By measuring and counting the long axis and short axis of several groups of poultry eggs,the geometric characteristic parameters of poultry eggs were obtained.By analyzing the moment of inertia of the bionic egg section and the traditional rectangular section,the bionic egg box girder with the same section moment of inertia as the rectangular box girder was designed. Meanwhile,the bending performance and anti-buckling ability of the two types of box girder were analyzed by finite element method. The relationship between the mechanical properties and geometric characteristic parameters of two kinds of box beams was obtained. Finally,the main beam of gantry crane was redesigned according to the geometric characteristics of egg shape,and the stiffness and strength of the two main beams in dangerous working conditions were analyzed. Through the application of gantry crane main beam,it is proved that the bionic egg-shaped box girder has similar structural mechanical properties as the traditional rectangular box girder,while its weight is 11.11 % lighter than that of the traditional rectangular box girder.

In order to reduce the large load disturbance exposed to the external of the unmanned combat hub motor,the Active Disturbance Rejection Control (ADRC) strategy based on the synovial load torque observer was proposed,which can observe the load disturbance change in real time and feed the observed load torque change forward into the torque current,thereby significantly improving the steady-state performance of the speed control system. Simulink simulation was used to compare and analyze the synovial velocity control,synovial load torque observer and ADRC velocity loop control. According to the simulation results,the model shows high smoothness and strong system immunity.

In order to reduce the total delay time of multi workshop joint scheduling with serial parallel heterogeneous process constraints, a scheduling solution method based on knowledge guided genetic algorithm was proposed. Firstly, an extended process tree was used to describe the constraints of serial parallel heterogeneous processes, and the distribution of machines in multiple workshops was described based on an undirected graph. To address the constraints of the extended process tree during chromosome initialization and evolution, the concepts of the number of tight preceding steps and the number of remaining tight preceding steps were defined. Based on the number of remaining tight preceding steps, chromosome initialization and evolution methods were designed. In order to improve the evolutionary ability of genetic algorithms, the population evolutionary ability and the optimal individual evolutionary ability were used as knowledge to drive the evolutionary mode and direction of the algorithm, thus a solution method based on knowledge guided genetic algorithm was proposed. After experimental verification, the average total delay time of knowledge driven genetic algorithm scheduling is the smallest, at 30.8 hours, indicating that the algorithm has the best optimization performance in multi workshop scheduling. And the length of the total delay time box graph is the smallest, indicating that the stability of knowledge driven genetic algorithm is also good.

The performance of continuous carbon fiber composite 3D printed parts has a demand for fiber laying direction,and the traditional path planning method is filled based on the shape profile of the part,which can not meet the actual performance of the part. To solve this problem,a path planning method for continuous carbon fiber composite 3D printing based on principal stress trajectory lines was proposed. Based on the finite element analysis data of the continuous carbon fiber composite 3D model,the corresponding principal stress trajectory lines were calculated by material mechanics. Through the printing parameters of continuous carbon fiber composite material 3D printing,the obtained principal stress trajectories were regulated to ensure that the spacing between each trajectory lines met the requirements of 3D printing. The finite element analysis coordinate system and printer coordinate system were adjusted by coordinate transformation. The G code planning file for continuous carbon fiber composite 3D printing was generated through the above regulation. Through path planning simulation comparison and print tensile test,the performance of the continuous carbon fiber print path generated based on the principal stress trajectory line was improved by 4.5 % compared with the traditional straight path,which verifies the effectiveness of the path planning method for continuous carbon fiber composite 3D printing based on the principal stress trajectory line.

The rapid and personalized manufacturing of braces puts forward the demand for unsupported molding of 3D printed braces.In the process of unsupported printing needs to change the deposition direction,corresponding to the layering needs to change the direction of the tangent plane,the tangent plane between the angle will be generated.If the angle is too large,it will produce a step phenomenon;if the angle is too small,there is no more subdivided cutting plane between the two neighboring cutting planes,and the model between the two cutting planes can not be layered,resulting in part of the model missing when printing;both of these situations will have a negative impact on the mechanical properties and surface quality of the support printing.Aiming at this problem,a variable layer height planning and path compensation method for unsupported rapid 3D printing of the support is proposed.Through the extraction of the central axis of the brace model and the layer planning based on the central axis, the ladder phenomenon is avoided;for the lack of model caused by the change of the tangent plane, the amount of compensation is calculated,and the variable layer height path planning is used to compensate for the mechanical properties and surface quality of the brace;and finally five-axis printer printing Gcode file is generated. The elbow brace model is used for path simulation and printing experiments,and the mechanical properties of the brace printed by this method are improved by 3.74 times compared with that before optimization,and the surface quality is also improved,which realizes unsupported rapid 3D printing of the brace.

As a key link in production,the intelligent level of workshop scheduling management plays an important role in the construction of digital workshop.In the existing workshop scheduling management,the information release medium is mainly two-dimensional physical kanban in public space,which limits the intelligent development of workshops.To meet the requirements of workshop scheduling management,Mixed Reality (MR) technology and digital twin technology were introduced to propose a six-dimensional model of MR digital twin workshop scheduling intelligent management system.On this base,a framework of MR-based digital twin workshop scheduling intelligent management system was established;the visualization technology of scheduling information for MR-based digital twin workshop was studied,and a full-element information model for workshop scheduling process was constructed,which provides a unified data foundation for workshop scheduling visualization management and intuitively expresses of workshop information;the multi-modal interactive information acquisition technology for MR-based digital twin workshop was explored,and a multi-modal interactive information intelligent acquisition strategy in MR application was proposed to achieve efficient information acquisition;finally,through human-computer interaction experiments,three typical scenarios of production scheduling were taken as examples to verify the performance of the system proposed.The results show that the proposed system can significantly improve the efficiency of workshop scheduling and enhance user experience.

In order to solve the problems of confused identification, prominent data islands, poor interoperability and difficult management of all element resources in transformer factories, the concept of fully connected transformer factory with identity resolution and 5G is proposed, the overall architecture of fully connected transformer factory is designed, the formal description and marking methods of all element objects in the factory are proposed, the management shell model of all element resources is studied, a mechanism for the identification and interoperability of factory full element data is proposed. Finally, on-site verification is conducted in a transformer factory, and the results showed that the above methods and models can achieve unified access and efficient management of all element resources in the transformer factory, which has certain reference significance for the implementation and construction of fully connected factories.

To overcome the influence of uncertainties such as mechanical friction,external interference,and model errors on the accuracy of industry robot dual-arm motion trajectory control,a collaborative robust control method for industry robot dual-arm based on adaptive neural network was designed. Firstly,a dynamic model of industry robot dual-arm with various uncertainties was established. Then,a collaborative control law with uncertainty was designed by constructing an obstacle Lyapunov function,and an adaptive neural network was designed to estimate the uncertainty of the system,obtaining a robust collaborative control law for industry robot dual-arm. Finally,the Lyapunov stability theory was used to demonstrate that the designed collaborative robust control law can constrain the trajectory tracking error,velocity tracking error,and uncertainty estimation error of the industry robot dual-arm within an arbitrarily small neighborhood. The simulation results show that the designed adaptive neural network can accurately estimate the uncertainty in the industry robot dual-arm system,and the maximum estimation error is only 0.04 N·m. The proposed collaborative robust control law can stably and accurately track trajectory control instructions,and the maximum trajectory tracking error is only 1.3 mm,verifying the rationality of the designed method. In the fixed coordinate positioning test in 3D space,the proposed collaborative robust control law has higher control accuracy compared with other methods,the average and maximum positioning error are only 1.1 mm and 1.4 mm,respectively,demonstrating stronger robustness and better engineering applicability.

Under industrial internet environment, a manufacturing task usually consists of multiple manufacturing services, each of which is not completed independently, and the effectiveness of their collaboration is one of the key factors for success of the service composition. Firstly, based on the number of historical service invocations in the industrial internet platform, the collaboration is defined; secondly, the service cost and time measures are improved based on the collaboration; finally, manufacturing service composition recommendation method based on collaboration is proposed and the Non-dominated Sorting Genetic Algorithm Ⅱ (NSGA-Ⅱ) is used to recommend the manufacturing service composition scheme with service quality optimization for users. The practicality and effectiveness of this algorithm are verified by comparison with three heuristic algorithms.

An IoT-based energy information collection system for aluminum foil rolling workshops was proposed, taking into account the workshop′s process flow and energy consumption data characteristics. To address the issue of missing energy consumption data during the collection process, missing a data processing flow was designed, which utilized a WOA-CNN-LSTM hybrid neural network algorithm to interpolate the missing data. The system development employed technologies such as the MQTT protocol, JAVA language, and SpringBoot framework. It achieved energy information collection during the production process, information statistics, and supervision, improved data accuracy by addressing the issue of missing data during energy collection in the rolling workshop.

Aiming at the problems such as rebound of top foot, immobility of continuous brake pedal and brake failure during braking of new energy vehicles, a mechanical model of electronic brake booster of new energy vehicles was established and analyzed, and a vector control model of three-phase Permanent Magnet Synchronous Motor (PMSM) of new energy vehicles was built and simulated based on MATLAB software. At the same time, CarSim and Simulink software were jointly used to simulate and verify the braking effect of three-phase PMSM of new energy vehicles, and finally a real vehicle platform was built for testing. The results show that the new energy vehicles with new electronic brake booster have higher braking performance and smaller braking distance.

In order to eliminate the meshing interference of the gear pair of the planetary reducer,the single-stage planetary gear in an involute planetary reducer was taken as the object,and the transmission error of the planetary gear level,the meshing contact performance of the s-p meshing pair and the contact stress of the gear pair were taken as the modification evaluation indexes. The influence of the tooth profile modification parameters of the sun gear and the planetary gear on the transmission performance of the gear was studied. Studies show that compared with the unmodified case,when the sun gear and the planetary gear were modified,the planetary gear level transmission error,the gear pair contact stress,the s-p meshing contact performance and the stability of the gear transmission were greatly improved. According to the comparative analysis of gear modification parameters,it is found that when the modification amount is (16 ± 4) μm (sun gear) and (11 ± 4) μm (planetary gear),all indexes reach the optimum,which has a certain reference significance for improving the transmission performance of planetary gear and the modification processing of planetary gear.

To accumulate and reuse the valuable knowledge in the aviation elastomeric seals structure design cases effectively,the method of MBD-based sealing structures case base construction was proposed. Firstly,the MBD based case content framework and representation of the aviation sealing structure were established based on the industry design standards of aviation elastomeric sealing structure and the 3D modeling and annotation of MBD,and the case representation was implemented by SolidWorks MBD module. Then,the geometric and semantic features from the MBD based case representation of sealing structures were extracted which were used to design case retrieval method. Finally,the MBD based case prototype system for aviation elastomeric sealing structure and its application show that the MBD based sealing structure case representation and retrieval have achieved knowledge accumulation and application.

Carbon Fiber Reinforced Polymer(CFRP) has gained widespread application in the aerospace industry due to its excellent properties such as high specific strength,fatigue resistance,and corrosion resistance.However,the heterogeneity and anisotropy of CFRP make the machining processes more complex compared to traditional metals.CFRP are prone to surface defects,and the high hardness of carbon fibers and carbon fiber powders leads to severe tool wear and low machining efficiency. To address this issue,it focuses on the structure of tool for milling T800-CFRP through comprehensive simulation analysis and milling tests,and analyzes the impact of tool structure on tool life and machining surface quality in terms of tool wear,surface roughness,and burr factors during the milling. Take tool flank wear width (VB),surface roughness (S_a),and burr factor (F_b) as optimization objectives,mapping relationships and a comprehensive evaluation model between these factors and tool parameters such as teeth of tool,rake angle,and clearance angle are established. Subsequently,using a Whale Optimization Algorithm (WOA),the optimal tool structure parameters are determined and validated through test. The results show a reduction of 16.95 % in tool wear,a decrease of 32.41 % in surface roughness,and a reduction of 52.93 % in burr factor.

The recast layer formed on the surface of a workpiece after Electrical Discharge Machining (EDM) significantly impacts the surface integrity and mechanical properties of the workpiece.The Recast Layer Thickness (RLT) has become an important process parameter in EDM,especially critical in EDM of titanium alloys. The RLT is primarily affected by electrical parameters. Taking the titanium alloy Ti6Al4V as a case,first,the influences law of main electrical parameters (peak current,pulse duration,duty cycle,and gap voltage) on the RLT were discussed.Furthermore,based on the impact of the recast layer on surface roughness and material removal rate,an optimized electrical parameter combination was conducted considering multiple objectives including RLT,surface roughness,and material removal rate. Finally,the principles for electrical parameter selection were summarized in accordance with different RLT requirements. Experiments verified that while the optimal electrical parameter combination achieved a thin RLT and low surface roughness while realizing an improved 2.76 times material removal rate.

Since the aircraft is continuously subjected to vibratory loads during flight process,the self-locking slotted nut-bolt connection pair is widely used in design to prevent loosening of the bolt and loss of clamping force.Studying the tightening characteristics of the slotted nut-bolt connection pair is of great significance for ensuring the mechanical performance,safety,and reliability of the connected structure.Theoretical analysis was conducted on the tightening process of the slotted nut,and the clamping force-tightening torque relationship formula was corrected.The influence of factors such as slotted nut type,connected material,lubrication conditions,and repeated tightening times on tightening characteristics was investigated through experiments.The results show that the prevailing torque of NASM14144 slotted nut is increased by 125.9 % and the torque coefficient is slightly decreased compared with the lower NASM14145 slotted nut.Torque coefficient and its fluctuation can be effectively reduced by saturated lubrication method,and lubrication of the nut-plate bonding surface is less effective.In the process of repeated tightening,the prevailing torque of NASM14144 nut was reduced and the torque coefficient was significantly increased,while the tightening characteristics of NASM14145 nut did not change significantly.

In order to realize the automatic crack detection of train wheel,a crack recognition and measurement algorithm based on machine vision is proposed. It reduces the image noise,improves the contrast of the image features,proposes crack feature segmentation algorithm, extracts the aspect ratio of the crack area,and completes the crack classification and recognition according to the connected domain information.Finally,the method is used to measure the crack length.Experiments show that the proposed method can effectively and accurately detect the cracks,with recall of 98.56 %,accuracy of 91.12 % and identification speed of 48.5 ms.

To ensure that the single-drum roller maintains stable steering during lane-changing compaction and guarantees compaction quality,a lane-changing path planning method was introduced.In this method,the smoothness of the single-drum roller′s lane-changing trajectory,stability of steering,and energy consumption during lane-changing operations were taken as optimization objectives.5th-order Bezier curve was used as the lane changing path curve. An articulated kinematic model was developed to establish a correspondence between the states of the lane-changing path points. The Light Spectrum Optimizer (LSO) algorithm was employed to optimize the coordinates of unknown key control points in the 5th-order Bezier curve,resulting in an approximate optimal lane-changing path. Taking a certain type of single-drum roller as an example,it is shown by simulation and test results that the curves planned by this method have a heading angle and curvature of 0 at both the starting and ending points,with continuous curvature throughout the entire trajectory. This complies with the operational requirements of the single-drum roller. In comparison to document [10] methods,the optimal changing path curves planned by this method exhibit a reduction of 3.8 % in maximum lateral error and 16.7 % in average lateral error. Furthermore,the maximum curvature and average curvature decrease by 18.0 % and 9.3 % respectively. The average fuel consumption of the vehicle also diminishes by 3.8 %. The research outcomes provide practical application reference value for unmanned operation of single-drum roller.

Aiming at the problem of the uncontrolled motion of the functional layer of the multilayer coaxial system of the direct-drive VICTS satellite antenna caused by the carrier impact, a fault-tolerant control algorithm for the rampant phenomenon was carried out. Firstly, the mathematical model and system composition of the multilayer coaxial direct-drive servo system were analyzed. Secondly, based on the motion state of the out-of-control layer and the conditions of the impact fault, a new type of fault-tolerant control algorithm for impact faults was put forward, which consists of three parts, that is planning the new motion state according to the current state of the out-of-control layer when the out-of-control occurs, smoothly switching to the original condition after the out-of-control was recovered, and adopting the real-time speed to predict and compensate control system delay. Finally, corresponding experiments were designed to verify the effectiveness of the proposed fault-tolerant control system for faults occurring in the acceleration, uniform speed, and deceleration segments, as well as for the upper and lower layers under various working conditions. The research is of great reference significance for improving the disturbance resistance of satellite antennas.

A fault diagnosis method based on adaptive Locality Preserving Projection (LPP) feature dimensionality reduction and improved Variable Predictive Model based Class Discriminate (VPMCD) was proposed to solve the issues of high fault feature dimensionality and high time consumption caused by pattern recognition in mechanical system condition monitoring and fault diagnosis. Firstly,time-frequency domain features,energy features,and complexity features were extracted from rolling bearing vibration signals to form a high-dimensional fault feature dataset;secondly,the high-dimensional fault feature set was downgraded by using the adaptive LPP method to obtain the low-dimensional sensitive fault features;lastly,the low-dimensional features were classified and recognized using the improved VPMCD method,and then the type of faults was judged. The analysis of rolling bearing fault diagnosis experiments showed that the adaptive LPP method overcomes the defect of manual pardameter selection in the LPP method,and has less computational time on the basis of obtaining low dimensional sensitive fault features.Compared with methods such as PCA,LTSA,LLTSA,Isomap,LLE,etc,it had obvious advantages;the improved VPMCD method can overcome the contingency and one-sided nature of the artificial selection model,and achieve 99.4 % diagnostic accuracy in the identification of 10 fault states of rolling bearings. Compared with the optimization parameter support vector machine method,it reduced the identification time and improved the efficiency of fault diagnosis,which has certain advantages.