In order to simulate the shot peening process and realize the rapid prediction of the shot peening effect, a random multi-shot pellet shot peening strengthening model was established based on Abaqus software using the discrete element method-finite element method (DEM-FEM) coupling, and the TC4 titanium alloy was used as the research object to carry out the shot peening strengthening test to verify the accuracy of the coupling model. The Box-Behnken design (BBD) method was used to design a three-factor and three-level shot peening simulation test scheme for the three process parameters of projectile size, shot peening speed and shot peening coverage.The surface residual stress value and surface roughness value were obtained by simulation analysis, and the numerical fitting was carried out by Design-Expert software. Finally, the function models between the shot peening process parameters and the surface residual stress or surface roughness were obtained, the interaction between the three factors of projectile size，shot peening speed and shot peening coverage was analyzed by the response surface method, and the influence law of shot peening strengthening effect was analyzed.The results show that the error between the results of the response surface prediction model and the simulation calculation results is less than 5%, the established response surface prediction model has high approximate accuracy and reliability，and the effective prediction of shot peening effect can be achieved by using this model.

To investigate the vibration performance of RV reducers and analyze the fault identification, the torsional vibration test bench for RV reducers was built.Based on the mechanical structure and transmission principles of RV reducers,the vibration frequencies under different operating conditions were calculated.The vibration signal of RV reducers of superior and inferior products was collected, and the acceleration signal of the torsional vibration under different speeds and swerves was collected.The torsional vibration signals were decomposed using the variational mode decomposition (VMD) to obtain the intrinsic mode function (IMF).The results demonstrate a high correlation between the extracted IMF features obtained through VMD and the vibration frequencies observed during the operation of RV reducers.Furthermore, by comparing the spectrum of IMF, the reasons behind the abnormal vibration in inferior RV reducers were identified.Ultimately, it is determined that the abnormal vibration in inferior RV reducers were caused by the excitation from the interaction between the auto rotation of the planetary gear and the crankshaft or the revolution of the cycloid gear.This study provides valuable insights for enterprises aiming to improve the transmission accuracy and product quality of RV reducers.

A single-degree-of-freedom mechanical collision vibration system model with nonlinear terms and unilateral new nonlinear constraints was studied.The dynamics characteristics of the p/1 periodic motion of the system under low-frequency excitation were analyzed by using the variable-step fourth-order Runge-Kutta numerical algorithm and multi-parameter co-simulation.And the frequency hysteresis characteristics of the grazing bifurcation and saddle-node bifurcation in the p/1 periodic motion were analyzed.It was found that two different motions will exist at the same time，revealing the irreversibility of the transition between adjacent periodic motions.Finally, the influence of the change of the gap on the multi-state coexistence region of the system was studied.As the gap increases, the coexistence region of partial periodic motion decreases and transits to the low-frequency region.

In order to solve the problem of the accuracy of the random vibration transmissibility calculation of airborne electronic equipment, the basic STEINBERG sinusoidal vibration transmissibility model and the IRVINE random vibration transmissibility model were firstly verified through tests, and it was found that there was room for improvement in the accuracy of the IRVINE random vibration transmissibility model. Therefore, on the basis of the "Three-interval method", the effects of 4σ and 5σ transient acceleration of random vibration were taken into consideration, and a more comprehensive"Five-interval method" was proposed; then, the structural fatigue coefficients of the model were corrected by combining with the characteristics of the airborne electronic equipments. The results show that the error between the proposed random vibration transmissibility calculation model and the measured value is less than 5%, which is closer to the measured value,proving that the proposed model is more accurate.

In practical engineering, gearboxes are subject to complex and variable operating environments, which hinder the ability of a single vibration signal to accurately and effectively represent fault information under different working conditions. To address this issue, a gearbox fault diagnosis method for variable working conditions based on weighted subdomain adaptive adversarial networks was proposed. Initially, a multi-source heterogeneous signal fusion strategy was employed to transform vibration signal spectrograms, current signal Gramian matrices, and infrared thermograms into a multi-channel dataset, offering diverse perspectives on gearbox operational states. Subsequently, a self-calibrated convolutions network (SCNet) incorporating an efficient channel attention (ECA) mechanism acted as a feature extractor, dynamically adjusting the interactions and dependencies between multi-source heterogeneous signals to balance the scale differences between the source and target domain heterogeneous data. Concurrently, during adversarial training of the feature extractor and domain discriminator, maximum mean discrepancy (MMD) and linear discriminant analysis (LDA) were introduced to measure the domain alignment degree of the current cross-domain task feature representation and the diagnostic task decision boundary. A dynamic balancing factor was constructed to real-time adjust domain alignment loss and class discriminability loss, effectively aligning each class space between the source and target domains. Finally, validated by a collected gearbox fault dataset under variable operating conditions. The results show that the proposed method achieves diagnostic accuracy exceeding 95% across different conditions, demonstrating its feasibility and effectiveness.

As the key equipment for collecting signals, the coupling performance of oil and gas exploration geophone and earth vibration affects the quality of collected signals and determines the exploration accuracy. In order to improve the exploration ability of the geophone, the structure of the tail vertebra of the geophone was taken as the research object. Based on the single-degree-of-freedom coupling vibration theory, a vibration model for the coupling of the tail vertebra of the geophone and the earth surface under the sweep frequency signal was proposed. The acceleration,velocity and displacement response of the received signal of the tail vertebra of the geophone under the sweep frequency were extracted and analyzed.The coupling degree evaluation index of the mean value of vibration displacement and the standard deviation of vibration acceleration was established, and the coupling degree response of the tail vertebra of the geophone and the earth was mastered.Through the geophone receiving test, the maximum error between the acceleration signal received by the geophone tail vertebra and the acceleration signal received by the test was less than 15%, which verified the correctness of the model and method. Finally, based on the response surface method, the key parameters of the length and radius of the tail vertebra under different shapes were optimized. The results show that the coupling degree of the tail vertebra under the triangular pyramid shape is the best. The coupling mean value of the displacement of the optimized ground-geophone tail vertebra is reduced by 7.94%, and the standard deviation of the acceleration is reduced by 6.42%, which effectively improve the ability of the geophone tail vertebra to receive signals.

Metal structures are widely used in industry. Metal structures in service are prone to crack defects under tensile and compressive fatigue load.In order to realize quantitative detection of metal structures’ crack defects, a quantitative analysis method of metal structures’ weak magnetic detection based on back propagation (BP) neural network was studied. In view of the poor effect and low efficiency of BP neural network in parameter adjustment, the improved whale optimization algorithm (IWOA) based on Sine chaotic mapping was adopted to optimize the BP neural network parameter adjustment mode,giving consideration to global optimization while improving the local optimization ability, and then the optimal parameters searched by IWOA were assigned to BP neural network, improving the quality of initial network parameters.The length, width and depth of the artificial rectangular slot were quantified by inversion. The results show that the average prediction accuracy of IWOA-BP neural network is above 80%, and the prediction accuracy of depth, length and width is improved respectively by 106.72%, 9.68% and 6.86%.

To address the creep issue that arises during the long-term vertical storage of solid rocket motor (SRM), a method was proposed that involved embedding a specially shaped functional combustible core model (reinforcement structure) into the propellant grain matrix without altering the basic structure of the grain. Initially, the distribution patterns of creep in the propellant grain under the coupled effect of solidification cooling and vertical self-weight were analyzed by using three-dimensional numerical simulation methods. Subsequently, the reinforcement structure was designed by using the solid isotropic material with penalization (SIMP) method for topology optimization, determining the geometric configuration of the embedded reinforcement structure. Finally, the final optimized design results were determined through comparative analysis of the anti-creep effect of the topology-optimized reinforcement structure. The research results demonstrate that the deformation stress and strain of the solid rocket motor propellant grain with the reinforcement structure are significantly reduced compared to those without the reinforcement structure, effectively suppressing the creep of the grain.

In the course of real operation, the drive axle housing is likely to undergo fatigue failure due to prolonged exposure to cyclic alternating loads.To determine whether the drive axle housing of a commercial vehicle’s wheel-side electric motor complying with fatigue life requirements at the design stage, a three-dimensional model and finite element model of the drive axle were established. Firstly, an initial inertia release analysis was performed，indicating that its static strength and stiffness met the requirements.Secondly, based on this foundation，utilizing nCode DesignLife software, using the nominal stress method in conjunction with the material’s S⁃N curve and fatigue loading curve, a new automotive industry standard was employed to predict the fatigue life of the housing under multiple conditions，such as vertical bending fatigue,braking fatigue and lateral fatigue.The results revealed that the fatigue life of the drive axle housing under braking fatigue and lateral fatigue conditions did not meet the requirements set out in the standard, necessitating structural optimization. Finally,reinforcement optimization was performed on the drive axle housing. The results show that, through optimization，the maximum stress of the drive axle housing is reduced by 95.8 MPa and the maximum deformation is decreased by 1.064 mm under the maximum impact conditions.Additionally, the minimum fatigue life under three different fatigue conditions is improved respectively by 1.076 million cycles, 289 000 cycles, and 497 000 cycles, exceeding the requirements stated in the standards.This validates the feasibility of optimizing the drive axle housing structure, effectively shortening and reducing the research and development cycles and associated costs.

In order to solve the problem of multi-source heterogeneous data fusion and improve the accuracy of reliability evaluation, a multi-source heterogeneous data fusion method based on approximate failure point was proposed by using D-S theory and the least squares method.Firstly, the probability envelope curves were obtained through constructing probability assignment for a single source of data and performing weighted fusion.A distribution fitting model based on approximate failure points was also established.Secondly, the parameter estimation value was obtained by the least squares method, and the area metric was constructed to determine the true failure distribution function，and then the reliability assessment was completed.Finally, the feasibility and effectiveness of the proposed method were verified by examples, and the accuracy was higher than that of Bayes method.