Gap exists in the interface of cement asphalt emulsion mortar and CRTS I track slab universally, which is more severe at four corners than other parts of the track slab. In this work, the temperature and elevation of ...Gap exists in the interface of cement asphalt emulsion mortar and CRTS I track slab universally, which is more severe at four corners than other parts of the track slab. In this work, the temperature and elevation of CRTS I slab track with and without rail were measured continuously to study the influence mechanism of rail on the gap. The results show that the alternating temperature gradient of track slab is the main reason that causes the gap, and laying rail can efficiently decrease the gap size in the slab track without rail. Compared with the slab track without rail, the maximum elevation occurred at the corner, the maximum gapwidth and the maximum gap depth of the slab track with rail laid were decreased by 0.45 mm （25.7%）, 0.75 mm （46.6%） and 9.5 mm （59.4%）, respectively; meanwhile, the disqualification ratio at corners was reduced to 5.9%, which is 50% less than that of the track without rail. When elevation mismatch occurs in adjacent track slabs, a gasket should be placed at rail-bearing bed below the track slab in order to avoid the lower slab being dragged up by the higher slab and the further occurrence of new gap.展开更多
According to the wire and nozzle movement track in groove, the movement parameters of wire were memorized and recalled for the following top welds by using a single chip computer. In this paper, it was also discussed...According to the wire and nozzle movement track in groove, the movement parameters of wire were memorized and recalled for the following top welds by using a single chip computer. In this paper, it was also discussed that the design problems of correcting deviation of wire movement track in narrow gap submerged arc welding process must be noticed in order to obtain the sound welding result.展开更多
The performance of the state-of-the-art Deep Reinforcement algorithms such as Proximal Policy Optimization, Twin Delayed Deep Deterministic Policy Gradient, and Soft Actor-Critic for generating a quadruped walking gai...The performance of the state-of-the-art Deep Reinforcement algorithms such as Proximal Policy Optimization, Twin Delayed Deep Deterministic Policy Gradient, and Soft Actor-Critic for generating a quadruped walking gait in a virtual environment was presented in previous research work titled “A Comparison of PPO, TD3, and SAC Reinforcement Algorithms for Quadruped Walking Gait Generation”. We demonstrated that the Soft Actor-Critic Reinforcement algorithm had the best performance generating the walking gait for a quadruped in certain instances of sensor configurations in the virtual environment. In this work, we present the performance analysis of the state-of-the-art Deep Reinforcement algorithms above for quadruped walking gait generation in a physical environment. The performance is determined in the physical environment by transfer learning augmented by real-time reinforcement learning for gait generation on a physical quadruped. The performance is analyzed on a quadruped equipped with a range of sensors such as position tracking using a stereo camera, contact sensing of each of the robot legs through force resistive sensors, and proprioceptive information of the robot body and legs using nine inertial measurement units. The performance comparison is presented using the metrics associated with the walking gait: average forward velocity (m/s), average forward velocity variance, average lateral velocity (m/s), average lateral velocity variance, and quaternion root mean square deviation. The strengths and weaknesses of each algorithm for the given task on the physical quadruped are discussed.展开更多
基金supported by the National Natural Science foundation of China (No. 51408610)
文摘Gap exists in the interface of cement asphalt emulsion mortar and CRTS I track slab universally, which is more severe at four corners than other parts of the track slab. In this work, the temperature and elevation of CRTS I slab track with and without rail were measured continuously to study the influence mechanism of rail on the gap. The results show that the alternating temperature gradient of track slab is the main reason that causes the gap, and laying rail can efficiently decrease the gap size in the slab track without rail. Compared with the slab track without rail, the maximum elevation occurred at the corner, the maximum gapwidth and the maximum gap depth of the slab track with rail laid were decreased by 0.45 mm （25.7%）, 0.75 mm （46.6%） and 9.5 mm （59.4%）, respectively; meanwhile, the disqualification ratio at corners was reduced to 5.9%, which is 50% less than that of the track without rail. When elevation mismatch occurs in adjacent track slabs, a gasket should be placed at rail-bearing bed below the track slab in order to avoid the lower slab being dragged up by the higher slab and the further occurrence of new gap.
文摘According to the wire and nozzle movement track in groove, the movement parameters of wire were memorized and recalled for the following top welds by using a single chip computer. In this paper, it was also discussed that the design problems of correcting deviation of wire movement track in narrow gap submerged arc welding process must be noticed in order to obtain the sound welding result.
基金Project(2022YFB2603400) supported by the National Key R&D Program of ChinaProjects(52208449, 52108420) supported by the National Natural Science Foundation of ChinaProject(2022NSFSC1908) supported by the Natural Science Foundation of Sichuan Province,China。
文摘The performance of the state-of-the-art Deep Reinforcement algorithms such as Proximal Policy Optimization, Twin Delayed Deep Deterministic Policy Gradient, and Soft Actor-Critic for generating a quadruped walking gait in a virtual environment was presented in previous research work titled “A Comparison of PPO, TD3, and SAC Reinforcement Algorithms for Quadruped Walking Gait Generation”. We demonstrated that the Soft Actor-Critic Reinforcement algorithm had the best performance generating the walking gait for a quadruped in certain instances of sensor configurations in the virtual environment. In this work, we present the performance analysis of the state-of-the-art Deep Reinforcement algorithms above for quadruped walking gait generation in a physical environment. The performance is determined in the physical environment by transfer learning augmented by real-time reinforcement learning for gait generation on a physical quadruped. The performance is analyzed on a quadruped equipped with a range of sensors such as position tracking using a stereo camera, contact sensing of each of the robot legs through force resistive sensors, and proprioceptive information of the robot body and legs using nine inertial measurement units. The performance comparison is presented using the metrics associated with the walking gait: average forward velocity (m/s), average forward velocity variance, average lateral velocity (m/s), average lateral velocity variance, and quaternion root mean square deviation. The strengths and weaknesses of each algorithm for the given task on the physical quadruped are discussed.
