2021 IEEE 19th International Conference on Industrial Informatics (INDIN)最新文献_第5页

Adaptive Canonical Correlation Analysis Method Based on Forgetting Factor for Fault Detection 基于遗忘因子的自适应典型相关分析方法用于故障检测

2021 IEEE 19th International Conference on Industrial Informatics (INDIN) Pub Date : 2021-07-21 DOI: 10.1109/INDIN45523.2021.9557411

J. Guan, Jinghui Yang, Guang Wang

{"title":"Adaptive Canonical Correlation Analysis Method Based on Forgetting Factor for Fault Detection","authors":"J. Guan, Jinghui Yang, Guang Wang","doi":"10.1109/INDIN45523.2021.9557411","DOIUrl":"https://doi.org/10.1109/INDIN45523.2021.9557411","url":null,"abstract":"In this paper, an adaptive canonical correlation analysis method is proposed for fault detection in time-varying processes. Firstly, a designed forgetting factor is used to update the canonical correlation analysis (CCA) model that builded with initial normal process data. Then, Mahalanobis distance is introduced as a classifier to distinguish whether data changes are caused by system modal changes or system abnormalities. In this way, the new model can not only be updated according to the system modality in real time, but also can accurately response to the occurrence of faults. Compared with traditional CCAbased methods, the proposed new method has the following two advantages: 1) it has a wider range of application scenarios since it can adapt to slow changes in the system or changes in operating points; and 2) it has a smaller amount of calculation because it only performs a simple data classification rather than require complex iterative operations on the threshold. The effectiveness of the new method is verified in a simulated superheated steam spray water temperature reduction process.","PeriodicalId":370921,"journal":{"name":"2021 IEEE 19th International Conference on Industrial Informatics (INDIN)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126551973","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

Anomaly Detection in the Time Series Data from Fehn Pollux Ship with ECO Flettner Rotor 带有ECO Flettner转子的Fehn污染型船舶时间序列数据的异常检测

2021 IEEE 19th International Conference on Industrial Informatics (INDIN) Pub Date : 2021-07-21 DOI: 10.1109/INDIN45523.2021.9557422

Farzaneh Nourmohammadi, A. Jumabayev, Elmar Wings

引用次数: 0

Analysis of Latency and Reliability Improvement with Multi-Link Operation over 802.11 基于802.11的多链路操作延迟和可靠性改进分析

2021 IEEE 19th International Conference on Industrial Informatics (INDIN) Pub Date : 2021-07-21 DOI: 10.1109/INDIN45523.2021.9557495

Guillermo Lacalle, I. Val, Óscar Seijo, M. Mendicute, D. Cavalcanti, Javier Perez-Ramirez

引用次数: 13

QoS-Aware Heterogeneous Data Transmission Mechanism for Industrial IoT Systems 基于qos感知的工业物联网异构数据传输机制

2021 IEEE 19th International Conference on Industrial Informatics (INDIN) Pub Date : 2021-07-21 DOI: 10.1109/INDIN45523.2021.9557412

Cheng Ren, Cailian Chen, Mingyan Li, X. Guan

{"title":"QoS-Aware Heterogeneous Data Transmission Mechanism for Industrial IoT Systems","authors":"Cheng Ren, Cailian Chen, Mingyan Li, X. Guan","doi":"10.1109/INDIN45523.2021.9557412","DOIUrl":"https://doi.org/10.1109/INDIN45523.2021.9557412","url":null,"abstract":"Various wireless manufacturing sensors facilitate the monitoring and control process in industrial internet of things (IIoT) systems. Control and image data generated by control and vision-based monitoring systems are transmitted over shared wireless network to edge computing devices for further decisions. Due to limited spectrum resources and sensor transmit power, it is challenging to design efficient quality of service (QoS) aware transmission mechanism for heterogeneous data with diverse real-time and system performance requirements. In this paper, in order to guarantee control system performance and image clarity, the time slot allocation and transmission power for heterogeneous sensors are jointly optimized by formulating a mixed integer nonlinear programming (MINLP) problem. The MINLP problem is decomposed into multiple subproblems which are proved to have strong duality and can be solved in dual domain. Then, according to acknowledge (ACK) signals, we propose a priority-aware heuristic algorithm to solve each subproblem. Finally, the simulation results prove that our proposed mechanism can reduce the number of slots and energy consumption for transmission while guaranteeing performance requirements of heterogeneous data.","PeriodicalId":370921,"journal":{"name":"2021 IEEE 19th International Conference on Industrial Informatics (INDIN)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127521092","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 PMSMs Motor Current Signature Analysis and Motor Torque Analysis Under Transient Conditions. 暂态条件下永磁同步电机电流特征分析与电机转矩分析的比较。

2021 IEEE 19th International Conference on Industrial Informatics (INDIN) Pub Date : 2021-07-21 DOI: 10.1109/INDIN45523.2021.9557553

A. Bonci, M. Indri, Renat Kermenov, S. Longhi, Giacomo Nabissi

引用次数: 2

Development of Cloud-Edge Collaborative Digital Twin System for FDM Additive Manufacturing 面向FDM增材制造的云边缘协同数字孪生系统开发

2021 IEEE 19th International Conference on Industrial Informatics (INDIN) Pub Date : 2021-07-21 DOI: 10.1109/INDIN45523.2021.9557492

Liang Guo, Yunxi Cheng, Yu Zhang, Y. Liu, Changcheng Wan, Jingyi Liang

{"title":"Development of Cloud-Edge Collaborative Digital Twin System for FDM Additive Manufacturing","authors":"Liang Guo, Yunxi Cheng, Yu Zhang, Y. Liu, Changcheng Wan, Jingyi Liang","doi":"10.1109/INDIN45523.2021.9557492","DOIUrl":"https://doi.org/10.1109/INDIN45523.2021.9557492","url":null,"abstract":"The physical and virtual access of manufacturing equipment to the cloud platform is an important direction of cloud manufacturing research, but the current research results in this direction are not enough to support the \"landing\" and wide application of cloud manufacturing model. In the traditional cloud manufacturing model, the direct access of manufacturing equipment to the cloud brings huge network pressure and unbearable latency, and also poses a privacy and security risk. Aiming at the cloudification of manufacturing equipment in the cloud manufacturing environment, the 3D printer is selected as the research object, and a cloud-edge collaboration architecture for 3D printers based on digital twin is proposed. To solve the lack of network reliability brought about by traditional cloudification, time-sensitive services are deployed at the edge, realizing the local extension of cloud services. The digital twin information model of FDM additive manufacturing is defined. Real time controlling and monitoring based on digital twin is realized. By cloud-edge collaboration, an application case is implemented, which verifies the effectiveness of the system and provides a reference solution for the cloudification of other manufacturing equipment in the environment of cloud manufacturing.","PeriodicalId":370921,"journal":{"name":"2021 IEEE 19th International Conference on Industrial Informatics (INDIN)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121511202","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: 4

An Autonomous Mobile Robot Navigation Architecture for Dynamic Intralogistics 面向动态内部物流的自主移动机器人导航体系结构

2021 IEEE 19th International Conference on Industrial Informatics (INDIN) Pub Date : 2021-07-21 DOI: 10.1109/INDIN45523.2021.9557419

David Taranta, Francisco Marques, André Lourenço, P. Prates, Alexandre Souto, Eduardo Pinto, J. Barata

引用次数: 0

Indirect Mass Flow Estimation based on Power Measurements of Conveyor Belts in Mineral Processing Applications 基于输送带功率测量的间接质量流量估算在选矿中的应用

2021 IEEE 19th International Conference on Industrial Informatics (INDIN) Pub Date : 2021-07-21 DOI: 10.1109/INDIN45523.2021.9557482

Bernhard Heinzl, Jorge Martínez Gil, Johannes Himmelbauer, M. Rossbory, Christian Hinterdorfer, Christian Hinterreiter

引用次数: 1

Overview and Trends for Application of AI Methods for Product Design 人工智能方法在产品设计中的应用综述与趋势

2021 IEEE 19th International Conference on Industrial Informatics (INDIN) Pub Date : 2021-07-21 DOI: 10.1109/INDIN45523.2021.9557531

Brikene Berisha, A. Lobov

引用次数: 2

Adoption of digital technologies during the COVID-19 pandemic: Lessons learned from collaborative Academia-Industry R&D case studies 2019冠状病毒病大流行期间数字技术的采用:从校企合作研发案例研究中吸取的经验教训

2021 IEEE 19th International Conference on Industrial Informatics (INDIN) Pub Date : 2021-07-21 DOI: 10.1109/INDIN45523.2021.9557470

A. Simões, F. Ferreira, Hélio Castro, Pedro P. Senna, D. Silva, G. Dalmarco

{"title":"Adoption of digital technologies during the COVID-19 pandemic: Lessons learned from collaborative Academia-Industry R&D case studies","authors":"A. Simões, F. Ferreira, Hélio Castro, Pedro P. Senna, D. Silva, G. Dalmarco","doi":"10.1109/INDIN45523.2021.9557470","DOIUrl":"https://doi.org/10.1109/INDIN45523.2021.9557470","url":null,"abstract":"The need of lockdown, due to COVID-19, led many manufacturing companies to accelerate the adoption of digital technologies. Manufacturing companies were strongly affected by workforce shortages associated with the spread of COVID-19 and the lockdown, as well by connectivity losses among business partners. Therefore, these companies are reviewing their strategies to increase productivity, mainly embracing digital manufacturing technologies. Here the adoption of digital technologies aims to improve efficiency and flexibility in their processes, also improving connectivity among business partners. This study investigates how collaborative academia-industry R&D cases accelerated the adoption of digital technologies by manufacturing companies, given the current COVID-19 pandemic situation. Based on multiple case studies, this article reports the challenges and the strategies of three ongoing collaborative industry-academia R&D projects developed during the COVID pandemic situation. The results are presented in four different perspectives derived from industry 4.0 readiness maturity models: interpersonal communication, personal competencies and skills, systems integration, and technological strategy. It highlights the importance of manufacturing companies to have a well-designed digitalization strategy, need of continuous training and development of their workforce, and the support of Research & Technology Organizations (RTO) to bring more maturity to the efforts required during a turbulent situation. The results of this paper can provide relevant decision support for manufacturing companies, and its stakeholders, in face of challenges of the actual pandemic and post-pandemic scenario.","PeriodicalId":370921,"journal":{"name":"2021 IEEE 19th International Conference on Industrial Informatics (INDIN)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125240613","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