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检索条件"任意字段=4th International Conference on Robotics and Control Engineering, RobCE 2024"

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Research on detection and measurement method of automotive connector terminal based on improved YOLOv7

Research on detection and measurement method of automotive c...

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Electronic Technology, Communication and Information (ICETCI), IEEE international conference on

作者： Guangze Bai Jun Gu Yan Xing Guiyan Xue Xu Guo Wanze Song Congbo Luo Yu Gu Lai Wei Xue Liu Automotive Institute Changchun Vocational and Technical College Changchun China Changchun Jielin Intelligent Technology Co. Ltd Changchun China Changchun City Construction Engineering School Changchun China Changchun Automotive Technical College Changchun China Xinhe Measurement and Control Technology (Changchun) Co. Ltd Changchun China

ISBN: (数字)9798350361643

ISBN: (纸本)9798350361650

As a vital part of the automotive electrical system, the connector pins support the transmission of electrical signals, data and power to ensure the correct connection and collaboration between the various components of the vehicle, and their quality and reliability are crucial to the performance, safety and reliability of the vehicle. therefore, it is of great significance to study an automatic detection method for the connection pins of automobile connectors. the traditional connector needle detection mainly relies on manual method, due to the relatively dense distribution of the connector needle and the human eye is easy to fatigue and other factors. this method has the problems of high detection error rate, low accuracy and low efficiency. therefore, this paper proposes an automatic detection method for connecting pins of automotive connector based on improved Yolov7 target detection. this method adds attention mechanism on the basis of Yolov7 target detection, which can be more suitable for small target detection. Finally, after the improvement, the results of the YOLOV7 target detection model training, mAP@0.5, reached 94.87%, and map@0.5:0.95, reached 75.28%. compared with the results before the improvement, mAP@0.5, 69.7%, map@0.5:0.95, 51.2%. Increases of 25.17% and 24.08%, respectively. It is proved that the improved model is more suitable for the detection of the connection pin of the auto-mobile connector. the detection rate of the final car connector pin is as follows: After the car connector pin is detected, the pin spacing is measured by the method of image processing in this paper, and the measurement accuracy meets the practical requirements. At the same time, the research content of this paper has laid the groundwork for other electrical and signal tests of automobile connector in the future.

关键词： Connectors Training Accuracy Object detection Needles Pins Safety

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Optimizing Charge Transport and Recombination in CH3NH3PbI3 Perovskite Solar Cells through Donor Density and thickness control

Optimizing Charge Transport and Recombination in CH3NH3PbI3 ...

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Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET), international conference on

作者： Aniket Verma Nikhil Shrivastav Jaya Madan VLSI Centre of Excellence Chitkara University Institute of Engineering and Technology Punjab India

ISBN: (数字)9798331528614

ISBN: (纸本)9798331528621

this work uses a CH-PSC structure to investigate the perovskite solar cells, therefore complementing the Climate Action and Affordable and Clean Energy. By means of SCAPS-1D simulations, the paper investigates how variation in donor density and active layer thickness affect important photovoltaic metrics like V OC , J SC , FF, and PCE. the results show the need of improving these parameters to increase solar cell efficiency, therefore aiding the development of reasonably priced and environmentally friendly energy sources. the paper shows that an ideal donor density reduces recombination and increases charge separation, hence improving V OC , J SC , and FF all of which are quite vital for high PCE. Concurrently, the thickness of the CH 3 NH 3 PbI 3 layer has to be balanced to maximize light absorption without causing too strong recombination losses. Achieving the ideal balance between these elements will help to significantly increase the quantity of renewable energy in the global energy mix and hence care means of developing high-performance perovskite solar cells. Moreover, this study helps to define the direction of forthcoming solar technical developments. By means of varied perovskite compositions and alternate materials for electron and hole transport layers (ETL & HTL), the researchers hope to provide means to enhance the stability, scalability, and efficiency of perovskite solar cells. these kinds of developments promote technology to enable the development of sustainable energy systems, lowers of greenhouse gas emissions, and so limits of influence of climate change. Moreover in line with the aim of increasing the availability of clean energy solutions so enabling a sustainable and resilient future for all is the integration of these advances into scalable, low-cost manufacturing techniques.

关键词： Photovoltaic systems Performance evaluation Spontaneous emission Absorption Photovoltaic cells Scalability Stability criteria Metals Perovskites Power conversion

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Nonlinear control strategy of hybrid energy storage system based on feedback linearization 4

Nonlinear control strategy of hybrid energy storage system b...

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4th CAA international conference on Vehicular control and Intelligence, CVCI 2020

作者： Lu, Zhangyu Zhang, Xizheng Wang, Yaonan College of Electrical and Information Engineering Hunan Institute of Engineering Xiangtan China School of Robotics Hunan University Changsha China

ISBN: (纸本)9781728184968

In view of the nonlinear characteristics of the hybrid energy storage system (HESS), a nonlinear control strategy based on feedback linearization theory is proposed. the control objectives of the strategy are battery/super capacitor current and DC bus voltage. Firstly, by analyzing the state equation of the circuit, the affine nonlinear model of the circuit is established. then, the input-output feedback linearization and sliding mode surface are designed to realize the current tracking control of the battery and super capacitor. Finally, the classic voltage closed-loop control is used to realize the bus voltage stability. the simulation model is established on Simulink, and the simulation results show that the proposed control strategy is effective. © 2020 IEEE.

关键词： Feedback linearization

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Research on intelligent identification method of power grid wiring diagram based on deep convolution neural network

Research on intelligent identification method of power grid ...

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Communication Technology and Information Technology (ICCTIT), international conference on

作者： Bing Zhou Chong Ruan Ruiqing Shan Dan Wang Zhongshan Qu Guosong Wu State Grid Henan Electric Power Company Zhengzhou Henan China HAEPC Electric Power Research Institute Zhengzhou Henan China Beijing Kedong Power Control System Company with limited liability Beijing China

ISBN: (数字)9798331528973

ISBN: (纸本)9798331528980

the continuous evolution of smart grid technology has promoted the intelligent level of power dispatching automation systems to meet more stringent requirements and challenges. In the context of the growing demand for unified grid standards in power systems, there is an increasing importance in the collaborative integration and sharing of models, data, and graphs. this paper proposes a set of intelligent identification schemes for power grid graphics, combining convolutional neural network and OCR technology with CAD and PDF graphics files commonly used in power grids. the proposed solution is capable of accurately identifying information such as standard components, topology associations, and device labels in power grid graphs, and automatically converting this information into standard CIM/G file format. Furthermore, by introducing natural language processing technology, this paper effectively establishes a close relationship between graphic elements in CIM/G files and power grid model data, and achieves accurate recognition of graphic elements in power grid wiring diagrams, accurate extraction of character information, and comprehensive analysis of topology structure. the implementation of these technological innovations has established a solid foundation for advanced functions, such as automated management and rapid response to failures of the smart grid. the model association method employs image recognition to construct a power grid pattern recognition platform that assists dispatch centre management. the platform has been shown to refine graphics, integrate AI efficiency, provide a user-friendly interface, reduce labour requirements, ensure information accuracy and stabilise the operation of smart grids. through the specific application in the engineering field, it is verified that this method improves the efficiency of model correlation, reduces the work of manual maintenance, and improves maintenance efficiency.

关键词： Graphics Wiring Solid modeling Accuracy Transformers Smart grids Topology Character recognition Standards Power generation

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Enhancing Data Center Efficiency with Docker & Kubernetes: Industry 4.0 Container-as-a-Service (CAAS) for IoE Cloud Technology

Enhancing Data Center Efficiency with Docker & Kubernetes: I...

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Technological Advancements in Computational Sciences (ICTACS), international conference on

作者： R.J.S. Jeba Kumar J. Roopa Jaya Singh K. Martin Sagayam Ravinder Kumar Pronaya Bhattacharya Gaurav Aggarwal Dept. of CS St. Peter's Institute of Higher Education and Research Chennai India Dept. of ECE Karunya Institute of Technology and Sciences Coimbatore India Dept. of Information Technology Manipal University Jaipur Jaipur Rajasthan India Dept. of CSE Amity Sch. of Engg. and Tech. Amity University Kolkata West Bengal India Dept. of IT and Engineering Amity University in Tashkent Tashkent Uzbekistan

ISBN: (数字)9798350387490

ISBN: (纸本)9798350387506

With the dawn of modern digital civilization i.e., Industry 4.0, a need for bi-directional intelligent communicable devices, is welcomed to the maximum extent by commons. this demand of intelligent bi-directional communication, paved the way to transform a fundamental communication to advanced short range confined network communication, then it grown gradually to the level of full-fledged inter-network connection across boundaries. this survey paper deals with comparative study of modern futuristic, Internet of Everything (IoE) technology over prevalent Internet of things (IoT) and basic era of Machine to Machine (M2M) Communication there by enhancing the data-center efficiency using AWS Cloud services for future IoE era. Much advancement in IoE will comprise all existing solution of IoT in a much smarter and secured way. the implementation of data-center with mirroring cloud technology to increase data availability efficiency. Dockers enables memory management among the containers. Ubuntu platform has been used to run docker and Kubernetes. Comparative study is done to portray every aspect of advancement in evolution, application, flipsides of the existing IoT and M2M technology and the same is compared with the new futuristic IoE technology with feasibility of fail-safe data-center schema.

关键词： Surveys Cloud computing Data centers Machine-to-machine communications Protocols Memory management Bidirectional control Transforms Fourth Industrial Revolution Internet of things

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Non-Destructive Compression Technology for Tool Wear Images in Unmanned Factories

Non-Destructive Compression Technology for Tool Wear Images ...

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Digital Society and Intelligent Systems (DSInS), international conference on

作者： Huiying Yin Zhichao You Hengkai Gao Hongli Gao School of Mechanical Engineering Southwest Jiaotong University Chengdu China School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu China Leading Optics (Shanghai) Co. Shanghai China State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798331528829

ISBN: (纸本)9798331528836

Addressing the real-time monitoring requirements for the wear status of micro-milling tools in the precision manufacturing industry, this paper proposes a lossless compression algorithm based on dual dictionary learning, specifically designed for efficiently compressing images of milling tool wear in unmanned factories. the core of this algorithm lies in utilizing image super-resolution technology to reconstruct lowresolution wear images collected on-site into high-resolution images through an iterative process, thereby enhancing the image clarity and detail representation. the research adopts a joint learning strategy for the primary and residual dictionaries, enabling the algorithm to progressively and precisely restore high-frequency details in the image, leading to more explicit images after super-resolution processing. Subsequently, the super-resolution operator is compressed using entropy encoding technology, achieving lossless compression for the entire dataset. this improves the visual quality of the images and effectively reduces the storage space required for the dataset. Experimental results demonstrate that the method proposed in this paper achieves a higher compression ratio than traditional lossless compression techniques, with Bps indicators reaching 5.12 and 4.24 and compression times of 0.041 and 0.035 seconds, respectively, while maintaining image quality without degradation. this means that images compressed using this algorithm and uploaded to the cloud can retain their original details and clarity after decompression, providing high-quality image data for subsequent processing. Overall, this achievement offers a new and effective image-processing tool for monitoring milling tool wear in unmanned factories. Leveraging efficient lossless compression technology enables rapid upload of on-site images and cloud processing, reducing computational requirements at the edge. this is of great significance for improving production efficiency and ensuring m

关键词： Image quality Image coding Runtime Computational modeling Superresolution Process control Milling Production facilities Real-time systems Monitoring

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Real-time In-situ Defect Detection in 3D Printing of Continuous Fiber-Reinforced Composites

Real-time In-situ Defect Detection in 3D Printing of Continu...

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Digital Twins and Parallel Intelligence (DTPI), IEEE international conference on

作者： Zhijian Yue Zhen Shen Xiangyang Dong Qihang Fang Weixing Wang Xisong Dong Gang Xiong Fei-Yue Wang School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Intelligent Manufacturing Center Qingdao Academy of Intelligent Industries Qingdao China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China State Key Laboratory for Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350349252

ISBN: (纸本)9798350349269

With the development of continuous fiber-reinforced composites (CFRCs) 3D printing technology, timely, efficient and accurate detection of fiber path defects is essential for ensuring product quality and performance. However, challenges still need to be addressed in this field, such as inadequate training data coverage and the complexity of fiber path structures. these factors hinder the capability of traditional methods to accurately assess the status of printed products. therefore, developing accurate and robust fiber path defect detection techniques is crucial for CFRCs 3D printing technology. In this paper, we propose a precise detection method for fiber path defects in CFRCs 3D printing using the YOLOv7 object detection model combined with a Squeeze-and-Excitation (SE) attention mechanism. By introducing the SE attention mechanism, we enhance the perception capability of the YOLOv7 model for crucial features, thereby improving the accuracy of fiber path defect detection. the experimental results show that the YOLOv7 model, when augmented with an attention mechanism, achieves an average accuracy of 93.9% in identifying fiber path defects during the printing process. Compared to models without this attention mechanism, the results show that there is 10.7% increase, with a notably enhanced learning capacity during the training phase, which substantiates the efficacy and practicality of the proposed approach.

关键词： Training Solid modeling Accuracy Attention mechanisms Training data three-dimensional printing Real-time systems Quality assessment Optical fiber testing Defect detection

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Design and Realization of Anti-scratch System on Vehicle Bottom Based on 51 Single-chip Microcomputer 2021

Design and Realization of Anti-scratch System on Vehicle Bot...

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2021 4th international conference on Electronics and Electrical engineering Technology

作者： Chunling Wang Haoran Chen Yunfei Xia Institute of Robotics Engineering Anhui Sanlian University China

ISBN: (纸本)9781450385169

Abstract: In order to realize the non-contact scratch detection of automobiles, a vehicle bottom anti-scratch system based on 51 single-chip microcomputer is designed. this system uses AT89C52 single-chip microcomputer as the core and combines the ultrasonic transmission and reception detection circuit to construct the vehicle bottom anti-scratch system. Relying on the hardware system of scratching, the corresponding software system of ultrasonic distance measurement is designed. Finally, the Protues platform is used in combination with Keil4 to realize the co-simulation of 51 control and acquisition of ultrasonic signals. Experiments show that the ranging system has high measurement accuracy. through the design circuit of this distance measurement, it is possible to monitor the anti-scratch condition of the underside of the vehicle.

关键词： Ultrasonic ranging Simulation system Keywords:51 Single-chip Microcomputer

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Optimal design for frequency fluctuation control system with SMES unit 4

Optimal design for frequency fluctuation control system with...

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4th international conference on robotics and Automation Sciences, ICRAS 2020

作者： Tran, Xuan Khoa Chen, Yuepeng Phan, Gia Tri Huynh, Duc Hoan Wuhan University of Technology School of Automation Wuhan430070 China Quy Nhon University Faculty of Engineering and Technology Quynhon59000 Viet Nam

ISBN: (纸本)9781728198576

Nowadays, frequency control is becoming more important due to complicated changes in the size increase and structural changes in the grid. To ensure the power demand, the effectiveness and reliability of the power system must be enhanced, resulting in requirements to maintain frequency and current control of the power system has a value close to the set value. With a modern power system, load frequency control (LFC) operates with a necessary role as a stable device and aids in the exchange and improve the electrical quality of suppliers. In this paper, the author focuses on designing the Fuzzy-PI controller for superconducting magnetic energy storage (SMES) unit to control the fluctuation of frequency due to abruptness changes of load in the single-area and two-area system. In which PI controller is the main controller with Ki and Kp parameters, which are adjusted online by Fuzzy controller. the simulation results show that the overshoot, set time, oscillation amplitude of the FL-PI controller are superior to the conventional PI controller. © 2020 IEEE.

关键词： Fuzzy logic

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Corrosion fault identification model of substation grounding grid based on PSO-LS-SVM 4

Corrosion fault identification model of substation grounding...

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4th international conference on Mechanical, Electric and Industrial engineering, MEIE 2021

作者： Qin, Jun Miao, Jin Wu, Xi Wang, Zibo Shao, Shuai State Grid Wuxi Power Supply Company Wuxi Jiangsu China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

As one of the important equipment to ensure the normal operation of substation, the performance of grounding grid has been highly concerned. In recent years, researchers propose that the theory of electromagnetic induction can be used to diagnose and identify the corrosion fault of substation grounding grid. In this paper, a fault classification model based on LS-SVM optimized by PSO is proposed to identify the corrosion fault of grounding grid. Firstly, the wavelet packet transform principle is used to filter the original data, and the wavelet packet energy is used to construct the fault eigenvalue as the input of the fault classification model. Based on LS-SVM, a corrosion fault classification model is constructed, and particle swarm optimization method is used to optimize the parameters of the model, which solves the problem of traditional SVM parameter optimization. through the practical application in substation, the model proposed in this paper can identify the corrosion of grounding grid conductor without excavation and power failure, which provides an effective scheme for engineering application. © Published under licence by IOP Publishing Ltd.

关键词： Corrosion

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