Taking the double-stage hammer crusher as the research object,considering the load sequence effect and the load interaction effect on pin shaft fatigue damage,the Manson-Halford (M-H) nonlinear fatigue damage model was modified,and the accuracy of the modified model was verified through experimental data. The dynamic load of the pin shaft was obtained through MFBD-DEM bidirectional coupling method,which takes into account the nonlinear collision contact between the hammer head and the pin shaft and the influence of material particles on the force of the pin shaft. Finally,the modified M-H model was used for fatigue analysis of the pin shaft.The results show that compared with the existing model,the modified M-H model has the smallest relative error in the validation of examples. Based on the modified M-H model,the minimum fatigue life of the pin shaft is calculated to be 9.918×10⁶ cycles (165 h). It is reasonable and feasible to use the MFBD-DEM bidirectional coupling method for fatigue analysis of large crushing equipment such as double-stage hammer crushers.

In order to solve the problem of inaccurate planning and coordination difficulties in the multi factory and multi workshop linkage production of automobile manufacturing enterprises,the problem was studied based on the leveling concept in lean production,considering the impact of inventory backlog or insufficient inventory in a limited capacity buffer zone on production stability. A dual level programming model for collaborative mixed flow production scheduling of multiple automobile factories was established.The upper layer establishes a cross factory transfer allocation model with the goal of minimizing the transfer volume between factories,while the lower layer establishes a workshop shift selection model with the goal of minimizing the reserve deviation in the buffer zone. A double layer genetic algorithm was designed to solve the model,and a minimum impact strategy was adopted to standardize the transportation volume and workshop output. The results of double layer optimization and single layer optimization were compared and analyzed through examples,and the scale of the examples was expanded.The simulation experiment results showed that the solution quality of double layer optimization was better,thus verifying the effectiveness and feasibility of the designed model and algorithm.

To achieve precise functional printing on the freeform surface of the hand,a method combining 3D point cloud digital molding process and freeform surface functionalization molding process is proposed. Firstly,the point cloud data of the hand is collected through a 3D scanner,and the surface feature points are smoothed and denoised using adaptive weighted guided filtering technology. Next,a curvature-based adaptive surface geometric sampling algorithm is employed to simplify the point cloud without losing detail features.Subsequently,the optimized point cloud data is used to accurately reconstruct the digital model of the hand,extract its freeform surface coordinates,and design functional circuit patterns on it. Finally,the hand structure is printed using a Fused Deposition Modeling (FDM) system with the NC code generated by computer-aided design and vector graphic editing software,followed by printing electronic skin on the freeform surface of the hand using aerosol jet printing technology. Experimental results show that the point cloud data strategy adopted in this experiment reduces the number of hand scanning points by 80 %,achieving significant simplification. The error range of the hand reverse reconstruction model is within 0.4 mm,showing a high degree of fitting to the physical prototype.The empirical demonstration showcases the potential of electronic skin in the integrated molding of the freeform surface of the hand and provides a technical reference for high-precision functional printing.

To accurately evaluate the effects of economic,environmental protection,and capacity improvement achieved by the equipment cloudification,solve the problem of lacking evaluation methods for equipment cloudification effects,enterprises generally rely on expert experience or economic indicators to evaluate equipment cloudification effect,resulting in strong subjectivity,single dimensionality,and inaccurate evaluation. An equipment cloudification effect evaluation index system for the steel industry has been established based on three dimensions of equipment access,equipment service and overall revenue. An improved entropy weight TOPSIS method is proposed to set indicator weights more accurately,and fuzzy comprehensive evaluation methods are applied to calculate cloudification effect scores. An equipment cloudification effect evaluation system for the steel industry is constructed to provide self-evaluation for steel enterprises,and select 5 typical enterprises′ data to verified that this method can help enterprises evaluate the effect of equipment cloudification and guide enterprises to scientifically carry out equipment cloudification work.

The hydrodynamic characteristics of bionic robotic fish with flexible caudal fin of different shapes were studied. The caudal fin of bionic robotic fish with four shapes has been developed based on the bionic observation results.By conducting hydrodynamic testing experiments,the effects of caudal fin shape,structure,material and motion parameters on hydrodynamic parameters were compared and analyzed. The results indicate that increasing the swing angle and frequency of the caudal fin is beneficial to improve the propulsive performance,but it can also cause instability in swimming;the flexible crescent shaped caudal fin has good propulsion performance;the smaller the aspect ratio,the better the high-frequency swimming performance of the finless caudal fin;the fin ray will reduce the high-frequency swimming performance of the caudal fin.

Nonlinear friction for motorized cylinders is difficult to identify and adversely affects the tracking accuracy of the position of the six-degree-of-freedom Electrically Driven Stewart Platform (EDSP),an improved Gray Wolf Optimization algorithm introducing Levy flight and Cauchy variation (LCGWO) with Levy flight and Cauchy variation is proposed to identify the friction parameters of the electric cylinder,and a feed-forward compensation method based on the friction model is designed. Firstly,a mathematical model of EDSP considering the nonlinear friction of the electric cylinder is developed and the friction is described using the Lugre friction model. Then,considering that the nonlinear friction of the electric cylinder is difficult to identify,an LCGWO is proposed to identify the static and dynamic parameters in the friction model at the same time,and compared and analyzed with the general identification method. Finally,a feed forward compensation algorithm based on the Lugre friction model is designed and experimentally verified. The experimental results show that compared with other algorithms,LCGWO has better convergence speed and prediction accuracy;and the friction compensation of the electric cylinder by the friction feed-forward compensation method based on the friction model can effectively improve the platform′s position tracking accuracy.

Aiming at the problem that the Automated Guided Vehicle (AGV) based on QR code navigation cannot quickly and smoothly eliminate the error when the starting pose deviation is large,a correction system based on auxiliary tracking trajectory and fractional sliding mode controller was proposed. The AGV kinematics and dynamics model were given,and the fractional order sliding mode controller was designed based on the fractional order integral operator and Exponential Super Twisting Algorithm (ESTA). Assistance systems were designed to compensate for possible input saturation issues and enhance the ability to handle transient disturbances. The auxiliary tracking trajectory was generated by uniform cubic B-spline curve,and the genetic algorithm was used to solve the optimal curve under the constraints of curvature and velocity. Stability proof was given by Lyapunov theory. The simulation results show that the system can effectively deal with the problem of excessive deviation of the starting pose,and has faster convergence speed and good anti-interference performance.

In response to the issue of brake squeal noise in a certain automotive disc brake,brake pads with different chamfer structures,shim with different damping layer thicknesses,and the impact of their matching on brake squeal noise were studied.The optimal matching scheme and the original scheme obtained from the research were tested for noise through bench tests.The research results show that among the five types of brake pad chamfer structures,the symmetrical straight chamfer has the best noise reduction effect,and the chamfer of the symmetrical structure is better than the asymmetric structure. The chamfer of the asymmetric structure has a better effect on solving single noise with concentrated frequency,but it is easy to induce new noise;when the thickness of the damping layer of the shim gradually increases,the tendency of squeal noise occurrence shows a trend of first decreasing and then increasing;the reasonable matching of brake pad and shim can effectively improve squealing noise. The noise reduction trend of brake pad with symmetrical chamfer and asymmetric chamfer structures when matched with shim is opposite. Among them,the brake pad with symmetrical oblique chamfer structure has the best noise reduction effect when matched with shim with a damping layer thickness of 0.28 mm,and the noise occurrence rate is reduced by 97.98 % compared to the original plan.

The mathematical model of the high-pressure common rail injection system of automotive engines was established based on the key component parameters,and the simulation using AMESim software was conducted. The accuracy of the simulation model was verified through experimental analysis. Through the simulation analysis of the system′s rail pressure fluctuations and pressure characteristics,it was found that the length and inner diameter of the common rail pipe,and the inner diameter of the high-pressure oil pipes are the important parameters that affect the system′s rail pressure characteristics. For the original common rail pipe and high-pressure oil pipe models,the response surface method was used to optimize and analyze the parameters of the common rail pipe and high-pressure oil pipes,and obtain the optimal size parameters of the common rail pipe and high-pressure oil pipes with the average rail pressure setting value as the target.After optimization,the average rail pressure of automotive engines′ high-pressure common rail injection system improved by 0.65 %,the overall average rail pressure fluctuation decreased by 79.48 %, the average rail pressure fluctuation during a single injection process decreased by 27.89 %, and the average fuel injection pressure increased by 0.63 %.Its fuel injection characteristics have been significantly improved.

Aiming at the focuses on the impact of wheel out-of-round on the profile changes of the wheel surface,a dynamic model for subway vehicles-rail was established using SIMPACK software.Involveing nine different rail cant settings and two different wheel out-of-round conditions,and including analysis of linear and four different radius curves,the influence of rail cant coupling wheel out-of-round on dynamics performance of subway vehicles was analyzed. Evaluation metrics include wheel-rail vertical force,wheel-rail lateral force,derailment coefficient,wheel load reduction rate,wheel-rail displacement,and wear index.Based on entropy weight method,a multi-objective optimization model was established to evaluate the linear riding smoothness and curve passing ability of the vehicle,and to obtain the optimal matching scheme between rail cant and wheel out-of-round.The study indicates that when there is wheel out-of-round,the impact of rail cant changes on lateral smoothness is greater than that on vertical smoothness. The existence of wheel out-of-round will increase the impact of rail cant on wheel-rail vertical force,wheel-rail lateral force,wheel load reduction rate. For linear and curved sections,the optimal rail cant for external or internal rail varies depends on the type of curvature radius. Specifically,the optimal rail cant for the R300,R400,R500 and R600 m is (1/40,1/30),(1/20,1/30),(1/40,1/30),(1/30,1/30) and (1/30,1/30),respectively. When there is no wheel out-of-round,the optimal rail cant for external or internal rail is (1/40,1/30),(1/30,1/40),(1/30,1/30),(1/30,1/30),and (1/40,1/30) respectively. This study provides technical support for wheel maintenance and repair for operational line design.

In order to solve the problems of high-speed trains,such as the deterioration of dynamic performance and the decline of running stability under long operating distance,an active direct feedback and full-state feedback control method are proposed. A nonlinear model of the whole vehicle is established based on Simpack simulation platform to simulate the real running state of the vehicle and the signals collected by real sensors. Based on the MATLAB platform,the vertical linear model of the vehicle is established,and the Kalman filter is used to establish a state observer with reference to the linear model,and the vehicle state quantity is restored in real time according to the set number and type of sensor signals. Using the Sky-Hook control based on direct signal feedback and the Linear Quadratic Regulator (LQR) and H∞ control method based on full state feedback respectively,the vertical full state feedback control algorithm of the whole vehicle is designed to realize the vertical active control of the secondary suspension of the vehicle. Aiming at the straight line operation and fault conditions,the SIMAT joint simulation method is used to simulate and analyze the signal acquisition,state observation and active control loop,and evaluate the effectiveness of the method.Simulation results show that the state observer can realize more accurate state observation of the whole vehicle. Combined with the state observation results,all three control methods can improve the running stability of the vehicle under normal operating conditions,and the vehicle body stability index can be reduced by 19 % at most,and the maximum vibration acceleration can be reduced by 54 %. When the air spring of the front bogie fails,the active control method can ensure the vehicle to run safely to a certain extent.With the H∞ control method,the maximum pitching angle during the simulation time is reduced by 83 %.

Aiming at the expected functional stability caused by internal and external disturbances during longitudinal movement of vehicles,an adaptive cruise control method is designed based on Model Predictive Control (MPC) and improved Active Disturbance Rejection Control (ADRC) strategies. Firstly,the vehicle kinematics model and the safe vehicle spacing model considering the speed of the vehicle ahead were established.Secondly,a model predictive controller and an improved active disturbance rejection controller are designed,and the MPC control algorithm is used to track the vehicle in front,and the tracked vehicle state is taken as the input of the improved active disturbance rejection controller to realize the stable cruise control of the vehicle in the disturbed environment. Finally,the simulation and comparison experiment are carried out. The results show that the adaptive cruise control strategy based on MPC and improved ADRC can effectively suppress the internal and external disturbances caused by distance error,and improve the tracking performance and system stability of the vehicle during the adaptive cruise process.

Aiming at the problem of reduced flexibility and temperature rise during the operation of ball screws caused by excessive frictional torque,a three-dimensional model of ball screws with raceway cutoff symmetry error and raceway radius error was established from its generation mechanism and the influence of different raceway cutoff errors on frictional torque was analyzed based on Adams simulation using Hertzian contact theory. Compared to the measured results,the relative error between the average friction torque generated by the simulated model with raceway radius error and the measured average torque is within 11.41 %,confirming the effectiveness of the simulation model. The simulation experiments have shown that changing the raceway radius can control the average friction torque. Controlling the symmetry error of the raceway profile can reduce the fluctuation range of the friction torque,providing a theoretical reference for reducing the friction torque of ball screw pairs and improving their smoothness.

In response to the issues of reliance on manual expertise,slow straightening speed,and low yield rate of quality products in traditional straightening processes,a straightening intelligent optimization process prediction model based on the Dung Beetle Optimizer (DBO) algorithm optimized Back Propagation (BP) neural network was proposed. Considering the influences of parameters such as plate thickness,elastic modulus,yield strength,and plastic ratio of the plate during the straightening process,as well as the issues of BP neural networks easily falling into local optima and weak generalization ability,the DBO algorithm was introduced.The model was trained using a training set consisting of 1 000 data points. A comparison between the BP neural network prediction model and the particle swarm algorithm optimized BP prediction model was conducted.Results show that the percentage errors of the DBO algorithm optimized BP neural network prediction model for the adjustment amounts of the head and tail rollers are within 0.5 % and 0.6 % respectively,and the total straightening force percentage error is within 0.6 %.The proposed model demonstrates high reference value for accurate prediction of the straightening process.

The visual system of gantry ion parts groove cutting platform is slow to recognize the cutting parts,inaccurate contour positioning information and mismatching. An efficient matching and positioning method combining Hu moment and image registration is presented. Firstly,the threshold segmentation algorithm is used to reduce the noise of the picture,separate the background and foreground of the part,identify the outline of the part,and realize the rapid matching of the graphic library based on Hu moment. Secondly,coordinate transformation is carried out on the read CAD graphics,and an initial value of rotation Angle is found based on the contour centroid,and a function model is established. The iterative optimal solution is optimized using the idea of genetic algorithm. Finally,the contour path of the CAD template is used to correct the positioning information of the contour of the part. The experimental results show that the proposed method can quickly and accurately search the corresponding parts from the CAD library and realize the positioning information correction,and the overall image error after correction is about 6 pixels.

To further improve the accuracy of tool wear value monitoring in the cutting machining process,a tool wear monitoring model that integrated the residual block and Swin-Transformer model was proposed.Firstly,the grouped convolutional residual block was used to extract the features of the signal.Then,the chunked sliding window self-attention mechanism in the Swin-Transformer model was used to translate the extracted features.Finally,the tool wear value prediction was realized through the regression layer.The experimental results show that the Swin-Transformer model fusing a layer of residual blocks with a layer of stage mechanism can effectively fuse the global information of tool wear state monitoring signals,which not only has a simple model structure but also has a higher monitoring accuracy compared with other Swin-Transformer models,and the MSE,MAE,and R² verified by utilizing the PHM2010 dataset reached 4.471 9,1.467 5,and 0.995 8,respectively.

In order to solve the problems of the traditional A^* algorithm in the hose harness path planning,such as too many search nodes,too large bending,and difficult to meet a variety of routing constraints,a hose harness automatic layout method based on the improved bidirectional A^* algorithm is proposed.Firstly,in order to meet the interface direction constraints at both ends of the pipeline,a two-way search strategy is adopted to dynamically define the forward and reverse search target nodes. Secondly,double weight parameters are introduced to optimize the evaluation function and add the bending cost to reduce the bending point and bending angle of the pipeline. A neighborhood search method based on adaptive step size is proposed,and the parent inflection point and bending constraint are set during the search process to improve the search efficiency and meet the requirements of the minimum bending radius of the pipeline. Finally,aiming at the problems of many inflection points and unsmooth path,a hose fairing method based on node filtering and B-spline curve interpolation is proposed. The simulation results show that,compared with the traditional bidirectional A^* algorithm,the number of pipeline path bends and the number of search path nodes planned by the proposed method are greatly reduced,and the generated hose path is smooth and meets the actual routing constraints.

Reliability is an important indicator of the quality and stability of remanufactured parts. Compared with new product parts,there are many reliability factors affecting remanufactured parts,complex mechanism relationships,and high residual value of blanks,which makes it difficult to carry out a large number of reliability tests,resulting in a small sample size of reliability data and low reliability prediction accuracy of remanufactured parts.Therefore,a reliability prediction method for remanufactured parts based on deep transfer learning is proposed. Firstly,the influence of personalized process in the manufacturing stage on the reliability of remanufactured parts is analyzed,the reliability is predicted by combining the operation data of the service stage,and the sample expansion is carried out by introducing the service stage operation data and manufacturing stage process quality data of new products and parts of different models of the same product,and the principal component analysis method is used to obtain key characteristic data such as running time,status information,processing accuracy and other key characteristics that affect reliability,and the source domain dataset is constructed. Secondly,a convolutional neural network is used to construct a deep learning model between key feature data and reliability in the source domain,taking the remanufactured parts data as the target domain dataset,and applying the model migration to the reliability prediction of remanufactured parts through the adaptive gradient algorithm to improve the prediction accuracy. Finally,taking the parts that need to be remanufactured in a CNC machine tool as an example,the effectiveness of the proposed prediction method is verified.

In order to meet the needs of precise control of the speed,feed distance, and cutting force of the motor spindle in the process of precision machining, an integrated motor spindle with rotation,micro-feed and force sensing functions is proposed by combining the permanent magnet synchronous motor and giant magnetostrictive actuator.In order to verify the structural of the main integrated motor spindle force sensing part,based on the magnetic circuit method and finite element analysis,the relationship between the micro-feed distance of the integrated motor spindle, the induced voltage of the outer coil, and the external load is obtained. Finally,in order to verify the accuracy of the simulation,an integrated motor spindle force sensing and micro-feed test platform is built. The results show that in this magnetic circuit model design,the magnetic flux density of the integrated motor spindle can exceed 0.551 9 T,the uniformity of magnetic flux density is greater than 77.85 %,and the micro feed distance of the distance of the integrated motor spindle can reach 26.5 μm. The induced voltage of the outer coil is inversely related to the external load,and the optimal impressed energizing current of the inner coil is 5 A. The research results show that the design of the integrated motor spindle with force sensing and micro-feed function is reasonable and feasible,which lays a foundation for further research and precise control of the integrated motor spindle.