Control Equipment Research Articles

Customer Loyalty Model of Export Product Shipment Certification

This paper investigates the loyalty model of customers towards a certification governing body for export product shipment certification. The present study investigates the impact of service quality, consumer satisfaction, customer trust, and customer loyalty on the established model. The model will be used to determine the specific areas that need enhancement to improve consumer loyalty. There were 104 participants took part in the study by means of convenience sampling and telephone questionnaire surveys. This study results that customer satisfaction is greatly influenced by the five components of Servqual service quality: tangibility, empathy, dependability, responsiveness, and assurance. Moreover, it was shown that the five categories of service quality had a substantial impact on customer trust. The level of product satisfaction and trust directly influences the loyalty of customers. In addition to examining direct effects, the study also detected indirect effects resulting from mediating variables. The findings indicate that consumer trust is influenced by reliability through customer satisfaction, and customer trust is influenced by assurance through customer satisfaction. Consumer satisfaction, in turn, influences consumer loyalty by means of customer trust. Managerial implication of this study encompasses the instruction of personnel in export product certification services, including areas such as communication, regulations, document control, and management of personal protective equipment. The organization is advised to establish a systematic service evaluation process and then execute a follow-up strategy to guarantee that the evaluation findings are acted upon.

Enhancing the reliance of emergency power supply systems for nuclear facilities using hybrid system

The performance of an atomic facility depends on the efficient supply of electricity, particularly emergency loads like monitoring and control equipment, radiation safety systems, and emergency lights. Most nuclear facilities rely on diesel generators to supply emergency loads during grid outages. Due to the diesel generator's imperfections, such as its starting time, it may fail to deliver power because it is unavailable due to maintenance, failure to start, or failure to run and supply the load. It cannot immediately supply the critical loads, resulting in a blackout and the release of radioactive substances into the environment. To address the previous issues, this paper proposes an improved method to enhance the reliability of nuclear facilities for providing electricity to safety and critical consumers during normal and emergency operating modes. The approach incorporates a photovoltaic (PV) system/battery, and its robustness and performance are tested using load flow and transient stability analysis. The simulation results demonstrated the effectiveness and speed of the proposed method when compared to the traditional method, as the emergency consumers were successfully powered within a very short time without fluctuations, and the voltage reduction and frequency were within the nominal values. The electrical transient analyzer program (ETAP) is used to validate these results.

Implementation of Electrical Equipment Control and Security System integrated with Internet of Things

Research on Electrical Equipment Security and Control Systems Using the Internet of Things aims to implement an IoT system for controlling electrical equipment and security systems. The owner of the security location will receive a phone call if an object is detected and can monitor and activate the alarm system while controlling electrical equipment. In addition to saving electricity, it is also intended that the detected object/human will change his mind. This system can be used anytime and anywhere. The specific target achieved is to implement a building security system and control electrical equipment using the internet of things. The method used is the experimental method, namely collecting data from the results of measuring electrical quantities in the system. The equipment used is the SIM800L module, PZEM sensor, PIR module-8 sensor, RTC, PCF8574, shift register 74HC595, ESP 32, Triac, Optocoupler, buzzer, contactor, and other supporting equipment. The results of the study show that the ability of the PIR sensor to detect objects has a sensitivity that is not all the same even with the same type, the sensitivity of the PIR sensor is influenced by the condition of the internet network, the location of the detection room, the length of the pir sensor cable to the esp 32, and the speed of the response of the designed system. Controlling electrical loads using the blynk application with contactor equipment can work effectively if the internet network conditions are stable, the effectiveness of using optocouplers and triacs allows the contactor to receive input quickly and responsively. Keywords: IoT, ESP 32, security, alarm, sensor

Automating Agriculture: The Impact of AI and IoT on Farming

The agriculture industry is under tremendous pressure to boost food grain productivity and production due to the effects of climate change and population growth. Agriculture automation is now the only viable choice and a pressing necessity in the majority of nations where agricultural growth is just not feasible. Artificial intelligence and the Internet of Things have already begun to make inroads into every sector, including agriculture. The development of these digital technologies has revolutionized agriculture by enabling intelligent systems that are as intelligent as human experts and are capable of real-time monitoring, control, and visualization of a variety of farm operations. The study discusses the possible uses of AI and IoT in the establishment of smart farm equipment, irrigation systems, greenhouse culture, storage buildings, weed and pest control, manure application, drones for crop monitoring, plant health monitoring, etc. This study's main objectives are to give a summary of new studies on agriculture powered by digital technology and to list the most well-known applications of artificial intelligence and the internet of things in agriculture engineering. Scientific databases like Web of Science, PubMed and Scopus have been used to examine research conducted in the fields over the past ten years. It has been found that the utilization of IoT and IoT, from its initial conceptual stage to its implementation stage, the effort to automate agriculture has advanced. The technical features of artificial intelligence and the Internet of Things are also covered, along with the challenges associated with putting these digital technologies into practice. It would aid people in understanding how digitalization may be incorporated into agricultural processes to make it easier for farmers to implement AI and IoT-based solutions.

Reconditioning and Enhancement of Automatic Pressure Control Equipment for Servo and Regulatory Processes

Reconditioning and Enhancement of Automatic Pressure Control Equipment for Servo and Regulatory Processes

Modbus RTU Protocol Timing Evaluation for Scattered Holding Register Read and ModbusE-Related Implementation

In parallel with the development of data transmission in the telecommunications sector to connect peripheral devices, hardware engineers have defined interfaces for independent communication systems. The basic idea of having standardized interfaces for external devices was quickly extended to control and instrumentation equipment, as the real-time characteristic of distributed systems became a challenge in the field. The proposed Modbus Extension (ModbusE) builds on these new techniques introduced in the UART interface, so that the newly introduced extension retains all the characteristics of the Modbus RTU except for the character bit structure. The validation of the ModbusE protocol allowed the proposal of a new communication message structure, a description of Modbus devices, an acquisition cycle to attain a deterministic temporal response behavior and the definition of an architecture for IIoT integration. In this work, practical research is based on data update times in SMARTConvert software when between 1 and 50 registers are accessed. These registers can, in the most favorable case, be at consecutive addresses and can all be read in a single bus query request, or at addresses 1 to 50, or the registers must be read in separate requests. The contributions of this paper are related to highlighting cases where Modbus modules are incorporated, the addressed registers are not consecutive and the Modbus reads 1 or more holding register records and the ModbusE proposal. As these registers must not be on consecutive addresses, it is necessary to make several requests, defining the function of a Modbus acquisition cycle, adapting the equations to the purpose of the tests carried out, measuring the Modbus communication signals and describing the ModbusE communication concept.

Research on Energy-Saving Optimization Method and Intelligent Control of Refrigeration Station Equipment Based on Fuzzy Neural Network

Under the background of dual carbon, the retrofitting of the equipment operation system of a refrigeration station and the optimization combination of its control system are significant for its efficient operation and energy saving. The single-direction variable flow technology is often used in the chilled water system in refrigeration stations nowadays. However, the single-direction variable flow technology cannot achieve both thermal balance and flow balance for the chiller system, which is unfavorable for improving energy efficiency and reliability. To improve the reliability and energy efficiency of the refrigeration station equipment, the bidirectional variable flow technology of primary and secondary chilled water pumps was presented. Meanwhile, the feasibility of fuzzy neural networks in bidirectional variable flow systems and their energy-saving effect were studied. Before the energy saving retrofit, the refrigeration station used traditional PID (proportional-integral-derivative) controllers, and the chilled water system used single-direction variable flow technology; After the energy-saving retrofit, the refrigeration station adopted a fuzzy neural network control algorithm to optimize the PID controller parameters, and at the same time, the chilled water system used bidirectional variable flow technology. Through a large number of trial calculations of the established neural network model, it was found that 2 hidden layers and 25 hidden layer nodes can achieve higher accuracy. Specifically, the controller of the central refrigeration station consists of a training neural network and a predictive neural network working in parallel. The task of training neural networks is to learn the relationship between different input parameters and the whole energy consumption. Then it serves as the excitation function of the prediction network. The function of the predictive neural network is to find the control parameters that minimize energy consumption. The application results showed that before and after the retrofit annual power consumption and energy-saving effects were very Significant. After the energy-saving retrofit of the refrigeration station, the energy saving is 422,775 KWh every year, the energy-saving rate is 11.67%, and the annual saving cost is about 0.3382 million yuan. The results demonstrated that bidirectional variable flow technology and its control methods were feasible, reasonable, and worthy of promotion.

Three-Position Vehicle Control Based on Neural Interface Using Machine Learning

The brain-computer interface is a complex system that allows you to control external electronic devices using brain activity. This system includes several elements – a device for reading brain activity signals, a hardware and software complex that processes and analyzes these signals, and a control object. The main challenge here is the development of methods and algorithms that can correctly recognize and predict the intentions of the person who uses this interface to provide solutions to control problems. This paper describes the mathematical formulation of the equipment control problem. Methods for preprocessing EEG signals, analyzing them, and making decisions about issuing a control signal are described; the structure of the software implementation of these methods is described, as well as a plan for experimental testing of the performance of the entire system that forms the brain-computer interface. For classification of EEG signals the methods of machine learning are used. A modification of the k-nearest neighbors method is proposed – the so-called fuzzy almost nearest neighbors method. An algorithm for the adaptive classification of EEG taking into account the drift of the parameters of the subject's model based on the method of recurrent objective inequalities (ROI) has also been developed. The control algorithm was implemented in the Python programming language. A remote-controlled wheelchair is considered as a control object, and turning the chair to the right or left is considered as a control task. To experimentally test the performance of the developed model and algorithms, more than 15 tests were carried out with five subjects in total. The approach developed and described in this article and its software implementation during testing demonstrated its effectiveness in the tasks of controlling the rotation of a wheelchair. Special attention was also paid to the resource intensity of the software implementation. Methods and algorithms were implemented taking into account the requirements that arise when performing calculations on low-performance devices with a limited amount of memory.

Model Predictive Control of Aerodynamic Levitation Systems

Airjet-driven levitation systems are an important emerging technology, as they can ensure the contactless movement of objects. From a control engineering perspective, the position set-point tracking of the levitating object poses many challenges because the aerodynamic characteristics of the air jet used for levitation are difficult to model. The unmodelled disturbances significantly affect the control performances. Moreover, the bound constraints imposed by the mechanical design and the applied actuators should also be considered during controller design. In this work, we present a motion control approach suitable for vertical levitation systems actuated by a fan-induced air jet. We developed the necessary hardware and software elements for the control equipment of the levitation system. We apply the MPC (Model Predictive Control) approach to ensure high-precision position regulation under various aerodynamic conditions with bounded control signals. We validate the applicability of the control system through simulation and real-time experimental measurements.

Deep learning-driven ultrasound equipment quality assessment with ATS-539 phantom data

IntroductionUltrasound equipment provides real-time visualization of internal organs, essential for early disease detection and diagnosis. However, poor-quality ultrasound images can compromise diagnostic accuracy and increase the risk of misdiagnosis. Quality assessments are often subjective, relying on the evaluator's experience and interpretation, which can vary. MethodsThis study introduces a two-stage deep learning framework designed to objectively assess ultrasound image quality using phantom data across three key parameters: ‘Dead zone’, ‘Axial/lateral resolution’, and ‘Gray scale and dynamic range’. Stage 1 automatically extracts regions of interest for each parameter, while Stage 2 employs detection or classification models to evaluate image quality within these regions. To generate an overall equipment quality score, a logistic regression model combines the weighted results from each parameter. ResultsThe classification model demonstrated high performance across datasets, achieving AUC scores of 98.6% for ‘Dead zone’, 87.7% for ‘Axial/lateral resolution’, and 96.0% for ‘Gray scale and dynamic range’. Further analysis using guideline-compliant images of individual devices showed AUC scores of 98.2%, 92.8%, and 100%, respectively. These findings highlight deep learning's potential for quantitative and objective assessments of ultrasound image quality. Ultimately, this framework provides a streamlined approach to quality management, enabling consistent quality control and efficient scoring-based evaluation of ultrasound equipment.

Research on Multi-Objective Vibration Control of Heavy-Duty Vehicles and Heavy Power Equipment

Research on Multi-Objective Vibration Control of Heavy-Duty Vehicles and Heavy Power Equipment

Exploration and Future Development Direction of Electrical Engineering and Automation in Office Property Management

The application of electrical automation technology in office property management has become an important trend in the industry. This paper discusses the exploration and future development direction of electrical engineering and automation in the property management of office buildings. By using advanced sensor technology, intelligent control algorithm, and Internet of Things technology, the electrical automation system can realize intelligent monitoring, control, and management of the internal equipment and facilities of office buildings, improve the energy efficiency, safety, and comfort of office buildings, and reduce the cost of property management and human investment. With the continuous development and application of new technologies such as artificial intelligence, big data analysis, and sustainable development, the role of electrical automation technology in office property management will become increasingly important. The key development directions include strengthening technology standardization and normalization, optimizing user experience and demand customization, and strengthening talent training and technology popularization. Through continuous technological innovation and application practice, electrical automation technology will bring more opportunities and challenges to office property management, and promote the intelligent, green, and sustainable development of the industry.

Control of boiler equipments during starting and stopping periods and methods of optimizing these processes through the use of a decision support system with a machine vision subsystem

Control of boiler equipments during starting and stopping periods and methods of optimizing these processes through the use of a decision support system with a machine vision subsystem

Remote control of home electronic equipment using dual tone multi-frequency signals

The majority of electrical appliances rely on a switch as a fundamental mechanism for activation, deactivation or adjustment of appliances operation based on their requirement. It ensures safe and efficient flow of electricity or power to these devices. With the rapid advancement of technology, automation and wireless control systems have gained significant popularity. The current conventional automation regards remote control of appliances is based on Infra-Red transmission technology. The challenges associated with Infra-red technology includes short distance of transmission or operating range, inability to penetrate solid barriers, limited line of sight, inability to communicate to the user the current status of the appliance, and complete lack of security as any other person can use the remote to operate the device. By leveraging the capabilities of modern smartphones, this equipment aims to provide a user-friendly solution for remote management of electrical appliances, further enhancing the efficiency and comfort of modern homes. The work primarily presents the design and functionality of a device that wirelessly regulates home electrical equipment through the integration of GSM and an 8051 microcontroller. The system functions by having an authenticated signal transmitted from the user's mobile phone via the Global System for Mobile Communication (GSM) network to a designated phone connected to the control equipment. This signal, or code, contains specific information about the operation to be executed, such as which electrical sockets need to be turned on or off. Upon receiving the Dual Tone Multi Frequency (DTMF) signal from the user's mobile phone, the receiver phone relays it to the integrated DTMF decoder. The decoder interprets the signal and converts it into a digital output signal, which is then forwarded to the 8051 microcontrollers. Based on the received digital signal, the microcontroller activates the appropriate relays connected to each electrical socket through the ULN2003 Darlington transistor array. This activation effectively controls the power supply to the targeted sockets, enabling the user to manage their electrical appliances remotely with precision and convenience. Comprehensive testing was performed on each circuit diagram module, and notable results were achieved for the overall system. The system's unique features allow end-users to conveniently control and isolate tasks using a mobile phone. By pressing specific buttons, users can easily manage various operations remotely, enhancing the system's functionality and flexibility in a range of applications.

Internet of Things Implementation Project in Industry 4.0: Opportunities and Challenges

Objective: In Industry 4.0, Internet of Things (IoT) is considered a basic technology that can be used in several areas, from to real-time equipment monitoring and control to other services, but its implementation is surrounded by challenges. The objective of this study is to analyze the most relevant opportunities and challenges in the IoT implementation projects. Method: The methodology used was literature review and field research developed in two manufacturing plants. To classify the opportunities and challenges under study, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), a multicriteria decision-making method (MCDM), was used. Results and Discussion: The main opportunities identified were: IoT helps reduce production costs, and IoT technology reduces production waste, and the main challenges were: there is uncertainty about the return on investment in IoT, and the lack of professional qualifications hinders/prevents the implementation of IoT. Research Implications: A practical and theoretical implication of this research is to present concerns about the possibility of having cleaner production practices in parallel with cost reduction in IoT implementation projects. Originality/Value: The theoretical relevance of this study is to classify opportunities and challenges according to their degree of importance. The practical contribution is to help those responsible for IoT implementation projects, so that they can try to maximize opportunities and minimize challenges.

Personal Protective Equipment and Infection Control: Evaluating the Impact on Healthcare Worker Safety – A Review

Personal protective equipment (PPE) is a cornerstone of infection control, serving as a critical barrier between healthcare workers (HCWs) and infectious agents. This review evaluates the effectiveness of PPE in reducing healthcare-associated infections (HAIs) and safeguarding HCWs, with a focus on its role during recent global outbreaks such as COVID-19. A systematic search of peer-reviewed studies from 2016 onward revealed that proper PPE use significantly reduces infection risks, with reductions of up to 85% reported during high-risk scenarios. However, challenges such as resource shortages, improper usage, discomfort, and compliance issues persist, particularly in low- and middle-income countries (LMICs). The review highlights disparities in PPE availability and effectiveness between high-income countries (HICs) and LMICs, underscoring the need for equitable access and targeted interventions. Recommendations include enhancing supply chains, providing regular training, and promoting innovation in PPE design to improve usability and compliance. These findings underscore the essential role of PPE in infection prevention and the importance of sustained efforts to address existing barriers and ensure HCW safety globally.

Replacement Strategy for Aging Nuclear Power Instrumentation and Control Equipment Based on Life Margin

The instrumentation and control (I&C) equipment in nuclear power plants gradually ages and becomes obsolete with increased operation time. Its performance deteriorates, and the probability of its failure also increases gradually. The failure of I&C equipment may directly lead to the degradation of the control or protection functions, reducing the reliability and safety margin required by the design. This will hurt the safety and stable operation of nuclear power plants. Therefore, an aging I&C management/replacement strategy is necessary to control and minimize this problem. In this regard, this paper establishes a module lifetime evaluation model described by a composite probability density function for modules composed of multiple components. On this basis, we have developed a multi-objective aging replacement optimization model aimed at high reliability, economy, and feasibility, and propose an equipment aging replacement optimization calculation method based on the linear-weighted discrete state transition algorithm. The procedure is verified by the application of data from nuclear power engineering. The results show that the proposed aging replacement strategy and method can significantly reduce computational difficulty, improve equipment reliability, and lower aging replacement costs.

The Effectiveness of Local Exhaust Ventilation (LEV) System in Welding Training Facilities using Validation Computational Fluid Dynamics (CFD) Simulation

The Local Exhaust Ventilation (LEV) is the most common type of engineering control equipment used to control employees' exposure to chemicals that are hazardous to their health. Before a contaminant disperses into the workroom environment, LEV systems operate on the principle of capturing it at or near its source. The welding guideline stated that the suggested minimum hood velocity is 100 ft/min, the recommended velocity along ducts for vapors, gases, and smoke is 1000 ft/min, and 2000 ft/min. The research objective is to identify the effectiveness of the LEV system using validation computational fluid dynamics (CFD) simulation. The data collected by experimental design during the pre-testing phase of the LEV system is quantitative and obtained through a fieldwork survey and document analysis. Findings found that LEV systems are effective to be used and meet all the minimum requirements set by the guideline. In CFD simulation, upon validation, the average absolute error obtained from the case study is 8.4%. There is good agreement between actual experimental and CFD simulation results, and the acceptable validity of CFD simulation is less than 10%. Therefore, simple CFD modeling is a tool to simulate air velocity in the LEV system, saving labor costs and time consumption during the earliest stage of LEV design development before actual construction. This study's outcome can serve as a benchmark or guideline for training facilities equipped with the LEV system to prioritize safety and health.

Available equipment for traumatic haemorrhage management in Austrian prehospital physician response units: a nationwide survey and analysis of guideline adherence

BackgroundTraumatic injuries, particularly those involving massive bleeding, remain a leading cause of preventable deaths in prehospital settings. The availability of appropriate emergency equipment is crucial for effectively managing these injuries, but the variability in equipment across different response units can impact the quality of trauma care. This prospective survey study evaluated the availability of prehospital equipment for managing bleeding trauma patients in Austria.MethodsA nationwide survey was conducted across 139 Austrian Prehospital Physician Response Units (PRUs) to evaluate the presence and adherence to guidelines of bleeding control equipment. The digitally distributed survey included questions on equipment types, such as pelvic binders, tourniquets, haemostatic gauze, and advanced intervention sets. Data were analysed against the most recent recommendations and guidelines to assess conformity and identify gaps.ResultsThe survey achieved a 96% response rate, revealing that essential equipment like pelvic binders and tranexamic acid was available in all units, with tourniquets present in 99% of them. However, few services carried advanced equipment for procedures like REBOA or thoracotomy. While satisfaction with the current equipment was high, with 80% of respondents affirming adequacy, the disparities in the availability of specific advanced tools highlight potential areas for improvement, offering a promising opportunity to enhance trauma care capabilities.ConclusionsWhile essential emergency equipment for haemorrhage control is uniformly available across Austrian PRUs, the variation in advanced tools underscores the need for standardised equipment protocols. The urgency for regular kit updates following prehospital guidelines and training is essential to enhance trauma care capabilities and ensure that all emergency response units are equipped to manage severe injuries effectively. This standardisation could lead to improved patient outcomes nationwide.

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.