Search

In recent years, rehabilitation robots have been developed and used in rehabilitation training for patients with hemiplegia. In this paper, a rehabilitation training robot with variable damping is designed to train patients with hemiplegia to recover upper limb function. Firstly, a magnetorheological joint damper (MR joint damper) is designed for the rehabilitation training robot, and its structural design and dynamic model are tested theoretically and experimentally. Secondly, the rehabilitation robot is simplified into a spring-damping system, and the rehabilitation training controller for human movement is designed. The rehabilitation robot dynamically adjusts the excitation current according to the feedback speed and human–machine interaction torque, so that the rehabilitation robot always outputs a stable torque. The magnetorheological joint damper acts as a clutch to transmit torque safely and stably to the robot joint. Finally, the upper limb rehabilitation device is tested. The expected torque is set to 20 N, and the average value of the output expected torque during operation is 20.02 N, and the standard deviation is 0.635 N. The output torque has good stability. A fast (0.5 s) response can be achieved in response to a sudden motor speed change, and the average expected output torque is 20.38 N and the standard deviation is 0.645 N, which can still maintain the stability of the output torque.

This study proposes a dual-coil magnetorheological torsional vibration damper (MRTVD) and verifies the effectiveness of semi-active damping control to suppress the shaft system’s torsional vibration via experimental research. Firstly, the mechanical model of the designed MRTVD and its coupling mechanical model with the rotating shaft system are established. Secondly, the torsional response of the shaft system is obtained via resonance experiments, and the influence of the current on the torsional characteristics of the magnetorheological torsional damper is analyzed. Finally, the MRTVD is controlled using the skyhook control approach. The experimental results demonstrate that when the main shaft passes through the critical speed range at various accelerations, the amplitude of the shaft’s torsional vibration decreases by more than 15%, and the amplitude of the shaft’s torsional angular acceleration decreases by more than 22%. These conclusions validate the inhibitory effect of MRTVD on the main shaft’s torsional vibrations under skyhook control.

Sports matches are very popular all over the world. The prediction of a sports match is helpful to grasp the team's state in time and adjust the strategy in the process of the match. It's a challenging effort to predict a sports match. Therefore, a method is proposed to predict the result of the next match by using teams' historical match data. We combined the Long Short-Term Memory (LSTM) model with the attention mechanism and put forward an AS-LSTM model for predicting match results. Furthermore, to ensure the timeliness of the prediction, we add the time sliding window to make the prediction have better timeliness. Taking the football match as an example, we carried out a case study and proposed the feasibility of this method.

Inspired by its highly efficient capability to deal with big data, the brain-like computational system has attracted a great amount of attention for its ability to outperform the von Neumann computation paradigm. As the core of the neuromorphic computing chip, an artificial synapse based on the memristor, with a high accuracy in processing images, is highly desired. We report, for the first time, that artificial synapse arrays with a high accuracy in image recognition can be obtained through the fabrication of a SiNz:H memristor with a gradient Si/N ratio. The training accuracy of SiNz:H synapse arrays for image learning can reach 93.65%. The temperature-dependent I–V characteristic reveals that the gradual Si dangling bond pathway makes the main contribution towards improving the linearity of the tunable conductance. The thinner diameter and fixed disconnection point in the gradual pathway are of benefit in enhancing the accuracy of visual identification. The artificial SiNz:H synapse arrays display stable and uniform biological functions, such as the short-term biosynaptic functions, including spike-duration-dependent plasticity, spike-number-dependent plasticity, and paired-pulse facilitation, as well as the long-term ones, such as long-term potentiation, long-term depression, and spike-time-dependent plasticity. The highly efficient visual learning capability of the artificial SiNz:H synapse with a gradual conductive pathway for neuromorphic systems hold great application potential in the age of artificial intelligence (AI).

The purpose of this study was to solve the problem that the damping of rubber or silicone oil torsional dampers used in crankshafts is not adjustable and cannot effectively control torsional vibration at different resonant frequencies. Based on the controlled rheological properties of magnetorheological (MR) smart materials, this study designed a new type of variable damping MR torsional damper (MRTD) and proposed a semi-active control method to effectively control the torsional vibration of the crankshaft under multiple harmonic resonances. First, a mechanical model of the MRTD and a lumped parametric mass model of the crankshaft system were developed, and the resonance frequency harmonic range of the crankshaft system operation was determined by the torsional vibration characteristics analysis. Then a semi-active skyhook control method for the MRTD was proposed, and a joint control simulation analysis was performed using Amesim and Matlab software. The torsional vibration control effects of the crankshaft system with no damper, MRTD with different damping coefficients, and MRTD with skyhook control under acceleration and uniform speed conditions were comprehensively investigated. The simulation results indicated that the skyhook damping control significantly reduced the torsional vibration amplitude under both acceleration and uniform speed conditions, verifying the effectiveness of the skyhook-based control strategy for MRTD.

To reveal the transient temperature distribution pattern inside the magnetorheological grease (MRG) torsional vibration damper and explore the relationship between the current and internal temperature of the device, the transient temperature simulation analysis of the MRG device was conducted in this study. Firstly, a theoretical heat transfer model of MRG torsional vibration damper with dual heat source structural feature was established based on the Bingham constitutive model and the temperature-dependent viscosity characteristic of MRG. Then, the transient temperature field model of the MRG torsional vibration damper was developed by the finite element method, the temperature field distribution and temperature–time variation characteristics of the MRG torsional vibration damper at 0A, 1A, and 2A working conditions were analyzed, and the effects of viscosity and slip factors on the temperature rise of the device were investigated. The simulation results show that the temperature rise of MRG in the working domain is the fastest, but a gradual slowing of the temperature rise rate. The magnitude and rate of temperature rise are maximum when the 1A current is applied to the torsional vibration damper. Finally, the current–temperature curve is obtained by fitting the simulation results. The results of the analysis reveal the internal temperature distribution and temperature rise characteristics of the torsional vibration damper, which provide a theoretical basis for the structural optimization and control strategy design of the MRG torsional vibration damper considering temperature as a factor.

Three-dimensional NAND flash memory with high carrier injection efficiency has been of great interest to computing in memory for its stronger capability to deal with big data than that of conventional von Neumann architecture. Here, we first report the carrier injection efficiency of 3D NAND flash memory based on a nanocrystalline silicon floating gate, which can be controlled by a novel design of the control layer. The carrier injection efficiency in nanocrystalline Si can be monitored by the capacitance–voltage (C–V) hysteresis direction of an nc-Si floating-gate MOS structure. When the control layer thickness of the nanocrystalline silicon floating gate is 25 nm, the C–V hysteresis always maintains the counterclockwise direction under different step sizes of scanning bias. In contrast, the direction of the C–V hysteresis can be changed from counterclockwise to clockwise when the thickness of the control barrier is reduced to 22 nm. The clockwise direction of the C–V curve is due to the carrier injection from the top electrode into the defect state of the SiNx control layer. Our discovery illustrates that the thicker SiNx control layer can block the transfer of carriers from the top electrode to the SiNx, thereby improving the carrier injection efficiency from the Si substrate to the nc-Si layer. The relationship between the carrier injection and the C–V hysteresis direction is further revealed by using the energy band model, thus explaining the transition mechanism of the C–V hysteresis direction. Our report is conducive to optimizing the performance of 3D NAND flash memory based on an nc-Si floating gate, which will be better used in the field of in-memory computing.

Artificial neural networks, as a game-changer to break up the bottleneck of classical von Neumann architectures, have attracted great interest recently. As a unit of artificial neural networks, memristive devices play a key role due to their similarity to biological synapses in structure, dynamics, and electrical behaviors. To achieve highly accurate neuromorphic computing, memristive devices with a controllable memory window and high uniformity are vitally important. Here, we first report that the controllable memory window of an HfO2/TiOx memristive device can be obtained by tuning the thickness ratio of the sublayer. It was found the memory window increased with decreases in the thickness ratio of HfO2 and TiOx. Notably, the coefficients of variation of the high-resistance state and the low-resistance state of the nanocrystalline HfO2/TiOx memristor were reduced by 74% and 86% compared with the as-deposited HfO2/TiOx memristor. The position of the conductive pathway could be localized by the nanocrystalline HfO2 and TiO2 dot, leading to a substantial improvement in the switching uniformity. The nanocrystalline HfO2/TiOx memristive device showed stable, controllable biological functions, including long-term potentiation, long-term depression, and spike-time-dependent plasticity, as well as the visual learning capability, displaying the great potential application for neuromorphic computing in brain-inspired intelligent systems.

The conventional pneumatic soft robot has the problem of insufficient stiffness, while in the magnetorheological soft robot, the magnetic field provided by electromagnet has the disadvantage of oversized structure and poor flexibility. This paper presents a variable stiffness pneumatic soft robot based on magnetorheological grease (MRG) to solve these problems. Its three soft fingers cooperate with the adjustable gripper to adjust the gripping range for the robot hand, and it is used to provide gripping driving force through the bending drive. The MRG layer is designed on the gripping surface to provide adaptivity and rigid support for the gripped objects. A magnetic-air structure consisting of a Halbach array and Halbach array actuator is designed inside the soft fingers to provide a flexible magnetic field for the MRG layer. Theoretical and simulation analysis is carried out, and the results show that the state of the MRG changes and the stiffness of the clamping surface changes under the working pressure of 30 kPa. Finally, the experiment further proves the variable and high adaptivity of the surface stiffness of the gripping surface to reduce the damage to the gripped objects.

To enable a-SiCx:H-based memristors to be integrated into brain-inspired chips, and to efficiently deal with the massive and diverse data, high switching uniformity of the a-SiC0.11:H memristor is urgently needed. In this study, we introduced a TiSbTe layer into an a-SiC0.11:H memristor, and successfully observed the ultra-high uniformity of the TiSbTe/a-SiC0.11:H memristor device. Compared with the a-SiC0.11:H memristor, the cycle-to-cycle coefficient of variation in the high resistance state and the low resistance state of TiSbTe/a-SiC0.11:H memristors was reduced by 92.5% and 66.4%, respectively. Moreover, the device-to-device coefficient of variation in the high resistance state and the low resistance state of TiSbTe/a-SiC0.11:H memristors decreased by 93.6% and 86.3%, respectively. A high-resolution transmission electron microscope revealed that a permanent TiSbTe nanocrystalline conductive nanofilament was formed in the TiSbTe layer during the DC sweeping process. The localized electric field of the TiSbTe nanocrystalline was beneficial for confining the position of the conductive filaments in the a-SiC0.11:H film, which contributed to improving the uniformity of the device. The temperature-dependent I-V characteristic further confirmed that the bridge and rupture of the Si dangling bond nanopathway was responsible for the resistive switching of the TiSbTe/a-SiC0.11:H device. The ultra-high uniformity of the TiSbTe/a-SiC0.11:H device ensured the successful implementation of biosynaptic functions such as spike-duration-dependent plasticity, long-term potentiation, long-term depression, and spike-timing-dependent plasticity. Furthermore, visual learning capability could be simulated through changing the conductance of the TiSbTe/a-SiC0.11:H device. Our discovery of the ultra-high uniformity of TiSbTe/a-SiC0.11:H memristor devices provides an avenue for their integration into the next generation of AI chips.

Magnetorheological (MR) absorbers in the artillery recoil systems are usually used to dissipate the impact energy as much as possible and reduce the recoil force transmitted to the artillery carriage, while the firing stability of artillery during the buffer process is rarely considered. In this paper, we analyzed the firing stability characteristics of the fixed artillery and the field artillery systems and established corresponding mechanical models. Then, we proposed the ideal recoil F–v curves of these two kinds of artillery, respectively. The “platform effect” of recoil curve was taken as the recoil force control target of the fixed artillery, while based on the firing stability, the linear segmented recoil curve was drawn up as the ideal recoil buffer control target of the field artillery. To verify the feasibility and controllability of the designed multi-stage MR absorber in two kinds of recoil buffer system, the impact tests were conducted under different current loadings. The test results show that the designed MR absorber can realize different buffer control effects by changing the input current, but the ideal “platform effect” recoil curve of the fixed artillery cannot be completely realized due to small controllable damping force output. In the field artillery recoil system, the MR absorber can realize ideal recoil buffer control in the range of 0°–25° firing angles.

Many applications of wireless power transmission (WPT) require high misalignment tolerance. However, the transmission power of WPT is highly susceptible to the misalignment. To solve this problem, the magnetic resonant WPT control method with high misalignment tolerance is proposed here. First, based on the general mutual model, the complex ratio transformer model is established. This model gives an intuitive physical picture in power transmission process and frequency splitting phenomenon. Second, approximately constant voltage gain at frequency splitting point in a wide range of misalignment is analysed. Considering this frequency splitting characteristics of Magnetic resonant WPT, the maximum peak point tracking control methods for wide misalignment, maintaining constant output power is proposed. Finally, the corresponding simulation and experimental validation is given, demonstrating the feasibility of the control method. When the misalignment reached 40%, the fluctuation of the output voltage will be

In order to increase the power rating of electric vehicles, insulated gate bipolar translator (IGBT) modules with multiple power terminals are usually adopted. The transient current sharing of the same polarity power terminals is related to the stray inductance in the branches of the bus-bar. Based on the laminated bus-bar of a three-phase inverter in the electric vehicles that consists of asymmetrical parallel branches, this paper investigates the transient current imbalance sharing caused by the asymmetrical stray inductance in the parallel branches of the bus-bar from the view of energy storing and releasing of stray inductance for the first time. Besides, the partial self-inductance and mutual-inductance model of the parallel branches is set up. Finally, a high-precision partial stray inductance measurement method is proposed, and the accuracy of the partial stray inductance model for asymmetrical parallel branches is verified by experimental tests.

In 1968, Steinberg [Endomorphisms of Linear Algebraic Groups, Memoirs of the American Mathematical Society, 80 (American Mathematical Society, Providence, RI, 1968)] proved a theorem stating that the exterior powers of an irreducible reflection representation of a Euclidean reflection group are again irreducible and pairwise nonisomorphic. We extend this result to a more general context where the inner product invariant under the group action may not necessarily exist. [ABSTRACT FROM AUTHOR]