Automatic Transfer Research Articles

Профіль ободу коліс вантажного вагона з перспективними візками для умов спільної експлуатації на українських і європейських залізницях

To solve the important problem of speeding up the integration of Ukraine into the European railway transportation, an interest has recently grown in the introduction of automatic car transfer from one track gauge to another using gauge-changeable wheelsets, thus dispensing with truck exchange or transshipment and thereby significantly shortening the delivery time. However, the combined operation of trains on the Ukrainian (1,520 mm gauge) and European (1,435 mm gauge) railways calls for the compatibility of the wheel-rail contact pair on both railways: R65 rails and a cant of 1/20 in Ukraine and UIC60 rails and a cant of 1/40 in Europe. The goal of this work is to develop a wheel profile for a freight car with prospective 18-7020 trucks for combined operation on the Ukrainian and European railways and predict the ride performance of a car with that wheel profile and its dynamic interaction with rails on both railways. An investigation was conducted into the wheel?rail interaction indices and the ride performance of a freight car with prospective 18-7020 trucks and wheels with existing profiles. It was shown that it is expedient to develop a new wheel profile to improve the service compatibility of the Ukrainian and European networks. A number of new wheel profiles were constructed, the efficiency of each profile in terms of dynamic stability at service speeds and wheel flange wear on the Ukrainian and European railways was calculated, and a compromise profile, ITM-73ES, was chosen. It was shown that the use of the chosen profile in a car with 18-7020 trucks will offer a high dynamic performance and improved indices of wheel?rail interaction for both truck gauges.

Smart Home System With Battery Backup and Internet of Things

This research enhances Smart Home Systems by integrating an Automatic Transfer Switch (ATS) for seamless power source switching between the grid and a backup battery, ensuring uninterrupted operation during power disruptions. An Automatic Battery Charging (ABC) system optimizes battery charging based on its condition, improving energy storage and efficiency. The system provides on-site electrical equipment control and sensor data access via a Human Machine Interface (HMI). Remote monitoring and control through the Blynk app offer convenience. Additionally, an energy consumption estimation feature allows users to estimate billing costs, with the Battery State of Charge (SoC) indicating the remaining battery capacity. Hardware testing showed the system's reliability with a 2-4 second ATS response and ±2-second ABC response. This research offers homeowners reliable power continuity and energy optimization. It contributes to IoT-based smart home systems, demonstrating ATS and ABC effectiveness, advancing both theory and practice for modern smart living.

Automatic Transfer Switch Kontrol Menggunakan Internet Of Thing (IoT)

This research aims to develop and implement an Automatic Transfer Switch (ATS) control system using the Internet of Things (IoT) within the Nurul Jadid University environment. ATS is an important device in an electrical distribution system that allows automation of switching between primary and backup electrical power sources in fault situations. By utilizing IoT technology, this research aims to improve the efficiency, performance and monitoring of ATS at Nurul Jadid University, The research methodology involves designing, manufacturing, and testing a prototype of an IoT-based ATS system. Smart sensors will be installed on ATS devices to monitor parameters such as voltage, current, temperature and device status. Data collected by sensors will be sent via the IoT network to a monitoring platform that can be accessed in real-time by operators and maintenance personnel. It is hoped that the results of this research will increase the availability and reliability of electricity supply at Nurul Jadid University, by enabling early detection and quick action in disturbance situations. In addition, this system will also help optimize the use of electrical resources and reduce unnecessary energy consumption.
 By combining IoT technology with ATS control, this research presents an innovative solution to increase the efficiency and reliability of electricity supply in university environments. The results of this research can be a guide for other institutions interested in adopting similar technology in their electricity resource management

Reinforcement Learning-Based Wind Farm Control: Toward Large Farm Applications via Automatic Grouping and Transfer Learning

The high system complexity and strong wake effects bring significant challenges to wind farm operations. Conventional wind farm control methods may lead to degraded power generation efficiency. A reinforcement learning (RL)-based approach is proposed in this paper to handle these issues, which can increase the long-term farm-level power generation subject to strong wake effects while without requiring analytical wind farm models. The proposed method is significantly distinct from existing RL-based wind farm control approaches, whose computational complexities usually increase heavily with the increase of total turbine numbers. In contrast, our method can greatly reduce training loads and enhance learning efficiency via two novel designs: (1) automatic grouping and (2) multi-agent-based transfer learning (MATL). Automatic Grouping can divide a large wind farm into small turbine groups by analyzing the aerodynamic interactions between turbines and utilizing some key principles from the graph theory. It enables the separated conduction of RL algorithms on small turbine groups, avoiding the complex training process and high computational costs of applying RL on the entire farm. Based on Automatic Grouping, MATL can further reduce the computational complexity by allowing agents (i.e. wind turbines) to inherit control policies under potential group changes. Case studies with a dynamical simulator show that the proposed method achieves clear power generation increases than the benchmark. It also dramatically reduces computational costs compared with typical RL-based wind farm control methods, paving the way for the application of RL in general wind farms.

Preliminary study of the dual power source system for 11kV manufacturing substation’s battery charger

In the future, renewable energy sources will be a more sustainable solution. Solar energy can be used by the factory to charge a substation’s battery charger. The plan is to use solar energy to charge a battery charger in a factory. Solar energy is more efficient than coal, petroleum, and natural gas. This paper demonstrates the design or reconstruction of an existing circuit drawing to achieve the goal of this project. The design incorporates a changeover switch to perform the power supply changeover for solar energy in order to compare the efficiency of the battery charger using solar power energy to the existing loads. The solar simulation will be built and performed by the MATLAB Simulink model for the simulation part. The PV array represents solar energy by stimulating the I-V and P-V for various irradiance (W/m2) and temperatures (oC). This project aims to improve the circuit design in the substation’s battery charger, develop a solar energy harvesting system, and create an efficient prototype of an energy storage automatic transfer switching system. As a result, this project helps to reduce the rate of global electricity consumption, which has an impact on the environment. Commercials’ pollution is significantly reduced by solar energy. We can demonstrate the global benefits and relevance of implementing this concept, particularly in our industry, by preparing this study. Solar energy is a dependable and cost-effective energy source. The sun is a renewable energy source. While fossil fuels will eventually run out, sunlight will not.

DESIGN AND CONSTRUCTION OF A SMART BLUETOOTH BASED AUTOMATIC TRANSFER SWITCH CHANGEOVER FOR SMALL HOUSEHOLD GENERATORS

The necessity to develop a cost-effective, smooth, and secure method to automate switching between different power sources resulted in this study. The paper proposes the use of an automatic transfer switch, which automatically switches between the utility power supply and a backup generator, to ensure uninterrupted power supply. The study aims to develop a cost-effective and secure system that utilizes an android device for remote control and monitoring of the power-generating unit. By employing Bluetooth technology, the study eliminates the delays and errors associated with manual source switching. The research specifically focuses on creating an automatic transfer switch compatible with 5 KVA key starter power generators and developing an android application for remote control within a 10-meter Bluetooth range. The system uses electromechanical and solid-state relays for the generator's start/stop sequence and power transmission, respectively.

Design of In-Orbit Sample Container Transfer Mechanism for Chang’E-5 Lunar Sample Return Mission

In this paper, a pawl composite linkage transfer mechanism is designed for the automatic in-orbit sample transfer mission of Chang’E-5 lunar sample return mission, which can realize the sample container in-orbit transfer under various critical constraints such as lightweight, miniaturization, and narrow working space. Resistance during the whole process as well as the sensitive factors that affect the resistance during the sample container transfer process are investigated and designed. The sample container transfer process has been verified by the test system on the ground, indicating that the design can satisfy the requirements of the sample transfer mission. The developed transfer mechanism completed the Chang’E-5 sample return mission successfully with good consistency between space and ground, verifying the correctness and effectiveness of the design.

IoT Monitoring for PV System Optimization in Hospital Environment Application

Purpose: The objective of this study is to implement IoT monitoring to remotely monitor PV system output and efficiency to ensure the continuous supply to ventilators and monitors in the ICU Room of RSI Siti Khadijah Palembang.
 Methodology/approach: The approach implemented in this study is by installing IoT Monitoring as an automatic transfer switch to ensure the continuous supply for the load.
 Results/findings: The IoT monitoring shows the real-time production of PV panels, battery capacity, and inverter output. Hence, the operator can monitor the PV system output and decide whether to keep using sources from PV panels or switch to grid utilities during cloudy/rainy days.
 Limitations: The IoT monitoring system has supervised the system's reliability, but it is necessary to improve the output and efficiency of the PV system by adding artificial intelligence algorithms and installing active cooling to prevent overheating.
 Contribution: This study shows the effectiveness of implementing IoT monitoring for the On-Grid PV system installed on the rooftop of RSI Siti Khadijah Palembang.

Automatic Transfer Switch (ATS) Using Omron CP1L PLC and Human Machine Interface

Airports in aviation services are required to use facilities with the latest technology. This requires a stable and uninterrupted electricity supply to operate correctly. The Automatic Transfer Switch design based on the CX-Designer Human Machine Interface moves the electrical power supply source from PLN to the Generator Set or vice versa. There are two operating modes, namely manual mode and auto mode. In operation, it is also equipped with an interlock function between the PLN contactor and the generator and a PLN phase loss sensor for the R, S and T phases. For auto mode, it uses a timer with a setting for PLN of 12 seconds and for the generator of 15 seconds. The control system uses an Omron CP1L-L20DR-D PLC with CX-Programmer programming for Human Machine Interface with CX-Designer. The Automatic Transfer Switch test was successful in system testing, starting from manual and auto mode, PLN phase loss testing, and timer testing; 100% of the entire hardware and software system ran well.

One year monitoring of an offshore wind turbine: Variability of modal parameters to ambient and operational conditions

This paper presents the variation of identified modal parameters of an offshore wind turbine (OWT) over one year of continuous monitoring. The considered OWT is a Haliade 150–6 MW GE turbine on a jacket substructure at the Block Island Wind Farm in Rhode Island, U.S. The turbine was instrumented with a monitoring system including accelerometers, strain gauges, inclinometers, and a data acquisition system with automatic data transfer to cloud storage. Continuous vibration measurements of the OWT have been collected over one year from April 2021 to April 2022. An automated output-only operational modal identification approach is developed to extract modal parameters of the OWT over this one-year period using windows of 10-min data. The identified modal parameters of the first few vibration modes show variability and correlation with several ambient and operational conditions. It is observed that the identified natural frequencies and damping ratios of the first side-to-side (SS) mode are stable over time and have very small variation, but those of the first fore-aft (FA) mode show significant variability. The second FA/SS modes can only be identified with reasonable accuracy when the turbine is in idle condition. Similar to the first FA/SS modes, the second FA mode has larger variability in frequencies and damping ratios than the second SS mode because of the aerodynamics effects. The system identification results over one full year verify the effectiveness and robustness of the proposed approach for long-term monitoring of this OWT and serve as the reference database.

Fully automatic transfer and measurement system for structural superlubric materials

Structural superlubricity, a state of nearly zero friction and no wear between two contact surfaces under relative sliding, holds immense potential for research and application prospects in micro-electro-mechanical systems devices, mechanical engineering, and energy resources. A critical step towards the practical application of structural superlubricity is the mass transfer and high throughput performance evaluation. Limited by the yield rate of material preparation, existing automated systems, such as roll printing or massive stamping, are inadequate for this task. In this paper, a machine learning-assisted system is proposed to realize fully automated selective transfer and tribological performance measurement for structural superlubricity materials. Specifically, the system has a judgment accuracy of over 98% for the selection of micro-scale graphite flakes with structural superlubricity properties and complete the 100 graphite flakes assembly array to form various pre-designed patterns within 100 mins, which is 15 times faster than manual operation. Besides, the system is capable of automatically measuring the tribological performance of over 100 selected flakes on Si3N4, delivering statistical results for new interface which is beyond the reach of traditional methods. With its high accuracy, efficiency, and robustness, this machine learning-assisted system promotes the fundamental research and practical application of structural superlubricity.

Integration of Home Automation and Security System Controller with FPGA Implementation

A home automation system is essential for promoting a safe and comfortable living environment and notable energy conservation for the user. However, the system’s favour had been obstructed by cost, power usage, inadequate security, complexity, and no emergency backup power. Current home automation systems with controllers were limited by their number of ports, fixed architecture, non-durable and non-parallel executions. Keeping this in view, integration of home comfort system, security system, and the automatic load transfer switch features are proposed using the base of Cyclone IV E: EP4CE115F29C7 FPGA Board (DE2-115). The top-level module is developed via Verilog Hardware Descriptive Language (HDL) with the bottom-up technique and used test bench for functional verification via ModelSim-Altera. The PWM method was applied to the lighting system to control the dimming of light through its digital signals via a maximum 500000 counter to improve energy efficiency for the proposed design. In this project, 200Hz pulses are successfully simulated to prevent visible flickering of lights in duty cycle generation. The light intensity of 40% and 100% are verified and successfully generated according to the inputs provided by the status of the LDR sensor and IR sensor. The proposed controller gives correct corresponding outputs to the 13 actuators based on the detected input stimuli. The proposed design utilized a total of 162 (<1%) logic elements, 32 registers, and total pins of 74 (14%). The proposed design successfully integrated the three-sub module and provided control on comfort and security system operations to prevent service failure during power blackout conditions at the top-level and utilized a low ratio of the FPGA.

Reinforcement learning methods for network-based transfer parameter selection

A significant challenge in self-driving technology involves the domain-specific training of prediction models on intentions of other surrounding vehicles. Separately processing domain-specific models requires substantial human resources, time, and equipment for data collection and training. For instance, substantial difficulties arise when directly applying a prediction model developed with data from China to the United States market due to complex factors such as differing driving behaviors and traffic rules. The emergence of transfer learning seems to offer solutions, enabling the reuse of models and data to enhance prediction efficiency across international markets. However, many transfer learning methods require a comparison between source and target data domains to determine what can be transferred, a process that can often be legally restricted. A specialized area of transfer learning, known as network-based transfer, could potentially provide a solution. This approach involves pre-training and fine-tuning "student" models using selected parameters from a "teacher" model. However, as networks typically have a large number of parameters, it raises questions about the most efficient methods for parameter selection to optimize transfer learning. An automatic parameter selector through reinforcement learning has been developed in this paper, named "Automatic Transfer Selector via Reinforcement Learning". This technique enhances the efficiency of parameter selection for transfer prediction between international self-driving markets, in contrast to manual methods. With this innovative approach, technicians are relieved from the labor-intensive task of testing each parameter combination, or enduring lengthy training periods to evaluate the impact of prediction transfer. Experiments have been conducted using a temporal convolutional neural network fully trained with the data from the Chinese market and one month's US data, focusing on improving the training efficiency of specific driving scenarios in the US. Results show that the proposed approach significantly improves the prediction transfer process.

Research on automatic matching of online mathematics courses and design of teaching activities based on multiobjective optimization algorithm.

The teaching of the optimization algorithm is a new kind of swarm intelligence optimization technique, which is superior in optimizing many simple functions. Still, it is not evident in processing some complex problems (group and teaching classification). Achieving automatic matching and knowledge transfer in online courses is imperative in mathematics education. This study proposes a design scheme MTCBO-LR (multiobjective capability optimizer-logistic regression), based on multitask optimization, which enables precise knowledge transfer and data interaction among many educators. It incorporates the standard TLBO algorithm to optimize, provides a variety of learning tactics for students at different stages of mathematics instruction, and is capable of adaptively adjusting these strategies in response to actual teaching needs. Experimental results on various datasets reveal that the proposed method enhances searchability and group diversity in various optimization extremes and outperforms similar methods in resolving to multitask teaching problems.

Automatic design-preserving virtual garment transfer

Design-preserving garment transfer which can transfer a garment from one body to another is a powerful technique in computer graphics. In this paper, we propose a novel method for automatic design-preserving garment transfer. Firstly, the correspondence between the source garment and the source body is automatically calculated by finding the nearest face’s barycenter from the garment to the body. Secondly, the mesh deformation transfer algorithm is utilized to obtain the target garment. After aligning the target garment and body with the ICP algorithm, the virtual fitting result can finally be obtained by fitting the target garment onto the target body. For a new garment worn on the source body, our approach can quickly and effectively transfer the garment to the target body while preserving the designed details. Two experiments were carried out to validate the applicability and effectiveness of our method. The results showed that our method could be applied to different garments for human bodies with different shapes and poses. Additionally, we introduced a new method for evaluating our transferred garments based on similarity and fit. Moreover, our approach can be applied to garments with different particle distances and performs better than the ‘Auto grading’ technique of CLO 3D. Our proposed method is simple, effective, automated and fast. Therefore, it has a significant potential for improving personalized garment development efficiency.

Coloration Parsing and Transfer Design of Han Folk Costumes

Traditional Costume Color has significant value of transmission and regeneration in contemporary design. In this article, we propose an automatic color parsing and transfer design system that assists designers to realize the creative design of the pattern color matching based on different traditional costume images and recommend sequence color schemes. The design system includes three modules: color extraction, automatic coloration, and color matching evaluation module. The adaptive bipartite k -means clustering algorithm is utilized to extract colors of each sample costume, while the genetic algorithm is applied to generate the optimal color matching scheme, and designers can participate in the design to obtain a satisfied scheme. The evaluation model combines the aesthetic measurement formula and the aesthetic measure of color harmony to evaluate the coloration quality. In the experiment, Jiangnan Han folk costumes are chosen as typical source samples to illustrate the effectiveness of the proposed method. Results show that different number of extracted colors and patterns can efficiently realize automatic coloration and can provide auxiliary decision-making for pattern color design in the fashion industry.

Penerapan Sistem ATS (Automatic Transfer Switch) sebagai Pengendalian, Pemantauan, dan Perawatan Berbasis IoT (Internet of Things)

The need for electricity is increasing along with population growth. The main electricity supply (PLN) is not always continuous in its distribution, so alternative power is needed, namely generators. The ATS (Automatic Transfer Switch) system can transfer the voltage source to the load. The ATS system is equipped with IOT in the form of a Blynk application on Android which functions as a controller and can send ATS damage notifications. This research was conducted to meet the electricity needs. Users can monitor, control and maintain the ATS system in the event of a breakdown. The method in this study uses a quantitative method, namely data collection by testing the ATS system and testing the IOT Blynk application function as a notification of damage to the ATS system. The result of transferring the PLN voltage to the generator is only 7 seconds and 3 seconds vice versa. There was damage to the lamp cable 1 time, the relay 1 time, and the fan cable 2 times. The results of measuring the current and voltage of the PLN source: lamp load 0.02A, 3.4V; fan 0.04A, 3.5V; AC motor 0.04A, 4V. Generator current and voltage measurements are as follows: lamp load 0.02 A, 9.1V; 0.03A, 9V fan; AC motor 0.05A, 4.5V.

Neural Rendering-Based 3D Scene Style Transfer Method via Semantic Understanding Using a Single Style Image

In the rapidly emerging era of untact (“contact-free”) technologies, the requirement for three-dimensional (3D) virtual environments utilized in virtual reality (VR)/augmented reality (AR) and the metaverse has seen significant growth, owing to their extensive application across various domains. Current research focuses on the automatic transfer of the style of rendering images within a 3D virtual environment using artificial intelligence, which aims to minimize human intervention. However, the prevalent studies on rendering-based 3D environment-style transfers have certain inherent limitations. First, the training of a style transfer network dedicated to 3D virtual environments demands considerable style image data. These data must align with viewpoints that closely resemble those of the virtual environment. Second, there was noticeable inconsistency within the 3D structures. Predominant studies often neglect 3D scene geometry information instead of relying solely on 2D input image features. Finally, style adaptation fails to accommodate the unique characteristics inherent in each object. To address these issues, we propose a novel approach: a neural rendering-based 3D scene-style conversion technique. This methodology employs semantic nearest-neighbor feature matching, thereby facilitating the transfer of style within a 3D scene while considering the distinctive characteristics of each object, even when employing a single style image. The neural radiance field enables the network to comprehend the geometric information of a 3D scene in relation to its viewpoint. Subsequently, it transfers style features by employing the unique features of a single style image via semantic nearest-neighbor feature matching. In an empirical context, our proposed semantic 3D scene style transfer method was applied to 3D scene style transfers for both interior and exterior environments. This application utilizes the replica, 3DFront, and Tanks and Temples datasets for testing. The results illustrate that the proposed methodology surpasses existing style transfer techniques in terms of maintaining 3D viewpoint consistency, style uniformity, and semantic coherence.

Development of a Genset Monitoring and Control System via PLC DSE 7420 MK II on Automatic Transfer Switch (ATS) and Automatic Mains Failure (AMF) Panels at PT. XYZ

Listrik merupakan kebutuhan utama bagi PT. XYZ dimana harus selalu aktif dan kontinu ke semua bagian devisi PT. XYZ, terlebih dikhususkan pada devisi TI dimana harus selalu tersuplai sumber listrik karena terkait pemantauan server jaringan dan keamanan data-data perusahaan yang harus selalu dipantau non-stop. Adapun permasalahan lainnya yang penulis dapatkan terkait belum ada parameter sensor engine yang mengharuskan operator untuk standby di lapangan pada saat terjadi pemadaman listrik PLN. Selain itu, untuk menjaga keawetan dan ketahanan usia genset perlu maintenance agar pada saat jadwal yang ditentukan untuk pengecekan maka akan menampilkan notifikasi alarm pada modul PLC ataupun pada SCADA. Metode yang digunakan pada penelitian ini adalah metode research and development yaitu pendekatan sistematis untuk mencari solusi baru, pengembangan sistem/inovasi baru untuk meningkatkan kinerja dari sistem kontrol dan monitoring genset di PT. XYZ. Adapun tujuan dari penelitian ini adalah untuk pengambilan data file lama pada Deep Sea 4620 dijadikan sebagai evaluasi perubahan, untuk monitoring dan tampilan notifikasi alarm parameter sensor engine, menampilkan notifikasi peringatan maintenance genset. Dari hasil penelitian tersebut dapat disimpulkan bahwa PLC Deep Sea 7420 MK II memudahkan operator untuk pengoperasian dan monitoring jarak jauh tanpa langsung turun lapangan, mampu mengontrol perpindahan daya dengan cepat (0,7 detik) sehingga server pada gedung devisi IT selalu aktif dan terjaga tanpa adanya pemadaman pada beban, mampu mengontrol dan memonitoring parameter sensor genset secara real time baik dari modul PLC, aplikasi SCADA Suite dan monitoring dari aplikasi web SCADA, mengoperasikan perawatan pemananasan genset setiap hari jumat pada pukul 17.30 WIB dengan durasi 10 menit, menampilkan notifikasi maintenance fuel bahan bakar saat mencapai 790 jam setara dalam 1 bulan dan memberi kemudahan dalam melakukan pemeliharaan secara rutin dan selain itu dengan adanya jadwal berkala memudahkan operator untuk perawatan berkala setiap bulan.

Prototype of Automatic Transfer Switch (ATS) for Solar Power Plant Based on Arduino Uno

Electrical energy plays an important role in supporting daily human activities. The need for electrical energy always increases according to population growth. However, the supply of electrical energy is not proportional to population growth. To meet the demand for electrical energy, it is necessary to develop and use alternative energy such as solar energy. In this paper, the prototype of Automatic Transfer Switch (ATS) for PLN and solar power plant (SPP) is carried out so that the supply of electrical energy to the load can be distributed continuously. ATS is electromechanical equipment that operates automatically to move the source of electrical energy from the main grid (PLN) network to SPP when the PLN network occur a faults or blackout. ATS will restore the source of electrical energy from PLN automatically when the supply of electrical energy from PLN has returned to normal condition. ATS components consist of voltage and current sensors, microcontroller and relay respectively. ATS use microcontroller Arduino Uno ATmega328 type to control the main switch (relay) automatically. The test results show that ATS succeeded in moving the source of electrical energy from PLN to SPP when there is a disturbance or blackout condition and ATS will returns the source of electrical energy to PLN when conditions back to normal.