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Journal articles on the topic 'DC machine'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Głowacz, A., and Z. Głowacz. "Diagnostics of DC Machine Based on Analysis of Acoustic Signals with Application of MFCC and Classifier Based on Words." Archives of Metallurgy and Materials 57, no. 1 (March 1, 2012): 179–83. http://dx.doi.org/10.2478/v10172-012-0007-6.

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Diagnostics of DC Machine Based on Analysis of Acoustic Signals with Application of MFCC and Classifier Based on Words Technical diagnostics is concerned with the assessment of technical conditions of the machine through the study of properties of machine processes. Diagnostics is particularly important for factories and ironworks. In paper is presented method of diagnostics of imminent failure conditions of DC machine. This method is based on a study of acoustic signals generated by DC machine. System of sound recognition uses algorithms for data processing, such as Mel Frequency Cepstral Coefficient and classifier based on words. Software to recognize the sounds of DC machine was implemented on PC computer. Studies were carried out for sounds of faultless machine and machine with shorted coils. The results confirm that the system can be useful for diagnostics of dc and ac machines used in metallurgy.

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2

Irawan, Jessica Christiani, Ineke M. A. Pakereng, and Ramos Somya. "Perancangan dan Implementasi Finite Automata pada Simulasi Vending Machine." d'CARTESIAN 1, no. 1 (September 30, 2012): 42. http://dx.doi.org/10.35799/dc.1.1.2012.534.

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Abstract Language and Automata Theory is one of information technology’s component. This theory is the based of ideas and model of a computation system. One example of the Automata implementation is a vending machine. A vending machine can sell goods to customers without an operator to operate the machine. However, in Indonesia,the presence of vending machines are rarely seen. In this study, the author will try to learn about how a vending machine works, as well as to apply part of the Language and Automata Theory to design and create a simulation of a vending machine. As the result of the design and implementation of Finite Automata in vending machine simulation, it can be concluded that Finite Automata can be used for basic logic to make a vending machine simulation. Through this application simulation, user can get an experience in operating a vending machine and learn how to use the vending machine. Keywords: Language and Automata Theory, Finite Automata, Vending Machine, Simulation. Abstrak Teori bahasa dan automata merupakan salah satu komponen ilmu informat ika. Teori inilah yang mendasari ide dan model dari sebuah sistem komputasi. Salah satu contoh penerapan automata adalah pada vending machine. Vending machine dapat menjual barang-barang untuk konsumen tanpa adanya seorang operator. Namun, di Indonesia, keberadaan vending machine masih dapat dikatakan langka. Dalam penelit ian ini, akan dipelajari cara kerja vending machine, sekaligus diterapkan bagian dari Teori Bahasa dan Automata untuk merancang dan membuat simulasinya. Berdasarkan hasil perancangan dan implementasi Finite Automata pada simulasi vending machine, dapat diambil kesimpulan bahwa Finite Automata dapat dijadikan sebagai logika dasar untuk membuat simulasi vending machine. Melalui aplikasi simulasi ini, diharapkan user dapat memperoleh pengalaman dalam mengoperasikan sebuah vending machine serta mengetahui cara menggunakan sebuah vending machine. Kata Kunci : Teori Bahasa dan Automata, Finite Automata, Vending Machine, Simulasi.

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3

Zhang, Zi Qiang, and Z. H. Liu. "On Reconfigurable Machines and Reconfigurable Assembling Machine for DC Connector Plug." Materials Science Forum 628-629 (August 2009): 329–34. http://dx.doi.org/10.4028/www.scientific.net/msf.628-629.329.

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Reconfigurable machines are essential components to implement a reconfigurable manufacturing system. This paper focuses on one of reconfigurable machines: reconfigurable assembling machine. A reconfigurable automatic assembling machine for DC connector plug is designed. It can be divided into the basal module and the changeable module. The same basal module with different changeable module can be assembled into different special assembling machines for DC connector plug with different shape, size or number of electrodes.

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4

Ramesh, P., R. Gokulakrishnan, N. Sathyanarayanan, R. Hemantha Kumar, and N. C. Lenin. "Step by Step Design of Flux Switching Machine Using Electromagnetic Principle." Applied Mechanics and Materials 787 (August 2015): 869–73. http://dx.doi.org/10.4028/www.scientific.net/amm.787.869.

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Flux switching motor (FSM) is one of the classification of brushless DC motor. The major drawback of the conventional DC machine is presence of brushes and commutator. This makes conventional DC machines not suitable to operate in hazardous conditions. FSM is a type of brushless DC motor without commutator and rotor windings, which has the advantages of both conventional DC and switched reluctance machines. Here a step by step electromagnetic design of FSM using the basic reluctance principle. The designed parameters are verified using two dimensional finite element analysis (FEA). Finally, the analytical results are compared with the simulated results.

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5

Rizvi, Masood. "Sensitivity Analysis of Dc Machine." International Journal of Engineering Trends and Technology 38, no. 5 (August 25, 2016): 268–70. http://dx.doi.org/10.14445/22315381/ijett-v38p248.

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6

Mabhula, Mkhululi, Udochukwu B. Akuru, and Maarten J. Kamper. "Cross-Coupling Inductance Parameter Estimation for More Accurate Performance Evaluation of Wound-Field Flux Modulation Machines." Electronics 9, no. 11 (October 22, 2020): 1748. http://dx.doi.org/10.3390/electronics9111748.

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In this paper, a proposed numerical frozen permeability modeling procedure is fully derived to accurately estimate the parameters of two variants of wound-field flux modulation machines (WF-FMMs) namely: wound-field flux switching machine (WF-FSM) and DC-excited vernier reluctance machine (DC-VRM). During the procedure, the contribution of saturation to the variation of the machine parameters is investigated. The parameter variation effects on the machine performance is also investigated. It is shown that analysis of WF-FMMs is better understood by using the proposed procedure which computes accurately the machine parameters.

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7

Lee, Christopher, Kwok Chau, Tze Ching, and Ching Chan. "Design and Analysis of Partitioned-Stator Switched-Flux Dual-Excitation Machine for Hybrid Electric Vehicles." World Electric Vehicle Journal 9, no. 3 (September 4, 2018): 40. http://dx.doi.org/10.3390/wevj9030040.

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In this paper, an advanced partitioned-stator switched-flux dual-excitation (PS-SFDE) machine, which is highly suitable for hybrid electric vehicles (HEVs), is proposed. By artfully implementing two excitation sources, namely the high-power-density permanent-magnet (PM) source and the DC-field excitation source, the proposed machine can take benefits from both sides. Unlike the existing PS-SFDE machines that sacrifice the PM materials for DC-field winding accommodation, the proposed machine instead shares the space of the armature winding with the DC-field winding. Hence, comparable power and torque levels can be potentially achieved.

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8

Krismadinata, Krismadinata. "Human Machine Interface for Step-up DC-DC Converter." International Journal of Advanced Trends in Computer Science and Engineering 9, no. 4 (August 25, 2020): 6197–201. http://dx.doi.org/10.30534/ijatcse/2020/296942020.

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9

Prasad, C. L. V. R. S. V., G. V. S. S. Sharma, and P. N. L. Pavani. "Capability Resurrection of DC Sputtering Machine." International Journal of Surface Engineering and Interdisciplinary Materials Science 9, no. 1 (January 2021): 60–76. http://dx.doi.org/10.4018/ijseims.2021010104.

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Nanocoatings are gaining popularity owing to their widespread applications and the physical vapour deposition constitutes an effective method of deposition of coatings onto a suitable substrate. This work comprises of capability resurrection of a newly installed DC sputtering machine through troubleshooting, calibration, and establishment of process parameter mainly in terms of critical-to-performance (CTP) characteristic identified as the sputtering voltage. This work exercises the identification of potential causes for the breakdown of the sputtering machine through Ishikawa diagram and root cause is identified through the why-why analysis. Prioritization of corrective actions through process failure modes and effects analysis (PFMEA). Correct functioning of the DC sputtering machine after taking corrective action, is validated and confirmed through experimentation. This work shall serve as a reference to the maintenance and process personnel and guide them to perform the experiments related to DC sputtering in a laboratory environment.

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10

Lin, Feng, Ronghai Qu, Dawei Li, and Kangfu Xie. "A Fully Superconducting Homopolar DC Machine." IEEE Transactions on Applied Superconductivity 27, no. 4 (June 2017): 1–5. http://dx.doi.org/10.1109/tasc.2017.2677483.

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11

Husain, Tausif, Yilmaz Sozer, and Iqbal Husain. "DC-Assisted Bipolar Switched Reluctance Machine." IEEE Transactions on Industry Applications 53, no. 3 (May 2017): 2098–109. http://dx.doi.org/10.1109/tia.2017.2675363.

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12

Liang, Y. C., and V. J. Gosbell. "DC machine models for SPICE2 simulation." IEEE Transactions on Power Electronics 5, no. 1 (January 1990): 16–20. http://dx.doi.org/10.1109/63.45995.

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13

Tang, Y., J. J. H. Paulides, T. E. Motoasca, and E. A. Lomonova. "Flux-Switching Machine With DC Excitation." IEEE Transactions on Magnetics 48, no. 11 (November 2012): 3583–86. http://dx.doi.org/10.1109/tmag.2012.2199100.

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14

Bazhar, Sara, Baptiste Ristagno, Julien Fontchastagner, Noureddine Takorabet, and Nicolas Labbe. "New topology of direct current claw-pole machines for stop-start application." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 37, no. 5 (September 3, 2018): 1635–44. http://dx.doi.org/10.1108/compel-12-2017-0542.

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Purpose This paper aims to propose a new topology of direct current (DC) machine using claw-pole stator to replace standard DC starter in micro-hybrid vehicles. The main interest of such a topology is the reduction of copper volume. Design/methodology/approach The design of the claw-pole machine is based on a multi-objective optimization of several topologies, based on a three-dimensional (3D) reluctance network modeling. The 3D finite element (FE) model is used to check the results of the optimization, and a prototype is manufactured and tested with satisfactory results. Findings The claw-pole topology with wave-shape windings allows to replace the current DC series classical starter because of to its copper volume saving. Research limitations/implications This model is only limited to the optimization of the claw-pole stator for a fixed geometry of the rotor. Practical implications The research outcome shows that claw-pole machine can replace the series-excited DC machines of starters and at the same time achieve the same performance at reduced copper volume. Originality/value The paper deals with a new DC machine topology to reduce the copper volume through the suppression of the classical stator end-windings. The use of Claw-Pole inductors ensures this copper reduction.

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15

Mahobia, S. K. "STUDY AND ANALYSIS OF PERMANENT MAGNET DC MOTORS WITH VARIOUS PARAMETERS." International Journal of Research -GRANTHAALAYAH 5, no. 2 (February 28, 2017): 151–55. http://dx.doi.org/10.29121/granthaalayah.v5.i2.2017.1716.

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The permanent magnet type DC motors are used in various applications as heater, wiper. DC motors are any of a class of electrical machines that converts direct current electrical power into mechanical power. The DC motor has important role in moving machine because of mostly use in the industry appliances. The speed control of DC motor is increasingly getting sophisticated and precise. The Speed of the DC motor is controlled by with the help of controlling the stator winding voltage. There are various methods of speed control of DC drives namely field control.

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16

Jumayev, Sultan, Aleksandar Borisavljevic, Konstantin Boynov, Juha Pyrhönen, and Elena A. Lomonova. "Inductance calculation of high-speed slotless permanent magnet machines." COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering 34, no. 2 (March 2, 2015): 413–27. http://dx.doi.org/10.1108/compel-08-2014-0207.

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Purpose – The purpose of this paper is to give a simple, fast and universal inductance calculation approach of slotless-winding machines and comparison of inductances of toroidal, concentrated and helical-winding machines, since these winding types are widely used among low-power PM machines. Design/methodology/approach – Harmonic modeling approach is applied to model the magnetic field of the windings in order to calculate the synchronous inductances. The method is based on distinction between electromagnetic properties of different regions in the machine where each region is represented by its own governing equation describing the magnetic field. The governing equations are obtained from Maxwell’s equations by introducing vector potential in order to simplify the calculations. Findings – Results of the inductances of toroidal, concentrated and helical-winding slotless PM machines, which have the same torque and dimensions, obtained by the proposed analytical method are in good agreement with 3D FEM, where the relative difference is smaller than 15 percent. However, the calculation time of the analytical method is significantly less than in 3D FEM: seconds vs hours. Additionally, from the results it is concluded that the toroidal-winding machine has the highest inductance and DC resistance values among considered machines. Helical-winding machine has lowest inductance and DC resistance values. Inductance of concentrated-winding machine is between inductance of helical and toroidal windings; however, DC resistance of the concentrated windings is comparable with resistance toroidal windings. Originality/value – In this paper the inductance calculation based on harmonic modeling approach is extended for toroidal and helical-winding machines which makes the method applicable for most of the slotless machine types.

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17

Graffeo, Federica, Silvio Vaschetto, Alessio Miotto, Fabio Carbone, Alberto Tenconi, and Andrea Cavagnino. "Lumped-Parameters Thermal Network of PM Synchronous Machines for Automotive Brake-by-Wire Systems." Energies 14, no. 18 (September 8, 2021): 5652. http://dx.doi.org/10.3390/en14185652.

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Thermal analysis represents a key factor in electrical machine design due to the impact of temperature increase on insulation lifetime. In this context, there has been a wide investigation on thermal modeling, particularly for machines used in harsh working conditions. In this perspective, brake-by-wire (BBW) systems represent one of the most challenging applications for electrical machines used for automotive smart actuators. Indeed, electro-actuated braking systems are required to repeatedly operate the electric machine in high overload conditions in order to limit the actuator response time, as well as to enhance gravimetric and volumetric specific performance indexes. Moreover, BBW systems often impose unconventional supply conditions to the electric machine, consisting of dc currents in three-phase windings to keep the rotor fixed during the braking intervals. However, a dc supply leads to uneven temperature distributions in the machine, and simplified thermal models may not accurately represent the temperature variations for the different machine parts. Considering such unconventional supply conditions, this paper initially investigates the applicability of a conventional lumped-parameters thermal network (LPTN) based on symmetry assumptions for the heat paths and suitable for surface-mounted PM synchronous machines used in BBW systems. An extensive test campaign consisting of pulses and load cycle tests representative of the real machine operations was conducted on a prototype equipped with several temperature sensors. The comparison between measurements and predicted average temperatures, together with insights on the unbalanced heat distribution under the dc supply obtained by means of finite element analyses (FEA), paved the way for the proposal of a phase-split LPTN with optimized parameters. The paper also includes a critical analysis of the optimized parameters, proposing a simplified, phase-split lumped-parameters thermal model suitable to predict the temperature variations in the different machine parts for PM synchronous electric machines used in BBW systems.

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18

Zhu, Jian Feng, Peng Xiang Hua, Jun Bang Liu, Xin Wang, and Di Min Wu. "Research on Speed Control Problem of Industrial Sewing Machine System." Applied Mechanics and Materials 602-605 (August 2014): 1117–21. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.1117.

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This paper presents a new method of braking control related to the brushless DC Motor control industrial sewing machine system by analyzing the braking method of brushless DC Motor and the characteristics of control method concerning industrial sewing machines system. With the RENESAS SH7125 MCU as the core controlling, this paper analyzes from the both aspects of speed regulation and braking control, adopts oscillating circuit frequency input method for frequency control, reversing locking brake by detecting needle position signal. Practice proves that the method has achieved good effect, met the control requirements of the industrial sewing machine system.

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19

Takruri, Maen, Maissa Farhat, Oscar Barambones, José Antonio Ramos-Hernanz, Mohammed Jawdat Turkieh, Mohammed Badawi, Hanin AlZoubi, and Maswood Abdus Sakur. "Maximum Power Point Tracking of PV System Based on Machine Learning." Energies 13, no. 3 (February 5, 2020): 692. http://dx.doi.org/10.3390/en13030692.

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This project studies the conditions at which the maximum power point of a photovoltaic (PV) panel is obtained. It shows that the maximum power point is very sensitive to external disturbances such as temperature and irradiation. It introduces a novel method for maximizing the output power of a PV panel when connected to a DC/DC boost converter under variable load conditions. The main contribution of this work is to predict the optimum reference voltage of the PV panel at all-weather conditions using machine learning strategies and to use it as a reference for a Proportional-Integral-Derivative controller that ensures that the DC/DC boost converter provides a stable output voltage and maximum power under different weather conditions and loads. Evaluations of the proposed system, which uses an experimental photovoltaic dataset gathered from Spain, prove that it is robust against internal and external disturbances. They also show that the system performs better when using support vector machines as the machine learning strategy compared to the case when using general regression neural networks.

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Rodrigues, Sandy, Gerhard Mütter, Helena Geirinhas Ramos, and F. Morgado-Dias. "Machine Learning Photovoltaic String Analyzer." Entropy 22, no. 2 (February 11, 2020): 205. http://dx.doi.org/10.3390/e22020205.

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Photovoltaic (PV) system energy production is non-linear because it is influenced by the random nature of weather conditions. The use of machine learning techniques to model the PV system energy production is recommended since there is no known way to deal well with non-linear data. In order to detect PV system faults, the machine learning models should provide accurate outputs. The aim of this work is to accurately predict the DC energy of six PV strings of a utility-scale PV system and to accurately detect PV string faults by benchmarking the results of four machine learning methodologies known to improve the accuracy of the machine learning models, such as the data mining methodology, machine learning technique benchmarking methodology, hybrid methodology, and the ensemble methodology. A new hybrid methodology is proposed in this work which combines the use of a fuzzy system and the use of a machine learning system containing five different trained machine learning models, such as the regression tree, artificial neural networks, multi-gene genetic programming, Gaussian process, and support vector machines for regression. The results showed that the hybrid methodology provided the most accurate machine learning predictions of the PV string DC energy, and consequently the PV string fault detection is successful.

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21

Alhaqeem, Mohammed Abdul Aziz, and Aswardi Aswardi. "Human Machine Interface Visual Basic Arduino untuk DC – DC converter Type Buck." JTEIN: Jurnal Teknik Elektro Indonesia 2, no. 2 (July 17, 2021): 148–54. http://dx.doi.org/10.24036/jtein.v2i2.126.

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Pada era teknologi yang semakin berkembang pesat, penggunaan elektronika daya semakin banyak digunakan seperti untuk penggontrolan motor dan lain – lain. Untuk mendukung semua itu tentu juga di iringi dengan metode – metode interfacing yang memudahkan user dalam penggunaaan alat – alat elektronika daya seperti contohnya buck conveter. Interfacing yang di maksud disini adalah dengan melakukan pengaturan keluaran buck converter dengan menggunakan interfacing pada personal computer sekaligus memonitoringnya. Buck converter adalah jenis dc-dc converter yang berfungsi untuk mengubah keluaran tegangan output lebh kecil dibandingkan dengan tegangan keluaran input. Perancangan monitoring menggunakan visual basic dalam pembuatan interfacing, hal ini dilakukan karena kemudahan komunikasi antara visual basic dengan arduino. Metode pengontrolan menggunakan pengaturan duty cycle yang diberikan dari visual basic ke arduino. Dengan mengatur duty cycle, maka tegangan yang dkeluarkan pun akan berubah-ubah. Berdasarkan hasil pengujiaan, maka dengan memperbesar duty cycle maka keluaran tegangan dari buck converter akan semakin kecil, Dengan hasil pengukuran buck converter pada input tegangan 24 volt dan duty 15.97 menghasilkan tegangan keluaran sebesar 19,5 sedangkan pada duty cycle 34.57 menghasilkan tegangan sebesar 13.9.

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Samanta, Soumya, Jyoti Prakash Mishra, and Binoy Krishna Roy. "Virtual DC machine: an inertia emulation and control technique for a bidirectional DC–DC converter in a DC microgrid." IET Electric Power Applications 12, no. 6 (April 11, 2018): 874–84. http://dx.doi.org/10.1049/iet-epa.2017.0770.

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23

Kohara, Akira, Katsuhiro Hirata, Noboru Niguchi, and Kazuaki Takahara. "AC/DC current ratio in a current superimposition variable flux reluctance machine." Open Physics 16, no. 1 (May 24, 2018): 215–18. http://dx.doi.org/10.1515/phys-2018-0031.

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Abstract We have proposed a current superimposition variable flux reluctance machine for traction motors. The torque-speed characteristics of this machine can be controlled by increasing or decreasing the DC current. In this paper, we discuss an AC/DC current ratio in the current superimposition variable flux reluctance machine. The structure and control method are described, and the characteristics are computed using FEA in several AC/DC ratios.

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24

Grishina, Anastasiia, Marta Chinnici, Ah-Lian Kor, Eric Rondeau, and Jean-Philippe Georges. "A Machine Learning Solution for Data Center Thermal Characteristics Analysis." Energies 13, no. 17 (August 25, 2020): 4378. http://dx.doi.org/10.3390/en13174378.

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The energy efficiency of Data Center (DC) operations heavily relies on a DC ambient temperature as well as its IT and cooling systems performance. A reliable and efficient cooling system is necessary to produce a persistent flow of cold air to cool servers that are subjected to constantly increasing computational load due to the advent of smart cloud-based applications. Consequently, the increased demand for computing power will inadvertently increase server waste heat creation in data centers. To improve a DC thermal profile which could undeniably influence energy efficiency and reliability of IT equipment, it is imperative to explore the thermal characteristics analysis of an IT room. This work encompasses the employment of an unsupervised machine learning technique for uncovering weaknesses of a DC cooling system based on real DC monitoring thermal data. The findings of the analysis result in the identification of areas for thermal management and cooling improvement that further feeds into DC recommendations. With the aim to identify overheated zones in a DC IT room and corresponding servers, we applied analyzed thermal characteristics of the IT room. Experimental dataset includes measurements of ambient air temperature in the hot aisle of the IT room in ENEA Portici research center hosting the CRESCO6 computing cluster. We use machine learning clustering techniques to identify overheated locations and categorize computing nodes based on surrounding air temperature ranges abstracted from the data. This work employs the principles and approaches replicable for the analysis of thermal characteristics of any DC, thereby fostering transferability. This paper demonstrates how best practices and guidelines could be applied for thermal analysis and profiling of a commercial DC based on real thermal monitoring data.

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Fujiwara, Shuhei, Akiko Takeda, and Takafumi Kanamori. "DC Algorithm for Extended Robust Support Vector Machine." Neural Computation 29, no. 5 (May 2017): 1406–38. http://dx.doi.org/10.1162/neco_a_00958.

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Nonconvex variants of support vector machines (SVMs) have been developed for various purposes. For example, robust SVMs attain robustness to outliers by using a nonconvex loss function, while extended [Formula: see text]-SVM (E[Formula: see text]-SVM) extends the range of the hyperparameter by introducing a nonconvex constraint. Here, we consider an extended robust support vector machine (ER-SVM), a robust variant of E[Formula: see text]-SVM. ER-SVM combines two types of nonconvexity from robust SVMs and E[Formula: see text]-SVM. Because of the two nonconvexities, the existing algorithm we proposed needs to be divided into two parts depending on whether the hyperparameter value is in the extended range or not. The algorithm also heuristically solves the nonconvex problem in the extended range. In this letter, we propose a new, efficient algorithm for ER-SVM. The algorithm deals with two types of nonconvexity while never entailing more computations than either E[Formula: see text]-SVM or robust SVM, and it finds a critical point of ER-SVM. Furthermore, we show that ER-SVM includes the existing robust SVMs as special cases. Numerical experiments confirm the effectiveness of integrating the two nonconvexities.

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Hajihosseini, Mojtaba, Milad Andalibi, Meysam Gheisarnejad, Hamed Farsizadeh, and Mohammad-Hassan Khooban. "DC/DC Power Converter Control-Based Deep Machine Learning Techniques: Real-Time Implementation." IEEE Transactions on Power Electronics 35, no. 10 (October 2020): 9971–77. http://dx.doi.org/10.1109/tpel.2020.2977765.

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27

Wu, Xu Sheng, and Wei Gao. "Research on Stator Winding Leakage Reactance Calculation of Double-Winding AC-DC Generator." Advanced Materials Research 383-390 (November 2011): 6861–67. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.6861.

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Double-winding AC-DC Generator are being widely used in self-contained electrical power systems for their obvious virtues. On their stator, two separate windings are distributed, one three-phase winding delivers AC power and the other twelve-phase winding, termed DC windings, are connected to the bridge rectifier to supply DC power. Unlike ordinary three-phase machines, there are four layers winding in each stator slot of the Double-winding AC-DC Generator and the total gap magnetic potential produced by the twelve-phase winding is more complex than 3-phase machines. By analyzing the leakage magnetic flux and the magnetic potential, relevant formulas are derived to calculate the leakage reactance of the machines. All the stator leakage reactance of a realistic Double-winding AC-DC Generator was calculated through the methods presented and the simulation of a sudden shortcut test of the machine was carried out with the parameters calculated. The simulation and test results agree quite well, and show that the formulas presented are correct.

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Gaiceanu, Marian, Cristian Eni, and Mihaita Coman. "Adaptive Control with Supraunitary Relative Degree for the DC Electrical Machine." Advanced Materials Research 677 (March 2013): 480–84. http://dx.doi.org/10.4028/www.scientific.net/amr.677.480.

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In order to obtain an appropriate control for the electrical drive systems the real parameters values must be known accurately. Moreover, due to the parametric and structural uncertainty of the DC drive system, an adaptive control method is necessary. Therefore, a new model reference adaptive control (MRAC) for DC drives is proposed in this paper. MRAC ensures on-line adjustment of the control parameters with DC machine parameter variation. The adaptive control developed in this paper assures the asymptotic cancellation of the tracking error, fast and smooth responses of the DC drive without knowing a priory any information about the DC drive parameters. The simulation results show the validity of the proposed solution.

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Wei, Jia Dan, Bo Zhou, Chu Han, Chang Chun Chen, and Qing Tang Deng. "A Novel Open-Winding Permanent Magnetic Starter-Generator for Vehicles." Advanced Materials Research 433-440 (January 2012): 2427–33. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.2427.

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This paper presents the analysis, design and implementation of a novel open-winding permanent magnetic starter-generator using the open-winding permanent magnetic machine for overcoming the difficulties of voltage regulation, narrow speed range and low power factor of the permanent magnetic machine for the vehicles applications. In the proposed method, one side of the open-winding permanent magnetic machine is connected to rectifier for the DC voltage output, the other is connected to the inverter for the regulation of the DC voltage. And the open-winding machine can be reconstructed to be the conventional machine as the starter. In contrast to the conventional starter-generator for the vehicle, the speed range of the generation process and efficiency of the machine are improved obviously. A new control algorithm of double-loop for regulation of the DC voltage and current of machine is developed and verified by the simulation results.

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30

Wang, Shusen. "A Sharper Generalization Bound for Divide-and-Conquer Ridge Regression." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 5305–12. http://dx.doi.org/10.1609/aaai.v33i01.33015305.

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We study the distributed machine learning problem where the n feature-response pairs are partitioned among m machines uniformly at random. The goal is to approximately solve an empirical risk minimization (ERM) problem with the minimum amount of communication. The divide-and-conquer (DC) method, which was proposed several years ago, lets every worker machine independently solve the same ERM problem using its local feature-response pairs and the driver machine combine the solutions. This approach is in one-shot and thereby extremely communication-efficient. Although the DC method has been studied by many prior works, reasonable generalization bound has not been established before this work.For the ridge regression problem, we show that the prediction error of the DC method on unseen test samples is at most ε times larger than the optimal. There have been constantfactor bounds in the prior works, their sample complexities have a quadratic dependence on d, which does not match the setting of most real-world problems. In contrast, our bounds are much stronger. First, our 1 + ε error bound is much better than their constant-factor bounds. Second, our sample complexity is merely linear with d.

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Dhannur, Somashekhar V. "Low Cost Noodles Making Machine." International Journal for Research in Applied Science and Engineering Technology 9, no. VIII (August 15, 2021): 649–51. http://dx.doi.org/10.22214/ijraset.2021.37390.

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This project aims to assist people in making noodles easily, quickly and on a wider scale. The primary stage of the project with brainstorming, visualizing the thought, forecasting all our needs within the project and deeper research was held between all competitive noodle machines within the market. Proposed Noodle machine with compact Design, portable and operated by the only person. Extrusion of noodle at shaping die by endless feed of dough within the hopper which is pushed towards shaping die by thread conveyor to realize the specified shape of noodle. Design and development of noodle machine by integrating all ideas together and testing of Automatic noodle machine which is operated by DC-power source.

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Sami, Saif Sabah, Zeyad Assi Obaid, Mazin T. Muhssin, and Ali N. Hussain. "Detailed modelling and simulation of different DC motor types for research and educational purposes." International Journal of Power Electronics and Drive Systems (IJPEDS) 12, no. 2 (June 1, 2021): 703. http://dx.doi.org/10.11591/ijpeds.v12.i2.pp703-714.

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The devastating impact of Covid-19 pandemic accelerated the shift to e-learning in the higher education. Particularly in the electrical machines courses, that often include laboratory experiments. However, no detailed models of DC motors, developed in MATLAB/Simulink, were reported in literature. Hence, in this paper, a virtual laboratory consist of models of DC motors was built for the first time. The proposed models are easy to use and modify, and allow all machines’ parameters to be altered for students to replicate easily to support and enhance the learning process of electrical machines courses. Consequently, the developed models are effective tools for educational and research purposes. Dynamic models of DC motors were developed using MATLAB/Simulink, namely separately excited, permanent magnet, shunt-connected and series-connected DC motors. Two different approaches for modelling were proposed, the block diagram representation and Simscape based models. The two modelling methods were validated against the built-in DC machine model. The proposed models are easy to use and modify, and allow all machines’ parameters to be altered for monitoring and comparison purposes. Consequently, the developed models are effective tools for research and educational purposes.

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Nakamura, Setsuo, and Noboru Morita. "Quantitative evaluation for transient commutation of DC machine." IEEJ Transactions on Industry Applications 108, no. 7 (1988): 691–98. http://dx.doi.org/10.1541/ieejias.108.691.

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Graham, Marcus L., and Sheldon Gruber. "Simulation Study of an Electronically Commutated DC Machine." IEEE Transactions on Industrial Electronics IE-32, no. 4 (November 1985): 399–405. http://dx.doi.org/10.1109/tie.1985.350116.

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PEURO, E., M. LECRIVAIN, M. K. GABSI, and J. F. RIALLAND. "MEASUREMENT AND MODELING OF THE DC MACHINE INDUCTANCES." Electric Machines & Power Systems 22, no. 1 (January 1994): 77–85. http://dx.doi.org/10.1080/07313569408955554.

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36

Ramshaw, R. S., and G. Xie. "Dual model of a DC machine with gyrators." IEE Proceedings B Electric Power Applications 132, no. 1 (1985): 57. http://dx.doi.org/10.1049/ip-b.1985.0005.

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37

Nakamura, Setsuo, and Noboru Morita. "Quantitative evaluation of transient commutation of DC machine." Electrical Engineering in Japan 108, no. 4 (1988): 126–35. http://dx.doi.org/10.1002/eej.4391080414.

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Linares-Flores, Jesús, Alberto Antonio-García, and Antonio Orantes-Molina. "Arranque suave para un motor de CD a través de un convertidor reductor CD-CD." Ingeniería, investigación y tecnología 12, no. 2 (April 1, 2011): 137–48. http://dx.doi.org/10.22201/fi.25940732e.2011.12n2.014.

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Zhang, Li Rong, Jing Zhou Zhang, Guo Dong, and Yang Ming. "Modeling and Simulation of Permanent Magnet Machines Output Voltage Conditioning in the Air Three Generator." Advanced Materials Research 588-589 (November 2012): 618–21. http://dx.doi.org/10.4028/www.scientific.net/amr.588-589.618.

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The main role of the permanent magnet machine in the aviation frequency alternator is as the exciter. Its main function is not only to supply power for the generator controller but also supply the excitation current to exciter by supplying field winding of exciter with DC excitation voltage in the case without the emergency power. So we have to rectify 115V AC of permanent magnet machine output and make DC/DC conversion, so that the output is the suitable DC voltage. In the actual, it is very troublesome to make parameter tuning to rectifier module and DC/DC module, so this it is necessary to make model and simulation research. In this paper, we make module, simulation and parameter tuning for the rectifier and DC/DC transformation module in the MATLAB environment. From the simulation results, we can get that the model is correct, the parameters are appropriate.

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Lu, Yuzhen, and Renfu Lu. "Detection of Surface and Subsurface Defects of Apples Using Structured- Illumination Reflectance Imaging with Machine Learning Algorithms." Transactions of the ASABE 61, no. 6 (2018): 1831–42. http://dx.doi.org/10.13031/trans.12930.

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Abstract. Machine vision technology coupled with uniform illumination is now widely used for automatic sorting and grading of apples and other fruits, but it still does not have satisfactory performance for defect detection because of the large variety of defects, some of which are difficult to detect under uniform illumination. Structured-illumination reflectance imaging (SIRI) offers a new modality for imaging by using sinusoidally modulated structured illumination to obtain two sets of independent images: direct component (DC), which corresponds to conventional uniform illumination, and amplitude component (AC), which is unique for structured illumination. The objective of this study was to develop machine learning classification algorithms using DC and AC images and their combinations for enhanced detection of surface and subsurface defects of apples. A multispectral SIRI system with two phase-shifted sinusoidal illumination patterns was used to acquire images of ‘Delicious’ and ‘Golden Delicious’ apples with various types of surface and subsurface defects. DC and AC images were extracted through demodulation of the acquired images and were then enhanced using fast bi-dimensional empirical mode decomposition and subsequent image reconstruction. Defect detection algorithms were developed using random forest (RF), support vector machine (SVM), and convolutional neural network (CNN), for DC, AC, and ratio (AC divided by DC) images and their combinations. Results showed that AC images were superior to DC images for detecting subsurface defects, DC images were overall better than AC images for detecting surface defects, and ratio images were comparable to, or better than, DC and AC images for defect detection. The ensemble of DC, AC, and ratio images resulted in significantly better detection accuracies over using them individually. Among the three classifiers, CNN performed the best, with 98% detection accuracies for both varieties of apples, followed by SVM and RF. This research demonstrated that SIRI, coupled with a machine learning algorithm, can be a new, versatile, and effective modality for fruit defect detection. Keywords: Apple, Defect, Bi-dimensional empirical mode decomposition, Machine learning, Structured illumination.

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Al Badwawi, Rashid, Mohammad Abusara, and Tapas Mallick. "Speed control of synchronous machine by changing duty cycle of DC/DC buck converter." AIMS Energy 3, no. 4 (2015): 728–39. http://dx.doi.org/10.3934/energy.2015.4.728.

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Zhi, Na, Ke Ding, Liang Du, and Hui Zhang. "An SOC-Based Virtual DC Machine Control for Distributed Storage Systems in DC Microgrids." IEEE Transactions on Energy Conversion 35, no. 3 (September 2020): 1411–20. http://dx.doi.org/10.1109/tec.2020.2975033.

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Pishbahar, Hesam, Hassan Moradi CheshmehBeigi, Navid Piri Yengijeh, and Shokoofeh Bagheri. "Inertia emulation with incorporating the concept of virtual compounded DC machine and bidirectional DC–DC converter for DC microgrid in islanded mode." IET Renewable Power Generation 15, no. 8 (March 15, 2021): 1812–25. http://dx.doi.org/10.1049/rpg2.12150.

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Muzzammel, Raheel, and Ali Raza. "A Support Vector Machine Learning-Based Protection Technique for MT-HVDC Systems." Energies 13, no. 24 (December 17, 2020): 6668. http://dx.doi.org/10.3390/en13246668.

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High voltage direct current (HVDC) transmission systems are suitable for power transfer to meet the increasing demands of bulk energy and encourage interconnected power systems to incorporate renewable energy sources without any fear of loss of synchronism, reliability, and efficiency. The main challenge associated with DC grid protection is the timely diagnosis of DC faults because of its rapid built up, resulting in failures of power electronic circuitries. Therefore, the demolition of HVDC systems is evaded by identification, classification, and location of DC faults within milliseconds (ms). In this research, the support vector machine (SVM)-based protection algorithm is developed so that DC faults could be identified, classified, and located in multi-terminal high voltage direct current (MT-HVDC) systems. A four-terminal HVDC system is developed in Matlab/Simulink for the analysis of DC voltages and currents. Pole to ground and pole to pole faults are applied at different locations and times. Principal component analysis (PCA) is used to extract reduced dimensional features. These features are employed for the training and testing of SVM. It is found from simulations that DC faults are identified, classified, and located within 0.15 ms, ensuring speedy DC grid protection. The realization and practicality of the proposed machine learning algorithm are demonstrated by analyzing more straightforward computations of standard deviation and normalization.

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Skarpetowski, Grzegorz. "Realisation of the mechanical characteristic of a series excited DC machine in the drive with converter – fed induction machine." MATEC Web of Conferences 180 (2018): 01007. http://dx.doi.org/10.1051/matecconf/201818001007.

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A control algorithm for converter-fed induction machines, which allows the operation of the drive along of mechanical characteristic similar to the characteristic of series-excited direct current machine especially suitable for adhesion traction drives, is presented.

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46

Stein, J. L., and Kyung-Chul Shin. "Current Monitoring of Field Controlled DC Spindle Drives." Journal of Dynamic Systems, Measurement, and Control 108, no. 4 (December 1, 1986): 289–95. http://dx.doi.org/10.1115/1.3143796.

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Unmanned machine tools as part of an automated factory require reliable inexpensive sensors to provide machine and process information. The electric current in the DC motor of a CNC machine tool can be inexpensively measured and used to calculate loads on the drive system. To characterize the bandwidth, sensitivity and accuracy of current monitoring on a DC field controlled spindle drive of a CNC lathe, a dynamic lumped parameter model of this sensor system is developed. The model is used to identify the system components that have a dominant effect on the behavior of the sensor when the spindle system is operated above the base speed. Tests were conducted to determine the model’s parameters and to verify the model. The bandwidth and sensitivity of this sensor are shown to be spindle speed dependent. High speeds improve sensitivity and reduce bandwidth. Sensitivity and bandwidth vary by factors of 4.3 and 18.5, respectively, over the speed range. The signal to noise ratio is limited by external load induced variations in the spindle system friction. Recommendations concerning machine designs and process operating conditions to improve current monitoring on spindle drives are presented.

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Nakamura, Setsuo, Noboru Morita, and Satoshi Tokoh. "DC machine commutation, in case of repetitive peak load." IEEJ Transactions on Industry Applications 108, no. 11 (1988): 1025–32. http://dx.doi.org/10.1541/ieejias.108.1025.

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Godoy Simões, M., and P. Vieira. "A Five-Phase Brushless Dc-Machine Direct Drive System." EPE Journal 14, no. 3 (August 2004): 15–24. http://dx.doi.org/10.1080/09398368.2004.11463561.

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Madawala, U. K., and J. T. Boys. "Magnetic field analysis of an ironless brushless DC machine." IEEE Transactions on Magnetics 41, no. 8 (August 2005): 2384–90. http://dx.doi.org/10.1109/tmag.2005.852952.

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Yang, Hui, Shukang Lyu, Heyun Lin, Z. Q. Zhu, Fei Peng, Erxing Zhuang, Shuhua Fang, and Yunkai Huang. "Stepwise Magnetization Control Strategy for DC-Magnetized Memory Machine." IEEE Transactions on Industrial Electronics 66, no. 6 (June 2019): 4273–85. http://dx.doi.org/10.1109/tie.2018.2860544.

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