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Zeitschriftenartikel zum Thema „Machine control system“

Autor: Grafiati

Veröffentlicht am 28. Juni 2021

Zuletzt aktualisiert am 13. Februar 2022

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1

YAMAMOTO, Takashi, Michihiro OSHIMA, Yoshio YOKOYAMA und Toshio MIYAGI. „High-precision Grinding System utilizing Machine Vision Control Unit(Advanced machine tool)“. Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2005.2 (2005): 439–42. http://dx.doi.org/10.1299/jsmelem.2005.2.439.

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2

Chiuso, A., und G. Pillonetto. „System Identification: A Machine Learning Perspective“. Annual Review of Control, Robotics, and Autonomous Systems 2, Nr. 1 (03.05.2019): 281–304. http://dx.doi.org/10.1146/annurev-control-053018-023744.

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Estimation of functions from sparse and noisy data is a central theme in machine learning. In the last few years, many algorithms have been developed that exploit Tikhonov regularization theory and reproducing kernel Hilbert spaces. These are the so-called kernel-based methods, which include powerful approaches like regularization networks, support vector machines, and Gaussian regression. Recently, these techniques have also gained popularity in the system identification community. In both linear and nonlinear settings, kernels that incorporate information on dynamic systems, such as the smoothness and stability of the input–output map, can challenge consolidated approaches based on parametric model structures. In the classical parametric setting, the complexity of the model (the model order) needs to be chosen, typically from a finite family of alternatives, by trading bias and variance. This (discrete) model order selection step may be critical, especially when the true model does not belong to the model class. In regularization-based approaches, model complexity is controlled by tuning (continuous) regularization parameters, making the model selection step more robust. In this article, we review these new kernel-based system identification approaches and discuss extensions based on nuclear and [Formula: see text] norms.

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Liu, Rui, Gui Xi Liu, Peng Ju Chang, Wei Hua He und Zeng Jian Huang. „Control System of PDP Lighting Inspection Machine“. Applied Mechanics and Materials 130-134 (Oktober 2011): 1903–6. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.1903.

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The test of panel’s display effect is a key step in the panel production. Lighting inspection machines test the electrical, optical and surface information of Plasma Display Panels (PDPs). This machine is based on a PLC control system and a color analysis system. The PLC system controls a visual positioning system and links to Manufacturing Execution System (MES) and a panel conveyor. This paper considers the structure design and action workflow of the lighting inspection machine. Multi-layer network is built to connect with the whole production system. Optional operation modes are designed in control program and Man-machine interface is introduced to facilitate the operation.

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4

Sui, Xiu Lin, Zheng Wei Kong, Jia Tai Zhang und Xiao Ping Yang. „Study of Virtual Numerical Control Milling Simulation System“. Key Engineering Materials 407-408 (Februar 2009): 174–79. http://dx.doi.org/10.4028/www.scientific.net/kem.407-408.174.

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Virtual numerical control milling simulation system, based on UG, is studied oriented to low utilization of NC machines. A virtual machine tools library, standard fixture library and visual machine tool processing environment were established by the second development techniques of UG and VC++. Through the example of XH715 NC machine center, tool path and motion of miller were simulated separately; at last processing scheme was evaluated and optimized. The experimental results show this system possesses good utility, and the utilization of machine tools could thus be improved.

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Freeman William, T., und D. Weissman Craig. „Hand gesture machine control system“. Computer Integrated Manufacturing Systems 10, Nr. 2 (Mai 1997): 175. http://dx.doi.org/10.1016/s0951-5240(97)84336-4.

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6

Pang, J., C. Chen, C. Wang, Y. Wang und Y. Shu. „HT-7 machine control system“. IEEE Transactions on Nuclear Science 41, Nr. 1 (1994): 181–83. http://dx.doi.org/10.1109/23.281485.

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7

Xiao, Jian, und Chundong Zhu. „The Development of Numerical Control System of Vertical Rotary Forging Machine“. International Journal of Materials, Mechanics and Manufacturing 6, Nr. 1 (Februar 2018): 78–81. http://dx.doi.org/10.18178/ijmmm.2018.6.1.351.

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8

Pereplyotchikov, E. F., I. A. Ryabtsev, Yu N. Lankin, V. F. Semikin und P. P. Osechkov. „Modernization of control system of A1756 machine for plasma-powder surfacing“. Paton Welding Journal 2014, Nr. 12 (28.12.2014): 41–44. http://dx.doi.org/10.15407/tpwj2014.12.09.

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9

Sorrell, Ethan, Michael E. Rule und Timothy O'Leary. „Brain–Machine Interfaces: Closed-Loop Control in an Adaptive System“. Annual Review of Control, Robotics, and Autonomous Systems 4, Nr. 1 (03.05.2021): 167–89. http://dx.doi.org/10.1146/annurev-control-061720-012348.

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Brain–machine interfaces (BMIs) promise to restore movement and communication in people with paralysis and ultimately allow the human brain to interact seamlessly with external devices, paving the way for a new wave of medical and consumer technology. However, neural activity can adapt and change over time, presenting a substantial challenge for reliable BMI implementation. Large-scale recordings in animal studies now allow us to study how behavioral information is distributed in multiple brain areas, and state-of-the-art interfaces now incorporate models of the brain as a feedback controller. Ongoing research aims to understand the impact of neural plasticity on BMIs and find ways to leverage learning while accommodating unexpected changes in the neural code. We review the current state of experimental and clinical BMI research, focusing on what we know about the neural code, methods for optimizing decoders for closed-loop control, and emerging strategies for addressing neural plasticity.

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Chen, Shao Ke. „Control System Design of Automatic Feeding Machine“. Applied Mechanics and Materials 157-158 (Februar 2012): 466–71. http://dx.doi.org/10.4028/www.scientific.net/amm.157-158.466.

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The research of the control system of automatic feeding machine in the present paper can be applied in different mechanical designs – from simple key-press input of cycling days, multiple time intervals and the feeding amount to setting steps of numbers of stepping motor via the control of SMC by time setting. This not only realizes the objective of “fixed-time” and “fixed-quantity” feeding, but also solves the problems of serious leaking, high failure rate, and loud noises during the process of using warehouse-type feeding machines, which brings favorable economic and social benefits for enterprises.

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Zavyalov, V. S., D. U. Mikhailov und A. C. Yatskevich. „Feedback system machine with numerical control - coordinate measuring machine“. IOP Conference Series: Materials Science and Engineering 940 (08.10.2020): 012002. http://dx.doi.org/10.1088/1757-899x/940/1/012002.

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12

SAINEN, Tsutomu. „Fuzzy Control System for Weaving Machine“. Journal of Japan Society for Fuzzy Theory and Systems 8, Nr. 6 (1996): 985–92. http://dx.doi.org/10.3156/jfuzzy.8.6_3.

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13

Antipov, V., und V. Kononov. „Wireless Control System for Mining Machine“. IFAC Proceedings Volumes 20, Nr. 8 (August 1987): 73–74. http://dx.doi.org/10.1016/s1474-6670(17)59073-4.

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14

Mikolajczyk, Tadeusz, Adrian Olaru und Piotr Krainski. „Adaptive Control System for Drill Machine“. Applied Mechanics and Materials 436 (Oktober 2013): 445–50. http://dx.doi.org/10.4028/www.scientific.net/amm.436.445.

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The paper shows an adaptive system for drilling. To drill diameter measure video optical method with USB camera was used. Rotation of drill tool was controlled using an inverter. Adaptive system was controlled by PC using special software made in C++.

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Song, Peng, Guo Kai Xu und Chang Hong Liu. „Adaptive Control System of Milling Machine“. Advanced Materials Research 588-589 (November 2012): 1577–80. http://dx.doi.org/10.4028/www.scientific.net/amr.588-589.1577.

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In this paper, the discrete model reference adaptive control (MRAC) system of milling machine is discussed. Firstly, the discrete Model of milling machine is presented. Based on it the design of the adaptive control is made, and the rule of discrete model reference adaptive control is proven. The results of simulation show that adaptive control has favorable performances.

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Lee, Kwangduk D., Nam P. Suh und Jae-Hyuk Oh. „Axiomatic Design of Machine Control System“. CIRP Annals 50, Nr. 1 (2001): 109–14. http://dx.doi.org/10.1016/s0007-8506(07)62083-6.

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17

Tugengol’d, A. K., E. A. Luk’yanov, E. A. Remizov und D. A. Nosenkov. „Smart control system for machine tools“. Russian Engineering Research 29, Nr. 3 (März 2009): 298–301. http://dx.doi.org/10.3103/s1068798x09030198.

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18

Liu, Hong Jun. „NC Machine Tool Control System Design“. Advanced Materials Research 753-755 (August 2013): 1526–29. http://dx.doi.org/10.4028/www.scientific.net/amr.753-755.1526.

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To adapt to the CNC machine high precision, high quality, high reliability requirements,This article designed NC machine tool control system with application of Lon-works technology. The hardware design method of input module and sensor interface, output module and the stepper motor interface in the system are introduced. This kind of control system rely on its core technology neural chip that based on Lon-works technology can realize the work-piece precision machining. It can be applied to different types of CNC machine tools and will make up for the deficiency of the traditional NC machine tool by PLC control.

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Wang, Xinxin, Xiaohong Lu, Zhenyuan Jia, Wentao Wang und Fengchen Wang. „Control system for micro milling machine“. International Journal of Industrial and Systems Engineering 21, Nr. 1 (2015): 83. http://dx.doi.org/10.1504/ijise.2015.070876.

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20

Petelin, D. P., und A. A. Makarov. „Control system for a winding machine“. Fibre Chemistry 32, Nr. 1 (Januar 2000): 83–86. http://dx.doi.org/10.1007/bf02359207.

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21

San-Payo, Gonçalo, João Carlos Ferreira, Pedro Santos und Ana Lúcia Martins. „Machine learning for quality control system“. Journal of Ambient Intelligence and Humanized Computing 11, Nr. 11 (16.12.2019): 4491–500. http://dx.doi.org/10.1007/s12652-019-01640-4.

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22

Long, Jia. „Vibration Application Based on Machine and Control System“. Applied Mechanics and Materials 443 (Oktober 2013): 281–84. http://dx.doi.org/10.4028/www.scientific.net/amm.443.281.

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Vibration is a mechanical phenomenon whereby oscillations occur about an equilibrium point.Vibration platform uses machine, control system and information technologies to optimize human performance. In order to explore the mechanical effect of vibration based on machines and control systems on human performance, twenty participants were voluntarily involved in this trial. The findings of this study indicated that automation vibration has significant difference on human performance. It has a positive effect on human body. Therefore, vibration can be used in auto regulation.

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Zhou, Jian Hong, Peng Shen und Zheng Weng. „Study on Numerical Control System of Lampcover Spinning Machine“. Applied Mechanics and Materials 336-338 (Juli 2013): 1303–8. http://dx.doi.org/10.4028/www.scientific.net/amm.336-338.1303.

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Chinese spinning technology has developed for more than 40 years. Especially in recent years, various kinds of spinning equipment have been developed and contributed a lot to Chinese equipment manufacturing industry, but it is blank in the light industry and civil industry. Due to the high cost and programming complexity of NC machine tools, we have no dedicated spinning machine and mostly rely on simple manual in the lampcover production. As to the above problems, we developed the lampcover NC spinning machines that can generate the track automatically and complete automatic control in the machining process.

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Zhang, Xin Ju, und Xiu Hong Ma. „Design of Control System in Strapping Machine for Paper Bills“. Advanced Materials Research 791-793 (September 2013): 603–6. http://dx.doi.org/10.4028/www.scientific.net/amr.791-793.603.

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The strapping machine for Paper Bills typically was designed to reduce labor intensity and enhance production automation level. The machines structure and working principle were described. There are three work posts in this equipment, they work continuously. This approach makes it very easy to split up a complex transformation into a series of simple transformations arranged in a loop line. The machine includes currency count/counterfeit distinguishing system, conveying system and strapping system. In the same time, the machine control system that adopts the PLC programmable controller can simplify the control system, and its reliability strengthens further. Practices show that the strapping machine has the advantages of simple structure, high efficiency, low cost and small vibrating noise.

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Paprocki, Marcin, Andrzej Wawrzak, Krystian Erwiński und Marek Kłosowiak. „Flexible PC-based CNC machine control system“. Mechanik 91, Nr. 4 (09.04.2018): 299–303. http://dx.doi.org/10.17814/mechanik.2018.4.46.

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In the article a PC-based CNC machine control system is presented which communicates with servo drives and auxiliary input/output devices via EtherCAT bus. LinuxRTAI real-time operating system and LinuxCNC control software were implemented in the PC controller. A software module implementing EtherCAT communication with the servo drives was developed and integrated with LinuxCNC. Experimental results were presented which show the trajectory smoothing capabilities of the control system. Experimental results were also presented that show following errors obtained by running an example trajectory on a linear motion module. Basic parameters that show the control systems capabilities obtained during the experimental tests have been presented. The CNC control system presented in this article was implemented on a 3-axis machine.

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Yang, Fei, und Lei Zhao. „Study on Auto Control System of No Decoupling Dynamic Compaction Machine“. Applied Mechanics and Materials 536-537 (April 2014): 1191–94. http://dx.doi.org/10.4028/www.scientific.net/amm.536-537.1191.

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This paper introduces the current development of dynamic compaction machine at home and abroad and the basic structure of no decoupling dynamic compaction machine. Besides, The design scheme of no decoupling dynamic compaction machines brake control system is focused on putting forward in order to achieve automatic ramming without decoupling and without artificial hook. This kind of dynamic compaction machine with the advantage of simple structure, convenient operation and high efficiency effectively reduces the construction cost.

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Sumorek, Andrzej, und Marcin Buczaj. „Control and data acquisition system for the rolling machine“. MATEC Web of Conferences 252 (2019): 06001. http://dx.doi.org/10.1051/matecconf/201925206001.

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Rolling machines are often used for forming flat elements or pipes. Problems occur when used to produce cylindrical elements other than pipes, or when experimental materials are used. It is required to introduce flexible control of the rolling process parameters in such cases. It is necessary to monitor the device operating parameters. When a rolling machine works with experimental materials, there are no typical control and acquisition data systems available. The article presents the concept and capabilities of the control and computer data acquisition system supporting the rolling process. The main task of software system is acquisition of force and kinetic parameters related to the analysed process of the compression during rolling. This system allows current recording and analysis of five physical values. The acquisition data application is developed in National Instruments LabVIEW environment. The software algorithm is based on the state machine. The article contains a detailed description of hardware and software implementation of the functions mentioned.

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Komiya, Seiji, Masao Ishihama, Takahiro Takahashi und Kazuya Kojima. „2B25 Motion Analysis and Control of Dual Wheel Vehicle as Human-Machine System“. Proceedings of the Symposium on the Motion and Vibration Control 2010 (2010): _2B25–1_—_2B25–9_. http://dx.doi.org/10.1299/jsmemovic.2010._2b25-1_.

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Wang, Shih Ming, Si Chi Ouh und Chun Tai Yen. „An Adaptive Parameter Tuning Method with On-Machine Weight Identification Function for CNC Machine Tools“. Applied Mechanics and Materials 479-480 (Dezember 2013): 268–73. http://dx.doi.org/10.4028/www.scientific.net/amm.479-480.268.

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Different inertia effect causes different control errors. To have an optimal control performance, the control parameters of a CNC machine tool should be adaptively tuned based on the variation of the weight of the workpiece in machining process. In this study, simulation based on a theoretical model was made to investigate the influence of inertial effect and friction force on the servo accuracy of a CNC machine tool’s. By using empirical method, an adaptive tuning system that can auto-tune the CNC control parameters based on the detected weight of workpiece was developed. An on-machine weight identification system that can on-machine identify the weight of the workpiece was developed. After integrating the two systems, a control parameter tuning system which can be implanted into CNC controller was developed with the macro executor. Experimental results have shown that the system can effectively improve the accuracy of a machine tool through adaptively tuning control parameters based on the current weight of the machined.

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Yang, Hai Yan, und Xiu Mei Zhu. „Design of a Vending Machine Control System“. Applied Mechanics and Materials 644-650 (September 2014): 786–89. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.786.

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The vending machine is the commercial automation equipment which can complete the vending without people. It is a production of social transformation from the labor-intensive to technology-intensive industry structure. This topic using Mitsubishi PLC FX2N - 32 MR controlled the vending machine control system, improved the stability of the vending machine system, make sure the vending machine can long-term and stable operation.

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Hou, Bo, Congpeng Zhang und Shoubo Yang. „Computer Vision Tool-Setting System of Numerical Control Machine Tool“. Sensors 20, Nr. 18 (16.09.2020): 5302. http://dx.doi.org/10.3390/s20185302.

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An automatic tool-setting and workpiece online detecting system was proposed to study the key technologies of next-generation intelligent vision computerized numerical control (CNC) machines. A computer vision automatic tool-setting system for a CNC machine was set up on the basis of the vision tool-setting principle. A rapid vision calibration method based on the position feedback from the CNC machine was proposed on the basis of the theory of traditional vision system calibration. The coordinate mapping relationship of the image and the CNC machine, the tool-setting mark point on the workpiece, and the tool tip were calibrated. The vision system performance testing and system calibration experiments were performed. Experimental results indicated that the time consumption was 128 ms in image processing. The precision of tool setting and measuring was less than 1 μm. The workpiece positioning and processing online detection function of the system can completely meet the requirements of visual CNC machine application, and the system has wide application prospects.

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Yang, Xiao Lan, Ji Feng Liu, Meng Nan Si, Jia Wei Li und Biao Huang. „Advance Control Experiment of Vibration Machine with High Vibration Intensity Based on SCM – Dynamics Characteristics and Advanced Control“. Advanced Materials Research 912-914 (April 2014): 554–58. http://dx.doi.org/10.4028/www.scientific.net/amr.912-914.554.

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The vibration-stress field could be formed by high vibration intensity in vibration machine to improve the ability of the collision, shock, shear and extrusion for the system, and it also can avoid plugging screen for vibration screening machine, which could make for solving some special requirements of the vibration machine. To research the vibration machines strongly nonlinear and high vibration intensity characteristic such as certain excitation and uncertain response, the vibration machine with its double-mass is built, and its vibration exciter uses two partial blocks as vibration motor. In addition, dynamic vibration differential equation is established. To achieve high vibration intensity results based on the vibration machines safe working, the advanced control based on the SCM and Intelligent frequency conversion is put forward, and the advanced control system with its host computer, frequency converter, SCM, charge-amplifier, sensor and the vibration machine is been established.

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Zerilli, John, Alistair Knott, James Maclaurin und Colin Gavaghan. „Algorithmic Decision-Making and the Control Problem“. Minds and Machines 29, Nr. 4 (Dezember 2019): 555–78. http://dx.doi.org/10.1007/s11023-019-09513-7.

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AbstractThe danger of human operators devolving responsibility to machines and failing to detect cases where they fail has been recognised for many years by industrial psychologists and engineers studying the human operators of complex machines. We call it “the control problem”, understood as the tendency of the human within a human–machine control loop to become complacent, over-reliant or unduly diffident when faced with the outputs of a reliable autonomous system. While the control problem has been investigated for some time, up to this point its manifestation in machine learning contexts has not received serious attention. This paper aims to fill that gap. We argue that, except in certain special circumstances, algorithmic decision tools should not be used in high-stakes or safety-critical decisions unless the systems concerned are significantly “better than human” in the relevant domain or subdomain of decision-making. More concretely, we recommend three strategies to address the control problem, the most promising of which involves a complementary (and potentially dynamic) coupling between highly proficient algorithmic tools and human agents working alongside one another. We also identify six key principles which all such human–machine systems should reflect in their design. These can serve as a framework both for assessing the viability of any such human–machine system as well as guiding the design and implementation of such systems generally.

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Zhu, Jian Feng, Peng Xiang Hua, Jun Bang Liu, Xin Wang und 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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Mikolajczyk, Tadeusz. „Numerical Control System of Conventional Milling Machine“. Applied Mechanics and Materials 841 (Juni 2016): 179–83. http://dx.doi.org/10.4028/www.scientific.net/amm.841.179.

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The paper presents a system of numerical control conventional milling machine, however with drives equipped with electromagnetic clutches. In control system was used relay controlled using PC. There are connected to buttons to manually panel milling machine with an electromagnetic system feeds. Developed using VB6 special software to control the machine with G-code.

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Tugengold, A. K., A. I. Izyumov, R. N. Voloshin und M. Y. Solomykin. „Fuzzy control system of multioperational machine status“. Vestnik of Don State Technical University 17, Nr. 2 (2017): 70–78. http://dx.doi.org/10.23947/1992-5980-2017-17-2-70-78.

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37

Li, Hai Kun. „The Control System Design of Newtextile Machine“. Advanced Materials Research 622-623 (Dezember 2012): 1462–66. http://dx.doi.org/10.4028/www.scientific.net/amr.622-623.1462.

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It is well-known that China is a textile production and export country, especially in Zhejiang and Hangzhou province, the textile industry is well-developed with tremendous amount of application of textile machinery. This paper is about the design of rapier textile machinery with programmable logic controller, including five major functions: opening weft, leading weft, fighting weft, warping and coiling off weft. It has accomplished the function of detecting a broken weft while leading weft, while the signal of detecting is completed by store, and the function of broken warp while warping. PLC Programmer of S7200 Siemens CPU224 is used.

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Yuan, Jian Xin, und Meng Ke Lu. „Research Rewinding Machine Constant Tension Control System“. Advanced Materials Research 926-930 (Mai 2014): 1558–61. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.1558.

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In industrial production process, Often due to winding or rewind tension control during problems lead to product quality problems. The reeling tension system complexity, uncertainty, simple open loop control cannot achieve the desired effect. The system use the MITSUBISHI FX3U series PLC as the control core. By sampling the floating roll location, the use of digital PID closed loop control winding motor speed so that the floating roll location constant so as to realize the constant tension control of winding

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Ding, Shou Cheng, Wen Hui Li und Shi Zhou Yang. „Research on Automatic Washing Machine Control System“. Key Engineering Materials 480-481 (Juni 2011): 1302–7. http://dx.doi.org/10.4028/www.scientific.net/kem.480-481.1302.

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Microprocessors and sensor technology together achieved a fully automatic washing machine based on fuzzy control. System used an integrated mixed-signal system-level C8051F020 microcontroller. The system would detect and reasoning on the amount of washing objects, fabricl quality, water level, reference washing time, the flow intensity, real-time temperature and dirt level of washing liquid, so as to achieve automatically complete the whole washing process. Experiments shows that the system is stable, easy to operate, cost-effective advanced features, so that it has a certain value.

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Zhang, Jun, Xihuai Wang und Jianmei Xiao. „Multi-machine Power System Robust Excitation Control“. Procedia Environmental Sciences 10 (2011): 350–55. http://dx.doi.org/10.1016/j.proenv.2011.09.057.

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41

Ding, Ning. „Human-machine intelligent control system for grinding“. Chinese Journal of Mechanical Engineering (English Edition) 17, supp (2004): 26. http://dx.doi.org/10.3901/cjme.2004.supp.026.

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WANG, H. G., und J. E. ROODA. „Fuzzy control in a single-machine system“. Production Planning & Control 7, Nr. 6 (November 1996): 577–84. http://dx.doi.org/10.1080/09537289608930391.

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43

Leman, Muhammad Naim, Shahrol Mohamaddan, Mohamad Syazwan Zafwan Mohamad Suffian, Abang Mohamad Aizuddin Abang Mohd Mohtar, Nur Alia Athirah Mohtadzar, Nazreen Junaidi und Satria Arjuna Julaihi. „Development of Control System forKeropok KepingDrying Machine“. MATEC Web of Conferences 87 (12.12.2016): 02016. http://dx.doi.org/10.1051/matecconf/20178702016.

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44

Fujita, Goro, Satoshi Shiratori und Goro Shirai. „TCSC Control for Multi-machine Power System“. IEEJ Transactions on Power and Energy 119, Nr. 6 (1999): 704–11. http://dx.doi.org/10.1541/ieejpes1990.119.6_704.

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45

Hace, A., und K. Jezernik. „Control system for the waterjet cutting Machine“. IEEE/ASME Transactions on Mechatronics 9, Nr. 4 (Dezember 2004): 627–35. http://dx.doi.org/10.1109/tmech.2004.839045.

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46

Antsaklis, Panos J., und Arash Rahnama. „Control and Machine Intelligence for System Autonomy“. Journal of Intelligent & Robotic Systems 91, Nr. 1 (11.04.2018): 23–34. http://dx.doi.org/10.1007/s10846-018-0832-6.

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47

Nepryaev, A. A. „Cognitive radar control system using machine learning“. IOP Conference Series: Materials Science and Engineering 1047, Nr. 1 (01.02.2021): 012119. http://dx.doi.org/10.1088/1757-899x/1047/1/012119.

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48

Zhuang, Li, Yaoguang Qi und Fenna Zhang. „Braking Control System of Oilfield Minor Repair Machine Based on Wireless Sensor Network“. Security and Communication Networks 2021 (08.09.2021): 1–14. http://dx.doi.org/10.1155/2021/6966041.

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Annotation:

Traditional minor repair machines have low control efficiency and low automation. In order to improve the brake control efficiency of the oilfield minor repair machine, the oilfield minor repair machine brake control system based on wireless sensor network is designed. The front-end controller collects the data of the oilfield repair machine through the wireless sensor and realizes the communication between the sensor nodes and the data interaction with the communication node through the field bus inside the equipment. The server uploads the processed data through the 3G network, and the server receives the data from the front-end controller and saves it in the database. The remote-control center accesses the server through the Internet to view the front-end controller data. The brake control module uses the expert fuzzy PID control method to control the speed, oil pressure, and operating status of the oilfield minor repair machine and sends the data to the front-end control center to complete the oilfield minor repair remote-control machine by sending control instructions. Experimental results show that the system can meet the braking control requirements of oilfield minor repair machines, the output can quickly track input changes, the braking control effect is good, the dynamic deviation of the machine can be reduced, and the braking control efficiency can be improved.

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49

Kaak, Hartmut, und Andrea Neuendorf. „Control system for a production machine, especially a ring-spinning machine“. Computer Integrated Manufacturing Systems 10, Nr. 2 (Mai 1997): 174. http://dx.doi.org/10.1016/s0951-5240(97)84332-7.

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50

WESTON, R. H., R. HARRISON, A. H. BOOTH und P. R. MOORE. „Universal machine control system primitives for modular distributed manipulator systems“. International Journal of Production Research 27, Nr. 3 (März 1989): 395–410. http://dx.doi.org/10.1080/00207548908942556.

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