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 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.

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.

Taking multicellular square tubes as the research object, the influence of the evolution of cross section shape on the energy absorption of the structure of multicellular square tubes was studied by using the verified finite element model. The results show that, under the same mass conditions, the multicellular tubes with the best energy absorption k=0.25 increased by 26.34% compared with those with the worst energy absorption k=0.40. Under the same wall thickness, the energy absorption with k=0.25 and the specific energy absorption of the multicellular tubes were 311.69% and 73.80% higher respectively than that of the ones with k=0, and the crushing force efficiency was increased by 52.51%. Finally, the parametric study of shape coefficient and wall thickness on the structural crashworthiness was carried out systematically. The research results can provide a reference for innovative design of multicellular square tubes.

In order to eliminate the restriction of the return spring stiffness on the power generation and system reliability of the energy harvesting speed bump with the full wave mechanical rectifier, a dual-speed bump energy harvester (DBEH) based on the half-wave mechanical rectifier was proposed. The device utilized a mechanical transmission module to convert the downward linear movement of two speed bumps, driven by wheels, into the one-way rotary movement of a single generator shaft, thereby converting mechanical energy into electrical energy. The unidirectional motion conversion reduced the demand for the load of the return spring. The theoretical model of the wheel excitation and speed bump dynamics was established and verified by road tests. Based on the theoretical model, the power generation performance of DBEH was studied by numerical simulation. The research results indicate that the root mean square (RMS) power and output electrical energy of the system increase with the increase of external excitation amplitude and the decrease of the spring stiffness. When the load resistance value is 7-9 Ω, the output performance of the system is optimal. Compared to reducing the gear radius, increasing the speed of the gearbox has a more significant impact on the improvement of system output. A small inertia flywheel can effectively improve the system’s capture of the mechanical energy and the conversion rate from the mechanical energy to the electrical energy.

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.

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 explore the impact of key parameters of brake pads on the dynamics characteristics of the braking system,the test research based on a friction testing machine with a slider-disc structure was conducted.The test research of the impact of key parameters of brake pads (rotation speed, pressure, mass, braking radius, etc.) and the braking environment (dry friction, wetness, sand) on the stability of the braking system was carried out. At the same time, a dynamics model of the brake pad braking system was established，compared with test results using the mathematical tool of autocorrelation coefficient. The results show that the key parameters of brake pads have a significant impact on the dynamics characteristics of the braking system; under different conditions of brake pad mass, tribological parameters, brake pad radius, and braking environment; the chaotic characteristics of the braking friction force signal show a trend of expansion or contraction; the chaotic vibration can be suppressed by adjusting the key parameters of brake pads. This study can provide reference for optimizing the braking strategy and reducing noise and vibration in brake pad systems.

In order to improve the traditional design concept and the lack of optimization of genetic algorithm, and promote the development and innovation of the shape optimization of truss structure, according to the basic principles of harmony search algorithm and genetic algorithm, a new hybrid genetic algorithm-harmony search genetic algorithm was proposed (the mixing of genetic algorithm and harmony search algorithm is to embed the harmony search operator after the operation of the genetic algorithm), and at the same time the cross-variation in the genetic algorithm was adaptively improved in three situations, and elitism and other improvement measures were introduced. In addition, the harmonious search algorithm is processed with mixed variables of discrete variables and continuous variables, and a truss structure shape optimization method based on the harmonic search hybrid genetic algorithm was established. In the optimization process, the two different types of design variables of node coordinates and cross-section area were considered uniformly, which solves the problem of difficulty in coupling of the two types of variables. Through the analysis of two typical examples, the results show that the harmonic search genetic algorithm (HS-GA) has efficient convergence speed and strong global ability. Compared with genetic algorithm (GA), heuristic particle swarm optimization (HPSO) and other optimization algorithms, the optimization effect is obvious, and it is a method suitable for the shape optimization of truss structure.

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.