Search

Inverters having high voltage levels, high power density, and high integration are widely used. However, many high-frequency switch units also increase the probability of failure. Therefore, developing an accurate and stable fault diagnosis method is necessary. This paper proposes a fault diagnosis algorithm based on deep learning and the evidence reasoning (ER) rule. It not only ensures high diagnostic accuracy, but also enhances the stability of the diagnostic results. The algorithm takes the three-phase voltage source inverter as the research object and extracts the three-phase current signals with different types of faults as features. First, Convolutional and Deep Neural Network methods were utilized independently to determine a preliminary diagnosis. Second, the softmax functions of the Convolutional and Deep Neural Network outputs provided the probability distribution of the fault category, which was used as the evidence body for the ER rule to construct the fusion diagnosis. In addition, a new method of determining the reliability and the importance factors of the evidence was proposed in which the evaluation index of the deep-learning diagnosis result was applied. Finally, the final classification result was obtained using the ER rule. The proposed method can effectively enhance the accuracy and robustness compared with a single classifier.

Innovation training in engineering is an important facet of technical education in universities across China. Robotics training is a new course that has been developed using an informatization-based engineering training system at the Engineering Innovation Practice Center of the Harbin Institute of Technology. In this study, we propose a pedagogical method that combines virtual and on-site modes of teaching. Feedback obtained from students enrolled in the course showed a positive response to it. They claimed that they gained valuable knowledge from it that enabled them to carry out the relevant tasks in a better manner and more quickly. The feasibility of the proposed scheme was verified by a virtual simulation.

The soft ground and stones on the surface of Mars may cause sinkage of and damage to the wheels of a Mars rover. Therefore, we analyzed the performance of a wheel-step Mars rover from the perspective of terramechanics and structural mechanics. Using China’s Mars rover wheel prototype and wheel-soil interaction testbed, we obtained the driving performance of the wheels of a Mars rover under various conditions, including full skidding conditions. The vertical load set in the tests was determined using the gravity of Mars and the mass of the wheel-step Mars rover. The results indicate that the driving torque, sinkage, and resistance coefficient have a linear relationship with the wheel vertical load. An analysis of the structural mechanical characteristics of the wheel of the Mars rover was conducted by testing the radial, axial, torsional, and deflection stiffness. We found that the wheel ribs can improve the stiffness of the wheel but may reduce its driving performance. The analysis methods and evaluation indices can be used to analyze the performance of the wheels of other Mars rovers. Furthermore, the findings of this study can be used to optimize wheel design and motion control of wheel-step Mars exploration rovers.

In this paper, a reinforcement learning-based adaptive control algorithm is proposed to solve the tracking problem of a discrete-time (DT) nonlinear state and input time delayed system of the wheeled mobile robot (WMR). With the typical model of the WMR transformed into an affine nonlinear DT system, a delay matrix function and appropriate Lyapunov–Krasovskii functionals are introduced to overcome the problems caused by the state and input time delays, respectively. Furthermore, with the approximation of the radial basis function neural networks (NNs), the adaptive controller, the critic NN, and action NN adaptive laws are defined to guarantee the uniform ultimate boundedness of all signals in the WMR system, and the tracking errors convergence to a small compact set to zero. Two examples of simulation are given to illustrate the effectiveness of the proposed algorithm.

With the increasing applications of wheeled mobile manipulators (WMMs), new challenges have arisen in terms of executing high-force tasks while maintaining precise trajectory tracking. A WMM, which consists of a manipulator mounted on a mobile base, is often a kinematically redundant robot. The existing WMM configuration optimization methods for redundant WMMs are conducted in the null-space of the entire system. Such methods do not consider the differences between the mobile base and the manipulator, such as their different kinematics, dynamics, or operating conditions. This may inevitably reduce the force exertion capability and degrade the tracking precision of the WMM. To enhance the force exertion capability of a WMM, this letter maximizes the directional manipulability (DM) of the manipulator, with consideration of the joint torque differences, first in Cartesian space and then in the null-space of the robotic system. To maintain precise end-effector trajectory tracking, this letter proposes a novel coordination method between the mobile base and the manipulator via a weighting matrix. The advantages and effectiveness of the proposed approach are demonstrated through experiments.

An adaptive neural network-based finite-time tracking control method is proposed for wheeled mobile robots (WMR) in the presence of the slipping with full state time-varying constraints. The practical WMR model with coupled inputs as two torques for each wheel is difficult for the designed controllers to achieve finite-time convergence. A novel adaptive finite-time tracking control strategy is proposed by satisfying the time-varying constraints and utilizing barrier Lyapunov functions. It is proved that the controllers we designed are finite-time stable, and each tracking error converges to a small neighborhood of the original states in a finite time without violation of the full state constraints. Finally, a simulation based on a practical WMR model is conducted to verify the effectiveness of the proposed tracking control method. By using the exponential-decayed time-varying constraints, the simulation results show that the tracking control effect is very optimistic, which means that the control method proposed in this paper has great significance in engineering.

In this paper, an adaptive dynamic programming-based online adaptive tracking control algorithm is proposed to solve the tracking problem of the partial uncertain time-delayed nonlinear affine system with uncertain resistance. Using the discrete-time Hamilton-Jacobi-Bellman function, the input time-delay separation lemma, and the Lyapunov-Krasovskii functionals, the partial state and input time delay can be determined. With the approximation of the action and critic, and resistance neural networks, a near-optimal controller and appropriate adaptive laws are defined to guarantee the uniform ultimate boundedness of all signals in the target system, and the tracking error convergence to a small compact set to zero. A numerical simulation of the wheeled mobile robotic system is presented to verify the validity of the proposed method.

In this paper, a dynamic model of a wheeled mobile robotic (WMR) system with coupled control input is developed, which will increase the complexity of its tracking control with time-varying advance angle. To deal with this problem, a partial reinforcement learning neural network (PRLNN)-based tracking algorithm is proposed for the WMR systems. The main contributions of the PRLNN adaptive tracking control method is that it is the first control method to introduce the PRLNN adaptive control to the WMR system, which determines to solve the WMR tracking control with the time-varying advance angle. The critic neural network (NN) and action NN adaptive laws for the decoupled controllers are designed using the standard gradient-based adaptation method. According to the Lyapunov stability analysis theorem, the uniform ultimate boundedness of all signals in the WMR system can be guaranteed with the design parameters chose properly, and the tracking error converge to a small compact set nearby zero. A numerical simulation is presented to verify the effectiveness of the proposed control algorithm.

Resistance coefficient ( RC ) is an important measure when designing wheel-driving mechanisms and accurate dynamic models for real-time mobility control of wheeled mobile robots (WMRs). This measure is typically formulated as a constant that depends on the wheel load, wheel dimensions, and soil that the WMR is designed for. This article proposes a novel variable RC that responds to terrain deformation. This variable RC is then applied to controllers for WMRs that estimate driving torques and slip ratios on deformable terrain. Simple yet accurate models of RC are developed from both experimental results and theoretical analysis, and these models are then compared with other methods. The proposed RC models give more accurate and more computationally efficient estimations of driving torques and slip ratios for WMRs, with average estimation errors less than 6% and the shortest computation time in experiments. The two proposed estimators are then applied to the design of the tracking-control systems for a WMR running on deformable terrain. Experiments with simulated sandy terrain demonstrate that both proposed control systems are feasible, and the slip estimation effectively decreases velocity tracking errors from more than 20% to less than 10%.

As a well-explored template that captures the essential dynamical behaviors of legged locomotion on sagittal plane, the spring-loaded inverted pendulum (SLIP) model has been extensively employed in both biomechanical study and robotics research. Aiming at fully leveraging the merits of the SLIP model to generate the adaptive trajectories of the center of mass (CoM) with maneuverability, this study presents a novel two-layered sagittal SLIP-anchored (SSA) task space control for a monopode robot to deal with terrain irregularity. This work begins with an analytical investigation of sagittal SLIP dynamics by deriving an approximate solution with satisfactory apex prediction accuracy, and a two-layered SSA task space controller is subsequently developed for the monopode robot. The higher layer employs an analytical approximate representation of the sagittal SLIP model to form a deadbeat controller, which generates an adaptive reference trajectory for the CoM. The lower layer enforces the monopode robot to reproduce a generated CoM movement by using a task space controller to transfer the reference CoM commands into joint torques of the multi-degree of freedom monopode robot. Consequently, an adaptive hopping behavior is exhibited by the robot when traversing irregular terrain. Simulation results have demonstrated the effectiveness of the proposed method.

The tractive capability of Multi-wheeled mobile robots (WMRs) depends heavily on the performance of the driving control of their steerable wheels. The recently proposed concept of a pseudo-driven wheel (PDW) provides a simple, versatile, and effective way to improve the tractive capability. However, its focus is to eliminate the internal forces between the wheels and save energy; therefore, it cannot provide sufficient driving force to the body on rough terrains. This paper proposes a control strategy to adjust the power output of a PDW along the directions of two degrees of freedom, an approach that improves the trajectory tracking control of WMRs, especially on rough terrains. To achieve the desired active following control of the PDW, an active disturbance rejection controller is used to compensate the disturbances arising from the wheel-terrain interaction. The Adams and Simulink are used for a joint simulation of which results show that the proposed control strategy is necessary for accurate trajectory tracking, for which the feasibility and effectiveness were verified by the experimental results. In summary, the trajectory tracking accuracy of the WMR and its tractive capabilities on rough, sandy terrain were improved.

The increasing application of wheeled mobile robots (WMR) in many fields has brought new challenges on its control and teleoperation, two of which are induced by contact slippage phenomenon between wheel and terrain as well as time delays in the master-slave communication channel. In the WMR bilateral tele-driving system, in this paper, the linear velocity of the slave mobile robot follows the position command from the haptic master robot while the slippage-induced velocity error is fed back as a haptic force felt by the human operator. To cope with the slippage-induced nonpassivity and constant time delays, this paper proposes three methods to design the WMR bilateral teleoperation system’s controller. An experiment system is set up with Phantom Premium 1.5A haptic device as the master robot and a simulation platform of WMR as the slave robot. Experiments with the proposed methods demonstrate that they can result in a stable WMR bilateral tele-driving system under wheel’s slippage and constant time-delays.

A recursive dynamic modeling and control is presented for the dual-arm manipulator with elastic joints carrying a common object. For decoupling the effect of elastic joints, the dynamic modeling approach is based on the classic recursive Newton-Euler method but involves high-order derivatives of motion and force variables. The high-order inverse kinematics which is needed in the motion control is presented firstly. With the classic Recursive Newton-Euler (RNEA) method, two-order dynamic model of the dual-arm robot is established, for decoupling the effect of the elastic joints, the form of four-order dynamic model is presented, meanwhile, combining with the high-order dynamic model of the carried object, the completed Dual-Arm Elastic Joints Newton-Euler Algorithm (DA-EJNEA) is established. Then the feedback linearization method is adopted to the motion control based on the DA-EJNEA. Finally, to verify the effectiveness of the proposed method, feedback linearization method based on the DA-EJNEA and the computed torque method based on the dynamic model with rigid joints are used to control the dual-arm coordinated system respectively, the simulation results illustrate the feedback linearization method based on the DA-EJNEA has an obvious advantage for trajectory tracking of the object in the operation space, it behaves reasonable potentials for the model-based control.

Wireless sensor network technology is widely used in various modern scenarios, and various industries have higher and higher requirements for the performance indicators of wireless sensor networks. A reasonable and effective layout of wireless sensor networks is conducive to the monitoring of environmental quality, various transactions, and status and transmits a large number of sensing data to the data aggregation center for processing and analysis. However, the operation and development of traditional wireless sensor networks are extremely dependent on the energy supply of the network. When the corresponding supply energy is limited, the operation life of the corresponding wireless sensor network will be greatly reduced. Based on the above situation, this paper proposes a nonuniform clustering routing protocol optimization algorithm from the energy loss of cluster head and clustering form algorithm in wireless sensor networks. At the level of cluster head calculation in wireless sensor networks, firstly, based on the adaptive estimation clustering algorithm, the core density is used as the estimation element to calculate the cluster head radius of wireless sensor networks. At the same time, this paper creatively proposes a fuzzy logic algorithm to further solve the uncertainty of cluster head selection, integrate the residual energy of cluster head nodes, and finally complete the reasonable distribution of cluster heads and realize the balance of node energy consumption. In order to further reduce the algorithm overhead of transmission between cluster heads and realize energy optimization, an intercluster routing optimization algorithm based on the ant colony algorithm is proposed. The pheromone is updated and disturbed by introducing chaotic mapping to ensure the optimal solution of the algorithm, and the optimal path is selected from the perspective of energy dispersion coefficient and distance coefficient, so as to optimize the energy consumption between cluster heads. The experimental results show that compared with the traditional algorithm, the proposed nonuniform clustering routing protocol optimization algorithm prolongs the corresponding life cycle by 75% and reduces the total network energy consumption by about 20%. Therefore, the algorithm achieves the purpose of optimizing network energy consumption and prolonging network life to a certain extent and has certain practical value.

The increase in the ageing population worldwide poses a severe challenge in assisting older individuals to live independently, including the provision of mobility assistance and support in daily activities. In this paper, a practical robotic system is developed to provide intelligent support for older persons using a wheeled mobile manipulator (WMM), consisting of an omnidirectional mobile platform and a robotic arm. We focus on two critical needs: 1) mobility assistance, and 2) object manipulation support. The tasks are not executed simultaneously and each uses a task-dependent end-effector. Learning from demonstration, or kinesthetic teaching, is adopted to help the WMM to learn an elderly or disabled user’s walking pattern or an able-bodied person’s object manipulation skill. The robotic system can assist the user in conducting a number of daily operations. For mobility assistance, the WMM is reconfigured into a smart walker, where a novel variable admittance control is adopted to detect the user’s walking intention. A learning approach based on dynamic movement primitives is implemented to capture and adapt the WMM to the user’s walking pattern. For object manipulation support, a demonstrator first collaborates with an elderly user to conduct the task, and then the WMM takes the role of the demonstrator to assist the user. The Gaussian mixture model and Gaussian mixture regression are used to learn and reproduce the demonstrator’s experience, respectively. The advantages and effectiveness of the proposed approach are experimentally demonstrated with a four-wheel omnidirectional WMM.

As the major construction equipment of asphalt pavement, the performance of the paver plays a critical role in pavement construction quality, directly affecting the smoothness and compactness of the pavement, etc. Therefore, by analyzing the influence of the paver leveling method on the levelness, this project uses 3D mechanical control technology to optimize the automatic leveling method of pavers, which can improve the asphalt pavement construction process. It can also improve the quality and economic efficiency of asphalt pavement construction by increasing the automation, standardization, and wisdom of pavers.

Motor vibration signal data sets are characteristically random and nonlinear, and its features are difficult to extract for fault identification. To reduce the uncertainty of fault diagnosis, a method based on principal component analysis (PCA) and discrete belief rule base (DBRB) was developed for the first time. Initially, the vibration signal was first denoised using a wavelet threshold algorithm to eliminate interference. Second, overlapping signals were segmented into 15 time windows and a total of 13 typical time domain features and mathematical statistical features were extracted. Third, the dimensions of the features were reduced to three principal components by PCA and were taken as the antecedent attributes of the DBRB. However, the amount of information in each principal component is different, so the variance contribution rate was taken as an antecedent attribute weight to restore the original data characteristics. Fourth, a PCA-DBRB model was established, which effectively avoided the combinatorial explosion problem of rule base in the DBRB model. In addition, to obtain appropriate reference values, the k-means algorithm was introduced to take the cluster centers as reference values. The method was then validated by collecting typical fault data from motor bench experiments. The results demonstrated that compared with other traditional classifiers, this approach is more effective and superior in classification performance and more accurate in diagnosing faults from motor vibration data.

An enhanced failure mode effect analysis (FMEA) based risk assessment for subsea compressor systems was proposed in this study. The enhanced model was established using a combination of fuzzy analytic hierarchy process (FAHP), fuzzy comprehensive evaluation, and FMEA. Different from the traditional FMEA model, the model improved the capability to identify system faults and to further measure the risk of a subsea compressor system through effective qualitative and quantitative analyses. A case study was then conducted to demonstrate the capability of the developed method in a complete risk assessment for a subsea compressor system and the subsystems and subcomponents with low reliabilities were identified. Comparing the enhanced model with previous models, it is found that the potential risks of some components are changed, and the components with higher potential risks in the system are identified. Sensitivity analysis to investigate the impact of parameters of subcomponents on system reliability was also performed.

China’s first Mars rover, Zhurong, has successfully touched down on the southern Utopia Planitia of Mars at 109.925° E, 25.066° N, and since performed cooperative multiscale investigations with the Tianwen-1 orbiter. Here we present primary localization and surface characterization results based on complementary data of the first 60 sols. The Zhurong rover has traversed 450.9 m southwards over a flat surface with mild wheel slippage (less than 0.2 in slip ratio). The encountered crescent-shaped sand dune indicates a NE-SW local wind direction, consistent with larger-range remote-sensing observations. Soil parameter analysis based on terramechanics indicates that the topsoil has high bearing strength and cohesion, and its equivalent stiffness and internal friction angle are ~1390-5872 kPa∙m-n and ~21°-34° respectively. Rocks observed strewn with dense pits, or showing layered and flaky structures, are presumed to be involved in physical weathering like severe wind erosion and potential chemical weathering processes. These preliminary observations suggest great potential of in-situ investigations by the scientific payload suite of the Zhurong rover in obtaining new clues of the region’s aeolian and aqueous history. Cooperative investigations using the related payloads on both the rover and the obiter could peek into the habitability evolution of the northern lowlands on Mars.

The hexapod robots equipped with six legs have higher stability and adaptability to challenging terrains than other legged robots with fewer legs. The ability of hexapods to traverse challenging terrains largely depends on practical planning approaches on their footstep sequence. However, suppose the stability of the robotic system is insufficiently considered with the footstep planning method, it cannot track the planning results in some extremely complex terrains, e.g., foot slippage or robot overturn. In this work, we develop a quasi-static equilibrium footstep planning method for hexapod robots to traverse challenging terrains. The core of this planning method is the proposed 3D quasi-static equilibrium support region (3D QESR), which can be employed as a constraint for the planning method to ensure the quasi-static stability of the hexapod robots. A new graph search algorithm for footstep sequence planning is also presented. The simulation and experiment results show that the proposed 3D QESR method has superior performance in bypassing unstable irregular regions compared with the widely used support polygon method.

This paper reports a magnetic-drive force-distance curve-based atomic force microscopy using an orthogonal cantilever probe (OCP), which can study the interactive effects between sidewall morphology and adhesion force. The OCP is composed of a horizontal arm and a vertical arm with a protruding tip, in which a ferroferric oxide bead is used to connect them orthogonally together. Based on this unique structure, the designed OCP can detect the interaction force between the sidewall and tip through torsional deformation, thus mapping steep vertical surface. The ferroferric oxide bead is magnetized along the direction perpendicular to the long axis of the horizontal arm, becoming a magnetic bead, in order to provide vibration at off-resonance for the OCP. Relevant theoretical analysis and calibration tasks are introduced at first, and then, two specimens including a micro-electro-mechanical system device with micro-comb structure and a microarray unit are adopted to verify its practicability of the proposed method. Experimental results show that there is a correlation between sidewall adhesion and surface roughness, in addition, these performance parameters can also be meaningful for the micro-operation process.

With the steam obtained from the waste heat of high temperature semi-coke, the hydrogen production through gasification method is considered more commercial. In order to improve the efficiency of waste heat recovery, the fractional model for heat conduction of semi-coke bed in waste heat recovery process was established. The non-destructive CT was employed to obtain the inner morphology of semi-coke bed and the image binarization processing was used to segment the CT image. With the MATLAB program, the box-counting method was used to calculate the fractal dimension of semi-coke bed. The fractional model for heat conduction of semi-coke bed was established by the fractal theory. The results showed that, the CT image and bit binary image of semi-coke bed can really reflect the inner morphology of semi-coke bed, and the inner morphology of semi-coke bed can be regarded as a fractal medium. The fractal dimension of semi-coke bed is 1.7537, which is very close to golden mean, 1.618, this could be the optimal structure for the heat conduction of semi-coke bed under the condition of natural accumulation. The one-dimensional heat conduction fractional equation of semi-coke bed was established and it can be accurately solved by fractal complex transformation and traveling wave transformation.

With the steam obtained from the waste heat of high temperature semi-coke, the hydrogen production through gasification method is considered more commercially. The heat transfer of semi-coke bed and steam was investigated using an unsteady convection heat transfer three-dimensional model of semi-coke. The effects of particle size, steam flow and particle bed thickness on heat transfer characteristics were considered. The particle temperature calculated by three-dimensional model was in good agreement with the corresponding particle temperature of experiment. The heat transfer characteristics of single particle, the particle temperature, the amount of heat recovery and the heat flux were investigated. The results show that, in the first 10 min of the heat transfer of semi-coke bed and steam, the bottom particle temperature decreases rapidly, but the top particle temperature is almost unchanged. The heat transfer rate evolution of the single particle in different positions is revealed. The heat transfer rate evolution of the bottom particle is different from that of the middle particle and top particle, and the heat transfer rate evolution of middle particle is similar to that of the top particle. The particle size, the steam flow and the particle bed thickness have great influence on the heat transfer mechanism of semi-coke and steam, and the 7.5 kg/h is considered to be the best steam flow for heat recovery. The intrinsic heat transfer mechanism between semi-coke bed and steam was revealed.

Purpose The purpose of this paper is to enable autonomous door-opening with unknown geometrical constraints. Door-opening is a common action needed for mobile manipulators to perform rescue operation. However, it remains difficult for them to handle it in real rescue environments. The major difficulties of rescue manipulation involve contradiction between unknown geometrical constraints and limited sensors because of extreme physical constraints. Design/methodology/approach A method for estimating the unknown door geometrical parameters using coordinate transformation of the end-effector with visual teleoperation assists is proposed. A trajectory planning algorithm is developed using geometrical parameters from the proposed method. Findings The relevant experiments are also conducted using a manipulator suited to extreme physical constraints to open a real door with a locked latch and unknown geometrical parameters, which demonstrates the validity and efficiency of the proposed approach. Originality/value This is a novel method for estimating the unknown door geometrical parameters with coordinate transformation of the end-effector through visual teleoperation assists.

This letter proposes a synthetic aperture radar (SAR) target recognition method via joint classification of deep features fused by multi-canonical correlation analysis (MCCA). A convolutional neural network (CNN) is designed for feature learning from original SAR images. For the multiple feature maps from different convolution layers, they are fused based on the MCCA to maintain the relevance while eliminating the redundancy. Afterwards, the joint sparse representation (JSR) is employed to jointly represent the fused deep feature vectors from different convolution layers under the constraint of their inner correlations. Based on the reconstruction errors from JSR, the target label can be classified. The proposed method can make full use of the multi-level deep features by using the correlations among the same layer and between different layers. Experiments are investigated on the Moving and Stationary Target Acquisition and Recognition (MSTAR) data set and the results confirm the performance of th...

In2O3 film was prepared by magnetron sputtering technology on rough surface Si (100) substrates. The results show that the film grown at the sputtering gas pressure of 0.6 Pa, the temperature of 60...

The scale parameter is one of the key factors which influence the structure and locomotion characteristics of the legged robot. The scale effect mechanism of animals in nature was revealed, and the influence of scale parameters on animal was analyzed. This paper establishes a dynamic model of insect-imitating hexapod robot. A high-fidelity simulation platform for hexapod robot was established based on Vortex, and the foot-ground interaction mechanics model was established and applied to the developed simulation platform. Based on the existing six-legged robot prototype, the validity of the relevant model and the fidelity of the simulation platform are verified. The influence of a robot’s mass and characteristic size on its feature locomotion was analyzed. The foot force rises with the increase of the whole robot mass, and the foot force of the unit robot mass decreases with the increase of the whole robot mass, eventually tending to a fixed value. The maximum joint torque rises with the increase of the whole robot mass. The system power rises with the increase of the whole robot mass, but the system power of unit robot mass is basically a constant value. The peak system power decreases with the increase of the distance between the front and the rear leg, and the joint torque rises with the increase of the distance between the front and rear leg. The related research results have guiding significance and reference value for the system design of hexapod robots.

Here, analytical expressions of the unbalanced magnetic force (UMF)of the stator and the rotor under static eccentricity (SE) are deduced by using complex relative magnetic conductivity method and Maxwell stress tensor method. The frequency characteristics of the UMF are obtained. Further the influence of different eccentricity ratio on the UMF is researched. Then, an external rotor permanent magnet brushless direct current motor (PMBLDCM) with 46 poles and 51 slots used as an in-wheel motor is taken as an example to verify the frequency characteristics by finite element analysis (FEA). The research shows that the frequency characteristics of the UMF of the stator s related to electric frequency. The frequency characteristics of the UMF of the rotor are related to the power source frequency and the rotation frequency of the wheel. It does not introduce new frequency components when the motor SE occurs. As the SE ratio increases, the amplitude of the UMF increases. The UMF without eccentricity exists in all directions with the change of the time. However, as the eccentricity ratio increases, the direction of the UMF is closer to the eccentric direction.

Wheel-soil interaction mechanics plays a crucial role for wheeled mobile robots (WMR) on rough and deformable terrains such as Martian and Lunar surfaces. Skid terramechanics is an essential component for WMRs and generates resistance force when a WMR brakes or on downhill slopes. The basis of classical terramechanics theories for WMRs – Bekker’s normal stress and Janosi’s shear stress equations – are so complex that the wheel-soil interaction force/torque equations are not amenable to closed form solutions, which seriously limits the application of terramechanics theories to WMRs. To establish analytical wheel-soil interaction expressions, the normal and shear stresses that can be characterized linearly by the proposed terrain stiffness and shear strength, respectively, are presented in this paper. Terrain stiffness and shear strength can be used to characterize terrain mechanical properties. Compared with the experimental data, the maximum relative error of the resistance forces estimated using these expressions at steady state is less than 7%. These validated expressions can be applied to estimate terrain parameters and resistance force online with high accuracy. Terrain’s stiffness and shear strength increase first, and then reach a constant. Before wheels entering steady state, the online estimated resistance force’s relative error is much higher, which can be explained using wheel’s vertical velocity.

Image enhancement is a very important process of image preprocessing and it plays a critical role in the improvement of image quality and the follow-up image analysis, which makes the research of image enhancement algorithm a hot research field. Image enhancement not only needs to strengthen image determination and recognition, but also needs to avoid the consequential color distortion. Pseudo-color enhancement is the technique to map different gray scales of a black-and-white image into a color image. As humans have extremely strong ability in distinguishing different colors visually and relatively weak capacity in discriminating gray scales, so, color the gray-scale changes which cannot be differentiated by human eyes so that they can tell them apart. The mapping function in conventional gray-scale transform method is not working well in dark and low-contrast images. So, this paper comes up with an improved gray-scale transformation algorithm. This algorithm can achieve the enhancement, preserve the image colors, process dark and low-contrast images, reinforce the enhancement and improve the blocking effect. The experiment proves that the enhanced image obtained by the method of this paper can have improved average brightness, natural colors and more detail information and it has good application value.

Composite materials could be applied to the bumper beam in order to enhance the structure performance and provide a light weight solution. This article assessed the impact performance of automobile...

The no-load radial magnetic field and no-load back electromotive force (EMF) of external rotor permanent magnet brushless DC motor (PMBLDCM) are calculated by applying the correction coefficient of magnetic conductance here, taking into account the stator slotting and static eccentricity effects. An external rotor PMBLDCM with 51-slot/46-pole, used as in-wheel motor, is taken as an example, the analytical calculation results of the no-load back EMF are validated by the finite-element method and experiment. The influences of static eccentricity ratio on the no-load radial magnetic field and no-load back EMF are investigated based on the analytical model. The investigation shows that static eccentricity does not change the harmonic contents of no-load radial magnetic field, so it does not change the harmonic contents of three-phase no-load back EMFs. However, static eccentricity changes the space order of no-load radial magnetic field, resulting in the different total harmonic distortions of three-phase no-load back EMFs; in other words, the asymmetric distortions of three-phase no-load back EMFs are generated. The asymmetric distortions of three-phase no-load back EMFs are intensified with the increase in static eccentricity ratio.

The articulated rotating speed is one of the important parameters to determine the drive devices and actuating devices of joints for legged robots. Compared with the small-scale multi-legged robots, the range of the output speed of the joint should be as accurate as possible for the large-load-ratio multi-legged robots. To reasonably select the devices of joints, the maximum walking speed method is proposed to quickly and accurately obtain the range of articulated rotating speed by taking an electrically driven large-load-ratio six-legged robot as an example. To prove the rapidity, accuracy, and conciseness of the maximum walking speed method, the analyses of the forward kinematics and inverse kinematics of the robot are implemented based on the Denavit-Hartenberg method. However, only one range of articulated rotating speed is effectively confirmed in a single leg. Through rotating one of the joints to achieve the maximum speed index of the robot, the maximum walking speed method is employed to establish the mathematical relationships between the articulated rotating angles and the maximum walking speed index of the robot. The ranges of the output speeds of all joints are accurately obtained. The simulation verification and walking experiments of the prototype are, respectively, carried out. The results of the simulation and walking experiments show that the maximum walking speed method is reasonable and effective in calculating the range of articulated rotating speed. The proposed method in this paper can be reliably applied to the development of large-load-ratio multi-legged robots.

Door-opening is a critical problem for robots used for rescue purposes in nuclear power plants (NPPs). A force and torque (F/T) sensor is not used in the rescue task for door-opening in the NPPs environment. It is, therefore, necessary to study the dynamic model of door-opening. The NPPs door and a door handle dynamic model are significant to the mechanical design, simulation, and dynamic feed-forward control of an NPP robot. To obtain the accurate force data of door-opening, a method based on a gravity compensation algorithm combined with a transformation of the contact force of the end effector is proposed. This paper analyzes the structural features and dynamics model of a fire door and a door handle. Methods for identifying the model parameters are also developed by combining a Nelder-Mead simplex search with the least-squares algorithm. The extensive door-opening experiments were carried out in this paper, and the results validate the fidelity of the derived dynamic models of the door and the door handle.

The foot-terrain interaction mechanics of human is important in understanding the biped locomotion mechanism. This paper aims to investigate the effect of walking speed and the hardness of the terrain on foot-terrain interaction mechanics. In the experiments, mobile portable plantar mechanical measuring insoles with 107 sensor elements were used to gauge the plantar force and contact area in real-time. Seven subjects with healthy feet have participated in typical experiments. The statistical methods including correlation analysis, univariance analysis, and systematic identification are primarily used to obtain several main results. Bimodal functions in describing the total pressure-time relations were performed at slow and regular speeds but only one hump is left if walking at fast paces; they can be unified and summed by three subsections' unimodal functions. The forefoot produces a large peak impact force in slow and regular quasi-static walking on both hard ground and deformable terrains, while the heel absorbs more dynamic impact shocks in fast walking on hard ground. The torques generated by the ankle joints are calculated based on plantar force or its derived information such as zero moment point. Some implications are drawn, for example, the dynamically changed positions of zero moment point (ZMP) for humans are similar to that generated by reptiles wiggling through the flowable terrains; increasing the stride length on the hard ground produces more impact vibrations than quickening paces but more effective in accelerating walks on deformable terrains.

This paper discusses a problem that has plagued researchers for a long time regarding the dynamic modeling of a multiple degree-of-freedom (multi-DOF) manipulator such that its manipulation exhibits a higher computational efficiency and accuracy. Unknown friction, unknown gravitational torque, an uncertain moment of inertia, and severe joint coupling are the primary disturbing factors in multi-DOF manipulator modeling. In addition, joint flexible problems caused by the integration of harmonic drives increase the modeling complexity. Hitherto, no effective method has been found to address these problems. The virtual decomposition (VD)-based method exhibits the advantages of joint dynamics decoupling and minor computation compared with the traditional Lagrangian formulation or Newton-Euler formulation. In this study, an estimation method for the deformation-related torque of harmonic drives is established based on a novel experimental model; subsequently, this method is utilized in the VD-based model for the multi-DOF manipulator. Hence, the decoupling dynamic model for the manipulator considering joint flexibility is established. The performance of this new method has been evaluated by a contrast simulation with the Newton-Euler formulation, and the multi-DOF manipulator control simulation and experiment have been conducted with a VD-based model as a feedforward compensator to verify its performance in real-time control. The results demonstrated the validity and efficiency of e proposed approach.

In low-gravity suspension simulation experiments, the partial gravitational forces of tested objects are balanced by the constant vertical forces on cables generated by constant-force systems. To improve system robustness against external payload disturbance, such systems usually employ low-stiffness mechanisms. The schematic diagram of our proposed low-stiffness mechanism is derived from an energy approach, which is especially preferable when the low-stiffness mechanism comprises two kinds of elastic components. The mechanism uses a combination of an axially arranged torsion bar and a group of radially arranged springs. While the former exhibits high energy density and generates major output force, the latter offers a negative stiffness to shape the output force curve so that it resembles a constant one. The mechanism has a comparatively smaller overall size, lower stiffness, and wider adjustable force range. The low-stiffness mechanism is used to form an active constant-force system. The system, as well as its dynamic model and controller, are also detailed in this paper. Experimental results demonstrate that the active constant-force system can be robustly controlled by a proportional-derivative controller with incomplete derivation to generate a high-accuracy dynamic force.

Background: Sepsis-induced myocardial dysfunction (SIMD), which is one of the features of multiple organ dysfunction in sepsis with extremely high mortality, is characterized by impaired myocardial compliance. To date, there are few effective treatment options to cure sepsis. Tannic acid (TA) is reportedly protective during sepsis. However, the underlying mechanisms by which TA protects against septic heart injury remains elusive. Methods: We investigated the potential effects and underlying mechanisms of TA in alleviating lipopolysaccharide (LPS)-induced H9C2 cardiomyocyte cell apoptosis. H9C2 cells were treated with LPS (15 μg/mL), TA (10 μM) and TA+LPS. Control cells were treated with media only. Apoptosis was measured using flow cytometry, RT-PCR, and Western blotting analysis. Additionally, laser confocal immunofluorescence analysis detected the production of reactive oxygen species (ROS). Western blot and RT-PCR were employed to detect ER stress-associated functional proteins. Results: The results demonstrated that TA reduced the degree of LPS-induced H9C2 cells injury, including the inhibition of ROS production and endoplasmic reticulum (ER) stress-associated apoptosis. ER stress-associated functional proteins, including ATF6, PERK, IRE1, XBP1s, and CHOP were suppressed in response to TA treatment. Furthermore, the expression levels of ER stress-associated apoptotic proteins, including JNK, Bax, Cyt, Caspase3, Caspase12, and Caspase9 were reduced following treatment with TA. Additionally, the protective effects of TA on LPS-induced H9C2 cells were strengthened following treatment with the ROS inhibitor, N-Acetylcysteine (NAC), which demonstrated that ROS-mediated ER stress-associated apoptosis and TA decreased ROS-mediated ER stress-associated apoptosis. Conclusion: Our findings demonstrated that the protective effects of TA against LPS-induced H9C2 cells apoptosis may be associated with the amelioration of ROS-mediated ER stress. These findings may assist the development of potential novel therapeutic methods to inhibit the progression of myocardial cell injury. (TA alleviates LPS-induced H9C2 cell apoptosis.)

In order to comprehensively evaluate the landing performance of vertical-landing vehicle and increase the probability of successful landing, a sagittal dynamics model of legged-type vertical landing vehicle on landing process was established, including the elastic-plastic collision model of multi-rigid body system to predict discontinuous process. The displacement-velocity diagram is used to investigate the influence mechanism of the initial tilt angle and the initial height on the trajectory of the center of mass of the vertical-landing vehicle in various typical landing modes. In addition, the leg buffering behavior of the vehicle is investigated. The buffering mechanism of touched-down legs of different time periods under different initial conditions were accordingly explored and analyzed. The results showed that the buffers in legs that touch the ground first are more sensitive to changes of the falling height, while the initial tilt angle has more influence on the buffers of legs that subsequently touch the ground more. Unlike that the influence of the initial tilt angle on the attitude recovery of the vehicle will continue throughout the landing process, and gradually decease as the convergence, the effect of the initial falling height mainly focused on the initial and final stages of the landing process. The phase diagram is a favorable angle for investigating and analyzing the effect of initial conditions on the entire landing process of the vertical landing vehicle.

We present an overview of a new method to print 3D volumetric gradient index (GRIN) micro-optics inside a porous silica scaffold and show results for the focusing properties of an array of cylindrical GRIN lenses.