Proceedings of the 2022 3rd International Conference on Artificial Intelligence in Electronics Engineering最新文献_第2页

Data Reconstruction and Optimal Design of Auto Rearview Mirror Based on RE 基于RE的汽车后视镜数据重构与优化设计

Proceedings of the 2022 3rd International Conference on Artificial Intelligence in Electronics Engineering Pub Date : 2022-01-11 DOI: 10.1145/3512826.3512835

Qian Zhou, Mananga Moulongo Vareine Daricka, Yong-You Ma, M. Huang

引用次数: 0

Design and Implementation of a Pump and Valve Integrated System Inspired by Bivalve 受Bivalve启发的泵阀集成系统的设计与实现

Proceedings of the 2022 3rd International Conference on Artificial Intelligence in Electronics Engineering Pub Date : 2022-01-11 DOI: 10.1145/3512826.3512844

Lei Cui, Haomin Wu, Bintang Yang

{"title":"Design and Implementation of a Pump and Valve Integrated System Inspired by Bivalve","authors":"Lei Cui, Haomin Wu, Bintang Yang","doi":"10.1145/3512826.3512844","DOIUrl":"https://doi.org/10.1145/3512826.3512844","url":null,"abstract":"Abstract: Pumps and valves are generally indispensable parts of the hydraulic system and a component that integrates the functions of pumps and valves plays an important role in the integration and lightweight development of hydraulic systems. In this paper, a magnetically actuated pump and valve integrated system is proposed. Inspired by bivalve, the driving structure of the pump and valve integrated system is designed for jet propulsion. This design intends to actively control flow of a pipe by switching the open and close state of the system. Different from some biomimetic bivalves driven by rotating motors, the proposed integrated pump and valve system is characterized with direct drive by shell-shaped magnetic actuators. Based on the equivalent magnetic charge modelling method, a theoretical model of the magnetic torque of the permanent magnet is established for the analysis and driving mechanism design. The numerical calculation results of the theoretical model are consistent with the finite element simulation results. Additionally, the magnetic torque of different arrangements of permanent magnets are compared through electromagnetic simulation. Motion analysis is carried out by discretizing time. Finally, experiment for flow control is conducted to verify the effectiveness of the proposed pump and valve system.","PeriodicalId":270295,"journal":{"name":"Proceedings of the 2022 3rd International Conference on Artificial Intelligence in Electronics Engineering","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130240107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Control Model for Metro Train Movements: The Piecewise Nonlinear Time-domain Model 地铁列车运动控制模型:分段非线性时域模型

Proceedings of the 2022 3rd International Conference on Artificial Intelligence in Electronics Engineering Pub Date : 2022-01-11 DOI: 10.1145/3512826.3512849

Jinlin Liao, Jiajun Lin, Guilian Wu, Hao Chen, Shiyuan Ni, Tingting Lin, Lu Tang

{"title":"A Control Model for Metro Train Movements: The Piecewise Nonlinear Time-domain Model","authors":"Jinlin Liao, Jiajun Lin, Guilian Wu, Hao Chen, Shiyuan Ni, Tingting Lin, Lu Tang","doi":"10.1145/3512826.3512849","DOIUrl":"https://doi.org/10.1145/3512826.3512849","url":null,"abstract":"Metros have been becoming a mainstream means of transportation in China. The research of various aspects of metro transportation has developed rapidly. However, how to construct a practical control model has always been a research hotspot. In this paper, we propose a piecewise nonlinear time-domain model (PNTM). This model describes a piecewise control process of the train driving in each section. The most notable feature of PNTM is that according to the electromagnetic principle of the motor, the acceleration process of the train is divided into three phases: constant torque, constant power, and natural characteristic. In each operation phase, speed, position, and instantaneous power are chosen to describe driving states of the train. Moreover, functional expressions instead of differential equation sets are used to formulate the driving states. Finally, the model is validated by numerical examples for comparison with the linear model and the measured data in real cases in Shanghai Metro Line 1 (SML1). The experimental results indicate that the correlation coefficients between PNTM and the measured data in terms of speed and power are 0.9874 and 0.9999, respectively, which are much higher than the 0.9251 and 0.9996 of the linear model.","PeriodicalId":270295,"journal":{"name":"Proceedings of the 2022 3rd International Conference on Artificial Intelligence in Electronics Engineering","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121381099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of Verification Device for Interval Velocity Measurement System based on GNSS 基于GNSS的区间测速系统验证装置的研制

Proceedings of the 2022 3rd International Conference on Artificial Intelligence in Electronics Engineering Pub Date : 2022-01-11 DOI: 10.1145/3512826.3512839

Hon-ting. Cheng, Jianqiong Huang, Zhongjun Cheng

引用次数: 0

Design and Experiment of Secondary Throwing Device of Cotton Straw Crushing and Returning Machine Using Fluent 棉花秸秆破碎回收机二次投掷装置的设计与试验

Proceedings of the 2022 3rd International Conference on Artificial Intelligence in Electronics Engineering Pub Date : 2022-01-11 DOI: 10.1145/3512826.3512838

Yongxin Jiang, Shunlin Hou, Li Zhang, Xuan Liu, Jiaxi Zhang, Yichao Wang

{"title":"Design and Experiment of Secondary Throwing Device of Cotton Straw Crushing and Returning Machine Using Fluent","authors":"Yongxin Jiang, Shunlin Hou, Li Zhang, Xuan Liu, Jiaxi Zhang, Yichao Wang","doi":"10.1145/3512826.3512838","DOIUrl":"https://doi.org/10.1145/3512826.3512838","url":null,"abstract":"Abstract: Regarding the agronomic requirements of the combined operation machine of cotton straw crushing and returning to field and residual film recovery, the existing straw crushing and returning machines cannot are still insufficient. In this work, a cotton straw crushing and returning device with the function of secondary backward throwing was designed, striving to realize the crushing and backward uniform throwing of cotton straw and lay the foundation for the residual film recovery operation. The curved surface housing comprises a logarithmic spiral curved front housing, a left side plate, a right side plate, and a back baffle. Fluent simulation showed that the logarithmic spiral shell has better fluidity than the broken line shell, which is more conducive to the flow of cotton straw in the shell. The straw crushing and returning device with the function of secondary backward throwing mainly consists of curved shell, transmission device, crushing device and secondary throwing device, and the secondary throwing shaft is equipped with spiral blades to recycle the straw. One time crushing and backward conveying can improve the backward throwing performance of cotton straw. The field experiment demonstrated that under the working conditions of knife roller rotation speed of 2490.00r/min, forward speed of 4.90km/h and ground clearance of 76.0mm, the cotton stalk crushing rate and cotton stalk dropping rate of the second throwing cotton straw chopping and returning machine were 98.78% and 2.88%, respectively. The relative error between the experimental value and the predicted value was less than 5%. The regression model was reliable, and the machine could well complete the operation of cotton straw chopping and returning.","PeriodicalId":270295,"journal":{"name":"Proceedings of the 2022 3rd International Conference on Artificial Intelligence in Electronics Engineering","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114456032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis on the Realization of Autonomous Driving Technologyand Its Development Prospect 自动驾驶技术的实现及其发展前景分析

Proceedings of the 2022 3rd International Conference on Artificial Intelligence in Electronics Engineering Pub Date : 2022-01-11 DOI: 10.1145/3512826.3512830

Hongxing Li

引用次数: 0

An Algorithmic Theory for Conscious Learning 有意识学习的算法理论

Proceedings of the 2022 3rd International Conference on Artificial Intelligence in Electronics Engineering Pub Date : 2022-01-11 DOI: 10.1145/3512826.3512827

J. Weng

{"title":"An Algorithmic Theory for Conscious Learning","authors":"J. Weng","doi":"10.1145/3512826.3512827","DOIUrl":"https://doi.org/10.1145/3512826.3512827","url":null,"abstract":"The new conscious learning mode here is end-to-end (3D-to-2D-to-3D) and free from annotations of 2D images and 2D motor images, such as a bounding box for a patch to be attended to. The algorithm directly takes that of the Developmental Networks that has been previously published extensively with rich experimental results. This paper fills the huge gap between 3D world, to 2D sensory images and 2D motor images, back to 3D world so the conscious learning is end-to-end without a need for motor-impositions. This new conscious learning methodology is a major departure from traditional AI—handcrafting symbolic labels that tend to be brittle (e.g., for driverless cars) and then “spoon-feeding” pre-collected “big data”. The analysis here establishes that autonomous imitations as presented are a general mechanism in learning universal Turing machines. Autonomous imitations drastically reduce the teaching complexity compared to pre-collected “big data”, especially because no annotations of training data are needed. This learning mode is technically supported by a new kind of neural networks called Developmental Network-2 (DN-2) as an algorithmic basis, due to its incremental, non-iterative, on-the-fly learning mode along with the optimality (in the sense of maximum likelihood) in learning emergent super Turing machines from the open-ended real physical world. This work is directly related to electronics engineering because it requires large-scale on-the-fly brainoid chips in conscious learning robots.","PeriodicalId":270295,"journal":{"name":"Proceedings of the 2022 3rd International Conference on Artificial Intelligence in Electronics Engineering","volume":"220 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116833260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Design and Application of Virtual Production Command Service in Power Distribution Network Based on Artificial Intelligence 基于人工智能的配电网虚拟生产指挥服务设计与应用

Proceedings of the 2022 3rd International Conference on Artificial Intelligence in Electronics Engineering Pub Date : 2022-01-11 DOI: 10.1145/3512826.3512836

Xueqiong Wu, Lei Chen, K. Ji, Huidong Wang, Hao Qian, Lidong Ma

引用次数: 0

Research on Anomaly Detection Method of Online Monitoring Data of Dissolved Gas in Transformer Oil 变压器油中溶解气体在线监测数据异常检测方法研究

Proceedings of the 2022 3rd International Conference on Artificial Intelligence in Electronics Engineering Pub Date : 2022-01-11 DOI: 10.1145/3512826.3512840

Xiaohui Yang, Chenxi Guo, Huan Ren, Ming Dong

{"title":"Research on Anomaly Detection Method of Online Monitoring Data of Dissolved Gas in Transformer Oil","authors":"Xiaohui Yang, Chenxi Guo, Huan Ren, Ming Dong","doi":"10.1145/3512826.3512840","DOIUrl":"https://doi.org/10.1145/3512826.3512840","url":null,"abstract":"Dissolved gases in oil analysis has been a significant conventional condition detection method for condition evaluation for power transformers. But false data and wrong data do exist in DGA on-line monitoring system, which often lead to misjudgment. To handle this problem, the monitoring system often uses a threshold method based on data distribution statistics to determine the authenticity of the data. However, it is difficult to grasp the rules of the data distribution in advance, resulting in the problem of generally low detection rate of abnormal data. In this paper, according to the time series characteristics of on-line monitoring data of DGA, an abnormal data detection method based on condensed hierarchical clustering is proposed. First, the sliding time window is used to preprocess a variety of oil gas monitoring data to obtain a time series set of monitoring data, and comprehensively apply statistical indicators to classify them and establish Typical time series map; on this basis, the agglomerated hierarchical clustering model is used to perform similarity clustering on the distance between different characteristic data points and the typical abnormal map to determine the abnormal type of the monitoring data. The verification of the application of actual monitoring data shows that this method can detect data anomalies in the online monitoring data stream and determine its type in real time.","PeriodicalId":270295,"journal":{"name":"Proceedings of the 2022 3rd International Conference on Artificial Intelligence in Electronics Engineering","volume":"607 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132857367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Indoor Scene Classification Algorithm Based on an Object Vector for Robot Applications 基于物体向量的机器人室内场景分类算法

Proceedings of the 2022 3rd International Conference on Artificial Intelligence in Electronics Engineering Pub Date : 2022-01-11 DOI: 10.1145/3512826.3512846

Ximing Fan, Bo Zhu, Xiang Gao, Bin Wang, Cong Wang, Guozheng Xu

{"title":"Indoor Scene Classification Algorithm Based on an Object Vector for Robot Applications","authors":"Ximing Fan, Bo Zhu, Xiang Gao, Bin Wang, Cong Wang, Guozheng Xu","doi":"10.1145/3512826.3512846","DOIUrl":"https://doi.org/10.1145/3512826.3512846","url":null,"abstract":"At present, many indoor scene classification algorithms are based on abstract feature descriptions and lack semantic interpretation for classification results. For robot applications, these classification methods fail to reuse prior knowledge of environmental objects, resulting in a waste of computing resources, and are not conducive to interaction. In addition, a large number of existing methods have not been verified for robot applications because training and test are performed on the same dataset. Here, intermediate semantic structure, called object vector, is proposed to describe the scene. The recognition confidence, category, and quantity of typical objects, which are related to scene concepts, can be captured by this structure. Based on the object vector, the semantic prototype models of scene categories are obtained using the prototype learning method, and the corresponding prototype confidence vector is generated for scene prediction. The object vector and prototype confidence vector are concatenated to form a complete descriptor. Applying sparse random forest learning, scene conceptual models are formed and used in real scene classification. In the experiment, the training and test sets were selected from sets with different styles. The average accuracy on the MIT Indoor 67, VPC, and Tsotsos_home datasets is higher than that of fine-tuned VGG. In particular, the accuracy on the VPC dataset improved by more than 5%. Moreover, the algorithm performance is evaluated on an actual robot platform.","PeriodicalId":270295,"journal":{"name":"Proceedings of the 2022 3rd International Conference on Artificial Intelligence in Electronics Engineering","volume":"13 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131540955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2