Control Equipment Research Articles

Method of testing the software of spacecraft electronic equipment based on fault injection in the algorithms of orientation and stabilization

The purpose of the work is to develop and describe a new method of testing spacecraft electronic equipment. The article substantiates the relevance of developing new methods and means of testing on-board electronic equipment of spacecraft based on the intentional introduction of faults for the purpose of testing survivability algorithms. It was shown that carrying out such tests makes it possible to increase the completeness of control and reliability of on-board electronic equipment of spacecraft while simultaneously reducing testing costs. A new method for testing spacecraft software based on fault injection is proposed, which is used to solve the specific task of checking orientation and stabilization modes. The proposed method makes it possible to develop semi-natural models of on-board electronic equipment of increased adequacy and reconfigurability due to the use of programmable logic integrated circuits as the basis of hardware and software complexes. The proposed method is implemented on the hardware and software of a ground-based debugging complex for on-board electronic equipment and is distinguished by the ability to simulate a wide range of on-board electronic equipment, low cost and mobility. All technical solutions described in the article were introduced into the production process when creating modern spacecraft for communications, radio navigation and geodesy.

Modeling of Accumulator in Roll-to-Roll Coating Equipment and Tension Control with Nonlinear PID

Modeling of Accumulator in Roll-to-Roll Coating Equipment and Tension Control with Nonlinear PID

Research on the Security of NC-Link Numerical Control Equipment Protocol Based on Colored Petri Net

Research on the Security of NC-Link Numerical Control Equipment Protocol Based on Colored Petri Net

Electromechanical-coupling modeling and experimental validation of piezoelectric active vibration isolation for truss structures

Truss structures provide support and connection as essential components of spacecrafts. However, they are constantly disturbed and vibrated, which affects the pointing accuracy and operating stability. An active vibration isolation method for truss structures with embedded piezoelectric actuators (EPAs) is proposed in this study to address the challenges of excessive weight, large size, and limited effectiveness in vibration control equipment. Firstly, the EPA with a sandwich structure is designed and strategically embedded in the truss structure. Secondly, a novel modeling method is developed using the transfer matrix method (TMM) to effectively characterize complex beam structures including truss structures. Finally, a prototype is developed and the measurement system is constructed. The accuracy of the modeling is confirmed by vibration response experiments, with measurement results indicating that the discrepancies between theoretical predictions and experimental data remain within 5 %. Further validation of the EPAs for active vibration isolation is achieved through dedicated experiments, revealing a maximum isolation effect of −27.87 dB for longitudinal vibrations and –22.08 dB for bending vibrations. The experimental findings substantiate the promising application of proposed EPAs in enhancing active vibration isolation for truss structures, offering significant potential for improving the precision pointing and operational stability of space structures and spacecraft.

Advancing Healthcare: Intelligent Speech Technology for Transcription, Disease Diagnosis, and Interactive Control of Medical Equipment in Smart Hospitals

Intelligent Speech Technology (IST) is revolutionizing healthcare by enhancing transcription accuracy, disease diagnosis, and medical equipment control in smart hospital environments. This study introduces an innovative approach employing federated learning with Multi-Layer Perceptron (MLP) and Gated Recurrent Unit (GRU) neural networks to improve IST performance. Leveraging the “Medical Speech, Transcription, and Intent” dataset from Kaggle, comprising a variety of speech recordings and corresponding medical symptom labels, noise reduction was applied using a Wiener filter to improve audio quality. Feature extraction through MLP and sequence classification with GRU highlighted the model’s robustness and capacity for detailed medical understanding. The federated learning framework enabled collaborative model training across multiple hospital sites, preserving patient privacy by avoiding raw data exchange. This distributed approach allowed the model to learn from diverse, real-world data while ensuring compliance with strict data protection standards. Through rigorous five-fold cross-validation, the proposed Fed MLP-GRU model demonstrated an accuracy of 98.6%, with consistently high sensitivity and specificity, highlighting its reliable generalization across multiple test conditions. In real-time applications, the model effectively performed medical transcription, provided symptom-based diagnostic insights, and facilitated hands-free control of healthcare equipment, reducing contamination risks and enhancing workflow efficiency. These findings indicate that IST, powered by federated neural networks, can significantly improve healthcare delivery, accuracy in patient diagnosis, and operational efficiency in clinical settings. This research underscores the transformative potential of federated learning and advanced neural networks for addressing pressing challenges in modern healthcare and setting the stage for future innovations in intelligent medical technology.

Standardization of radiation therapy quality control system through mutual quality control based on failure mode and effects analysis.

The advancement of irradiation technology has increased the demand for quality control of radiation therapy equipment. Consequently, the number of quality control items and required personnel have also increased. However, differences in the proportion of qualified personnel to irradiation techniques have caused bias in quality control systems among institutions. To standardize the quality across institutions, researchers should conduct mutual quality control by analyzing the quality control data of one institution at another institution and comparing the results with those of their own institutions. This study uses failure mode and effects analysis (FMEA) to identify potential risks in 12 radiation therapy institutions, compares the results before and after implementation of mutual quality control, and examines the utility of mutual quality control in risk reduction. Furthermore, a cost-effectiveness factor is introduced into FMEA to evaluate the utility of mutual quality control.

Design and Testing of a Small-Scale Composting Facility for Sheep Manure Utilizing Aeration and Thermal Treatment

Inner Mongolia has the largest sheep population among China’s provinces, resulting in the production of a substantial amount of sheep manure. If left untreated, this manure can contribute to environmental pollution. However, sheep manure serves a dual purpose: it can be both a pollutant and a valuable source of organic fertilizer. Consequently, there is an urgent need to address the environmental issues arising from manure accumulation and its unused status. In this paper, a viable solution is proposed: the conversion of manure into fertilizer through a composting unit incorporating high-temperature aerobic fermentation technology. This unit, tailored for small farms and individual farmers, integrates critical functions such as ventilation, heating, and turning. Additionally, it boasts excellent thermal insulation, enhancing composting efficiency and enabling precise control over fermentation conditions. This design mitigates heat loss and accelerates maturation, addressing common challenges in traditional composting. The design process encompassed both equipment construction and control systems, with a primary focus on compost fermentation and aeration heating. The components were carefully designed or selected based on theoretical analysis and subsequently validated using simulation software, including EDEM and Fluent. The control system seamlessly integrates a touch screen interface, PLC programming, and control circuits to manage air pumps and electric heaters in response to changes in temperature and oxygen concentration. Furthermore, it controls the motors during the recovery phase. A comprehensive performance evaluation was conducted, revealing notable improvements. Under artificially heated conditions, the maximum temperature of the compost increased by approximately 20 °C, the composting cycle was reduced by roughly 4 days, and the seed germination index (GI) rose by about 9% when compared to natural fermentation. Thus, this device significantly accelerates composting and improves fertilizer quality by increasing the decomposition rate.

Synergistic integration of control equipment and renewable resources for improved self-healing in smart distribution networks

Synergistic integration of control equipment and renewable resources for improved self-healing in smart distribution networks

Management of diverse smart homes: Coordination among controllable loads, EVs, and PVs

Growing energy demand, driven by urbanization, transportation electrification, and smart home devices, highlights the significance of residential electricity consumption. However, controllable loads, including HVAC systems, water heaters, electric vehicles (EVs), and industrial processes, can be managed to balance electricity supply and demand. Therefore, this study addresses the escalating energy demand in residential buildings including the integration of electric vehicles (EVs) and renewable energy technologies. It focuses on controllable loads, which offer flexibility that can be managed to balance supply and demand through demand response programs. First, the controllable loads are categorized as HVAC (air conditioners, electric heaters, and electric heat pumps), uninterruptable (washing machines, dishwashers, and electric cookers), interruptible (water heater), and EVs. Then, this study proposes a detailed clustering approach for homes, categorizing them into six clusters to capture diverse consumption patterns, including scenarios such as work-from-home setups. The analysis includes examining the adaptability of these home clusters and controllable load groups under different EV charging levels (level 1 and level 2) and coordinating them with PV systems. The study evaluates the coordination of each controllable load group with EVs and PVs, aiming to optimize overall energy usage and enhance renewable resource integration. Parameters such as energy management, operation of controllable equipment, and indoor temperature are analyzed to provide insights for homeowners and policymakers to make informed decisions about load management and energy resource utilization in residential settings. Simulation results show that with level 1 chargers, type 2 homes achieve higher average EV avoidance (81.94 %) and lower PV consumption (31.22 %), while with level 2 chargers, all homes reach 100 % EV avoidance.

Formulation and Evaluation of Herbal Hand Sanitizers Based on Plants Producing Essential Oil

Hand hygiene is important because it can easily be transmitted through direct contact with microbial spores produced during coughing and sneezing. It is important to prevent the spread of the disease, especially in cases such as epidemics, through the use of antibiotics. This can be achieved by establishing and maintaining strict infection control equipment such as good hygiene in hospitals and public places. The aim of this study is to prepare an alcohol-based sanitizer against bacterial infections. After the test, the pH value of the disinfectant is between 6.65 and 6.67. The viscosity of the antiseptic is between 389 cps to 835. The spread ability was good and found in range between 6.55 to 7.18 g-cm/sec. The drug content of Eucalyptus Oil in formulations was found to be 93% in F1 and 97.5% in F2. In-vitro drug release study was found to be 56.2% in F1 and 60.6% in F2, and the stability of the preparation remained stable after 3 months of storage. All these studies showed that the F2 formulation is the best as it has better pH, viscosity, spreading ability and safety.

Application of the integrated well-surface facility production system for selecting the optimal operating mode of equipment

This work is dedicated to the analysis and development of an integrated production system that combines wells and surface facilities to select the optimal operating mode for equipment. The main focus is on studying data analysis methods, as well as collecting and processing information, which ensures high accuracy in process control and optimal use of technological capabilities. The integration of data from various levels of the production chain, from the well to the surface facilities, opens up new opportunities for optimizing equipment performance and improving resource management quality. Integration of wells and surface facilities – The effective integration of wells and surface facilities is crucial for optimizing production processes, minimizing operational costs, and reducing environmental impact. Integrated management systems allow the automation of many processes, providing continuous monitoring of operating parameters, automatic adjustment of settings, and supplying data for quick decision-making. This includes real-time data collection, analysis, and the use of the obtained information to select optimal operating modes, which helps improve both overall efficiency and safety in production processes. In the modern oil and gas industry, the efficient use of equipment at all stages of hydrocarbon production is of particular importance. Optimizing the operation of wells and surface facilities is a key aspect for increasing economic efficiency and reducing environmental impact. In this regard, the development and application of integrated systems that enable real-time control and adaptation of equipment operating modes has become a relevant and significant task.

Vapor–liquid phase equilibrium prediction for mixtures of binary systems using graph neural networks

AbstractVapor–liquid phase equilibrium (VLE) plays a crucial role in chemical process design, process equipment control, and experimental process simulation. However, experimental acquisition of VLE data is a challenging and complex task. As an alternative to experimentation, VLE data prediction offers great convenience and utility. In this article, an artificial intelligence network is proposed to predict the temperature and the vapor phase composition of binary mixtures. We constructed a graph neural network (GNN) and designed an uncertainty‐aware learning and inference mechanism (UALF) in the prediction process. The model was tested on both a self‐constructed dataset and a publicly available dataset. The results demonstrate that the proposed method effectively reveals the phase equilibrium properties of the target data. This work presents a novel approach for predicting vapor–liquid phase equilibrium in binary systems and proposes innovative ideas for investigating phase equilibrium mechanisms and principles.

Research on coal rock parameter calibration based on discrete element method

To ensure that the discrete element model of the coal wall accurately reflects the actual cutting process of coal and rock during virtual prototype simulation of mining equipment, this study aims to expedite the development of intelligent mining machinery. Using coal samples from the 4602 working face of Yangcun Coal Mine, operated by Yanzhou Coal Mining Group, we conducted coal rock packing experiments and uniaxial compression tests to obtain the packing angle and compressive strength of the coal samples. Based on the experimental results, we designed Plackett–Burman experiments (PB experiments), steepest ascent experiments, and Box-Behnken experiments to study the influence of particle contact mechanics parameters and bonding mechanics parameters on the packing angle and compressive strength, using the packing angle and compressive strength as response variables. Our objective is to minimize the relative error between the simulated packing angle and the measured packing angle. We solved and optimized the parameter calibration model and conducted simulation calibration experiments based on the optimization results. A comparative analysis with the actual test results revealed that the maximum relative errors between the simulated and measured values for the packing angle and compressive strength were only 2.9% and 5.0%, respectively. Additionally, a discrete element model of a typical working face coal wall was established based on the parameters obtained from this calibration method. A bidirectional coupling model of the cutting process between the coal and rock was created using EDEM-RecurDyn to simulate the rigid-flexible coupling of the coal cutter. An experimental coal wall model was constructed based on similarity theory, and both simulation and physical experiments were conducted. The evaluation metrics for comparison were the time-domain and frequency-domain characteristics of the drum’s vibration signals. The maximum relative error for the time-domain signal characteristics between the two experimental setups was only 4.19%, while the maximum relative error for the frequency-domain signal characteristics was 3.75%. This validates the feasibility of the proposed calibration method for the discrete element coal wall model and the accuracy of the calibration results. Furthermore, it demonstrates that the constructed discrete element coal wall accurately represents the actual coal and rock properties. The virtual simulation based on this model effectively replicates the interaction process between mining machinery and coal, providing a safe, efficient, and low-cost technological approach for performance analysis of mining equipment and intelligent control of supporting devices.

Augmented Reality Control based Energy Management System for Residence

Introduction: The roots of virtual reality (VR) go back to the work of Ivan Sutherland in the 1960s. At the time, virtual reality showed promise in universities and labs, peaking in the early 1990s at a stable level. The latest form of IoT is merging with the Internet of Everything (IOE). Using this technology, users can access any device, device, and machine in the environment through any middleware application or system. In recent years, smart speakers have become a common commercial method for controlling household appliances, solving some of the problems of remote control. For example, speech recognition is difficult in noisy environments and is minimized using noise cancellation. It also takes a long time to determine the current state of the device as the user need to request or issue a command to the smart speaker and need to wait for a response. The evaluation of prototype system found, using a device with gestures and interacting with a virtual 3D device instead of a real device was acceptable in terms of usability. In this article, the Unity and Vuforia are used to create an AR-based IoT virtual switch that can control any device connected to a LAN controller via HTTP requests. Methods: The system is made experimental with the Augmented Reality (AR), the virtual communication system is designed instead of physical mode. It provide the real time based image for active control of Energy management. It consist of virtual switches, it supports the AR based power control system. Results: The proposed system are made evaluated and tested under various load conditions. The virtual image consist of virtual switches to make real time control of power equipment. The proposed system achieve the latency of about 0.06 sec. Conclusion: The advancement in day today activities required with AR based energy management system with proper control measures. The designed system is supportive for such mechanism. The further system is proposed to make more energy saving concept for enhancement in proposed work.

Preface

The 7th International Conference on Downhole Measurement and Control (ICDMC2024) is originated from the Conference on Measurement and Control While Drilling. This conference was organized by China University of Petroleum (East China) and Beijing Liuhe Greatness Technology Co., Ltd., and has been held six times successfully. This year, in view of the academic and industrial trends and aiming to enhance the influence of the conference, the 7th conference has been named as the 7th International Conference on Downhole Measurement and Control (ICDMC2024), and was held successfully on 22nd-23rd August, 2024 in Beijing, China. ICDMC2024 was organized and supported by Sinopec Research Institute of Petroleum Processing Co., Ltd., China University of Petroleum (East China), Southwest Petroleum University, China University of Petroleum (Beijing), Central South University, China Oilfield Services Limited (COSL), Sichuan Tianshi Hechuang Technology Co., Ltd, Beijing Liuhe Greatness Technology Co., Ltd., and Beijing Petroleum Machinery Co., Ltd. ICDMC2024 gathers distinguished scholars, researchers, and practitioners from diverse institutions of the globe to engage in comprehensive discussions on downhole parameter measurement technology, high-speed data transmission technology while drilling, research and development of borehole trajectory control technology and equipment, intelligent development of measurement and control while drilling, and application of measurement and control while drilling technology. We are grateful to the notable speakers from the academic institutions and the industries. The speakers share their profound knowledge and advanced insight, promoting high-quality development of the technology and the industry. The proceeding of ICDMC2024 collects academic papers that underwent double-anonymous reviews and contribute to the technical advancements of the fields. The reviewer evaluated the paper’s originality, relevance, technical contribution, data accuracy, and writing structure. The ICDMC20242024 Committee appreciate the reviewers and committee members’ effort to complete the reviews and deal with the manuscripts. We also sincerely thank all the authors, participants, committee members, organizing staffs and volunteers for their support to the ICDMC2024. Committee of ICDMC2024. List of Committee of ICDMC2024 is available in this Pdf.

A study on environmental elements of residential open spaces for grandparent-child rearing based on a field survey in Tianjin, China

With the advent of an aging society, grandparents' involvement in childcare is becoming increasingly common, saving families and society huge nursing costs. Residential open space (ROS) is a common place for grandparents' outdoor childcare activities, influencing the health of grandparents and children. However, existing research on the ROS environmental needs of intergenerational users is still insufficient. This study regards grandparents and children as a cohesive entity, based on environment behavior theory, and constructs a research framework for the ROS environmental elements needs for grandparent-child rearing. Taking a residential area in Tianjin as an example, four types of grandparent-child rearing are identified based on the age of the children. Through interviews with grandparents and observation of outdoor activities involving grandparent-child rearing, significant differences in the needs of ROS environmental elements such as enclosure feeling, pet control, and adult fitness equipment among different types of grandparent-child rearing were found, stemming from different caregiving patterns. This study provides important implications for constructing supportive childcare environments and promoting physical activities and childcare education among intergenerational populations.

Growing Need for Web-Based Simulation in Low and Middle-Income Countries: A Narrative Review

Web-based simulation programs are poised to offer a productive means of delivering asynchronous training in healthcare professionals’ education. Similarly, web-based simulation programs could also sponsor specialty-specific, web-based fellowships for clinicians of low- and middle-income countries. Web-Based Simulation has been utilized for instruction in critical care fields such as emergency medicine and pediatric anesthesia. Studies have shown that enhanced self-reported knowledge and confidence have been achieved through tele simulation which is in line with in-person simulation. During the COVID-19 pandemic, simulations have helped clinicians hone their use of personal protective equipment and other infection control measures. Additionally, it has helped them in learning new and expanded roles, like processing equipment and assisting infected patients in prone position experiencing respiratory failure. However, web-based simulation programs also have unique challenges that must be satisfied: reliable broadband internet network access, multilingual capability, and programming quality. Studies indicate that cost-effective simulation training can be delivered to learners in remote, low-resource areas worldwide, including South Asia, where access to such education is limited. We aimed to explore the effectiveness, challenges, and strategies for implementing web-based simulation education in low- and middle-income countries, based on a thorough PubMed search focused on web-based simulation programs in medical education.

Device to Measure, Monitor and Control Variables for Agricultural Purposes

The measurement of meteorological variables is important for decision-making in the field. Accurate data can help farmers optimize their activities to improve food production. Traditional methods of monitoring variables can be expensive or complex for small-scale farmers to use. This indicates a need for low-cost and user-friendly devices. Currently, there is technology for developing these types of devices, which could be useful to automate processes based on variable monitoring and improve food production. Due to this, a device based on the Arduino Mega<SUP>TM</SUP> board was developed to monitor air temperature, relative humidity, rain, and soil moisture. In addition, equipment was developed to be controlled based on a rain gauge. The device has a TFT touch screen for easy-user interaction and 4 menus for information display (summary, floor, date-time and manual equipment control). The program of the device required more lines of code (59.65%) to establish user-device interaction compared to its internal processes (18.66%) and variable declarations (21.68%). A container was 3D printed to house all the integrated circuits and the device was tested under both indoor (Jun-10, 2024 to July-17, 2024) and outdoor (Jul-22, 2024 to Aug-18, 2024) conditions. Under indoor conditions, a 3% difference was found in the temperature measurements taken under the same conditions (using DS18B20 and MLX90614 sensors). Under outdoor conditions it was found that the air temperature decreased by an average of 2.33°C when increasing the height from 8ft to 16ft and the relative humidity decreased by an average 3.48% when increasing the height from 8ft to 16ft. There was a 3.4% difference in total rain measured by the rain gauges. Finally, the developed device performed adequately during the two months of testing in both conditions, measuring variables and controlling equipment (the equipment went from waiting mode to rain harvesting mode 92 times).

The knowledge of medical staff on the impact of noise on neonatal intensive care units patients and its application in practice.

Noise is an undesirable environmental factor whose control and reduction should be standard in every Neonatal Intensive Care Unit. Its impact can have negative effects on both the mental and physical health of the body. Newborns, especially premature infants, are particularly sensitive to the negative effects of noise. the negative impact of noise can be reduced through appropriate behaviour of the medical staff. Aim. The aim of the study is to analyse the knowledge of medical staff on the impact of noise on newborns staying in Neonatal Intensive Care Units and to evaluate its use in practice. Methods. A total of 104 respondents working in neonatal wards participated in the study. The survey was conducted online using social media. The study employed the diagnostic survey method with a self-designed questionnaire. The first part of the ques- tionnaire concerned the aspects of knowledge on the impact of noise on hospitalised new- borns; the second part addressed the socio-demographic issues of the medical staff. Results. Training on noise exposure for newborns is not common in the workplace. There are no recommendations regulating noise standards and control equipment. The surveyed individuals do not have in-depth knowledge about acceptable noise levels in newborn rooms. Only one in three employees was able to provide the correct answers in this regard. Older employees with longer experience and residents of large cities scored higher in knowledge than younger individuals. Those with a higher level of knowledge and satisfaction with their work and earnings show the greatest care in reducing noise intensity in the ward. Conclusions. In neonatal pathology wards and (NICUs), noise standards and recom- mendations are more common than in physiology wards. Employees caring for new- borns need training on the sources and impact of noise on babies. it is necessary to limit the noise generated by the staff, such as loud conversations, slamming furniture, placing objects on incubators, or moving equipment.

Integrating sensor networks to facilitate efficient energy management for smart grids

Organizations are implementing Smart Energy Management Systems (SEMS) to regulate energy consumption patterns and respond to energy-saving instructions due to rising energy prices and demand. The study proposes an intelligent energy management solution that integrates an IoT middleware module and Energy Controller for effective demand side regulation. The study offers an intelligent energy management solution for smart settings that integrates an IoT middleware module and Energy Controller to regulate the demand side effectively. Every IoT device has an energy controller connected, incorporating sensors and actuators. The proposed solution optimizes air conditioner energy usage in Pakistan by analyzing exterior temperature conditions, building dynamics, and data from smart devices. It uses functional interfaces, robust algorithms, and continuous tracking for assessment. To evaluate the proposed methodology the research highlights the system's key benefits and reveals significant energy savings. The smart energy management system provides better air conditioning system control, real-time monitoring, cost savings, environmental advantages, and longer equipment life.