Linear motion: selecting the best solution for your needs

Simon Gass

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Linear motion: selecting the best solution for your needs

机译：线性运动：为您的需求选择最佳解决方案

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The need to increase productivity and reduce downtime is a key focus for manufacturers. However, when it comes to selecting linear actuators for motion applications, some confusion remains on whether an electric or pneumatic solution is most suitable.

机译：需要提高生产率并减少停机时间是制造商的关键重点。但是，在选择用于运动应用的线性执行器方面，一些混淆仍然保持在电动或气动溶液最适合。

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《Design Products and Applications》 |2019年第8期|18-19|共2页
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Simon Gass;
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1. Linear motion: selecting the best solution for your needs [J] . Simon Gass Design Products and Applications . 2019,第AUGa期

机译：直线运动：根据需要选择最佳解决方案
2. Approximate solutions and chaotic motions of a piecewise nonlinear-linear oscillator [J] . Ji JC, Hansen CH Chaos, Solitons and Fractals: Applications in Science and Engineering: An Interdisciplinary Journal of Nonlinear Science . 2004,第5期

机译：分段非线性线性振荡器的近似解和混沌运动
3. Analytical solutions of periodic motions in a first-order quadratic nonlinear system [J] . Zhou Guopeng, Jin Peng, Zhou Fang, The European physical journal: Special topics . 2019,第9期

机译：一阶二次非线性系统中周期运动的分析解
4. Comparison of selected off-the-shelf solutions for emotion recognition based on facial expressions [C] . Grzegorz Brodny, Agata Kołakowska, Agnieszka Landowska, International Conference on Human System Interactions . 2016

机译：选择的基于面部表情的现成情感识别解决方案的比较
5. THE ESTABLISHMENT OF A PROCEDURE FOR SELECTING A FAVORABLE METHOD OF DETERMINING NATURAL FREQUENCIES AND NATURAL MODES OF VIBRATION OF MULTI-DEGREE-OF-FREEDOM MECHANICAL SYSTEMS, THE MOTIONS OF WHICH CAN BE DESCRIBED BY LINEAR DIFFERENTIAL EQUATIONS. [D] . ALLEY, THOMAS LEROY. 1964

机译：建立选择确定多频率自由度机械系统振动的自然频率和自然模式的方法的程序，可以用线性微分方程来描述运动。
6. Diffusive Motion of Linear Microgel Assemblies in Solution [O] . Marco-Philipp Schürings, Oleksii Nevskyi, Kamill Eliasch, 2016

机译：溶液中线性微凝胶组件的扩散运动
7. EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed TarekShahriar Abstract—An EMD-chaos based approach is proposed todiscriminate EEG signals corresponding to healthy persons,and epileptic patients during seizure-free intervals and seizureattacks. An electroencephalogram (EEG) is first empiricallydecomposed to intrinsic mode functions (IMFs). The nonlineardynamics of these IMFs are quantified in terms of the largestLyapunov exponent (LLE) and correlation dimension (CD).This chaotic analysis in EMD domain is applied to a large groupof EEG signals corresponding to healthy persons as well asepileptic patients (both with and without seizure attacks). It isshown that the values of the obtained LLE and CD exhibitfeatures by which EEG for seizure attacks can be clearlydistinguished from other EEG signals in the EMD domain.Thus, the proposed approach may aid researchers in developingeffective techniques to predict seizure activities. Index Terms—Electroencephalogram (EEG), empiricalmode decomposition (EMD), largest Lyapunov exponent (LLE),correlation dimension (CD), epileptic seizures. The Authors are with the Electrical and Electronic EngineeringDepartment, Bangladesh University of Engineering and Technology,Dhaka-1000, Bangladesh (e-mail: imamul@eee.buet.ac.bd) PDF Cite: S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed Tarek Shahriar, "EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain," International Journal of Computer and Electrical Engineering vol. 4, no. 3, pp. 326-330, 2012. PREVIOUS PAPER Perception of Emotions Using Constructive Learningthrough Speech NEXT PAPER Physical Layer Impairments Aware OVPN Connection Selection Mechanisms Copyright © 2008-2013. International Association of Computer Science and Information Technology Press (IACSIT Press) [O] . S. M. Shafiul Alam, Syed TarekShahriar 2012

机译：EEG信号在EMD域S. S. Shafiul Alam，S中的非线性动力学使用非线性动力学。 M. Shafiul Alam，Aurangozeb和Syed Tarekshahriar摘要 - 基于EMD Chaos的方法，提出了对应于健康人的EEG信号，癫痫发作期间的癫痫患者和Seizureattacks。脑电图（EEG）首先被凭经上分解为内在模式功能（IMF）。这些IMF的非线性动力学在最大范围的指数（LLE）和相关尺寸（CD）方面是量化的。本域中的混沌分析应用于与健康人相对应的大型脑电图（Asepileptic患者）（两者都有癫痫发作）。因此，所获得的LLE和CD表展的价值可以从EMD领域的其他EEG信号中清晰地区分脑电图的表达展示。本拟议的方法可以帮助研究人员以预测癫痫发作的癫痫发作技术。索引术语 - 脑电图（EEG），仿真态分解（EMD），最大的Lyapunov指数（LLE），相关维度（CD），癫痫发作。作者与电气电子和电子工程公司，孟加拉国工程和技术大学，孟加拉国达卡 - 1000（电子邮件：imamul@eee.buet.ac.bd）pdf cite：s. m. shafiul Alam，s。 M. Shafiul Alam，Aurangozeb和Syed Tarek Shahriar，“EEG信号歧视在EMD领域的非线性动态，”计算机电气工程卷国际杂志。 4，不。 3，pp。326-330,2012，上一篇论文对情绪的看法，使用建设性的学习言论下一篇论文物理层障碍意识到OVPN连接选择机制版权所有©2008-2013。国际计算机科学与信息技术协会出版社（IACSIT Press）
8. Stability Solution to Linearized Equations of Motion for a Symmetric Spinning Satellite in an Elliptical Orbit Applied to the Non-Linear Equations [R] . Shell, D. E. 1988

机译：应用于非线性方程的椭圆轨道对称旋转卫星线性化运动方程的稳定性解

Linear motion: selecting the best solution for your needs

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