Pub Date : 2021-09-07DOI: 10.1109/ETFA45728.2021.9613350
Hongyu Lu, Xiaodong Ren, M. Tong
The current visual object tracking algorithm of Fully-Convolutional Siamese Networks (SiamFC) has good performance of accuracy and frame rate. However, when tracking an object moving in a scene with complex background, the templates applied in SiamFC tend to introduce the excessive background information that may cause interference to the target. In this paper, a method of suppressing the background information in templates is proposed to cope with this problem. On one hand, it reduces the introduction of background information by using adaptive aspect ratio when making templates. On the other hand, it decreases the impact of background information on matching results through Gaussian weighting after the templates inevitably introduce background information. The effectiveness of the proposed method has been experimentally validated without loss of real-time performance. In the comparison experiments, the proposed algorithm has improved the area under curve (AUC) of success plots by 9.07% and 13.31% on OTB2013 dataset and OTB50 dataset, respectively, compared with the original SiamFC under the complex background interference scenarios.
{"title":"Object Tracking Algorithm of Fully-Convolutional Siamese Networks Using the Templates with Suppressed Background Information","authors":"Hongyu Lu, Xiaodong Ren, M. Tong","doi":"10.1109/ETFA45728.2021.9613350","DOIUrl":"https://doi.org/10.1109/ETFA45728.2021.9613350","url":null,"abstract":"The current visual object tracking algorithm of Fully-Convolutional Siamese Networks (SiamFC) has good performance of accuracy and frame rate. However, when tracking an object moving in a scene with complex background, the templates applied in SiamFC tend to introduce the excessive background information that may cause interference to the target. In this paper, a method of suppressing the background information in templates is proposed to cope with this problem. On one hand, it reduces the introduction of background information by using adaptive aspect ratio when making templates. On the other hand, it decreases the impact of background information on matching results through Gaussian weighting after the templates inevitably introduce background information. The effectiveness of the proposed method has been experimentally validated without loss of real-time performance. In the comparison experiments, the proposed algorithm has improved the area under curve (AUC) of success plots by 9.07% and 13.31% on OTB2013 dataset and OTB50 dataset, respectively, compared with the original SiamFC under the complex background interference scenarios.","PeriodicalId":312498,"journal":{"name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115773169","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}
Pub Date : 2021-09-07DOI: 10.1109/ETFA45728.2021.9613365
Jan Nicolas Weskamp, Juilee Tikekar
Gaining value out of data provided in industrial application in a standardized Industrie 4.0 compliant way is a challenging and time-extensive task. Not only does the data need to be integrated into a data platform, it also needs to be described and integrated in an appropriate way, that allows a standardized processing for its value-added services. One way to achieve this, lies in the use of OPC UA and the asset administration shell. Together they can implement an Industrie 4.0 Component as the standardized service for tailored data integration and usage. Data in OPC UA is available in different levels of abstraction, both in terms of the data and its description. Rarely is the asset administration shell (AAS) considered in this context. This paper will introduce a first approach to harmonize OPC UA and the AAS in an I4.0 compliant Aggregation Server. The server is able to aggregate information models based on the current meta model mapping of the AAS, regardless of whether the base servers implement this or not. Moreover the aggregated server can route OPC UA services down to the base servers and is managing itself in case of discovery and information aggregation. This approach can be used as the standalone interface for data integration in respective data platforms.
{"title":"An Industrie 4.0 compliant and self-managing OPC UA Aggregation Server","authors":"Jan Nicolas Weskamp, Juilee Tikekar","doi":"10.1109/ETFA45728.2021.9613365","DOIUrl":"https://doi.org/10.1109/ETFA45728.2021.9613365","url":null,"abstract":"Gaining value out of data provided in industrial application in a standardized Industrie 4.0 compliant way is a challenging and time-extensive task. Not only does the data need to be integrated into a data platform, it also needs to be described and integrated in an appropriate way, that allows a standardized processing for its value-added services. One way to achieve this, lies in the use of OPC UA and the asset administration shell. Together they can implement an Industrie 4.0 Component as the standardized service for tailored data integration and usage. Data in OPC UA is available in different levels of abstraction, both in terms of the data and its description. Rarely is the asset administration shell (AAS) considered in this context. This paper will introduce a first approach to harmonize OPC UA and the AAS in an I4.0 compliant Aggregation Server. The server is able to aggregate information models based on the current meta model mapping of the AAS, regardless of whether the base servers implement this or not. Moreover the aggregated server can route OPC UA services down to the base servers and is managing itself in case of discovery and information aggregation. This approach can be used as the standalone interface for data integration in respective data platforms.","PeriodicalId":312498,"journal":{"name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116965150","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}
Pub Date : 2021-09-07DOI: 10.1109/ETFA45728.2021.9613152
Pushparaj Bhosale, W. Kastner, T. Sauter
The application of Industry 4.0 (I4.0) architectures to the conservative nature of present Industrial Control System (ICS) has brought along many challenges. The ever-changing and dynamically altering threat landscape has led to many hazards and risks w.r.t. safe and secure operation of underlying assets. To understand and manage such risks, organizations perform assessments. Risk assessments performed today are typically handled in a centralized manner on a higher layer of the automation pyramid. The concept of the Asset Administration Shell (AAS) for I4.0 component might provide means to access and process data at the component level throughout the lifecycle, thus taking the assessment from a strictly centralized to a distributed manner. This paper, thus, focuses on the possibility of risk assessment either performed centrally or in a distributed manner aiming at highlighting data sources, acquisition, and processing mechanisms for the same relying on the AAS.
{"title":"A Centralised or Distributed Risk Assessment using Asset Administration Shell","authors":"Pushparaj Bhosale, W. Kastner, T. Sauter","doi":"10.1109/ETFA45728.2021.9613152","DOIUrl":"https://doi.org/10.1109/ETFA45728.2021.9613152","url":null,"abstract":"The application of Industry 4.0 (I4.0) architectures to the conservative nature of present Industrial Control System (ICS) has brought along many challenges. The ever-changing and dynamically altering threat landscape has led to many hazards and risks w.r.t. safe and secure operation of underlying assets. To understand and manage such risks, organizations perform assessments. Risk assessments performed today are typically handled in a centralized manner on a higher layer of the automation pyramid. The concept of the Asset Administration Shell (AAS) for I4.0 component might provide means to access and process data at the component level throughout the lifecycle, thus taking the assessment from a strictly centralized to a distributed manner. This paper, thus, focuses on the possibility of risk assessment either performed centrally or in a distributed manner aiming at highlighting data sources, acquisition, and processing mechanisms for the same relying on the AAS.","PeriodicalId":312498,"journal":{"name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115017810","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}
Pub Date : 2021-09-07DOI: 10.1109/ETFA45728.2021.9613546
Fiorella Sibona, Pangcheng David Cen Cheng, M. Indri, Danilo Di Prima
In the last decades, industrial manipulators have been used to speed up the production process and also to perform tasks that may put humans at risk. Typical interfaces employed to teleoperate the robot are not so intuitive to use. In fact, it takes longer to learn and properly control a robot whose interface is not easy to use, and it may also increase the operator's stress and mental workload. In this paper, a touchscreen interface for supervised assembly tasks is proposed, using an LCD screen and a hand-tracking sensor. The aim is to provide an intuitive remote controlled system that enables a flexible execution of assembly tasks: high level decisions are entrusted to the human operator while the robot executes pick-and-place operations. A demonstrative industrial case study showcases the system potentiality: it was first tested in simulation, and then experimentally validated using a real robot, in a laboratory environment.
{"title":"PoinTap system: a human-robot interface to enable remotely controlled tasks","authors":"Fiorella Sibona, Pangcheng David Cen Cheng, M. Indri, Danilo Di Prima","doi":"10.1109/ETFA45728.2021.9613546","DOIUrl":"https://doi.org/10.1109/ETFA45728.2021.9613546","url":null,"abstract":"In the last decades, industrial manipulators have been used to speed up the production process and also to perform tasks that may put humans at risk. Typical interfaces employed to teleoperate the robot are not so intuitive to use. In fact, it takes longer to learn and properly control a robot whose interface is not easy to use, and it may also increase the operator's stress and mental workload. In this paper, a touchscreen interface for supervised assembly tasks is proposed, using an LCD screen and a hand-tracking sensor. The aim is to provide an intuitive remote controlled system that enables a flexible execution of assembly tasks: high level decisions are entrusted to the human operator while the robot executes pick-and-place operations. A demonstrative industrial case study showcases the system potentiality: it was first tested in simulation, and then experimentally validated using a real robot, in a laboratory environment.","PeriodicalId":312498,"journal":{"name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116111977","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}
Pub Date : 2021-09-07DOI: 10.1109/ETFA45728.2021.9613175
S. Sarkar, R. ChandrikaK.
Industrial process automation engineering implements a control code of a process plant manually. This paper proposes an approach that reads a control specification as a multi-page graphical document and implements control code as a Control logic diagram (CLD) for a target controller. We use a novel vector image processing-based approach to extract entities, equipment blocks, and the control flow from this document. We represent the control flow information as language-agnostic intermediate equipment and control flow graph. The translator traverses the graph and applies a set of mapping rules to generate the control logic. A preliminary analysis reveals that our approach has the potential of saving a significant amount of manual effort to generate a CLD from such a specification.
{"title":"Automatic Control Code Generation from SAMA Specification","authors":"S. Sarkar, R. ChandrikaK.","doi":"10.1109/ETFA45728.2021.9613175","DOIUrl":"https://doi.org/10.1109/ETFA45728.2021.9613175","url":null,"abstract":"Industrial process automation engineering implements a control code of a process plant manually. This paper proposes an approach that reads a control specification as a multi-page graphical document and implements control code as a Control logic diagram (CLD) for a target controller. We use a novel vector image processing-based approach to extract entities, equipment blocks, and the control flow from this document. We represent the control flow information as language-agnostic intermediate equipment and control flow graph. The translator traverses the graph and applies a set of mapping rules to generate the control logic. A preliminary analysis reveals that our approach has the potential of saving a significant amount of manual effort to generate a CLD from such a specification.","PeriodicalId":312498,"journal":{"name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","volume":"428 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116551326","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}
Pub Date : 2021-09-07DOI: 10.1109/ETFA45728.2021.9613314
Irlán Grangel-González, Fasal Shah
Industry 4.0 requires the integration of many actors to provide correct, personalized, and quick answers to customers. In order to meet this integration, data coming from different actors demand to be semantically integrated and harmonized. In these settings, knowledge graphs have proven to be successful in the task of semantic data integration of distinct data silos. Despite the increasing adoption of knowledge graphs in the Industry 4.0 domain for integrating and harmonizing data, still, all the power of the integrated data is not exploited. In this article, we tackle the problem of knowledge graph completion presenting an approach that applies supervised machine learning algorithms on top of the knowledge graph. In general, observed results indicate that supervised machine learning algorithms perform with an AUC of more than 88%. These outcomes suggest that knowledge graph completion enables to unveil new relations by connecting entities in the knowledge graph. Thus, the discovered relations in the knowledge graph bring added value to the Industry 4.0 domain.
{"title":"Link Prediction with Supervised Learning on an Industry 4.0 related Knowledge Graph","authors":"Irlán Grangel-González, Fasal Shah","doi":"10.1109/ETFA45728.2021.9613314","DOIUrl":"https://doi.org/10.1109/ETFA45728.2021.9613314","url":null,"abstract":"Industry 4.0 requires the integration of many actors to provide correct, personalized, and quick answers to customers. In order to meet this integration, data coming from different actors demand to be semantically integrated and harmonized. In these settings, knowledge graphs have proven to be successful in the task of semantic data integration of distinct data silos. Despite the increasing adoption of knowledge graphs in the Industry 4.0 domain for integrating and harmonizing data, still, all the power of the integrated data is not exploited. In this article, we tackle the problem of knowledge graph completion presenting an approach that applies supervised machine learning algorithms on top of the knowledge graph. In general, observed results indicate that supervised machine learning algorithms perform with an AUC of more than 88%. These outcomes suggest that knowledge graph completion enables to unveil new relations by connecting entities in the knowledge graph. Thus, the discovered relations in the knowledge graph bring added value to the Industry 4.0 domain.","PeriodicalId":312498,"journal":{"name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122327368","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}
Pub Date : 2021-09-07DOI: 10.1109/ETFA45728.2021.9613695
Christoffer Fink, Wilma Krutrök, O. Schelén, Ulf Bodin
In truck manufacturing, an assembly line is typically used to produce many models and variations of trucks in any desired order. Thus, stations are fed with specific sets of parts, known as kits, depending on what truck is next in line. This paper focuses on how to automate the layout planning for placing parts on a kitting wagon. Layout planning resembles the pallet loading problem, but differences include that there is no layering, there may be constraints on how each part can be placed (orientation) and there may be predefined layout hints suggesting positions. A layout planner based on constraint programming is presented. The objective is to facilitate a decision support loop where an engineer may add placement hints as constraints (e.g., for enhancing the workflow at assembly stations) and reuse placements from similar kits to provide recognition. The layout planner automatically generates layout proposals. Finally, it is the engineer that approves the layout plan. There may be many acceptable solutions that have different scores (i.e., levels of quality). We show some approaches to reduce the search space to improve performance. The evaluations show the score and time needed for finding results on some problem instances that are optimally solvable. In the general case, however, finding an optimal solution may be unnecessary or even intractable.
{"title":"Layout planning in assembly line kitting - a constraint programming approach","authors":"Christoffer Fink, Wilma Krutrök, O. Schelén, Ulf Bodin","doi":"10.1109/ETFA45728.2021.9613695","DOIUrl":"https://doi.org/10.1109/ETFA45728.2021.9613695","url":null,"abstract":"In truck manufacturing, an assembly line is typically used to produce many models and variations of trucks in any desired order. Thus, stations are fed with specific sets of parts, known as kits, depending on what truck is next in line. This paper focuses on how to automate the layout planning for placing parts on a kitting wagon. Layout planning resembles the pallet loading problem, but differences include that there is no layering, there may be constraints on how each part can be placed (orientation) and there may be predefined layout hints suggesting positions. A layout planner based on constraint programming is presented. The objective is to facilitate a decision support loop where an engineer may add placement hints as constraints (e.g., for enhancing the workflow at assembly stations) and reuse placements from similar kits to provide recognition. The layout planner automatically generates layout proposals. Finally, it is the engineer that approves the layout plan. There may be many acceptable solutions that have different scores (i.e., levels of quality). We show some approaches to reduce the search space to improve performance. The evaluations show the score and time needed for finding results on some problem instances that are optimally solvable. In the general case, however, finding an optimal solution may be unnecessary or even intractable.","PeriodicalId":312498,"journal":{"name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121908264","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}
Pub Date : 2021-09-07DOI: 10.1109/ETFA45728.2021.9613602
Alexander Ressel, Ronald Schmidt-Vollus
This paper provides a method for the reverse engineering process of automation engineering data and a suitable data format for storage and further information enrichment of the gathered data. A method is presented that analyzes process automation flowcharts. Artificial neural networks recognize apparatus and text in the flowchart. Synthetic training data for another artificial neural network is created to detect connections between the recognized apparatus. The neutral data format AutomationML is used to store the gathered data and make it available for further enrichment with plant data. With the method presented in this paper it is possible to overcome the lack of compatible interfaces in the heterogeneous tool landscape of process automation engineering and to reuse analog engineering data for further development of a plant.
{"title":"Reverse engineering in process automation","authors":"Alexander Ressel, Ronald Schmidt-Vollus","doi":"10.1109/ETFA45728.2021.9613602","DOIUrl":"https://doi.org/10.1109/ETFA45728.2021.9613602","url":null,"abstract":"This paper provides a method for the reverse engineering process of automation engineering data and a suitable data format for storage and further information enrichment of the gathered data. A method is presented that analyzes process automation flowcharts. Artificial neural networks recognize apparatus and text in the flowchart. Synthetic training data for another artificial neural network is created to detect connections between the recognized apparatus. The neutral data format AutomationML is used to store the gathered data and make it available for further enrichment with plant data. With the method presented in this paper it is possible to overcome the lack of compatible interfaces in the heterogeneous tool landscape of process automation engineering and to reuse analog engineering data for further development of a plant.","PeriodicalId":312498,"journal":{"name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122133384","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}
Pub Date : 2021-09-07DOI: 10.1109/ETFA45728.2021.9613490
R. Hill, J. Delbos, Selena Trebosc, Junior Tsague, Gregoire Feroldi, J. Martin, Tobiah R Master, N. Lassabe
It is well-known that one the most important challenges in industrial manufacturing processes is the reduction of lead-times and delays during the on-site commissioning. In applications in which several automation systems are used, such as in aeronautics or automotive manufacturing cells, several PLC's and drives are used to control the motion of the different electromechanical components. In order to verify and validate (V&V) automation code before deployment in the production environment, virtual commissioning (VC) techniques have become of great interest in the last decades. Even if VC simulation approaches, based on software/hardware-in-the-loop (SiL, HiL), have shown effectiveness to V&V automation code, the continuity from the execution to the simulation layers may not be ensured due to a lack of interoperability in the toolchain. Additionally, the development of reliable component models is a complex task of the VC solution since it requires a high level of mechatronics expertise. In order to avoid losing information between the execution and the simulation layers of VC toolchains, this paper presents a SiL based approach for interconnecting the PLC's with the VC simulation tool by means of OPC-UA-based technologies. In addition, in order to develop the functional models, we propose a library-based development. This will facilitate seamless flow of information between different PLC editors and the simulation layer. SiL simulations of the suggested approach on an automotive manufacturing cell are performed and show digital continuity from the execution to the simulation layer.
{"title":"Improving interoperability of Virtual Commissioning toolchains by using OPC-UA-based technologies","authors":"R. Hill, J. Delbos, Selena Trebosc, Junior Tsague, Gregoire Feroldi, J. Martin, Tobiah R Master, N. Lassabe","doi":"10.1109/ETFA45728.2021.9613490","DOIUrl":"https://doi.org/10.1109/ETFA45728.2021.9613490","url":null,"abstract":"It is well-known that one the most important challenges in industrial manufacturing processes is the reduction of lead-times and delays during the on-site commissioning. In applications in which several automation systems are used, such as in aeronautics or automotive manufacturing cells, several PLC's and drives are used to control the motion of the different electromechanical components. In order to verify and validate (V&V) automation code before deployment in the production environment, virtual commissioning (VC) techniques have become of great interest in the last decades. Even if VC simulation approaches, based on software/hardware-in-the-loop (SiL, HiL), have shown effectiveness to V&V automation code, the continuity from the execution to the simulation layers may not be ensured due to a lack of interoperability in the toolchain. Additionally, the development of reliable component models is a complex task of the VC solution since it requires a high level of mechatronics expertise. In order to avoid losing information between the execution and the simulation layers of VC toolchains, this paper presents a SiL based approach for interconnecting the PLC's with the VC simulation tool by means of OPC-UA-based technologies. In addition, in order to develop the functional models, we propose a library-based development. This will facilitate seamless flow of information between different PLC editors and the simulation layer. SiL simulations of the suggested approach on an automotive manufacturing cell are performed and show digital continuity from the execution to the simulation layer.","PeriodicalId":312498,"journal":{"name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124647821","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}
Pub Date : 2021-09-07DOI: 10.1109/ETFA45728.2021.9613604
Tao Zheng, Zuyao Meng, Qing Gu, Fei Huang, M. Gidlund
Fault diagnosis in Industrial Internet of Things and Cyber-Physical Systems is essential, especially for the rapidly developing 5G and coming 6G technology. Hardware working status is the basis for fault diagnosis. However, in actual engineering, accurately locating faults is not easy for hardware engineers. In this paper, a prototype based on FPGA is developed to connect with the target field device in data acquisition. This prototype aims to extract the underlying data information in a real-time and unattended manner like the mimicry of natural immunity. The preliminary experiment results from the prototype can be used to guide practice through providing real-time data support for hardware troubleshooting and spontaneous and intelligent analysis.
{"title":"A Preliminary Prototype Based on Biological Mimicry for Hardware Data Acquisition","authors":"Tao Zheng, Zuyao Meng, Qing Gu, Fei Huang, M. Gidlund","doi":"10.1109/ETFA45728.2021.9613604","DOIUrl":"https://doi.org/10.1109/ETFA45728.2021.9613604","url":null,"abstract":"Fault diagnosis in Industrial Internet of Things and Cyber-Physical Systems is essential, especially for the rapidly developing 5G and coming 6G technology. Hardware working status is the basis for fault diagnosis. However, in actual engineering, accurately locating faults is not easy for hardware engineers. In this paper, a prototype based on FPGA is developed to connect with the target field device in data acquisition. This prototype aims to extract the underlying data information in a real-time and unattended manner like the mimicry of natural immunity. The preliminary experiment results from the prototype can be used to guide practice through providing real-time data support for hardware troubleshooting and spontaneous and intelligent analysis.","PeriodicalId":312498,"journal":{"name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124770232","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}
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