In order to solve the problem of difficulty in testing and performance verification of compliant mechanisms in the process of optimal design, the mechanical properties of thermoplastic polyurethane (TPU) material were studied by 3D printing technology. The effects of material hardness and print fill rate on the mechanical properties of TPU material were analyzed, and the better 3D printing parameters of TPU material were obtained. Using single factor and two factor tset combined with variance analysis, the primary and secondary factors that significantly affect the flexibility of TPU specimens were identified as TPU material hardness and print fill rate. Combined with the mechanical property test data of TPU material, the mapping relationships between the material parameters and material hardness, print fill rate of four commonly used hyperelastic material constitutive models, i.e. Mooney-Rivlin, Yeoh, Ogden and Valanis-Landel, were obtained. The results showed that with the increase of TPU material hardness and print fill rate, the flexibility of the specimens decreased; among the four hyperelastic models, Ogden model has a good prediction effect on the mechanical properties of TPU specimens under different printing parameters; there was no significant difference in the predictive effect of the four models under the same TPU material hardness and different print fill rates. The research results can provide reference for 3D printing and finite element simulation analysis of TPU material, and provide reliable technical support for the test, performance verification and sample production of compliant mechanisms in the design process.

In order to improve the folding rate and support performance of deployable mechanisms, a scissor deployable mechanism with variable Poisson motion characteristics is proposed and its kinematics analysis is conducted. Firstly, a thick panel support unit with single-closed-loop was proposed and applied to sandwich structures. Through analyzing the influence of different shape sandwich layers on the support stiffness of sandwich structure by using ANSYS Workbench software, it was found that the sandwich structure with thick plate support unit had better support effect and smaller mass, and the positive and negative Poisson' ratio could be switched by changing the structural design parameters. Secondly, according to the definition of Poisson' ratio, a regular n-sided scissor deployable mechanism with variable Poisson motion characteristics was designed. Based on the screw theory, the screw constraint topology graph of the closed-loop deployable mechanism was drawn to analyze its degree of freedom as 1. The deployable mechanism was divided into three modules, and the principle and process of modular longitudinal expansion were described. Finally, the kinematics model of the m-layer regular n-sided scissor deployable mechanism was established and the prototype of the regular quadrilateral scissor deployable support structure was set up to further verify the variable Poisson motion characteristics of the mechanism, which could provide a theoretical basis for the follw-up research.

With the gradual shift of oil and gas exploration to deep, ultra-deep and complex rock formations, the existing mechanical drill bits have the problems of low rock breaking efficiency and high operating cost. Therefore, a new type of laser-PDC (polycrystalline diamond compact) drill bit was proposed to achieve efficient rock-breaking and energy-saving and cost-reducing. Using finite element method and based on the HJC (Holmquist-Johnson-Cook) constitutive model of rock, a nonlinear dynamic model of laser-PDC drill bit joint rock-breaking was established, and simulation research on laser-PDC drill bit joint rock-breaking was conducted. The simulation results showed that the radiation effect of laser generated higher temperature and greater prestress in the radiated area of rock surface, which in turn formed interpenetrating damage zones on the rock surface, reduced the strength of the rock, and was more conducive to cutting teeth to break the rock; compared with non-laser single PDC drill bit, laser-PDC drill bit experienced a 24.8% reduction in anti-torque during rock breaking, a 10.5% reduction in axial acceleration fluctuation, an increase in drilling displacement of 8.67 mm, and an increase in drilling speed of 112.79%. A laser-mechanical joint rock-breaking experimental bench was built to conduct laser-PDC drill bit joint rock-breaking experiment. The experimental results showed that laser-PDC drill bit joint rock-breaking had better drilling stability and continuity, greatly improving the rock-breaking efficiency. The research results can provide theoretical and technical support for the development and application of laser-mechanical rock-breaking technology.

Multi-functional small robots have broad application prospects. To meet different operational requirements, a small land-air deformable amphibious robot was designed, which could achieve efficient ground movement and avoid obstacles through takeoff flight. The robot adopted a dual-mode design, in which the ground mode adopted a two-wheel drive motion design, and the airplane mode adopted a four-rotor flight design. The switching between the two modes was realized through the support and extension of the robot tilting mechanism. In order to verify the motion performance of the robot, the whole robot model was established by SolidWorks software, the kinematics modeling for the robot was carried out, and the kinematics equation of the robot mode switching process was derived. Then, the robot servo output was simulated by MATLAB and the robot prototype mode switching experiment was carried out. The simulation results of the output torque were basically consistent with the measured results, with a range of 0-250 N·cm. Finally, the robot prototype was used to conduct ground movement and air flight tests, and its motion process was analyzed to verify the stability of the land-air motion and mode switching of the robot. The research results verify the effectiveness of the designed robot, and it has a long endurance, which can provide a reference for the design of land-air amphibious robots.

Aiming at the problems of poor forming quality and long printing time of concrete 3D printing components, a path planning algorithm based on continuous vertex partitioning was proposed. Firstly, the continuous vertex partitioning method based on Hamiltonian circuit was used to divide the print area into several continuous regions to ensure that the print nozzle would not pass the same vertex many times during the printing process, thus avoiding the problem of repeated printing and poor forming quality. Then, the genetic algorithm was used to search each region, and the shortest printing path was determined through iteration and optimization. The experimental results showed that compared with other path planning algorithms, the proposed algorithm could significantly reduce the empty travel and start-stop times of the print nozzle, and shorten the printing time by more than 10%, which effectively improved the forming quality and printing efficiency for concrete components. The concrete 3D printing path planning algorithm based on continuous vertex partitioning solves the problems of poor forming quality and long printing time of concrete components by effectively dividing the print area, intelligentiy searching the shortest path and combining the optimal path, which can provide strong technical support for the development and application of concrete 3D printing technology.

In the current civil aircraft cabin door operation panel design, there is a lack of unified standards and specifications for human-machine efficacy and interface design, and the design process overly relies on personal experience and personal preferences, resulting in poor human-machine efficacy of the designed operation panel during use. For this purpose, the design principles for the display and operation of the civil aircraft cabin door operation panel were discussed based on the ergonomics principle, and a design scheme of centralized cabin door operation panel and regional control panel was proposed. Firstly, the information organization, coding, display elements and display forms of the cabin door operation panel were determined through questionnaire survey. Then, the three-dimensional models of the cabin door operation panel, the regional control panel and the aircraft were conducted. Finally, the ergonomics simulation software DELMIA was used to conduct dynamic operation simulation on the layout, key size and touch area of the operation panel. The simulation results showed that the designed cabin door operation panel could enhance the human-machine efficacy, improve the safety and efficiency of the operation, and reduce the misoperation and workload of flight attendants. The designed operation panel and regional control panel not only realize centralized monitoring and management and regional actuation control for the entire cabin door, but also can be used as a human-machine interaction device, which is suitable for the cabin and cargo hold of large-sized wide-body aircraft in the future, and has a very broad application prospect.

In order to further improve the response speed and lightweight extent of piezoelectric wavefront correctors, the dynamics simulation and optimization method of unimorph piezoelectric deformable mirrors for high dynamic shape control was studied. Firstly, based on the parameterized finite element model of unimorph piezoelectric deformable mirror, an efficient and high-precision electromechanical coupling dynamics simulation analysis method was proposed. Then, through orthogonal traversal of multi-dimensional design parameters (material type, geometric dimension and fixation mode of the optical reflector and piezoelectric ceramic), the influence of different parameters on the dynamic shape control performance of unimorph piezoelectric deformable mirrors was explored. Finally, the optimized design scheme of the unimorph piezoelectric deformable mirror with expected response bandwidth and actuation displacement performance was obtained. The experimental results show that the natural frequency and mirror actuation displacement amplitude of the developed unimorph piezoelectric deformable mirror are in line with expectations, which verifies the effectiveness of the proposed dynamics simulation and optimization method and provides a scientific theoretical method for the efficient development of high-bandwidth unimorph piezoelectric deformable mirrors.

In extremely harsh working environments such as strong impacts, intense radiation and extremely high temperature, the fault modes of mechanical equipment are complex and varied, and it is very difficult to obtain sufficient and effective fault data, even difficult to achieve, so that the accuracy of fault diagnosis is limited, and subsequent maintenance and repair programs are difficult to be effectively developed.To solve this problem, a data enhancement algorithm for multi-discriminator auxiliary classifier generative adversarial network was proposed. By setting up 3 discriminators, 1 generator and adding independent classifier, a new auxiliary classifier generative adversarial network model was constructed. Aiming at the instability issue in the model's training, the Wasserstein distance was introduced to construct a new loss function, and the unilateral soft constraint regularization term with more stability was used to replace the original L2 gradient penalty term to solve the problem of model collapse. Building on this, an efficient channel attention mechanism was adopted to further improve the model's feature extraction capability. The proposed model was applied to extend the fault data set of mechanical equipment to assist the training of deep learning intelligent diagnosis model. Multiple fault data set expansion experiments showed that compared with the existing model, the new model could generate higher quality data, and the accuracy of fault diagnosis was further improved, so it had high application value.

The impact load is an important factor in the structural design of aerospace equipment. The design of thin-walled structures with high load-bearing capacity and good energy-absorbing characteristics is a research focus. Based on Voronoi algorithm, the pseudo-random arrangement of structure similar to honeycomb hexagon was developed by combining the structural characteristics of bone and honeycomb. According to the arrangement of loose inside and tight outside of the bone, a new type of impact resistant structure was constructed by partition design.The impact resistance simulation of bio-inspired thin-walled structure and uniform honeycomb structure of laser selective melted titanium alloy and laser selective sintered carbon fiber/PEEK (polyether ether ketone) composites was conducted to compare the energy-absorbing characteristics of the two kinds of structure. The simulation results showed that the maximum energy-absorption of the bio-inspired thin-walled structure of laser selective melting titanium alloy and laser selective sintered carbon fiber/PEEK composites was increased by 17.7% and 27.7% respectively, compared with the uniform honeycomb structure under axial impact, and the maximum energy-absorption was increased by 422.6% and 99.2% respectively under lateral impact.The bio-inspired thin-walled structure designed has important application prospects in aerospace field.

Aiming at the key issues in the overall development of snakelike robots, including material selection, structure design and motion realization, a new multi-joint snakelike robot was developed. This snakelike robot was composed of 11 two-degree-of-freedom orthogonal joints, which could achieve three-dimensional high biomimetic motion while ensuring flexibility. The basic gaits of snakelike robot such as meandering, wriggling and tumbling were designed by using the serpentine curve, and an improved obstacle surmounting gait was further proposed. At the same time, the gaits of the snakelike robot were simulated in the V-REP software, and the motion trajectories and efficiency of different gaits were compared. Finally, through the gait experiment of the snakelike robot prototype, the influence of each control parameter in the gait model on the motion waveform and speed of the snakelike robot was analyzed, and the reliability of the body structure and control system of the snakelike robot was verified. The research results have important theoretical significance and practical guiding value for realizing the gait planning and motion control of snakelike robots.

The container reach stacker (hereinafter referred to as reach stacker) plays a crucial role in practical port operations. With the increasing attention of society to energy and environmental issues, the electrification trend of reach stackers is becoming more and more significant, and the number of electric reach stackers on the market has been steadily rising year by year. The electric energy consumption performance directly affects endurance capacity, working efficiency and working cost of electric reach stackers, which is one of the important performance of electric reach stackers. Various factors such as driving behavior, operation conditions and equipment malfunctions will have diverse effects on the energy consumption of electric reach stackers. Therefor, by collecting the actual operating data of the customer side of electric reach stackers and based on the LightGBM (light gradient boosting machine) model, the energy consumption modeling for the driving and operational processes of electric reach stackers was conducted at the micro and macro levels, respectively. The SHAP (Shapley additive explanations) theory was used to quantitatively analyze the impact of different operation conditions and behaviors on the energy consumption of reach stackers, while simultaneously identifying energy consumption anomalies caused by equipment malfunctions. The results show that the energy consumption model based on SHAP-LightGBM can accurately predict and analyze the driving and operational energy consumption of reach stackers, which provides valuable input for the design and optimization of energy consumption strategy for electric reach stackers. Additionally, the energy consumption model establishes a theoretical energy consumption benchmark for the actual operational processes of electric reach stackers, effectively guiding driving behavior and identifying energy consumption anomalies caused by malfunctions.

Because of the asymmetric structure of axial piston pump, its output pressure and output flow have pulsating characteristics, which affects the output stability and reliability of hydraulic system. Therefore, an optimization design method of low pulsation structure of swashplate axial piston pump based on multi-objective genetic algorithm is proposed. Firstly, the CFD (computational fluid dynamics) simulation analysis method was used to analyze the generation mechanism of pressure-flow pulsation at the upper/lower dead points of the axial piston pump; secondly, the influence of damping groove structural parameters on the output pressure-flow pulsation of axial piston pump was analyzed, and a multi-objective optimization model of damping groove structure was constructed; finally, the structure of the low pulsation damping groove was solved. The optimized structural parameters were as follows: the damping groove radius was 2.21 mm, the damping groove length was 10.32 mm, and the damping groove deflection angle was 16.54°. After optimization, the pressure pulsation rate was 0.59%, which was reduced by 0.16% compared to the pre-optimization value of 0.75%, and the pulsation amplitude was 0.25 MPa. The flow pulsation rate was 12.02%, which was reduced by 43.59% compared to the pre-optimization rate of 55.61%. The research results provide effective theoretical support and practical guidance for the optimal design of low pulsation structure of axial piston pump.

Wind turbine blade is the core component of wind turbines. The blade bolt is not only the part that bears complex stress, but also the part that bears the highest load. In order to avoid potential hazard and economic loss caused by bolt breakage, an axial stress measurement system for in-service bolts based on ultrasonic guided waves is designed, which can achieve accurate measurement of axial stress for various types of bolts. Firstly, the group velocity dispersion curve of ultrasonic guided wave was obtained through numerical calculation, and a linear mathematical model of bolt axial stress and ultrasonic guided wave acoustic time was established based on the Hooke's law and acoustic elasticity effect. The effectiveness of ultrasonic guided wave stress measurement by single longitudinal wave transducer was verified by simulation in COMSOL software. Then, in view of the modal aliasing of ultrasonic guided wave echo signals and the interference of noise on the measured results of ultrasonic guided wave acoustic time in actual measurement, the denoising algorithm based on echo compensation was used to denoise the actual measurement signal. The empirical wavelet transform algorithm was used to decompose the modal of ultrasonic guided wave echo signal, and the cross-correlation method was used to obtain the accurate acoustic time of ultrasonic guided wave modal. Finally, the precise measurement of axial stress for 18 types of bolts within the 30%-90% yield strength was completed through experimental tests, and the relative measurement error was less than 2%. The research results are helpful to improve the bolt assembly process and standardize the worker's operation process.

In order to reduce the risk of the integrated leakage rate measurement test of reactor containment and make the leakage rate test results more conservative and reliable, an optimization method for the integrated leakage rate measurement stage duration of containment for China's nuclear power plants is proposed based on the air stability criteria, function curvature criteria and data distribution criteria. Combined with the adjustment method for the containment integrated leakage rate measurement stage duration of the French Power Group, the determination requirements for the end of integrated leakage rate measurement test for containment were clarified, and an optimization method was proposed to add the criteria for determining the stability of air inside the containment and the termination of integrated leakage rate measurement. Taking 20 groups of containment pressure test samples as examples, the integrated leakage rate measurement stage duration for containment was calculated. The results showed that 17 groups of samples met the optimization conditions, of which 15 groups of samples were able to meet the integrated leakage rate measurement termination criteria within 16 h, and 2 groups of samples met all acceptance criteria within 19.25 h and 18.25 h, respectively. The proposed optimization method can shorten the duration of the integrated leakage rate measurement stage for reactor containment, which is more conservative and reliable than the French method.

Aiming at the shortcomings of rigid robot arm in fruit and vegetable picking, a flexible picking robot arm with simple structure and flexible movement was designed. Firstly, the kinematics model of the flexible picking robot arm was established based on the equal arc hypothesis, and the forward and inverse kinematics analysis from joint space to operation space and from driving space to joint space was carried out, as well as the decoupling analysis between the flexible joints. Then, the kinematics models of the flexible picking robot arm were numerically calculated by using MATLAB software, and the virtual prototype model of the flexible picking robot arm was established by ADAMS software. The kinematics simulation was carried out under the same working conditions as the theoretical analysis, and the accuracy of the theoretical analysis results was verified. The simulation results showed that the flexible picking robot arm could move flexibly and coordinatedly. The research results can provide a basis for the subsequent motion control of flexible robot arms.

In response to solve the current issue of requiring external rigid body pump and valve for flexible actuator, a flexible bending actuator driven by an embedded electrohydrodynamic pump was designed based on the motion characteristics of human finger bending and grasping. A electrohydrodynamic pump was designed, and the influence of electrode plate spacing and electrode hole diameter on the output flow and pressure of the electrohydrodynamic pump were analyzed through experiments. The dimensions of the needle electrode, hole electrode and other components of electrohydrodynamic pump were determined, and a prototype of the electrohydrodynamic pump was developed. Multiple electrohydrodynamic pumps were connected in series and parallel, and the relationships between input voltage and output pressure, output flow were obtained. Two electrohydrodynamic pumps in series were determined to drive the flexible actuator; a mechanical model of the flexible actuator was established, and bending simulation and experiments were conducted on the flexible actuator. The relationship between the driving pressure and the bending angle of the flexible actuator was obtained, proving the good bending performance of the flexible actuator. The experimental, simulation, and theoretical values of the bending angle were relatively consistent, and the theoretical and simulation models could accurately describe the bending deformation of the flexible bending actuator. The high integration of the electrohydrodynamic pump and the flexible actuator allows the electrohydrodynamic pump to directly drive the bending deformation of the flexible actuator, achieving the portability of the flexible bending actuator.

An intelligent recognition approach was proposed, which was based on information fusion and a multi-granularity cascaded forest model (IFMCFM) to tackle the challenge of low reliability in excavator working stage identification methods. Information fusion technology was utilized to merge the category probability vector of the excavator working stage with high-importance features, thereby forming new identification features. The novel features were subsequently fed into the cascaded forest model, which was trained using different proportions of the training set. Subsequent analysis was carried out on the identification results. The identification outcomes of IFMCFM were compared with those of other models, including DAGSVM (directed acyclic graph support vector machine), PCA-SVM (support vector machine based on principal component analysis), LIBSVM (library for support vector machines), and LSTM (long short-term memory). The research findings revealed that the recognition accuracy, recall, and F₁ (harmonic average of accuracy and recall) index of IFMCFM were 95.00%, 95.17%, and 95.02% respectively, indicating good recognition performance when the training set ratio was 80%. In comparison to the other identification models, the highest accuracy and reliability were exhibited by IFMCFM. IFMCFM can effectively identify the operation stage of excavators and has high application value.

In order to accurately determine the ergonomics problems of products and improve the human-computer interaction performance, a conflict zone determination method based on functional surface drive and extension tools is proposed by using TRIZ (Teoriya Resheniya Izobreatatelskikh Zadatc). Firstly, the functional process model was improved by the functional surface to identify the initial problem functional elements of the ergonomics problems, and the transformation of the initial problem functional elements and the determination of the final problem functional elements were completed by combining the extension expression and correlation analysis. Then, the functional relationship model was improved by the functional surface to identify the initial conflict zone of the product, and the transformation of the initial conflict zone and the determination of the final conflict zone were completed by combining the extension expression, correlation analysis, implication analysis and superiority evaluation. Finally, the standard solution was used to solve the adverse effects in the conflict zone, and the evaluation and screening of the scheme were completed through the superiority evaluation. The feasibility of the proposed method was verified by an example of improved design of lawn mower. The research shows that this method is helpful for the determination of conflict zones in interactive products and can improve the efficiency of solving ergonomics problems.

Power battery is the core component of new energy vehicle, and its electrochemical and thermal performances are the key to the large-scale promotion and application of new energy vehicle. However, the electrochemical and thermal performances at the macro scale are affected not only by the electrode material characteristics at the micro scale, but also by the battery structural parameters at the mesoscale. In order to reveal the influence mechanism of battery material parameters, electrode structure parameters and battery working parameters on the performance of power battery, taking 18650 nickel-cobalt-manganese ternary power battery lithium as the research object, the influence law of the above parameters on the electrochemical and thermal performances of power battery was explored by constructing the battery electrochemical-thermal coupling model. The material-structure-performance cross-scale correlation effect of power battery was analyzed comprehensively. The results showedt hat the effects of battery material parameters, electrode structural parameters and battery working parameters on the performances of power battery had the characteristic of strong cross-scale correlation.The design and performance optimization of power battery at a single scale can not achieve optimal results, and the material-structure-performance cross-scale design and optimization is the fundamental way to improve the safety and dynamic performances of power battery.

Aiming at the lightweight problem of auxiliary tail rope pulling device for winch mill, an optimization design method based on response surface methodology is proposed in combination with the stiffness and strength requirements of the device. Through the parametric modeling and statics analysis of the auxiliary tail rope pulling device for winch mill, the key structural dimensions of the auxiliary tail rope pulling device were taken as the design parameters, the minimum overall mass was taken as the objective function, and the maximum equivalent stress and maximum deformation were taken as the constraint conditions. The response surface model was established by the central composite design method, and the fitting degree of the response surface and the sensitivity of the design parameters were analyzed. Based on the response surface model, the optimal solution set was iteratively sought, and the optimal design parameters of the auxiliary tail rope pulling device were obtained. After optimized design, the mass of the auxiliary tail rope pulling device was reduced by 29%, and the engineering verification showed that the auxiliary tail rope pulling device was light, efficient and reliable, and had achieved the expected application effect, which verified the feasibility and effectiveness of the proposed optimization design method. The research results can provide theoretical support and technical guidance for structural optimization design and practical application of the same type of engineering equipment.

Robot grasping detection has always been a research focus in the field of robotics, but the robot faces the problem of inaccurate pose estimation when performing multi-object grasping tasks in complex environments. In order to improve this problem, a Transformer based grasping detection model called PTGNet (pyramid Transformer grasp network) was proposed. The PTGNet adopted Transformer modules with pyramid pooling structure and multi-head self-attention mechanism. The pyramid pooling structure could segment and pool feature maps to capture semantic information at different levels and reduce computational complexity, and the multi-head self-attention mechanism effectively extracted global information through powerful feature extraction capabilities, making PTGNet more suitable for visual grasping tasks. In order to verify the performance of the PTGNet, the training and testing for PTGNet were conducted based on different datasets, and the robot arm grasping experiments based on PTGNet were carried out in both simulated and real physical environments. The results showed that the accuracy of PTGNet on Cornell dataset and Jacquard dataset was 98.2% and 94.8%, respectively, showing excellent competitive performance. Compared with other detection models, the PTGNet had excellent generalization ability in multi-target datasets. In the single-object and multi-object grasping experiments conducted in the PyBullet simulation environment, the average grasping success rate of the robot arm reached 98.1% and 96.8%, respectively. In the multi-object grasping experiments conducted in the real physical environment, the average grasping success rate of the robot arm was 93.3%. The experimental results demonstrate the effectiveness and superiority of PTGNet in predicting multi-object grasping pose in complex environment.

Digital modeling, system simulation and optimization in the automotive production process are of great significance for improving the quality and efficiency of automotive production. In order to solve the common problem of low resource allocation efficiency caused by data link breakage in automobile manufacturing enterprises, a new type of digital pedestal system was proposed based on the painted body storage (PBS) of automobile, to achieve data chain integration and multi-source heterogeneous data fusion. At the same time, a vehicle sequencing strategy for PBS was designed, taking into account the constraints of the final assembly process on sequence optimization. The PBS outbound sequence was obtained by a genetic algorithm, and then the inverse ordinal pair was used as a reference index for PBS lane layout. The effectiveness of the proposed method and strategy was verified by applying the PBS system based on digital pedestal system to a certain automotive manufacturing enterprise. The research results provide a reference for enterprises to build internal integrated manufacturing platforms and design specific workshop units.

Aiming at the problems of unstable operation and easy failure of transmission parts during acceleration and deceleration of carbon fiber winding machine with large moment of inertia, an optimization scheme of spindle operation curve based on improved Sigmoid acceleration and deceleration curve was proposed. Firstly, the quintic polynomial was used to compensate the mutation of the traditional Sigmoid acceleration and deceleration curve by constraining the velocity, acceleration and jerk of the starting point, connecting point and ending point of the curve. Then, the mathematical models of load torque, motor output power, strength and stiffness of spindle and number of winding coils were established based on the velocity and acceleration functions of the improved curve. The multi-objective optimization for the curve was carried out with the operating time of each stage as the design variables and the maximum motor output power and total operating time as the optimization objectives. Under the constraints of the number of winding coils, strength and stiffness of transmission parts and so on, the non-dominated solution set was solved by the multi-objective genetic algorithm NSGA-Ⅱ(non-dominated sorting genetic algorithm-Ⅱ), and the optimal solution was selected by the proportion selection function. Finally, through AMESim-ADAMS co-simulation, the operation effects of winding machine before and after acceleration and deceleration curve optimization were compared. The results showed that the total operating time, maximum acceleration, maximum load torque and maximum output power of the optimized winding machine were reduced by 41.7%, 75.8%, 75.5% and 72.8%, and the spindle operation curve was smoother, which verified the feasibility of the optimization scheme. The research results provide a new solution for the problem of unstable operation or transmission parts failure of rotating equipment with large moment of inertia.

The adaptive crossover operators and mutation operators were introduced to integrate the improved jump point search (JPS) algorithm with the adaptive genetic algorithm, solving the problems of multiple inflection points, susceptibility to getting stuck in local optima, large number of iterations, and long optimization time in the optimal path analysis of genetic algorithm. The jump point search-genetic (JPSG) algorithm was obtained. JPSG algorithm used the efficient local search ability of JPS algorithm to improve the overall search ability and accelerate the overall convergence trend of the algorithm. The global search capability of improved genetic algorithm was used to change the state that JPS algorithm could not resolve the optimal path under complex obstacles, and improved the adaptability of the algorithm to dynamic environment. The path planning simulation in the grid matrix shows that compared with improved genetic algorithm and traditional genetic algorithm, JPSG algorithm can effectively shorten the optimization execution time, improve the optimization accuracy and reduce the operation execution times, and has obvious advantages in stability, accuracy and rapidity.

The production process of high-performance hydraulic cylinders is flexible and has a long processing cycle. Its production belongs to a typical non-standard, single piece, small batch discrete manufacturing model, which is difficult to optimize and control in design and production. A high-performance intelligent design and manufacturing platform for hydraulic cylinders was designed to address the issues of low software integration and high coupling when using digital design and process control software for hydraulic cylinder production enterprises. Through reconfigurable middleware technology, the platform integrated software interfaces such as AutoCAD and SolidWorks. While integrating neural network algorithms and multi-objective optimization techniques, digital design and production control modules such as graph library, working hour prediction, and flexible process planning were constructed. The digital design and manufacturing platform can achieve full lifecycle control of the design and manufacturing process, providing strong support for manufacturing enterprises to achieve digital transformation.