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Utilization of CAD models for the object oriented measurement of industrial and architectur

UTILIZATION OF CAD MODELS FOR THE OBJECT ORIENTED MEASUREMENT OF INDUSTRIAL AND ARCHITECTURAL OBJECTS

André Streilein

Institute of Geodesy and Photogrammetry

Swiss Federal Institute of Technology

CH-8093 Zurich, Switzerland

e-mail: andre@geod.ethz.ch

Commission V, Working Group 3

KEY WORDS: CAD, digital close-range photogrammetry, model based analysis, object oriented measurement. ABSTRACT

An object oriented measurement approach using CAD models for the initialization of an automatic measurement process and for the verification of the measurement results is presented. CAD models are used in an a priori and a posteriori mode. The human operator assigns responsibility for the image understanding part (high level grouping), and the computer for the actual measurement and the data handling. The performance and results of this measurement approach is demonstrated on an architectural object.

KURZFASSUNG

Eine objekt-orientierte Messmethode, die auf der Grundlage eines CAD-Models eine automatische Messroutine ausl?st und deren Resultate überprüft, wird vorgestellt. Dabei werden CAD Modelle sowohl im a priori als auch im a posteriori Modus angewendet. Der Operateur zeichnet für die Bildinterpretation verantwortlich, w?hrend der Computer für die aktuellen Messungen und die Verwaltung der Daten zust?ndig ist. V orgehensweise und Resultate dieser Methode werden am Beispiel eines Architekturobjektes dargestellt.

1. INTRODUCTION

This paper describes an object oriented measurement ap-proach using CAD models for the initialization of an auto-matic measurement process and for the verification of the measurement results. This measurement approach is em-bedded in the software environment DIPAD, currently un-der development at ETH Zurich.

DIPAD combines digital photogrammetric methods with the capabilities of a CAD system. CAD models are used in an a priori and a posteriori mode. The overruling princi-ple is, that the human operator assigns responsibility for the image understanding part (high level grouping), and the computer for the actual measurement and the data han-dling. The user indicates relevant parts of the object in the CAD environment by approximating a geometric topolo-gy to it. The photogrammetric algorithm matches this to-pology with the image data of multiple images, iteratively refines the coarse object model that is given and transfers the final result back to the CAD environment, including information about precision and reliability of the result. In Sect. 2 the ability of CAD systems for the representa-tion and structuring of 3D data is discussed. Sect. 3 gives an overview of the modelling and measurement principles of DIPAD. And finally in Sect. 4 results of this measure-ment approach will be demonstrated on an architectural object, the Otto-Wagner-Pavillon in Vienna).

2. MODEL REPRESENTATION AND DATA

STRUCTURES OF CAD

For the representation of three-dimensional data CAD models have been used widely in photogrammetric appli-cations. Various examples can be found in the field of ar-chitecture (Saint-Aubain, 1990; Stevens and McKay, 1990; Kempa and Schlüter, 1992; Albertz and Wiede-mann, 1995), in the ?eld of heritage recording (Robson, et al., 1994; Sawyer and Bell, 1994), in the ?eld of city mod-els (Lang and Schickler, 1993; Gruber, et al., 1995; Mason and Streilein, 1996), or in the field of industrial applica-tions (Oshima, 1992; Chandler, Still, 1994; Chapman, et al., 1994). Examples can be found even for the design of close-range photogrammetric networks (Mason, 1994). Different software packages employ CAD models. Some of which are addressed in (Fellbaum, 1992), where an overview of low-cost photogrammetric systems using CAD is given and in (McGlone, 1995) where an overview of various systems in computer vision using CAD models is given. Most systems use CAD models exclusively for the representation of photogrammetric results. However, there are systems, who accept or require CAD information prior the measurement process (e.g. the systems described in by El-Hakim and Pizzi (1993) or Schickler (1992)). Object models can be treated as abstractions of real world objects. The most important role played in model definition is the proper balance between correctness and tractability, i.e., the results given by the model must be adequate both in terms of the solution attained and the cost to attain the solution.

The information usually conveyed in any CAD applica-tion is geometry, and the most common way of introduc-ing geometry is by using the concept of building blocks. Every object maybe decomposed into a small number of geometric pieces or graphic primitives. Basic graphic primitives, e.g. points or dots, straight lines, polylines, filled areas, exist both in 2D and 3D environments. In ad-dition there are advanced primitives in 2D, e.g. circles,

Published in: International Archives of Photogrammetry and Remote Sensing, V ol. XXI, Part B5, Vienna 1996, pp. 548-553.

arcs, ellipses, conic curves, Bezier curves, B-spline curves; and in 3D, e.g. surfaces, solids (rectangular boxes, cylinders, spheres, wedges, cones). The usage of such primitives permits the representation of a complex solid, by gathering and combining them in order to approximate the real 3D form.

The following are some known and frequently used geo-metric representations employed in CAD systems.Bound-ary Representation (BREP): The object is represented by its boundary, which is decomposed into a set of faces, edges and vertices. The result is an explicit model based on a combined topological and geometric description of the object. The topology is captured by a set of relations that indicate how the faces, edges, and vertices are con-nected to each other.Sweep Representation: A solid is de-fined as the volume that swept by a planar or a two-dimensional shape along a curve. There can be both rota-tional and translational sweep, e.g. generalized cylinders or cones.Constructive Solid Geometry (CSG): Primitive instances of objects are combined to more complex ob-jects by use of geometric transformations and Boolean set operations. The representation is usually in form of a tree where the leaf nodes correspond to the primitive instances and the non-leaf nodes correspond to Boolean set opera-tions.Cell Decomposition: This yields a decomposition of object space into cells, usually of different sizes. The re-gion octree is a regular decomposition of this representa-tion. An octree method consists of dividing the working space into cells marked as occupied or empty.

For the structuring of CAD models there are a number of functionalities and methods that standard CAD systems offer (Schmitt, 1993). Probably the ?rst and foremost that comes to mind is the structuring in layers (incl. colours and linestyles). If it is applied ef?ciently this can be a very powerful tool as it allows for multiple groupings of the same element. The concept of blocks (types and instanc-es) introduces hierarchies and higher level groupings. It allows fast modelling and testing of alternatives The con-cept of levels of detail (logical zoom) generates different modes of representation depending on the task. These are the most used means of structuring a model in standard CAD systems. Additional structuring can be achieved by extending the drawing database or by linking an external database to the drawing database.

3. STRATEGY OF DIPAD

The reconstruction of man-made objects is difficult. They are often complex, irregular, appear different according to their function or context, etc. In a typical non-controlled environment like outdoor scenes, their extraction from im-agery is difficult due to occlusions (from other objects or due to perspective projection), illumination effects (shad-ows or weak contrast), radiometric interferences or vary-ing background.

The strategy of DIPAD is that a human operator assigns responsibility for the image understanding part (high level grouping), and the computer for the actual measurement and the data handling. CAD models are used both, in an a priori and a posteriori mode. The user indicates relevant parts of the object in the CAD environment by approxi-mating a geometric topology to it. The photogrammetric algorithm matches this topology with the image data of multiple images, iteratively re?nes the coarse given object model and transfers the ?nal result back to the CAD envi-ronment, including information about precision and relia-bility of the result.

3.1.Modelling environment

A CAD system (in our case AutoCAD) supports 2D and 3D modelling facilities and controls hybrid viewers, which serve as a general feedback generator during the modelling process. The camera-icons in the CAD system are linked with corresponding camera parameters of the image viewer. When the parameters of a camera-icon are edited in the CAD system, the changes of its view can be monitored in the viewer. The intention is to facilitate the initial positioning of a camera with respect to the model and for the creation of a coarse object model for the meas-urement process (see Figure 1). Moving around these icons can however also be used to do real-time fly-throughs in the model or for the production of montages and the creation of new objects in existing contexts.

Figure 1: The modelling in the CAD system can

be entirely monitored in the viewers

linked to the model. Each camera icon

corresponds to one viewer.

The constrained relationships between different objects,can be introduced by attaching or nesting the individual (parametric) objects to one another. Both methods, nesting as well as attaching, define a fixed geometric relationship between two objects: they can share an edge, have com-planar sides or the like. Nesting an element also introduc-es a hierarchy in the model which can be used as a means to provide different levels of detail. A more detail descrip-tion of the modelling concept is given in (Hirschberg,1996).

3.2.Feature measurement

The feature measurement employed in DIPAD is a semi-automatic routine, where a generic object model is used to detect the features described by this model. Therefore,only relevant features (as defined by the user) are extract-ed and redundant or useless informations are reduced to a minimum. The use of a priori knowledge makes explicit assumptions, that allows the checking of whether or not these assumptions are fulfilled in the images. The three-dimensional position of the object is derived by a simulta-neous multi-frame feature extraction, where the object model is reconstructed and used to triangulate the object points from corresponding image points.

Although boundaries of objects are only a small percent-age of the whole image content, they have major impor-tance for the description of object discontinuities. This routine takes advantage of this knowledge, by first locat-ing the edges of the features to be measured and then de-riving the vertices as intersections of appropriate lines.This routine consists basically of three loops (see Fig. 2).First an internal loop performs the feature extraction in 2D-space, based on the radiometric information given by the digital imagery. An external loop allows the determi-nation of object coordinates from multi-frames, and final-ly an orientation loop provides for the estimation of the a priori unknown camera parameters (interior/exterior ori-entation) by a bundle adjustment.3.2.1Internal loop

The approximation of object space features transformed into image space are used as starting values for the two-di-mensional automatic extraction algorithm. It is based on the assumption that discontinuities or rapid changes in the intensity of the image signal often occur at the physical extent (edges) of objects within the image.

Local searches are carried out at regular intervals along directions perpendicular to the approximate (a priori)

boundary. A Sobel edge operator (Eq. 1) is applied to each of the discrete points along each of these perpendicular di-rections.

(Eq. 1)

Every pixel is assigned a gradient value, which is a vector containing the amplitude and the direction. The spatial gradient amplitude is given by:

(Eq. 2)

The direction of the spatial gradient with respect to the row axis is:

(Eq. 3)

For each such direction, the pixel with the highest ampli-tude within a user defined search window, starting from the approximate line, is pre-selected as an edge pixel. This pixel has to be confirmed by applying the same search window, now starting from the previously selected pixel.This procedure continues until the selected pixel remains at its position.

The subpixel position of the edge is then determined by fitting a second-order polynomial (parabola) in the direc-tion of the gradient. The maximum point of the fitting curve corresponds to the subpixel position of the edge (see Figure 3).

The coef?cients (c 0, c 1, c 2) of the parabola

(Eq. 4)

object space

image space performed in:

Figure 2: General data ?ow of feature measurement

h r 1

--121000

1–2–1

–=h c 1

--101–202

–101

–=g j k ,()r j k ,()2

g c j k ,()

θj k ,()arc g c j k ,()

g r j k ,()

-----------------tan =π–θπ

?++=

are estimated in a least-squares adjustment. The vector x

of unknown parameters (c0, c1, c2) is determined by mini-mizing the sum of squares of the estimated residuals as

(Eq. 5) The precision of the estimates x can be derived by error propagation.

(Eq. 6) As the result should not depend on a user de?ned window size, the determination of the best fitting parabola is re-peated with different window sizes of odd number, grow-ing from a width of five pixel until the estimated results are not improved by the next higher window size.

The extremum of the best parabola gives the subpixel so-lution of the line point (u0):

(Eq. 7) The precision of subpixel solution can be estimated by er-ror propagation with the know covarinace matrix of the estimates x (parameters of parabola):

(Eq. 8) Finally a pixel is accepted as a line pixel, if

q the extremum of the parabola falls inside the pixel, and if

q c2 is negative and differs signi?cantly from zero.

By applying additional user de?ned criteria, a pixel can be automatically rejected by the algorithm. Such optional cri-teria are:

q if the orientation of the gradient differs more than a certain treshold from the mean orientation of all line points,

q if the distance between the estimated line point and the approximate line is above a certain treshold,

q if the standard deviation of the determined subpixel line point u0 is above a certain treshold, or

q if the amplitude of the gradient, corresponding to the line point, is below a certain treshold.

Once the line points of all objects within the image will be detected, the algorithm converts this raster data into vector format by ?tting straight lines to the linear boundaries.

(Eq. 9) The estimates for the standard deviation of line points are used as weighting functions. The line parameters (a0 and a1) are estimated by a least-squares adjustment (Eq. 5, 6). These vectors will then be used to determine the image coordinates of object vertices (x0, y0) by line intersection.

(Eq. 10)

(Eq. 11) Here the estimates for the standard deviation of the line parameters serve as weighting functions. If more than two lines intersect in one point, the intersection is calculated as a weigthed mean of all possible intersections.

3.2.2Problems to be faced during internal loop

For the image-based feature measurement not only an ideal appearing edge has to be taken into account, often a real world scene disturbed by additional phenomena. Such phenomena can be occlusions, weak or missing contrast, inversion of gradient directions, shadows, radiometric interferences, or re?ections (see Fig. 4).

Shadow edges can easily be rejected with the information about the approximate lines. This criterion does not work, if the shadow edges run parallel in a short distance to the edge one is looking for. Weak contrast, reflections, and occlusions can be handled by accepting a line pixel only if the parabola fit is significant and if the first parameter is negative. Interferences and occlusions tend to mislead the measurement of the correct edge. This problem can be faced by taking the gradient orientation into account. Line parameters can be determined significantly, if just a part of the entire line can be observed. Inversion of the gradi-ent direction along an object line, typically occurring in real world scenes, where the horizon is imaged or an ob-ject feature has different re?ection properties, can be han-dled if the gradient orientation is taken into account. It is notable, that the gradient orientation is a strong criterion in order to determine the correct line pixels (H?nisch, 1992).

3.2.3External loop and orientation loop

The internal loop is performed sequentially in all images. The object coordinates of a point imaged in two or more images are calculated either by a spatial intersection, by a bundle adjustment or by a bundle adjustment with self-

x?A T PA

()1–A T Py

=σ?02

e?T Pe?

-----------=

D?x?()Σx?x?σ?02Q x?x?

?σ?02A T PA

()1–

===

f u()

?u??0

=u0

–

2c2

-----------=

D y()A D x()A T

f x()a0a1x?

=f y()a0a1y?

y0a1b1x0

=y0a2b2x0

b1b2

–

a2a1

–

----------------

=y0

a2b1

?a1b2

–

a2a1

–

-----------------------------------

Figure 4: Problematic cases occuring during internal loop.

occlusion

weak contrast

re?ection interference

inversion of gra-

dient direction shadow

calibration, depending on which model parameters are treated as a priori known or unknown.

The functional model describing the relationship between the derived and measured quantities consists of the well known colinearity equations (Eq. 12). For each pair of im-age coordinates (x, y) observed on each image the follow-ing pair of equations is written:

(Eq. 12) with the auxiliaries:

(Eq. 13) with the image coordinates (x, y), the elements of interior orientation (x p, y p, c), functions of additional parameters (?x,?y), the object coordinates (X, Y, Z), a 3 by 3 orthog-onal rotation matrix D with the three rotationsω,?,κ and the object coordinates of the perspective centre (X0, Y0, Z0). Starting from observed values the overconstrained equation system (Eq. 12) can be solved leading to esti-mates of the unknown parameters (cf. Eq. 5,6). In most applications it can be assumed that the exterior and interi-or orientation parameters of the camera are unknown.

In the next step the derived object coordinates are re-pro-jected into each image and used to restart the 2D feature extraction. This proceeds until the estimated unknowns do not change signi?cantly form on iteration step to the next. The result of this process is then transferred with addition-al information about precision and reliability to the CAD environment, which allows the ?nal judgement by the hu-man operator.

4. PRACTICAL EXAMPLE

The work described in this paper was done as part of the contribution to the CIPA project “Wagner-Pavillon”. The idea and the initiative of this project belongs to P. Wald-h?usl (Waldh?usl, 1991) and the aim was to check the cur-rent state-of-the-art in architectural photogrammetry.

The Otto-Wagner-Pavillon is one of Otto Wagner’s Stadt-bahn Station buildings (see Fig. 5) on the Karlsplatz in Vi-enna, built in 1898/1899. The dimensions of the building are 15x8x10m3. The object coordinates of 44 non-sig-nalized (but well defined in the majority) control points have been determined geodetically with an accuracy of 2mm.

4.1.Image acquisition

In this test the image acquisition was performed with an inexpensive S-VHS camcorder. Although camcorders are not intended for photogrammetric use, they exhibit many useful characteristics. They are inexpensive and widely used for other purposes as well, they are portable and free-hand, they need no special equipment, they offer the abili-ty of on-site quality control. Furthermore they provide very inexpensively means for storage of huge amount of video data on video tapes.

The JVC GR-S77E camcorder is a free-hand portable camera, which allows on-site control for the acquired im-agery via an internal monitor. The camera incorporates a 1/2” colour sensor (6.4x4.8mm2). The analog images are stored on a S-VHS video tape and have to be digitized by a framegrabber. The digitized images have a size of 728x568 pixel, which results in a pixel spacing of 8.8μm in the horizontal and 8.5μm in the vertical direction. The focal length (zoom lens) can vary between 8.5mm and 65mm, which was ?xed at its shortest focal length during the image acquisition.

4.2.Object reconstruction

The image acquisition took place in a way that an image sequence from the object was generated by a person walk-ing with the camera around the object and ?lming all four facades. From this video tape 38 single frames were ran-domly digitized with a framegrabber. The mean distance between the camera and the object was about 16 m, which results in an image scale of 1:1800.

The measurement of image features, the estimation of ex-terior orientation parameters and additional camera pa-rameters for self-calibration as well as the determination of the object coordinates was performed with the feature measurement routine as described above.

A total of 1611 object coordinates was determined to de-scribe the entire building. Therefore 2589 image points have been measured semi-automatically by the feature measurement routine. The normal equation system, which has to be solved consists of 5178 observations and 1726 unknowns. The precision of the object coordinates was determined as a part of the bundle adjustment routine. The results indicate a precision in object space of 1.1 cm in X, 1.3 cm in Y, and 0.7 cm in Z, with X- and Y-axis in the plane and Z-axis in height. This corresponds to 6.7μm in image space. A more detailed description of the numerical results of this test is given in (Streilein, 1995).

These results are comparable to the results derived with classical photogrammetric equipment in the CIPA test

F x x x p

–

()c U W -----

–x

F y y y p

–

()c V W -----

–y

V W

Dω?κ

()

X X0

–

Y Y0

–

Z Z0

–

Figure 5: Otto-Wagner-Pavillon, Vienna.

(Patias, et al., 1993). There a total of 51 solutions was processed with different hard- and software. The average precision of these solutions is in a range of 0.3cm to 2.0cm. Among these, 29 solutions with small format cameras were calculated. The precision of these solutions is in a range of 0.6cm to 1.1cm.

The final product of the photogrammetric analysis with DIPAD is a three-dimensional geometric and semantic ob-ject description of the Otto-Wagner-Pavillon in the CAD environment (see Fig. 6). The representation of the archi-tectural object can be given either by its object points,lines (wireframes), surfaces or any combinations of these.The representation in a CAD environment offer also the capabilities of Virtual Reality in terms of visualization and animation. The original image data can be draped onto the derived object model and animations (walk-through, fly-through) can be performed.

5. CONCLUSIONS

This paper described an object oriented measurement ap-proach using CAD models for the for the initialization of an automatic measurement process and for the veri?cation of the measurement results. Accurate image measurement using conventional technology demands expertise, is time-consuming, tiring and not without errors. The semi-automated approach delivers results in less time and more reliable than a user with conventional (manual) tools. The final solution can easily be interpreted and judged by an operator in the CAD environment, which still requires ex-pertise, but is feasible for an untrained person.

6. REFERENCES

Albertz, J., Wiedemann, A., 1995. Acquisition of CAD data from existing buildings by photogrammetry. Proc. 6th Intern. Conf. on Computing in Civil and Building Engineering, Berlin, 1995.A.A. Balkena, Rotterdam, pp. 859-866.

Chapman, D.P., Deacon, A.T.D., Hamid, D., 1994. HAZMAP: a remote digital measurement system for work in hazardous envi-ronments. Photogrammetric Record, 14(83), pp. 747-758.

El-Hakim, S., Pizzi, N., 1993. Multicamera vision-based approach to flexible feature measurement for inspection and reverse engi-neering. Optical Engineering, V ol. 32, No. 9, pp. 2201-2215.Fellbaum, M., 1992. Low cost surveying systems in architectural photogrammetry. IAPRS, V ol. XXIX, Part B5, pp. 771-777.Gruber, M, Meissl, S., B?hm, R., 1995. Das dreidimensionale digitale Stadtmodell Wien: Erfahrungen aus einer V orstudie. ?s-tereichische Zeitschrift für V ermessung und Geoinformation.1+2/95, pp. 29-36.

Hirschberg, U., 1996. Object-oriented data-integration between digitasl architectural photogrammetry and CAAD. IAPRS, V ol.XXXI, Part 5, to appear.

H?nisch, U., 1992. Veri?cation of graphical primitives in gradient direction images. IAPRS, V ol. XXIX, Part B5, pp. 646-651.Oshima, T., 1992. Some recent examples in industrial photogram-metric application with CAD techniques. IAPRS, V ol. XXIX,Part B5, pp. 250-255.

Kempa, M., Schlüter, M., 1992. Graphical representation of an ar-menian castle with AutoCAD. IAPRS, V ol. XXIX, Part B5, pp.241-244.

Lang, F., Schickler, W., 1993. Semi-automatische 3D-Geb?uder-fassung aus digitalen Bildern, Zeitschrift für Photogrammetrie und Fernerkundung, 5/93, pp. 193-200.

Mason, S., 1994. Expert System-Based Design of Photogrammet-ric Networks. Diss., ETH Zürich, Published as Mitteilung Nr.53, Institute of Geodesy and Photogrammetry, ETH Zürich.Mason, M., Streilein, A., 1996. Photogrammetric Reconstruction of 3D City Models. Submitted to SA J. Surveying and Mapping.Mc Glone, C., 1995. Some considerations in 3D object modeling.Published in Photogrammetric Reports No. 63, Royal Institute of Technology, Stockholm, 1995.

Patias, P., Rossikopoulos, D., Georgoula, O., 1993. CIPA Test O.Wagner Pavillon. Preliminary Report. Presented at the CIP A XV International Symposium, Bucharest, Romania, September 22-26, 1993..

Robson, S., Littleworth, R.M., Cooper, M.A.R., 1994. Construc-tion of accurate 3D computer models for archaeology , exempli-fied by a photogrammetric survey of the tomb of christ in Jerusalem. IAPRS, V ol. XXX, Part 5, pp. 338-344.

Saint-Aubain, J.-P.., 1990. L’image photogrammetrique de syn-these. IAPRS, V ol. 28, Part 5/1, pp. 182-190.

Sawyer, P., Bell, J., 1994. Photogrammetric recording and 3D vis-ualization of Ninstints - a world heritage site. IAPRS, V ol. XXX,Part 5, pp. 345-348.

Schickler, W., 1992. Feature matching of Outer Orientation of Single Images Using 3-D Wireframe Controlpoints. IAPRS, V ol.XXIX, Part B3, pp. 591-598.

Schmitt, G., 1993. Architectura et Machina, Vieweg, Braunsch-weig, 251 pages.

Stevens, D. Mc Kay, W.M., 1990. Combined use of photogram-metry and CAD in the reconstruction of ?re-damaged buildings.IAPRS, V ol. XXVIII, Part B5/1, pp. 77-85.

Streilein, A. Videogrammetry and CAAD for architectural restitu-tion of the Otto-Wagner-Pavillon in Vienna, Optical 3-D Meas-urement Techniques III, Gruen/Kahmen (Eds.), Wichmann,Heidelberg, pp. 305-314.

Waldh?usl, P., 1991. A test object for architectural photogramme-try: Otto Wagners underground station Karlsplatz in Vienna,Proceedings of the XIV . International Symposium of CIPA, Oc-tober 2-5, 1991, Delphi, Greece, pp. 247-251.

IAPRS = International Archives of Photogrammetry and Remote Sensing

Figure 6: Photogrammetrically generated CAD-model of Otto-Wagner-Pavillon. From left to right: wireframe

model, surface model, texture model draped with original image data.

的、地、得的用法和区别

“的、地、得”的用法和区别导入（进入美妙的世界啦~） “的、地、得”口诀儿歌的地得，不一样，用法分别记心上，左边白，右边勺，名词跟在后面跑。美丽的花儿绽笑脸，青青的草儿弯下腰，清清的河水向东流，蓝蓝的天上白云飘，暖暖的风儿轻轻吹，绿绿的树叶把头摇，小小的鱼儿水中游，红红的太阳当空照，左边土，右边也，地字站在动词前，认真地做操不马虎，专心地上课不大意，大声地朗读不害羞，从容地走路不着急，痛快地玩耍来放松，用心地思考解难题，勤奋地学习要积极，辛勤地劳动花力气，左边两人双人得，形容词前要用得，兔子兔子跑得快，乌龟乌龟爬得慢，青青竹子长得快，参天大树长得慢，清晨锻炼起得早，加班加点睡得晚，欢乐时光过得快，考试题目出得难。知识典例（注意咯，下面可是黄金部分！）的、地、得 “的”、“地”、“得”的用法区别本是中小学语文教学中最基本的常识，但在使用中也最容易发生混淆，再加上一段时间里，中学课本中曾将这三个词的用法统一为“的”，因此造成了很多人对它们的用法含混不清进而乱用一通的现象。

一、“的、地、得”的基本概念 1、“的、地、得”的相同之处。 “的、地、得”是现代汉语中高频度使用的三个结构助词，都起着连接作用；它们在普通话中都读轻声“de”，没有语音上的区别。 2、“的、地、得”的不同之处。吕叔湘、朱德熙所著《语法修辞讲话》认为“的”兼职过多，负担过重，而力主“的、地、得”严格分工。50 年代以来的诸多现代汉语论著和教材，一般也持这一主张。从书面语中的使用情况看，“的”与“地”、“得”的分工日趋明确，特别是在逻辑性很强的论述性、说明性语言中，如法律条款、学术论著、外文译著、教科书等，更是将“的”与“地”、“得”分用。 “的、地、得”在普通话里都读轻声“de”，但在书面语中有必要写成三个不同的字：在定语后面写作“的”，在状语后面写作“地”，在补语前写作“得”。这样做的好处，就是可使书面语言精确化。二、“的、地、得”的用法 1、的——定语的标记，一般用在主语和宾语的前面。“的”前面的词语一般用来修饰、限制“的”后面的事物，说明“的”后面的事物怎么样。结构形式一般为：形容词、名词（代词）+的+名词。如： ①颐和园(名词)的湖光山色（主语）美不胜收。 ②她是一位性格开朗的女子(名词，宾语)。 2、地——状语的标记，一般用在谓语（动词、形容词）前面。“地”前面的词语一般用来形容“地”后面的动作，说明“地”后面的动作怎么样。结构方式一般为：形容词（副词）+地+动词（形容词）。如： ③她愉快(形容词)地接受(动词，谓语)了这件礼物。 ④天渐渐(时间副词)地冷(形容词，谓语)起来。 3、得——补语的标记，一般用在谓语后面。“得”后面的词语一般用来补充说明“得”前面的动作怎么样，结构形式一般为：动词（形容词）+得+副词。如： ⑤他们玩(动词，谓语)得真痛快(补语)。

CAD系统变量与LISP函数摘要

CAD系统变量与LISP函数摘要二○○○年二月

目录 AutoCAD系统变量 (1) A (1) B (4) C (4) D (8) E (26) F (27) G (29) H (30) I (32) L (33) M (36) N (38) O (39) P (40) Q (46) R (46) S (47) T (53) U (56) V (59) W (60) X (61) AutoLISP函数 (63) 运算符 (63) A (66) B (73) C (74) D (79) E (82) F (91) G (92) H (102) I (103) L (106) M (109) N (112)

O (115) P (117) Q (118) R (119) S (122) T (133) U (138) V (138) W (139) X (141) Z (143) 附1：错误代码 (144) 附2：AutoLISP 标准错误信息 (146)

AutoCAD系统变量 A ACADPREFIX （只读）类型：字符串保存方式：无本系统变量存储由ACAD 环境变量指定的目录路径（如果有的话），如果需要则添加路径分隔符。 ACADVER （只读）类型：字符串保存方式：无本系统变量存储AutoCAD 版本号，其值可能为14 或14a。这个变量与DXF 文件标题变量$ACADVER 不同，$ACADVER 包含图形数据库的级别号。 ACISOUTVER 类型：整型保存方式：图形初始值：16 本系统变量控制使用ACISOUT 命令创建的SAT 文件的ACIS 版本。当前ACISOUT 支持的值只有15 到18、20、21 和30。 AFLAGS 类型：整型保存方式：无初始值：0 本系统变量设置A TTDEF 位码的属性标记。包括以下标记： 0 选定无属性模式 1 不可见 2 常数 4 验证 8预置 ANGBASE 类型：实型保存方式：图形

of与for的用法以及区别

of与for的用法以及区别 for 表原因、目的 of 表从属关系介词of的用法（1）所有关系 this is a picture of a classroom （2）部分关系 a piece of paper a cup of tea a glass of water a bottle of milk what kind of football，American of soccer？（3）描写关系 a man of thirty 三十岁的人 a man of shanghai 上海人（4）承受动作 the exploitation of man by man．人对人的剥削。（5）同位关系 It was a cold spring morning in the city of London in England．（6）关于，对于 What do you think of Chinese food？你觉得中国食品怎么样？介词 for 的用法小结 1. 表示“当作、作为”。如: I like some bread and milk for breakfast. 我喜欢把面包和牛奶作为早餐。What will we have for supper? 我们晚餐吃什么?

2. 表示理由或原因,意为“因为、由于”。如: Thank you for helping me with my English. 谢谢你帮我学习英语。 Thank you for your last letter. 谢谢你上次的来信。 Thank you for teaching us so well. 感谢你如此尽心地教我们。 3. 表示动作的对象或接受者,意为“给……”、“对…… (而言)”。如: Let me pick it up for you. 让我为你捡起来。 Watching TV too much is bad for your health. 看电视太多有害于你的健康。 4. 表示时间、距离,意为“计、达”。如: I usually do the running for an hour in the morning. 我早晨通常跑步一小时。We will stay there for two days. 我们将在那里逗留两天。 5. 表示去向、目的,意为“向、往、取、买”等。如: let’s go for a walk. 我们出去散步吧。 I came here for my schoolbag.我来这儿取书包。 I paid twenty yuan for the dictionary. 我花了20元买这本词典。 6. 表示所属关系或用途,意为“为、适于……的”。如: It’s time for school. 到上学的时间了。 Here is a letter for you. 这儿有你的一封信。 7. 表示“支持、赞成”。如: Are you for this plan or against it? 你是支持还是反对这个计划? 8. 用于一些固定搭配中。如: Who are you waiting for? 你在等谁? For example, Mr Green is a kind teacher. 比如,格林先生是一位心地善良的老师。

to与for的用法和区别

to与for的用法和区别一般情况下, to后面常接对象; for后面表示原因与目的为多。 Thank you for helping me. Thanks to all of you. to sb.表示对某人有直接影响比如，食物对某人好或者不好就用to; for表示从意义、价值等间接角度来说，例如对某人而言是重要的，就用for. for和to这两个介词，意义丰富，用法复杂。这里仅就它们主要用法进行比较。 1. 表示各种“目的” 1. What do you study English for? 你为什么要学英语？ 2. She went to france for holiday. 她到法国度假去了。 3. These books are written for pupils. 这些书是为学生些的。 4. hope for the best, prepare for the worst. 作最好的打算，作最坏的准备。 2．对于 1．She has a liking for painting. 她爱好绘画。 2．She had a natural gift for teaching. 她对教学有天赋/ 3．表示赞成同情，用for不用to. 1. Are you for the idea or against it? 你是支持还是反对这个想法？ 2. He expresses sympathy for the common people.. 他表现了对普通老百姓的同情。 3. I felt deeply sorry for my friend who was very ill. 4 for表示因为，由于（常有较活译法） 1 Thank you for coming. 谢谢你来。 2. France is famous for its wines. 法国因酒而出名。 5．当事人对某事的主观看法，对于（某人），对…来说（多和形容词连用）用介词to，不用for.. He said that money was not important to him. 他说钱对他并不重要。 To her it was rather unusual. 对她来说这是相当不寻常的。 They are cruel to animals. 他们对动物很残忍。 6．for和fit, good, bad, useful, suitable 等形容词连用，表示适宜，适合。 Some training will make them fit for the job. 经过一段训练，他们会胜任这项工作的。 Exercises are good for health. 锻炼有益于健康。 Smoking and drinking are bad for health. 抽烟喝酒对健康有害。 You are not suited for the kind of work you are doing. 7. for表示不定式逻辑上的主语，可以用在主语、表语、状语、定语中。 1．It would be best for you to write to him. 2．The simple thing is for him to resign at once. 3．There was nowhere else for me to go. 4．He opened a door and stood aside for her to pass.

“的、地、得”的用法和区别

的、地、得的用法和区别的、地、得的用法和区别老班教育一、的、地、得的基本概念 1、的、地、得的相同之处。的、地、得是现代汉语中高频度使用的三个结构助词，都起着连接作用；它们在普通话中都读轻声de，没有语音上的区别。 2、的、地、得的不同之处。吕叔湘、朱德熙所著《语法修辞讲话》认为的兼职过多，负担过重，而力主的、地、得严格分工。50 年代以来的诸多现代汉语论著和教材，一般也持这一主张。从书面语中的使用情况看，的与地、得的分工日趋明确，特别是在逻辑性很强的论述性、说明性语言中，如法律条款、学术论著、外文译著、教科书等，更是将的与地、得分用。的、地、得在普通话里都读轻声de，但在书面语中有必要写成三个不同的字：在定语后面写作的，在状语后面写作地，在补语前写作得。这样做的好处，就是可使书面语言精确化。二、的、地、得的用法（一）、用法 1、的——定语的标记，一般用在主语和宾语的前面。的前面的词语一般用来修饰、限制的后面的事物，说明的后面的事物怎么样。结构形式一般为：形容词、名词（代词）+的+名词。如：颐和园(名词)的湖光山色（主语）美不胜收。她是一位性格开朗的女子(名词，宾语)。 2、地——状语的标记，一般用在谓语（动词、形容词）前面。地前面的词语一般用来形容地后面的动作，说明地后面的动作怎么样。结构方式一般为：形容词（副词）+地+动词（形容词）。如：她愉快(形容词)地接受(动词，谓语)了这件礼物。天渐渐(时间副词)地冷(形容词，谓语)起来。 3、得——补语的标记，一般用在谓语后面。得后面的词语一般用来补充说明得前面的动作怎么样。结构形式一般为：动词（形容词）+得+副词。如：他们玩(动词，谓语)得真痛快(补语)。她红(形容词，谓语)得发紫(补语)。（二）、例说的，一般用在名词和形容词的后面，用在描述或限制人物、事物时，形容的词语与被形容的词语之间，表示一种描述的结果。如：漂亮的衣服、辽阔的土地、高大的山脉。结构一般为名词（代词或形容词）+的+名词。如，我的书、你的衣服、他的孩子，美丽的景色、动听的歌曲、灿烂的笑容。地，用法简单些，用在描述或限制一种运动性质、状态时，形容的词语与被形容的词语之间。结构通常是形容词+地+动词。前面的词语一般用来形容后面的动作。一般地的后面只跟动词。比如高兴地跳、兴奋地叫喊、温和地说、飞快地跑；匆匆地离开；慢慢地移动......... 得，用在说明动作的情况或结果的程度时，说明的词语与被说明的词语之间，后面的词语一般用来补充和说明前面的情况。比如。跑得飞快、跳得很高、显得高雅、显得很壮、馋得直流口水、跑得快、飞得高、走得慢、红得很……得通常用在动词和形容词（动词之间）。

CAD命令大全(CAD系统变量设置)

CAD快捷键命令命令大全(CAD系统变量设置） A ACADLSPASDOC 控制AutoCAD 是将acad.lsp 文件加载到所有图形中，还是仅加载到在AutoCAD 任务中打开的第一个文件中 ACADPREFIX 存储由ACAD 环境变量指定的目录路径（如果有的话），如果需要则添加路径分隔符 ACADVER 存储AutoCAD 版本号 ACISOUTVER 控制ACISOUT 命令创建的SAT 文件的ACIS 版本AFLAGS 设置ATTDEF 位码的属性标志 ANGBASE 设置相对当前UCS 的0 度基准角方向 ANGDIR 设置相对当前UCS 以0 度为起点的正角度方向 APBOX 打开或关闭AutoSnap 靶框 APERTURE 以像素为单位设置对象捕捉的靶框尺寸 AREA 存储由AREA、LIST 或DBLIST 计算出来的最后一个面积 ATTDIA 控制-INSERT 是否使用对话框获取属性值 ATTMODE 控制属性的显示方式 ATTREQ 确定INSERT 在插入块时是否使用缺省属性设置 AUDITCTL 控制AUDIT 命令是否创建核查报告文件 AUNITS 设置角度单位 AUPREC 设置角度单位的小数位数 AUTOSNAP 控制AutoSnap 标记、工具栏提示和磁吸 B BACKZ 存储当前视口后剪裁平面到目标平面的偏移值 BINDTYPE 控制绑定或在位编辑外部参照时外部参照名称的处理方式BLIPMODE 控制点标记是否可见 C CDATE 设置日历的日期和时间 CECOLOR 设置新对象的颜色 CELTSCALE 设置当前对象的线型比例缩放因子 CELTYPE 设置新对象的线型 CELWEIGHT 设置新对象的线宽 CHAMFERA 设置第一个倒角距离 CHAMFERB 设置第二个倒角距离 CHAMFERC 设置倒角长度 CHAMFERD 设置倒角角度 CHAMMODE 设置AutoCAD 创建倒角的输入模式 CIRCLERAD 设置缺省的圆半径 CLAYER 设置当前图层 CMDACTIVE 存储一个位码值，此位码值标识激活的是普通命令、透明命令、脚本还是对话框 CMDECHO 控制AutoLISP 的(command) 函数运行时AutoCAD 是否回显

常用介词用法(for to with of)

For的用法 1. 表示“当作、作为”。如: I like some bread and milk for breakfast. 我喜欢把面包和牛奶作为早餐。 What will we have for supper? 我们晚餐吃什么? 2. 表示理由或原因,意为“因为、由于”。如: Thank you for helping me with my English. 谢谢你帮我学习英语。 3. 表示动作的对象或接受者,意为“给……”、“对…… (而言)”。如: Let me pick it up for you. 让我为你捡起来。 Watching TV too much is bad for your health. 看电视太多有害于你的健康。 4. 表示时间、距离,意为“计、达”。如: I usually do the running for an hour in the morning. 我早晨通常跑步一小时。 We will stay there for two days. 我们将在那里逗留两天。 5. 表示去向、目的,意为“向、往、取、买”等。如: Let’s go for a walk. 我们出去散步吧。 I came here for my schoolbag.我来这儿取书包。 I paid twenty yuan for the dictionary. 我花了20元买这本词典。 6. 表示所属关系或用途,意为“为、适于……的”。如: It’s time for school. 到上学的时间了。 Here is a letter for you. 这儿有你的一封信。 7. 表示“支持、赞成”。如: Are you for this plan or against it? 你是支持还是反对这个计划? 8. 用于一些固定搭配中。如: Who are you waiting for? 你在等谁? For example, Mr Green is a kind teacher. 比如,格林先生是一位心地善良的老师。尽管for 的用法较多，但记住常用的几个就可以了。 to的用法: 一：表示相对，针对 be strange (common, new, familiar, peculiar) to This injection will make you immune to infection. 二：表示对比，比较 1：以-ior结尾的形容词，后接介词to表示比较，如：superior ,inferior,prior,senior,junior 2: 一些本身就含有比较或比拟意思的形容词，如equal，similar，equivalent，analogous A is similar to B in many ways.

的地得的用法和区分

《“的、地、得”的用法》语文微课教案一、教学背景在语言文字规范化大背景下，帮助学生解决应用“的地得”的疑惑与困难。二、设计思路针对学生对于“的地得”的误用与忽视展开教学，规范结构助词“的地得”的使用。按照“问题的提出、问题的分析、问题的解决”的思路展开教学，总结归纳优化的方式方法。三、教学目标 1、知道“怎么样的什么、怎么样地干什么、干得怎么样”三种固定搭配。 2、掌握“的、地、得”的区别与联系。 3、运用小儿歌“动前土、名前白、行动后面双人来”的口诀帮助正确使用“的、地、得”。四、教学重难点 1、知道“的、地、得”的区别。 2、在实际情境中正确运用“的、地、得”。五、教学时间 8分钟微课堂六、教学适用对象义务教育九年制内的学生七、教学准备

多媒体课件、录屏软件八、教学设计与过程开场白：同学们好！今天我们一起来学习“的、地、得”的正确用法。首先我们来了解一下它们的区别。 1、相同之处：原来它们都是念轻声“de”，都是结构助词，起连接作用。 2、不同之处：在书面语中要写成三个不同的字，而且它们的搭配及用法也各不相同。（1）怎么样的什么（2）怎样样地干什么（3）干得怎么样下面我们就来学习一下它们的正确用法。白勺“的”的结构是用“形容词或名词或代词+的+名词”来表示，而我们最常见，用得最多的还是“形容词+的+名词”的结构。而土也“地”的用法可以用“形容词+地+动词”的结构来表示。双人“得”是用“动词+得+形容词”的结构来表示 3、练习巩固（1）形近区分静静（的）河面静静（地）写字欢乐（的）山谷

欢乐（地）歌唱满意（地）点头满意（的）作品（2）类别区分 1）跑（得）飞快飞快（地）跑 2）愉快（的）旅行旅行（得）愉快 3）强烈（的）渴望强烈（地）渴望（3）综合杂糅小雏鹰飞到大树的上方，高兴地喊起来：“我真的会飞啦！而且飞（得）很高呢！” 小结：能填对这个句子的你肯定就已经学会它们的用法了！ 4、特殊情况质疑：假如遇到特殊情况怎么办呢？我从书包里拿出书交给她们，她们高兴得．围着我跳起舞来。（出自二年级上册《日记两则》）（1）质疑：为什么这里要使用“得”呢？（2）释疑：原来这里强调的是心情，动词在后，形容词在前，相当于后置，“得”修饰“跳舞”而非“围”。现在你明白了吧？ 5、小结归纳：怎么样，你们学会了吗？为了让同学们能够更快的记住它们的用法，老师送给大家一首口诀来帮助你们熟记三个“的”的正确使用方法：动前土、名前白、行动后面双人来。

of和for的用法

of 1....的,属于 One of the legs of the table is broken. 桌子的一条腿坏了。 Mr.Brown is a friend of mine. 布朗先生是我的朋友。 2.用...做成的;由...制成 The house is of stone. 这房子是石建的。 3.含有...的;装有...的 4....之中的;...的成员 Of all the students in this class,Tom is the best. 在这个班级中,汤姆是最优秀的。 5.(表示同位) He came to New York at the age of ten. 他在十岁时来到纽约。 6.(表示宾格关系) He gave a lecture on the use of solar energy. 他就太阳能的利用作了一场讲演。 7.(表示主格关系) We waited for the arrival of the next bus. 我们等待下一班汽车的到来。

I have the complete works of Shakespeare. 我有莎士比亚全集。 8.来自...的;出自 He was a graduate of the University of Hawaii. 他是夏威夷大学的毕业生。 9.因为 Her son died of hepatitis. 她儿子因患肝炎而死。 10.在...方面 My aunt is hard of hearing. 我姑妈耳朵有点聋。 11.【美】(时间)在...之前 12.(表示具有某种性质) It is a matter of importance. 这是一件重要的事。 For 1.为,为了 They fought for national independence. 他们为民族独立而战。 This letter is for you. 这是你的信。

CAD系统变量_C

系统变量快速参考单击按字母顺序列出的系统变量的首字母。 3D A B C D E F G H I J K L M N O P Q R S T U V W X Y Z CACHE MAXF ILE S（系统变量）设置为产品保存的图形缓存文件的最大数量。 CACHE MAXTOTALSIZE（系统变量）设置为产品保存的所有图形缓存文件的总大小的最大值。 CALCINPUT（系统变量）控制是否计算文字中以及窗口和对话框的数字输入框中的数学表达式和全局常量。CAME RADISPLAY（系统变量）打开或关闭相机对象的显示。 CAME RAHE IG HT（系统变量）为新相机对象指定默认高度。 CANNOSCALE VALUE（系统变量）显示当前注释比例的值。 CANNOSCALE（系统变量）为当前空间设置当前注释比例的名称。 CAPTURE THUMBNAILS（系统变量）指定是否及何时为回放工具捕捉缩略图。 CBARTRANSPARE NCY（系统变量）控制约束栏的透明度。 CCONSTRAINTF ORM（系统变量）控制是将注释性约束还是将动态约束应用于对象。 CDATE（系统变量）以编码的小数格式存储当前的日期和时间。 CE COLOR（系统变量）设置新对象的颜色。 CE LTSCALE（系统变量）设置当前对象的线型比例缩放因子。 CE LTY PE（系统变量）设置新对象的线型。 CE LWE IG HT（系统变量）设置新对象的线宽。 CE NTE RMT（系统变量）控制通过夹点拉伸多行水平居中的文字的方式。 CE TRANSPARE NCY（系统变量）设定新对象的透明度级别。 CG E OCS（系统变量）存储指定给图形文件的 GIS 坐标系的名称。 CHAMF E RA（系统变量）当 CHA M M ODE 设定为 0 时设置第一个倒角距离。 CHAMF E RB（系统变量）当 CHA M M ODE 设定为 0 时设置第二个倒角距离。 CHAMF E RC（系统变量）当 CHA M M ODE 设定为 1 时设置倒角长度。 CHAMF E RD（系统变量）当 CHA M M ODE 设定为 1 时设置倒角角度。 CHAMMODE（系统变量）设置 CHA M FER 的输入方法 CIRCLE RAD（系统变量）设置默认的圆半径。 CLASSICKE Y S（系统变量）设置 DOS 和 Windows 标准间的多个控制键的行为。 CLAY E R（系统变量）设置当前图层。

双宾语 to for的用法

1.两者都可以引出间接宾语，但要根据不同的动词分别选用介词to 或for：(1) 在give, pass, hand, lend, send, tell, bring, show, pay, read, return, write, offer, teach, throw 等之后接介词to。如：请把那本字典递给我。正：Please hand me that dictionary. 正：Please hand that dictionary to me. 她去年教我们的音乐。正：She taught us music last year. 正：She taught music to us last year. (2) 在buy, make, get, order, cook, sing, fetch, play, find, paint, choose,prepare, spare 等之后用介词for 。如：他为我们唱了首英语歌。正：He sang us an English song. 正：He sang an English song for us. 请帮我把钥匙找到。正：Please find me the keys. 正：Please find the keys for me. 能耽搁你几分钟吗(即你能为我抽出几分钟吗)? 正：Can you spare me a few minutes? 正：Can you spare a few minutes for me? 注：有的动词由于搭配和含义的不同，用介词to 或for 都是可能的。如：do sb a favour＝do a favour for sb 帮某人的忙 do sb harm＝do harm to sb 对某人有害

的地得的用法教案

“的、地、得”的用法教案教学目标： 1.能通过看视频知道“的、地、得”的用法区别。 2.能在小组合作中正确掌握“的、地、得”的用法。 3.能正确熟练地运用“的、地、得”。教学重点：通过看视频知道“的、地、得”的用法区别。教学难点：正确熟练地运用“的、地、得”。教学过程：一、导入（板书课题：“的、地、得”的用法“的、地、得”）这三个字认识吧！虽然它们都有一个相同的读音de，但用法却不一样，可不能把他们用错了。究竟他们的用法有什么不同，我们来听听他们的故事吧！二、看微视频，学习“的、地、得”的用法区别。三、小结： 1.孩子们，刚才看了视频知道他们是谁吗？（白勺的，土也地，双人得。）（1）白勺的是个杂货铺老板，她的店里都有什么？（彩色的毛巾美味的汉堡结实的帐篷舒适的儿童车捕捉风的网会唱歌的小树开个没完的花朵优美动听的歌曲飘来飘去的云……）还可能有什么？你们一定会发现，白勺的的用法有什么特点？（后面是名词。）板书：名词（2）土也地是个运动男孩，他喜欢？（悠闲地散步欢快地跳舞兴奋地跳跃开心地捕蝴蝶看图书踢球骑自行洗澡吃冰淇淋……）他还可能喜欢干什么呢？你发现了吗？土也地的用法特点？（后面是动词。）板书：动词（3）双人得呢？她是个总喜欢评价别人的小妹妹。（球踢得真棒舞跳得精彩长得好高呀……）她可能还怎么评价别人？（歌唱得动听饭吃得很饱人长得漂亮）你们会发现，双人得的前面通常都是——动词。板书：动词 2.小结：所以，他们的用法也很简单，区别就在这里。（白勺的用在名词前面；土也地用在动词前面；双人得用在动词后面。）你明白了吗？四、我来考考你们，看哪一组完成得又对又快！ 1.菜鸟级练习 2.老鸟级练习 3.大虾级练习五、总结

for和of的用法

for的用法： 1. 表示“当作、作为”。如: I like some bread and milk for breakfast. 我喜欢把面包和牛奶作为早餐。 What will we have for supper? 我们晚餐吃什么? 2. 表示理由或原因,意为“因为、由于”。如: Thank you for helping me with my English. 谢谢你帮我学习英语。 Thank you for your last letter. 谢谢你上次的来信。 Thank you for teaching us so well. 感谢你如此尽心地教我们。 3. 表示动作的对象或接受者,意为“给……”、“对…… (而言)”。如: Let me pick it up for you. 让我为你捡起来。 Watching TV too much is bad for your health. 看电视太多有害于你的健康。 4. 表示时间、距离,意为“计、达”。如:

I usually do the running for an hour in the morning. 我早晨通常跑步一小时。 We will stay there for two days. 我们将在那里逗留两天。 5. 表示去向、目的,意为“向、往、取、买”等。如: Let’s go for a walk. 我们出去散步吧。 I came here for my schoolbag.我来这儿取书包。 I paid twenty yuan for the dictionary. 我花了20元买这本词典。 6. 表示所属关系或用途,意为“为、适于……的”。如: It’s time for school. 到上学的时间了。 Here is a letter for you. 这儿有你的一封信。 7. 表示“支持、赞成”。如: Are you for this plan or against it? 你是支持还是反对这个计划? 8. 用于一些固定搭配中。如:

for和to区别

1.表示各种“目的”，用for （1）What do you study English for 你为什么要学英语？（2）went to france for holiday. 她到法国度假去了。（3）These books are written for pupils. 这些书是为学生些的。（4）hope for the best, prepare for the worst. 作最好的打算，作最坏的准备。 2．“对于”用for （1）She has a liking for painting. 她爱好绘画。（2）She had a natural gift for teaching. 她对教学有天赋/ 3．表示“赞成、同情”，用for （1）Are you for the idea or against it 你是支持还是反对这个想法？（2）He expresses sympathy for the common people.. 他表现了对普通老百姓的同情。（3）I felt deeply sorry for my friend who was very ill. 4. 表示“因为，由于”（常有较活译法），用for （1）Thank you for coming. 谢谢你来。

（2）France is famous for its wines. 法国因酒而出名。 5．当事人对某事的主观看法，“对于（某人），对…来说”，（多和形容词连用），用介词to，不用for. （1）He said that money was not important to him. 他说钱对他并不重要。（2）To her it was rather unusual. 对她来说这是相当不寻常的。（3）They are cruel to animals. 他们对动物很残忍。 6．和fit, good, bad, useful, suitable 等形容词连用，表示“适宜，适合”，用for。（1）Some training will make them fit for the job. 经过一段训练，他们会胜任这项工作的。（2）Exercises are good for health. 锻炼有益于健康。（3）Smoking and drinking are bad for health. 抽烟喝酒对健康有害。（4）You are not suited for the kind of work you are doing. 7. 表示不定式逻辑上的主语，可以用在主语、表语、状语、定语中。（1）It would be best for you to write to him. （2） The simple thing is for him to resign at once.

cad系统特殊变量

1、MBUTTONPAN 系统变量控制定点设备第三按钮或滑轮的动作响应。 0 支持菜单(.mnu) 文件定义的动作 1 当按住并拖动按钮或滑轮时，支持平移操作默认为平移操作。 IntelliMouse 或其他滑轮鼠标 IntelliMouse 是一种双按钮鼠标，在两个按钮之间有一个滑轮。左右按钮的功能和标准鼠标一样。滑轮可以转动或按下。不用任何AutoCAD 命令而直接使用滑轮就可以缩放和平移图形。默认情况下，缩放比例设为10%；每次转动滑轮都将按10% 的增量改变缩放级别。ZOOMFACTOR 系统变量控制滑轮转动（无论向前还是向后）的增量变化。其数值越大，增量变化就越大。下表列举了AutoCAD 支持的IntelliMouse 动作。 2、MINSERT 命令在矩形阵列中插入一个块的多重引用。使用MINSERT 命令插入的块不能被分解。注意：在插入过程中，不能象使用INSERT 命令那样在块名的前面用星号来分解块对象。在指定插入点位置之前，插入点处的选项将预置块的比例和旋转角。对于使用 1 和0 之外的比例因子和旋转角来拖动块，预置非常有用。

其它相关命令：INSERT、ADCENTER、REFEDIT。 3、XPLODE 命令将合成对象分解成它的部件对象。合成对象由多个（一个以上）AutoCAD 对象组成。例如，块就是一个合成对象。可以同时分解多个合成对象并分别修改每个对象的颜色、图层和线型，或者全局性的修改整个选择集。可以指定颜色、图层线宽和线型，或者从被分解的对象中继承这些属性。可以使用绝对值相等的缩放比例分解块。绝对值相等表示如果将缩放比例值前的负号(-) 删除，则比例值相等。例如，可以使用值分别为1、-1、1 的X、Y、Z 比例因子分解块，包括被镜像的块。该命令在中了CAD病毒后同样有效。其它相关命令：EXPLODE。 4、DBLCLKEDIT 命令控制双击操作 DBLCLICKEDIT 控制双击对象时是否导致对话框显示。如果双击编辑模式是打开的，将根据双击的对象类型显示一个对话框。双击大多数对象时，都将显示“特性”窗口。双击某些类型的对象时，将显示专用的编辑器，这些编辑器的功能更强大，使用更方便，也更常用。双击时显示专用编辑器的对象包括：属性：显示“编辑属性定义”对话框(DDEDIT)。块中的属性：显示“增强属性编辑器”(EATTEDIT)

英语形容词和of for 的用法

加入收藏夹主题：介词试题It’s + 形容词 + of sb. to do sth.和It’s + 形容词 + for sb. to do sth.的用法区别。内容： It's very nice___pictures for me. A.of you to draw B.for you to draw C.for you drawing C.of you drawing 提交人：杨天若时间：1/23/2008 20:5:54 主题：for 与of 的辨别内容：It's very nice___pictures for me. A.of you to draw B.for you to draw C.for you drawing C.of you drawing 答：选A 解析：该题考查的句型It’s + 形容词+ of sb. to do sth.和It’s +形容词+ for sb. to do sth.的用法区别。 “It’s + 形容词+ to do sth.”中常用of或for引出不定式的行为者，究竟用of sb.还是用for sb.，取决于前面的形容词。 1) 若形容词是描述不定式行为者的性格、品质的，如kind，good，nice，right，wrong，clever，careless，polite，foolish等，用of sb. 例： It’s very kind of you to help me. 你能帮我，真好。 It’s clever of you to work out the maths problem. 你真聪明，解出了这道数学题。 2) 若形容词仅仅是描述事物，不是对不定式行为者的品格进行评价，用for sb.，这类形容词有difficult，easy，hard，important，dangerous，（im）possible等。例： It’s very dangerous for children to cross the busy street. 对孩子们来说，穿过繁忙的街道很危险。 It’s difficult for u s to finish the work. 对我们来说，完成这项工作很困难。 for 与of 的辨别方法：用介词后面的代词作主语，用介词前边的形容词作表语，造个句子。如果道理上通顺用of，不通则用for. 如： You are nice.(通顺，所以应用of)。 He is hard.(人是困难的，不通，因此应用for.) 由此可知，该题的正确答案应该为A项。提交人：f7_liyf 时间：1/24/2008 11:18:42

的地得用法辨析

的、得、地的用法：动词前提土旁、动词后双人旁、一动不动白字旁（一）的地得，不一样，用法分别记心上，左边白，右边勺，名词跟在后面跑。美丽的花儿绽笑脸，青青的草儿弯下腰，清清的河水向东流，蓝蓝的天上白云飘，暖暖的风儿轻轻吹，绿绿的树叶把头摇，小小的鱼儿水中游，红红的太阳当空照，左边土，右边也，地字站在动词前，认真地做操不马虎，专心地上课不大意，大声地朗读不害羞，从容地走路不着急，痛快地玩耍来放松，用心地思考解难题，勤奋地学习要积极，辛勤地劳动花力气，左边两人就使得，形容词前要用得，兔子兔子跑得快，乌龟乌龟爬得慢，青青竹子长得快，参天大树长得慢，清晨锻炼起得早，加班加点睡得晚，欢乐时光过得快，考试题目出得难。（二）“的、地、得”快板的地得、的地得，用作助词都读de. 作文写话用不准，朗读往往会念错。有趣的活动、绿的树，活动是事，树是物。事物前面用的字，小朋友们都记着。认真地想、快快地跑，想跑看摸是动作。动作前面用地字，位置千万不要挪。看得清，记得准，唱得好，飞得高。动作后面用得字，补充说明要记牢。（三）“的、地、得”用法简要口诀名词前面“白勺”“的”，动词前面“土也”“地”，形容动后“双人”“得”，当作助词都读“de”。二、“的、地、得”用法小析 “的”后面跟的都是表示事物名称的词或词语，如：敬爱的总理、慈祥的老人、戴帽子的男孩、珍贵的教科书、鸟的天堂、伟大的祖国、有趣的情节、优雅的环境、可疑的情况、团结友爱的集体、他的妈妈、可爱的花儿、谁的橡皮、清清的河水...... “地”后面跟的都是表示动作的词或词语，如：高声地喊、愉快地唱、拼命地逃、疯狂地咒骂、严密地注视、一次又一次地握手、迅速地包围、沙沙地直响、斩钉截铁地说、从容不迫地申述、用力地踢、仔细地看、开心地笑笑......” “得”前面跟的多数是表示动作的词或词语，后面跟的都是形容事物状态的词或词语，表示怎么怎么样的，如：走得很快、踩得稀烂、疼得直叫唤、瘦得皮包骨头、红得发紫、气得双脚直跳、理解得十分深刻、乐得合不拢嘴、惊讶得目瞪口呆、大得很、扫得真干净、笑得多甜啊...... 三、“的、地、得”的用法补充说明：

CAD全参数及技巧

Aperture —这个变量是设置捕捉过程磁吸围大小，可设为1~50间的整数。举例来说，图面上有好几根直线，我们假设捕捉方式已经预设了中点、交点、端点，如果 aperture的值过大，那么当我们移动鼠标靠近一根直线时，捕捉框有可能同时在几个点间闪烁，不易选择；如果值过小，那么只有我们将鼠标很靠近要选择的点，才能选中，也不方便。此时我们可在命令行输入Aperture，根据提示，调整它的值（本篇所列变量，如无特殊提示，皆为此操作方式）。该变量用于图面上容较多时的捕捉选点。 Blipmode—设置每次点击鼠标左键时是否在屏幕上留下一个小十字点标记，可设为on或off。这种点标记并非真实存在，regen或者拉动一下屏幕它都会消失，对于这种标记的用途本人不是很清楚，但是我很讨厌它的存在。 Cursorsize—设置十字光标的大小，可设为1~100。对应的菜单操作为：工具à选项，显示标签组，左下角十字光标大小。调整十字光标大小的好处是它相当于提供了一把直尺用于观测对象的相对位置，判断是否对齐。个人喜欢设为100。 Dimaso—有时我们打开一个图形进行尺寸标注时，发现标注的尺寸全被打碎，就是该变量在作祟。可设置为on或off。在此建议绘图中无论如何不要打碎尺寸，打碎会带来种种不便。个人将该变量设为on（强烈建议）。 Edgemode —设置trim和extend命令是否启用延伸模式。可设为0或1。比如两条直线不相交，edge mode为0，以一条直线为边，剪切另一条，将没反应， edgemode 为1，则可剪切成功。这个变量可在执行trim或extend命令的过程中设置，如下：命令行输入trim（或extend），空格，任选一直线，空格，输入e,空格，再输入e,空格。则设为延伸模式，个人认为此模式比较好用。 Filedia—控制执行如下命令时是以对话框方式还是命令行提示方式：文件à新建，或另存为等。不用我说了，当然是对话框比较直观。 Fillmode —我们在做填充时，如果填充不上去，首先应该想到的是边界是否封闭，然后是调整填充比例，如果以上调整没用，那么多半是该变量的设置问题。可设为0和1 （这里加一句，很多变量都是可设为0或1，on或off，我们只要对某种情况的发生可能是由哪个变量引起的有个印象即可，不需记住0是什么，1是什么， cad中一试即知）。