2020 20th International Conference on Control, Automation and Systems (ICCAS)最新文献_第4页

Electrical characteristics analysis of 18650 lithium-ion battery pack with the earthquake vibration condition 地震振动条件下18650锂离子电池组电气特性分析

2020 20th International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2020-10-13 DOI: 10.23919/ICCAS50221.2020.9268337

Seongyun Park, Pyeongyeon Lee, Jeong-Joon Ahn, S. Park, Youngmi Kim, W. Na, Jonghoon Kim

{"title":"Electrical characteristics analysis of 18650 lithium-ion battery pack with the earthquake vibration condition","authors":"Seongyun Park, Pyeongyeon Lee, Jeong-Joon Ahn, S. Park, Youngmi Kim, W. Na, Jonghoon Kim","doi":"10.23919/ICCAS50221.2020.9268337","DOIUrl":"https://doi.org/10.23919/ICCAS50221.2020.9268337","url":null,"abstract":"Nowadays, the usage of lithium-ion batteries is an increase highly for electric vehicles (EVs), energy storage systems (ESSs), and portable electrical devices. The electrical characteristics of lithium-ion batteries are changed by discharge/charge current magnitudes, depth of discharge (DoD), environment temperature, degradation, and so on. In addition, the mechanical stress such as vibration and shock are degraded due to deformation of electrode or stress of electrolyte. The previous literatures of vibration are limited to the conditions of electric vehicle and satellites. These vibrations are tested on a single axis. However, earthquake vibration is applied to three axes simultaneously. A lot of literatures have analyzed the change of single cell's electrical characteristics with mathematical analysis method. In this paper, lithium-ion battery module which is consisted of 14 series and 20 parallel by 18650 cylindrical cells is tested to analyze the change of electrical characteristics such as cell-to-cell voltage difference, internal resistance, discharge capacity and temperature difference in module by the earthquake vibration.","PeriodicalId":6732,"journal":{"name":"2020 20th International Conference on Control, Automation and Systems (ICCAS)","volume":"140 1","pages":"360-364"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75822492","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: 1

Comparison of motor fault diagnosis performance using RNN and K-means for data with disturbance 含干扰数据的RNN与K-means电机故障诊断性能比较

2020 20th International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2020-10-13 DOI: 10.23919/ICCAS50221.2020.9268271

Dong-Jin Choi, Ji-hoon Han, Sang-Uk Park, Sun-Ki Hong

{"title":"Comparison of motor fault diagnosis performance using RNN and K-means for data with disturbance","authors":"Dong-Jin Choi, Ji-hoon Han, Sang-Uk Park, Sun-Ki Hong","doi":"10.23919/ICCAS50221.2020.9268271","DOIUrl":"https://doi.org/10.23919/ICCAS50221.2020.9268271","url":null,"abstract":"Maintenance of an industrial electric motor is very important. The most commonly used algorithm for deep learning motor diagnosis using deep learning is CNN, which is one of the representative supervised learning algorithms. However, the failure diagnosis algorithm made with the CNN algorithm is vulnerable to this data. For this reason, an algorithm that complements this has been proposed, and that is to use the RNN and K-means algorithms. The method using RNN has a cyclic neural network structure, so it can grasp the similarity of data. K-means also uses the Euclidean distance method to grasp the similarity between data and classify the data using it. Due to the characteristics of these two algorithms, even if a disturbance is an input, if the similarity of data is high, it is determined as similar data. In this paper, two algorithms were used to perform fault diagnosis and two experiments were conducted to understand the differences and characteristics of the two algorithms. As a result of experiment 1 classifying only normal failures, experiment 2 experimented by increasing the number of failures to be classified. In the case of RNN, the results of experiments 1 and 2 showed similar accuracy. However, in the case of the algorithm using K-means, the accuracy decreased as the number of classifications increased.","PeriodicalId":6732,"journal":{"name":"2020 20th International Conference on Control, Automation and Systems (ICCAS)","volume":"518 1","pages":"443-446"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82997339","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

Improving Instance Segmentation using Synthetic Data with Artificial Distractors 基于人工干扰的合成数据分割方法的改进

2020 20th International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2020-10-13 DOI: 10.23919/ICCAS50221.2020.9268390

Kanghyun Park, Hyeongkeun Lee, Hunmin Yang, Se-Yoon Oh

引用次数: 1

Object Removal and Inpainting from Image using Combined GANs 使用组合gan从图像中去除和修复物体

2020 20th International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2020-10-13 DOI: 10.23919/ICCAS50221.2020.9268330

Jeongwon Pyo, Yuri Goncalves Rocha, Arpan Ghosh, Kwanghee Lee, Gun-Gyo In, Tae-Yong Kuc

引用次数: 3

Control system for V2H applications V2H应用控制系统

2020 20th International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2020-10-13 DOI: 10.23919/ICCAS50221.2020.9268383

Martin Kosinka, Z. Slanina, Michal Petruzela, Vojtech Blazek

引用次数: 3

Human Recognition and Tracking in Narrow Indoor Environment using 3D Lidar Sensor 基于三维激光雷达传感器的狭窄室内环境中人的识别与跟踪

2020 20th International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2020-10-13 DOI: 10.23919/ICCAS50221.2020.9268208

Jae-Seong Yoon, Sanghyeon Bae, Tae-Yong Kuc

引用次数: 5

Tendon-Driven Continuum Robot Systems with only A Single Motor and A Radius-Changing Pulley 肌腱驱动的连续机器人系统，只有一个电机和一个半径变化的滑轮

2020 20th International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2020-10-13 DOI: 10.23919/ICCAS50221.2020.9268288

Myung-oh Kim, Useok Jeong, D. Choi, Duk-Yeon Lee, Bo-Hyeong Seo, Dong-Wook Lee

引用次数: 0

Active Probing Signal-Based Attack Detection Method for Autonomous Vehicular Systems 基于主动探测信号的自动驾驶车辆系统攻击检测方法

2020 20th International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2020-10-13 DOI: 10.23919/ICCAS50221.2020.9268237

Gyujin Na, Y. Eun

引用次数: 3

Study on multi-modal sensor system based sematic navigation map building 基于语义导航地图构建的多模态传感器系统研究

2020 20th International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2020-10-13 DOI: 10.23919/ICCAS50221.2020.9268414

Gi-Deok Bae, Taeyoung Uhm, Young-Ho Choi, Junghwan Hwang

{"title":"Study on multi-modal sensor system based sematic navigation map building","authors":"Gi-Deok Bae, Taeyoung Uhm, Young-Ho Choi, Junghwan Hwang","doi":"10.23919/ICCAS50221.2020.9268414","DOIUrl":"https://doi.org/10.23919/ICCAS50221.2020.9268414","url":null,"abstract":"Localization technology is essential for robots. The map created to recognize the location mainly contains metric information. However, in a changing environment, a Semantic Map containing Semantic object information is required a multi-modal sensor composed of multiple types and multiple sensors[RGBD, thermal, night vision, global shutter camera, microphone, 16 channel laser sensor(=Lidar)] was created for semantic information recognition and semantic map creation in various environments, and calibration was performed to integrate the coordinate system. After that, we introduce the method of generating the metric map according to the configuration of the multi-modal sensor. Also, we propose a method to obtain a single accurate location by integrating the location recognition results obtained from various maps. This can be used to specify the position of the semantic object. Finally, it can be expected that the semantic object and the semantic map information obtained through the multi-modal sensor can be used for various different sensor configurations and various types of robots.","PeriodicalId":6732,"journal":{"name":"2020 20th International Conference on Control, Automation and Systems (ICCAS)","volume":"23 1","pages":"1195-1197"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76534076","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: 1

GOPE: Geometry-Aware Optimal Viewpoint Path Estimation Using a Monocular Camera 基于单目摄像机的几何感知最佳视点路径估计

2020 20th International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2020-10-13 DOI: 10.23919/ICCAS50221.2020.9268299

Nuri Kim, Yunho Choi, Minjae Kang, Songhwai Oh

{"title":"GOPE: Geometry-Aware Optimal Viewpoint Path Estimation Using a Monocular Camera","authors":"Nuri Kim, Yunho Choi, Minjae Kang, Songhwai Oh","doi":"10.23919/ICCAS50221.2020.9268299","DOIUrl":"https://doi.org/10.23919/ICCAS50221.2020.9268299","url":null,"abstract":"The goal of the optimal viewpoint path estimation is to generate a path to the optimal viewpoint location where the robot can best see the Point of Interest (POI). There are several learning-based methods to find an optimal viewpoint, but these methods are limited to a specific object POI and it is necessary to newly learn in a situation where a new POI is added, and not robust to the environment changes. In this paper, we propose an algorithm that generates a path to the optimal viewpoint by using the geometrical features of the environment in the situation where the target POI is in the field of view. This method makes it easy to add new POIs and is robust to environmental changes because it uses semantic and geometric information. We assume that the robot can make a simple estimation of the geometric characteristics of the surrounding environment by using pretrained networks or by using sensor values. We collected the Kwanjeong street dataset for testing our algorithm. In this dataset, the distance accuracy of our method to reach the optimal viewpoint of the POI achieved 81.8% and 70.9% for template matching accuracy.","PeriodicalId":6732,"journal":{"name":"2020 20th International Conference on Control, Automation and Systems (ICCAS)","volume":"91 1","pages":"1062-1067"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79606110","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