外文翻译改善电磁阀和液力偶合器的控制.docx

1、外文翻译改善电磁阀和液力偶合器的控制中文2467字附录A 译文改善电磁阀和液力偶合器的控制摘要本文针对一个电磁阀连接的液力偶合器的操作法，是一种新、改善的控制方法。通过输送机动力学模拟对该方法进行了验证，在本文将介绍验证结果。1 介绍液力偶合器是自1987 年在南非被用在处理大块固体生产上。但是, 最初的高期望未被履行, 主要由于缺乏对控制系统联结的限制的理解的一些应用。液力偶合器能通过各种各样的方式完成它的性能1，并且对工程师来说是扣人心弦工作，因为唯一的限制也许是某人的假想。扭矩控制最常见的方法依靠电磁阀，电磁阀启动并在被预先确定的极限内由PLC 系统监督整体性能。扭矩特征曲线呈锯牙样式。

2、上部和下部的扭矩极限依照具体要求确定。在多数场合这个技术是满足的, 然而, 有不希望的副作用的源头譬如那些与所谓的“抨击”控制技术相关的。尽管这些困难, 但电磁阀是一种有效耐用的设备, 也适合原材料处理产业的环境。随后人们企图运用这个具体设备挖掘它的全部潜能，并在期间用一台输送机的改善的控制技术研制一个适当的控制系统。2 背景知识经过一段时间研究，我们采用控制参量调整分离开关实现连续控制，在电子学和农业领域执行试验并且在区域内通过递象开关方式实施系统。PUTTER 和Gouws2方法，保持相互依赖的参量是可能的，譬如在温室里使用通过风扇、加热器和喷水隆头的分离行动使温度和湿气保持平衡。当接受温

3、室里高变化动力学差异时, 对电磁阀和液力偶合器的应用开发和研究一个相似的概念是有意思的。2.1 控制系统算法近年来，控制系统在现代控制技术上应用有许多种, 譬如模糊逻辑控制4 、神经网络5，它是作为对非线性和多变量控制问题的解决办法。尽管所有成功例子, 许多典型的技术, 譬如比例-积分-导数(PID)控制。PID控制比智能控制技术的优势是少处理器容量和所需时间。但是, 虽然已解决一些问题6, 但PID 控制器仍然保留一个难题, 尤其是在系统中有不可接受的实验错误方法。PID控制的缺点是调节系统非线形性能力受限制。电磁阀和液体偶合器组合应用PID控制技术。通过控制阀门的开关, 电动机/连轴器扭矩

4、能保持不变。系统失效时间是足够短的，但对系统非线形性调节不明显, 在这些情况下，可应用PID控制技术，描述控制等式得如下7： （1-1）E 误差，区别在凝固点和被观察的价值之间；T 所需扭矩变动量Nm；Kc 比例增量；Td 派生导数时间常数s；Tj 累积时间常数s；Ts 样品时间常数s；n 样品数字；公式1-1与常规PID方法相反，它相对于当前的扭矩(T)确定所需变化量。这是一种快而方便的确定输出量的方式, 因为没有数字微分或积分。数字n 是当前的测量误差, n - 1是早先测量，n - 2是n-1的前一个。测量间的时间是重要的。太短的采样时间能引起设备过分循环, 而太长采样的时间能引起超载和

5、不稳定8。常数Kc、Tj、Td最初根据知名的ZIEGLER-NICHOLS方法在理论上确定6。在控制器的性能上这些常数的每个作用用史密斯描述了3, 被总结如下7：Kc值小产生超载现象但稳定性好, 但当Kc值大时减少超载现象但增加设备循环。Tj值小消除恒定值误差, 但导致控制设备迅速循环。反过来, Tj 值大导致产生恒定误差。Td值小导致超载大, 当Td值大提高反应时间时, 导致稳定性提高。虽然阀门只能关起, 但如果通过控制开关开启、停滞时间的线性地变化的阀来控制开关是可能的。公式1-2，T被转换成使用率, 被定义如下：使用率：T = （1-2）交换阀门的时间() s；各样品间在一时间间隔期间阀

6、门交换的最大时间的时间(tmax =)s；实际上，转换能以不同方式完成，涉及T与阀门操作的时间之间从一个简单的比例关系到一相当复杂关系，其中要考虑扭矩/油流量变化率。假想的发展或者选择通过几个因素治理，其中由软件控制和硬件限制的简单化是二个最明显部分的。对于这种具体应用，阀门交换每秒不可以超过5次或5赫兹。最大工作循环(tmax)的最佳值要根据指定的标准或动态模仿实验经反复试验确定。机模拟实验校核改善概念的性能：测试概念并通过输送机模拟校核。第一套由计算机编程建造的输送机模型是以两年之前用这种材料的详细设计而研制的。输送机是通过液力偶合器驱动，它连接着三项换向阀。有关系统和输送机的详细的信息可

7、能都来自9。偶合器的应用指标与在11中描述的差不多，比如在南非很有代表性的那种液力偶合器。在重要的零件图中，需要分析启动阶段的转矩。合格的运行结果是通过调节运行周期和控制设置来实现的。这样可以进一步探索启动阶段速度。为了完成进一步的研究工作，制作的模型将拓展到输送机的高配置的动力装置。在这张图表上涉及到了8.5m长带有顶部和尾部驱动装置的输送机。尽管是带有铲斗的系统操作，但是在这些模拟装置中输送机的模型是与液力偶合器连接在单向阀口处。2.2 输送机动态模型的结果3.3km长钢丝输送机扭矩率116.0Nm/s，在开始阶段描绘的图的坡度大，尤其在泵刚工作的前6秒之间。从而，大约延迟12秒后，控制系

8、统开始启动，存在两个问题：1）最初，低扭矩传输不允许输送机机立即加速度，但通过软件的调整这种情况就可以，正如模拟实验的那样，注意速度变化和控制开始的时间不少于在电机启动后的8秒，双向泵启动后的6秒。2）油从偶合器卸荷的速度是有限的，也许不够抵制输送机机的动态反应，因此，在开始的初始阶段注意某种的程度超速。尽管已提出一些问题，但启动开始速度的变化的情况比希望从控制操作的分散模块上解决问题更有深远意义。进一步测试, 运用不同的速度曲线或者控制常数能得到更好的结果。整体的结果是合理的，但是，值得注意是在某种程度上尾部驱动比头部的性能好。对于每个驱动装置，在开始的12秒到22秒之间提高扭矩或者张力是可

9、行的，再一次调整设备或者工作因数，能改善结果。3 结论基于模拟的结果能得一下结果：1）电磁阀的控制概念在很大程度上已实现，把阀的分散运动变成精确的、连续的输出是可能的。2）新系统允许电磁阀的应用可根据原策略的速度，然而，对于扭矩来说控制可能不精确，尤其在开始启动阶段。3）保证控制参数的优化，模拟实验的结果表示选择不当的控制参数会导致不好的性能结果。4）如所示，这个概念能被应用于中长型输送机中，尾部驱动不易限制，然而，在这种情况上，只有对开始的扭矩进行测试。5）PID控制是传统的控制技术，它广泛应用于加工工业中，并能解决不同的控制问题。附录B 外文文献Improved control of a

10、solenoid valve and drain couplingSummaryThe paper looks at a new, improved control concept for a fluid coupling operating in conjunction with a solenoid valve.Verification of the method has been done by means of conveyor dynamic simulations and some of the results are presented in the paper.1. Intro

11、ductionDrain fluid couplings have been available in South Africa since 1987 and have found acceptance in the bulk solids handling industry. However, initial high expectations have not always been fulfilled, mainly due to some applications which showed a lack of understanding of the couplings limits

12、of performance and/or deficient control systems. The drain coupling can be assisted in its performance by various means 1 and in this respect is exciting to work with for an engineer, as the only limit may be ones imagination and/or finances. The most common method of torque control relies on a sole

13、noid valve which operates in an on/off mode supported by a PLC system which supervises overall performance within pre-determined limits. The resulting torque curve is characterized by a saw tooth pattern as presented. The upper and lower torque limits can be adjusted as determined by specific demand

14、s.This technique is sufficient in most instances, but, however, may be the source of undesirable side effects such as those associated with so called “bang-bang” control techniques. Despite these difficulties, the solenoid valve remains a cost effective and robust device, well suited to the environm

15、ent of materials handling industry.Subsequently an attempt has been made to utilize this specific device to its full potential and to develop a suitable control system which would allow improved control of a conveyor during start up.2. Background InformationFor some time research has been performed

16、into continuous control by means of discrete on/off adjustment of control parameters. Trials were performed and systems implemented in areas as far afield from bulk solid handing as switch mode power electronics and agriculture. As an example of the potential of this approach PUTTER and Gouws 2 stat

17、ed that it was possible to maintain a pre-determined level of interdependent parameters such as temperature and humidity in a greenhouse by means of discrete action of fans. heaters and sprinklers. While accepting definite differences in the dynamics of climactic change in a greenhouse and conveyor

18、start up. It was interesting to develop and test a similar concept for the application of a solenoid valve and a drain fluid coupling.2.1 Control System AlgorithmThe control system arena has, in recent years, been filled with publications on modern control techniques, such as fuzzy logic control 4 a

19、nd neural networks 5 as solutions to non-linear and multi-variable control problems. Despite all the success stories, more classical techniques, such as Proportional-Integral-Derivative Control (PID). An advantage of PID-control, is that less processor capacity and time is required, than with the in

20、telligent control techniques. However, even though many solutions have been suggested 6, tuning a PID-controller still remains a difficult task, especially in systems where trail and error methods are not acceptable. A disadvantage of PID-control is its restricted ability to accommodate system non-l

21、inearities.The solenoid valve and drain coupling combination lends itself to the application of PID control. By controlling the switching of the valve, the motor/coupling torque could maintain a pre-determined pattern. The system dead time is short enough not to contribute significantly to system no

22、n-linearity, in which case PID-control may be applied. The control equation is described as follows 7:1where:E - error, difference between set point and observed valueT- required torque change NmKc -proportional gain Td- derivative time constant sTj- integral time constant sTs- sample time constant

23、sn- sample number.Contrary to the conventional PID approach Eq. (1) determines the change required relative to the current torque (T) and not the amount of torque required as a function of the error. This is a quicker and more convenient way to determine the output, since no numeric integration or d

24、ifferentiation is required.The number n refers to the current error measurement, n 1 to the previous measurement and n- 2 to the one before that. The time between measurements is critical. A too short sampling time can result in excessive equipment cycling, while a too long sampling time can result

25、in overshoot and instability 8. The constants Kc,Tj Td are originally determined theoretically according to the well-known ZIEGLER-NICHOLS method 6. These values serve as a starting point from where further fine tuning was done experimentally. The effect of each of these constants on the controllers

26、 performance has been described by SMITH 3 and can be summarised as follows 7:A small value of Kc produces large overshoot but gives good stability, while larger values of Kc reduce the overshoot but increase equipment cycling.-Small values of Tj eliminate constant errors quickly, but result in rapi

27、d cycling of control equipment. In turn, large values of Tj cause constant errors to occur.-A small value of Td causes large overshoot, while a large value of Td increases the reaction time, which results in increased stability.Although the valve can only be switched on or off, it is still possible

28、to control the switching as if it were a linearly varying valve by controlling the time for which it is switched on or off. By applying Eq. (2), T is converted to a duty cycle, which is defined as follows:Duty cycle = 2where: -time for which the valve is switched on () s -time between each sample wh

29、ich also represents maximum time for which the valve can be switched on during one interval (tmax =)s.In fact the conversion may be done in several ways ranging from a simple proportional relationship between T and time of valve operation to a rather complex one where rates of torque/oil flow change

30、 are taken into account. Development and/or selection of the concept may be governed by several factors of which simplicity of the control software and limitations of the hardware are the two most obvious ones.For this specific application, the valve may not be switched more than 5 times per second

31、or 5 Hz. The optimum length of the maximum duty cycle (tmax) may be determined by trial and error according to specified criteria or by dynamic simulation.Conveyor Simulations Verifying the Performance of the Developed Concept: The concept has been tested and verified by means of conveyor dynamic si

32、mulations. The first set of simulations utilised a computer model of a conveyor which was a subject of a detailed design investigation by Dynamika Materials Handing two years ago. The conveyor was supplied with drain couplings working in conjunction with a three way valve. Detailed information about the system and the conveyor may be found in 9. The coupling characteristics utilised are similar to that