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Since the fault vibration data collected in real engineering may be accompanied by noise，traditional diagnostic models are difficult to identify fault categories，to address this problem，a rolling bearing fault diagnosis research method based on channel and spatial reconstruction and progressive convolutional neural networks （CSRP-CNN） was proposed.The model utilizes channel and spatial reconstruction convolution （CSConv） to reduce the redundant information of channels and space in fault features，and reduces the complexity and computation to improve the performance； using convolutional block attention module （CBAM），attention enhancement operation was carried out in the channel and spatial dimensions to make the model pay attention to important fault feature information； and progressive convolutional network structure was used in the shallow layer of the network，which will fuse the previous fault feature information fused with the current input to obtain richer feature information.The performance of CSRP-CNN was evaluated by two different datasets of Case Western Reserve University（CWRU）and machinery fault simulator magnum（MFS-MG）.After the noise and ablation tests，it is verified that CSRP-CNN has strong robustness and the effects of CSConv，CBAM and progressive convolutional neural network（PCNN） on the model noise immunity performance.

The outer ring spalling failure angle position of the rolling bearing has an important influence on the vibration size and service life of the rotating machine. It is necessary to judge the outer ring spalling failure angle within the load-bearing interval. Based on the peak change law of the acceleration vibration signal, a fault location method was proposed for ball bearing outer ring spalling. This method established the Lagrangian dynamic equation with time-varying impact force. By analyzing the change trend of the contact force in the bearing area of the ball bearing, the law of the peak ratio of the absolute value of the vibration acceleration signal was obtained by analogy, and the impact point of the acceleration vibration signal was analyzed. For nearby locations, a new judgment index was proposed, and the specific location of the fault was obtained. Simulation and experiment results show that there is a corresponding functional relationship between the horizontal vertical synchronization peak ratio of the vibration signals at different positions of the ball bearing outer ring spalling fault. Simulation and experiment verify the accuracy of the positioning law. It provides a theoretical basis for the diagnosis method to determine the location of the ball bearing outer ring spalling fault location.

Aiming at the problem of insufficient labeled samples in the process of rolling bearing fault diagnosis, a rolling bearing fault diagnosis model based on semi supervised Laplace score（SSLS） and kernel principal component analysis（KPCA） is proposed by combining with the idea of feature selection and secondary mining. SSLS applies the semi supervised idea to the Laplace score feature selection method, uses a small number of labeled samples and a large number of unlabeled samples, and combines KPCA to excavate fault features for a second time. At the same time, particle swarm optimization-based support vector machine（PSO-SVM） algorithm is used for fault classification. Finally, the model is applied to the process of experimental data analysis. The results show that the model can not only reduce the workload of sample marking, but also maintain a high accuracy in rolling bearing fault classification, which verifies the effectiveness and engineering practicability of the model.

In recent years, negative Poisson′s ratio（NPR） materials have attracted extensive attention from the academic community due to their excellent mechanical properties and huge application potential in traditional industrial fields. The mechanical properties of a new type of material with negative Poisson′s ratio（based on YSH structural cell） under dynamic compression are designed and studied. Through the finite element simulation method, the response difference of different structural parameters（inclined wall angle, width ratio, aspect ratio） to the equivalent elastic mechanical performance parameters of the cell is compared, and the influence of these structural parameters on the energy absorption performance is explored, and the research is further extended to the structure under four common functional gradient arrays. The energy absorption effect of the structure is evaluated by three indexes: energy absorption, energy absorption efficiency and platform stress. The study shows that, inclined wall inclination θ the larger, the better the energy absorption performance of the whole structure; width ratio α it has little influence on the equivalent mechanical properties and energy absorption of the whole structure; aspect ratio β the smaller the value, the more obvious the negative Poisson′s ratio effect of the structure, but on the contrary, the larger the value, the higher the energy absorption efficiency. The results can provide a reference for the function-oriented design of materials with negative Poisson′s ratio.

The lubrication state of wire rope has an important influence on the working characteristics and fatigue life of wire rope. 6X19 steel wire rope is taken as the research object, and three kinds of steel wire rope without grease lubrication, partially lubrication and fully lubrication are selected. The bending fatigue tests are carried out on the bending fatigue test machine under different tension states, and the fatigue damage states of each specimen in different stages are statistically analyzed and microscopic studied. Under good lubrication condition, between wire rope and pulley rope groove of the oil film to improve the contact state, reduce the friction coefficient between steel wire rope, steel wire surface is not easy to wear and tear scratches, delay the formation and extension of cracks and improve the steel wire rope section stress distribution and reduce the stress concentration phenomenon, make more effective load effect on the number of steel wire. The steel wire in the rope is fully drawn, and the proportion of necked broken wire in the total broken wire is higher than that of the wire rope with poor lubrication condition. For the wire rope with poor lubrication condition, the proportion of flush fracture is high, and the steel wire in the rope is not fully drawn, resulting in wire breakage due to local damage. Under the same lubrication condition, the increase of tension force destroys the lubricating oil film between the wire rope and pulley groove on the one hand, on the other hand, under the action of compressive stress, the lubricating oil in the rope core is not easy to infiltrate into the side of the wire rope and pulley groove, which deteriorates the lubrication state.

Shot peening is an important mechanical treatment process for metal surface. Its treatment quality is closely related to the shot motion behavior which is derived by high speed airflow. To accurate control shots motion and improve treatment quality in shot peening, it is great significance to explore an accurate measurement method and uncover the law of shots motion in peening process. With high speed camera, a high-speed image data acquisition system for shots in peening process was established. In addition, the images of instantaneous spatial position of shots in peening were captured. In order to improve contrast, Photoshop was used to covert the collected photos into black-and-white binary images. The open source particle image velocimetry（PIV） software PIVLab was used to analyze these images, and the velocity field of shot flow was carefully calculated. The results show that, under the condition of 0.4 MPa gas pressure and 0.4 mm cast steel shot, the scattering cone angle of shot flow was 10 degrees, and the maximum velocity of shot was about 46.5 m/s. On different spatial sections, the velocity of shots presents Gaussian distribution. In addition, the standard deviation of this Gaussian distribution is increased with enlarge the distance between shots and nozzles. The velocity of shots increases rapidly to a stable value after leaving nozzle, and the velocity variation conforms to the Logistic function. Compared with the empirical formula, the obtained formula of velocity field distribution of shots is more accurate. Furthermore, the spatial distribution characteristics of shots flow in peening process can be exactly gained.

In order to improve the reliability of the front subframe of a front drive SUV, the strength and fatigue characteristics of the subframe under different working conditions are analyzed by comprehensively using the finite element method, multi-body dynamics theory, strength analysis theory and fatigue analysis theory, and through the established three-dimensional model of the front subframe and the rigid flexible coupling model of multi-body dynamics. The strength and fatigue tests of the subframe are carried out. The simulation results show that the deformation of steering connection point is 2.924 mm and 3.411 mm respectively under straight driving and steering conditions, and the deformation of stabilizer bar and torsion arm is 3.383 mm and 2.695 mm respectively. The strength test results show that, in the straight driving and steering conditions, the deformation of the steering point is 3.263 mm and 3.622 mm respectively, which are 11.59% and 6.19% higher than the simulation results. The deformation of the connection point of the stabilizer bar and the connection point of the torsion arm are 3.538 mm and 2.957 mm respectively. The experimental results are 4.58% and 9.72% higher than the simulation results respectively. The results show that there is no obvious difference between the experimental results and the simulation results, and the deformation of the subframe at each point conforms to the design. The fatigue test results of the subframe show that there are no cracks and plastic deformation in the subframe after 800 thousand torsion arm fatigue tests, 400 thousand braking force fatigue tests and 800 thousand lateral force fatigue tests, indicating that the fatigue characteristics of the subframe meet the requirements.

In order to construct a constitutive model that reasonably describes the changing relationship of flow stress of 440C stainless steel, quasi-static and dynamic compression experiments were carried out with the help of a universal testing machine and a Hopkinson compression bar device. Based on the obtained experimental data, the parameters of the original J-C constitutive model were calibrated, and its applicability and prediction accuracy for describing the stress-flow behavior of the studied materials were discussed. Based on the analysis results, a modified J-C constitutive model considering the coupling among strain, strain rate and temperature was proposed, and the model parameters were calibrated. The experimental data and the model predicted value were compared and analyzed, and the validity of the proposed model was evaluated by three statistical parameters: correlation coefficient R, average relative error AARE and root mean square deviation RMSE. The results show that the dynamic mechanical behavior of 440C stainless steel is jointly dominated by the coupling between strain, strain rate and temperature. The correlation coefficient R of the proposed modified J-C constitutive model is 0.995 9, the average relative error AARE is 0.073, and the root mean square deviation RMSE is 0.761 8, which can reasonably describe its stress flow behavior.

A two-degree-of-freedom collission vibration system model with nonlinear constraints and initial precompression is established. The hysteresis region and distribution of the system are studied by using the 4-order Runge-Kutta numerical algorithm and multi-parameter co-simulation method. The stability of the co-existing motions in the hysteresis region is analyzed by cell mapping method. Finally, the influence of the change of basic parameters on the hysteresis domain of the system is deeply studied. The results show that the stability of coexisting motion changes with the change of excitation frequency in hysteresis domain. The decrease of the elastic stiffness ratio will reduce the hysteretic frequency of the system.

Taking the seat vibration system of a certain type of engineering vehicle as an object, using the characteristics of adaptive network-based fuzzy inference system（ANFIS） self-learning and fuzzy reasoning, a semiactive control method of seat suspension vibration based on ANFIS was proposed, which solved the problem of excessive seat vibration in the working process of engineering vehicles. Firstly, the vibration process of the seat suspension of engineering vehicles was analyzed, and the dynamic model of the seat suspension was established. Then, the fuzzy neural control system of seat suspension was designed by adding feed-forward and feedback links. Finally, the control effects of different vibration excitation frequencies, different controller control objects and the input of measured seat signals were observed respectively. The results show that the fuzzy neural control system reduces the vibration energy and frequency of the seat, and the root mean square value of the seat vibration displacement is 52% to 66% of the passive suspension seat.

Aiming at the problem of fatigue life prediction of aluminum alloy wheel hub, a fatigue life prediction model considering damage accumulation is proposed and tested. The Finite Element Models of a wheel hub under bending fatigue test and radial fatigue test are established, and the main failure positions are studied by simulation analysis. The S-N curves of material and part are established by using the nominal stress method, and the average stress of the asymmetric cyclic load borne by the wheel hub is corrected by using the Morrow line. Considering the rotation process of the wheel hub, a theoretical model for predicting the fatigue life is constructed by using the linear cumulative damage theory. Taking an aluminum alloy wheel hub as an example, the life calculated by the theoretical model is 448.2 thousands revolutions. Compared with the fatigue life of 473.3 thousands revolutions given by the bending fatigue test, the error is about 5.6%, which verifies the effectiveness of the fatigue life prediction theoretical model.

The oil film temperature of the spherical hybrid sliding bearings would increase due to the friction and shear of the lubricating oil at high speed or super high speed, which leads to the thermal deformation of bearing and rotor. As a result, the deformation seriously affects the rotation accuracy of the spindle, because it is in the same order of magnitude as the oil film thickness. Therefore, the fluid lubrication mathematical model is established by taking the spherical hybrid sliding bearings with orifice throttling mode as the research object, and the Reynolds equation and energy equation of lubricating oil film are derived. The pressure distribution and temperature distribution of oil film of the spherical hybrid sliding bearings are calculated by combining the finite difference method and relaxation iteration method. The influence of working parameters on bearing capacity and oil film temperature rise was investigated. The results show that the oil film shear effect is stronger and the temperature rise increases with the increase of rotating speed and the decrease of oil film thickness. When the speed is 3 000 r/min and the oil film thickness is 28 μm, the maximum temperature rise of the bearing is 18.65 K higher than that of 1 000 r/min. When the speed is 3 000 r/min and the oil film thickness is 20 μm, the maximum temperature rise of the bearing is 27.685 K higher than that of the oil film thickness of 28 μm.

In order to meet the requirements of machining accuracy indexes such as the entry, exit and shape of micro-hole, a multi-objective parameter optimization weigh method for micro electrical discharge machining（EDM） based on grey relational analysis（GRA） and entropy weight method is proposed.By designing orthogonal experiment and processing test for H62 brass, the grey relational coefficient of each index of the experiment result sequence is calculated.The entropy weight method and grey relational analysis method are used to comprehensively evaluate the model, and the grey relational degree of each experiment sequence is obtained, and the mean value analysis is carried out to realize the transformation from multi-objective optimization to single objective optimization.The research results show that the entry Overcut（EnOV）, exit Overcut（ExOV） and taper（TA） of the optimized process parameters are reduced by 8.97%, 4.11% and 8.33% respectively compared with those of the H-22 group with the largest grey relational degree, and the machining accuracy of micropores is improved.

In view of the small number of data samples in the field test, a method of data expansion by using probability distribution and proxy model was proposed. This method determines the interval division and the number of sample points that need to be generated in each interval by analyzing the basic probability characteristics of the data. The sample points were generated based on the back propagation（BP） neural network method to build a semi-physical simulation system proxy model, and were selected by the histogram statistical method. Therefore, the additional sample points not only retain the probability characteristics of the original data, but also have the physical connotations. The expanded testing data improved the aircraft′s landing point coordinate information and the accuracy of the landing point data fusion model. The practicability and effectiveness of the method were verified through the field and semi-physical simulation experiments of the aircraft 534A respectively.

In order to solve the optimization design problem of complex shape of underwater glider and improve the optimization efficiency of Kriging surrogate model while improving its lift drag ratio, an adaptive surrogate optimal algorithm is proposed. The proposed improved parallel expectation improvement（PEI） criterion and probability of improvement（PI） criterion are used for global exploration, and the minimizing surrogate prediction（MSP） criterion is used for local exploration. The switching between global exploration and local exploration is realized according to the relationship between new sample points and known sample points. The proposed algorithm, the maximum expected improvement（EI） criterion multiple expectation of improvement（q-EI） and the improved probability improvement（IPI） are combined through a mathematical example. The result shows that the proposed algorithm converges faster and has higher accuracy. Finally, the optimal algorithm is used to optimize the shape of the underwater glider, and the maximum lift drag ratio is increased by 19.37%.

The accuracy of traditional milling force prediction model is low, and it is difficult to provide effective support for the reasonable selection of process parameters in practical production, by synthetically considering the equivalent turning force model of working angle, cutting edge arc and radius of tool tip arc, in this model, the actual turning tool is equivalent to the ideal turning tool model to identify the material constant, the chip flow angle and the average friction angle in the material constitutive equation, according to the oblique cutting model, the shear stress on the main shear plane and the F0 vector of the unit cutting force at different cutting speeds are calculated, thus the instantaneous cutting force on the front face of the end mill can be calculated, the three-dimensional cutting force of end mill in X-Y-Z coordinate system is obtained by coordinate transformation. The prediction of the cutting force model is verified by simulation and experiment.

In order to solve the problem of single design method of the existing guided anti-collision pad, the guided anti-collision pad is designed to meet the requirements of the current regulations, and based on the collision-resistant topology optimization method, by establishing the model of the car-anti-collision pad and topologically carrying out the topology optimization analysis under the condition of its positive encounter, from which to extract the basic configuration of the energy absorption unit, to the positive collision of the car center acceleration size as an evaluation index, the use of orthogonal design and robust design method to further optimize the size of the energy absorption unit, and finally obtain the optimal size of the energy absorption unit. The simulation results show that the design method based on collision resistance topology optimization is effective, and the TS-grade guided anti-collision pad is designed to meet the current requirements