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检索条件"机构=Mechatronics Engineering and Automation College"

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Rigid-Flexible Coupled Soft Gripper with Treble Modular Fingers 7th

Rigid-Flexible Coupled Soft Gripper with Treble Modular Fing...

引用

7th International Conference on Cognitive Systems and Information Processing, ICCSIP 2022

作者： Tang, Shijie Huang, Haiming Chai, Wenqing Wu, Di’en Lu, Qinghua School of Mechatronics Engineering and Automation Foshan University Foshan528000 China College of Electronics and Information Engineering Shenzhen University Shenzhen518060 China

ISBN: (纸本)9789819906161

Soft gripper is used in various fields for grasping, handling and manipulating objects. However, soft pneumatic gripper, which is one of the most widely studied grippers in robotics, has limitations in handling different objects and cannot qualify complicated operation tasks with inherent structures and entirely composed of soft materials. Therefore, we present a rigid-flexible coupled soft gripper with treble modular fingers, which has movable frames, air chamber actuator modules and membrane-type sensing module. The rigid frames provide rigidity to allow the gripper generating a large grasping. The actuator modules can be inflated and vacuumed, thereby enabling gripper to execute different grasping operation. The sensing module, inflating a preset pressure, is able to sense grasping force. Furthermore, the work range of gripper is adjustable, changing by contraction and elongation motion of each finger. The gripper transforms from original state to contraction state by vacuuming actuator modules, and from original state to elongation state by inflating actuator modules. Through a multi-channel pneumatic control system with positive and positive-negative pressure output, the gripper achieves flexible and stable grasping for a variety of objects, such as cherry tomato (15 g), apple (204 g), banana (420 g), etc. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Grippers

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Collaborative Coverage Strategy for Multiple UAVs Considering Coverage Utility 8

Collaborative Coverage Strategy for Multiple UAVs Considerin...

引用

8th IEEE International Conference on Advanced Robotics and mechatronics, ICARM 2023

作者： Wang, Jiali Pi, Yangjun Xiao, Dengyu Xu, Lang Yi, Jin Wang, Gang Pu, Huayan Luo, Jun College of Mechanical and Vehicle Engineering Chongqing University Chongqing400044 China School of Mechatronics Engineering and Automation Shanghai University Shanghai200444 China

ISBN: (纸本)9798350300178

To complete the monitoring and searching task of large amphibious areas, multiple Unmanned Amphibious Vehicles (UAVs) have been introduced to solve the coverage problem of such areas. However, few studies were conducted on the coverage problem in amphibious environments, which is particularly challenging and urgent. In this case, we propose a collaborative coverage strategy to achieve amphibious regional coverage. Our approach is based on the following parts. Firstly, a centralized area allocation strategy is used to allocate subregion coverage tasks to each agent. Secondly, a distributed path planning algorithm is used to plan the coverage of each UAV in the amphibious environment to minimize the energy loss of the UAVs. This strategy incorporates the importance of the region and the ability of the agent, which shows great adaptability to the amphibious environment. Finally, the proposed strategy is compared with several previous popular methods in the simulations to verify its effective performance. © 2023 IEEE.

关键词： Energy dissipation

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Multi-Class Machine Learning Based Approach for SleepDisorder Identification Using EEG Signals 7

Multi-Class Machine Learning Based Approach for SleepDisorde...

引用

7th IET Smart Cities Symposium, SCS 2023

作者： Murugesan, Rajalakshmi Chandran, Karthik Dutta, P.K. Department of Mechatronics Thiagarajar College of Engineering Tamilnadu Madurai India Department of Robotics & Automation Jyothi Engineering College Kerala India Department of Electronics and Communication School of Engineering and Technology Amity University Kolkata India

ISBN: (纸本)9781839539831

Accurately identifying sleep stages is crucial for the analysis and management of sleep disorders. Electroencephalogram (EEG) signals have shown promise in sleep stage identification. This research presents a novel method for classifying different sleep stages using EEG data based on a multi-class support vector machine (SVM) approach. The proposed method involves preprocessing the EEG signals to remove noise and artifacts, followed by feature extraction using wavelet transform and statistical methods. A multi-class SVM classifier is then trained to identify four sleep stages: waking, non-rapid eye movement (NREM) stage 1, non-rapid eye movement (NREM) stage 2, and rapid eye movement (REM) stage. The method is evaluated on a dataset comprising EEG signals collected from 20 healthy individuals during a full-night sleep study. The results demonstrate that the proposed technique outperforms existing EEG-based approaches, achieving anaverage classification accuracy of 86.2 for sleep stage identification. The suggested method has potential applications in clinical settings for sleep disorder evaluation and management. Additionally, it can be extended to other applications requiring the identification of various classes from EEG data. © The Institution of engineering & Technology 2023.

关键词： Support vector machines

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Wind Power Prediction Based on the Stacking Model of XGBoost and Random Forest 11

Wind Power Prediction Based on the Stacking Model of XGBoost...

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11th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2022

作者： Liu, Wangjie Jia, Li Shanghai University Shanghai Key Laboratory of Power Station Automation Technology Department of Automation College of Mechatronics Engineering and Automation Shanghai200444 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

Due to the uncontrollability of wind energy, the conversion efficiency of wind is low. By improving the prediction accuracy of wind power, the conversion efficiency of wind energy can be greatly improved. For the purpose of solving the problems of overfitting of most wind power prediction models, the over-dependence of wind speed and the ignorance of other important features, this paper proposes a stacking method to integrate two models: XGBoost and Random Forest. Stacking of these two models can solve the above problems and greatly improve wind power prediction accuracy. The dataset from Kaggle verifies that the stacking model can extract the useful information contained in the data effeciently and has better accuracy than a lot of mainstream models. The evaluation metrics Mean Squared Error(MSE) and R2 of the stacking model are reduced by about 10% compared with the mainstream models. © 2022 IEEE.

关键词： Wind power

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Prediction of Photovoltaic Power Generation Based on D-vine Copula Model in Typical Climates 11

Prediction of Photovoltaic Power Generation Based on D-vine ...

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11th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2022

作者： Zhang, Ruiyin Jia, Li Zhou, Yang Shanghai University Shanghai Key Laboratory of Power Station Automation Technology Department of Automation College of Mechatronics Engineering and Automation Shanghai200444 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

Multi-dimensional climate factors like irradiation and humidity will lead to strong randomness of photovoltaic power generation, and it is difficult to consider all climate factors in traditional photovoltaic power generation point forecasting. Vine copula can accurately and flexibly describe the dependencies between multi-dimensional variables, establish conditional distribution expressions between photovoltaic power generation and multi-dimensional climate factors, and improve prediction accuracy. This paper proposes a D-vine copula model under typical climatic conditions. The model uses fuzzy C-means (FCM) to complete typical climate clustering, and then proposes a D-vine copula model to achieve point predictions and probability interval predictions. The results of the example show that the model has a good performance in point predictions and provide corresponding probability interval predictions, which prove the accuracy and applicability of the model. © 2022 IEEE.

关键词： Forecasting

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Tire Defect Detection Based on Improved DeepLabv3+

Tire Defect Detection Based on Improved DeepLabv3+

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第42届中国控制会议

作者： Xiaoyu Li Chen Peng Department of Automation College of Mechatronics Engineering and Automation Shanghai University

Tire defect detection is an essential step to control product quality, and accurate segmentation is the key to product grading. However, due to the fact that the internal defects of tires need to be judged manually through X-ray imaging, as well as the complex background and various types of defects, the grading of defects is marked differently, and the accuracy is affected by subjective factors. An improved algorithm based on DeepLabv3+ is proposed in this paper to solve the above problems. Firstly,the high-level semantic and low-level position features of image is integrate by encoder-decoder structure, which can face any input size. Secondly, atrous spatial pyramid pooling module and lightweight mobilnetv2 backbone can be used to accurately segment defects of different shapes and sizes, and reduce edge calculation pressure. The experimental results show that the improved deeplabv3+ can detect different defects, while the accuracy performance of model is improved to 81.42% MIoU.

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Machine Vision based automated 3-DOF Articulated Robot for fruit defect Identification and Segregation 14

Machine Vision based automated 3-DOF Articulated Robot for f...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Ramkumar, S. Venusamy, Kanagaraj Eswaran, A. Jeevitha, N. Ramyapriya, G. Kannadhasan, S. Rajalakshmi Engineering College Department of Robotics and Automation Thandalam Chennai India Rajalakshmi Engineering College Department of Mechatronics Engineering thandalam Chennai India Roever Engineering College Department of Electrical and Electronics Engineering Perambalur India Study World College of Engineering Department of Electronics and Communication Engineering Coimbatore Chennai India

ISBN: (纸本)9798350335095

The automation scenario in the current industrial as well as domestic applications has seen an exponential growth over the decade. Robot plays an important role in industrial automation but in some cases, it needs some extent of human intervention in quality inspection. This paper focuses on solving problems related to defect identification and segregation of fruits using 3-DOF articulated robot configuration with the integration of machine vision system and deep learning algorithms. To perceive the features of object, A USB camera is utilized. The machine vision algorithm will next use a variety of methods for processing digital images to extract the relevant data and decide whether to continue processing the product, redirect it to a different stage of production, or just throw it away. In recent days, the advancement in deep learning leads to the phenomenal growth in computer vision. There are many state-of-the-art object detection algorithms available in deep learning technology and we are using Inception-V3 algorithm that can be used for the machine vision operation in our solution. Based on the results from the algorithm, segregation operation is carried out successfully. © 2023 IEEE.

关键词： Fruits

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Research on Control Strategy of PMSM for Electric Vehicles Based on Nonlinear Model 5

Research on Control Strategy of PMSM for Electric Vehicles B...

引用

5th IEEE Advanced Information Management, Communicates, Electronic and automation Control Conference, IMCEC 2022

作者： Li, Xuerong Song, Wenxiang College of Mechanical and Electrical Engineering Donghai Vocational and Technical College Shanghai China School of Mechatronics Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9781665479677

In actual operation, the performance of PMSM used in electric vehicle and its drive system is greatly affected by magnetic circuit saturation and cross-saturation, and the traditional linear model can no longer meet the requirements of high-precision and high-performance control systems. The nonlinear model of vehicle permanent magnet synchronous motor based on finite element is established, the influence of motor parameters on the control algorithm is analyzed, the current loop decoupling control based on the table lookup method is proposed, The simulation results show that the motor control system considering the nonlinear model can adapt to different operating conditions and output the maximum torque, and has good speed dynamics and anti load disturbance performance. © 2022 IEEE.

关键词： Magnetic circuits

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Fault Coding Inspired Agile Diagnosis for Traction Motor System with Improved GWO-SVM Model 6

Fault Coding Inspired Agile Diagnosis for Traction Motor Sys...

引用

6th IEEE International Electrical and Energy Conference, CIEEC 2023

作者： Zhang, Kunpeng Li, Hao Yu, Yinquan Jiang, Bin An, Chunlan School of Electrical and Automation Engineering East China Jiaotong University Nanchang330013 China School of Mechatronics and Vehicle Engineering East China Jiaotong University Nanchang330013 China College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China

ISBN: (纸本)9798350346671

This paper analyzes the incipient fault detection and isolation issues of high speed train (HST) traction motor. The multiple fault feature in such a motor is obscure with few fault samples, and the fault separation vary in nonlinear pattern. This paper presents an agile diagnosis combining electromagnetic torque energy entropy coding and support vector machine(SVM) model optimized by improved grey wolf optimizer(IGWO) algorithm. The perform of the proposed work is validated through experimentation on a fault testing verification platform for HST traction motor system. © 2023 IEEE.

关键词： Railroad cars

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Design of Isolated Bi-Directional DC-DC Converter for Aerospace 2

Design of Isolated Bi-Directional DC-DC Converter for Aerosp...

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2nd IEEE International Power Electronics and Application Symposium, PEAS 2023

作者： Zeng, Xiaohui Chen, Chunzhi Yang, Lei Chen, Wei Chen, Qingbin Huang, Yuping College of Electrical Engineering and Automation Fuzhou University Fuzhou China Beijing Institute of Precision Mechatronics and Controls Laboratory of Aerospace Servo Actuation and Transmission Beijing China

ISBN: (纸本)9798350313765

The servo power supply is the key power supply equipment of aerospace electromechanical servo systems, and its volume, specific energy, and instantaneous output power directly determine the overall performance of the system. This paper proposes a two-stage topology that can satisfy the capacitive voltage with a wide input range based on the technical specification requirements of an isolated bi-directional DC-DC converter for aerospace applications. Firstly, the operation principle of the topology is analyzed, and the volume and weight of the converter can be reduced with magnetic integration technology. Moreover, the whole control scheme is introduced and the fast charge and discharge control strategy of the capacitor is analyzed in detail. Finally, a prototype with a peak output power of 7.6 kW was developed, the overall weight was 2.24 kg (with the case), and the volume was 286.4 146.4 63.5 mm3. The experimental results show that the rising and falling time of the output current is less than 1.5 ms, and the stabilized current precision is less than 10%. At the same time, the prototype can achieve 50 times continuous charge and discharge, which effectively meets the requirements of complex power conditions of the aerospace electromechanical servo system. © 2023 IEEE.

关键词： control strategy isolated bidirectional DC-DC converter magnetic integration servo power supply

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