Wind power converter(WPC)is a key part of a wind power unit which delivers electric energy to power *** of a large number of semiconductors,WPC has a high failure *** paper proposes a method to accurately evaluate the...
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Wind power converter(WPC)is a key part of a wind power unit which delivers electric energy to power *** of a large number of semiconductors,WPC has a high failure *** paper proposes a method to accurately evaluate the reliability of WPC,which is crucial for the design and maintenance of wind ***,the index of effective temperature(ET)is presented to quantify the effects of temperature and humidity on the semiconductor operation.A novel method is proposed to evaluate the lifetime and calculate the aging failure rates of the semiconductors considering the fluctuations of ***,the failure mode and effect analysis(FMEA)of WPC is investigated based on the topology and control *** conventional two-state reliability model of the WPC is extended to the multi-state reliability model where the partial working state under the fault-tolerant control scheme is ***,a reliability evaluation framework is established to calculate the parameters of the WPC reliability model considering the variable failure rates and repair activities of *** studies are designed to verfify the proposed method using a practical wind turbine.
Snake robot is a robot that can move freely in a small and complex space with super-redundant DOF and motion flexibility, and it has been proven to have a wide range of application prospects. RGB-D camera is a new typ...
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Currently, prosthetic hands can only achieve several prespecified and discrete hand motion patterns from popular myoelectric control schemes using electromyography(EMG) signals. To achieve continuous and stable graspi...
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Currently, prosthetic hands can only achieve several prespecified and discrete hand motion patterns from popular myoelectric control schemes using electromyography(EMG) signals. To achieve continuous and stable grasping within the discrete motion pattern, this paper proposes a control strategy using a customized, flexible capacitance-based proximity-tactile sensor. This sensor is integrated at the fingertip and measures the distance and force before and after contact with an object. During the pregrasping phase, each fingertip’s position is controlled based on the distance between the fingertip and the object to make all fingertips synchronously approach the object at the same distance. Once contact is established, the sensor turns to output the tactile information, by which the contact force of each fingertip is finely controlled. Finally, the method is introduced into the human-machine interaction control for a myoelectric prosthetic hand. The experimental results demonstrate that continuous and stable grasping could be achieved by the proposed control method within the subject’s discrete EMG motion mode. The subject also obtained tactile feedback through the transcutaneous electrical nerve stimulation after contact.
Multi-agent path finding (MAPF) is an essential issue for warehouse automation, where multiple agents plan collision-free paths from the start to goal positions. Reinforcement learning (RL) has been employed to develo...
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Multi-agent path finding (MAPF) is an essential issue for warehouse automation, where multiple agents plan collision-free paths from the start to goal positions. Reinforcement learning (RL) has been employed to develop partially observable distributed MAPF methods that can be scaled to any number of agents. However, existing RL-based MAPF methods still have some limitations in handling redundant information and avoiding deadlock, resulting in a low success rate or longer makespan. This paper proposes a Priority-aware Communication & Experience learning method (PCE), which combines RL with a novel priority-aware multi-agent communication and a new priority-aware deadlock experience replay to tackle this challenge. To be specific, our innovation encompasses two-fold. Our proposed communication mechanism aims to handle redundant information, which establishes a dynamic communication topology based on agents' priorities and proposes a two-head priority-aware graph attention network to aggregate information. In order to help the agent avoid deadlock, we prioritize the expert experience that solves the deadlock when performing experience replay. We conduct multiple simulation experiments on warehouse-like structured grid maps. Compared with the state-of-the-art RL-based MAPF methods, PCE performs significantly better with a higher success rate and lower makespan in small and large MAPF and higher average throughput in the lifelong MAPF, which can further improve the efficiency of warehouse automation. Finally, we validate PCE using three Turtlebot3-Burger robots, which shows that PCE can be applied in real warehouse automation scenarios. IEEE
In this study,the competitive failure mechanism of bolt loosening and fatigue is elucidated via competitive failure tests on bolts under composite *** on the competitive failure mechanism,the mode prediction model and...
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In this study,the competitive failure mechanism of bolt loosening and fatigue is elucidated via competitive failure tests on bolts under composite *** on the competitive failure mechanism,the mode prediction model and“load ratio-life prediction curve”(ξ-N curve)of the bolt competitive failure are *** the poor correlation of theξ-N curve,an evaluation model of the bolt competitive failure life is proposed based on Miner’s linear damage accumulation *** on the force analysis of the thread surface and simulation of the bolt connection under composite excitation,a theoretical equation of the bolt competitive failure life is established to validate the model for evaluating the bolt competitive failure *** results reveal that the proposed model can accurately predict the competitive failure life of bolts under composite excitation,and thereby,it can provide guidance to engineering applications.
This study aims to design and optimize a motor-driven frog-like jumping robot leg for efficient vertical jumps and multiple consecutive horizontal jumps. We have conducted bionic research on frog legs' structure a...
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The Mars quadrotor is a vertical take-off and landing aerial platform developed to enhance the efficiency of Mars exploration. The four-blade rotor has a high thrust coefficient due to its high solidity, which enables...
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This paper analyzed the impact of phase back electromotive force (back EMF) harmonics on torque of dual three phase permanent magnet synchronous motor (DTPPMSM) from the view of electromagnetic power, and proposed a t...
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With the increasing requirement for agile and efficient controllers in safety-critical scenarios, controllers that exhibit both agility and safety are attracting attention, especially in the aerial robotics domain. Th...
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With the increasing requirement for agile and efficient controllers in safety-critical scenarios, controllers that exhibit both agility and safety are attracting attention, especially in the aerial robotics domain. This paper focuses on the safety issue of Reinforcement Learning (RL)-based control for agile quadrotor flight in restricted environments. To this end, we propose a unified Adaptive Safety Predictive Corrector (ASPC) to certify each output action of the RL-based controller in real-time, ensuring its safety while maintaining agility. Specifically, we develop the ASPC as a finite-horizon optimal control problem, formulated by a variant of Model Predictive Control (MPC). Given the safety constraints determined by the restricted environment, the objective of minimizing loss of agility can be optimized by reducing the difference between the actions of RL and ASPC. As the safety constraints are decoupled from the RL-based control policy, the ASPC is plug-and-play and can be incorporated into any potentially unsafe controllers. Furthermore, an online adaptive regulator is presented to adjust the safety bounds of the state constraints with respect to the environment changes, extending the proposed ASPC to different restricted environments. Finally, simulations and real-world experiments are demonstrated in various restricted environments to validate the effectiveness of the proposed ASPC. IEEE
Wear topography is a significant indicator of tribological behavior for the inspection of machine health *** intelligent in-suit wear assessment method for random topography is here ***-dimension(3D)topography is empl...
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Wear topography is a significant indicator of tribological behavior for the inspection of machine health *** intelligent in-suit wear assessment method for random topography is here ***-dimension(3D)topography is employed to address the uncertainties in wear ***,3D topography reconstruction from a worn surface is accomplished with photometric stereo vision(PSV).Then,the wear features are identified by a contrastive learning-based extraction network(WSFE-Net)including the relative and temporal prior knowledge of wear ***,the typical wear degrees including mild,moderate,and severe are evaluated by a wear severity assessment network(WSA-Net)for the probability and its associated uncertainty based on subjective *** integrating the evidence information from 2D and 3D-damage surfaces with Dempster–Shafer(D–S)evidence,the uncertainty of severity assessment results is further *** proposed model could constrain the uncertainty below 0.066 in the wear degree evaluation of a continuous wear experiment,which reflects the high credibility of the evaluation result.
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