The welded joints were susceptible to defects and stress concentration, rendering them vulnerable areas for fatigue crack initiation and propagation under fatigue loads. In comparison to homogeneous materials, the microstructure and stress localization in each of regions for the joints further complicated the fatigue issue in welded structures. Unlike ideal experimental conditions, the actual service environments of welded structures were intricate, it was necessity to consider the coupling characteristics between environmental factors and welded structures when predicting welded structure fatigue life. Therefore, the internal factors influencing welded structures were summarized and analyzed while reviewing existing life prediction models from perspectives encompassing complex loads and extreme service environment. Combining the latest research progresses, the recommendations were proposed to enhance fatigue life assessment methods for the welded structures.

The theoretical system of intelligent manufacturing for HCPS confirmed the central position of human in the intelligent manufacturing system. Starting from the demand of human-machine collaboration in the intelligent manufacturing system, the emphases of human factors in HCIM were discussed from three levels such as behavior, intention, and cognition, based on the theory of gulf. Focusing on virtual-real fusion scenarios, multimodal human-machine interaction, cognitive quantification and other methods, the importance of human factor engineering in promoting the integration of human-computer intelligence was expounded. Finally, research direction and development suggestions of human-centered intelligent manufacturing from the implementation of HCPS intelligent manufacturing systems were put forward.

The pace of large wind turbine units was accelerating, and the reliability of core components was increasingly important for wind turbine operations. Sliding bearings had the advantages of high load capacity, long life, easy maintenance, scalability and small size, and they had advantages and great potential for the reliable replacement of wind turbine main bearings key components produced at home. The problems of main shaft rolling bearings in high-power wind turbines and the advantages of using sliding bearings on the main shaft were analyzed herein. The technical methods and application status of wind turbine main shaft sliding bearing design, materials, lubrication, and experimental verification were present in detail, and the existing problems of high-power wind turbine main shaft sliding bearings and future development trends were summarized. It is expected to provide reference for the digital design and industrial development of high-power wind turbine main bearings.

To solve the problem that it was difficult to obtain a large number of high-quality rolling bearing fault data in the actual industrial environment， and the generalization performance of the intelligent diagnosis model was poor， a fault diagnosis method was proposed based on simulation data driven and domain adaptation. Firstly， a physical model was established to obtain rich simulation data， which simulated different failure forms of bearings according to bearing parameters and corresponding operating conditions. Secondly， the transfer learning method was used to solve the problem of inconsistent data feature distributions between simulation and actual fault data. The residual channel attention mechanism network was used to extract the transfer fault features of different domains， and the adaptive operation of different domains in the network training processes was carried out through the condition maximum mean discrepancy metric criterion， which taken into account the conditional distribution discrepancies between different domains. Finally， different transfer model tests were carried out on the bearing data sets damaged by man-made damage and accelerated life test. The results show that the method proposed may obtain better recognition accuracy when the target domain contains a small number of labels. 

 The reliability analysis results of complex structures based on the Kriging model were highly dependent on the fitting accuracy of the Kriging model. In the constructing processes of the Kriging model, the selection of different correlation and regression functions affected the accuracy of the model. In order to solve the impacts of model uncertainty on the reliability analysis results, while considering computational efficiency and accuracy, based on the Kriging model and Monte Carlo simulation(MCS) method, a structural reliability calculation method combining adaptive ensemble strategy and active learning function was proposed. Considering the modeling uncertainty of Kriging models, combined with multiple Kriging models, this methed constructed an active learning function that comprehensively considered sample point contribution and sample point distance. The ensemble Kriging model was iteratively updated through the active learning function until the convergence conditions were satisfied. Finally the structural reliability analysis was carried out by the constructed ensemble Kriging model and MCS method. The validity of the proposed method was verified by numerical and engineering examples, and the results show that the proposed method is more robust than other major methods, and the computational efficiency is higher while ensuring the computational accuracy.

Aiming at the hybrid flow-shop scheduling problems, an adaptive genetic algorithm with ITPX was proposed. Firstly, the solution performance of two-points crossover（TPX） was improved by exacting point taking method. Secondly, adaptive selection probability was demonstrated based on hormonal regulation guiding convergence trend of populations. Then, a pool of high-quality chromosomes and a memory factor were established to record the high-quality chromosomes during population evolution, and two different regional crossovers were implemented. Experimentsal results show that ITPX may save optimization time and improve solution performance; the adaptive probability may enhance convergence; ITPX-IAGA may reduce solution time by more than 40% and improve solution performance.

In the intelligent photovoltaic tracker brackets， cold-formed purlins were used to support the photovoltaic panels， and located spannig the horizontal single-axis and the module frame. Firstly， the minimum compliance of the structures was taken as the target and relative densities of elements were taken as the design variables， and the topology optimum design models were constructed under the given volume and the first natural frequency constraints. Optimal material distributions of the purlins were obtained based on SIMP (solid isotropic material with penalization) method， and this topology optimization structure was engineering designed and manufactured. Then， test load conditions were designed according to the practical environment where the photovoltaic tracker brackets were applied under different wind loads. The static and dynamic finite element analyses of the original and optimized purlins were carried out respectively， the simulation results show that the optimized purlins are improved in terms of bending resistance， torsion resistance， and natural frequency. Thus， the effectiveness of the optimization design method is verified. After that， the optimal purlins whose mass is reduced by 8.8% were also manufactured by engineering methods， and the mechanics performances were verified by the experiments. 

Aiming at the large deviations between the actual paths and the predetermined ones of underwater gliders affected by ocean current, a neural network ocean current prediction model with long-term and short-term memory and attention mechanism was established based on the traditional long-term and short-term memory network model.The dynamic Q-table of underwater glider motions was generated by depth neural network, and the optimal motion attitude was selected by reinforcement learning algorithm. Considering the influences of ocean current, an underwater glider path tracking algorithm was constructed based on depth reinforcement learning. The results show that the long-term and short-term memory network based on attention mechanism has less mean square errors and root mean square errors in ocean current prediction than that of the traditional integrated moving average autoregressive model and long-term and short-term memory network.Compared with the traditional PID control, the deep reinforcement learning model may reduce the root mean square errors of the underwater glider trajectory by 50.9%, and significantly improve the path tracking accuracy.

Aiming at distributed flexible assembly job-shop environments, the machine selection flexibility, worker scheduling flexibility, and process sequence flexibility in scheduling were comprehensively considered, and a model of DMFAJSP was constructed taking minimizing the makespan and minimizing the total energy consumption as optimization objectives. To solve the DMFAJSP model, MDMA was proposed using estimation of distribution algorithm as the global search component and the neighborhood search operators as the local search component. Finally, comparative experiments were conducted between the proposed algorithm and other algorithms, and the results show that the MDMA has significant advantages in solving DMFAJSP model.

In order to solve the problems of product consistency and low production efficiency caused by manually reinforced carbon/carbon crucible preforms， a flexible winding forming system of carbon fiber reinforced crucible preform was proposed. The line type design process of crucible core die for special rotary body structure with one end plane head and one end ellipsoid head was presented based on the non-geodesic method. Each module and implementation method of computer aided line type design were introduced， and the design line type was simulated. A special winding machine with four degrees of freedom was designed according to the winding characteristics. The control system of four-axis winding machine was designed based on programmable controller and touch screen， and the winding tests were carried out. It is indicated that the winding machine runs stably and the fiber may be wound continuously and stably on the surfaces of the core die， and the system may realize automatic winding of carbon fiber reinforced carbon/carbon crucible preforms. 

FISH technology was a common method to detect the nucleic acid sequence of malignant tumor cells. It was widely used in the field of cancer diagnoses and treatments. In order to realize the full automation of FISH experiments, a full-automatic pathological staining system was designed, which was provided with multi axis control arm, reagent sampler, slide, cover slide fixture, auxiliary module and so on. The positioning erorrs of the multi axis control arm are less than ±0.1 mm, the accuracy of extracting and discarding the pipette head is more than 99.5%, the success rate of extracting the cover glass is more than 99%, and the erorrs of micro reagent sampling are less than 0.6 μL. The errors of adding a large amount of reagent are less than 0.5 mL, the temperature control erorrs of slide clamp are less than ±1 ℃, and there is no reagent leakage. The results of biological experiments show that the system has good fluorescence staining effectiveness, the signal points are clearly visible, and the interpretable rate of fluorescence image is more than 90%.

To investigate the plastic deformation behaviors and martensitic transformation rules of 0.5 mm thick 304 stainless steels at room temperature, uniaxial tensile tests were conducted at five different strain rates of 0.000 67 s-1, 0.002 s-1, 0.01 s-1, 0.1 s-1 and 1.0 s-1, with subsequent X-ray diffraction(XRD) analysis for phase analysis. The results reveal a notable increase in yield strength with rising strain rate, indicating strain rate strengthening effects. Additionally, due to plastic work converting into heat during tensile processes, martensitic transformation was inhibited, resulting in a slight tensile strength reduction. Below a true strain of 0.27, work hardening rates decrease under varying strain rates. However, beyond this threshold true strain, significant secondary hardening occurs under low strain rates, which is attributed to the internal martensitic transformation.To address this phenomenon, the Olson-Cohen equation was integrated into the traditional Johnson-Cook model to characterize secondary hardening during tensile processes across different strain rates. The improved Johnson-Cook model achieves high accuracy in predicting rheological stress changes, with deviations of 3.23%, 3.42%, 4.13%, 4.09%, and 5.14% respectively compared to experimental values, effectively capturing the secondary hardening stage at various strain rates.

Aiming at the flexible job shop scheduling problems under the mode of multi variety and small batch production, an intelligent scheduling method was proposed to minimize the total tardiness of orders based on combination rules and reinforcement learning. Transforming the flexible job shop production scheduling problem into a Markov decision process, according to the characteristics and optimization objectives of the problems, seven features were used to represent the workshop states, and six combination rules were designed as an action library. The problem was solved by using the improved DQN algorithm. Taking the aerospace structural parts machining workshop as a case study, the feasibility and effectiveness of the proposed method in shortening task delivery time are verified by comparing with other common rule-based methods in five different scale calculation examples.

Slip oil pumps often needed to operate stably at high altitude and under low pressure conditions, which often led to cause problems such as insufficient oil supply and reduced efficiency. In order to get the best performance of the pump to meet the design requirements, this paper taken the impeller of a helicopter oil pump as the research object and to optimise the structure. The efficiency and lift of two typical working conditions at high altitude were selected as the optimisation targets, and the NSGA-Ⅱ was used to optimise the geometric parameters of the oil pump impellers, and the efficiency and lift of the oil pump before and after the optimisation were compared and analysed. CFD fluid simulation and experimental methods were used to verify the optimisation results. The results show that: the selected optimization parameters have a greater impact on the performance of the slip oil pumps, near the optimized slip oil pump vane positions the flow is more smooth, the high and low pressure areas of the excessively smooth, the energy loss is smaller, and the possibility of cavitation is reduced. The optimized slip oil pump design point lift increases 2.6 m, the efficiency increases 2.86%.

 The vehicle would produce load transfer during acceleration and hill climbing， which led to the interference of tire pressure monitoring results. To address this problem， a tire pressure monitoring result compensation correction method was proposed based on tire loads herein. Dual estimation of vehicle mass and center of mass position was carried out based on Dual-UKF， and recursive least square (RLS) was used for slope identification. The data of load， vehicle speed， tire pressure and tire sinkage were collected by using a tire rotation hub test bench. The relational expression of load, speed, tire pressure and tire sinking were obtained by fitting the data. Using slope identification， the four-wheel independent load was calculated by estimating the vehicle mass and center of mass position to correct the corresponding wheel speed pulse. The test results show that the calculated values of tire pressure without load correction have 20% stable error and large fluctuation. with load correction， although there is a certain hysteresis and fluctuation， it will eventually converge to the true value quickly and the stable error is within 5%， which solves the problem of inaccurate tire pressure estimation due to load changes. 

There were many calibration errors in complex visual measurement systems， and the coupling between errors directly affected the accuracy of system measurement， so the accuracy improvelment of system calibration parameters was the key to ensure the system measurement accuracy. Thus， a calibration parameter optimization method was proposed based on multi-dimensional angular point error compensation. Firstly， a multi-dimensional angular point error function was defined， and the corresponding optimization model whose parameters were solved by LM algorithm was established. Then， the effects of the parameter optimization method on the system calibration optimization were evaluated by the optimization rate of the system calibration errors. Experimental results show that the optimization rate of the system calibration errors may reach 48%， the system measurement accuracy is high and meets the measurement requirements. 

The rapid advancement of topology optimization and additive manufacturing technology provided efficient methods for designing and manufacturing high-performance complex equipment. However, current topology optimization techniques for high-performance structures only considered the design of thermal-mechanics coupling or fluid-thermal coupling, and were mostly limited to simple structures. The design under the combined effects of fluid-thermal-mechanics fields was not considered, which restricted the enhancement of structural performance. This paper tackled the challenge of designing high-performance complex structures under multi-physics fields, encompassing fluid-thermal-mechanics interactions. A topology optimization method was proposed to enhance the ability to withstand temperature of intricate structures. Firstly, the governing equations of flow field, temperature field and structural displacement field were introduced to provide a unified description of the fluid-solid materials within the computational domain. Secondly, the topology optimization model was formulated with fluid-thermal-mechanics coupling. The objective function was set to minimize the average temperature, while flow energy dissipation and structural compliance served as constraint functions. Sensitivity analysis of design variables was carried out by using a combination of the variational method and Lagrangian function. Finally, the established topology optimization model was applied to the structural design of a turbine, resulting in a structure suitable for additive manufacturing with excellent heat dissipation performance and well-balanced flow channel distribution.

Aiming at the problems that, based on data statistical characteristics, the classification and recognition method of driving style was easy to ignore the diversity of driving style during driving, a classification and recognition method of driving style was proposed based on driving events, spectral clustering and random forest. Experiments were designed to collect driving data, and the data were preprocessed to extract turning events and braking events. After standardization and dimensionality reduction, the spectral clustering algorithm was used to cluster the driving style of turning events and braking events respectively. The entropy weight method was used to obtain the driving style weights of each driver, and the accuracy of five machine learning algorithms was compared for driving style recognition. Results show that the accuracy of driving style recognition is as 92.73% based on random forest, which significantly improves the accuracy of driving style recognition.

 In response to the problems of low transmission efficiency, high power consumption, poor performance in heavy load starting, and asynchronous operations of multiple motors in the traditional asynchronous motor driving system of belt conveyors in coal mines, a multi-motor permanent magnet direct driving belt conveyor was proposed based on the fuzzy active disturbance rejection deviation coupling control strategy. Then, the simulation tests of fuzzy active disturbance rejection deviation coupling control strategy and the on-site industrial tests of underground transportation groove belt conveyor were carried out, and the results show that compared with traditional master-slave control, the multi motor permanent magnet direct driving system of the belt conveyors based on fuzzy PI active disturbance rejection deviation coupling control strategy has a maximum speed difference of only 0.04% among multi motors under rated loads, and a maximum synchronization performance improvement of 99.7%. In the on-site dynamic coal dropping tests, the maximum asynchronous speed is only 2%, which may meet the zero speed heavy load starting requirements of long distance and heavy duty belt conveyors, significantly improving the synchronization performance and anti-interference ability of the multi motor driving system of belt conveyor.

In order to improve the measurement efficiency and accuracy of the overall blisk by CMM and to solve the problems that large-sized blisk exceeded the measuring range of measuring machine, a six-axis measurement system was constructed based on CMM and a high-precision turntable. According to the principle of space coordinate transformation, a mathematical model of the turntable coordinate system and the blisk workpiece coordinate system were established. A space error compensation method was proposed after the coordinate systems of different blades of the blisk rotated with the turntable. Test results show that the measurement efficiency increases by 28.22% on average under the premise of ensuring that the measurement accuracy of each blade profile parameter meets the process requirements. Compared with the measurement data without the turntable, the new six-axis measurement system measures the horizontal blisk blade profile, and the profile comparison errors are almost all within 0.008 mm. The maximum comparison error is less than 0.015 mm, which is smaller and more stable than the measurement errors of the inclined blisk.

 Sediment penetration test was an important in-situ testing technique for deep-sea sediment strength. In view of the extreme environmental characteristics of the 7000 meter deep sea and the scientific demands for fine in-situ measurement， a deep-sea non-contact strong magnetic sediment penetration strength in-situ measurement device was developed based on the Jiaolong manned submersible， which broke through the problem that the original penetration measurement techniques in the 7000 meter deep sea structure was complex and could not achieve in-situ and fine measurement， A new method of solving deep-sea pressure resistance and strain gauge deformation conduction was proposed based on the non-contact principle of permanent magnetic force balance conduction of manned submersible. The prototype development and deep-sea sea tests were completed， and good test results were obtained. The whole system adopted self-contained working mode to collect and store data， and might be connected with the computer to realize in-situ data reading. The operating water depth is as 7000 m， the maximum penetration depth is as 250 mm， the measuring range is as 0～100 kPa， and the accuracy may reach 5%~10% FS(full scale). In March 2021， the Jiaolong manned submersible completed 5200 m and 6650 m sea trials in 181 and 185 dives in the Parihivila basin， and successfully obtained geotechnical data. 

A dot matrix offshore wind turbine integrated foundation design scheme was established based on the concept of wind turbine integration. The overall structural parameters and mechanics model were analyzed， and the feasibility and advantages of the overall scheme of the new dot matrix foundation（DMF） were established. Combined with the traditional OC4 semi-submersible wind turbine system， the hydrodynamic simulation was carried out under wind wave current loads. Results show that the stability of DMF in pitch motion is 70% higher than that of the traditional OC4 system. The small-scale prototype processing of DMF and the simulation experiments of wind and wave trough were completed based on similarity theory. Experimental results are in good agreement with the simulation data. 

In order to improve the success rate of the preparation of monolithic micro tungsten ball tips, the high-voltage micro-arc was studied during the preparation processes. A multi-physics field coupled simulation model of tungsten-pole high-voltage micro-arc was established to calculate the arc temperature distribution at electrode spacing of 0.5~2.0 mm and voltage of 1~12 kV. The simulation results were then subjected to least-squares fitting, and a mathematical model between the arc temperature and the discharge parameters was obtained. Finally, the mathematical model was validated by building a spectral temperature measurement system based on the Boltzmann graphing method. The results show that the arc is elliptically distributed, and there is a high temperature barrier in the near-anode region, and the anode temperature is much lower than that of the cathode temperature. The arc temperature has a parabolic relationship with the voltage and electrode spacing. The average relative error between the model calculation results and the experimental results is as 3.3%. The model may be used to calculate the arc temperature for controlled preparation of the tungsten ball tips. 

From the perspective of the pedestrian-vehicle-environment system, the effects of pedestrian safety facility, AVs yielding behavior, approaching direction and eHMI on pedestrian-AV interaction were investigated. Based on a cave automatic virtual environment(CAVE) simulation platform, the Unity 3D software was utilized to design and develop the AVs driving scenario. Thirty-eight volunteers were recruited for the pedestrian-AV interaction experiments. During the experiments, the participants decision time, decision results and subjective experience were recorded and further statistically analyzed with survival analysis. The results indicate that with the presence of an AV in the traffic, pedestrian safety facility, AVs yielding behavior and eHMI may significantly shorten pedestrians decision time, enhance their interactive experience and improve traffic efficiency. However, the influences of pedestrian safety facility on pedestrians crossing decision and behavior exist from the earlier stage of the crossing gap, compared with AVs yielding behavior. Meanwhile, the efficacy and clarity of a light band-based eHMI are somewhat limited for conveying AVs yielding intention.

 Aiming at the problems that the standard unscented Kalman filter（UKF） localization algorithm could not meet the high-precision localization requirements of mobile robots when moved on uneven ground， an ARUKF localization algorithm was proposed based on robust estimation theory. The ARUKF adaptively adjusted the predicted value of UKF according to the dynamic residual， reduced the influences of external interference on the predicted values of the systems， improved the accuracy and robustness of the system， speeded up the operation by reducing the computational complexity of the sampling processes， and improved the real-time performance of the system. The simulation and field test results show that the ARUKF algorithm may converge faster for the disturbance generated by uneven ground， and have better accuracy， robustness， and real-time performance， compared with the UKF algorithm and the improved UKF algorithm based on Sage-Husa. The average distance error is less than 2 mm， and the average angle error is less than 0.016 rad， which may meet more stringent requirements of the construction site. 

Aiming at the overall design parameters and mission profile requirements of commuter aircrafts, according to the hydrogen-lithium propulsion system architecture scheme, the propulsion system parameter matching method and energy dynamic balance management strategy were proposed. A 19-seat commuter aircraft was used to select and manage the power plant and reserve energy. According to the selected distributed aerodynamic layout scheme, then the effects of propeller rotation directions on aircraft aerodynamic characteristics were analyzed with full factorial design of experiments, and the optimum propeller rotation direction configuration for aircraft cruise states was obtained.

In views of the coupling of structural parameters affecting different performance of high-pressure threaded plug-in relief valves, it was difficult to optimize the comprehensive performance, a multi-objective particle swarm optimization algorithm was proposed to optimize the comprehensive performance. Based on the structural characteristics of high-pressure threaded plug-in relief valves, the mathematical models of opening and closing characteristics, pressure regulation deviation and stability were established. Based on the first-order sensitivity analysis of the influences of structural parameters on the dynamic response, according to the mapping relationship between structure and performance, with the opening rate, pressure regulation deviation, stability and dynamic response performance improvement as the optimization objectives and coupling structure parameters as variables, a comprehensive performance optimization model was established, and the optimal solution of coupling structural parameters was obtained in the form of Pareto set by particle swarm optimization algorithm. The experimental results show that after optimization, the pressure oscillation of the high pressure threaded plug-in relief valves is reduced by 22.7%, the opening rate is increased by 1.5%, the pressure flow gradient is reduced by 14.58%, the pressure overreach in front of the valves is reduced by 14.1%, the response time is shortened by 9.52%.

To improve the accuracy of battery SOC estimation， a higher order EKF algorithm was used to estimate SOC. Firstly， the first-order Thevenin equivalent circuit model（ECM） of lithium-ion battery was established， and the function relationship between open circuit voltage（OCV） and SOC was expressed by spline function. In order to more accurately identify the ECM parameters， a new kind of with VFFRLS algorithm was proposed for on-line identification of model parameters. Since the accuracy of the VFFRLS solution depended on the setting of the initial values of the algorithm， the improved particle swarm optimization algorithm was used to obtain the initial parameters of ECM， which helped to obtain more accurate initial values of VFFRLS. Finally， the second-order EKF was employed to estimate the SOC of the batterys to improve the estimation accuracy. Two different datasets were used to demonstrate the universality of second-order EKF estimation SOC. The experimental results indicate that the mean absolute error（MAE） of second-order EKF is within 1% when estimating SOC under different working conditions， which proves the effectiveness of the proposed method. 

A UWB positioning algorithm was proposed based on neural networks and self-adjusting Kalman filters for improving the positioning accuracy of current a certain three-line automatic driving rail transport system vehicles. The UWB tags and base stations were used to collect large amount of distance information between tags and various base stations and collect the actual locations of the corresponding tags, and the neural network was trained. The distance information between the tags and various base stations was sent to the centralized control center server through the network during the real-time positioning stage, and the real-time locations of the UWB positioning tags were obtained by the optimized neural network. The self-adjusting Kalman filter was used to improve the accuracy of the real-time tag positions furtherly. A set of UWB tag moving trajectories containing inclines, straight paths, and curves were designed for simulation based on the actual vehicle operation, and a UWB positioning system was built, the moving trajectories of the tags were designed, the UWB positioning algorithm combining the neural network and self-adjusting Kalman filter was verified through experiments. The results show that the maximum positioning error of the positioning algorithm combining neural network and self-adjusting Kalman filter is as 223.58 mm, and the average positioning error is as 43.16 mm, and the root mean square value of the positioning errors is as 42.06 mm. The positioning algorithm proposed combining the neural network and self-adjusting Kalman filter has the advantages of higher accuracy, better real-time performance and stability compared with the three-point positioning algorithm, Kalman filtering algorithm, and neural network algorithm, and the current positioning requirements of the three-line rail transports may be fulfilled.

In response to the unmanned inspection requirements of mining wire ropes, a rope-twisting climbing inspection robot was designed and developed. Compared to traditional axial climbing robots, which required approximately 91.5% of the driving force. When carrying a load of 3 kg, the robot may overcome obstacles with a height 0.6 mm higher than that of axial climbing robots. With an obstacle height of 3 mm, the maximum load capacity exceeds that of axial climbing robots by 0.4 kg. Climbing experiments were conducted under simulated deep mine conditions with wire rope vibrations. The results show that the climbing robots exhibite stable climbing performance when the wire ropes are stationary, achieving a maximum climbing speed of 8.25 m/min and capable of continuous climbing for 500 m. Under low-frequency large-amplitude vibration conditions, the climbing speed of the robot is higher than that when stationary, while under high-frequency small-amplitude vibration conditions, slight fluctuations in climbing speed are observed due to wire rope vibrations.

The transmission system of heavy-duty vehicles had the characteristics of large speed ratio and large torque. The welded structures of transmission intermediate shafts carried complex working loads， and multiaxial fatigue failure was easy to occur at the weld seams. In order to evaluate the fatigue life more accurately and effectively， a fatigue life analysis method for the welded structures of transmission intermediate shafts of heavy-duty vehicles was proposed based on the multi-axial structural stress method. First， the finite element model with weld details for the welded structures of transmission intermediate shafts was built. Then， the time history of the structural stress components at the fatigue hazard points of the welds was solved， the load path was synthesized on the structural stress planes to obtain the equivalent stress range of the non-proportional loading path. Finally， the fatigue life was determined by combining the main S-N curve. This method was used to evaluate the fatigue life of the weld roots and weld toes of the welded structures of transmission intermediate shafts， and the results were compared with those of the fatigue bench tests. Results show that the predicted damage location and fatigue life are both in good agreement with the experiments， and the differences between the fatigue life of the weld roots and toes are consistent with the multi-axial fatigue test results in the existing literature， which indicating that the proposed multi-axial structural stress method is reliable for the fatigue life assessment of the welded structures of transmission intermediate shafts. 

In order to solve the problems of large minimum turning radius and inadequate steering maneuverability of Ackermann steering-based off-road vehicles， a road adaptive pivot steering control strategy was developed by taking advantages of the independent control of vehicle torque driven by in-wheel motors. A seven-degree-of-freedom pivot steering dynamics model was constructed to explain the evolution of the longitudinal and transverse coupled motion tire forces during pivot steering， and a quantitative model was established to quantify the pivot steering resistance moment and transverse sway moment with wheel slip rate and road adhesion coefficient. The desired trajectory of transverse sway angular velocity under different adhesion conditions was designed with steering power responsiveness as the optimization objective， and the safety threshold of each wheel slip rate was used as the stability constraint to reduce the steering center offset. The executive layer tracked the transverse angular velocity based on the model prediction algorithm， while the adaptive sliding mode controller was introduced to adjust the wheel slip rate to ensure the stability of the longitudinal and transverse motions. Simulation tests and real vehicle tests show that the developed pivot steering control strategy achieves accurate tracking of the desired pivot steering trajectory under high， medium and low adhesion surfaces， and limits the steering center offset to within 500 mm， which improves the pivot steering flexibility and lateral stability of the off-road vehicles and realizes "fast and stable" pivot steering. 

 The examines automatic fiber placement on point cloud surfaces was researched. The direct projection method with moving least-squares projection technique was proposed to project the initial path. A point cloud slicing method was improved to propose a point cloud projection slicing method. A cubic B-spline interpolation algorithm was used to generate initial paths by fitting projection points， and an equidistant offset algorithm for chord length subdivision projections was proposed. Based on stretching the path splines end， a boundary processing method was proposed to solve the problem that the offsetting paths could not reach the surface boundary. Finally， the algorithm was visualized by reverse engineering module of CATIA， and the systematic relationship between the path planning algorithm and the 3D modelling software was established. 

Based on parameter prediction， a RBF neural network adaptive control scheme was proposed for the motion control problems of autonomous electric vehicles with uncertainties. Firstly, the influences of system parameter uncertainties and external interferences were considered, and a dynamic model which might reflect the tracking and following behaviors of vehicles was established by the preview method. Secondly, RBF neural network compensator was adopted to compensate system uncertainties adaptively, and a generalized coordinated control law was designed for the lateral and longitudinal motions of vehicles. Thirdly, the impacts from the front vehicle speeds and road curvatures were taken into account, and the minimization of the energy consumption and the average jerks in the tracking and following control processes were regarded as the optimization objects. Afterwards, PSO algorithm was utilized to rolling optimize the gain parameter K in the coordinated control law, and then a series of optimized sample data were obtained. Then, to ensure the economy and ride comfort of vehicles, a BP neural network was designed and trained to realize the real-time prediction of gain parameter K in the generalized coordinated control law. Simulation results validate the effectiveness of the proposed control scheme.

 Gear geometry and meshing properties of the low-angle face gear drives were investigated in order to enhance meshing capabilities of the gear drives with small shaft angle in helicopter transmission systems. The applied coordinate systems for generation of the low-angle face gear drive were established and the equation of the tooth surface of the small cone angel face gear was derived based on gear meshing theory. The tooth surface equation of a double-crowned cylindrical involute pinion was deduced by application of a generating worm.  The generated double-crowned pinion was then introduced into the low-angle face gear drive. The TCA was implemented and the influences of misalignments on the contact were researched. Stress analysis was performed for the purpose of evaluating the performance of the proposed face gear drives. And the stresses of the low-angle face gear drive were compared with the conical involute gear and cylindrical involute gear pair. The results show that the application of double-crowned pinion avoids edge contact， providing lower contact and bending stresses compared with the face-gear drive with a longitudinal modification pinion. Under the same conditions， the contact and bending stresses of the tapered face gear are 27% decrease than that of the conical involute gears. 

As a key weak link of oil and gas pipelines， the girth weld of high-grade steel pipeline was always concerned by the engineering and scientific research communities.  As a typical welding structure， the welds had obvious heterogeneity， which led to the inability to accurately test the axial mechanics properties of girth weld materials， which seriously affected the accuracy of safety evaluation of pipeline girth welds.  Based on MATLAB-PYTHON-ABAQUS co-simulation， an optimization inversion method of the material stress-strain constitutive relationship was proposed in the weld zones for the high-grade steel pipelines.  Four groups of uniaxial tensile tests with different notch sizes were carried out， and the load-displacement curves of each sample were obtained.  The true stress-strain constitutive relationship of the weld zone materials was obtained by BRBP neural network and GWO， and the accuracy of the constitutive relationship was fully verified by the testing data， the results show that the relative error is less than 1%.  The inversion method proposed is also suitable for the determination of stress-strain curves of homogeneous metal materials in large strain ranges.  The inversion method may provide accurate stress-strain constitutive relationship and strength matching relationship for the safety evaluation of girth welds of high-grade steel pipelines， and further ensure the safe operation of oil and gas pipelines. 

 Large-scale deformation monitoring of allomorphic aircrafts in the flight processes was a research difficulty and hot spot in the aerospace field， and the existing methods were difficult to achieve high-precision three-dimensional deformation monitoring during the flight of the aircrafts. Aiming at this problem， a flexible skin-shaped fiber reconstruction method for a variant aircraft was proposed based on optical fiber sensing to achieve deformation monitoring during flight of the aircrafts. Based on the principle of fiber grating strain sensing， the relationship between fiber strain and curvature was derived， the conversion matrix between the local coordinate system and the global coordinate system of optical fiber sensing was established， the conversion of fiber measurement point coordinates to the global coordinate system was realized， and the three-dimensional deformation reconstruction algorithm was studied based on curve fitting according to the spatial curve fitting method. At the same time， in order to reduce the measurement errors of the fiber optic sensors， the calibration tests of the fiber optic sensors were carried out to obtain the strain sensitivity of the sensors. In order to verify the effectiveness of the proposed method， the three-dimensional deformation reconstruction of flexible skin samples under different curvatures was tested experimentally. Experimental results show that the average error of the shape reconstruction method is as 3.5% and the minimum error is less than 2.1% in the deformation ranges of 0～15.38 m-1 curvature of flexible skin samples. The proposed method has a good application prospect in aerospace and other fields. 

A novel bio-syncretic hip exoskeleton with large-angle and weak-coupling characteristics was proposed to solve the problems such as small workspace， difficult forward kinematics modeling， and complex control of parallel hip exoskeletons. The detailed structures of two-stage prismatic joint were designed， and the expression for calculating the slope of the groove was obtained. The man-machine complexs forward and inverse position solutions were derived by closing-vector-circle method. The inverse Jacobian matrix was obtained by taking the derivative of the inverse position solution equation. Performance analysis shows that the man-machine complex has the advantages such as large range motion， no internal singularities， good force transfer performance， and easy control.

 To address the problems that the effective sound absorption bandwidth of conventional micro-perforated panels was too narrow in the middle and low frequencies, a UMPP constructed lightweight structure was proposed. A theoretical model of sound absorption based on the micro-perforated plate theory and a high-fidelity finite element model were established, and an acoustic impedance tube-based sound absorption test system was built. The sound absorption characteristics of single-layer, double-layer, and triple-layer UMPP sound absorbing structure were investigated. Results show that the single-layer UMPP sound absorbing structure has a better sound absorption bandwidth, but there are obvious sound absorption valleys. The sound absorption mechanism was revealed from the perspective of normalized acoustic resistance and normalized acoustic reactance. To further improve the sound absorption performance of the proposed UMPP structures, a structural optimization design strategy was proposed to realize effective sound absorption in the sub-wavelength scale(1/8 wavelength) with a wide frequency range of 369~7000 Hz.

 An optimization method of integrated casting structures was constructed systematically, and based on the super-element model of body system, body casting part lightweight improving with multi-performance constraints was realized. Firstly, complex body systems were reduced, the sub-system division principle and method were proposed for continuous body structure. Super-element reduction of the sub-system was conducted to ensure analysis accuracy and improve calculation efficiency, laying the foundation for rapid optimization. Secondly, performances of casting structures and body systems were considered simultaneously, the compromise programming methods were used to normalize static and dynamic sub-targets and construct the comprehensive objective function, weight coefficients of sub-targets were obtained by analytic hierarchy process(AHP), and then multi-model topology optimization was carried out to determine position distribution of reinforcements. Furthermore, designability and manufacturability were considered simultaneously, parametric definition of variable thickness drawing surface of casting structure was carried out, manufacturing constraints were applied during optimization processes, and then thickness parameter design was completed based on combined surrogate model. The results show that, under the premise of ensuring the analysis accuracy, reduced body system models improve computing efficiency greatly, and save 97.3% of computing resources. Casting triangular beam lightweight may be achieved while improving related performance by conducting structure optimization, which indicates correctness and practicability of the proposed method.