|Leading Engineer, Scientific Department, Branch of the National Research University “MPEI” in Smolensk|
Rubrication of text information based on the voting of intellectual classifiers
The practical implementation of the concept of electronic government is one of the priorities of Russian state policy. The organization of effective interaction between authorities and citizens is an important element of this concept. In addition to providing public services, it should include the processing of electronic appeals (applications, complaints, suggestions, etc.). Research has shown that the speed and efficiency of appeal processing largely depend on the quality of determining the thematic rubric, i.e. solving the rubrication task. The analysis of citizens' appeals received by the e-mail and official websites of public authorities has revealed several specific features (small size, errors in the text, free presentation style, description of several problems) that do not allow the successful application of traditional approaches to their rubrication. To solve this problem, it has been proposed to use various methods of intellectual analysis of unstructured text data (in particular, fuzzy logical algorithms, fuzzy decision trees, fuzzy pyramidal networks, neuro-fuzzy classifi convolutional and recurrent neural networks). The article describes the conditions of the applicability of six intellectual classifiers proposed for rubricating the electronic citizens’ appeals. They are based on such factors as the size of the document, the degree of intersection of thematic rubrics, the dynamics of their thesauruses, and the amount of accumulated statistical information. For a situation where a specific model cannot make an unambiguous choice of a thematic rubric, it is proposed to use the classifier voting method, which can significantly reduce the probability of rubrication errors based on the weighted aggregation of solutions obtained by several models selected using fuzzy inference. Read more...
Creation of a chemical-technological system digital twin using the Python language
Currently, when modeling complex technological processes in cyber-physical systems, procedures for creating so-called "digital twins" (DT) have become widespread. DT are virtual copies of real objects which reflect their main properties at various stages of the life cycle. The use of digital twins allows real-time monitoring of the current state of the simulated system, and also provides additional opportunities for engineering and deeper customization of its components to improve the quality of products. The development of the "digital twin" technology is facilitated by the ongoing Fourth Industrial Revolution, which is characterized by the massive introduction of cyber-physical systems into production process. These systems are based on the use of the latest technologies for data processing and presentation and have a complex structure of information chain between its components. When creating digital twins of such systems elements, it is advisable to use programming languages, that allow visualization of simulated processes and provide a convenient and developed apparatus for working with complex mathematical dependencies. The Python programming language has similar characteristics. In the article, as an example of a cyber- physical system, a chemical-technological system based on a horizontal-grate machine is considered. This system is designed to implement the process of producing pellets from the apatite-nepheline ore mining wastes. The article describes various aspects of creating a digital twin of its elements that carry out the chemical-technological drying process in relation to a single pellet. The digital twin is implemented using the Python 3.7.5 programming language and provides the visualization of the process in the form of a three-dimensional interactive model. Visualization is done using the VPython library. The description of the digital twin software operation algorithm is given, as well as the type of the information system interface, the input and output information type, the results of modeling the investigated chemical-technological process. It is shown that the developed digital twin can be used in three versions: independently (Digital Twin Prototype), as an instance of a digital twin (Digital Twin Instance), and also as part of a digital twins set (Digital Twin Aggregate). Read more...
Tools for automated collection and analysis of sociological information on the territorial identity of city residents
The paper proposes an algorithm for automated search and initial analysis of sociological information aimed at studying the territorial identity of city area residents using Internet sources. Communities of social networks, e.g. VKontakte, are considered as the main data source, and websites of topographic objects found in the territories under study are used as auxiliary information sources. It is demonstrated that, in terms of information support, public pages and groups with open or restricted access walls have the greatest potential. The developed algorithm implies selecting relevant groups, finding content concerning area issues, and determining the indices of community activity in discussing territorial problems. The required information is retrieved through the interaction with a social network server with the use of the official Application Programming Interface (API). To identify communities and posts, it is proposed to apply methods of morphological analysis of textual information. The software implementation of the algorithm is described in Python 3.8.5, including original functions for the acquisition of data on communities by their identification numbers, for the formation of a set of urbanonyms for a specified area, and some other ones. The developed program has been used to analyze territorial groups in three areas of Moscow; the results of the analysis enable us to estimate the degree of the territorial identity of their residents. The analysis of the error in the results of automated data collection and processing shows good agreement of these results with manually obtained ones, i.e. the error is 2.6% in the identification of relevant groups and about 3% in the identification of posts on area issues. Therewith, a much higher speed of response and lower labor effort required to perform routine operations allow the algorithm and the implementing computer program to be viewed as an effective tool for sociological research based on data from social networks. Read more...
A computer program for electromechanical system operational diagnostics based on the topological approach
The paper presents a method, a mathematical model, and a computer program for the operational diagnostics of an electromechanical system (EMS). During EMS operation, service aging changes the properties of the parametric matrices of the windings and, as a consequence, the characteristics of the EMS vector space. Periodic testing of the vector space offers relevant and reliable data on the current health of the EMS, its changes during operation, and the risk of loss of function. The object of the study is an asynchronous electric motor (AEM). It is urgent to automate the process of assessing the current health of an AEM and to organize the storage of information on its states at different stages of its life cycle. To solve the problem, software (SW) for accumulation of information on AEM operation and for evaluation of its basic performance metrics has been developed in the Python programming language. The SW is based on the topological approach to diagnostics, which implies the analysis of the current responses of motor rotor windings to phase voltage pulses. The SW enables one to determine the rate of the service aging of an item, the probability of its survival and residual life, to obtain access to the history of previous diagnostics, and to visualize the in-service history of the above-mentioned performance metrics. The developed SW can be used to increase the AEM operation efficiency and to plan engineering or repair work; it can also be used as an information source for re- engineering and modification of existing AEMs. The described SW can be extended to perform operational diagnostics based on the topological approach of devices of various types. Also, this SW can be considered as a separate information component of the digital twin of a complex EMS, which will allow us to study the main indicators of its reliability, fault tolerance and operational efficiency at all stages of the life cycle. Read more...
Computer program for modeling of technical state indicators of electromechanical systems
The article is aimed at solving the problem of scientific justification of criteria and methods for assessing the technical state of electromechanical systems based on the topological diagnostic method. Mathematical model and computer program for simulation of technical state indices of asynchronous electric motors (AEM) are presented. Functions and Green matrices, as well as deviation matrices, are considered as such indicators. The basis of the program is the mathematical model of the AEM with a non-accelerated rotor and non-homogeneous windings. AEM is supplied from pulse voltage source. The action is carried out in different directions of the vector space of the motor in order to determine its characteristics and degree of homogeneity. Based on the reactions of the object, the program calculates and analyzes technical indicators for intact and damaged states of the AEM. A computer program for mathematical modeling of the technical state indicators of the AEM was carried out using the Maple package of symbolic and numerical calculations, which provides extensive opportunities for mathematical studies of various levels. A description of a software implementation of the proposed mathematical model is given. An example of using a program to model the performance of a serial motor with specified technical characteristics is given. The article presents the results of modeling the object indicators corresponding to the object different operational states. A reference state, a damaged state characterized by a change in the properties of the vector space during long-term operation, as well as a limit state, which corresponds to a break in one of the phases of the rotor winding, were defined as these states. Conclusions on each of the given electric motor states are given. Read more...
Solving the inverse kinematics problem for sequential robot manipulators based on fuzzy numerical methods
Nowadays the introduction of robotic systems is one of the most common forms of the technological operations automation in various spheres of human activity. Among the robotic systems a special place is occupied by sequential multi-link robotic manipulators (SRM). SRM have become widespread due to relatively small dimensions and high maneuverability, which makes their use indispensable to solve various tasks. In practice, the effectiveness of the functioning of the SRM can be influenced by various types of external environment fuzzy factors. Among the external factors there is a group affecting the ability to determine the exact target position. Such factors often affect technical vision systems. This problem is especially relevant for special purpose mobile robots operating in aggressive environmental conditions. A situation similar to the described one also occurs when a medical robot manipulator is used for minimally invasive surgery, when the role of the control and monitoring system is assumed by an operator. In this regard, the organization of effective control taking into account influence of the external fuzzy factors, that prevent the correct recognition of the target position of the SRM instrument, is an urgent problem. The authors consider the solution of the inverse kinematics problem for SRM based on the use of fuzzy numerical methods, taking into account the possible occurrence of singular configurations in the process of solving. Read more...
Neural network analysis method of heat treatment processes of pelletized phosphate ore raw materials
Currently, there is an acute problem of waste disposal of mining and processing plants, which accumulate in significant volumes in the territories adjacent to them and pose a serious threat to the environment. In this regard, the creation of technological systems for processing ore waste and the improvement of their information support represent an urgent area of research. An example of such a system is a complex chemical and energy technology system for the production of yellow phosphorus from waste apatite-nepheline ores. The purpose of the study was to develop a model for collecting data on the parameters of the processes of heat treatment of pelletized phosphate ore raw materials in such a system, as well as a method for identifying dependencies between these parameters. The identification of dependencies in the information support of the yellow phosphorus production system will improve the quality of its functioning in terms of management criteria, energy and resource efficiency. To achieve this goal, the tasks of choosing a mathematical concept for the basis of the method being developed, constructing an algorithm and creating software implementing this method, conducting model experiments were solved. The method is based on the use of deep recurrent neural networks of long-term short-term memory, which have a high generalizing ability and are used in solving problems of regression and classification of multidimensional time sequences, in the form of which, as a rule, the parameters of a chemical and energy technology system are presented. The method is implemented as an application created in the MatLab 2021 environment. The application interface allows you to interactively conduct experiments with various sets of input and output parameters to identify the relationship between them, as well as change the hyperparameters of neural networks. As a result of the application, a repository of trained neural networks is created that simulate the relationships found between the specified parameters of the technological system and can be applied in decision support systems, management and engineering. Read more...
An intelligent model for managing the risks of violation of the characteristics of electromechanical devices in a multi-stage system for processing ore raw materials
The results of studies on the development of the structure of an intelligent model for managing the risks of violation of the characteristics of electromechanical devices in a multi-stage system for processing ore raw materials are presented. Such devices are involved in all cycles of the technological process, so the assessment of this risk for them is an urgent task. A method for assessing such risks is proposed, which is based on the assessment of the useful life of equipment, performed on the basis of the prediction of characteristics by a deep recurrent neural network, with further generalization of the results of such an assessment in a fuzzy inference block. Recurrent neural networks with long short-term memory were used, which are one of the most powerful tools for solving time series regression problems, including predicting their values for long intervals. The use of deep neural networks to predict the characteristics of electromechanical devices made it possible to obtain a high prediction accuracy, which made it possible to apply a relatively less accurate recurrent least squares method for the iterative process of estimating the useful life of equipment. This approach made it possible to build a computational evaluation process with its constant refinement as new results of measurements of the characteristics of electromechanical devices become available. The results of a model experiment with a software implementation of the proposed method, performed in the MatLab 2021a environment, are presented, which showed the consistency of the program modules and obtaining a risk assessment result that is consistent with the expected dynamics of its change. Read more...