational solution of the unknown Fourier coefficient was carried out to obtain the matrix equation of the model. The matrix equation was solved by numerical calculation method to obtain the free vibration frequency and eigenvector of the thin plate. Finally, the classical boundary conditions and elastic boundary conditions were used as examples to calculate and analyze. The calculation efficiency and accuracy of the proposed method were verified by comparison with the results of finite element simulation and existing literature. Additionally, the influence of the aspect ratio and constrained the spring stiffness coefficient on the vibration characteristics of the thin plate was discussed.

In order to improve the carrying capacity of double curved beams negative stiffness structure composed of two curved beams arranged in parallel, the curved sandwich beam negative stiffness structure was proposed. The design idea was to array the sandwich straight beam between the upper and lower curved beams of the double curved beam negative stiffness structure, and the bearing capacity and energy absorption characteristics were studied systematically. Firstly, the negative stiffness structure model was fabricated using 3D printing technology and silicone emolding process, the compressive mechanical response of the curved sandwich beam and double curved beam negative stiffness structure was compared and analyzed by quasi-static compression experiment, and the reliability of the finite element simulation model was verified. Then,the influence of structural parameters (width, spacing, height and angle) of the sandwich straight beam on the bearing capacity and energy absorption characteristics of the negative stiffness structure was studied by simulation. The results indicate that the introduction of the sandwich significantly enhances the load-bearing capacity of the double curved beam negative stiffness structure. Compared with the spacing and angle of the sandwich straight beam, increasing the width and height of the sandwich straight beams can notably enhance the load-bearing capacity and energy absorption capacity of the structure.

Based on Reddy’s layerwise theory (RLWT) and O(1) homogenization method, a three-scale layerwise multiscale analysis method (LMAM) for composite honeycomb sandwich structures was established. The macroscopic model of composite laminates was discretized by RLWT, and the microscopic unit cell model composed of fibers and matrix was established by three-dimensional finite element method. In the numerical example, the numerical simulation of the cubic block with inclusions was carried out, and the simulation results were compared with those of the direct numerical simulation (DNS)method, which verified the correctness of the LMAM. LMAM is also used to calculate and analyze the macroscopic,mesoscopic and microscopic stress distribution of composite honeycomb sandwich structures.

During the gear meshing process, the driving speed plays a crucial role in evaluating mesh stiffness, a factor that many scholars often overlook along with the accompanying centrifugal effects. Based on Euler beam theory,a original computational algorithm was proposed to calculate the dynamic mesh stiffness of spur gears considering driven-speed effects by introducing centrifugal effects into the velocity field. Using the driving speed as a control parameter, the dynamic mesh stiffness in relation to driving speed was investigated, and the nonlinear relation between centrifugal effects and dynamic mesh stiffness was demonstrated. The results indicate that, under the influence of a centrifugal field, both the natural frequency and the dynamic mesh stiffness of the gears increase with rising driving speed. Additionally, materials with a high elastic modulus tend to suppress the impact of driving speed on dynamic mesh stiffness, while higher density has the opposite effect. The research results provide reference for further analysis of gear vibration and noise under centrifugal effects.