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检索条件"任意字段=3rd International Conference on Robotics, Control and Automation Engineering, RCAE 2020"

共 546 条记录，以下是151-160 订阅

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Design a High-Frequency Dual Active Bridge Converter for Discrete Time Frequency

Design a High-Frequency Dual Active Bridge Converter for Dis...

引用

Advancements in Electrical, Electronics, Communication, Computing and automation (ICAECA), international conference on

作者： M. Karthik G. Hemalatha M. Mathankumar L. Sreevidya R. Deepalakshmi V. Kandasamy Department of Electrical and Electronics Engineering SRM Madurai College for Engineering and Technology Pottapalayam Tamil Nadu India Department of Robotics and Automation Sri Ramakrishna Engineering College Coimbatore Tamil Nadu India Department of Electrical and Electronics Engineering SRM Institute of Science and Technology Trichy Tamil Nadu India Department of Electrical and Electronics Engineering V.S.B College of Engineering Technical Campus Coimbatore Tamil Nadu India Department of Computer Science Engineering SRM Madurai College for Engineering and Technology Pottapalayam Tamil Nadu India Department of Electrical and Electronics Engineering Kumaraguru College of Technology Coimbatore India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

The dual active bridge (DAB) has become a crucial interface element in today's sophisticated systems. Renewable energy sources produce DC power, which is then stored in batteries, ultra-capacitors, and other energy storage devices. DAB is a crucial part of power exchange between two different buses because of its galvanic separation and bidirectional power transfer capabilities. The operation of the DAB is compatible with a broad range of input voltages and output loads. The creation of DAB is covered in most works. A well-known semiconductor integrated circuit with programmable control parameters is used in this straightforward, inexpensive method.

关键词： Time-frequency analysis Renewable energy sources Costs Bridge circuits Switched reluctance motors Stability analysis Batteries Telecommunication computing Time-domain analysis Stress

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Research on Driver’s License OCR Based on CRNN Deep Network

Research on Driver’s License OCR Based on CRNN Deep Network

引用

robotics, Artificial Intelligence and Intelligent control (RAIIC), international conference on

作者： Jun Wang Hongke Chen Chengyi College Jimei University Xiamen Fujian China School of Mechanical and Electrical Engineering & Automation Xiamen University Tan Kah Kee College Zhangzhou Fujian China

ISBN: (数字)9798350352627

ISBN: (纸本)9798350352634

A driver’s license OCR method based on deep learning was designed, in response to the poor performance of traditional methods in driver’s license recognition. Disturbed by equipment issues and external environment, the collected driver’s license images suffer from uneven lighting and tilting, which seriously affect the recognition effect. Carry out driver’s license pre-processing through image enhancement, tilt correction, red stamp localization, text ROI extraction, and character region segmentation. Then, recognize the extracted text regions based on the CRNN deep learning network model. The experimental results show that this method can achieve significantly better recognition performance than traditional methods, with character and field recognition accuracy respectively reaching 92.89% and 8.87%, proving its effectiveness.

关键词： Deep learning Image segmentation Image recognition Text recognition Optical character recognition Licenses Character recognition

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Application of lightweight YOLOv8n networks for insulator defect detection

Application of lightweight YOLOv8n networks for insulator de...

引用

robotics, Artificial Intelligence and Intelligent control (RAIIC), international conference on

作者： Fulin Ma Xinbin Chai Zhengzhong Gao College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China Wenshang Yiqiao Coal Mine Co Ltd Jining China

ISBN: (数字)9798350352627

ISBN: (纸本)9798350352634

To solve the problems of small insulator defect targets and complex background information in transmission lines, as well as the difficulty of edge-end devices to meet real-time detection requirements, a lightweight insulator defect detection algorithm based on YOLOv8n is proposed. The backbone network of YOLOv8n is reconstructed by introducing a lightweight bottleneck structure, GhostNetV2 BottleNeck, which reduces the number of network parameters and improves the detection speed of the model, and the CBAM attention mechanism is embedded in the backbone network, which improves the ability of the network to extract the target features, and thus improves the detection accuracy of the model. By validating the improved algorithmic model on the insulator dataset, the results show that the mean average accuracy of the improved algorithmic model reaches $85.7 \%$, and the detection speed reaches 171.4 frames $/ \mathrm{s}$, which verifies the effectiveness of the improved algorithmic model for the detection of insulators and their defects.

关键词： Solid modeling Accuracy Power transmission lines Image edge detection Insulators Feature extraction Real-time systems

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Improved Factor Graph Algorithm for Adaptive Weight Function Based on Residual Adjustment 1

引用

3rd international conference on Autonomous Unmanned Systems, ICAUS 2023

作者： Wang, Congcong Wang, Rong Zhao, Jingxin Xiong, Zhi Liu, Jianye Navigation Research Center College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China

ISBN: (数字)9789819710997

ISBN: (纸本)9789819710980

To address the issue of traditional factor graph methods being unable to handle the dynamic change in sensor measurement accuracy during the operational process, an adaptive weight function is introduced and an improved factor graph method based on adaptive weight is proposed. By calculating the residual between the predicted value of inertial preintegration and the measured value of auxiliary sensors in real-time, the fusion information weight of the corresponding factor nodes are dynamically adjusted. Compared with traditional factor graph algorithms, this method can improve the optimization accuracy and robustness of factor graph algorithms in the situation of step faults, gradual faults, or rejection faults in auxiliary sensors. The simulation experimental results show that when the auxiliary sensor produces measurement faults, compared with traditional factor graph method, the improved factor graph method based on adaptive weights has higher robustness and accuracy. When measurement faults occur in auxiliary sensors, its position, velocity, and attitude estimation accuracy RMSE values have been improved by more than 45%. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Adaptive weight function Factor graph Kernel function Residual adjustment

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Vibration control of a Smart Composite Engine Fan Blade by Neural Network controller

Vibration Control of a Smart Composite Engine Fan Blade by N...

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Computer, control and robotics (ICCCR), international conference on

作者： Tebogo Lucky Mamela Baoming Li Weiguo He Shunqi Zhang Engineering and Automation School of Mechatronic Shanghai University Shanghai P. R. China Zhejiang CHR Intelligent Equipment Co Ltd Zhejiang Jingun P. R. China

This research analyzes the adoption of an artificial neural network (ANN) method for a smart engine fan blade bonded with a piezoelectric (PZT) patch made of macro fiber composite (MFC) for vibration control and suppression. The MFC material that functions as a sensor and an actuator is embedded on the surface of the fan blade to provide structural active damping on the structure. The finite element model (FEM) also the system state-space model of the engine fan blade is formulated to establish the structural numerical model as a basis to initialize the impulse input disturbance to measure the performance of the controllers. To predict the future reaction of the smart fan blade, the recommended controller is trained using the nonlinear autoregressive moving average with an exogenous input model of order 2 (NARMA-L2). The PID-supplemented compensation method improves the controller's performance, and the NARMA-L2 and fuzzy generate the necessary control signal. The performance will then be assessed by contrasting the reactions of the NARMA-L2-PID, fuzzy-PID, and classical PID controllers under a specified dynamic excitation. The outcomes show that the proposed controller model is effective and reliable regardless of the input disturbance exerted on the structure's vibration response.

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A Method of Robot Grasping Based on Reinforcement Learning 3

A Method of Robot Grasping Based on Reinforcement Learning

引用

2021 3rd international conference on robotics, Intelligent control and Artificial Intelligence, ICRICA 2021

作者： Lu, Liangliang Zhang, Ming He, Dingxin Gu, Qiang Gong, Dongjun Fu, Lei Artificial Intelligence and Automation College Huazhong University of Science and Technology Wuhan China Guyue Home PS-Micro Wuhan China School of Mechanical Engineering Wuhan Vocational College of Software and Engineering Wuhan China

In this paper, we propose a method for robot grasping based on reinforcement learning. A six-degree-of-freedom robot is used to execute the grasping action, and an RGB-D camera is used as a sensing module to collect the information. Different from previous model-based methods, our whole system is data-driven. In order to better grasp a bunch of randomly placed objects, the pushing action is added to spare more space for grasping. The whole process is described as a Markov decision process (MDP). The training is carried out in simulation. Experimental results show that our method can complete the grasping work efficiently, especially in those complicated and difficult scenarios. At the same time, the model can be directly applied in actual grasping tasks which greatly reduce the risk of training in the physical world. © Published under licence by IOP Publishing Ltd.

关键词： Reinforcement learning

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A New Type of Wind Generator Blades Mechanical Automatic control System 3

A New Type of Wind Generator Blades Mechanical Automatic Con...

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3rd international conference on Communications, Information, Electronic and Energy Systems, CIEES 2022

作者： Fazylova, Alina Iliev, Teodor Satbayev University Dept. of Robotocs And Engineering Tools of Automation Almaty Kazakhstan Almaty University of Power Engineering And Telecommunications Named After G.Daukeev Dept. of Electronics And Robotics Almaty Kazakhstan University of Ruse Dept. of Telecommunications Ruse Bulgaria

ISBN: (数字)9781665491495

ISBN: (纸本)9781665491495

Wind power in Kazakhstan, following the global trend, continues to develop and there is an increase in the number of RES power plants. The development of wind energy involves the creation of large-sized and high-power installations. The rotors of wind turbines experience heavy loads on their design. Thus, the actual task and problem for the wind energy park of Kazakhstan is to reduce the load on the structure by regulating it during wind gusts. The use of a control system for the rotation of the blades makes it possible to significantly reduce the load on the structure. However, due to the non- linearity of the process and the difficulty of accurately measuring the wind speed, the blade turning control system must be designed with great care. This paper presents the development of a lever mechanical system for controlling the blades of a wind turbine, which makes it possible to secure the operation of a wind generator. The purpose of the study is to develop a 3D model of a lever control system and create an automatic control system for it. A three-dimensional study of the rotor in various states of the rotor was carried out. This dynamic computer model is proof of the functionality of the communication system. The transfer function of the entire control system is also determined and, based on experimental data, a mathematical model of an experimental laboratory sample is developed. This installation will optimize the operation of a vertical axis wind generator by creating a wind flow control system for further converting the wind flow into electrical energy. © 2022 IEEE.

关键词： Wind power

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3D Porous Stacked Organic Electrochemical Transistor for Wearable Glucose Sensing: Enhancing Comfort, Breathability, and Real-Time Monitoring

3D Porous Stacked Organic Electrochemical Transistor for Wea...

引用

international conference on Micro/Nano Sensors for AI, Healthcare, and robotics (NSENS)

作者： Changjian Liu Wei Huang Haihong Guo Yujie Peng Junsheng Yu School of Optoelectronic Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798350375213

ISBN: (纸本)9798350375220

With an excessively indulgent diet and irregular routine, diabetes has emerged as a pervasive and life-threatening chronic condition. Real-time monitoring of glucose levels and stringent glycemic control are imperative for the efficient prevention and management of this ailment. Organic electrochemical transistors (OECTs) have attracted significant attention owing to its mechanical flexibility and its property to operate effectively in aqueous environments. Herein, a wearable glucose sensor is developed via ionic solutions as well as for the enzyme-based detection performance. Taking inspiration from nature, we have innovatively designed a 3D porous stacked OECT to attain passive cooling and enhanced breathability, ensuring an improved and comfortable wearing experience. The device has proven successful in detecting glucose concentrations within artificial sweat, paving the way for the development of next-generation sensors.

关键词： Performance evaluation Three-dimensional displays Medical services Robot sensing systems Real-time systems Glucose Transistors

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Wireless and Voice-controlled Automated 2-Wheel Drive Forklift for Enhanced Industrial Warehouse Operations

Wireless and Voice-Controlled Automated 2-Wheel Drive Forkli...

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Emerging Trends in Electrical, control, and Telecommunication engineering (ETECTE), international conference on

作者： Misbah Mehrab Muhammad Sohaib Muhammad Yasir Jamal Muhammad Shahid Aashir Waleed Muhammad Zia Ur Rahman Electrical Engineering Department UET Lahore (Faisalabad Campus) Faisalabad Pakistan MCT Department UET Lahore (Faisalabad Campus) Faisalabad Pakistan

ISBN: (数字)9798331504861

ISBN: (纸本)9798331504878

The automation technology is expected to become integrated into two-wheel drive forklifts, which is one of the fascinating growths in the rapidly growing forklift automation field. Forklift automation technologies have enhanced the management of material handling and warehouse operations in modern societies. Research has indicated that it enhances efficiency, security and productivity of a facility where it is applied. With it the industrial sector could be revolutionized by the reduction of labor costs, the minimization of the risks of accidents and the optimization of the utilization of space. robotics, automation, IoT, and artificial intelligence will all be utilized for the manufacture of fully automated two-wheel drive forklifts. This technology enables forklifts to lift and transport pallets, load and unload cargo or transport goods within a given area. Forklifts designed with automation technologies interlinked and running do run safer and with less manpower input. To make operations using the forklift easy to perform, research efforts will focus on enhancing the use of advanced wireless communication technologies, Mobile Computing, and Speech Recognition. One of the primary controls that helps the customers to drive the forklift using their smart devices by sending instructions is through the application developed for the purpose. It is hands-free as speech recognition capability is also provided. Future expansions of voice and mobile controlled industrial automation systems are enabled by this program.

关键词： Productivity Wireless sensor networks automation Service robots Speech recognition Communication system security Security Artificial intelligence Usability Smart devices

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State-of-the-art Research in Perception and control of Lower Limb Exoskeletons: A Systematic Review

State-of-the-art Research in Perception and Control of Lower...

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Service robotics (ICoSR), international conference on

作者： Xiaofeng Luo Yang Ma Zhibin Cai Tianqi Zhou Xiaoyu Liu Yi Long Faculty of Robot Science and Engineering Northeastern University Shenyang China Weapon Equipment Research Institute China Ordnance Industries Group Beijing China School of Mechanical Engineering and Automation Northeastern University Shenyang China Foshan Graduate School of Innovation Northeastern University Foshan China

ISBN: (数字)9798350367119

ISBN: (纸本)9798350367126

The lower limb exoskeleton is an intelligent robot worn by the human body and moves in coordination with the human limbs. It can enhance the human body's weight-bearing capacity, maneuverability and operation capabilities. Perception and control, as the brain of the exoskeleton robot, directly determine its collaborative performance and auxiliary effect with the main body. However, the current lower limb exoskeleton has not been widely adopted. One of the reasons is that the ‘brain’ of the exoskeleton robot is not intelligent enough. Therefore, this article reviewed relevant literature on lower limb exoskeleton sensing and control technology in the past five years, and studied the impact of different sensing methods and control strategies on exoskeleton performance. In addition, this article discusses the current challenges of lower limb exoskeletons and provides some innovative insights into future research directions to promote the further development of lower limb exoskeleton technology.

关键词： Mechanical sensors Limbs Robot kinematics Exoskeletons Collaboration Robot sensing systems Sensor systems Pattern recognition Complexity theory Biosensors

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