控制工程外文文献翻译

中英文对照资料外文翻译文献外文文献：Designing Stable Control LoopsThe objective of this topic is to provide the designer with a practical review of loop compensation techniques applied to switching power supply feedback control. A top-down system approach is taken starting with basic feedback control concepts and leading to step-by-step design procedures, initially applied to a simple buck regulator and then expanded to other topologies and control algorithms. Sample designs are demonstrated with Math cad simulations to illustrate gain and phase margins and their impact on performance analysis.I. I NTRODUCTIONInsuring stability of a proposed power supply solution is often one of the more challenging aspects of the design process. Nothing is more disconcerting than to have your lovingly crafted breadboard break into wild oscillations just as its being demonstrated to the boss or customer, but insuring against this unfortunate event takes some analysis which many designers view as formidable. Paths taken by design engineers often emphasize either cut-and-try empirical testing in the laboratory or computer simulations looking for numerical solutions based on complex mathematical models. While both of these approach a basic understanding of feedback theory will usually allow the definition of an acceptable compensation network with a minimum of computational effort.II. S TABILITY D EFINEDFig. 1. Definition of stabilityFig. 1 gives a quick illustration of at least one definition of stability. In its simplest terms, a system is stable if, when subjected to a perturbation from some source, its response to that perturbation eventually dies out. Note that in any practical system, instability cannot result in a completely unbounded response as the system will either reach a saturation level –or fail. Oscillation in a switching regulator can, at most, vary the duty cycle between zero and 100% and while that may not prevent failure, it wills ultimate limit the response of an unstable system. Another way of visualizing stability is shown in Fig. 2. While this graphically illustrates the concept of system stability, it also points out that we must make a further distinction between large-signal and small-signal stability. While small-signal stability is an important and necessary criterion, a system could satisfy thisrt quirement and yet still become unstable with a large-signal perturbation. It is important that designers remember that all the gain and phase calculations we might perform are only to insure small-signal stability. These calculations are based upon – and only applicable to – linear systems, and a switching regulator is – by definition –a non-linear system. We solve this conundrum by performing our analysis using small-signal perturbations around a large-signal operating point, a distinction which will be further clarified in our design procedure discussion。

Control Technology1.Introduction to Control EngineeringWhenever energy is to be used purposefully, some form of control is necessary, in recent times there has been a considerable advance made in the art of automatic control. The art is, however, quite old, stemming back to about 1790 when James Watt invented the centrifugal governor to control the speed of his steam engines. He found that while in many applications an engine speed independent of load was removed the speed increased.In a simple centrifugal governor system, variations in engine speed are detected and used to control the pressure of the steam entering the engine. Under steady conditions the moment of the weight of the metal spheres balances that due to the centrifugal force and the steam valve opening is just sufficient to maintain the engine speed at the required level. When an extra load torque is applied to the engine, its speed will tend to fall, the centrifugal force will decrease and the metal spheres will tend to fall slightly. Their height controls the opening of the steam valve which now opens further to allow a greater steam pressure on the engine. The speed thus tends to rise, counteracting the original tendency for the speed to fall. If the extra load is removed, the reverse process takes place, the metal spheres tend to rise slightly, so tending to close the steam valve and counteracting any tendency for the speed to rise.It is obviously that without the governor the speed would fall considerably on land. However, in a correctly designed system with a governor the fall in speed would be very much less. An undesirable feature which accompanies a system which has been designed to be very sensitive to speed changes is the tendency to “hunt” or oscillate about the final speed. The real problem in the synthesis of all systems of this type is to prevent excessive oscillation but at the same time produce good “regulation”. Regulation is defined as the percentage change in controlled quantity on load relative to the value of the controlled under condition of zero load. Regulators form an important class of control system, their object generally being to keep some physical quantity constant (e.g. speed, voltage, liquid level, humidity, etc.) regardless of load variation. A good regulator has only very small regulation.The automatic control of various large-scale industrial processes, as encountered in the manufacture and treatment of chemicals, food and metals, has emerge duringthe last thirty years as an extremely important part of the general field of control engineering. In the initial stages of development it was scarcely realized that the theory of process control was intimately related to the theory of servomechanisms and regulators. Even nowadays complete academic design of process control systems is virtually impossible owing to our poor understanding of the dynamics of processes. In much of the theory introduced in this book, servomechanisms and regulators are used as example to illustrate the methods of analysis. These methods are, however, often applicable to process control systems, which will be themselves introduced separately.2. Programmable ControllersIn the 1960s, electromechanical devices were the order of the day as far as far as control was concerned. These devices, commonly known as relays, were being used by the thousands to control many sequential-type manufacturing processes and stand-alone machines. Many of these relays were in use in the transportation industry, more specifically, the automotive industry. These relays used hundreds of wires and their interconnections to affect a control solution. The performance of a relay panels called for 300 to 500 or more relays, and the reliability and maintenance issues associated with supporting these panels became a very great challenge. Cost became another issue, for in spite of the low cost of the relay itself, the installed cost of the panel could be quite high. The total cost including purchased parts, wiring, and installation labor, could range from ＄30～＄50 per relay. To make matters worse, the constantly changing needs of a process called for recurring modifications of a control panel. With relays, this was a costly prospect, as it was accomplished by a major rewiring effort on the panel. In addition, these changes were sometimes poorly documented, causing a second-shift maintenance nightmare months later. In light of this, it was not uncommon to discard an entire control panel in favor of a new one with the appropriate components wired in a manner suited for the new process. Add to this the unpredictable, and potentially high, cost of maintaining these systems as on high-volume motor vehicle production lines, and it became clear that something was needed to improve the control process-to make it more reliable, easier to troubleshoot, and more adaptable to changing control needs.That something, in the late 1960s, was the first programmable controller. This first “revolutionary” system was developed as a specific response to the needs of the major automotive manufacturers in the United States. These early controllers, or Programmable Logic Controllers(PLC), represented the first systems that (1)could beused on the factory floor, (2)could have there “logic” change without extensive rewiring or component changes, and(3)were easy to diagnose and repair when problems occurred. It is interesting to observe the progress that has been made in the past 15 years in the programmable controller area. The pioneer products of the late 1960s must have been confusing and frightening to a great number of people. For example, what happened to the hardwired and electromechanical devices that maintenance personnel were used to repairing with hand tools? They were replaced with “computers” disguised as electronics designed t o replace relays. Even the programming tools were designed to appear as relay equivalent presentations. We have the opportunity now to examine the promise, in retrospect, what the programmable controller brought manufacturing?Figure 10.1All programmable controllers consist of the basic functional blocks shown in Figure 10.1. We will examine each block to understand the relationship to the control system. First we looked at the center, as it is the heart of the system. It consists of a microprocessor, logic memory for the storage of the actual control logic, storage or variable memory for use with data that will ordinarily change as a function of the control program execution, and a power supply to provide electrical power for the processor and memory. Next comes the I/O block. This function takes the control level signals for the CPU and converts them to voltage and current levels suitable for connection with factory grade sensors and actuators. The I/O type can range from digital, analog, or a va riety of special purpose “smart” I/O which are dedicated to a certain application task. The programmer is normally used only to initially configure and program a system and is not required for the system to operate. It is also used in troubleshooting a system, and can prove to be a valuable tool in pinpointing the exactcause of a problem. The field devices shown here represent the various sensors and actuators connected to the I/O. These are the arms, legs, eyes, and ears of the system, including pushbuttons, limit switches, proximity switches, photo sensors, thermocouples, position sensing devices, and bar code reader as input; and pilot light, display devices, motor starters, DC and AC drivers, solenoids, and printers as outputs.控制技术1.控制工程绪论只要有目的地利用能量，都有必要采取某种控制形式。

外文文献翻译20106995 工机2班吴一凡注：节选自Neural Network Introduction神经网络介绍，绪论。

HistoryThe history of artificial neural networks is filled with colorful, creative individuals from many different fields, many of whom struggled for decades to develop concepts that we now take for granted. This history has been documented by various authors. One particularly interesting book is Neurocomputing: Foundations of Research by John Anderson and Edward Rosenfeld. They have collected and edited a set of some 43 papers of special historical interest. Each paper is preceded by an introduction that puts the paper in historical perspective.Histories of some of the main neural network contributors are included at the beginning of various chapters throughout this text and will not be repeated here. However, it seems appropriate to give a brief overview, a sample of the major developments.At least two ingredients are necessary for the advancement of a technology: concept and implementation. First, one must have a concept, a way of thinking about a topic, some view of it that gives clarity not there before. This may involve a simple idea, or it may be more specific and include a mathematical description. To illustrate this point, consider the history of the heart. It was thought to be, at various times, the center of the soul or a source of heat. In the 17th century medical practitioners finally began to view the heart as a pump, and they designed experiments to study its pumping action. These experiments revolutionized our view of the circulatory system. Without the pump concept, an understanding of the heart was out of grasp.Concepts and their accompanying mathematics are not sufficient for a technology to mature unless there is some way to implement the system. For instance, the mathematics necessary for the reconstruction of images from computer-aided topography (CAT) scans was known many years before the availability of high-speed computers and efficient algorithms finally made it practical to implement a useful CAT system.The history of neural networks has progressed through both conceptual innovations and implementation developments. These advancements, however, seem to have occurred in fits and starts rather than by steady evolution.Some of the background work for the field of neural networks occurred in the late 19th and early 20th centuries. This consisted primarily of interdisciplinary work in physics, psychology and neurophysiology by such scientists as Hermann von Helmholtz, Ernst Much and Ivan Pavlov. This early work emphasized general theories of learning, vision, conditioning, etc.,and did not include specific mathematical models of neuron operation.The modern view of neural networks began in the 1940s with the work of Warren McCulloch and Walter Pitts [McPi43], who showed that networks of artificial neurons could, in principle, compute any arithmetic or logical function. Their work is often acknowledged as the origin of theneural network field.McCulloch and Pitts were followed by Donald Hebb [Hebb49], who proposed that classical conditioning (as discovered by Pavlov) is present because of the properties of individual neurons. He proposed a mechanism for learning in biological neurons.The first practical application of artificial neural networks came in the late 1950s, with the invention of the perception network and associated learning rule by Frank Rosenblatt [Rose58]. Rosenblatt and his colleagues built a perception network and demonstrated its ability to perform pattern recognition. This early success generated a great deal of interest in neural network research. Unfortunately, it was later shown that the basic perception network could solve only a limited class of problems. (See Chapter 4 for more on Rosenblatt and the perception learning rule.)At about the same time, Bernard Widrow and Ted Hoff [WiHo60] introduced a new learning algorithm and used it to train adaptive linear neural networks, which were similar in structure and capability to Rosenblatt’s perception. The Widrow Hoff learning rule is still in use today. (See Chapter 10 for more on Widrow-Hoff learning.) Unfortunately, both Rosenblatt's and Widrow's networks suffered from the same inherent limitations, which were widely publicized in a book by Marvin Minsky and Seymour Papert [MiPa69]. Rosenblatt and Widrow wereaware of these limitations and proposed new networks that would overcome them. However, they were not able to successfully modify their learning algorithms to train the more complex networks.Many people, influenced by Minsky and Papert, believed that further research on neural networks was a dead end. This, combined with the fact that there were no powerful digital computers on which to experiment,caused many researchers to leave the field. For a decade neural network research was largely suspended. Some important work, however, did continue during the 1970s. In 1972 Teuvo Kohonen [Koho72] and James Anderson [Ande72] independently and separately developed new neural networks that could act as memories. Stephen Grossberg [Gros76] was also very active during this period in the investigation of self-organizing networks.Interest in neural networks had faltered during the late 1960s because of the lack of new ideas and powerful computers with which to experiment. During the 1980s both of these impediments were overcome, and researchin neural networks increased dramatically. New personal computers and workstations, which rapidly grew in capability, became widely available. In addition, important new concepts were introduced.Two new concepts were most responsible for the rebirth of neural net works. The first was the use of statistical mechanics to explain the operation of a certain class of recurrent network, which could be used as an associative memory. This was described in a seminal paper by physicist John Hopfield [Hopf82].The second key development of the 1980s was the backpropagation algo rithm for training multilayer perceptron networks, which was discovered independently by several different researchers. The most influential publication of the backpropagation algorithm was by David Rumelhart and James McClelland [RuMc86]. This algorithm was the answer to the criticisms Minsky and Papert had made in the 1960s. (See Chapters 11 and 12 for a development of the backpropagation algorithm.)These new developments reinvigorated the field of neural networks. In the last ten years, thousands of papers have been written, and neural networks have found manyapplications. The field is buzzing with new theoretical and practical work. As noted below, it is not clear where all of this will lead US.The brief historical account given above is not intended to identify all of the major contributors, but is simply to give the reader some feel for how knowledge in the neural network field has progressed. As one might note, the progress has not always been "slow but sure." There have been periods of dramatic progress and periods when relatively little has been accomplished.Many of the advances in neural networks have had to do with new concepts, such as innovative architectures and training. Just as important has been the availability of powerful new computers on which to test these new concepts.Well, so much for the history of neural networks to this date. The real question is, "What will happen in the next ten to twenty years?" Will neural networks take a permanent place as a mathematical/engineering tool, or will they fade away as have so many promising technologies? At present, the answer seems to be that neural networks will not only have their day but will have a permanent place, not as a solution to every problem, but as a tool to be used in appropriate situations. In addition, remember that we still know very little about how the brain works. The most important advances in neural networks almost certainly lie in the future.Although it is difficult to predict the future success of neural networks, the large number and wide variety of applications of this new technology are very encouraging. The next section describes some of these applications.ApplicationsA recent newspaper article described the use of neural networks in literature research by Aston University. It stated that "the network can be taught to recognize individual writing styles, and the researchers used it to compare works attributed to Shakespeare and his contemporaries." A popular science television program recently documented the use of neural networks by an Italian research institute to test the purity of olive oil. These examples are indicative of the broad range of applications that can be found for neural networks. The applications are expanding because neural networks are good at solving problems, not just in engineering, science and mathematics, but m medicine, business, finance and literature as well. Their application to a wide variety ofproblems in many fields makes them very attractive. Also, faster computers and faster algorithms have made it possible to use neural networks to solve complex industrial problems that formerly required too much computation.The following note and Table of Neural Network Applications are reproduced here from the Neural Network Toolbox for MATLAB with the permission of the Math Works, Inc.The 1988 DARPA Neural Network Study [DARP88] lists various neural network applications, beginning with the adaptive channel equalizer in about 1984. This device, which is an outstanding commercial success, is a single-neuron network used in long distance telephone systems to stabilize voice signals. The DARPA report goes on to list other commercial applications, including a small word recognizer, a process monitor, a sonar classifier and a risk analysis system.Neural networks have been applied in many fields since the DARPA report was written. A list of some applications mentioned in the literature follows.AerospaceHigh performance aircraft autopilots, flight path simulations, aircraft control systems, autopilot enhancements, aircraft component simulations, aircraft component fault detectorsAutomotiveAutomobile automatic guidance systems, warranty activity analyzersBankingCheck and other document readers, credit application evaluatorsDefenseWeapon steering, target tracking, object discrimination, facial recognition, new kinds of sensors, sonar, radar and image signal processing including data compression, feature extraction and noise suppression, signal/image identificationElectronicsCode sequence prediction, integrated circuit chip layout, process control, chip failure analysis, machine vision, voice synthesis, nonlinear modelingEntertainmentAnimation, special effects, market forecastingFinancialReal estate appraisal, loan advisor, mortgage screening, corporate bond rating, credit line use analysis, portfolio trading program, corporate financial analysis, currency price predictionInsurancePolicy application evaluation, product optimizationManufacturingManufacturing process control, product design and analysis, process and machine diagnosis, real-time particle identification, visual quality inspection systems, beer testing, welding quality analysis, paper quality prediction, computer chip quality analysis, analysis of grinding operations, chemical product design analysis, machine maintenance analysis, project bidding, planning and management, dynamic modeling of chemical process systemsMedicalBreast cancer cell analysis, EEG and ECG analysis, prosthesis design, optimization of transplant times, hospital expense reduction, hospital quality improvement, emergency room test advisement0il and GasExplorationRoboticsTrajectory control, forklift robot, manipulator controllers, vision systemsSpeechSpeech recognition, speech compression, vowel classification, text to speech synthesisSecuritiesMarket analysis, automatic bond rating, stock trading advisory systemsTelecommunicationsImage and data compression, automated information services,real-time translation of spoken language, customer payment processing systemsTrans portationTruck brake diagnosis systems, vehicle scheduling, routing systemsConclusionThe number of neural network applications, the money that has been invested in neural network software and hardware, and the depth and breadth of interest in these devices have been growing rapidly.翻译：在人工神经网络的发展历程中，涌现了许多在不同领域中富有创造性的传奇人物，他们艰苦奋斗几十年，提出了许多至今仍然让我们受益的概念。

控制工程基础论文英中对照翻译专业：机电一体化二班学号：20087687姓名：罗庚Machinery control applications in the modern textile industrySome years, as people more conscious of the aesthetic and living standards, high-grade yarn-dyed products are increasingly popular. Not real silk, chemical fiber, rayon, cotton yarn, also can be blended and Silk weaving, dyeing bobbins which led the industry in the yarn is widely available. General yarn before dyeing tube blanks need to be purchased to suit the yarn package dyeing contact with the "pine-style cheese" for the next procedure to use, so slack increasing demand for precision windingExisting domestic slack winding machine structure is generally focused on single-spindle drive mode, usually including winding, yarn, over-feed, such as several sports, the use of mechanical gears and cam completion, for a variety of yarns of different winding process, equipment is more difficult to adjust; yarn organizations to adopt a grooved drum and rotary wing, for some high-end yarn is easy to produce injury; the same time as the structure is used in mechanical transmission, winding speed is not high. This pine-style winding currently abroad has been completely based on electronic gear and all digital electronic cam winding structure, namely, the independent single spindle drive; winding, traversing yarn guide, yarn over-feed, tension compensation are used separate motor control the movement of the relationship between the motor can be described by parameter setting, flexible response to various characteristics of the yarn winding process needs; traversing yarn guide used the "yarn guide", commonly known as "rabbit head" , damage to the yarn is very small, especially for high-grade yarn-dyed yarn winding; In addition, as the motor drive there is no direct mechanical connection, combined with high-speed precision motion control software algorithms, can easily achieve high precision cross-winding, winding speed of winding is much larger than mechanical slack, greatly improving the efficiency of the windingBeijing and Li Technology Co., Ltd. through the motor and domestic well-known textile machinery group co slack for precision winding process characteristics, in their many years of accumulation of the servo and motion control technology, based on the successful development of the country for the first time round with their own Intellectual property rights of high-speed precision slack winding electrical control program. The scheme has good performance and low cost, greatly enhancing the domestic slack winder automation level, the major technical indicators have reached the level of similar foreign equipment.System control program profilesSingle-spindle control, for example, a system control program shown in Figure principle, traverse the motor shaft connected to a wire wheel, wire wheel through the positive and negative spin-driven fastening the wire yarn guide and move around, to achieve cross-yarn Fixed cable movement; winding yarn tube direct-drive rotary motor, to achieve the yarn winding movement, the horizontal motion and the synthesis of the two movements after winding yarn showed the shape of a spiral wire wound on bobbins surface back and forth . Tension compensation and over-feed motor is mainly used to control the motor in the process of yarn winding tension.The yarn guide traverse the program uses a motor through the unique design of the ultra-small inertia servo motor, motor winding, and over-feed is also used in custom designed high-speed brushless DC motor, the tension motor uses a common step motor. Figure in the "single-spindle control driver" is and the benefits of the motor development in its own all-digital AC servo drive, based on the embedded high-speed electronic yarn winder precision motion control algorithms, winding brushless motors speed control and special yarn tension control strategy based motor drive control system. The whole system is simple, functional and communication through the adjustment of the keyboard or the "single-spindle control driver" parameter can be easily set up the internal memory of yarn winding forming the geometric parameters (full tube diameter, to close edge amplitude, etc.), winding the line speed , the winding ratio, traverse the length of yarn, hard-edged trim tube differential amplitude, differential cycle, the cam curve of the differential parameters, along with RS232, RS485, CAN bus communication interface of three, can easily complete networked multi-spindle control, the full realization of flexible digital winding. The main technical parameters are listed below:Than the control winding 2.000 ~ 12.000;Traverse to the acceleration of the servo motor for up to 8000r/s2, reciprocating frequency of the maximum is 800 beats / minute, 160 per minute 0 commutation;Traverse servo motor function with dynamic range automatically give change, no external zero position sensor;Embedded winding and compensation for the three over-feed and tension motor control, can drive, brushless DC motor driver, stepper motor driver interface, easy to realize the winding motor, over-feed motor and motor control tension compensation ;Embedded winding and compensation for the three over-feed and tension motor control, can drive, brushless DC motor driver, stepper motor driver interface, easy to realize the winding motor, over-feed motor and motor control tension compensation ;Calibration function with an empty tube diameter;A variety of real-time parameter display, such as the actual line speed, yarn diameter cylinder, reciprocating frequency;Multiple fault protection measures, such as abnormal parameters, motorspeed, dynamic range tolerance, hardware fault, etc.;Operating parameters in real time with power-down protection functions, such as the length of winding, winding diameter;Introduction to traverse servo motor controTo ensure the bobbins with good dyeing properties, need to start winding to the full tube diameter between any point on the yarn on the cheese into the interchange in space, not parallel to each other to ensure that each yarn is no overlap That is the need for winding bobbins for precise control over. The so-called winding ratio, is the yarn guide traverse back and forth each time, the number of laps winding bobbins. The traditional cross-grooved drum winding winding (any winding), a constant winding ratio of precision winding, three forms of NC layer winding, the program mainly to achieve a constant winding ratio, and numerical precision cross-winding layer Winding two functionsIn order to achieve precision cross-winding, "Control of single spindle drive " real-time collection through the winding motor feedback encoder pulse signal calculation of real-time speed, precision winding process according to the requirements come with a unique numerical algorithm traverse servo motor speed reference Instructions to ensure the traverse servo motor speed and the winding ratio of the motor speed according to the definition of the winding to maintain a certain relationship, so that the yarn helix shape of space around the bobbins on the back and forth. Winding through the precise control over, winding the yarn back and forth to each other cross, do not overlap, that clever use of electronic gear and electronics to replace mechanical cam and cam gear to achieve precision yarn winding tubeIn addition to differential electronic cam algorithm to eliminate hard-edged technology, the program has achieved full of original yarn guide for minimum arc length control algorithm to take full advantage of the high-speed DSP digital signal processor computing power, real-time calculation and correction Yarn guide traverse servo motor and the motor drive winding bobbins cam curve law, ensure that in any winding speed and winding diameter state, the yarn guide to the arc length for the minimum, maximum cylinder to eliminate winding yarn Hard-edged phenomenon.Introduction to the winding wire speed controlT heoretically, the line speed winding bobbins with yarn winding tube radius changes, and changes in velocity fluctuations directly caused by the winding tension, which will affect the yarn quality and yarn tube forming the mechanicaland physical properties . If the outer yarn yarn tension greater than the inner tension, it is easy to produce cheese yarn extrusion outer edge of the inner bulge phenomenon of yarn; if the yarn tension during the change is too large, may easily lead to a result of winding yarn Stretch yarn tension there different rates in different, which requires the winding process to minimize tension and pressure fluctuations. Therefore, apart from ensuring a constant pressure on bobbins to ensure the relative stability of the control of winding speed is an important measure tension fluctuationAbout Tension ControlProcessing precision winding yarn tension directly affects the size of the tightness of winding bobbin, thus affecting the capacity of cheese around the yarn and the difficulty of dyeing and processing of yarn breakage rate, so all kinds of precision winding winding machines are part of the yarn tension control, especially for the yarn package dyeing process with tension, not be too big to get the slack drum, is conducive to staining. In addition to taking measures to ensure the program is relatively constant yarn winding speed, but also another design of a tension adjustment device decreases, the use of a stepper motor control of the tension lever. Online Speed up Process, by adjusting the stepper motor rotation status, control the angle of the tension lever to change the yarn strength by holding the door of the gate in order to ensure constant tension winding; Also in accordance with the special bobbins "in tight outside Song, "the process requirements, the radius can be adjusted according to yarn winding tension rod tube angle, to ensure thatsmall-diameter tube when winding yarn winding tension, winding tension and large diameterPrecision winding, yarn, textile machinery textile process to improve the quality of key equipment, high-speed precision digital winding program successfully mastered the high-speed precision yarn winding process in the "KNOW HOW", all with permanent magnet motor drive technology, machine energy consumption is far lower than the conventional variable frequency motor drive equipment. At the same time the flexible use of digital control technology, is ideal for high-grade fabric in many varieties, small batch production of bobbins, with good social and economic benefits. And facilitate the development of the motor technology company involved in the innovative electronic control solutions, digital servo motor and drive, precision motion control, and computer network communication technology, is a typical high-tech mechanical and electrical integration of control programs is to use digital control a typical case of the transformation of traditional industries机械控制在现代纺织工业的应用些年，随着人们审美意识增强和生活水平的提高，高档色织产品愈加受到人们喜爱。

Principles of Mass Transfer1. General RemarksSome of the most typical chemical engineering problems lie in the field of mass transfer. A distinguishing mark of the chemical engineer is his ability to design and operate equipment in which reactants are prepared, chemical reactions take place, and separations of the resulting products are made. This ability rests largely on a proficiency in the science of mass transfer.Applications of the principles of momentum and heat transfer are common in many branches of engineering, but the application of mass transfer has traditionally been largely limited to chemical engineering. Other important applications occur in metallurgical processes, in problems of high-speed flight, and in waste treatment and pollution-control processes.By mass transfer is meant the tendency of a component in a mixture to travel from a region of high concentration to one of low concentration. For example, if an open test tube with some water in the bottom is placed in a room in which the air is relatively dry, water vapor will diffuse out through the column of air in the test tube. There is a mass transfer of water from a place where its concentration is high (just above the liquid surface) to a place where its concentration is low (at the outlet of the tube). If the gas mixture in the tube is stagnant, the transfer occurs by molecular diffusion. If there is a bulk mixing of the layers of gas in the tube by mechanical stirring or because of a density gradient, mass transfer occurs primarily by the mechanism of forced or natural convection. These mechanisms are analogous to the transfer of heat by conduction and by convection; there is, however, no counterpart in mass transfer for thermal radiation.The analogy between momentum and energy transfer has already been studied in some detail, and it is now possible to extend the analogy to include mass transfer.In discussing the fundamentals of mass transfer we shall consider mainly binary mixtures, although multicomponent mixtures are important in industrial applications. Some of these more complicated situations will be discussed after the basic principles have been illustrated in terms of binary mixtures,2. Molecular DiffusionMolecular diffusion occurs in a gas as a result of the random motion of the molecules. This motion is sometimes referred to as a random walk. Across a plane normal to the direction of the concentration gradient (or any other plane), there are fluxes of molecules in both directions. The direction of movement for any one molecule is independent of the concentration in dilute solutions. Consequently, in a system in which there is a concentration gradient, the fraction of molecules of a particular species (referred to as species A) which will move across a plane normal to the gradient is the same for both the high-and low-concentration sides of the plane. Because the total number of molecules of A on the high-concentration side is greater than on the low-concentration side, there is therefore a net movement of A in the direction in which the concentration of A is lower. If there are no counteracting effects, the concentrations throughout the mixture tend to become the same. In the analogous transfer of heat in a gas by conduction, the distribution of hotter molecules (those which have a higher degree of random molecular motion) tends to be evened out by random mixing on a molecular scale. Similarly, if there is a gradient of directed velocity (as distinguished from random velocity) across the plane, the velocity distribution tends toward uniformity as a result of the random molecular mixing. There is a transfer of momentum, which is proportional to the viscosity of the gas.The above remarks apply only in an approximate and qualitative way. The quantitative prediction of the diffusivity, thermal conductivity, and viscosity of a gas from a knowledge of molecular properties can be quite complicated. The consideration of such relations forms an important part of the subject of statistical mechanics.Molecular diffusion also occurs in liquids and solids. Crystals in an unsaturated solution dissolve, with subsequent diffusion away from the solid-liquid interface. Diffusion in solids is of importance in metallurgical operations. When iron which is unsaturated with respect to carbon is heated in a bed of coke, the concentration of the carbon near the surface is increased by inward diffusion of carbon atoms.3. E ddy DiffusionJust as momentum and energy can be transferred by the motion of finite parcels of fluid, so mass can be transferred. We have seen that the rate of these transfer operations, caused by bulk mixing in a fluid, can be expressed in terms of the eddy kinematics viscosity, the eddy thermal diffusivity, and the eddy diffusivity. This latter quantity can be related to a mixing length which is the same as that defined in connection with momentum and energy transfer. In fact, the analogy between heat and mass transfer is so straightforward that equations developed for the former are often found to apply to the latter by a mere change in the meaning of the symbols.Eddy diffusion is apparent in the dissipation of smoke from a smokestack. Turbulence causes mixing and transfer of the smoke to the surrounding atmosphere. In certain locations where atmospheric turbulence is lacking, smoke originating at the surface of the earth is dissipated largely by molecular diffusion. This causes serious pollution problems because mass is transferred less rapidly by molecular diffusion than by eddy diffusion.4. C onvective Mass-Transfer CoefficientsIn the study of heat transfer we found that the solution of the differential energy balance was sometimes cumbersome or impossible, and it was convenient to express the rate of heat flow in terms of a convective heat-transfer coefficient by an equation like)(m s t t h Aq -= The analogous situation in mass transfer is handled by an equation of form)(Am As P A k N ρρ-=The mass flux NA is measured relative to a set of axes fixed in space. The driving force is the difference between the concentration at the phase boundary (a solid surface or a fluid interface) and the concentration at some arbitrarily defined point in the fluid medium. The convective coefficient kp may apply to forced or natural convection; there are no mass-transfer counterparts for boiling, condensation, or radiation heat-transfer coefficients. The value of kp is a function of the geometry of the system and the velocity and properties of the fluid, just as was the coefficient h.(Selected from* C. O. Bennett, and J. E. Myens, Momentum, Heat, and Mass Transfer, 2nd Edition, McGraw-Hill Inc. , 1974. )传质原理1. 概述一些典型的化学工程问题存在于传质领域。

材料成型及控制工程外文翻译文献(文档含英文原文和中文翻译)在模拟人体体液中磷酸钙涂层激光消融L. Cle`ries*, J.M. FernaHndez-Pradas, J.L. Morenza德国巴塞罗那大学,西班牙1999年七月二十八日-2000年2月文摘:三种类型的磷酸钙涂层基质,在钛合金激光烧蚀技术规定提存,沉浸在一个模拟的身体# uid为了确定条件下他们的行为类似于人的血浆。

羟基磷灰石涂层也也非晶态磷酸钙涂层和a-tricalcium磷酸盐做溶解阶段b-tricalcium磷酸盐的涂料有细微的一个阶段稍微瓦解。

一个apatitic阶段降水量偏爱在羟基磷灰石涂层的涂料磷酸b-tricalcium上有细微的一个阶段。

在钛合金基体上也有降水参考,但在大感应时代。

然而,在非晶态磷酸钙涂层不沉淀形成。

科学出版社有限公司(2000保留所有权利。

关键词:磷酸钙,脉冲激光沉积,SBF1 介绍激光消融技术用于沉积磷酸钙涂层金属基体上,将用作植体骨重建。

用这个技术,磷酸钙涂层量身定做阶段和结构也成功地研制生产了[1,2]和溶解特性鉴定海洋条件]。

然而,真正的身体条件# uid饱和对羟基磷灰石的阶段,这是钙离子的浓度高于均衡的这个阶段。

因而,这就很有趣也测试条件磷酸钙涂料接近体内的情况,以了解其完整性,在这些条件及其催化反应性质}表面沉淀过程。

因此,非晶态磷酸钙涂层(ACP),羟基磷灰石(HA)涂层,涂层中的一个阶段b-tricalcium磷酸盐较小(ba-TCP)积下激光烧蚀是沉浸在饱和溶液为迪!时间、不同的结构性演变进行了测定。

饱和溶液的使用的是身体uid(SBF模拟#),解决了其离子浓度、酸碱度几乎等于那些人类血浆[5]。

该解决方案也是一个利用在仿生(沉淀)工艺生产磷灰石层在溶胶凝胶活性钛基体。

2 实验模拟身体化学溶解试剂级严格依照以下的顺序,除氢钠,NaHCO3:)3,K2HPO4 H2O,MgCl2)6 H2O,氯化钙和Na2SO4)2 H2O,在去离子水。

毕业设计（论文）外文文献翻译文献、资料中文题目：U形管换热器文献、资料英文题目：文献、资料来源：文献、资料发表（出版）日期：院（部）：专业：过程装备与控制工程专业班级：姓名：学号：指导教师：翻译日期： 2017.02.14毕业设计（论文）外文翻译毕业设计（论文）题目： U形管式换热器设计外文题目： U-tube heat exchangers译文题目：指导教师评阅意见U-tube heat exchangersM. Spiga and G. Spiga, Bologna1 Summary:Some analytical solutions are provided to predict the steady temperature distributions of both fluids in U-tube heat exchangers. The energy equations are solved assuming that the fluids remain unmixed and single-phased. The analytical predictions are compared with the design data and the numerical results concerning the heat exchanger of a spent nuclear fuel pool plant, assuming distinctly full mixing and no mixing conditions for the secondary fluid (shell side). The investigation is carried out by studying the influence of all the usual dimensionless parameters (flow capacitance ratio, heat transfer resistance ratio and number of transfer units), to get an immediate and significant insight into the thermal behaviour of the heat Exchanger.More detailed and accurate studies about the knowledge of the fluid temperature distribution inside heat exchangers are greatly required nowadays. This is needed to provide correct evaluation of thermal and structural performances, mainly in the industrial fields (such as nuclear engineering) where larger, more efficient and reliable units are sought, and where a good thermal design can not leave integrity and safety requirements out of consideration [1--3]. In this view, the huge amount of scientific and technical informations available in several texts [4, 5], mainly concerning charts and maps useful for exit temperatures and effectiveness considerations, are not quite satisfactory for a more rigorous and local analysis. In fact the investigation of the thermomechanieal behaviour (thermal stresses, plasticity, creep, fracture mechanics) of tubes, plates, fins and structural components in the heat exchanger insists on the temperature distribution. So it should be very useful to equip the stress analysis codes for heat exchangers withsimple analytical expressions for the temperature map (without resorting to time consuming numerical solutions for the thermal problem), allowing a sensible saving in computer costs. Analytical predictions provide the thermal map of a heat exchanger, aiding in the designoptimization.Moreover they greatly reduce the need of scale model testing (generally prohibitively expensive in nuclear engineering), and furnish an accurate benchmark for the validation of more refined numerical solutions obtained by computer codes. The purpose of this paper is to present the local bulk-wall and fluid temperature distributions forU-tube heat exchangers, solving analytically the energy balance equations.122 General assumptionsLet m, c, h, and A denote mass flow rate (kg/s), specific heat (J/kg -1 K-l), heat transfer coefficient(Wm -2 K-l), and heat transfer surface (m2) for each leg, respectively. The theoretical analysis is based on classical assumptions [6] :-- steady state working conditions,-- equal flow distribution (same mass flow rate for every tube of the bundle),-- single phase fluid flow,-- constant physical properties of exchanger core and fluids,-- adiabatic exchanger shell or shroud,-- no heat conduction in the axial direction,-- constant thermal conductances hA comprehending wall resistance and fouling.According to this last assumption, the wall temperature is the same for the primary and secondary flow. However the heat transfer balance between the fluids is quite respected, since the fluid-wall conductances are appropriately reduced to account for the wall thermal resistance and thefouling factor [6]. The dimensionless parameters typical of the heat transfer phenomena between the fluids arethe flow capacitance and the heat transfer resistance ratiosand the number of transfer units, commonly labaled NTU in the literature,where (mc)min stands for the smaller of the two values (mc)sand (mc)p.In (1) the subscripts s and p refer to secondary and primary fluid, respectively. Only three of the previous five numbers are independent, in fact :The boundary conditions are the inlet temperatures of both fluids3 Parallel and counter flow solutionsThe well known monodimensional solutions for single-pass parallel and counterflow heat exchanger,which will be useful later for the analysis of U-tube heat exchangers, are presented below. If t, T,νare wall, primary fluid, and secondary fluid bulk temperatures (K), and ξ and L represent the longitudinal space coordinate and the heat exchanger length (m), the energy balance equations in dimensionless coordinate x = ξ/L, for parallel and counterflow respectivelyread asM. Spiga and G. Spiga: Temperature profiles in U-tube heat exchangersAfter some algebra, a second order differential equation is deduced for the temperature of the primary (or secondary) fluid, leading to the solutionwhere the integration constants follow from the boundary conditions T(0)=T i , ν(0)≒νifor parallel T(1) = Ti ,ν(0) = νifor counter flow. They are given-- for parallel flow by - for counterflow byWishing to give prominence to the number of transfer units, it can be noticed thatFor counterflow heat exchangers, when E = 1, the solutions (5), (6) degenerate and the fluidtemperatures are given byIt can be realized that (5) -(9) actually depend only on the two parametersE, NTU. However a formalism involving the numbers E, Ns. R has been chosen here in order to avoid the double formalism (E ≤1 and E > 1) connected to NTU.4 U-tube heat exchangerIn the primary side of the U-tube heat exchanger, whose schematic drawing is shown in Fig. 1, the hot fluid enters the inlet plenum flowing inside the tubes, and exits from the outlet plenum. In the secondary side the fluid flows in the tube bundle (shell side). This arrangement suggests that the heat exchanger can be considered as formed by the coupling of a parallel and a counter-flow heat exchanger, each with a heigth equal to the half length of the mean U-tube. However it is necessary to take into account the interactions in the secondary fluid between the hot and the cold leg, considering that the two flows are not physically separated. Two extreme opposite conditions can be investigated: no mixing and full mixing in the two streams of the secondary fluid. The actual heat transfer phenomena are certainly characterized by only a partial mixing ofthe shell side fluid between the legs, hence the analysis of these two extreme theoretical conditions will provide an upper and a lower limit for the actual temperature distribution.4.1 No mixing conditionsIn this hypothesis the U-tube heat exchanger can be modelled by two independent heat exchangers, a cocurrent heat exchanger for the hot leg and a eountercurrent heat exchanger for the cold leg. The only coupling condition is that, for the primary fluid, the inlet temperature in the cold side must be the exit temperature of the hot side. The numbers R, E, N, NTU can have different values for the two legs, because of thedifferent values of the heat transfer coefficients and physical properties. The energy balance equations are the same given in (2)--(4), where now the numbers E and Ns must be changed in E/2 and 2Ns in both legs, if we want to use in their definition the total secondary mass flow rate, since it is reduced in every leg to half the inlet mass flow rate ms. Of course it is understood that the area A to be used here is half of the total exchange area of the unit, as it occurs for the length L too. Recalling (5)--(9) and resorting to the subscripts c and h to label the cold and hot leg, respectively, the temperature profile is given bywhere the integration constants are:M. Spiga and G. Spiga: Temperature profiles in U-tube heat exchangersIf E, = 2 the solutions (13), (14) for the cold leg degenerate into4.2 Full mixing conditionsA different approach can be proposed to predict the temperature distributions in the core wall and fluids of the U-tube heat exchanger. The assumption of full mixing implies that the temperaturesof the secondary fluid in the two legs, at the same longitudinal section, are exactly coinciding. In this situation the steady state energy balance equations constitute the following differential set :The bulk wall temperature in both sides is thenand (18)--(22) are simplified to a set of three equations, whose summation gives a differential equation for the secondary fluid temperature, withgeneral solutionwhere # is an integration constant to be specified. Consequently a second order differential equation is deduced for the primary fluid temperature in the hot leg :where the numbers B, C and D are defined asThe solution to (24) allows to determine the temperaturesand the number G is defined asThe boundary conditions for the fluids i.e. provide the integration constantsAgain the fluid temperatures depend only on the numbers E and NTU.5 ResultsThe analytical solutions allow to deduce useful informations about temperature profiles and effectiveness. Concerning the U-tube heat exchanger, the solutions (10)--(15) and (25)--(27) have been used as a benchmark for the numerical predictions of a computer code [7], already validated, obtaining a very satisfactory agreement.M. Spiga and G. Spiga: Temperature profiles in U-tube heat exchangers 163 Moreover a testing has been performed considering a Shutte & Koerting Co. U-tube heat exchanger, designed for the cooling system of a spent nuclear fuel storage pool. The demineralized water of the fuel pit flows inside the tubes, the raw water in the shell side. The correct determination of the thermal resistances is very important to get a reliable prediction ; for every leg the heat transfer coefficients have been evaluated by the Bittus-Boelter correlation in the tube side [8], by the Weisman correlation in the shell side [9] ; the wall material isstainless steel AISI 304.and the circles indicate the experimental data supplied by the manufacturer. The numbers E, NTU, R for the hot and the cold leg are respectively 1.010, 0.389, 0.502 and 1.011, 0.38~, 0.520. The difference between the experimental datum and the analytical prediction of the exit temperature is 0.7％ for the primary fluid, 0.9% for the secondary fluid. The average exit temperature of the secondary fluid in the no mixing model differs from the full mixing result only by 0.6%. It is worth pointing out the relatively small differences between the profiles obtained through the two different hypotheses (full and no mixing conditions), mainly for the primary fluid; the actual temperature distribution is certainly bounded between these upper and lower limits,hence it is very well specified. Figures 3-5 report the longitudinal temperaturedistribution in the core wall, τw = (t -- νi)/(Ti -- νi), emphasizing theeffects of the parameters E, NTU, R.As above discussed this profile can be very useful for detailed stress analysis, for instance as anM. Spiga and G. Spiga: Temperature profiles in U-tube heat exchangersinput for related computer codes. In particular the thermal conditions at the U-bend transitions are responsible of a relative movement between the hot and the cold leg, producing hoop stresses with possible occurrence of tube cracking . It is evident that the cold leg is more constrained than the hot leg; the axial thermal gradient is higher in the inlet region and increases with increasing values of E, NTU, R. The heat exchanger effectiveness e, defined as the ratio of the actual heat transfer rate(mc)p (Ti-- Tout), Tout=Tc(O), to the maximum hypothetical rateunder the same conditions (mc)min (Ti- νi), is shown in Figs. 6, 7respectively versus the number of transfer units and the flow capacitance ratio. As known, the balanced heat exchangers E = 1) present the worst behaviour ; the effectiveness does not depend on R and is the same for reciprocal values of the flow capacitance ratio.U形管换热器m . Spiga和g . Spiga,博洛尼亚摘要:分析解决方案提供一些两相流体在u形管换热器中的分布情况。

Introductions to Control SystemsAutomatic control has played a vital role in the advancement of engineering and science. In addition to its extreme importance in space-vehicle, missile-guidance, and aircraft-piloting systems, etc, automatic control has become an important and integral part of modern manufacturing and industrial processes. For example, automatic control is essential in such industrial operations as controlling pressure, temperature, humidity, viscosity, and flow in the process industries; tooling, handling, and assembling mechanical parts in the manufacturing industries, among many others.Since advances in the theory and practice of automatic control provide means for attaining optimal performance of dynamic systems, improve the quality and lower the cost of production, expand the production rate, relieve the drudgery of many routine, repetitive manual operations etc, most engineers and scientists must now have a good understanding of this field.The first significant work in automatic control was James Watt’s centrifugal governor for the speed control of a steam engine in the eighteenth century. Other significant works in the early stages of development of control theory were due to Minorsky, Hazen, and Nyquist, among many others. In 1922 Minorsky worked on automatic controllers for steering ships and showed how stability could be determined by the differential equations describing the system. In 1934 Hazen, who introduced the term “ervomechanisms”for position control systems, discussed design of relay servomechanisms capable of closely following a changing input.During the decade of the 1940’s, frequency-response methods made it possible for engineers to design linear feedback control systems that satisfied performance requirements. From the end of the 1940’s to early 1950’s, the root-locus method in control system design was fully developed.The frequency-response and the root-locus methods, which are the core of classical theory, lead to systems that are stable and satisfy a set of more or less arbitrary performance requirements. Such systems are, ingeneral, not optimal in any meaningful sense. Since the late 1950’s, the emphasis on control design problems has been shifted from the design of one of many systems that can work to the design of one optimal system in some meaningful sense.As modern plants with many inputs and outputs become more and more complex, the description of a modern control system requires a large number of equations. Classical control theory, which deals only with single-input-single-output systems, becomes entirely powerless for multiple-input-multiple-output systems. Since about 1960, modern control theory has been developed to cope with the increased complexity of modern plants and the stringent requirements on accuracy, weight, and industrial applications.Because of the readily available electronic analog, digital, and hybrid computers for use in complex computations, the use of computers in the design of control systems and the use of on-line computers in the operation of control systems are now becoming common practice.The most recent developments in modern control theory may be said to be in the direction of the optimal control of both deterministic and stochastic systems as well as the adaptive and learning control of complex systems. Applications of modern control theory to such nonengineering fields as biology, economics, medicine, and sociology are now under way, and interesting and significant results can be expected in the near future.Next we shall introduce the terminology necessary to describe control systems.Plants. A plant is a piece of equipment, perhaps just a set of machine parts functioning together, the purpose of which is to perform a particular operation. Here we shall call any physical object to be controlled (such as a heating furnace, a chemical reactor, or a spacecraft) a plant.Processes. The Merriam-Webster Dictionary defines a process to be a natural, progressively continuing operation or development marked by a series of gradual changes that succeed one another in a relatively fixed way and lead toward a particular result or end; or an artificial or voluntary, progressively continuing operation that consists of a series of controlledactions or movements systematically directed toward a particular result or end.Here we shall call any operation to be controlled a process. Examples are chemical, economic, and biological process.Systems. A system is a combination of components that act together and perform a certain objective. A system is not limited to abstract, dynamic phenomena such as those encountered in economics. The word “system” should, therefore, be interpreted to imply physical, biological, economic, etc., system.Disturbances. A disturbance is a signal which tends to adversely affect the value of the output of a system. If a disturbance is generated within the system, it is called internal, while an external disturbance is generated outside the system and is an input.Feedback control.Feedback control is an operation which, in the presence of disturbances, tends to reduce the difference between the output of a system and the reference input (or an arbitrarily varied, desired state) and which does so on the basis of this difference. Here, only unpredictable disturbance (i.e., those unknown beforehand) are designated for as such, since with predictable or known disturbances, it is always possible to include compensation with the system so that measurements are unnecessary.Feedback control systems. A feedback control system is one which tends to maintain a prescribed relationship between the output and the reference input by comparing these and using the difference as a means of control.Note that feedback control systems are not limited to the field of engineering but can be found in various nonengineering fields such as economics and biology. For example, the human organism, in one aspect, is analogous to an intricate chemical plant with an enormous variety of unit operations.The process control of this transport and chemical-reaction network involves a variety of control loops. In fact, human organism is an extremely complex feedback control system.Servomechanisms. A servomechanism is a feedback control system in which the output is some mechanical position, velocity, or acceleration. Therefore, the terms servomechanism and position- (or velocity- oracceleration-) control system are synonymous. Servomechanisms are extensively used in modern industry. For example, the completely automatic operation of machine tools, together with programmed instruction, may be accomplished by use of servomechanisms.Automatic regulating systems. An automatic regulating system is a feedback control system in which the reference input or the desired output is either constant or slowly varying with time and in which the primary task is to maintain the actual output at the desired value in the presence of disturbances.A home heating system in which a thermostat is the controller is an example of an automatic regulating system. In this system, the thermostat setting (the desired temperature) is compared with the actual room temperature. A change in the desired room temperature is a disturbance in this system. The objective is to maintain the desired room temperature despite changes in outdoor temperature. There are many other examples of automatic regulating systems, some of which are the automatic control of pressure and of electric quantities such as voltage, current and frequency.Process control systems. An automatic regulating system in which the output is a variable such as temperature, pressure, flow, liquid level, or pH is called a process control system.Process control is widely applied in industry. Programmed controls such as the temperature control of heating furnaces in which the furnace temperature is controlled according to a preset program are often used in such systems. For example, a preset program may be such that the furnace temperature is raised to a given temperature in a given time interval and then lowered to another given temperature in some other given time interval. In such program control the set point is varied according to the preset time schedule. The controller then functions to maintain the furnace temperature close to the varying set point. It should be noted that most process control systems include servomechanisms as an integral part.控制系统介绍自动控制在工程学和科学的推进扮演一个重要角色。

建筑施工质量控制外文翻译参考文献(文档含中英文对照即英文原文和中文翻译)译文：建筑施工过程中质量管理的动机分析和控制方法的研究摘要在建筑施工过程中实施质量管理可以有效地防止在后续建筑产品使用过程中安全事故的发生。

与此同时可以减少建设供应链的总成本，这也有利于增强建筑施工企业的品牌知名度和声誉。

在建筑施工过程中结合质量管理过程和当前建筑施工阶段的主要质量问题，分析了建设过程中的管理动机，将供应链管理与目标管理理念和方法应用到质量管理中，最后提出了具体的质量控制措施。

这些都是为了在建筑施工过程中提高建筑产品的总体质量。

关键字——建筑施工、质量管理、质量动机、控制1.引言调查显示建筑施工企业主要采用现场控制的质量管理模式是预先控制。

大多企业常常使得建筑施工过程中与建设管理中的质量管理相同，他们通常忽略了施工准备阶段质量问题的预防，如供应商的选择、道路的规划和临时设施，这些因素在建筑施工过程中的质量管理上起着至关重要的作用。

建设质量事故频繁发生，引起了许多领域的高度关注，如各级政府部门、施工企业和业主，特别是重庆綦江虹桥的坍塌、五龙的滑坡和洪湖湿地路基施工中的一系列质量安全事故，人们开始对施工质量问题做全方位的思考。

通过研究李秀峰总结归纳了造成工程的质量问题并引入项目质量控制分析方法，Low Sui Pheng 和Jasmine Ann Teo[2] 建立了施工中的质量管理框架来通过经验分析实现项目的质量控制，SangHyun Lee and others[3] 利用系统质量动态结构和变更管理模型的编程方法和控制方法，最终实现了大规模的并行设计和施工项目的管理和控制。

方唐分析了建设项目质量管理的整个过程和控制方法，她认为应该实现对影响建设单位质量的人、材料、机械、方法和环境的完全控制；吴天翔研究出管理因素是影响建设项目质量控制的重要因素，强调了施工过程中需要严格控制的各个方面和整体实现加强管理的需要。

为了解决建设施工过程中的建设质量问题，韩伟建立了一个建筑项目的分析和处理程序。

控制工程英语介绍English:"Control engineering, also known as control systems engineering, is a branch of engineering that deals with the design, analysis, and application of systems to maintain desired levels of performance and stability. This field combines knowledge from various disciplines such as mathematics, physics, and engineering to create automated systems that can regulate or guide processes efficiently. Control systems can be found in a wide range of industries, including manufacturing, automotive, aerospace, and robotics, where precise control of variables such as temperature, pressure, speed, or position is essential.The fundamental concept in control engineering is feedback, which involves monitoring the output of a system and using it to adjust the input for desired outcomes. There are two primary types of control systems: open-loop and closed-loop (also known as feedback control systems). In an open-loop system, the input is not adjusted based onthe output, while in a closed-loop system, the system continuously monitors and adjusts itself based on feedback.Control engineers use various mathematical and computational techniques to model systems and design controllers. These techniques include linear and nonlinear control theories, state-space representation, frequency domain analysis, and digital control methods. With the rise of smart technologies and the Internet of Things (IoT), control engineering plays an increasingly vital role in the development of intelligent, interconnected systems.As a discipline, control engineering offers the potential to improve efficiency, safety, and reliability across numerous sectors. For instance, in manufacturing, control systems can optimize production processes and improve product quality. In transportation, they contribute to the development of autonomous vehicles and traffic management systems. In the energy sector, control engineering can enhance the integration of renewable energy sources and grid stability. Thus, control engineering is a crucial field that drives innovation and advancements in modern technology."中文翻译:"控制工程，也称为控制系统工程，是工程学的一个分支，涉及设计、分析和应用系统以保持所需的性能和稳定性水平。