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With the rapid development of modern robotics and medical industry, the use of rehabilitation robots for the treatment of patients with lower limb sports injuries has become one of the research hotspots at home and abroad. In order to achieve better rehabilitation treatment effect, trajectory planning of a three-degree-of-freedom lower limb rehabilitation robot is studied, and the motion law of healthy ankle joint is simulated to optimize the trajectory design of the lower limb rehabilitation robot. Based on the rehabilitation, injury mechanism, and motion form of the ankle joint, a comparative analysis of several low degree of freedom planar symmetric parallel mechanisms is conducted, and a design prototype using a 2UU-UPU mechanism as the rehabilitation actuator is determined; research on trajectory planning for lower limb rehabilitation training of lower limb rehabilitation robots, trajectory planning motion formulas for cycloidal motion laws and superimposed cycloidal motion laws are derived, and the rationality of trajectory under different rehabilitation training conditions is verified. In order to further explore a more reasonable rehabilitation trajectory, the optical motion capture system is used to collect the ankle joint movement trajectory in the sitting position, establish the rehabilitation trajectory constraints, improve the similarity between the planned trajectory and the human movement, and achieve better rehabilitation effect.

According to the requirements of energy supply of lunar exploration engineering spacecraft， a novel adjustable solar panel with three degrees of freedom is proposed. The 2UU-UPU parallel mechanism is adopted as the prototype of adjustable solar panel mechanism. The constraint equation and positional relationship of the adjustable solar panel mechanism are analyzed， the degree of freedom of parallel robot is solved by the theory of spiral， and the positional anti-solution equation is introduced by the modified Kutzbach-Grübler formula. On this basis， the system is simulated by using Adams software， and the simulation results are compared with theoretical numerical calculations to verify the correctness of mathematical modeling of the adjustable solar panel mechanical and the rationality of the three-dimensional solid model.

The rehabilitation of the upper limbs of human body is determined by the recovery of shoulder joint movement function. Based on the analysis of the shoulder joint physical characteristics and movement characteristics of the shoulder joint,according to shoulder rehabilitation exercise training requirements,a novel shoulder joint rehabilitation robot is designed based on 3- DOF series- parallel mechanism. The shoulder joint has three rotation degrees of freedom and can complete three- dimensional composite sports. The series- parallel mechanism is adopted to ensure the neutral and stability of mechanism,and the mechanism movement space is increased. By using the Creo software,the three- dimensional modeling of the shoulder joint rehabilitation robot is carried out. According to the methods of nerve repairment,aiming at the rehabilitation of shoulder joint in soft paralysis,the shoulder joint rehabilitation robot is simulated. The results of the analysis show that the shoulder joint rehabilitation robot can meet the needs of patients with soft paralysis,and the design of the shoulder joint rehabilitation robot is reasonable. It laid a theoretical foundation for the design and research of shoulder rehabilitation robot.

The lower limb rehabilitation robot is an automated functional rehabilitation equipment,with a scientific and reasonable rehabilitation conditions,the patients can make their lower extremity motor function get good recovery. In order to improve the rehabilitation training work space of the lower limb rehabilitation robot,increases the bearing capacity,the statics analysis of rehabilitation robot is very important. A kind of lower limbs rehabilitative robot with 3- UPS parallel mechanism as the mechanism prototype is puts forward,the statics equations of the lower limb rehabilitation robot driving force and output force are established based on the virtual work principle,the static performance evaluation index is defined and the evaluation index distribution map is drawn. The relationship between the structure parameters and the statics performance evaluation indexes is analyzed,the influence of structure parameters on the statics performance is obtained. And the lower limb rehabilitation robot is designed based on the structure parameters. The analysis results lay a foundation for further analysis and research of the lower limbs rehabilitative robot.

According to the working principle of pulse oxygen supplies, we analyze how to realize the control of the oxygen flow by double different valves. a two-dimensional fuzzy control system is proposed to solve the unstable problem, which is brought by the shortcomings of the open-loop control system. We add a new parameter, the rate of the differential pressure signal changes, which contributes to a close –loop control system and increases the stability of the system. The experiments and the data show that the fuzzy control system make the process of breathing much more comfortable and solve the hysteresis and overshoot caused by the open-loop control system. The product reliability has been greatly improved.

Urban transportation systems, particularly underground interchanges, present significant challenges for sustainable and resilient urban design due to their complex road geometries and dense traffic signage. These challenges are further compounded by the interaction of diverse road users, which heightens the risk of accidents. To enhance both safety and sustainability, this study integrates advanced driving simulation techniques with machine learning models to improve driving safety and comfort in underground interchanges. By utilizing a driving simulator and 3D modeling, real-world conditions were replicated to design key traffic safety features with an emphasis on sustainability and driver well-being. Critical safety parameters, including speed, acceleration, and pedal use, were analyzed alongside comfort metrics such as lateral acceleration and steering torque. The LightGBM machine learning model was used to classify safety and comfort grades with an accuracy of 97.06%. An important ranking identified entrance signage and deceleration zones as having the greatest impact on safety and comfort, while basic road sections were less influential. These findings underscore the importance of considering visual cues, such as markings and wall color, in creating safer and more comfortable underground road systems. This study's methodology and results offer valuable insights for urban planners and engineers aiming to design transportation systems that are both safe and aligned with sustainable urban mobility objectives. [ABSTRACT FROM AUTHOR]

In-line inspection (ILI) is important to pipeline integrity management since it can detect pipeline defects and identify potential failure locations through periodical examinations. However, effectively evaluating defects based on ILI data is challenging. Measurements of ILI are easily influenced by instrument performance and maintenance activities, leading to unmatched and imbalanced data. Poor ILI data make it difficult to establish defect growth models based on multiple inspections. This study conducted comprehensive analysis of ILI data for evaluating corrosion defects of a steel pipeline. First, statistical analysis was performed on raw data to visualize distributions of corrosion depths and number of corrosions. Second, hierarchical clustering method was used to classify corrosion severity levels based on features of corrosion depth and estimated repair factor. The interaction effect between adjacent corrosions was considered. Machine learning methods, including k-nearest neighbor, support vector machine, random forest, and light gradient boosting machine were used to explore the relationship between the location parameters of adjacent corrosions and severity levels. Then, maximum corrosion depths and corrosion density were filtered from raw ILI data of multiple inspections, which were critical for pipeline failure prediction. Finally, distribution parameters were fitted to establish stochastic growth models on maximum corrosion depth and corrosion number density. This study presents data analytics based approach to obtain valid information from ILI data in practice. [ABSTRACT FROM AUTHOR]