System Equipment Research Articles

A novel coaxial heat pipe with an inner vapor tube for cooling high power electronic devices

Improving heat transfer limit of heat pipe is important for their application in high-power equipment system. Shear stress at the liquid–vapor interface affects the heat transfer capacity of heat pipe. In this study, a novel coaxial heat pipe is designed to eliminate vapor entrainment from interfacial shear stress for the first time. An inner thin-walled tube is sintered with the powder wick in the adiabatic section by one-step sintering process. The effects of filling ratio and powder size of sintered wick on the thermal performance of coaxial heat pipe are investigated experimentally. The results indicate that the optimal powder size range for the sintered wick of coaxial heat pipe is 106–125 μm, while the optimal filling ratio is about 125 %. It means that the sintered wick with 106–125 μm powder can achieve better trade-off between capillary performance and permeability. The coaxial heat pipe can operate at heat loads of 70 ∼ 140 W with the total thermal resistance less than 0.06 °C /W. Moreover, compared with the normal heat pipe, the heat transfer capacity of coaxial heat pipe is increased by 57 %, while the evaporation temperature is decreased by 9.6 ∼ 19.1 °C and the total thermal resistance is decreased by 41 %∼320 %. The inner tube can improve the replenishment efficiency of working liquid by eliminating interfacial shear stress, resulting in the significant heat transfer improvement. The design of coaxial heat pipe is an effective and low-cost solution to improve the thermal performance of heat pipe.

Evolution of Digital Health and Exploration of Patented Technologies (2017-2021): Bibliometric Analysis.

The significant impact of digital health emerged prominently during the COVID-19 pandemic. Despite this, there is a paucity of bibliometric analyses focusing on technologies within the field of digital health patents. Patents offer a wealth of insights into technologies, commercial prospects, and competitive landscapes, often undisclosed in other publications. Given the rapid evolution of the digital health industry, safeguarding algorithms, software, and advanced surgical devices through patent systems is imperative. The patent system simultaneously acts as a valuable repository of technological knowledge, accessible to researchers. This accessibility facilitates the enhancement of existing technologies and the advancement of medical equipment, ultimately contributing to public health improvement and meeting public demands. The primary objective of this study is to gain a more profound understanding of technology hotspots and development trends within the field of digital health. Using a bibliometric analysis methodology, we assessed the global technological output reflected in patents on digital health published between 2017 and 2021. Using Citespace5.1R8 and Excel 2016, we conducted bibliometric visualization and comparative analyses of key metrics, including national contributions, institutional affiliations, inventor profiles, and technology topics. A total of 15,763 digital health patents were identified as published between 2017 and 2021. The China National Intellectual Property Administration secured the top position with 7253 published patents, whereas Koninklijke Philips emerged as the leading institution with 329 patents. Notably, Assaf Govari emerged as the most prolific inventor. Technology hot spots encompassed categories such as "Medical Equipment and Information Systems," "Image Analysis," and "Electrical Diagnosis," classified by Derwent Manual Code. A patent related to the technique of receiving and transmitting data through microchips garnered the highest citation, attributed to the patentee Covidien LP. The trajectory of digital health patents has been growing since 2017, primarily propelled by China, the United States, and Japan. Applications in health interventions and enhancements in surgical devices represent the predominant scenarios for digital health technology. Algorithms emerged as the pivotal technologies protected by patents, whereas techniques related to data transfer, storage, and exchange in the digital health domain are anticipated to be focal points in forthcoming basic research.

Optimal placement of light sensor for improving energy efficiency and visual comfort in smart buildings

The energy consumed by artificial lighting accounts for a significant part of the energy consumption in buildings. Thus, energy consumption can be significantly decreased using optimization techniques, such as the optimum placement of the lighting sensors. In this paper, an optimal placement method of the light sensors is presented to minimize the lighting system's equipment costs and energy consumption and also meet visual comfort under the requirements of the European standard EN12464–1 regarding illuminance-based criteria. In the beginning, based on the illumination measurement grid's mathematical model, the potential location of the sensors is determined. As an average of the dimming levels of the LED lights, the objective function has been introduced. Then, the illuminance and uniformity levels are defined as constraints for the optimization problem. The Battle Royale Optimization (BRO) algorithm is used to solve the optimization problem. Ultimately, based on the results of the BRO algorithm and the calculation of the illuminance deviation, the optimal location of the light sensors is determined. The proposed method is tested in an office room. A fuzzy logic controller is developed to regulate the lighting control system's dimming levels to evaluate the proposed method's performance with other approaches. The comparison results have shown that the proposed method is superior as regards the number of sensors and the optimal sensor position, significant savings in energy consumption of up to 30.8%, and satisfactory visual comfort per the requirements of the European standard EN12464–1.

Localization for Dual Partial Discharge Sources in Transformer Oil Using Pressure-Balanced Fiber-Optic Ultrasonic Sensor Array.

The power transformer is one of the most crucial pieces of high-voltage equipment in the power system, and its stable operation is crucial to the reliability of power transmission. Partial discharge (PD) is a key factor leading to the degradation and failure of the insulation performance of power transformers. Therefore, online monitoring of partial discharge can not only obtain real-time information on the operating status of the equipment but also effectively predict the remaining service life of the transformer. Meanwhile, accurate localization of partial discharge sources can assist maintenance personnel in developing more precise and efficient maintenance plans, ensuring the stable operation of the power system. Dual partial discharge sources in transformer oil represent a more complex fault type, and piezoelectric transducers installed outside the transformer oil tank often fail to accurately capture such discharge waveforms. Additionally, the sensitivity of the built-in F-P sensors can decrease when installed deep within the oil tank due to the influence of oil pressure on its sensing diaphragm, resulting in an inability to accurately detect dual partial discharge sources in transformer oil. To address the impact of oil pressure on sensor sensitivity and achieve the detection of dual partial discharge sources under high-voltage conditions in transformers, this paper proposes an optical fiber ultrasonic sensor with a pressure-balancing structure. This sensor can adapt to changes in oil pressure environments inside transformers, has strong electromagnetic interference resistance, and can be installed deep within the oil tank to detect dual partial discharge sources. In this study, a dual PD detection system based on this sensor array is developed, employing a cross-positioning algorithm to achieve detection and localization of dual partial discharge sources in transformer oil. When applied to a 35 kV single-phase transformer for dual partial discharge source detection in different regions, the sensor array exhibits good sensitivity under high oil pressure conditions, enabling the detection and localization of dual partial discharge sources in oil and winding interturn without obstruction. For fault regions with obstructions, such as within the oil channel of the transformer winding, the sensor exhibits the capability to detect the discharge waveform stemming from dual partial discharge sources. Overall, the sensor demonstrates good sensitivity and directional clarity, providing effective detection of dual PD sources generated inside transformers.

Flood risk assessment of the Garita River in the urban zone of San Luis Potosí City, by hydrodynamic modeling

Rapid and uncontrolled urban growth and land use changes in watersheds worldwide have led to increased surface runoff within metropolitan areas, coupled with climate change, creating a risk for residents during the rainy season. The city of San Luis Potosí is no exception to this phenomenon. One affected watercourse is the Garita Stream, which flows inside the city near urbanization. It is essential to analyze the effects of urban sprawl on this stream based on historical precipitation data for the town. Hydrological and topographical information were required to conduct this research. The hydrological study of the basin involved analyzing the region’s geomorphology and historical climatological data. For the stream’s topography, aerial photogrammetry using an unmanned aerial Vehicle (UAV) and Global Navigation Satellite System (GNSS) equipment was employed to conduct topographic surveys in the area. To find out when the Garita stream would overflow and which areas are most likely to flood, numerical modeling was done using 1D, 2D, and 3D programs like SWMM5 (Storm Water Management Model), HEC-RAS (Hydrologic Engineering Center’s River Analysis System), and EDFC Explorer (Environmental Fluid Dynamics Code). These models simulated different return periods and their correlation with current flooding events recorded in the area, thereby further proposing solutions to mitigate overflow issues. By conducting these simulations and analyzing the results, solutions can be suggested to address the overflow problems in the area based on historical flood events at various return periods caused by the Garita Stream.

Monitoring the developmental trend and competitive landscape of natural gas hydrate through patent analysis.

Natural gas hydrate (NGH) is a significant alternative energy resource in achieving carbon neutrality. The developmental trend and competitive landscape of NGH exploitation and production are crucial for policymakers in government, managers of enterprises, and researchers. This study introduces a novel framework for conducting an in-depth analysis of NGH, integrating patentometrics, technology evolution, and correlation relationships to monitor developmental trends and competitive landscape through patent analysis. The results indicate that China, the USA, and Japan have distinct technology advantages. Current technological developments in the NGH field focus primarily on extraction technologies, equipment, and processing systems. The co-opetition analysis among countries reveals that the most extensive international cooperation network is primarily in Europe and the USA, with national partnerships in Asia concentrated in China and Japan. Institutional cooperation remains limited, primarily within universities in China, while both the USA and Japan foster collaboration between enterprises. The competitive landscapes of key NGH-related technologies among countries and institutions are also examined. This study contributes not only to monitoring the developmental trend and competitive landscape in NGH but also to providing policy recommendations for government and enterprises regarding strategic management and collaborative innovation.

Noise-resistant multi-frequency phase local radionavigation system based radio interference transmitters

Formulation of the problem. The widespread use of electronic warfare has led to significant difficulties in the use of consumer navigation equipment (CNE) of global navigation satellite systems (GNSS). Local radio navigation systems, alternatives to GNSS, are characterized by low accuracy and low noise immunity. At the same time, a spatially distributed system of radio interference transmitters CNE GNSS, using wide-band multi-frequency BPSK signals, can be used to organize a noise-resistant LRNS, in which phase measurements will be used to increase the accuracy of measurements. Purpose. The purpose of this work is to justify the requirements for a local radio navigation system based on spatially distributed radio interference transmitters NAP GNSS, using the noise-resistant method of multi-frequency phase radio navigation. Results. An interference-resistant method of multi-frequency phase radio navigation is presented, and the requirements for a local radio navigation system based on this method are substantiated. For the given typical characteristics of NAP GNSS radio interference transmitters, the value of the frequency detuning of the spectral components of the multi-frequency signal was obtained, at which the best positioning accuracy is achieved. Practical significance. The results obtained can be used to organize a noise-resistant multi-frequency phase local radio navigation system based on NAP GNSS radio interference transmitters.

Model for generating data from navigation sensors for assessing the spatial position of objects

When selecting or developing new algorithms for assessing the spatial position of objects based on data from consumer navigation equipment (CNA) of global navigation satellite systems (GNSS) and data from inertial MEMS modules, the task of generating test model input data that meets certain conditions arises. Such conditions include, for example, the requirements for limited time increments of elements of spatio-temporal trajectories and ease of formation of their characteristic sections. The characteristic sections of spatio-temporal trajectories can be sections of a stationary position – sections of “Rest” or sections of rectilinear movement. The importance of forming these areas is due to the need to test the potential capabilities of compared or developed algorithms for assessing the spatial position of objects to ensure an improvement in their accuracy characteristics in the presence of such areas in various conditions. A data generation model is proposed for comparing algorithms for estimating the spatial position of objects, which ensures that the time increments of elements of spatio-temporal trajectories are limited in time and the simple formation of their characteristic sections is met. The model is based on the selection of a set of specified parameters that would allow, on the one hand, to form characteristic sections of spatio-temporal trajectories, and, on the other hand, to obtain model output data of NAP GNSS and inertial MEMS modules. The selected set of specified model parameters is determined through a set of analytically specified functions with sequential calculation of their parameters, which is much simpler compared to traditional approaches that involve solving boundary value problems of optimal control with restrictions on the type of control functions or the construction and application of genetic models and algorithms. The use of the developed model makes it possible to generate test model input data for the selection or development of new algorithms for assessing the spatial position of objects, implemented in devices that include CNA of GNSS and inertial MEMS modules and produce results both in real time and in delayed time. The effectiveness of the proposed solution is confirmed by the criterion of suitability under the considered conditions.

Analysis of the features of the shielding system of polymer insulation structures of high voltage electrical equipment

In the article, the authors analysed the existing shielding systems of insulating structures of high-voltage devices together with electrodes under high potential. At the same time, the possibilities of using toroidal screens of various designs and the conditions of their installation in gas-filled equipment structures (gas-filled current and voltage measuring transformers, arresters, etc.) using polymer insulating materials are considered. Based on the analysis of literary sources, the most effective method of estimating the electric load parameters for determining the electric field strength distribution along the continuous insulating structure of gas-filled high-voltage devices with axial symmetry is proposed. This design is a support-insulating shell filled with SF6 as an internal insulating medium. Methodical materials are recommended that allow you to estimate the electrical load parameters (voltage and field strength) depending on the design features of the device and the shielding system used to level the electric field. Based on them, it is possible to evaluate the effectiveness of the calculation coefficients of the shielding system of gas-filled high-voltage equipment in the design process and during the improvement of individual design solutions. The results of the analytical evaluation by such methods are in good agreement with the data of experimental studies and statistical information obtained as a result of monitoring the work of insulating structures, taking into account real operating conditions and the influence of external factors. The introduction of the obtained materials allows you to take into account the influence of external factors and operational characteristics inherent in measuring transformers and overvoltage limiters. To explain the results of the analysis of methodical materials carried out in the article, as an example, the results of calculations of the support-insulation shell of the gas-filled current transformer of the TOG series, which was the most affected during operation, are given. in adverse conditions, given under such conditions as external pollution, humidity and their combination, as well as under conditions of overvoltage of various origins, etc. On the basis of the presented materials, it is possible to more accurately determine the effectiveness of various screenings. system, as well as how to predict the field strength distribution parameters under the influence of the shielding system, taking into account its design features. In addition, on the basis of the conclusions formed in the work, it is possible to plan and conduct an additional series of calculations and experimental tests taking into account the features of specific structures. Thus, the obtained results can be used to evaluate the external insulation parameters of both gas-filled measuring transformers and similar high-voltage equipment of distribution devices and transformer substations.

The Application of Electrical Automation Technology in Automobile Manufacturing

The application of information technology in electrical automation is gainning more momentum in the field of automobile manufacturing. High-quality electrical automation system enables the managers monitoring the various conditions of the system equipment in an allround way, and furthing interaction with the equipment, making the use of electrical equipment and related production equipment more scientific, thus not only improves the production efficiency, but also make automobile manufacturing more standardised, and effectively enhanced the efficiency of the entire industry. At the same time, there are still many problems with electrical automation technology in the manufacturing process. In order to ensure the efficiency of automobile manufacturing and promote the sustainable development of automobile manufacturing, there is an urgent need to strengthen the research and development investment.

Research on new method of transformer winding deformation detection

As one of the most important electrical equipment in power system, the stable operation of transformer is the key factor to ensure the safety of power grid system. Winding deformation is the most common fault of transformer, which will seriously affect the reliable operation of the whole power system. Therefore, the detection of transformer winding deformation is of great significance to prevent transformer accidents. In order to further improve the reliability of transformer winding deformation detection, this paper proposes a transformer winding deformation detection method based on oscillation wave method. Firstly, the equivalent circuit model of transformer winding is established, and the transformer winding fault is simulated by changing the inductance and capacitance parameters in the model, and the law between the change of oscillation wave curve and the change of related performance indexes and equivalent parameters is obtained. Finally, the field test verification is carried out on a 10 kV transformer in the laboratory. The results show that the oscillation wave method can diagnose the transformer winding deformation and can be used for the actual transformer winding deformation detection.

Intelligent Diagnosis Method of Transformer Based on Oil Chromatographic Data

Abstract As one of the most important equipment in the operation of power system, ensuring the safe and stable operation of power transformer is a prerequisite for ensuring the normal supply of power grid. The failure of the power transformer will lead to the interruption of the power supply of the power grid and cause huge losses to the national economy. With the rapid development of China’s power grid scale and the continuous improvement of the intelligent construction of modern power system, the number of power equipment such as transformers is increasing. Therefore, it is necessary to make timely and accurate judgment on the status of key power transformation and distribution equipment in the power system, and grasp the operation of electrical equipment in real time, so as to ensure the reliability of power supply in the power system. This paper takes 220kV oil-immersed transformer as the research object. This paper considers the problems and characteristics of the current transformer fault diagnosis methods. By making full use of dissolved gas analysis (DGA) information in oil, a method for diagnosing faults in electrical transformers based on particle swarm optimization and generalized regression neural networks has been proposed. The simulation comparison experiment is carried out to select the most suitable transformer intelligent diagnosis method based on oil chromatographic data.

Study on Breakdown Characteristics and Attenuation Characteristics of Air Mixed Gas

Abstract Nowadays, the global demand for environmental protection and energy saving is getting higher and higher. In the past, SF6 gas was regarded as an environmentally unfriendly gas in the circuit breaker with SF6 gas as the insulating medium. In order to save energy and reduce emissions, this paper uses clean and environmentally friendly air as the arc extinguishing medium. The gas mixture studied contains N2, O2 and CO2. Through two approximate values of Boltzmann equation, we obtain the electron energy distribution function of air mixed gas under different electric field reduction conditions. By studying the changes of ionization and adsorption coefficients of particles under various collision conditions, we obtained the conversion breakdown field strength (E/N) Cr of air mixture. An arc attenuation model is built to characterize the arc attenuation characteristics using the prior transport characteristics as input. The arc attenuation process is broken down into three steps: heat recovery, pre-ignition, and arcing. All of these phases are determined by the changes in axial temperature and arc conductance over time. Analysis is done on the air and nitrogen thermal recovery and pre-dielectric recovery phases. This study explores the use of clean dielectrics to ensure optimum performance of primary equipment in the power system, based on current circumstances.

Order reduction of special valve models based on pod method

Abstract The opening size of the disc-type special regulating valve (referred to as the special valve) can be used to regulate the fluid pressure and flow inside the cabin, and is an important equipment in the intake system of the high-altitude simulation test bench (referred to as the high-altitude bench). Due to the high dimensionality and complex solution of the special valve model, the calculation time is relatively long. In this paper, the Proper Orthogonal Decomposition (POD) model reduction method is applied to the mathematical model of the special valve, and the POD basis matrix is constructed through snapshots, thus obtaining a low-dimensional model and improving computational efficiency. The research results indicate that, while ensuring sufficient accuracy, this method can reduce the dimensionality of the special valve model, improve the computational speed of the simulator in calculating this case, and verify the effectiveness of the POD method.

Automatic detection system of secondary equipment in smart substation based on decision tree and support vector machine

Automatic detection system of secondary equipment in smart substation based on decision tree and support vector machine

Mise en place d’une antenne pharmaceutique de blocs opératoires dans un centre hospitalier universitaire

An operating room pharmaceutical unit centralizes medical devices and drugs for various surgical specialities. The aim of this work is to present the methodology used in our establishment to set up the operating room pharmaceutical unit. This approach involved the formation of multi-professional working groups. The needs of operating theatres were defined based on an analysis of healthcare product consumption and stock inventories. Material sheets were defined for each procedure. On the basis of simulations, material supply arrangements were selected, specifying material flows, equipment, workstations and information systems. Over 3200 healthcare product references were identified and 862 equipment files were created. Local stocks have been limited to medical trolleys for nursing staff. Emergency operating packs have been deployed for unforeseen operations. Cabinets have been dedicated to transporting re-sterilizable medical devices, and carts have been purchased for programmed operating packs. The equipment is made available by logistics agents and pharmacy assistants under pharmaceutical responsibility. This innovative approach is a model for facilities desiring to centralize and secure the logistics of healthcare products in the operating room. Ongoing adjustments will be required to meet new operating rooms needs.

Transformer Fault Diagnosis Based on Intelligent Algorithm and Partial Discharge

Abstract As an important part of power transmission and transformation equipment and power systems, transformers’ operating conditions will have a direct impact on the stability and reliability of the power system. In view of the problems of high diagnosis cost and low accuracy of diagnosis results in existing fault diagnosis technology, this paper uses the pulse current method to detect the pulse signal generated by the discharge model based on the partial discharge experimental platform data, analyzes and studies the discharge characteristics of different discharge defects, and draws For the partial discharge phase distribution (PRPD) spectrum of each defect type, the statistical characteristic parameters characterizing the characteristics of the spectrum were extracted. The partial discharge statistical characteristics were used as classification feature quantities and input into three network models: RBF, GRNN, and PSO-GRNN. The results show that PSO-GRNN has a good recognition effect and is suitable for partial discharge type identification. It has important practical significance and application value for the all-round health management of power transformers.

Integration of maintenance policy and statistical process monitoring for a cascade process with multiple assignable causes and random failures

This study develops an integrated model of statistical process monitoring and maintenance policy (MP) for a two-stage cascade process, involving two machines in series where the output of one stage affects the next stage. Instead of a single assignable cause (AC) affecting the quality characteristic, this production process experiences multiple ACs to more precisely simulate real conditions. Traditional and Hotelling’s T2 charts cannot detect the specific stage in which a shift occurs; therefore, this study employs a Cause-selecting control chart. The possibility of equipment failure and system stoppage are considered, with the process failure mechanism following a Weibull distribution. Depending on the conditions affecting the process or equipment, four MPs are considered to acheive the system’s initial condition, resulting in sixteen defined scenarios. The goal is to determine decision variables by minimizing a cost function subject to some statistical measures. This economic-statistical design can improve statistical and/or economic measures. However, it creates a more complex problem. Due to this complexity, a particle swarm optimization algorithm is used for optimization. The proposed model is implemented for a system that produces cotton yarn, with fiber length and skein strength are as the outputs of the first and second stages, respectively. Comparisons with two models validate the proposed model’s performance in cost reduction. A sensitivity analysis is performed for further investigations. The results indicate significant cost savings of the proposed model.

CO2 emission mitigation of a hybrid photovoltaic and cogeneration system in computer hardware manufacturing industry: A case study in Thailand

Abstract In the wake of COP26 and the growing urgency of addressing climate change, achieving carbon neutrality by 2050 has become a central global objective. This imperative extends to industries like computer hardware manufacturing, which are now actively pursuing decarbonization strategies through the strategic adoption of renewable energy sources and energy efficiency enhancements. This research paper assessed the CO2 emission mitigation potential of a hybrid system of photovoltaic (PV) roof and cogeneration where a large factory of computer hardware manufacturing in tropical Thailand was selected as a study site. On one hand, a one-Megawatt photovoltaic system was installed over the roof of the production building to generate electricity from solar radiation to serve the building. On the other hand, a twenty-four-Megawatt cogeneration system of gas engines as the prime mover was used to supply power to meet the building’s electricity demand. Waste heat from the gas engine was used by the absorption chiller to generate chilled water for cooling inside the building. Based on the system equipment specifications, the annual simulation using Thailand’s solar radiation showed that the installed photovoltaic system could generate electricity of 1,412.4 MWhelec/year while the implementation of the absorption chillers for cooling helped to reduce the electrical energy consumed by the traditional electric chiller by 10,211.4 MWhelec/year. In our study case where the CO2 emission of the grid power was 0.4758 kgCO2/kWhelec in the year 2022 and was reduced to 0.350 kgCO2/kWhelec in the year 2050, the total CO2 emission mitigation from the hybrid photovoltaic and cogeneration system with the genset efficiency of 50% and the waste heat recovery of 60% could reduce approximately 207,388.5TonCO2 for over 20 years as compared to the scenario where the grid electricity alone powered the building. These findings underscored the critical role of the proposed hybrid system in addressing the climate crisis and exemplified how the industry could make meaningful strides toward more environmental sustainability.

Rancang Bangun Alat Pendeteksi Kerusakan pada Bearing Kendaraan Angkut NPS 75 4x4 milik TNI Angkatan Darat Berbasis K- (Nearest Neightbor)

The Indonesian National Army (TNI) is a key element in maintaining national defense. However, challenges in the TNI's performance arise due to the need to modernize the main defense system equipment (alutsista) especially related to the condition of the NPS75 4x4 transport vehicle. One of the problems that often occurs is damage to wheel bearings, which can threaten personnel safety. Traditional methods such as listening to the sound of the engine and carrying out a physical inspection have been used before, but with the development of electronic technology, automatic devices can be created that monitor the condition of vehicle bearings using vibration detection. In this research, we propose the use of the Wemos D1 Mini which is connected to the driver's mobile phone via a WiFi network. This device uses the K-Nearest Neighbor (KNN) method to classify damage to bearings based on learning data. The aim is to assist in automatically detecting and classifying bearing damage categories on NPS75 4x4 transport vehicles, so that timely and targeted maintenance actions can be taken.