一篇机电一体化的英语论文及翻译

A Systems Approach for Modelling Mechatronics Systems

Bassam A. Hussein

Production and Quality Engineering Department, The Norwegian University of Science and

Technology, NTNU,

Trondheim, Norway

Received on December 3,1997

ABSTRACT

This paper presents a unified approach based on utilizing multidimensional arrays in order to model the physical and logical properties of mechatronics systems. A mechatronics system model consists of two interacting submodels.A submodel that describes aspects related to energy flow in the physical system, and another submodel that describes aspects related to information flow in the control system. The multidimensional array based approach of modelling provides us with the possibility to use one terminology and the same formalism for modelling both subsystems. The consequence of using the same formalism is that simulation of the mechatronics system can be performed using only one simulation environment

Keywords: Mechatronics, System, Modelling

1. INTRODUCTION

Mechatronics system is defined as the synergetic integration of mechanical engineering with electronics, and intelligent computer control in the design and manufacturing of industrial products and processes [5]. The components of mechatronics systems must be designed concurrently, that is, the constraints imposed on the system by each discipline must be considered at the very early stages. Therefore, proper system design will depend heavily on the use of modelling and simulation throughout the design and prototyping stages. The integration within a mechatronics system is performed through the combination of the hardware components resulting in a physical system and through the integration of the information processing system resulting in an intelligent control system [7].

The mechatronics system then, is the result of applying computer based control systems to physical systems. The control system is designed to execute commands in real time in order to select, enhance, and supervise the behavior of the physical system. The only possible way to guarantee that these control functions will keep the behavior of the whole system within certain boundaries before we actually build it, is to create a model of the real system that takes into account all the imposed constraints by both the hardware and software components. This implies that a model of the real system must be powerful enough to capture all the properties of

mechatronics system. That includes; the dynamic, static, discrete event, logic, as well as cost related properties of the real system, a task we believe, defies any fragmented approach of modelling. In this paper we present a unified approach for modelling mechatronics systems. This unified approach utilizes geometric objects or multidimensional arrays to formulate models of mechatronics systems. The multidimensional array based approach of modelling provides us with the possibility to use the same formalism for a large variety of systems [2,3,4,9]. The consequence of using the same formalism is that simulation of mechatronics systems can be performed using only one simulation environment.

2. MODEL STRUCTURE

Intuitively speaking, a model that describes the dynamic behavior of a given system can not be used to investigate the static behavior of the very same system. Therefore, in order to capture all aspects, we need a variety of models, each one of them encapsulates some aspects of the real system.

We will consider the mechatronics system model as a set of connected submodels, each submodel corresponds to some realizable aspects. In this regard, the term connected was used to emphasize the dependency between the variables in these submodels. Throughout the process of modelling, we shall distinguish between the following concepts, see Figure 1.

Decomposition: in order to handle the complexity of mechatronics systems, they should be decomposed into subsystems. This decomposition is carried out on a multilevel fashion until we reach the basic elements that constitute the total system. The primitive system model: is a description of the system in the disconnected state. It expresses the relation between the variables in the individual elements when the bonds between these elements are removed. By this model we isolate a specific behavior; static, dynamic, etc., in each element. A pair of local variables defines the behavior of a given element locally. The Connected system model: is a description of the same system after taking the internal constraints into account. The internal constraints within the system are given by the way the local variables are connected or related directly as well as indirectly by the variables of the connected system. The connected system model resembles the actual structure of the real system.

The applied sources are generated due to interaction between the system and its environment. They could be seen as the external constraints imposed on the system or even inherent constraints in the form of stored energy in system elements.

3. APPLICATION EXAMPLE

Consider, the manufacturing system shown in Figure 2.

The system consists of a boring spindle powered by a direct current motor. The feed forward motion of the boring spindle is carried out by means of a hydraulic linear actuator. The hydraulic actuator is powered by a constant pressure hydraulic pump. The volumetric flow in the hydraulic circuit is controlled by a servo valve [8].

The above manufacturing system has the following specifications: The positions of boring spindle are sensed by three micro breakers. Breaker ( B ) which indicates that the boring spindle is at the rear position. At the rear position the rapid phase valve ( I ) will be switched on in order to allow a rapid forward motion ( F ) and the signal (S) will switch on the spindle motor. Breaker (M) indicates that the boring spindle has reached the feeding position. At this position the rapid phase valve will be switched off in order to start a controlled feed forward motion. This motion is regulated by the servo valve (St). Breaker (€) which indicates that the bo ring spindle has reached its final position, at this position and the backward motion ( R ) will begin, simultaneously the rapid phase valve ( I ) will be switched on in order to allow a rapid backward motion. It is also specified that the rotating speed of the spindle motor should be kept at 3000 rpm. during boring the work piece and the feed forward speed must be kept at 2cm/sec under all loading conditions. Our objective is to set up a complete model of the given system using multidimensional arrays and to carry out necessary experiments on the model to verify that specifications are satisfied.

3.1 Physical System Modelling

When modelling physical systems, we are concerned with modelling the evolution of the physical variables that lives within this system. The decomposition of the physical system is shown in Figure 3.

The groups of basic physical elements are classified into three categories: Generalized resistor: examples of this category are; electric resistor, mechanical damper, and hydraulic resistor. Generalized capacitor: examples of this category are; electric capacitor, mechanical spring, and hydraulic reservoir. Generalized inductor examples of this category are; electric inductor, mechanical mass, and hydraulic inductor. Breaking down the physical system into subsystems and further into basic elements will provide us with a sharp insight about the evolution of the physical quantities within each subsystem, yielding to better understanding of the modes and the states that each subsystem would attain. The advantages of having such insight will become visible during the design phase of a local control system.

Modelling can be considered as the opposite procedure of decomposition. The difference is that, in decomposition, we divide the system into independent physical entities, while in modelling we reconnect the models of these physical entities. Therefore, modelling can be seen as the procedure of connection.

In modelling, we start at the bottom level of this hierarchy and move upwards. At each level, we propagate from a primitive system model to a connected system model. In the succeeding level, the primitive system model would then be established by aggregating the connected system models from the former level as shown in Figure 4.

At the bottom level of each subsystem, the primitive system model will be established by utilizing the governing equation or the fundamental law of each individual element. That fundamental law, such as Newton's law or Ohm's law, describes the local behavior of that element. Direct and indirect connections that resemble the internal constraints within the boundaries of each subsystem define the transformation from the primitive system model to the connected system model. For systems with linear connections such as direct current servomotor, the internal constraints are given by one connection object, the velocity object (V). The velocity object is a 2- dimensional array, the rows in that array correspond to the variables in the primitive system (local variables) and the columns correspond to the variables in the connected system (global variables). Thus, the velocity object is a transformation from the global variables in the connected system model to local variables in the primitive system model.

The model of the physical system is set up by aggregating diagonally the connected system models of the hydraulic subsystem and the boring spindle. Modelling the physical system resulted in a set of different all algebraic equations [7]. In a state space form, the behavior of the physical system is given by: y = ~ ( A , x , u , ~ ) Where ( x ) is the set of initial state variables, ( u ) is the set of input sources, ( A ) is the state transition matrix for the physical specific control function of truth or falsehood (1 0).

3.2 Control System Modelling Before a control algorithm can be designed and implemented we need a description of its required properties or behavior. A precise and comprehensive mathematical model of the properties of the control system could be expressed by employing logic notation. This mathematical model provides us with means to reveal the inconsistency and conflicts in the control system and to verify that the control system meets design specifications. In order to carry out all control functions outlined in problem description, the control system should be decomposed into three subsystems. A process controller subsystem, which will be responsible to issue start and stop commands for the different physical entities and two continuos controllers. One controller for the servo valve in the hydraulic subsystem in order to regulate the feed forward motion of the hydraulic actuator. The second controller is for the servomotor in order to regulate the angular

speed of the spindle motor. The decomposition is shown in Figure 5.

The functions of each subsystem are described by a set of logical arguments or rules. Each of these logical arguments could be considered as a subsystem that can be decomposed further into a number of factious logical elements. These elements could be literally anything that could carry a logical variable that assumes either the stateof truth or falsehood (1 0). These elements represent the primitive system model of aspecific control function.The procedure of modelling the control system will also move upward along the hierarchy until a total model is obtained as shown in Figure 6.

In the primitive system model, the connections between the logical variables are defined by three connection objects. In classical logic, they are referred to as basic logical connectives. The group of basic logical connectives includes; conjunction (AND) , disjunction (OR), and

negation (NOT). We propagate to the connected system model by aggregating the logical variables in the primitive system using the above logical connectives. A connected subsystem is nothing else but the truth table of a logical argument expressed in a multi-dimensional array form. The number of axes in that array should be equal to the number of variables, therefore all repeated axes must be fused together by the method of colligation. The connected system expresses all the possible states of the system after imposing the internal constraints on the structure by connecting its individual elements. The behavior of the control system could be represented in the following form s = f( p , , i , n ) . Where, (0) is a set of input variables that is external constraints due to interaction with the environment. (P,) is the state transition matrix of the control system expressed in multidimensional array format. (s) is a set of output variables. The index ( n ) is analogues to a time index in that it specifies the order of a given state.

3.3 Model of The Total System

Since both systems utilize different types of signals internally, then intuitively speaking, the only possible interface between the physical and the control system model will take place externally, through the environment by means of the impressed sources. In the above manufacturing system, we can distinguish between two ways of interface between the physical and the control system. Discrete interface: takes place in the process controller when the purpose of the control system is to coordinate asynchronous tasks to satisfy system requirements. For example, when an event command "start the spindle motor" is issued by the process controller, the spindle motor starts rotating. The process of rotation itself is controlled by the lower level controller (continuos controller). Continuous interface: takes place locally on lower level control schemes when the purpose of the control system is to keep the behavior of the physical system within given boundaries such as implementing speed control. The resultant system model in this case is said to be a hybrid system model. The identifying characteristics of hybrid systems are that they incorporate both continuos dynamic behavior, i.e., the evolution of physical quantities governed by differential and algebraic equations ( y = f ( A , x , u , r ) ), and discrete event dynamic behavior governed by logic equations: ( s = f ( p , , i , n ) ). A total model can be obtained by generating a simple interface between the physical system model and the control system model. The interface will be consisting of two simple memoryless mapping functions ( a ) and ( p ) [l]. The first map ( a ) converts the controller output (s) into a constant incremental input to the physical system as follows: u ( i ) = a ( s n ) The second map ( p ) converts the physical system output into a set of input logic variables to the control system as follows: i= p ( y ( r ) ) , as shown in Figure 7.

What we have gained so far is establishing a consistent and complete mathematical descript ion of mechatronics system model by using arrays to identify the properties of the whole system. The interface between the submodels is kept as simple as possible by employing simple mapping functions.

4. SIMULATION

Considering that the whole system is at rest and the boring spindle is at the rear position and the user has just pressed start button. The combination of input signal from the breakers and from the interface with the physical system will cause the control system to attain a new state and consequently a new set of output logical variables will be generated. This combination of output signals will cause the boring spindle to start moving forward in a rapid phase motion (uncontrolled motion). At the same time the spindle motor will be switched on and start rotating. However, since the spindle motor has not yet reached the feeding position, this rotation speed will remain unaffected by the servo motor control algorithm. Simulation for the angular velocity of the spindle motor is shown in Figure 8.

It is shown from Figure 8 that the spindle motor will attain a constant rotation speed of 3173 rpm. after a transient period of about 5 seconds. The spindle motor was simulated assuming zero load torque on the spindle that is because the boring spindle has not yet reached feeding position. The objective of the control system will be to keep spindle motor within 3000 r.p.m. under all loading conditions. Simulation of the linear speed and the differential pressure of the hydraulic actuator is shown in Figure 9. I t shows that the rapid phase velocity of the actuator is about 6cm/sec.

The system will continue to operate within the boundaries shown in Figure 8 and Figure 9 until i t receives a new set of input sources. That set will be initiated when the boring spindle reaches position M.

Due to the signals generated from the interface with physical system, which is no longer at rest, combined with a new set of signals from the micro breakers. The control system will attain a new state and generate another set of output signals to be interpreted by the mapping function and converted into new input physical signals. In this case, the boring spindle w ill go from rapid phase motion (6cmkec) to a controlled feed forward motion in such way that the feed forward motion will be kept at 2cm/sec, and the rotating speed of the spindle motor should be reduced from 3173 r.p.m. to be within 3000 r.p.m. under all loading conditions. The actuator linear velocity will be controlled by the servo valve controller algorithm. And the boring spindle motor will be controlled by the servo motor controller algorithm. Assuming that the servomotor is subjected to cosine load torque given by ( q = 2 x cost ) and the hydraulic cylinder is subjected to load force given by ( F ~ = 0.0s x c o s t ) . Simulation results are shown in Figure 10 and Figure 1 1.

The simulation shows that the output speed of both the spindle motor and the actuator cylinder are kept within the boundaries specified by control algorithm.

5. CONCLUSIONS

A systems approach that utilizes multidimensional arrays for modelling mechatronics systems has been proposed and presented in this paper. The array approach provided us with a powerful mathematical representation of the real system. By utilizing multidimensional arrays we set up two submodels embodying the physical and the logical properties of mechatronics system. The interface between these two submodels is kept as simple as possible by employing a simple mapping functions.

6. REFERENCES

Antsaklis, et. al. 1993, Hybrid system modelling and autonomous control systems. Hybrid systems workshop, Technical university of Denmark.

Bjrarke, 0., 1989, Manufacturing systems theory - A survey paper- keynote paper at the ClRP general assembly, Trondheim-Norway

Bjrarke, 0., 1995, Manufacturing systems theory - A geometric approach to connection. Tapir- Trondheim

Franksen, Ole I., 1992, The geometry of logic, from truth tables to nested arrays. The 4th international symposium on systems analysis and simulations. Berlin

Harashima, et. al. 1996, Mechatronics- What is it, why, and how?. IEEWASME Transactions on Mechatronics, Vol.1, No.

Hussein, B.A., 1997, On modelling mechatronics systems. NTNU report, Trondheim, Norway Isermann, R., 1996, Modelling and design methodology for mechatronics system. IEEE/ASME Transactions on Mechatronics, Vol.1, No.

Mprller, G. L, 1995, On the technology of array based logic. Ph. D. dissertation Electric power engineering department, Technical University of Denmark

建立机电一体化模型的系统方法

Bassam A. Hussein

生产和质量工程部，挪威科技大学，师大，

挪威特隆赫姆

1997年11月3日

摘要

本文介绍了一个统一的基于利用多维阵列以模拟物理和逻辑机电系统的性能。机电系统模型由两个相互作用的子模型描述与物理系统的能量流方面，和另一个子模型，介绍了有关控制系统中的信息流方面。多维数组的建模方法，为我们提供的可能性，使用的术语和相同的两个子系统建模形式主义。使用相同的形式主义的后果是，机电系统的仿真，可以只使用一个仿真环境

关键词：机电一体化，系统建模

1. 引言

机电一体化系统就是在工业产品设计和制造的过程中综合了电子和计算机控制的机械产品设计的协同作用的协同整合[5]。机电一体化系统在最初级阶段就必须考虑到各个学科对于本系统的约束。因此，适当的系统设计将在很大程度上依赖于整个设计和原型阶段使用的建模与仿真。集成了机电一体化的系统通过硬件的组合来影响物理系统还有信息处理系统来影响智能控制系统来执行它的功能[7]。

机电系统是基于计算机控制系统的应用物理系统的结果。控制系统设计实时执行的命令，以选择、增强和监督物理系统的正常运行。唯一可能验证这些控制功能可以将这整个系统的动作在我们建立边界之前就能明显的区分开来的途径，就是建立一个同时包括硬件和软件部分的包括所有约束条件的全真的系统模型。这表明了一个真正的系统模型必须强大到足以捕获所有的机电一体化系统的性能。这包括动态、静态的、离散事件，以及逻辑的上的与真正的系统的成本以及相关的属性和任务，不忽视其中任何零散的建模方法。在本文中，我们提出了一个统一的机电一体化系统的建模方法。这种统一的方法是利用几何对象或多维数组来制定机电一体化系统的型号。多维数组的建模方法，为我们提供了可能使用相同的形式主义，种类繁多的系统[2,3,4,9]。使用相同的形式主义的后果是，机电一体化系统的仿真可以只使用一个仿真环境中进行。

2．模型结构

直观地说，一个用来描述给定系统的动态行为的模型并不能用来研究一个完全相同的系统的静态行为。因此，为了捕获所有相关信息，我们需要用到多种型号的模型，其中每一个模型封装真实系统的某些方面。我们会考虑的机电一体化系统模型作为一套综合在一起的子模型集，每个子模型对应真实系统的一些方面。所以从这个角度讲，长期的关联被用来强调这些子模型的变量之间的依赖关系。整个建模过程中，我们应当区分以下概念，见图1。

分解：为了处理复杂的机电一体化系统，他们应该被分解成子系统。这样进行了一个多层次的分解，直到我们达到构成整个系统的基本要素。原始系统模型应该是对一个断开状态下的系统的描述。它表示在这些元素之间互不影响时一个独立的元素的变量之间的关系。通过这个模型，我们

隔离每个元素特定的行为，比如静态，动态等。对局部变量再义一个给定的元素的行为。一个联合的系统模型在描述了相同的系统的同时还要考虑到系统内部的制约。局部变量的间接相关或直接相关以及连接系统变量间的连接的方式给系统以内部约束。相互关联的系统模型就类似于真正的系统的实际结构。应用的来源是由系统和环境之间的相互作用产生的。他们可以被看作是系统或形式存储在系统要素的能源，甚至是在固有的限制下施加外部约束。

3. 应用实例

图2所示的是制造系统。

该系统包含一个由直流电动机驱动的镗杆。镗主轴向前运动的进给运动采用液压线性驱动的方法。液压执行机构是一个恒定的压力液压泵，由伺服阀控制液压回路中的体积流量[8]。上述制造系统具有以下规格：镗轴的位置由三个微型断路器来感应，断路器（B）表明镗主轴是在后方的位置。在后方位置的快速阶段（I）将切换阀，以便快速向前运动（F），信号（S）将切换主轴电机。断路器（M）用来表明镗主轴是否已达进给位置。在这个位置上的快速阶段阀将关闭以开始控制进给运动。这项动作是由伺服阀（ST）监管。断路器（€）用来表明镗主轴已达到其最后的位置，在这个位置，反向运动（R）将开始，同时阶段阀（I）将被迅速的打开，以便快速向后运动。同时还规定主轴电机转速应保持3000r/min，同时在所有负载条件下必须保持进给速度2cm/sec。我们的目标是建立一个完整的模型和系统，使多维数组在实验模型验证中均能达到我们的要求。

3.1物理系统建模

物理系统建模时，我们需要关注的是融合在这个系统的物理变量的演化建模。物理系统的分解如图3所示。

基本物理元素组分为三类：广义电阻：如普通电阻，机械阻尼器，液压电阻。广义电容：如电力电容器，机械弹簧，液压水库。广义电感：如电动机械电感，质量，和液压电感。基本要素分解成子系统，物理系统内各子系统的物理量的演变进一步的分解，以让每个子系统的功能得以实现。这种可以随时感知的优势，将在每个控制系统的设计阶段成为现实。建立模型可以被视为分解系统的相反过程。所不同的是，在分解的过程中我们是将系统划分成独立的物理实体的子系统，而在建模过程中我们是重新对这些物理实体组合建成模型。因此，建立模型可以看作为将这些子系统重新组合的过程。

在建模时我们刚开始在这些所有层次的最底层，在每个级别上，我们从原始系统模型进而到全部关联起来的系统模型。在随后的层面，原始的系统模型，然后建立由前一级连接的系统模型如图4所示。

在各子系统的最底层，原始系统模型将利用方程或每个元素的基本规则来建立。这些基本规则如牛顿定律或欧姆定律，用来说明该元素的原本动作。直接和间接的关联就类似于各子系统的转变，从原始的系统模型定义关联之后的系统模型的边界内的内部制约。如直流伺服电机的线性连接的系

统，一个连接对象，速度对象（V）内部制约。速度对象是一个二维数组，该数组中的行对应在原始系统中的变量（局部变量），列对应的变量在连接系统（全局变量）。因此，速度的目的是在连接的系统模型，以实现原始的系统模型中的局部变量、全局变量的转变。

?通过聚合对角线的连接的液压子系统和镗主轴系统模型的物理系统的模型建立，模型的物理系统中[7]所有不同的代数方程组。在状态矢量空间，物理系统的运动方程是：Y =（，X，U，?），其中（x）是初始状态变量，（U）是输入源，（A）是为控制具体的物理功能的状态是真或假的（1 0）转移矩阵。

?

? 3.2在控制算法之前控制系统建模

?在控制算法之前控制系统建模，可以设计和实施我们需要描述的属性或行为。一个准确和全面的数学模型控制系统的性能可以用逻辑符号表示。这个数学模型，为我们提供了揭示在控制系统中的互相冲突的方法，同时可以验证该控制系统是否满足我们的设计规范，这样就可以开展问题说明我们列出的所有控制功能。控制系统应分解成三个子系统，一个过程控制器子系统，这将是负责发出启动和停止不同的物理实体和两个连续的控制器命令。一个是控制器伺服阀的液压子系统，以约束进给液压执行机构的运动。另一个是为伺服电机，主轴电机调节角速度的控制器。如图5所示的分解。

每个子系统的功能是由一组逻辑来约束。这些元素可以携带一个假定的真理或谬误（1 0）的逻辑变量。这些元素代表原始的具有普通的控制功能的系统模型。而模拟控制系统的程序也将沿着层次结构向上，直到总的模型，得到如图6所示。

在原始系统模型，逻辑变量之间的关联是指由三个对象的连接。在经典逻辑，他们被称为基本逻辑连接词，包括基本的逻辑连接词，如结合（AND），分离（OR），否定（NOT）。我们传送到所连接的系统模型，通过聚集在原始系统中使用上述逻辑连接词的逻辑变量。

连接子系统的不是别的，而是在一个多维数组的形式上表达逻辑论证的真值表。该数组中的轴数应该等于变量的数目，因此，所有重复的轴必须绑扎方法融合在一起。连接系统在连接各个元素的结构后对系统的所有可能的状态应该实行内部制约。控制系统的行为，可以在以下形式表示小号= F （P，I，N）。其中，（0）是输入变量的集合，是由于外部约束与环境的相互作用（P）是多维数组，表示控制系统的状态转移矩阵（S）是一组输出变量。该指数（n）是时间指数，它指定一个同样条件情况下给定的状态。

3.3总系统模型

由于这两个系统内部使用不同类型的信号，直观地说，物理和控制系统模型之间唯一可能的接口采取的是通过外部环境来联通。在上面的制造系统，我们可以将物理和控制系统区分为两种接口方式：离散界面：在这个过程中的控制器中的控制系统的目的是协调异步任务，以满足系统的要求。例如，当由程序控制器发出一个事件命令“启动主轴电机”时，主轴电机开始转动。在旋转过程本身是由下级控制器（连续控制器）控制。连续界面：处于较低的水平控制级别的地方，目的是为了保持物理系统的运动，如使其执行速度处于控制界限内。在这种情况下产生的系统模型被认为是一个混合动力系统模型。混合动力系统的识别特征是它们包含两个连续的动态行为，即，微分代数方程（Y = F（A，X，U，R））和离散事件动态行为受约束的物理量的演变逻辑方程：（S = F（P，I，N））。一个总的模型可以由一个简单的接口连接的物理系统模型和控制系统模型来组成。该接口将包括两个简单的记忆映射功能（a）和（p）[1]。第一个（a）转换成一个常数的增量输入，物理系统的控制器输出如下：（S）：U（I）=（SN）第二个（P）转换成物理系统输出的输入，逻辑变量的一套控制系统如下：I= P（Y（R）），如图7所示。

通过使用数组来确定整个系统的性能，这是我们迄今取得是建立一致和完整的机电一体化系统模型的数学描述。子模型之间的接口应采用简单的映射功能，并且保持尽可能简单。

4.模拟

我们可以看到整个控制系统是在主轴后方的位置，用户只需按下启动按钮。断路器和物理系统的接口输入信号的组合将使控制系统达到一个新的状态，因此将会产生一套新的输出逻辑变量。这种输出信号的组合将导致镗轴开始运动（不受控制的约束）在快速阶段向前迈进。同时将开启主轴电机开始旋转。然而，由于主轴电机尚未达到进给位置，将保持这个由伺服电机控制算法的影响的转速。主轴电机角速度仿真如图8所示。

从图8所示，主轴电机将达到3173转的恒定转速后约5秒钟的短暂。主轴电机是模拟假设零负载转矩主轴，是因为主轴尚未达到进给的位置上，将所有负载条件下保持在3000转主轴电机控制系统的目的。如图9所示的线性速度和液压执行器压差模拟。我T显示，快速的执行机构相速度是6cm/sec。

该系统将在图8和图9所示的边界范围内操作，直到它接收到新的输入源。该集将启动时，镗主轴到达M处。控制系统将达到一个新的状态，并产生另一种映射功能并转换成新的输入输出信号集。在这种情况下，镗主轴将进入快速运动阶段（6cmkec），进给运动将保持在2cm/sec的速度，主轴电机这在这样负载条件下转速应从3173转减少到3000转以内。执行器的线性速度将由伺服阀控制算法来控制。镗主轴的电机由伺服电机控制算法来控制。现在假设收到余弦负载转矩伺服电机（q = 2 x cost）和液压缸受到加载（F=0.0sxcost）共同作用的负载，其模拟结果如图10和图11。

仿真结果表明，主轴电机和油缸的输出速度控制算法由保持在指定的边界内。

5. 结论

现在已经提出了一个系统的方法，利用建模，机电系统的多维数组和本文提出的阵列的方法提供了强大的实时系统的数学表示。利用多维数组，我们设立了两个子模型，体现了机电一体化系统的物理和逻辑特性。这两个子模型之间的接口保持尽可能简单，并采用一个简单的映射功能。

6．参考文献

Antsaklis, et. al. 1993年，混合动力系统建模与自主控制系统，混合动力系统车间，丹麦技术大学。Bjrarke, 0., 1989年制造系统理论----ClRP大会一个调查纸基调纸，特隆赫姆 - 挪威

Bjrarke, 0., 1995年，制造系统的理论 - 几何方法来连接，T apir- Trondheim

Franksen, Ole I., 1992年，几何逻辑，从真值表嵌套数组，第四届国际研讨会上系统的分析和模拟，柏林

Harashima, et. al. 1996年，机电一体化是什么，为什么，怎么样？机电一体化，第一卷Hussein, B.A., 1997年，机电一体化系统的建模，师大的报告，挪威特隆赫姆

Isermann, R., 1996年，机电一体化系统的建模与设计方法，机电一体化，第一卷， IEEE / ASME 标准

Mprller, G. L, 1995年，阵列技术为基础的逻辑，电力工程部门博士论文，丹麦科技大学

机械专业外文翻译(中英文翻译)

外文翻译 英文原文 Belt Conveying Systems Development of driving system Among the methods of material conveying employed，belt conveyors play a very important part in the reliable carrying of material over long distances at competitive cost．Conveyor systems have become larger and more complex and drive systems have also been going through a process of evolution and will continue to do so．Nowadays，bigger belts require more power and have brought the need for larger individual drives as well as multiple drives such as 3 drives of 750 kW for one belt(this is the case for the conveyor drives in Chengzhuang Mine)．The ability to control drive acceleration torque is critical to belt conveyors’performance．An efficient drive system should be able to provide smooth，soft starts while maintaining belt tensions within the specified safe limits．For load sharing on multiple drives．torque and speed control are also important considerations in the drive system’s design. Due to the advances in conveyor drive control technology，at present many more reliable．Cost-effective and performance-driven conveyor drive systems covering a wide range of power are available for customers’ choices[1]. 1 Analysis on conveyor drive technologies 1．1 Direct drives Full-voltage starters．With a full-voltage starter design，the conveyor head shaft is direct-coupled to the motor through the gear drive．Direct full-voltage starters are adequate for relatively low-power, simple-profile conveyors．With direct fu11-voltage starters．no control is provided for various conveyor loads and．depending on the ratio between fu11-and no-1oad power requirements，empty starting times can be three or four times faster than full load．The maintenance-free starting system is simple，low-cost and very reliable．However, they cannot control starting torque and maximum stall torque；therefore．they are

毕业论文英文参考文献与译文

Inventory management Inventory Control On the so-called "inventory control", many people will interpret it as a "storage management", which is actually a big distortion. The traditional narrow view, mainly for warehouse inventory control of materials for inventory, data processing, storage, distribution, etc., through the implementation of anti-corrosion, temperature and humidity control means, to make the custody of the physical inventory to maintain optimum purposes. This is just a form of inventory control, or can be defined as the physical inventory control. How, then, from a broad perspective to understand inventory control? Inventory control should be related to the company's financial and operational objectives, in particular operating cash flow by optimizing the entire demand and supply chain management processes (DSCM), a reasonable set of ERP control strategy, and supported by appropriate information processing tools, tools to achieved in ensuring the timely delivery of the premise, as far as possible to reduce inventory levels, reducing inventory and obsolescence, the risk of devaluation. In this sense, the physical inventory control to achieve financial goals is just a means to control the entire inventory or just a necessary part; from the perspective of organizational functions, physical inventory control, warehouse management is mainly the responsibility of The broad inventory control is the demand and supply chain management, and the whole company's responsibility. Why until now many people's understanding of inventory control, limited physical inventory control? The following two reasons can not be ignored: First, our enterprises do not attach importance to inventory control. Especially those who benefit relatively good business, as long as there is money on the few people to consider the problem of inventory turnover. Inventory control is simply interpreted as warehouse management, unless the time to spend money, it may have been to see the inventory problem, and see the results are often very simple procurement to buy more, or did not do warehouse departments . Second, ERP misleading. Invoicing software is simple audacity to call it ERP, companies on their so-called ERP can reduce the number of inventory, inventory control, seems to rely on their small software can get. Even as SAP, BAAN ERP world, the field of

电气自动化专业毕业论文英文翻译

电厂蒸汽动力的基础和使用 1.1 为何需要了解蒸汽 对于目前为止最大的发电工业部门来说, 蒸汽动力是最为基础性的。 若没有蒸汽动力, 社会的样子将会变得和现在大为不同。我们将不得已的去依靠水力发电厂、风车、电池、太阳能蓄电池和燃料电池,这些方法只能为我们平日用电提供很小的一部分。 蒸汽是很重要的,产生和使用蒸汽的安全与效率取决于怎样控制和应用仪表,在术语中通常被简写成C&I(控制和仪表 。此书旨在在发电厂的工程规程和电子学、仪器仪表以 及控制工程之间架设一座桥梁。 作为开篇,我将在本章大体描述由水到蒸汽的形态变化,然后将叙述蒸汽产生和使用的基本原则的概述。这看似简单的课题实际上却极为复杂。这里, 我们有必要做一个概述:这本书不是内容详尽的论文,有的时候甚至会掩盖一些细节, 而这些细节将会使热力学家 和燃烧物理学家都为之一震。但我们应该了解,这本书的目的是为了使控制仪表工程师充 分理解这一课题,从而可以安全的处理实用控制系统设计、运作、维护等方面的问题。1.2沸腾:水到蒸汽的状态变化 当水被加热时,其温度变化能通过某种途径被察觉(例如用温度计 。通过这种方式 得到的热量因为在某时水开始沸腾时其效果可被察觉,因而被称为感热。 然而,我们还需要更深的了解。“沸腾”究竟是什么含义?在深入了解之前,我们必须考虑到物质的三种状态:固态,液态,气态。 (当气体中的原子被电离时所产生的等离子气体经常被认为是物质的第四种状态, 但在实际应用中, 只需考虑以上三种状态固态,

物质由分子通过分子间的吸引力紧紧地靠在一起。当物质吸收热量,分子的能量升级并且 使得分子之间的间隙增大。当越来越多的能量被吸收,这种效果就会加剧,粒子之间相互脱离。这种由固态到液态的状态变化通常被称之为熔化。 当液体吸收了更多的热量时,一些分子获得了足够多的能量而从表面脱离,这个过程 被称为蒸发(凭此洒在地面的水会逐渐的消失在蒸发的过程中,一些分子是在相当低的 温度下脱离的,然而随着温度的上升,分子更加迅速的脱离,并且在某一温度上液体内部 变得非常剧烈,大量的气泡向液体表面升起。在这时我们称液体开始沸腾。这个过程是变为蒸汽的过程,也就是液体处于汽化状态。 让我们试想大量的水装在一个敞开的容器内。液体表面的空气对液体施加了一定的压 力,随着液体温度的上升,便会有足够的能量使得表面的分子挣脱出去,水这时开始改变 自身的状态,变成蒸汽。在此条件下获得更多的热量将不会引起温度上的明显变化。所增 加的能量只是被用来改变液体的状态。它的效用不能用温度计测量出来,但是它仍然发生 着。正因为如此,它被称为是潜在的,而不是可认知的热量。使这一现象发生的温度被称为是沸点。在常温常压下,水的沸点为100摄氏度。 如果液体表面的压力上升, 需要更多的能量才可以使得水变为蒸汽的状态。 换句话说, 必须使得温度更高才可以使它沸腾。总而言之,如果大气压力比正常值升高百分之十,水必须被加热到一百零二度才可以使之沸腾。

毕业论文外文翻译模版

吉林化工学院理学院 毕业论文外文翻译English Title（Times New Roman ，三号） 学生学号：08810219 学生姓名：袁庚文 专业班级：信息与计算科学0802 指导教师：赵瑛 职称副教授 起止日期：2012.2.27～2012.3.14 吉林化工学院 Jilin Institute of Chemical Technology

1 外文翻译的基本内容 应选择与本课题密切相关的外文文献（学术期刊网上的），译成中文，与原文装订在一起并独立成册。在毕业答辩前，同论文一起上交。译文字数不应少于3000个汉字。 2 书写规范 2.1 外文翻译的正文格式 正文版心设置为：上边距：3.5厘米，下边距：2.5厘米，左边距：3.5厘米，右边距：2厘米，页眉：2.5厘米，页脚：2厘米。 中文部分正文选用模板中的样式所定义的“正文”，每段落首行缩进2字；或者手动设置成每段落首行缩进2字，字体：宋体，字号：小四，行距：多倍行距1.3，间距：前段、后段均为0行。 这部分工作模板中已经自动设置为缺省值。 2.2标题格式 特别注意：各级标题的具体形式可参照外文原文确定。 1．第一级标题（如：第1章绪论）选用模板中的样式所定义的“标题1”，居左；或者手动设置成字体：黑体，居左，字号：三号，1.5倍行距，段后11磅，段前为11磅。 2．第二级标题（如：1.2 摘要与关键词）选用模板中的样式所定义的“标题2”，居左；或者手动设置成字体：黑体，居左，字号：四号，1.5倍行距，段后为0，段前0.5行。 3．第三级标题（如：1.2.1 摘要）选用模板中的样式所定义的“标题3”，居左；或者手动设置成字体：黑体，居左，字号：小四，1.5倍行距，段后为0，段前0.5行。 标题和后面文字之间空一格（半角）。 3 图表及公式等的格式说明 图表、公式、参考文献等的格式详见《吉林化工学院本科学生毕业设计说明书（论文）撰写规范及标准模版》中相关的说明。

电气供配电系统大学毕业论文英文文献翻译及原文

毕业设计（论文） 外文文献翻译 文献、资料中文题目：供配电系统 文献、资料英文题目：POWER SUPPLY AND DISTRIBUTION SYSTEM 文献、资料来源： 文献、资料发表（出版）日期： 院（部）： 专业： 班级： 姓名： 学号： 指导教师： 翻译日期： 2017.02.14

POWER SUPPLY AND DISTRIBUTION SYSTEM ABSTRACT The basic function of the electric power system is to transport the electric power towards customers. The l0kV electric distribution net is a key point that connects the power supply with the electricity using on the industry, business and daily-life. For the electric power, allcostumers expect to pay the lowest price for the highest reliability, but don't consider that it's self-contradictory in the co-existence of economy and reliable.To improve the reliability of the power supply network, we must increase the investment cost of the network construction But, if the cost that improve the reliability of the network construction, but the investment on this kind of construction would be worthless if the reducing loss is on the power-off is less than the increasing investment on improving the reliability .Thus we find out a balance point to make the most economic,between the investment and the loss by calculating the investment on power net and the loss brought from power-off. KEYWARDS：power supply and distribution,power distribution reliability，reactive compensation,load distribution

机械类英语论文及翻译翻译

High-speed milling High-speed machining is an advanced manufacturing technology, different from the traditional processing methods. The spindle speed, cutting feed rate, cutting a small amount of units within the time of removal of material has increased three to six times. With high efficiency, high precision and high quality surface as the basic characteristics of the automobile industry, aerospace, mold manufacturing and instrumentation industry, such as access to a wide range of applications, has made significant economic benefits, is the contemporary importance of advanced manufacturing technology. For a long time, people die on the processing has been using a grinding or milling EDM (EDM) processing, grinding, polishing methods. Although the high hardness of the EDM machine parts, but the lower the productivity of its application is limited. With the development of high-speed processing technology, used to replace high-speed cutting, grinding and polishing process to die processing has become possible. To shorten the processing cycle, processing and reliable quality assurance, lower processing costs. 1 One of the advantages of high-speed machining High-speed machining as a die-efficient manufacturing, high-quality, low power consumption in an advanced manufacturing technology. In conventional machining in a series of problems has plagued by high-speed machining of the application have been resolved. 1.1 Increase productivity High-speed cutting of the spindle speed, feed rate compared withtraditional machining, in the nature of the leap, the metal removal rate increased 30 percent to 40 percent, cutting force reduced by 30 percent, the cutting tool life increased by 70% . Hardened parts can be processed, a fixture in many parts to be completed rough, semi-finishing and fine, and all other processes, the complex can reach parts of the surface quality requirements, thus increasing the processing productivity and competitiveness of products in the market. 1.2 Improve processing accuracy and surface quality High-speed machines generally have high rigidity and precision, and other characteristics, processing, cutting the depth of small, fast and feed, cutting force low, the workpiece to reduce heat distortion, and high precision machining, surface roughness small. Milling will be no high-speed processing and milling marks the surface so that the parts greatly enhance the quality of the surface. Processing Aluminum when up Ra0.40.6um, pieces of steel processing at up to Ra0.2 ~ 0.4um.

英语专业毕业论文翻译类论文

英语专业毕业论文翻译 类论文 Document number：NOCG-YUNOO-BUYTT-UU986-1986UT

毕业论文（设计）Title:The Application of the Iconicity to the Translation of Chinese Poetry 题目:象似性在中国诗歌翻译中的应用 学生姓名孔令霞 学号 BC09150201 指导教师祁晓菲助教 年级 2009级英语本科（翻译方向）二班 专业英语 系别外国语言文学系

黑龙江外国语学院本科生毕业论文（设计）任务书 摘要

索绪尔提出的语言符号任意性，近些年不断受到质疑，来自语言象似性的研究是最大的挑战。语言象似性理论是针对语言任意性理论提出来的，并在不断发展。象似性是当今认知语言学研究中的一个重要课题，是指语言符号的能指与所指之间的自然联系。本文以中国诗歌英译为例，探讨象似性在中国诗歌翻译中的应用，从以下几个部分阐述：（1）象似性的发展；（2）象似性的定义及分类；（3）中国诗歌翻译的标准；（4）象似性在中国诗歌翻译中的应用，主要从以下几个方面论述：声音象似、顺序象似、数量象似、对称象似方面。通过以上几个方面的探究，探讨了中国诗歌翻译中象似性原则的重大作用，在诗歌翻译过程中有助于得到“形神皆似”和“意美、音美、形美”的理想翻译效果。 关键词：象似性；诗歌；翻译

Abstract The arbitrariness theory of language signs proposed by Saussure is severely challenged by the study of language iconicity in recent years. The theory of iconicity is put forward in contrast to that of arbitrariness and has been developing gradually. Iconicity, which is an important subject in the research of cognitive linguistics, refers to a natural resemblance or analogy between the form of a sign and the object or concept. This thesis mainly discusses the application of the iconicity to the translation of Chinese poetry. The paper is better described from the following parts: (1) The development of the iconicity; (2) The definition and classification of the iconicity; (3) The standards of the translation to Chinese poetry; (4) The application of the iconicity to the translation of Chinese poetry, mainly discussed from the following aspects: sound iconicity, order iconicity, quantity iconicity, and symmetrical iconicity. Through in-depth discussion of the above aspects, this paper could come to the conclusion that the iconicity is very important in the translation of poetry. It is conductive to reach the ideal effect of “the similarity of form and spirit” and “the three beauties”. Key words: the iconicity; poetry; translation

机械类数控车床外文翻译外文文献英文文献车床.doc

Lathes Lathes are machine tools designed primarily to do turning, facing and boring, Very little turning is done on other types of machine tools, and none can do it with equal facility. Because lathes also can do drilling and reaming, their versatility permits several operations to be done with a single setup of the work piece. Consequently, more lathes of various types are used in manufacturing than any other machine tool. The essential components of a lathe are the bed, headstock assembly, tailstock assembly, and the leads crew and feed rod. The bed is the backbone of a lathe. It usually is made of well normalized or aged gray or nodular cast iron and provides s heavy, rigid frame on which all the other basic components are mounted. Two sets of parallel, longitudinal ways, inner and outer, are contained on the bed, usually on the upper side. Some makers use an inverted V-shape for all four ways, whereas others utilize one inverted V and one flat way in one or both sets, They are precision-machined to assure accuracy of alignment. On most modern lathes the way are surface-hardened to resist wear and abrasion, but precaution should be taken in operating a lathe to assure that the ways are not damaged. Any inaccuracy in them usually means that the accuracy of the entire lathe is destroyed. The headstock is mounted in a foxed position on the inner ways, usually at the left end of the bed. It provides a powered means of rotating the word at various speeds . Essentially, it consists of a hollow spindle, mounted in accurate bearings, and a set of transmission gears-similar to a truck transmission—through which the spindle can be rotated at a number of speeds. Most lathes provide from 8 to 18 speeds, usually in a geometric ratio, and on modern lathes all the speeds can be obtained merely by moving from two to four levers. An increasing trend is to provide a continuously variable speed range through electrical or mechanical drives. Because the accuracy of a lathe is greatly dependent on the spindle, it is of heavy construction and mounted in heavy bearings, usually preloaded tapered roller or ball types. The spindle has a hole extending through its length, through which long bar stock can be fed. The size of maximum size of bar stock that can be machined when the material must be fed through spindle. The tailsticd assembly consists, essentially, of three parts. A lower casting fits on the inner ways of the bed and can slide longitudinally thereon, with a means for clamping the entire assembly in any desired location, An upper casting fits on the lower one and can be moved transversely upon it, on some type of keyed ways, to permit aligning the assembly is the tailstock quill. This is a hollow steel cylinder, usually about 51 to 76mm(2to 3 inches) in diameter, that can be moved several inches longitudinally in and out of the upper casting by means of a hand wheel and screw. The size of a lathe is designated by two dimensions. The first is known as the swing. This is the maximum diameter of work that can be rotated on a lathe. It is approximately twice the distance between the line connecting the lathe centers and the nearest point on the ways, The second size dimension is the maximum distance between centers. The swing thus indicates the maximum work piece diameter that can be turned in the lathe, while the distance between centers indicates the maximum length of work piece that can be mounted between centers. Engine lathes are the type most frequently used in manufacturing. They are heavy-duty machine tools with all the components described previously and have power drive for all tool movements except on the compound rest. They commonly range in size from 305 to 610 mm(12 to 24 inches)swing and from 610 to 1219 mm(24 to 48 inches) center distances, but swings up to 1270 mm(50 inches) and center distances up

大学毕业论文---软件专业外文文献中英文翻译

软件专业毕业论文外文文献中英文翻译 Object landscapes and lifetimes Tech nically, OOP is just about abstract data typing, in herita nee, and polymorphism, but other issues can be at least as importa nt. The rema in der of this sect ion will cover these issues. One of the most importa nt factors is the way objects are created and destroyed. Where is the data for an object and how is the lifetime of the object con trolled? There are differe nt philosophies at work here. C++ takes the approach that con trol of efficie ncy is the most importa nt issue, so it gives the programmer a choice. For maximum run-time speed, the storage and lifetime can be determined while the program is being written, by placing the objects on the stack (these are sometimes called automatic or scoped variables) or in the static storage area. This places a priority on the speed of storage allocatio n and release, and con trol of these can be very valuable in some situati ons. However, you sacrifice flexibility because you must know the exact qua ntity, lifetime, and type of objects while you're writing the program. If you are trying to solve a more general problem such as computer-aided desig n, warehouse man ageme nt, or air-traffic con trol, this is too restrictive. The sec ond approach is to create objects dyn amically in a pool of memory called the heap. In this approach, you don't know un til run-time how many objects you n eed, what their lifetime is, or what their exact type is. Those are determined at the spur of the moment while the program is runnin g. If you n eed a new object, you simply make it on the heap at the point that you n eed it. Because the storage is man aged dyn amically, at run-time, the amount of time required to allocate storage on the heap is sig ni fica ntly Ion ger tha n the time to create storage on the stack. (Creat ing storage on the stack is ofte n a si ngle assembly in structio n to move the stack poin ter dow n, and ano ther to move it back up.) The dyn amic approach makes the gen erally logical assumpti on that objects tend to be complicated, so the extra overhead of finding storage and releas ing that storage will not have an importa nt impact on the creati on of an object .In additi on, the greater flexibility is esse ntial to solve the gen eral program ming problem. Java uses the sec ond approach, exclusive". Every time you want to create an object, you use the new keyword to build a dyn amic in sta nee of that object. There's ano ther issue, however, and that's the lifetime of an object. With Ian guages that allow objects to be created on the stack, the compiler determines how long the object lasts and can automatically destroy it. However, if you create it on the heap the compiler has no kno wledge of its lifetime. In a Ianguage like C++, you must determine programmatically when to destroy the