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.

Fused deposition modeling (FDM) 3D printing requires the print nozzle to be heated the desired temperature of the material before printing begins. Due to the low printing efficiency of the single nozzle FDM 3D printer, and the large lag and poor stability of its heating system, the whole forming process is time-consuming and wasteful of resources, and the quality of the formed parts is not high. In order to solve the above problems, a temperature control method based on genetic algorithm-fuzzy PID (proportional-integral-derivative) was proposed to control the heating method of dual-nozzle FDM 3D printer, which combined the differences in physical and chemical properties of printing materials. The MATLAB/Simulink simulation model of the temperature control system was established to verify the reliability of the proposed control method. The simulation and experimental results showed that compared with the traditional PID control and fuzzy PID control, the response time of the genetic algorithm-fuzzy PID control was shortened by 36.03% and 32.45%, and the adjustment time was shortened by 28.06% and 20.99%, which had the advantages of fast response, short adjustment time, small overshoot and stable control effect. The research results can provide reference for dual-nozzle FDM 3D printing of composite materials.

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.

The internal toothed slewing bearing has both the slewing bearing characteristics of rolling bearing and the gear meshing transmission characteristics. Under the action of combined load, its dynamic performance is affected by many factors, and it is easy to suffer from tooth wear or broken teeth, ring raceway wear and poor running accuracy. Considering the dynamic contact between the steel ball and the inner and outer ring raceway, the cage pocket hole and the meshing transmission between the inner ring teeth, the parametric multi-body contact dynamic model of an internal toothed slewing bearing was established. The influence of key design parameters such as radius of curvature of groove, hole diameter of cage pocket, initial contact angle and tooth displacement coefficient on the gear meshing force of slewing ring, contact force between No.1 steel ball and N1 raceway, and the axial and radial vibration displacement of the center of mass of the inner ring were analyzed. On this basis, the design of experiments (DOE) method was used to design and calculate the key design parameters of the toothed slewing bearing, and the dynamic performance of slewing bearing under the influence of multiple parameters was obtained. Combined with linear weighting method, a new multi-objective optimization function was constructed and solved by using unified dimension method and weight coefficient method, and a multivariate multi-objective optimization design method for the dynamic performance of slewing bearings was proposed, which provides a reference for the dynamic design of slewing bearings.The gear meshing force of slewing ring decreased by 49.27%, the contact force between No. 1 steel ball and N1 raceway decreased by 29.6%, the axial vibration displacement of the center of mass of the inner ring decreased by 5.41%, the radial vibration displacement of the center of mass of the inner ring decreased by 15.88%. The performance of the rotary bearing was optimized. The research results provide a reference for the dynamic design of slewing bearing.

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.

In order to improve the lightweight level and performance of the car door, the integrated method of "material-structure-performance" is adopted to design the cast aluminum integrated car door. Based on the constructed finite element model of the cast aluminum integrated car door, with the thickness of the car door as the design variable, the radial basis function (RBF) neural network approximation model and the second-order response surface approximation model were used in combination with the non-dominated sorting genetic algorithm-Ⅱ (NSGA-Ⅱ), multi-objective particle swarm optimization (MOPSO) algorithm and multi-island genetic algorithm (MIGA) to conduct the deterministic optimization design for the sinking stiffness condition displacement, upper torsional stiffness condition displacement, lower torsional stiffness condition displacement, first-order bending mode frequency, first-order torsional mode frequency and mass of the car door. On this basis, the 6Sigma reliability analysis and optimization for the quality level of the deterministic optimization solution were carried out considering the uncertainties of materials and manufacturing. The results showed the optimal combination of second-order response surface approximation model and MOPSO algorithm achieved the optimal lightweight of the car door, and the optimal combination of RBF neural network approximation model and MOPSO algorithm could minimize the the displacement of the car door under the sinking stiffness condition. The above two combinations achieved the design goals of lightweight and safety for the car door, respectively. The research results can provide reference for the optimization design of car parts.

A magnetorheological damper (MRD) with simple structure and capable of collecting vibration energy was designed to address the over-dependence of MR damper on external power sources and avoid the power failure risk. The damper consisted of a vibration reduction device based on magnetorheological effect and a power generation device based on electromagnetic induction principle. Firstly, the mathematical model of vibration energy harvesting of the power generation device was established based on the Ohm theorem of magnetic circuit. Secondly, MATLAB software was used to analyze the power generation performance. The relationship between the power generation performance and the structural design variables was studied. Then, electromagnetic simulation analysis and comparison were conducted on two power generation devices with different permanent magnet group structures using COMSOL software, with a focus on the impact of permanent magnet group height on power generation performance. Finally, the impact of different vibration frequencies and amplitudes on the power generation performance of the device was simulated and analyzed. The results showed that within a certain range, the height of winding slot of induction coil was basically linear with the power generation performance index, and there were optimal values for the height of permanent magnet group, the height of magnetic gasket and radial thickness of winding cylinder. Regardless of the frequency or amplitude of vibration excitation. The peak induced voltage of a single coil of generation device with a permanent magnet group height of 30 mm was about 42.5% larger than that with a permanent magnet group height of 20 mm, and the peak output power was about 22.3% higher. The research results can provide reference for improving the power generation performance of vibration energy harvesting MRD.

In order to better assist the rehabilitation training for hemiplegic patients, a lower limb rehabilitation exoskeleton robot driven by disk motor is designed, and the effectiveness of its different rehabilitation training modes is verified through visualization research of power-assisted effect and performance analysis. Firstly, the detailed structural design for the lower limb rehabilitation exoskeleton robot was performed, and the biomechanical analysis of human-machine coupling was carried out by using OpenSim software. Then, the passive rehabilitation training experiment based on position tracking control and resistance rehabilitation training experiment were carried out, and the surface electromyographic signals were collected to verify the effectiveness of the designed lower limb rehabilitation exoskeleton robot to assist patients in rehabilitation training under different modes. The results showed that wearing lower limb rehabilitation exoskeleton robot could reduce the human knee joint torque by about 50%. In the passive rehabilitation training experiment, the following error was within -4°-8°, and the muscle activation of the target muscle group of human lower limbs showed an obvious periodic change. In the resistance rehabilitation training experiment, the muscle activation of the target muscle group of human lower limbs increased with the increase of weight. The designed lower limb rehabilitation exoskeleton robot has good sensitivity and followability, and its passive and resistance rehabilitation training modes are conducive to lower limb rehabilitation of hemiplegia patients, which has broad application prospect.

In order to design a large angle bending actuator with a simple structure, convenient production and easy modeling, a soft multi chamber bending actuator with a fan-shaped chamber structure was proposed. The actuator was made of super-elastic material. The functional relationship between input air pressure and bending angle was established based on the Yeoh model. The simulation of the bending actuator under different air pressures was carried out using Abaqus. The effects of structural parameters such as chamber end radius, chamber wall thickness, the angle between chamber ends, groove depth, and bottom thickness on the bending angle were analyzed. The soft actuator was manufactured and an experimental platform was built. The bending performance of the actuator was tested. The input air pressure was 0-65 kPa, and the bending angle was 0-218°. The simulation results were basically consistent with the experimental results. A flexible gripper with adjustable claw length was designed based on a bending driver, and its clamping effect on objects of different sizes, shapes, and masses was tested. The experimental results verified the practicality of the designed driver and gripper, and the driver had good bending performance. The research results can provide reference for further research on software drivers.

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.

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.

A simple structure and stable performance swing spraying mechanism was innovatively designed to address the complex structure, unstable operation, and low construction efficiency of the spraying module of the previous generation of building wall mortar plastering machines. The swing of the mortar spraying swing arm was achieved through the linkage between the linear guide rail slider and the screw and slide table. A 3D model of the oscillating spraying mechanism was created using SolidWorks. The dynamic automatic analysis of the mechanical system using ADAMS (automated dynamic analysis of mechanical systems) software was used to simulate the motion of the spraying mechanism. The kinematic characteristics and trajectory of the mortar spraying swing arm were obtained. A prototype of a swing spraying mechanism was made and installed on a plastering machine for on-site mortar spraying experiments. The experimental results showed that the swing spraying mechanism was designed reasonably, with a simple structure, stable operation, and high construction efficiency. The sprayed mortar was continuous and uniform, and the trajectory tended to be close to a straight line. The quality of mortar spraying construction was relatively high. The construction wall mortar plastering machine using the swing spraying mechanism has good application prospects.

At present, the shale shakers in China are operated by manually detecting the solid-liquid separation status and manually adjusting the inclination angle of the screen surface, which can not realize self-adaptive work, and the phenomenon of drilling fluid "running" often occurs. To solve this problem, an inclination angle adjustment system for shale shaker based on Raspberry Pi and visual image was proposed. The system used Raspberry Pi, dedicated camera, motor drive board and two stepper motors as hardware platform, and was equipped with an image recognition software developed based on OpenCV and improved AlexNet model, which could achieve visual detection of screen surface solid-liquid separation status and automatic adjustment of screen surface inclination angle of the shale shaker. Firstly, according to the position characteristics of the liquid phase termination line during the solid-liquid separation process of shale shaker, the collected screen surface images were divided into three categories: normal, low mud and slurry running state, and the screen surface image dataset was constructed. Then, the AlexNet model based on transfer learning was constructed using TensorFlow platform to automatically recognize the screen surface solid-liquid separation status of shale shaker. Finally, based on the recognition results, two stepper motors were controlled synchronously by the GPIO (general purpose input/output) interface of Raspberry Pi to realize the inclination angle adjustment for the shale shaker. The results showed that the accuracy of the designed inclination angle adjustment system for recognizing screen surface solid-liquid separation status reached 97.3%, and the response time was about 1.5 s, which could meet the inclination angle adjustment requirements of the shale shaker. The inclination angle adjustment system equipment has small volume, low cost and is easy to debug and maintain, which can effectively improve the automation level of shale shakers.

During the rock breaking process of tunnel boring machine (TBM) cutter, the cutting stress generated by the strong impact load is transmitted to the cutterhead through the tool holder system, causing severe vibration of the tool holder system, resulting in bolt loosening and breaking, even cutter falling and other serious engineering problems. Therefore, the vibration characteristics of the TBM cutter holder system were studied by rock breaking experiments. The multi-function cutter cutting performance test bench was used to carry out cutter cutting experiments on the red sandstone and granite, and the data of three-directional load and cutter shaft vibration acceleration during the rock breaking process were collected. By comparing and analyzing the load-time history curve of cutter rock breaking under red sandstone and granite strata, the dynamic load change characteristics of cutter holder system during rock breaking and the vibration response characteristics of cutter shaft under different strata were obtained. The research results can provide a theoretical basis for the vibration reduction design of TBM cutter holder system.