Traditional field gas station monitoring follows a pyramid control system scheme, and the system was divided into 4 layers: field, control, monitoring, and management. With the advance of technologies, two problems appear: 1). A variety of specialty controllers contribute to the control of a field gas station, each has its own HMI, the SCADA of the monitoring layer focuses on the integration of HMI functions, not on collection and analysis of big data. 2). To build an edge-cloud collaboration big data platform, data from all field gas stations are required, the traditional PLCs of the control layer and the SCADA system of the monitoring layer do not have enough computing power to collect and process data from all of the controllers. This paper proposed a software-defined PLC technology to integrate the control function of the control layer and the HMI function of the monitoring layer into an edge computing server with 5G support, that provide unified data acquisition, display, and data access functionalities on the premise, and support the required data collection for the cloud. This has been proven to be a consolidated and cost effective approach with improved customer values.
{"title":"Field gas supply station monitoring based on software-defined PLC edge server","authors":"Dai JiYuLei, Hu Jun, S. Kai, Zhou Honbo","doi":"10.1117/12.2679696","DOIUrl":"https://doi.org/10.1117/12.2679696","url":null,"abstract":"Traditional field gas station monitoring follows a pyramid control system scheme, and the system was divided into 4 layers: field, control, monitoring, and management. With the advance of technologies, two problems appear: 1). A variety of specialty controllers contribute to the control of a field gas station, each has its own HMI, the SCADA of the monitoring layer focuses on the integration of HMI functions, not on collection and analysis of big data. 2). To build an edge-cloud collaboration big data platform, data from all field gas stations are required, the traditional PLCs of the control layer and the SCADA system of the monitoring layer do not have enough computing power to collect and process data from all of the controllers. This paper proposed a software-defined PLC technology to integrate the control function of the control layer and the HMI function of the monitoring layer into an edge computing server with 5G support, that provide unified data acquisition, display, and data access functionalities on the premise, and support the required data collection for the cloud. This has been proven to be a consolidated and cost effective approach with improved customer values.","PeriodicalId":438484,"journal":{"name":"International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114358085","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}
Dai JiYuLei, Zhang QiuYan, Ou JiaXiang, Deng YueDan, Zhou Honbo, Pan RongZhen
Some of the traditional power distribution network fault location, isolation, and service restoration (FLISR) tasks were conducted with feeder automation (FA), which is part of the distribution automation (DA) system. Existing FA scheme have issues such as long fault processing time, due to centralized decision making. In this paper, a FLISR scheme for distribution network based on edge computing and 5G is proposed. Three key technologies of the scheme are introduced: ① Edge computing servers with local terminal units (LTU); ② FLISR algorithms with software-defined control and edge-cloud collaboration; ③ 5G integrated with edge computing (MEC). The proposed scheme is the first case with integrated 5G and MEC in DA applications, which can effectively shorten the fault processing time as evidenced by the deployed system’s performance.
{"title":"Distribution network fault location and isolation based on edge computing and 5G","authors":"Dai JiYuLei, Zhang QiuYan, Ou JiaXiang, Deng YueDan, Zhou Honbo, Pan RongZhen","doi":"10.1117/12.2679658","DOIUrl":"https://doi.org/10.1117/12.2679658","url":null,"abstract":"Some of the traditional power distribution network fault location, isolation, and service restoration (FLISR) tasks were conducted with feeder automation (FA), which is part of the distribution automation (DA) system. Existing FA scheme have issues such as long fault processing time, due to centralized decision making. In this paper, a FLISR scheme for distribution network based on edge computing and 5G is proposed. Three key technologies of the scheme are introduced: ① Edge computing servers with local terminal units (LTU); ② FLISR algorithms with software-defined control and edge-cloud collaboration; ③ 5G integrated with edge computing (MEC). The proposed scheme is the first case with integrated 5G and MEC in DA applications, which can effectively shorten the fault processing time as evidenced by the deployed system’s performance.","PeriodicalId":438484,"journal":{"name":"International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116015057","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}
To solve the traditional water quality detection using ZigBee, GPRS, and other communication technologies having limited coverage distance, high power consumption, high cost, and complex deployment problems, according to the water quality testing real-time monitoring requirements, an NB-IoT-based water quality monitoring system platform is designed. The system uses the "end-tube-cloud" of the Internet of things mode, through the temperature, pH, dissolved oxygen, and other sensors to collect water quality parameters. M5310-A module will receive the sensor data uploaded to the OneNET cloud platform to achieve the remote transmission of water quality information and display functions, while the user can be in the application terminal real-time monitoring and directly read the water quality parameters of the measured waters. The system effectively improves the efficiency and modernization of water quality monitoring work, with good application prospects and economic benefits.
{"title":"The construction of an intelligent water environment automatic monitoring system based on the Internet of Things","authors":"Zhao Weichen, Wu Shouyuan","doi":"10.1117/12.2679578","DOIUrl":"https://doi.org/10.1117/12.2679578","url":null,"abstract":"To solve the traditional water quality detection using ZigBee, GPRS, and other communication technologies having limited coverage distance, high power consumption, high cost, and complex deployment problems, according to the water quality testing real-time monitoring requirements, an NB-IoT-based water quality monitoring system platform is designed. The system uses the \"end-tube-cloud\" of the Internet of things mode, through the temperature, pH, dissolved oxygen, and other sensors to collect water quality parameters. M5310-A module will receive the sensor data uploaded to the OneNET cloud platform to achieve the remote transmission of water quality information and display functions, while the user can be in the application terminal real-time monitoring and directly read the water quality parameters of the measured waters. The system effectively improves the efficiency and modernization of water quality monitoring work, with good application prospects and economic benefits.","PeriodicalId":438484,"journal":{"name":"International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121743319","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}
The differential evolution algorithm is a random search algorithm. Aiming at the problems of premature convergence and slow optimization in differential evolution algorithm, a differential adaptive SA-DEPSO algorithm based on particle swarm optimization is proposed. First, the positioning problem is transformed into a function iteration optimization problem by using the least square method. Then the adaptive differential evolution strategy is fused on the basis of the particle swarm optimization algorithm. This algorithm can not only avoid the problem of premature convergence, but also improve the optimization speed and reduce the positioning error. Simulation analysis shows that when the number of iterations reaches 40, the algorithm in this paper reaches the optimal value and converges, saving the optimization time. Compared with DEPSO, SA-MCDE and literature 11, the average number of optimization runs is reduced by 75, 55 and 25 times; the average positioning error of the algorithm in this paper is reduced by 17.3%, 13.1% and 7.5% respectively.
{"title":"Differential adaptive SA-DEPSO algorithm based on particle swarm","authors":"Peng Duo, Zhao Xiaopeng, Li Suoping","doi":"10.1117/12.2679558","DOIUrl":"https://doi.org/10.1117/12.2679558","url":null,"abstract":"The differential evolution algorithm is a random search algorithm. Aiming at the problems of premature convergence and slow optimization in differential evolution algorithm, a differential adaptive SA-DEPSO algorithm based on particle swarm optimization is proposed. First, the positioning problem is transformed into a function iteration optimization problem by using the least square method. Then the adaptive differential evolution strategy is fused on the basis of the particle swarm optimization algorithm. This algorithm can not only avoid the problem of premature convergence, but also improve the optimization speed and reduce the positioning error. Simulation analysis shows that when the number of iterations reaches 40, the algorithm in this paper reaches the optimal value and converges, saving the optimization time. Compared with DEPSO, SA-MCDE and literature 11, the average number of optimization runs is reduced by 75, 55 and 25 times; the average positioning error of the algorithm in this paper is reduced by 17.3%, 13.1% and 7.5% respectively.","PeriodicalId":438484,"journal":{"name":"International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127288903","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}
In order to strengthen the promotion of model-based system engineering (MBSE) in the development and production of civil aircraft, this paper adopts model-based system engineering method based on MBSE to establish a functional architecture model of pressure control system based on SysML language to carry out architecture design and verification. In the early stage of system development, the correctness of functional logic and data flow is checked through the model, unexpected errors in the logic are identified, and missing interfaces for logic operation are captured. Realize early exposure of design problems, avoid downward transmission of design problems, reduce system design changes, improve work efficiency, and reduce costs.
{"title":"Model-based design and verification of functional architecture of civil aircraft pressure control system","authors":"He Yan, Tang Chao","doi":"10.1117/12.2679533","DOIUrl":"https://doi.org/10.1117/12.2679533","url":null,"abstract":"In order to strengthen the promotion of model-based system engineering (MBSE) in the development and production of civil aircraft, this paper adopts model-based system engineering method based on MBSE to establish a functional architecture model of pressure control system based on SysML language to carry out architecture design and verification. In the early stage of system development, the correctness of functional logic and data flow is checked through the model, unexpected errors in the logic are identified, and missing interfaces for logic operation are captured. Realize early exposure of design problems, avoid downward transmission of design problems, reduce system design changes, improve work efficiency, and reduce costs.","PeriodicalId":438484,"journal":{"name":"International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121488042","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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