Due to bolt looseness or operating ambient temperature, fit clearance can often be found between the outer ring and housing. The vibration characteristics of a cylindrical roller bearing with localized defects are greatly affected by the fit clearance and the accuracy of bearing fault diagnosis may be reduced. Thus, a mathematical model for a cylindrical roller bearing was constructed and the interaction between the outer ring and housing was described. The classical localized defects were modeled, such as the inner ring defect, outer ring defect and roller defect. The relative experiments were conducted to check the constructed model. Then, it was found that the RMS (Root Mean Square) of housing acceleration decreased with increasing housing stiffness and viscous damping. When the fit clearance and friction coefficient increased, the RMS values increased. Except for housing stiffness and viscous damping, there were no uniform change rules of defect frequency amplitudes for other conditions. In the bearing with an outer ring defect or roller defect, the shock times of housing acceleration and the contact force between outer ring and housing were delayed, while fit clearance decreased. However, contrary variation trends were found for the inner ring defect. If the phase difference between defect location and rotor unbalanced force increased, the RMS and acceleration fluctuation amplitudes for the inner ring defect decreased. When the location angle of the outer ring defect increased, RMS and frequency amplitudes increased and RMS_y/RMS decreased. The calculated results may provide the theoretical foundation for condition monitoring rotating machinery systems.

In order to accurately evaluate the working state of RV reducer, a fault identification method based on the fault identification model established by Self-Organizing Feature Map (SOM) Neural Network is proposed. Firstly, the data measured by the RV reducer test platform are analyzed by wavelet to obtain the wavelet coefficient. Then, combined with the efficiency data of RV reducer, the mean square frequency, center of gravity frequency and frequency variance of the two groups of data are calculated after Fourier transform and power spectrum analysis. After optimization, several eigenvalues are obtained. The eigenvalues are input into the competitive neural network and SOM neural network to establish the fault identification model. Finally, the results of the fault identification model established by the competitive neural network and SOM neural network are compared. The prediction results show that the fault identification model established by SOM neural network can effectively determine the working state of RV reducer.

In modern complex environments, achieving accurate and efficient target localization is essential in numerous fields. However, existing systems often face limitations in both accuracy and the ability to recognize small targets. In this study, we propose a bionic stabilized localization system based on CA-YOLO, designed to enhance both target localization accuracy and small target recognition capabilities. Acting as the ”brain” of the system, the target detection algorithm emulates the visual focusing mechanism of animals by integrating bionic modules into the YOLO backbone network. These modules include the introduction of a small target detection head and the development of a Characteristic Fusion Attention Mechanism (CFAM). Furthermore, drawing inspiration from the human Vestibulo- Ocular Reflex (VOR), a bionic pan-tilt tracking control strategy is developed, which incorporates central positioning, stability optimization, adaptive control coefficient adjustment, and an intelligent recapture function. The experimental results show that CA-YOLO outperforms the original model on standard datasets (COCO and VisDrone), with average accuracy metrics improved by 3.94%and 4.90%, respectively. Further time-sensitive target localization experiments validate the effectiveness and practicality of this bionic stabilized localization system.

More hemiplegia patients tend to use equipment for rehabilitation training due to the lack of physical therapists and the low effect of manual training. Nowadays, lower limb rehabilitation training devices for patients in grade 2 of the Medical Research Council (MRC-2) scale are still scarce and have some issues of poor autonomy and cannot relieve the muscle weakness of patients. To address these problems, a prototype based on gravity balance was designed with the combination of springs and linkages to enable patients to passively experience the rehabilitation training in the state of balancing the gravity of lower limbs. The motion of the mechanism was analyzed to obtain the functional relation between the motor rotation angle and the joints’ angle. Based on the principle of constant potential energy, a gravity balance mathematical model of the device was established, analyzed, and simulated. Moreover, through the training experiment, the results show that when subjects in three different weights were trained under the rehabilitation device with and without gravity balance, the required torques of the motor and EMG signal strength of the knee and hip joints decreased by a degree of significance, which verified the effectiveness of the device’s gravity balancing characteristics for MRC-2 patients.

In order to achieve controllable behavior in soft robots, it is necessary to analyze the dynamic response characteristics of soft actuators and thereby gain a deeper understanding of the dynamic response mechanisms of actuators. In this study, the two-way fluid structural interaction (FSI) method was used for the first time to reveal the transient flow field inside the soft pneumatic actuator and its influences on the dynamic motions under high-speed pressurization. Moreover, the simulation results were verified by experimentally by using a high-speed camera to capture the transient morphology of the actuator. The simulation results indicated that streamlines inside the actuator were not uniformly distributed, and the air pressure was not even either. Driven by the high-speed air flow, the head of actuator bent at first, resulting in the expansion of the chambers gradually, followed by the arching of the actuator and more violent variation in air streamlines and pressure distribution. Accompanying the deformation of the actuator, the stress distribution, as well as the streamline and pressure, changed dramatically within a total 0.1 second. Experimentally, the transient morphologies captured by the high-speed camera at various moments coincided with the simulation results. Compared to the conventional solid-mechanics finite element analysis (FEA) method, the FSI simulation showed better precision and accuracy. This work serves as a valuable reference for research on the fine-structured design and controllable motion of soft actuators and soft robots

This article presents a virtual tactile display using a shape-displaying method with flexible tendon-driven transmission to enhance performance. Sixteen tactors move perpendicularly in a 4 × 4 module to render the local shape of the virtual object to the skin of the user’s fingertip. We detail the display structure design and the transmission system, and we combine the compact design of the drive unit and tactor module with a flexible tendon-driven transmission to address the ergonomic constraints on previous devices and make them more suitable for tactile feedback. In this work, we integrate the display with leap motion controller and a ray detection rendering method to generate tactile feedback. To evaluate the performance, we perform a virtual touch experiment that assesses how much the display can render the surface of three-dimensional objects to aid the participant to match the tactile sensation with visual stimuli in the virtual scene. Results show that the display improves the user experience and has good feasibility and effectiveness. In addition, the portable structure allows the user’s hand to move more freely without redundant restrictions, and the larger tactor amplitude provides more shape patterns than previous models.