Pub Date : 2023-03-27DOI: 10.1109/SmartIndustryCon57312.2023.10110787
R. Galin, Saniya B. Galina
The presented article considers the formation and engagement of a mixed heterogeneous team within a robotic system designed for completing collaborative tasks. A qualitative comparative analysis of approaches, methods and algorithms related to efficient task allocation in a collaborative robotic system by reducing the time and/or costs is carried out. A method and its corresponding algorithm for task allocation in a mixed heterogeneous team of a collaborative robotic system are presented. The proposed algorithm for task allocation with cost minimization is applicable for a mixed heterogeneous team consisting of humans and collaborative robots (i.e., heterogeneous groups of participants of various types). Thus, the within the problem statement the following is considered: different cost functions for different types of team members; limited robot activity; the dependence of the cost of robots for performing a certain type of work on the number of people. The developed method and algorithm of task allocation and work distribution within a CRS with minimizing the costs is applicable to a mixed heterogeneous team consisting of humans and cobots (groups of participants of different types), taking into account the specific heterogeneity of team members, as well as the mandatory requirements for safe interaction of participants within a CRS. The simulation of five scenarios of task allocation between the participants using the proposed solution is carried out. The results of the experiment showed the increased efficiency of a mixed heterogeneous team functioning.
{"title":"Approach to Efficient Task Allocation in a Collaborative Robotic System Using Modified Cost Functions","authors":"R. Galin, Saniya B. Galina","doi":"10.1109/SmartIndustryCon57312.2023.10110787","DOIUrl":"https://doi.org/10.1109/SmartIndustryCon57312.2023.10110787","url":null,"abstract":"The presented article considers the formation and engagement of a mixed heterogeneous team within a robotic system designed for completing collaborative tasks. A qualitative comparative analysis of approaches, methods and algorithms related to efficient task allocation in a collaborative robotic system by reducing the time and/or costs is carried out. A method and its corresponding algorithm for task allocation in a mixed heterogeneous team of a collaborative robotic system are presented. The proposed algorithm for task allocation with cost minimization is applicable for a mixed heterogeneous team consisting of humans and collaborative robots (i.e., heterogeneous groups of participants of various types). Thus, the within the problem statement the following is considered: different cost functions for different types of team members; limited robot activity; the dependence of the cost of robots for performing a certain type of work on the number of people. The developed method and algorithm of task allocation and work distribution within a CRS with minimizing the costs is applicable to a mixed heterogeneous team consisting of humans and cobots (groups of participants of different types), taking into account the specific heterogeneity of team members, as well as the mandatory requirements for safe interaction of participants within a CRS. The simulation of five scenarios of task allocation between the participants using the proposed solution is carried out. The results of the experiment showed the increased efficiency of a mixed heterogeneous team functioning.","PeriodicalId":157877,"journal":{"name":"2023 International Russian Smart Industry Conference (SmartIndustryCon)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127886779","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 : 2023-03-27DOI: 10.1109/SmartIndustryCon57312.2023.10110755
I. F. Yasinskiy, Tatyana V. Gvozdeva, V. Tyutikov
An important issue that arises before every person is the choice of a profession. It is obvious that the potential of success in different areas can be influenced both by the knowledge and skills acquired in the process of study, as well as the character traits of a person. The article proposes an intelligent predictive system that allows to assess the student's capabilities in the area of analytics. The topic relevance is explained by the need to increase the importance of connection between the employer and the university on the formation of knowledge, skills and abilities of the student that are in demand on the labor market. When designing the prognostic structure of the system, a hybrid intellectual approach is used that combines the advantages of known methods. It includes a neural network model and a method of accounting of arguments groups. The most demanded professions in the labor market have been identified. Professional skill maps are compiled, based on the description of the requirements. The training samples of are supplemented with images generated by the Monte Carlo method. Using data on the student's progress in selected key disciplines, as well as other available information, the system offers a numerical equivalent of the potential for the declared professions. Such recommendation allows the student to timely and consciously adjust the orientation in the educational process, which positively affects the competitiveness of the labor resources produced by the higher education institution.
{"title":"Combined Method of Cognitive Assessment of the Specialist Professional Potential","authors":"I. F. Yasinskiy, Tatyana V. Gvozdeva, V. Tyutikov","doi":"10.1109/SmartIndustryCon57312.2023.10110755","DOIUrl":"https://doi.org/10.1109/SmartIndustryCon57312.2023.10110755","url":null,"abstract":"An important issue that arises before every person is the choice of a profession. It is obvious that the potential of success in different areas can be influenced both by the knowledge and skills acquired in the process of study, as well as the character traits of a person. The article proposes an intelligent predictive system that allows to assess the student's capabilities in the area of analytics. The topic relevance is explained by the need to increase the importance of connection between the employer and the university on the formation of knowledge, skills and abilities of the student that are in demand on the labor market. When designing the prognostic structure of the system, a hybrid intellectual approach is used that combines the advantages of known methods. It includes a neural network model and a method of accounting of arguments groups. The most demanded professions in the labor market have been identified. Professional skill maps are compiled, based on the description of the requirements. The training samples of are supplemented with images generated by the Monte Carlo method. Using data on the student's progress in selected key disciplines, as well as other available information, the system offers a numerical equivalent of the potential for the declared professions. Such recommendation allows the student to timely and consciously adjust the orientation in the educational process, which positively affects the competitiveness of the labor resources produced by the higher education institution.","PeriodicalId":157877,"journal":{"name":"2023 International Russian Smart Industry Conference (SmartIndustryCon)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127200769","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 : 2023-03-27DOI: 10.1109/SmartIndustryCon57312.2023.10110836
S. Oskin, Zaur Hamedovich Naguchev, Dmitry Mikhailovich Taranov
Operation of electric drives in agroindustrial complex has confirmed the necessity of controlling the temperature condition of electric machines. Overheating of electric motor can occur due to its operation in a non-nominal mode, including the change of rotor speed. For adequate adjustment of electric motors temperature protection systems and maximum use of their overload capacity it is necessary to have mathematical models of states, taking into account real operating conditions and changes of operating mode. It is proposed to carry out such modeling in the Comsol software. Taking into account the previously obtained aerodynamic models, the model of thermal state of electric motor is implemented in this software. Patterns of thermal fields both outside the electric machine and inside were obtained. The simulation was carried out at different rotor speeds and taking into account the cooling air temperature. It was confirmed that the most heated part is the frontal part of stator windings. Results of simulation showed that the temperature of the most heated parts of the electric motor corresponded to the maximum permissible value for the given class of insulation. Thermal imaging of the electric motor has proved the adequacy of the simulation to the real values of the temperature of the outer shell of the electric machine. The experiment with built-in thermocouples in the most critical places of the electric motor has also proved the correspondence of temperature data to the data obtained during modeling.
{"title":"Investigation of the Temperature Condition of Electric Motors Using the Comsol Package","authors":"S. Oskin, Zaur Hamedovich Naguchev, Dmitry Mikhailovich Taranov","doi":"10.1109/SmartIndustryCon57312.2023.10110836","DOIUrl":"https://doi.org/10.1109/SmartIndustryCon57312.2023.10110836","url":null,"abstract":"Operation of electric drives in agroindustrial complex has confirmed the necessity of controlling the temperature condition of electric machines. Overheating of electric motor can occur due to its operation in a non-nominal mode, including the change of rotor speed. For adequate adjustment of electric motors temperature protection systems and maximum use of their overload capacity it is necessary to have mathematical models of states, taking into account real operating conditions and changes of operating mode. It is proposed to carry out such modeling in the Comsol software. Taking into account the previously obtained aerodynamic models, the model of thermal state of electric motor is implemented in this software. Patterns of thermal fields both outside the electric machine and inside were obtained. The simulation was carried out at different rotor speeds and taking into account the cooling air temperature. It was confirmed that the most heated part is the frontal part of stator windings. Results of simulation showed that the temperature of the most heated parts of the electric motor corresponded to the maximum permissible value for the given class of insulation. Thermal imaging of the electric motor has proved the adequacy of the simulation to the real values of the temperature of the outer shell of the electric machine. The experiment with built-in thermocouples in the most critical places of the electric motor has also proved the correspondence of temperature data to the data obtained during modeling.","PeriodicalId":157877,"journal":{"name":"2023 International Russian Smart Industry Conference (SmartIndustryCon)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125739774","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 : 2023-03-27DOI: 10.1109/SmartIndustryCon57312.2023.10110769
N. Smirnov, A. S. Trifonov
This paper deals with the task of text messages classification. The authors analyzed and reviewed the results of other researchers in this task and provided a brief overview of the machine learning and deep learning methods used in the study. The dataset of 1200 incoming messages of university admission campaign was used in the study. The authors pre-processed message texts, classified messages in three ways and applied three types of text vectorization. Based on machine learning and deep learning methods, the authors developed and applied multiclass and binary message classifiers. The paper presents classification metrics and confusion matrices for tasks of multiclass and multilabel classification. The models that provide the highest f1 score were selected as the best models.
{"title":"Classification of Incoming Messages of the University Admission Campaign","authors":"N. Smirnov, A. S. Trifonov","doi":"10.1109/SmartIndustryCon57312.2023.10110769","DOIUrl":"https://doi.org/10.1109/SmartIndustryCon57312.2023.10110769","url":null,"abstract":"This paper deals with the task of text messages classification. The authors analyzed and reviewed the results of other researchers in this task and provided a brief overview of the machine learning and deep learning methods used in the study. The dataset of 1200 incoming messages of university admission campaign was used in the study. The authors pre-processed message texts, classified messages in three ways and applied three types of text vectorization. Based on machine learning and deep learning methods, the authors developed and applied multiclass and binary message classifiers. The paper presents classification metrics and confusion matrices for tasks of multiclass and multilabel classification. The models that provide the highest f1 score were selected as the best models.","PeriodicalId":157877,"journal":{"name":"2023 International Russian Smart Industry Conference (SmartIndustryCon)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130320974","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 : 2023-03-27DOI: 10.1109/SmartIndustryCon57312.2023.10110817
V. A. Karapetyan, V. Miryanova
The article is devoted to the algorithm’s development for a multi-link redundant robot manipulator’s autonomous operation. A manipulator with seven degrees of freedom (DOF) is considered. It is well known that the inverse kinematics problem (IKP) plays an important role in planning the robotic manipulators’ movement. The multi-link robot manipulator’s IKP, unlike a direct task, requires more calculations and time due to the complex nonlinear equations’ presence. One of the actual solving the IKP methods is the particle swarm optimization algorithm. The proposed approach based on methods for solving the direct kinematics problem, which avoids complex calculations and the singularity problem.
{"title":"Solving the Inverse Kinematics Problem for a Seven-Link Robot-Manipulator by the Particle Swarm Optimization","authors":"V. A. Karapetyan, V. Miryanova","doi":"10.1109/SmartIndustryCon57312.2023.10110817","DOIUrl":"https://doi.org/10.1109/SmartIndustryCon57312.2023.10110817","url":null,"abstract":"The article is devoted to the algorithm’s development for a multi-link redundant robot manipulator’s autonomous operation. A manipulator with seven degrees of freedom (DOF) is considered. It is well known that the inverse kinematics problem (IKP) plays an important role in planning the robotic manipulators’ movement. The multi-link robot manipulator’s IKP, unlike a direct task, requires more calculations and time due to the complex nonlinear equations’ presence. One of the actual solving the IKP methods is the particle swarm optimization algorithm. The proposed approach based on methods for solving the direct kinematics problem, which avoids complex calculations and the singularity problem.","PeriodicalId":157877,"journal":{"name":"2023 International Russian Smart Industry Conference (SmartIndustryCon)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115052134","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 : 2023-03-27DOI: 10.1109/SmartIndustryCon57312.2023.10110824
A. Zotkina, A. Martyshkin
The article examines the analysis of the depressive state of social network users. It is noted that the VKontakte social network will be used as a social platform for collecting information in the study. It is noted that a combination of vocabulary-based and machine learning methods is used to achieve the highest accuracy. Two methods based on vocabulary are considered: the dictionary-based method and the corpus method. The stages of analysis are considered: collecting data obtained using the VK_API script creation module, preprocessing data through the natural language processing pipeline (deleting raw data that does not carry a semantic role), creating a model and evaluating it. It is noted that the implementation of this task uses a high-level Python programming language with dynamic strict typing and automatic memory management, the syntax of which contains a natural language processing module (NLTK). The paper presents 4 machine learning classifiers: support vector machine (SVM), k—nearest neighbor method (KNN), random forest, logistic regression, LSTM. It is revealed that machine learning algorithms such as decision tree, support vector machine, logistic regression and LSTM demonstrate good accuracy in detecting the depressive mood of a social network user. The LSTM network showed the greatest accuracy during this experiment. In conclusion, the main conclusions on the work done are formulated.
{"title":"Identification of a Depressive State Among Users of the Vkontakte Social Network","authors":"A. Zotkina, A. Martyshkin","doi":"10.1109/SmartIndustryCon57312.2023.10110824","DOIUrl":"https://doi.org/10.1109/SmartIndustryCon57312.2023.10110824","url":null,"abstract":"The article examines the analysis of the depressive state of social network users. It is noted that the VKontakte social network will be used as a social platform for collecting information in the study. It is noted that a combination of vocabulary-based and machine learning methods is used to achieve the highest accuracy. Two methods based on vocabulary are considered: the dictionary-based method and the corpus method. The stages of analysis are considered: collecting data obtained using the VK_API script creation module, preprocessing data through the natural language processing pipeline (deleting raw data that does not carry a semantic role), creating a model and evaluating it. It is noted that the implementation of this task uses a high-level Python programming language with dynamic strict typing and automatic memory management, the syntax of which contains a natural language processing module (NLTK). The paper presents 4 machine learning classifiers: support vector machine (SVM), k—nearest neighbor method (KNN), random forest, logistic regression, LSTM. It is revealed that machine learning algorithms such as decision tree, support vector machine, logistic regression and LSTM demonstrate good accuracy in detecting the depressive mood of a social network user. The LSTM network showed the greatest accuracy during this experiment. In conclusion, the main conclusions on the work done are formulated.","PeriodicalId":157877,"journal":{"name":"2023 International Russian Smart Industry Conference (SmartIndustryCon)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114686445","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 : 2023-03-27DOI: 10.1109/SmartIndustryCon57312.2023.10110814
G. Titova, M. Malsagov
Part of the Russian population lives in small settlements in remote areas in remote areas at long distances from each other and is not connected to centralized power systems. For the peasant farms of the Republic of Ingushetia, the issues of creating an autonomous power supply system in the highlands, independent of external circumstances, are relevant for the life and development of economic activity. microgeneration based on renewable energy sources for the trade of goods and services on the international market with a certificate of "green" energy makes the products of enterprises more competitive. The classification of microgenerating hybrid systems based on renewable energy sources is presented. Optimization of the internal structure of microgenerating hybrid systems by types and installed capacity for each type of equipment included in the autonomous electrical complex has been carried out. The problem of finding the value of objective functions for optimal combinations of equipment, taking into account the parameters of reliability and capital costs of an autonomous power supply system, is formulated. A parametric model and algorithm of an optimal microgenerating hybrid system based on renewable energy sources have been developed.
{"title":"Mathematical Model of a Micro Grid for a Hybrid Autonomous Station Based on Renewable Energy Sources for the Republic of Ingushetia","authors":"G. Titova, M. Malsagov","doi":"10.1109/SmartIndustryCon57312.2023.10110814","DOIUrl":"https://doi.org/10.1109/SmartIndustryCon57312.2023.10110814","url":null,"abstract":"Part of the Russian population lives in small settlements in remote areas in remote areas at long distances from each other and is not connected to centralized power systems. For the peasant farms of the Republic of Ingushetia, the issues of creating an autonomous power supply system in the highlands, independent of external circumstances, are relevant for the life and development of economic activity. microgeneration based on renewable energy sources for the trade of goods and services on the international market with a certificate of \"green\" energy makes the products of enterprises more competitive. The classification of microgenerating hybrid systems based on renewable energy sources is presented. Optimization of the internal structure of microgenerating hybrid systems by types and installed capacity for each type of equipment included in the autonomous electrical complex has been carried out. The problem of finding the value of objective functions for optimal combinations of equipment, taking into account the parameters of reliability and capital costs of an autonomous power supply system, is formulated. A parametric model and algorithm of an optimal microgenerating hybrid system based on renewable energy sources have been developed.","PeriodicalId":157877,"journal":{"name":"2023 International Russian Smart Industry Conference (SmartIndustryCon)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122840437","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}
Every year, biometric systems are becoming increasingly popular. This is facilitated by the successful application of biometrics in various areas of human life. In particular, forensics (it was the first and most important area of fingerprinting, and remains so until now), locks and safes equipped with a scanner, encryption devices in computers and mobile devices, payment for purchases in stores, and so on. This article tells about the need to ensure the security of personal data, the growing popularity of the collection and processing of biometric personal data, its advantages and disadvantages, analyzed the characteristic features of biometric identification and authentication, explored the market for bio-metric products, examined the problems of biometric protection in face geometry and fingerprints. Since one of the most popular and widely practiced biometric systems is fingerprints, the practical part of the work was to create a fingerprint cast to bypass the blocking of any device using this type of biometric identification. Also, the need for using a thermogram for biometric authentication is identified and substantiated in the article. Based on the study, the authors put forward a number of recommendations to improve the reliability of personal data security and eliminate biometric authentication vulnerabilities by fingerprint and face image.
{"title":"Vulnerability of Biometric Protection","authors":"Kuzmina Yliana, Azovtseva Arina, Perminova Anastasia","doi":"10.1109/SmartIndustryCon57312.2023.10110772","DOIUrl":"https://doi.org/10.1109/SmartIndustryCon57312.2023.10110772","url":null,"abstract":"Every year, biometric systems are becoming increasingly popular. This is facilitated by the successful application of biometrics in various areas of human life. In particular, forensics (it was the first and most important area of fingerprinting, and remains so until now), locks and safes equipped with a scanner, encryption devices in computers and mobile devices, payment for purchases in stores, and so on. This article tells about the need to ensure the security of personal data, the growing popularity of the collection and processing of biometric personal data, its advantages and disadvantages, analyzed the characteristic features of biometric identification and authentication, explored the market for bio-metric products, examined the problems of biometric protection in face geometry and fingerprints. Since one of the most popular and widely practiced biometric systems is fingerprints, the practical part of the work was to create a fingerprint cast to bypass the blocking of any device using this type of biometric identification. Also, the need for using a thermogram for biometric authentication is identified and substantiated in the article. Based on the study, the authors put forward a number of recommendations to improve the reliability of personal data security and eliminate biometric authentication vulnerabilities by fingerprint and face image.","PeriodicalId":157877,"journal":{"name":"2023 International Russian Smart Industry Conference (SmartIndustryCon)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125389547","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 : 2023-03-27DOI: 10.1109/SmartIndustryCon57312.2023.10110775
E. Rusyaeva, Aleksandr Poltavsky, G. Akhobadze
An integrative approach is presented as a particular dialectical method for building information-analytical and expert systems (IAS, ES). This method is based on the complex use of expert assessments and automated analysis of text objects. The fundamental basis of the method was the classical entropy analysis of sign systems of information theory in combination with modern elements of digital and cognitive expert linguistic analytics. The method is relevant for the formation of information and analytical projects and a formalized model of linguistic analysis of texts.
{"title":"Integrative Approach to Creation of Information Systems and Entropy Analysis of Linguistic Information","authors":"E. Rusyaeva, Aleksandr Poltavsky, G. Akhobadze","doi":"10.1109/SmartIndustryCon57312.2023.10110775","DOIUrl":"https://doi.org/10.1109/SmartIndustryCon57312.2023.10110775","url":null,"abstract":"An integrative approach is presented as a particular dialectical method for building information-analytical and expert systems (IAS, ES). This method is based on the complex use of expert assessments and automated analysis of text objects. The fundamental basis of the method was the classical entropy analysis of sign systems of information theory in combination with modern elements of digital and cognitive expert linguistic analytics. The method is relevant for the formation of information and analytical projects and a formalized model of linguistic analysis of texts.","PeriodicalId":157877,"journal":{"name":"2023 International Russian Smart Industry Conference (SmartIndustryCon)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130434779","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 : 2023-03-27DOI: 10.1109/SmartIndustryCon57312.2023.10110766
Elena Jharko, K. Chernyshov
Industries, especially in the energy sector, are using digital twins to improve work efficiency and optimize operating modes. Digital twins have based on models that accurately describe the geometry, physical properties, behavior, and rules that characterize an object. The article presents an example of functional decentralization of digital twin models as a decomposition of an NPP power unit (PU) with a VVER-1000 reactor as a control object into a set of technological subsystems of functional groups. Approaches to the digital twins’ creation of NPP PU and the main directions for using digital twins based on dynamic models of a PU in advanced control systems for NPP power units are presented. Within the framework of the intelligent operator support system, a "three-stage" approach to the problem of forecasting the state of the NPP PU, based on digital twins, and the principles of forming the PU optimal control are proposed. The proposed approaches to creating digital twins are used to create intelligent support systems for operators.
{"title":"Digital Twins: Forecasting and Formation of Optimal Control Programs for NPP Power Units","authors":"Elena Jharko, K. Chernyshov","doi":"10.1109/SmartIndustryCon57312.2023.10110766","DOIUrl":"https://doi.org/10.1109/SmartIndustryCon57312.2023.10110766","url":null,"abstract":"Industries, especially in the energy sector, are using digital twins to improve work efficiency and optimize operating modes. Digital twins have based on models that accurately describe the geometry, physical properties, behavior, and rules that characterize an object. The article presents an example of functional decentralization of digital twin models as a decomposition of an NPP power unit (PU) with a VVER-1000 reactor as a control object into a set of technological subsystems of functional groups. Approaches to the digital twins’ creation of NPP PU and the main directions for using digital twins based on dynamic models of a PU in advanced control systems for NPP power units are presented. Within the framework of the intelligent operator support system, a \"three-stage\" approach to the problem of forecasting the state of the NPP PU, based on digital twins, and the principles of forming the PU optimal control are proposed. The proposed approaches to creating digital twins are used to create intelligent support systems for operators.","PeriodicalId":157877,"journal":{"name":"2023 International Russian Smart Industry Conference (SmartIndustryCon)","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122939810","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：