Abstract:To study the development status of wearable soft upper limb exoskeleton and its key technical challenges, the current literature in this field was analyzed and summarized. Exoskeletons can effectively provide functions such as protection and support to address limb fatigue and physical function decline resulting from high-intensity and repetitive work, as well as limb movement disorders caused by stroke or occupational diseases. Additionally, they have the capability to restore or enhance human movement ability through additional power and functionality. Wearable soft exoskeletons, as a new development direction of exoskeletons, have obvious advantages over traditional rigid exoskeletons, such as structural flexibility, human-machine interaction, and wearable comfort. Firstly, this paper provides a detailed analysis of three main driving methods of soft upper limb exoskeleton (rope drive, pneumatic, shape memory alloy). The relevant research results and corresponding structural characteristics of different driving methods are throughly examined. Then, the key technical challenges of soft upper limb exoskeleton are analyzed and expounded from four aspects: structure, material, control and auxiliary technology. Finally, considering the needs of exoskeleton applications in different fields, future trends in soft upper limb exoskeleton technology are speculated to focus on flexibility, comfort, compliance and intelligence. This study shows that the technology for wearable soft upper limb exoskeletons is still in its early stages, with many technical challenges to be solved. Futhurmore, breakthroughs in key technological challenges can be facilitated by novel soft actuators, soft sensors and other related advancements.

Abstract:To further realize lightweighting of the tank bottom structure of liquid launch vehicle tanks, a parametric approach is proposed by considering the load characteristics of existing tank bottoms (thickness parameters and the theoretical relationship with internal pressure during rocket operation) under actual working conditions. The residual strength coefficient is proposed as a design load index of the storage tank bottom, and a design criterion of the tank bottom thickness is established by combining the working conditions. When the residual strength coefficient is not less than 1, the tank bottom thickness is considered satisfactory, meeting the engineering needs, and the thickness of the tank bottom is optimized based on this criterion. According to the design criterion, the relationship between the opening and the bottom thickness can be established, and the critical thickness value of the bottom of the storage tank can be determined more accurately. The established bottom thickness design criterion can be used to verify the internal pressure bearing capacity of the designed storage tank bottom. The usability of the design criterion is validated by using actual working condition data, and a thickness partitioning and lightweighting method for spinning-type tank bottom is proposed. In addition, a multi-constraint evaluation model for the opening of the tank bottom is established based on the interaction of the inputs and outputs of the piping and sensor interfaces of the tank bottom. The specific practicality of the method and automated modeling are realized through a parametric platform. The results show that the thickness partitioning lightweighting method for spinning-type tank bottoms can realize an average weight reduction of about 30% for tank bottoms. The parametric platform and automated modeling provide a new method to improve the efficiency of storage tank bottoms.

Abstract:To improve the performance of variable area wing and realize smooth and flexible deformation, a new variable area wing design based on negative Poisson’s ratio honeycomb structure is proposed. Firstly, the negative Poisson’s ratio honeycomb structure element is applied to the design of variable area wing. By using the auxetic characteristics of the negative Poisson’s ratio element, the wing structure undergoes both span direction and chord direction deformation, so as to achieve greater area change. Then, in order to realize the deformation control of variable area wing structure, a new type of honeycomb structure unit with local negative Poisson’s ratio adjustable is designed. The control rules for its relative elastic modulus and Poisson’s ratio are analyzed by finite element simulation. Finally, by optimizing the parameters of the honeycomb structure unit in the wing structure, the deformation control ability of honeycomb structure unit is validated. The results show that when the deformation of the wing structure along the span direction is 10.0%, the variable-area wing achieves a 23.9% area change. Furthermore, the deformed contour of the wing structure matches the target contour well, with a shape error of only 1.09%. The wing structure also exhibits good bearing performance. For a variable area wing structure made of 7075 aluminum alloy, the maximum out-of plane-displacement is 0.645 mm under the aerodynamic load of 15 kPa. The feasibility of variable area wing design based on negative Poisson’s ratio honeycomb structure is preliminarily validated, which provides a new idea for the design of variable area wing structures.

Abstract:To decrease landing velocity of parafoil system and improve landing safety of payload, a method for determining the optimal flare landing altitude was proposed, and a study on the influencing factors and calculation models of relative flare landing altitude and landing velocity was completed. Firstly, a two-body nine-degree-of-freedom(DOF) dynamic model of the parafoil system and a coupled aerodynamic characteristic model of flare landing control were established, providing a more realistic simulation of the motion performance of the parafoil system under control between two bodies. The velocity and attitude changes of the parafoil system under flare landing control were studied, and the numerical results were consistent with the results in the literature, with a maximum error of 8.20% in glide ratio. Secondly, based on this model, with the minimum vertical landing velocity as the optimization objective, the optimal landing altitude was determined using the time dichotomy method, and the impact of flare maneuver timing on the landing velocity was analyzed. Then, simulation calculations were conducted on the optimal landing altitude under different initial conditions, wing load, landing altitude, and attack angle. The formula fitting of relative flare altitude and landing velocity was completed by the least squares method. It was found that the initial parameters have a minimal effect on the optimal landing altitude. As the wing load and landing altitude increase, the landing velocity and relative landing altitude also increase. The attack angle has a minor impact on the landing velocity, but an increase in the attack angle leads to an increase in the height of flare landing. The relative flare altitude and landing velocity calculation model proposed in this paper is in goof agreement with the numerical calculation results, with a maximum error less than 4.00%, indicating that the calculation model has good applicability.

Abstract:To solve the complex problem of multi-projectile-multi-phase cooperative trajectory programming, an augmented centralized collaborative trajectory programming method (AC-CTPM) is proposed. Firstly, a five-phase trajectory programming model is established based on the characteristics of each phase in the flight process of guided projectiles. Then, the five-phase trajectory programming problems of n_p guided projectiles are combined and extended to a more complex 5np phases optimal control problem (OCP). The multi-phase Radau pseudo-spectral method is used to discretize the infinite-dimensional OCP into a finite-dimensional nonlinear programming problem (NLP), which is finally solved using the mature NLP solver SNOPT. To improve the efficiency of solving the complex 5n_p phases OCP, in AC-CTPM, we propose an initial guess value acquisition method (IGVAM) for converting 2D scheme trajectories into 3D predicted trajectories in cooperative trajectory programming problem. Each guided projectile establishes a new ground coordinate system with its own launch point as the origin. Within this new coordinate system, 2D scheme trajectories of the projectile are rapidly programmed. Subsequently, by expanding and transforming the coordinates, the programmed 2D trajectories in the new coordinate system are transformed into the 3D scheme trajectory. The 3D scheme trajectories of each projectile are combined to form the initial prediction of the cooperative trajectory programming problem. By applying the AC-CTPM algorithm, we conducted simulation-based solving for the scenario of simultaneous impact tasks with single-gun multiple-firing and multiple-gun salvo. We obtained cooperative trajectory solutions that satisfy the projectile self-constraints and cooperative constraints, which verifies the effectiveness of AC-CTPM algorithm. Simulation comparisons with distributed collaborative trajectory programming algorithm (D-CTPM) and traditional centralized collaborative trajectory programming algorithm (TC-CTPM) shows that the objective function of the cooperative scheme trajectory programmed by AC-CTPM algorithm is on average 5.07% better than that of TC-CTPM algorithm and 32.98% better than that of D-CTPM algorithm on average, while the solution time of the AC-CTPM algorithm is reduced by 86.48% compared with TC-CTPM algorithm and by 82.36% compared with D-CTPM algorithm, which verifies the superiority of the AC-CTPM algorithm.

Abstract:To accurately predict the curing deformation of sandwich structures with variable thickness layup, a numerical simulation of the curing process of AS4/8551 carbon fiber/epoxy resin composite-Nomex honeycomb sandwich structure was conducted based on the thermal-chemical-structural multiphysics coupling method. Considering the influence of material time-varying characteristics, a three dimensional finite element model of sandwich structure was established by combining the transient linear elastic constitutive model of composites, micromechanics theory, and an improved Gibson equivalent theory. The distribution relationship between the curing degree field, temperature field, and stress-strain field of the structure throughout the entire curing cycle was studied. The simulation results were compared and validated against existing experimental data. Finally, the influence of pre-curing process on the structural rebound deformation was analyzed through the analytical model. The results show that the established finite element model can accurately reflect the curing process of the structure, with average prediction error of 4.8% and a maximum prediction error of no more than 6.0% for curing deformation. The variable thickness layup design has a significant impact on the curing stress of the thinner panel, resulting in upward shear stress along the thickness direction. During the cooling stage, these stresses concentrate at the ends of the structure and transforms into structural warping. The pre-curing preocess of the panels weakens the influence of curing heat release and material anisotropy on the curing deformation of the sandwich structure. At a pre-curing degree of 0.25, the reduction in maximum curing deformation reaches 14.78%. The research results provide important references for improving the manufacturing accuracy and optimizing the processes of complex designed honeycomb sandwich parts.

Abstract:To address the limitatios of global outlier detection methods in detecting local outliers and the performance degradation of local anomaly factors in the presence of a large number of local outliers, this paper proposes an outlier detection and interpretation method based on an improved fast search and discovery density peak clustering algorithm (KDPC), utilizing k-nearest neighbor (KNN) and kernel density estimation (KDE) methods. This method enables simultaneous analysis of both global and local data points. Firstly, the local density of data points is calculated using the k-nearest neighbor and kernel density estimation methods instead of the local density based on the truncation distance in the traditional DPC algorithm. Secondly, the sum of the k-nearest neighbor distances of the data points is used as the global outlier and the cluster density as well as the local outliers of the data points are calculated by the KDPC clustering algorithm. Finally, the global and local outliers of the data points are multiplied as the final anomaly score. The Top-n data points with the highest anomaly score is selected as the outlier, and the global and local outliers are interpreted by constructing a global-local outlier decision diagram. Experiments were conducted using both artificial and UCI datasets and our method was compared with 10 commonly used outlier detection methods. The results show that our method achieves high detection accuracy and performance for both global and local outliers. Moreover, the AUC performance is minimally affected by the k-value. Additionally, our method is also used to analyze NBA player data, further demonstrating its practicality and effectiveness.

Abstract:To solve the problem of control performance degradation caused by unknown interference in maglev system, an active disturbance rejection control method (adaptive linear active disturbance rejection control,ALADRC) based on gradient information adaptive observation bandwidth is proposed. Firstly, a nonlinear model of single-point suspension system is established, and the stability region of auto-disturbance rejection parameter is deduced theoretically, and the concept of critical bandwidth is obtained. Secondly, the iterative formula of the adaptive linear extended observer is derived based on the minimization of the observation error, which enhances the stability of the system parameters. Even if the current bandwidth may diverge the system, ALADRC can automatically adjust to the relatively optimal stable bandwidth point, making self-tuning feasible. At the same time, when encountering disturbances, the bandwidth will be adjusted accordingly to enhance the immunity of the system. Then, the convergence of the observed bandwidth of ALADRC under different learning rates is simulated. It is concluded that higher learning rate leads to faster convergence of the observed bandwidth, and the final convergence bandwidth value is relatively larger. In addition, the order of magnitude of the learning rate can be reversely derived according to the critical bandwidth and the system unit scale to simplify the adjustment of the learning rate. Finally, the control performance of PID(proportional integral derivative), LADRC(linear active disturbance rejection control) and ALADRC are compared respectively on a single-point suspension platform. The experimental results show that, compared with PID and LADRC, ALADRC has the best comprehensive control performance, which can realize fast non-overshoot flotation with excellent self-regulation and disturbance immunity.

Abstract:To solve the problems of imperfect dynamic model and difficulty in obtaining nonlinear dynamic characteristics of non-circular planetary gear systems, a dynamic modeling method of non-circular planetary gear systems is proposed. The focus is on the dynamic response mechanism of the system under time-varying parameter excitation, aiming to study the nonlinear dynamic characteristics of non-circular planetary gear systems. In order to accurately analyze the nonlinear vibration of the system, the backlash function of non-circular gear is fitted. By considering the combined effects of tooth surface friction, time-varying meshing stiffness, viscoelastic damping and static transfer error, the variable coupling of nonlinear equations is eliminated by introducing relative displacement coordinates. On this basis, the dynamic model of non-circular planetary gear systems is established, and the fourth-order variable step Runge-Kutta numerical method is used to solve the nonlinear dynamic equations of the system. Bifurcation diagram, time domain diagram, phase trajectory and Poincaré map are obtained to reveal the distribution pattern of system’s the dynamic response under the influence of control parameters such as damping, tooth surface friction and time-varying meshing stiffness. The results show that with the different values of excitation parameters, the system presents a transition state between chaotic and periodic motion depending on the values of various excitation parameters. By selecting appropriate excitation parameters, the time interval between chaos and periodic motion can be reduced, leading to a quicker transition to a stable motion state. The research results can provide a theoretical basis for suppressing nonlinear vibrations of non-circular planetary gear systems and predicting the dynamic behavior of the system.

Abstract:To accurately predict the acoustic radiation of rotating sound field, a prediction method of Kirchhoff rotating sound field is proposed. Based on the acoustic radiation of rotating point sound source, using spherical harmonics, Legendre function and dipole geometry, the frequency domain analytical expressions of acoustic radiation of rotating transverse and longitudinal dipole sources are constructed. The contributions of transverse and longitudinal dipole sources to acoustic radiation of rotating sound field are quantified. By introducing Kirchhoff integral and combining rotating point source with dipole source, the rotating Kirchhoff source is constructed. The mathematical model of acoustic radiation prediction of rotating Kirchhoff source and its analytical expression of sound pressure are derived. The key factors influencing its cutoff threshold for analyzing infinite harmonic order truncation are determined. Through numerical simulation, the effects of fundamental frequency, rotation frequency and rotation radius on the rotating sound field are discussed when Ma<1. The spatial distribution of sound pressure, Doppler and directivity characteristics of the rotating sound field are analyzed. The validity of the rotated Kirchhoff source is verified by the equivalence verification of the sound field, with a relative error of the sound pressure value at any arbitrary point being within 0.05, which further demonstrates the effectiveness of the rotating Kirchhoff source. The results obtained from experimental testing in a semi-anechoic chamber confirm the effectiveness and accuracy of the Kirchhoff integral method, consistent with the simulations. This method effectively improves the prediction accuracy of the rotating sound radiation by replacing the traditional point source superposition with the constructed rotating Kirchhoff source. These research findings hold significant theoretical reference value and significance for the control of rotating machinery radiation noise and the design of low-noise rotation structures.

Abstract:To improve the processing quality of complex curved surfaces and their features in a five-axis hybrid mechanism, a time-optimal speed planning and precise interpolation method for accurately identifying curvature points is proposed. First, the centripetal method is used to generate path node parameters, and intensive processing is performed to generate speed node parameters. Secondly, a B-spline is used to describe the velocity curve, and the third-order constraint model is transformed into a linear model through pseudo-jerk. Then, the speed node parameters are used as segmentation points to construct the time integral function for each segment path, and an adaptive Simpson’s integration method is used to solve the function. Finally, the obtained discrete point information is input to the motion control card for trajectory processing. The experimental results show that the proposed research model in this paper can quickly converge to the global optimum, effectively reduce the curvature point velocity and quickly recover its neighborhood velocity. The total path time calculated only fluctuates by 3.5 μs, comparable to the accuracy achieved by conventional interpolation methods but with a shorter convergence time. The maximum interpolation errors of position and angle are 0.76×10^-3 mm and 0.9×10^-3° respectively, which are smaller than the encoder resolution and meet the processing requirements. Specifically, at the extreme curvature, the proposed method reduces the interpolation error by 95.37% compared to conventional approaches. Therefore, the speed node parameters generated based on the path curve have better curvature identification, and the total path time calculated by constructing the time integral function for each segment path has higher robustness and efficiency.

Abstract:To enhance the perception ability of snow field environments during nighttime and improve both the maintenance quality and operational efficiency of ski pistes, this paper proposes a novel segmentation algorithm based on time-domain waveform characteristics detection using vehicle-mounted LiDAR for the snow groomer and an improved simultaneous localization and mapping (SLAM) algorithm in ski pistes. First, based on a model of reflectivity distribution of the point cloud, snow noise points are identified and processed using linear interpolation to maintain the continuity of the time-domain waveform. Consequently, the grid is partitioned into specific scan perspectives to accurately estimate the real-time slope based on the elevation variation between neighboring grids. Then, a corresponding criterion for detecting step values in the time-domain waveforms is established to select the boundary points between pistes and obstacles according to the typical obstacles in alpine ski resorts. The segmentation can be achieved by enveloping the step values. Moreover, based on the segmentation results, features are classified and matched using feature constraint methods to improve the mapping speed. Finally, tests were conducted on the pistes of the Wanlong Ski Resort in Zhangjiakou. Experimental results show that the proposed algorithm for segmenting ski pistes achieves an average processing time of 2.36 ms per single-frame point cloud, while achieving an accuracy rate of over 98.54%. Moreover, when integrated into an improved SLAM approach with snow piste segmentation capabilities, it can achieve segmentation accurately while demonstrating superior mapping accuracy performance, as well as significantly reduced computational time.

Abstract:To realize the recovery function of the fuze safety system state and meet the needs of the global safety control of the fuze, a duplex piezoelectric drive is proposed for application in electromechanical safety systems. Firstly, the bipedal piezoelectric drive was referred to and the structure design of the duplex piezoelectric drive was carried out according to the design requirements, and the working mechanism was analyzed. Subsequently, the structure of the designed duplex piezoelectric driver was optimized, and the motion trajectory equation of the driving foot was given based on the optimization results, which ensures that the driving foot forms an elliptical-like motion trajectory. Then, an experimental platform was built to test and analyze the drive characteristics of the duplex piezoelectric drive prototype. The optimal working frequency was determined, and the relationship curve between the round-trip motion speed and the excitation voltage peak-peak of the duplex piezoelectric driver was obtained. Finally, in consideration of the high impact working environment of the fuze, the anti-high overload measures of the duplex piezoelectric driver were proposed, and the anti-high impact overload test of the piezoelectric driver was carried out. The results showed that the motion speed of the piezoelectric driver is positively correlated with the peak-to-peak excitation voltage, and the movement speed of the piezoelectric driver exhibits the optimal motion speed under the action of the excitation voltage with a frequency of 130 Hz. The duplex piezoelectric drive was able to work properly under the shock load of 20 kg, which verifies the effectiveness of the anti-high overload measures. Furthermore, the feasibility of the duplexed piezoelectric drive in achieving the recovery funtion of the fuze safety state was further verified.

Abstract:To quickly and accurately detect the gradation of reclaimed asphalt pavement (RAP) and improve the detection efficiency of RAP gradation while reducing the influence of manual operation on detection results, this study proposes a method for integrated detection of RAP moisture content, RAP oil-stone ratio, and gradation by combining currently commonly used equipment and methods for testing RAP performance. At the same time, in view of current issues in RAP detection, a new type of automatic detection equipment for RAP gradation is designed, enabling real-time and automated detection of RAP gradation. Firstly, according to the functional requirements of RAP gradation detaction, the overall structure of the detection equipment is designed. Secondly, a simulation model of the key structure of the testing equipment, the vibrating screening unit, is established, and the whole screening process is simulated by EDEM discrete element simulation software. A controlled variable method is used to compare and analyze the aggregate particles in the vibrating screen under different parameters such as inclination angle, vibration frequency, vibration direction angle. Finally, the vibrating screen is optimized for the optimal screening efficiency that meets the requirements of the standard. The results show that when the inclination angle of the vibrating screen is 3°, the amplitude is 4mm, the frequency is 16 Hz, and the vibration direction angle is 63°, the screening efficiency of each layer of the vibrating screen mesh reaches over 91%, meeting the practical needs. This demonstrate that the automatic real-time RAP gradation detection system is capable of measuring RAP moisture content, asphalt content, and gradation, providing a possibility for the development of intelligent regenerative mixing stations and can also replace manual as a new means of daily asphalt mixture gradation monitoring.

Abstract:Corner cracking phenomenon in square and rectangular pipes during roll bending, which has become a key issue that seriously restricts the quality of square rectangular tubes. In order to address this issue and find a way to control the cracking defect, a comprehensive study was conducted. Firstly, the mechanical properties of the MS1180 material were obtained by uniaxial tensile, notched tensile and plane strain experiments. Three fracture criteria, Ayada, Rice-Tracey and standardized Cockroft-Latham criteria, were calibrated using these test date, and the criterion with the smallest prediction error was selected. This criterion was then used to construct a square rectangular tube roll bending cracking model. Next, using COPRA RF design software and finite element MARC simulation professional software of roll bending, a three-dimensional finite element model for continuous roll bending of square rectangular tube was established in combination with the actual production conditions. The accuracy of the model was verified by roll bending experiments. Finally, scanning electron microscopy and metallographic microscope were used to observe the cracks and fractures of the rectangular tube. The stress-strain distribution of the square rectangular tube during continuous roll bending was investigated using the finite element model, and the effects pass number, corner forming radius and frame spacing on the stress-strain distribution of the corner of the rectangular tube were analyzed. It is found that the initiation of cracking point of the material occurs near the outer layer of the corner. In addition, the cracking fracture is analyzed, which reveals that the cracking mechanism is quasi-cleavage fracture, where excessive principal stress on the corner shear surface leads to cracking. Increasing the number of roll bending passes, the forming radius of the square rectangular pipe corner and the spacing between the frames can effectively reduce the occurrence of cracking issues. These findings provide a theoretical basis for solving the problem of cracking in the corners of square rectangular pipes in the future.

Abstract:To improve the safety performance of offshore operation equipment and realize the real-time prediction of motion of offshore structures, a hybrid deep learning model combining convolutional neural network (CNN) and long short-term memory (LSTM) methods is used in this study. The hybrid model extracts the features from motion data by CNN, and utilizes LSTM to learn the temporal relationship among the extracted features. Additionally, Bayesian optimization algorithm is introduced to optimize the hyperparameters of the hybrid model. Firstly, the numerical simulation of the offshore platform is carried out, and the obtained surge motion data is used as experimental data. Secondly, the experimental dataset is divided into training set, verification set and test set. The training and verification set are used for model training and validation to obtain the optimal prediction models for 6 s, 12 s and 18 s of motion. The performance of the developed models is compared with that of the LSTM model using the testing set. The results show that the hybrid model, compared with the LSTM model, can improve the prediction accuracy by 15% to 30% for 6 s, 12 s and 18 s predictions. Furthermore, this study also investigates the relationship between prediction accuracy and input duration as well as prediction duration. The results suggest that the input duration has a minimal impact on the prediction accuracy, while the prediction accuracy shows a linear downward trend with the increase of the prediction duration. Finally, combined with the training time, the hybrid model in this paper demonstrates advantages over LSTM and other models.