Operation Control System Research Articles

Study of the internal environment quality monitoring system for a laboratory model of a mining separator at key sensitive points of operation and process control using artificial intelligence

Modeling the quality of the indoor environment in buildings using neural networks, as an element supporting automatic process control, has become extremely popular nowadays. By analogy, attempts are being made to use the experience gained in construction and implement it in industry. The publication proposes a method of modeling feedforward neural networks, thanks to which it is possible to obtain the most efficient network with one hidden layer in terms of the given quality criterion. This network was implemented in the control system of the mining separator operation as part of pilot studies. The research included testing a laboratory model of the separator placed in a sea container modified for the separator function, in which modern automation technologies and monitoring of environmental parameters were integrated. Among others, time, outside temperature, set temperature, temperature error and controller output were measured. The measurements were taken at the points of installation of devices sensitive to the working environment - controllers, I/O modules, X-ray (XRT-DE) and optical analysis (VIS-NIR), enabling precise examination of the composition and quality of mineral resources. The internal environmental conditions in the housings of the above-mentioned sensitive elements and in the server room were the basis for the analysis. The aim was to develop a performance model enabling effective improvement of the working environment of all electrical and mechanical devices affecting energy efficiency and the internal environment. Separators operate in a very diverse environment, such as: tropical forests, Canadian Tundra, or desert areas in Africa, as well as EU countries, the USA and Australia. These devices are used in both open pit and underground mines. The use of modern technologies and mobile solutions in the mining industry contributes to increased efficiency, operational safety and, consequently, minimizing the negative impact on the environment. The research results confirmed that precise monitoring and control to ensure environmental conditions at selected separator points is crucial to ensuring the continuity and quality of the separation process.

Spindle Bearing Preload Control Using NI MyRIO

The article presents an application for controlling the preload of bearings in a model spindle system. The bearing preload will be implemented using piezoelectric elements, which allow for changing the preload of bearings during spindle operation, which results in a change in the stiffness of the entire system. Such a change in stiffness allows for effective reduction of the vibration amplitudes of the spindle tip. The use of the MyRIO 1900 device from National Instruments, which was programmed using LabVIEW 2021 SP1 (32 bit), is described in detail. The effectiveness of the control algorithm was confirmed on the basis of actual measurements of the vibration amplitude of the front spindle tip on which three different substitute masses (model grinding wheels) were placed. The values for the system without and with the operating control system were compared. The results were recorded five times for each state of the device and each substitute mass. The value of the maximum amplitude was taken into account after averaging it from all five tests without control and with control. The effectiveness of the control algorithm was the greater the heavier the substitute mass, which allowed for reducing the vibration amplitude by up to 20%.

Human Operator Mental Fatigue Assessment Based on Video: ML-Driven Approach and Its Application to HFAVD Dataset

The detection of the human mental fatigue state holds immense significance due to its direct impact on work efficiency, specifically in system operation control. Numerous approaches have been proposed to address the challenge of fatigue detection, aiming to identify signs of fatigue and alert the individual. This paper introduces an approach to human mental fatigue assessment based on the application of machine learning techniques to the video of a working operator. For validation purposes, the approach was applied to a dataset, “Human Fatigue Assessment Based on Video Data” (HFAVD) integrating video data with features computed by using our computer vision deep learning models. The incorporated features encompass head movements represented by Euler angles (roll, pitch, and yaw), vital signs (blood pressure, heart rate, oxygen saturation, and respiratory rate), and eye and mouth states (blinking and yawning). The integration of these features eliminates the need for the manual calculation or detection of these parameters, and it obviates the requirement for sensors and external devices, which are commonly employed in existing datasets. The main objective of our work is to advance research in fatigue detection, particularly in work and academic settings. For this reason, we conducted a series of experiments by utilizing machine learning techniques to analyze the dataset and assess the fatigue state based on the features predicted by our models. The results reveal that the random forest technique consistently achieved the highest accuracy and F1-score across all experiments, predominantly exceeding 90%. These findings suggest that random forest is a highly promising technique for this task and prove the strong connection and association among the predicted features used to annotate the videos and the state of fatigue.

Human Resource Management in Complex Environments: A Viable Model Based on Systems Thinking

Developing the company’s capacity to deal with changing environments means ceasing to see processes as a traditional and linear model. Therefore, the objective of this research is to apply VSM to HRM to show its complexity. It is qualitative research, which is carried out in two moments. The first consists of a literature review in the WoS, and the second, is the design of the model “MV-HRM”, based on the approach of complex adaptive systems, viable system model, soft system methodology, and holistic theory. The MV-HRM consists of five systems: (S1) HRM processes, (S2) information system (S4) operational control, (S4) strategic planning and (S5) governance. The model emphasizes the relationships and interactions it has with its immediate and future environment. Finally, the contribution of the research is to show another look and understanding of the functioning of HRM, in addition to awakening the interest of strategists to develop best practices that allow them to respond in an agile way to the dynamic and complex environment.

Project Report: Thermal Performance of FIRSTLIFE House

The paper deals with selected thermal properties of a small building that was built during the international student competition Solar Decathlon 2021/2022 and is now part of the Living Lab in Wuppertal. It summarizes the essential information about the overall design of this wooden building with construction and technologies corresponding to the passive building standard. Built-in sensors and other equipment enable long-term monitoring of thermal parameters. Part of the information comes from the building operation control system. The thermal transmittance value for the perimeter wall matches calculated expectation well, even from a short period of time and not at an achievable perfectly steady state boundary condition. The (positive) difference between the calculated values and the measured ones did not exceed 0.015 W/(m2K). It was proven that even for such a small building with a very small heat demand, the heat transfer coefficient can be estimated alternatively from a co-heating test (measured electricity power for a fan heater) and from energy delivered to underfloor heating (calorimeter in heating system). Differences among both measurement types and calculation matched in the range ± 10%. In the last section, the dynamic response test is briefly described. The measured indoor air temperature curves under periodic dynamic loads (use of fan heater) are compared with the simulation results. The simulation model working with lumped parameters for each element of the building envelope was able to replicate the measured situation well, while its use does not require special knowledge of the user. In the studied case, the differences between measured and simulated air temperatures were less than 1 Kelvin if the first two to three days of the test period are ignored due to large thermal inertia. Finally, the measurement campaign program for the next period is outlined.

OCTOPUS: operation control system for task optimization and job parallelization via a user-optimal scheduler

The material acceleration platform, empowered by robotics and artificial intelligence, is a transformative approach for expediting material discovery processes across diverse domains. However, the development of an operating system for material acceleration platform faces challenges in simultaneously managing diverse experiments from multiple users. Specifically, when it is utilized by multiple users, the overlapping challenges of experimental modules or devices can lead to inefficiencies in both resource utilization and safety hazards. To overcome these challenges, we present an operation control system for material acceleration platform, namely, OCTOPUS, which is an acronym for operation control system for task optimization and job parallelization via a user-optimal scheduler. OCTOPUS streamlines experiment scheduling and optimizes resource utilization through integrating its interface node, master node and module nodes. Leveraging process modularization and a network protocol, OCTOPUS ensures the homogeneity, scalability, safety and versatility of the platform. In addition, OCTOPUS embodies a user-optimal scheduler. Job parallelization and task optimization techniques mitigate delays and safety hazards within realistic operational environments, while the closed-packing schedule algorithm efficiently executes multiple jobs with minimal resource waste. Copilot of OCTOPUS is developed to promote the reusability of OCTOPUS for potential users with their own sets of lab resources, which substantially simplifies the process of code generation and customization through GPT recommendations and client feedback. This work offers a solution to the challenges encountered within the platform accessed by multiple users, and thereby will facilitate its widespread adoption in material development processes.

Resilient energy management of a multi-energy building under low-temperature district heating: A deep reinforcement learning approach

The corrective control of a building-level multi-energy system (MES) for emergency load shedding is essential to optimize the operating cost after contingency. For a Danish case, the heating devices in the building are connected to a developing low-temperature district heating (LTDH) system and operated under a heat market. Due to the coupling between the electrical power and heating system, an electricity outage can be propagated to the heating network, and heat prices as well as tariffs can impact the MES operating cost. In the previous studies, only electrical load shedding is modeled, while the impact of electricity outages on heating system operation and heat load control is ignored. On the other hand, the problem is traditionally solved by model-based optimization methods which are highly nonconvex leading to high computing complexity. Moreover, operating uncertainties can lead to infeasible solutions. To address these challenges, this paper proposes a deep reinforcement learning-based corrective control method for the resilient energy management of a building-level MES. In the method, the proximal policy optimization algorithm is applied, where multiple uncertainties, system dynamics, and operating constraints are considered. A case study of a real-life residential building connected to the LTDH system in Denmark is carried out, where electricity outages are simulated. The results verify the performance of the proposed method in achieving resilient energy management of the MES.

Computing Unit and Data Migration Strategy under Limited Resources: Taking Train Operation Control System as an Example

There are conflicts between the increasingly complex operational requirements and the slow rate of system platform upgrading, especially in the industry of railway transit-signaling systems. We attempted to address this problem by establishing a model for migrating computing units and data under resource-constrained conditions in this paper. By decomposing and reallocating application functions, optimizing the use of CPU, memory, and network bandwidth, a hierarchical structure of computing units is proposed. The architecture divides the system into layers and components to facilitate resource management. Then, a migration strategy is proposed, which mainly focuses on moving components and data from less critical paths to critical paths and ultimately optimizing the utilization of computing resources. Specifically, the test results suggest that the method can reduce the overall CPU utilization by 27%, memory usage by 6.8%, and network bandwidth occupation by 35%. The practical value of this study lies in providing a theoretical model and implementation method for optimizing resource allocation in scenarios where there is a gap between resource and computing requirements in fixed-resource service architectures. The strategy is compatible for distributed computing architectures and cloud/cloud–edge-computing architectures.

Different nitrogen conditions regulating extracellular polymeric substances and erosion resistance of sewer sediment: Mechanism of microbial metabolism and molecular response

Nitrogen biotransformation plays a vital role in the metabolism of microbial communities in sewers. Extracellular polymeric substances (EPS) secreted by microbial communities can form gel-like sewer sediments, causing clogging of the sewer. However, knowledge on the effects of varying nitrogen conditions on the erosion resistance of sewer sediments and EPS produced by sewer microorganisms is limited. In this study, two typical organic/inorganic nitrogen ratios of sewage were reproduced in simulated sewer reactors, i.e., 3/7 (R1 group) and 7/3 (R2 group). Higher organic nitrogen (ON) concentrations were found to increase the critical erosion shear stress by 26.43%; this was ascribed to increased particle diameter, weakened electrostatic repulsion of sediments and stimulated EPS secretion in the R2 group. The protein and polysaccharide contents of the R2 group were 48.84% and 34.25% higher than those of the R1 group, respectively, which was supported by increased gene abundances for aromatic amino acid synthesis, general secretory pathways of protein, and synthesis of precursors and polysaccharides. Tightly-bound EPS in R2 group exhibited increased contents of hydrophobic protein secondary structures and intermolecular hydrogen bonds, thereby promoting the formation of gel-like sediment structures with enhanced erosion resistance. However, the microbial diversity and the abundance of key genes involved in EPS generation and secretion (e.g., tyrB, yajC, secB, gumF, and gumH) obviously decreased in the R1 group. Moreover, high ON concentrations increased microbial diversity and enhanced microbial glycolysis, tricarboxylic acid cycle and ammonium assimilation. This study reveals the formation mechanisms of EPS in sewer sediments under different nitrogen conditions and their effects on sediment erosion resistance, which contributed to improved sewer system operation and sewer sediment control.

МЕСТО И ЗНАЧЕНИЕ ОПЕРАТИВНО-РОЗЫСКНОГО КОНТРОЛЯ ОРГАНОВ ВНУТРЕННИХ ДЕЛ ЗА ЛИЦАМИ, СКЛОННЫМИ К СОВЕРШЕНИЮ ПРЕСТУПЛЕНИЙ, В ГОСУДАРСТВЕННОЙ СИСТЕМЕ ПРОФИЛАКТИКИ ПРАВОНАРУШЕНИЙ

The article deals with topical issues of the activities of the operational units of the internal affairs bod-ies for the control of persons prone to commit crimes in modern Russia. A brief retrospective analysis of the doctrinal foundations of the formation of the operational investigative control system is car-ried out the relevant conclusions are projected onto the current realities caused by the aggravation of the foreign policy situation and the conduct of a special military operation. The author's vision of the classification of persons in need of operational investigative control with varying degrees of involve-ment of special forces, means and methods, depending on the level of potential public danger of objects, is outlined and reasoned. The author has formulated a theoretical and legal model of the system of operational investigative control over persons prone to committing crimes, with the definition of its subjects, objects, goals and objectives of this area of operational investigative provision of crime prevention.

Management and Operator Control System based on Microservice Architecture and Application on the HIPr Accelerator

The paper describes the basic principles of developing a distributed control system (DCS) and a GARNET operator control system based on a microservice architecture as part of a high-availability cluster. The application of the operator’s control system as a DCS component is described. The main elements of software components of operator control and DCS are presented and described. The process of conveyor assembly and publication of software tools into a working product environment, which implements the principle of continuous integration, is described. The mechanism of interaction of key components among themselves is presented. The mechanism for hosting management services using the Docker containerization system and Kubernetes container orchestration is demonstrated. Examples of services for interaction with users in the environment of the GARNET operator control system being developed, separation of users by roles and access rights, integration of the data visualization service using Grafana are shown. The vector of further development of DCS and operator control tools is described, in particular, the possibility of using the practice of developing user web interfaces using the micro frontend approach. The components and results of the operation of a prototype system designed to interact with the measurement infrastructure of the linear heavy ion accelerator HIPR are presented.

Study on the Operation Optimization of Medium-Depth U-Type Ground Source Heat Pump Systems

Deep geothermal energy is a sustainable and renewable spacing heating source. Although many studies have discussed the design optimization of deep borehole systems, few have accomplished optimization and in-depth analysis of system operation control. In this study, an analytical model of the U-type deep borehole heat exchanger is proposed, and the average relative error between the simulated outlet temperatures and experimental data is −3.2%. Then, this paper presents an integrated model for the operation optimization study of the U-type deep-borehole ground source heat pump system. The optimal control of flow rate is adopted to match the variation in heating load. Compared with the constant-flow rate (110 m3/h) operation mode, the variable flow rate method reduces the power consumption of the heat pump and circulating pump by 22.1%, from 288,423 kW·h to 224,592 kW·h, during 2112 h of operation. In addition, the system has a larger RHS and COP when the thermal conductivity of the backfill material increases. When the borehole depth increases by 200 m from 2300 m, the energy consumption of the circulating pump will drop from 85,844 kW·h to 56,548 kW·h. The COP of the heat pump unit will decrease approximately linearly as the heating load increases, and the total power consumption will increase accordingly. This work can provide guidance for the design and optimization of U-shaped GSHP systems.

Configuration method for medium-deep ground source heat pump system considering renewable energy consumption and smart grid interaction

Medium-deep ground source heat pump (GSHP) systems have the advantages of low carbon, high heat exchange intensity, good thermal storage capacity, and intermittent operation characteristics, which are conducive to renewable energy consumption and grid demand response. The source-side parameters affect the configuration of underground borehole engineering, heat pump units, and other equipment. However, current research mainly focuses on the underground heat exchanger modeling, underground heat exchange, and system operation control, while there are few studies on multi-factor ground source-side parameter design and optimal configuration. In this study, the indicator analyzing the unsteady features and thermal balance state of medium-deep geothermal resources was introduced, and the source-side water temperatures were optimized based on the dynamic characteristics of the geothermal and building sides. A simulation configuration methodology for the source-side flow rate and storage capacity was developed considering the electricity prices, life-cycle cost (LCC), and grid interaction. The optimization of the ground source-side design temperature, flow rate, and capacity parameters of residential and office building heating scenarios were analyzed in northern China, respectively. The results showed that the borehole inlet and outlet temperature can be designed to 5.5 °C/17.5 °C under the annual sustainable state, and the optimal flowrate can be set to 65.77 m3/h, to achieve the lowest cost and highest heating season guarantee rate for the residential scenario. For the office building with optimal system and storage capacity, the average annual LCC is 192,000 yuan/year, with the cumulative peak shaving of 55.8 %, and an increase of 103.3MWh renewable electricity consumption.

Development and implementation of technological measures to extend the campaign of blast furnace No. 5 of PJSC Severstal

The work presents generalized experience in the development and implementation at PJSC Severstal of technological measures to extend the campaign of blast furnace No. 5. The authors carried out an analysis, identified and described the problem areas, generalized the principles for ensuring the safety of the shaft lining, boshes and metal receiver of the blast furnace. The results of a study of the working space of blast furnace No. 5 in 2006 are also presented. The identified technological factors ensure an increase in duration of the unit campaign. Technolo­gical measures are given for: washing the blast furnace hearth, reducing chemical erosion of the carbon blocks of the hearth and flange, forming a protective skull in the blast furnace shaft, special methods for loading solid coke substitutes, and organizing an effective structure of the charge column in the blast furnace. It is necessary to use digital models integrated into the blast furnace expert system for operational control of blast furnace technology. The results of the current blast furnace campaign were compared with previous ones. It was proven that the systematic use of all elements of the developed technology makes it possible to achieve high economic indicators while exceeding the standard duration of the campaign by 1.75 times. Experience in technology development made it possible to increase the furnace campaign duration to 17.46 years, achieve a reduction in specific coke consumption by 15.9 %, and increase the specific consumption of natural gas for cast iron smelting by 46.4 %; reduce the specific carbon consumption for cast iron smelting by 6.3 %.

Adaptive Approach as a Tool of Library Management in the Conditions of Turbulent External Environment

The purpose of the article is to define the role, place and possibilities of the adaptive approach in library management within the framework of practical implementation of the concept of sustainable innovative development of the library industry; to study the reasons for applying adaptive management methods in libraries. Research methods. The following methods and approaches were used: general scientific methods of cognition, in particular, analysis and synthesis, abstract and logical, monographic and analytical, decomposition and systematic approach. Using these methods ensured the validity of the provisions of this study. The scientific novelty lies in creating a holistic view of the features, trends and factors of the adaptive approach in library management. Conclusions. A system is considered adaptive if it can adapt to changes in internal and external conditions. Such a system remains operational in the event of unforeseen changes in the properties of the managed object, management goals, or environmental conditions by changing its functioning algorithm, behavioural programme, or search for optimal states. The task of adaptive library management is to keep the library as a system and its processes within the specified limits. The adaptive management system assesses the state of the process within the limits of permissible fluctuations and determines the need for corrective adaptation measures. Fluctuations in the processes of a library institution are expressed in terms of library production. Thus, the use of adaptive management methods meets the practical tasks of sustainable innovative development of the library industry and can be used in the library management tools for its implementation. An adaptive approach to library management is possible in the following cases: a) a developed forecasting system for prompt monitoring of the current situation of the library; b) the possibility of promptly changing plans if they no longer correspond to the new reality; c) an effective system of operational management accounting and control.

Investigating the Impact of Methanol Concentration and Implementation of a Coefficient Diagram-Based Control System for Direct Methanol Fuel Cell Operation

Investigating the Impact of Methanol Concentration and Implementation of a Coefficient Diagram-Based Control System for Direct Methanol Fuel Cell Operation

Research and design of urban flood control and drainage dispatching system

In order to solve the problem of frequent flood disasters in urban areas, water conservancy models such as hydrological forecast, flood simulation and operation decision-making were studied and constructed for the waterway-region-urban flood control and drainage engineering facilities, and urban flood control and drainage operation system was designed with the model as the core. The overall structure of the system is "five horizontal and two vertical". The "five horizontal" bottom up are respectively the intelligent perception layer, cloud infrastructure layer, data layer, service layer and application layer, and the "two vertical" are respectively the security system and the standard specification system. On this basis, the function customization of the system is completed to achieve comprehensive display, early warning and forecast, flood simulation, risk assessment, project scheduling and intelligent decision-making functions.

Использование нечеткой логики в системе управления технологическим комплексом напыления покрытий летательных аппаратов

The reliability of aircraft is ensured by various functional coatings applied to them. The quality indicators of coatings are determined by the capabilities of the control system for the technological complex of their spraying. The control system is effective if, with a large number of input parameters, it adopts the optimal technological solution to achieve the set values of coating quality indicators. The use of fuzzy logic in the control system of the technological complex of coating spraying is proposed. Using the Fuzzy Logic Toolbox package of the MATLAB program, an analysis of the fuzzy logic-based control system for the technological operation of applying a sprayed composition to a coated surface was carried out. It is shown that the use of fuzzy logic as an element of artificial intelligence is effective in the control system of the technological spraying process.

Real-time water quality forecasting in rivers using satellite data and dynamic models: an online system for operational management, control and citizen science

Increasingly scarce water resources and growing global populations have exacerbated the problems of water quality in river systems and freshwaters in general. New monitoring methodologies and tools to democratize access to water quality information are needed if we are to reach ambitious societal objectives such as the UN Sustainable Development Goals and the European Green Deal. Here we present a cloud-based system for producing publicly accessible real time water quality forecasts coupled to novel biosensor technology. Short term forecasts of water quality impairments, e.g., as cyanobacteria blooms, sediment plumes and toxic pollution incidents are increasingly relevant both to citizens and stakeholders. Here, we present a new cloud based system that utilizes satellite data to produce real time forecasts of flow and water quality using a chain of dynamic catchment-scale models at multiple locations in a river network. We demonstrate this new system using two case studies: the River Thames and the Essex Colne River (United Kingdom). These rivers are key water supply sources for London and South-East England, respectively and are of high interest to recreational water users. We show how the new system can predict and forecast water quality, estimate toxicity and connect to citizen science observations using an App (www.aquascope.com) for information synthesis and delivery.

Comprehensive evaluation of the working mode of multi-energy complementary heating systems in rural areas based on the entropy-TOPSIS model

BackgroundThe establishment of a multi-energy complementary heating system (MECHS) using abundant renewable energy is currently an effective way to solve the rapid growth of heating demands in rural areas. However, coupling schemes for different energy sources have become a critical barrier to the MECHS development. ObjectivesThe entropy-TOPSIS method was used to conduct a comprehensive evaluation of MECHS, which provided a basis for optimizing system operation strategy. MethodsWe built a test platform for MECHS based on solar-biomass-electricity energy in Tumxuk, Northwest China. Frist, six working modes were established according to the system operation control strategy. Second, we constructed the evaluation indexes of MECHS considering energy, environment and economy and determined their weights using entropy weight method. Third, the TOPSIS model was used to perform a comprehensive evaluation of the different working modes to identify optimal energy supply schemes. ResultsOur case study showed that the MECHS operated stably and met the indoor temperature demands of rural houses in cold regions. To maximize the heating efficiency of the system, it is necessary to reduce the types of energy appropriately. Next, based on entropy-TOPSIS model, the recommended order of energy supply mode for heating systems were solar-biomass energy (0.6202), solar-biomass-electric energy (0.6152), solar-electric energy (0.5895), biomass energy (0.4075), biomass-electric energy (0.3680), and electrical energy (0.3603). We found that the optimal energy supply mode was solar-biomass. ConclusionOur results indicated that the entropy-TOPSIS model could provide practical recommendations for the design and operation strategies of MECHS in cold rural areas.