Vibration performance prediction and reliability analysis for rolling bearing

The bearing vibration signal is a rich dynamic symptom of bearing wear, and the vibration signal of rolling bearing presents chaotic characteristics. Input and output variables of vibration signal can be constructed through phase space reconstruction, the Input and output variables can be imported into the prediction model for prediction. The prediction accuracy of the extreme learning machine (ELM) model, Kriging model and RBF model are compared, the results show that ELM has higher accuracy, so ELM chaos model is used to predict the future vibration time series data, and the forecasting error can be obtained by comparing the prediction value with the actual values so as to verity the feasibility of the ELM model. The prediction results of the future state of the bearing are processed as the grey-bootstrap method, and the performance reliability prediction of the bearing is realized by the Poisson counting process. The experimental data show that with the deepening of the fault degree, the reliability performance decreases gradually. The reliability performance of the bearing without fault is 100 %, and the reliability performance is 47.56 % when the inner ring faulty size is 0.72 mm

Research on an Ankle Joint Auxiliary Rehabilitation Robot with a Rigid-Flexible Hybrid Drive Based on a 2-S′PS′ Mechanism

An ankle joint auxiliary rehabilitation robot has been developed, which consists of an upper platform, a lower platform, a dorsiflexion/plantar flexion drive system, a varus/valgus drive system, and some connecting parts. The upper platform connects to the lower platform through a ball pin pair and two driving branch chains based on the S′PS′ mechanism. Although the robot has two degrees of freedom (DOF), the upper platform can realize three kinds of motion. To achieve ankle joint auxiliary rehabilitation, the ankle joint of patients on the upper platform makes a bionic motion. The robot uses a centre ball pin pair as the main support to simulate the motion of the ankle joint; the upper platform and the centre ball pin pair construct a mirror image of a patient’s foot and ankle joint, which satisfies the human body physiological characteristics; the driving systems adopt a rigid-flexible hybrid structure; and the dorsiflexion/plantar flexion motion and the varus/valgus motion are decoupled. These structural features can avoid secondary damage to the patient. The rehabilitation process is considered, and energy consumption of the robot is studied. An experimental prototype demonstrates that the robot can simulate the motion of the human foot