The ultrasonic rolling process can strengthen the compressor blades and extend their working life,but due to the limited structure of the blade root,conventional ultrasonic rolling equipments are difficult to process the restricted space at the root.In order to make the ultrasonic rolling equipment better adapt to such spaces,after improving the structure of the ultrasonic rolling tool head,the influence of tool head size was concerned in the optimization design of the horn size.With the joint simulation of Abaqus and Matlab software,the horn size with stable longitudinal vibration frequency and amplification factor was obtained when installing the tool head,and the overall design of the ultrasonic rolling equipment was improved.By processing flat test specimens,the influence of the equipment on surface integrity under different processing parameters was analyzed.Based on this,the optimal processing parameters were selected and fatigue performance experiments were conducted on bending fatigue vibration test specimens.The fatigue life of the processed test specimens was improved.The processing experiment was conducted in the confined space at the root of the blade-type structural component,and the surface integrity of the processed sample piece was significantly improved.The successful strengthening of confined spaces proves that the ultrasonic rolling equipment with wheeled cutting heads can be applied to parts with narrow confined spaces such as the root of compressor blades,and is expected to further improve the surface integrity and fatigue life of some components with complex features and structures.

To analyze the flow characteristics of double circular arc gear pumps under different operating conditions,AMESim software was used to accurately model the double circular arc gear pump, different rotational speeds,load pressures,and gas mass fractions were set,and its instantaneous outlet flow rate and outlet flow pulsation rate were analyzed. The results show that the rotational speed is positively correlated with the instantaneous outlet flow rate,with an average outlet flow rate of 3 000 r/min being 2.17 times that of 1 500 r/min; the load pressure is negatively correlated with the instantaneous outlet flow rate,and the average outlet flow rate at a load pressure of 6 MPa is reduced by 0.621 L/min compared to the average outlet flow rate at a load pressure of 2 MPa; when the rotational speed is 3 000 r/min and the load pressure is 2 MPa,the outlet flow pulsation rate is the smallest; the pulsation rate of outlet flow is negatively correlated with rotational speed and positively correlated with load pressure. An increase in the gas mass fraction of the oil will exacerbate the cavitation phenomenon of the double circular arc gear pump,which has a negative impact on the flow characteristics.

In order to obtain the optimal scheduling scheme for flexible workshops under uncertain conditions,a workshop scheduling method based on interval grey number and operation order adaptive genetic algorithm was proposed.Taking into account uncertain conditions such as fuzzy processing time and machine maintenance,an optimization model was established with the goal of minimizing the grey number in the processing time interval.In terms of solving algorithms,the genetic operation order was adaptively adjusted based on chromosome aggregation,maintaining the evolutionary ability of the algorithm in different situations,thus proposing a scheduling method based on the operation order adaptive genetic algorithm.Taking the production scheduling case of a certain workshop as an example,simulation verification shows that compared with genetic algorithms,elite retained genetic algorithms,migratory bird algorithms,etc.,the operation sequence adaptive genetic algorithm has the smallest grey number in the completion time interval,which is [74 ,84 ] min; and the scheduling plan meets the constraints of production sequence and time,making it a feasible scheduling plan. The experimental results show that the operation sequence adaptive genetic algorithm is effective and feasible in workshop scheduling.

Aiming at the dynamic energy-saving batch scheduling of flexible job shop problem,a mathematical model aiming at optimizing the production cost of the workshop,the energy consumption cost of the machine tool and the difference cost of the dynamic and static scheduling scheme is established.Then,a dynamic scheduling scheme is designed for the dynamic disturbance in the production practice,and the reorganizing batch technology is designed for the problem of the dynamic disturbance leading to the change of the process route of the workpiece,and an improved grey wolf optimization algorithm is designed for the solution of the dynamic scheduling scheme. The hierarchical location update method is used to update the location of the wolves to improve the search efficiency of the algorithm. Finally,the effectiveness and superiority of the algorithm to solve the dynamic energy-saving batch scheduling problem of flexible job shop are verified by a standard example.

For solving the trajectory planning problem that often occurs in the welding process of welding robots,a six-degree-of-freedom robotic arm PUMA 560 was taken as the research object,Cartesian space was used to plan the trajectory,and a hybrid algorithm was used to optimize the inertia moment of each joint at different end positions with the minimum amount of joint inertia moment variation as the optimization objective,thus the problems of unstable operation and unstable motion of the robot arm during welding were eliminated.The problems of slow convergence of the simulated annealing algorithm and poor local optimization capability of the quantum genetic algorithm were overcome,and the optimal trajectory of the joint inertia moments of the robot arm was successfully planed.MATLAB simulation results show that,the convergence time of the simulated annealing quantum genetic algorithm is reduced by 30.56 % compared with the traditional genetic algorithm,and the inertia moment of the joint is optimized,which verifies the feasibility of the algorithm and lays the foundation for the subsequent research.

In order to explores the optimal maneuver of a five-link robotic manipulator navigating through obstacle within a confined workspace, the Denavit-Hartenberg convention was applied in order to define the configuration of the manipulator. The Euler-Lagrange equation was adopted to describe the dynamics of the manipulator system. Optimal control theory was introduced to yield a least energy consumption path planning control scheme.This study takes Direct Collocation and Nonlinear Program (DCNLP) method to solve the Two-Point Boundary-Value Problem (TPBVP). DCNLP converts TPBVP into nonlinear programming problem and solves it numerical with Symbolic language.The manipulator needs to stay away from the obstacle and come up with a least energy control scheme and a smooth path planning maneuver. According to the simulations with MATLAB software, once the mechanism of obstacle avoidance is turned on,it is obvious that the working time and cost index value keep increasing as the radius of the obstacle sphere gets larger and larger. When the radius exceeds the extreme value,the mission becomes infeasible to complete. This study provides a scheme which foretells the maximal size of the obstacle sphere.

Intelligent manufacturing requires industrialized software bases.Deep application of industrial software is the key to accelerating the digital transformation of the manufacturing industry. The Manufacturing Execution System (MES) plays an increasingly important role in workshop production. In the future development,intelligent manufacturing puts forward the demand for modularization,componentization,and platformization of the MES system.Based on microservices,first of all,the business functions of the MES system are divided into microservices,and the manufacturing execution system framework based on microservices architecture is designed. Then the binding mechanism of the registration center and the micro service library is proposed,which can effectively respond to the changing and dynamic changes of the business process of the enterprise. On this basis,how to select the optimal microservices and business process microservices required by the MES system from the microservices library is further studied,which plays a reference role for the development of MES system based on microservices.

In response to the dynamic characteristics and complex driving control strategies of four wheel independent electric drive vehicles,a driving collaborative control strategy based on torque distribution coefficient method was proposed,and a driving torque sliding mode coordination controller was designed. In conjunction with the vehicle instability judgment module,the additional yaw torque required for maintaining stability of the vehicle was calculated. At the same time,the load distribution method was used to design the optimal driving torque distribution controller,based on load distribution method, the driving torque was distributed to four wheels to maintain stable vehicle operation. To verify the effectiveness of the driving collaborative control strategy,a four wheel independent electric drive vehicle model was established based on CarSim software,and the proposed driving collaborative control strategy was compared with the ordinary sliding mode control strategy through simulation. The results showed that the driving collaborative control strategy reduces the yaw rate deviation by 25 % and the center of mass lateral deviation by 23 %,which can meet the requirements of vehicle stability control and reduce the difficulty of vehicle driving torque distribution control.

In order to study the effect of torsion beam deformation on toe and camber angle of a torsion beam suspension vehicle when the vehicle is offline,taking the toe and camber angle of the torsion beam of an electric taxi as the research object,the combination of numerical simulation technology and bench verification was used to complete the toe and camber angle mechanical compensation and bench verification at the development stage of the torsion beam components. Compared with the traditional method of using the statistical analysis results of small batch of vehicle toe and camber angle to compensate the toe and camber angle of torsion beam, the development cycle of the method proposed was greatly shortened,and a new design and verification method was provided for the mechanical compensation of the toe and camber angle of torsion beam suspension by the main engine factory. The main results are as follows: 1) using the numerical simulation method of torsion beam deformation,after the offline load applied by the spring to the torsion beam,the toe and camber angle changes of torsion beam are calculated and obtained, which are 2.7′ and -31.5′ respectively; 2) the torsion beam structure has little influence on the toe angle change,but has great influence on the camber angle change; 3) based on the numerical simulation deformation results of the toe and camber angle of the torsion beam,the equivalent and reverse mechanical angle compensations are given to the toe and camber angle of the torsion beam,and the physical verification was carried out using the torsion beam suspension system test bench; 4) comparing the numerical simulation data of the toe and camber angle change of the torsion beam with the bench verification data,the error is within 10 %,and the numerical simulation results of the torsion beam deformation are in good agreement with the bench verification results. Finally,through the batch verification of the whole vehicle,it meets the production requirements of the main engine factory.

An active energy storage component is a new type of gas-electric hybrid energy storage component proposed to address the shortcomings of existing hydraulic accumulators. However,there is an energy coupling problem between hydraulic energy,compression gas energy,and electrical energy,which leads to poor anti-interference ability during operation and reduces the energy-saving efficiency of the working hydraulic system.In order to solve the problem of poor anti-interference ability,a system architecture that uses active energy storage components to achieve arm potential energy regeneration was proposed based on the working characteristics of the hydraulic circuit of the hydraulic excavator arm.A self-disturbance control strategy and its parameter optimization method were designed to solve problems such as interference and parameter uncertainty by designing an expansion state observer. To verify the feasibility of the control strategy,the structure of the active energy storage component was first introduced,followed by the design of a self-disturbance controller based on the active energy storage component as the control object. A simulation model of the arm potential energy regeneration system based on the active energy storage component was established and experimentally verified. The research results show that the recovery efficiencies of the accumulator mode,normal control mode,and self-disturbance control mode are 42.81 %,56.76 %,and 58.60 %,respectively;the reuse efficiencies are 96.01 %,97.06 %,and 95.81 %,respectively;and the regeneration efficiencies are 41.1 %,55.1 %,and 56.1 %,respectively. The simulation and experimental results also show that the self-disturbance control strategy proposed for the active energy storage component effectively improves the control performance and enhances the system pressure stability.

Based on the principal distortion issue of helical gear tooth surfaces during the grinding processing by worm-wheel machining,the contact trace equation was deduced, the evaluation scope of gear tooth profile and lead was selecteel and the distortion model was created, the deviation values of tooth profile and lead angles were calculated. The distortion optimization parameters also included the tooth profile drum and the counterpart gear tooth drum or the distortion. Through the experiment and verification,the distortion compensate methods could effectively optimize the distortion,load bearing capacity,the gear meshing impact force,the gear precision and vibration or noise level.

Aiming at the low-carbon flexible process planning problem of CNC machining process,an optimization model aiming at the conversion times of machine tools,tools and clamping and carbon emissions in the machining process was established,and a solution method based on the improved beluga whale optimization algorithm was proposed. The algorithm enhances its global search ability by introducing mutation operations,and adopts a heuristic rule selection strategy oriented to processing resources combined with random generation in population initialization to improve the quality of the initial population and accelerates the convergence speed of the algorithm. Finally,taking the machining information of a part as a test example,the feasibility of the proposed model was verified,and compared with the other three algorithms. The experimental results show that the proposed algorithm can obtain a better solution and has a faster convergence speed.

When the high-pressure turbine unit of turbofan engine with medium bypass ratio is assembled,due to the concentricity affection factors of spline fit gap,radial bearing clearance and elastic seat deformation,the seal labyrinth of high-pressure turbine rotor goes downward eccentrically,leading to the collision failure with air oil deflector on the stator. By means of finite element method of statics,the specific geometric deformation of elastic seat was analyzed and obtained. Taking use of least square principle,the eccentricity of seal labyrinth on the rotor was calculated. A new method of the eccentricity assembly process of the high-pressure turbine rotor and stator was advocated,and the simulation process axis of high-pressure turbine was designed.Based on the assembly deviations of spline fit gap and radial bearing clearance during the process axis installation,combining with the affection factors of actual axis assembly deviations,the final eccentricity adjustment account of the air oil deflector on the stator can be acquired comprehensively to achieve the optimization concentricity of the seal clearance between the rotor and stator of high-pressure turbine,getting rid of the collision between the rotor and stator of engine and solving the problems of high vibration and oil leakage from bearing cavity.This method is proved to take effect through the assembly test and the research results can afford the reference to the assembly process designation of the rotor and stator concentricity of other engine types.

In light of such problems as low accuracy and low efficiency resulted from the traditional manual size detection method for E-type circlips,an improved detection method based on machine vision was proposed herein. Firstly, the grayscale image was passed through a bilateral filter to attenuate the noise. The measurement zone was quickly and accurately determined through shape matching and a priori knowledge,while the image pyramid hierarchical search strategy was used to improve the shape matching and locating efficiency. The edge contours were extracted from the measurement zone down to the subpixel level using a subpixel edge detection algorithm,and the inner and outer diameter edges and opening edges were obtained. Finally,circle fitting was performed using Iterative reweighted least squares,and the minimum distance among the convex polygons was calculated using the rotation method,which completes the size measurement. Results of experiments carried out using the proposed method indicate high measurement accuracy,high measurement efficiency,and good stability,all of which fulfill the criteria for industrial automation.

In order to solve the problems that HTCC board used in camera module breaks away from the fixed slot,and the subsequent parts are poorly installed,a dislocation detection algorithm of HTCC board based on improved LSD was proposed. Firstly,gamma transform was used to eliminate the shadow on the product image. Then,bilateral filtering was applied to the image. Compared with LSD algorithm,bilateral filtering can keep more complete edge information.Then,a scaling algorithm based on bilinear interpolation and improved mapping relation was proposed to eliminate quantization artifacts and reduce image distortion. Then,a disconnection and reconnection algorithm was proposed to solve the problem of over-segmentation of line segments in LSD algorithm. Finally,based on the improved LSD algorithm,the dislocation detection algorithm of HTCC board was designed,and the number and position of dislocation HTCC board in the product were obtained. The factory verification shows that the average detection time of this method is less than 800 ms,and the detection accuracy is over 97 %. Compared with the traditional LSD algorithm,the detection time is reduced by at least 38 %,and the accuracy is improved by at least 21 %.This method can meet the real-time and accuracy of production.

In the intelligent assembly in a narrow space,the datum surface pose needs to be measured.However,the existing attitude measurement devices have some shortcomings. For example,their sizes are large,or they require additional scanning motion mechanism. These disadvantages make devices difficult to deploy.The present study proposed a monocular active vision attitude measurement method based on two line lasers,which is suitable for the narrow space. First,the center points of the two line lasers were extracted for laser plane calibration. Second,according to the central projection relationship,the conversion matrix between the laser plane and the image plane was calculated. Then,the pixel coordinates of the line laser center point on the target plane were extracted and converted to camera coordinates.Finally,the RANSAC algorithm was applied to filter the anomalies and then the least square algorithm was used to fit the object plane equation to realize the attitude measurement of the spatial object plane.The experimental results show that the mean value of the roll angle measurement error is 0.029° and standard deviation is 0.016°. The mean value of the pitch angle measurement error is 0.035° and standard deviation is 0.025°. The validity of the method is verified by completing the plane attitude measurement in a cylindrical cavity with diameter of 170 mm and height of 520 mm using the method.

To improve the safety and traffic efficiency of vehicle platoon at signalized intersections,a signalized intersection control strategy for connected vehicle platoon in V2X environment is proposed.A control zone is set up upstream of the signalized intersection,with the aim of optimizing the speed of the vehicle platoon for the lead vehicle to queue and evacuate the signalized intersection.Considering the effect of speed variation on the longitudinal safety distance of the vehicle platoon,a distributed model predictive method is introduced.A speed tracking control model for the platoon vehicles is established under the fixed following headway control strategy.Weighted quadratic performance functionals are used to transform the speed tracking control problem into a convex quadratic programming problem that can be easily solved online.PreScan/Simulink softwore simulations are conducted to compare the signalized intersection control strategy with the traditional car-following strategy,to verify the effectiveness of the speed tracking control model.The results show that the proposed control strategy can avoid collision conflicts between vehicles and reduce the travel time of the platoon vehicles at signalized intersections,while ensuring safety and improving traffic efficiency.

During the machining process,it is difficult to obtain comprehensive information about tool wear characteristics using a single signal due to the complex and varied machining environment. A method is proposed that utilizes a combination of sound signals and surface image signals of workpieces through deep learning networks to recognize tool wear states. Initially,sound signals and surface image data from milling processes are synchronously collected,followed by the establishment of a dual-channel parallel convolutional neural network for feature extraction and fusion of one-dimensional sound signals and two-dimensional workpiece surface images. Finally,tool wear recognition is conducted. The results indicate that the use of information fusion methods can obtain more comprehensive tool wear characteristic information compared to single information recognition results,which is advantageous in improving the tool wear recognition effect.Moreover,the tool wear recognition accuracy and F1-score are above 95 %,allowing for effective recognition of the tool wear condition.

Aiming at the problems of low integration, low efficiency, and high labor costs in traditional electronic yarn packaging and sealing production lines, an automated electronic yarn packaging and sealing production line has been designed. Based on the requirements of electronic yarn packaging and sealing, the layout, composition, and workflow of an automated production line for electronic yarn packaging and sealing were designed. Key components such as the yarn tube turning machine and industrial robot specialized fixtures were developed. Communication between multiple processes such as conveying, packaging, weighing, labeling, and sealing was achieved using a Programmable Logic Controller (PLC). Practical applications have shown that the designed automated production of electronic yarn packaging and sealing can be stable and reliable, effectively improving production efficiency and automation level, saving space, and reducing labor costs.

In order to improve the accuracy of fault diagnosis for the electric drive assembly of pure electric vehicles,a fault diagnosis method based on Particle Swarm Optimizing (PSO) algorithm was proposed to optimize the Improved Back Propagation (IBP) neural network.The Rectified Linear Unit (ReLU) was used as the activation function for the BP neural network.Through the Particle Swarm Optimizing algorithm,the weights and thresholds of the BP neural network were dynamically optimized to build the PSO-IBP model. By collecting fault data from the electric drive assembly of pure electric vehicles,PSO-IBP model,along with the BP neural network model and the Probabilistic Neural Network (PNN) model,were trained and simulated. The results showed that compared to the BP neural network methods and PNN methods,fault diagnosis method for pure electric vehicle electric drive assembly based on PSO-IBP neural network model has higher accuracy.

Metal micro-tube has the functions of micro-channel closure,directional guidance,steadying and guiding flow etc.,which is widely used in medicine,electrical and electronics,heat transfer,optics and other fields.The preparation of metal micro-tubes is very challenging due to the limitations of the miniaturization of tools and changes in material properties and friction behavior due to size effect.The process principles,manufacturing characteristics,forming capabilities,advantages and disadvantages of the commonly used manufacturing technologies for metal micro-tubes are summarized,including hot extrusion forming,cold drawing forming,dieless drawing forming and electroforming forming.Finally,the future development trends and research focuses of metal micro-tube manufacturing technology are prospected.

Flexible roll forming is a new plastic processing technology,compared with the traditional strip forming technology,the process takes the multi-pass forming roll small angle changes to complete the forming requirements,combined with automation and high-level intelligent control system,high technology advanced,the upgrade of the process can better use the frame structure to achieve lightweight. According to the different characteristics of forming members,including equal section,variable section,axis side bending and variable depth members,the research status of roll forming technology was investigated,including the mechanism,forming force and finite element simulation. The types and mechanisms of defects in the process of forming were described,and the improvement measures used to control these defects were given. Finally,the application fields of this process and the key development and application fields in the future were summarized.It was pointed out that this process has a good development prospect in manufacturing high-precision and high-quality components with high automation level.