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2020 International Symposium on Flexible Automation最新文献

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Application of MOSA Algorithm in Gleeble Testing Model Updating MOSA算法在Gleeble测试模型更新中的应用
2020 International Symposium on Flexible Automation Pub Date : 2020-09-25 DOI: 10.1115/isfa2020-9646
Dong Xu, K. Zhou, J. Tang
{"title":"Application of MOSA Algorithm in Gleeble Testing Model Updating","authors":"Dong Xu, K. Zhou, J. Tang","doi":"10.1115/isfa2020-9646","DOIUrl":"https://doi.org/10.1115/isfa2020-9646","url":null,"abstract":"\u0000 This research concerns the parametric identification of Johnson-Cook constitutive model which is frequently used to describe the mechanical behavior of metal material at high temperature. An improved multi-objective simulated annealing (MOSA) algorithm is introduced to update Johnson-Cook model based on Gleeble testing data for Steel T24. Our case study produces Pareto solutions ranked by the error corresponding to each parameter to be optimized. This algorithm improves the previous methods and yields a more suitable solution corresponding to the actual situation.","PeriodicalId":159740,"journal":{"name":"2020 International Symposium on Flexible Automation","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133243972","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
Identifying the Cyber-Incidents in Additive Manufacturing Systems via Multimedia Signals 利用多媒体信号识别增材制造系统中的网络事故
2020 International Symposium on Flexible Automation Pub Date : 2020-09-25 DOI: 10.1115/isfa2020-9648
Wei Yang, Jialei Chen, K. Paynabar, Chuck Zhang
{"title":"Identifying the Cyber-Incidents in Additive Manufacturing Systems via Multimedia Signals","authors":"Wei Yang, Jialei Chen, K. Paynabar, Chuck Zhang","doi":"10.1115/isfa2020-9648","DOIUrl":"https://doi.org/10.1115/isfa2020-9648","url":null,"abstract":"\u0000 Additive Manufacturing (AM) is an emerging manufacturing technology that plays a growing role in both industrial and consumer settings. However, security concerns of the AM have been raised among researchers. In this paper, we present an online detection mechanism for the malicious attempts on AM system, which taps into both audios and videos collected during the actual printing process. For audio signals, we propose to monitor the characteristics or patterns in the spectrogram via the Wasserstain metric. For video signals, we present a path reconstruction method which effectively monitors the motion of the printer extruder. We then show the effectiveness of our methods in a case study using Ender 3D printer, where the cyber-incidence of modifying the internal fill density can be easily identified in an online manner.","PeriodicalId":159740,"journal":{"name":"2020 International Symposium on Flexible Automation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129332692","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
Dynamic Gesture Design and Recognition for Human-Robot Collaboration With Convolutional Neural Networks 基于卷积神经网络的人机协作动态手势设计与识别
2020 International Symposium on Flexible Automation Pub Date : 2020-07-08 DOI: 10.1115/isfa2020-9609
Haodong Chen, Wenjin Tao, M. Leu, Zhaozheng Yin
{"title":"Dynamic Gesture Design and Recognition for Human-Robot Collaboration With Convolutional Neural Networks","authors":"Haodong Chen, Wenjin Tao, M. Leu, Zhaozheng Yin","doi":"10.1115/isfa2020-9609","DOIUrl":"https://doi.org/10.1115/isfa2020-9609","url":null,"abstract":"\u0000 Human-robot collaboration (HRC) is a challenging task in modern industry and gesture communication in HRC has attracted much interest. This paper proposes and demonstrates a dynamic gesture recognition system based on Motion History Image (MHI) and Convolutional Neural Networks (CNN). Firstly, ten dynamic gestures are designed for a human worker to communicate with an industrial robot. Secondly, the MHI method is adopted to extract the gesture features from video clips and generate static images of dynamic gestures as inputs to CNN. Finally, a CNN model is constructed for gesture recognition. The experimental results show very promising classification accuracy using this method.","PeriodicalId":159740,"journal":{"name":"2020 International Symposium on Flexible Automation","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132584450","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
Behavior Modeling for Product Design Support Focusing on Topological Information of Components 基于部件拓扑信息的产品设计支持行为建模
2020 International Symposium on Flexible Automation Pub Date : 2020-07-08 DOI: 10.1299/jsmedsd.2019.29.2310
Itsuki Hatano, E. Morinaga, H. Wakamatsu
{"title":"Behavior Modeling for Product Design Support Focusing on Topological Information of Components","authors":"Itsuki Hatano, E. Morinaga, H. Wakamatsu","doi":"10.1299/jsmedsd.2019.29.2310","DOIUrl":"https://doi.org/10.1299/jsmedsd.2019.29.2310","url":null,"abstract":"\u0000 In recent years, with globalization in industry, there is a concern about increase of defects caused by using products in unexpected ways. To solve this problem, a method to predict such defects in a product in advance in the design stage has been proposed, in which behavior of a product and physical phenomena caused by a way of usage are represented by Petri net. However, in order to achieve a more accurate prediction, it is necessary to consider topological information about components of a product. In this research, we aim to represent topological information about elements of an electric circuit, and to make it possible to detect failures in cooperation with the method of the previous research. By modeling each element of an electrical circuit by Petri net and connecting them each other, it is possible to build a model that represents topological information about the circuit, and it can be checked whether there is a closed circuit and which element the current flows through. In addition, by reflecting the information about the circuit to the conventional model, more accurate failure detection can be performed. The fundamental effectiveness of the method was shown by case studies using an example circuit.","PeriodicalId":159740,"journal":{"name":"2020 International Symposium on Flexible Automation","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122113833","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
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