畢業(yè)論文英語(yǔ)翻譯及原文

1、A RESEARCH ON DATA PROCESSING MODEL OF GPS DAMDEFORMATION MONITORING NETWORKAbstract: Considering the particularity of the GPS dam deformation monitoring network, a data processing model based on the station orthogonal coordinate system for three-dimension GPS dam deformation monitoring network, was

2、 put forward. Also, a mathematical model of using the clustering analysis method in fuzzy mathematics to test the relative stability of quasi-stable points(or datum marks) was successfully brought forward. The adjustment method during the course of data processing was quasi-stable adjustment. At las

3、t, a software system of three-dimension GPS dam deformation monitoring network was designed and opened up with the help of Visual Basic Language. With three periods observation data from the GPS deformation monitoring network of a dam, an adjustment calculation was done by the software.The calculati

4、on result shows that the mathematical models can be more suitable for the data processing in GPS dam deformation monitoring network.Key words: GPS, Dam deformation monitoring, Quasi-stable adjustment, Clustering analysis1.IntroductionWGS-84 coordinate system is generally used in GPS. But local or in

5、dependent coordinate systems are usually chosen in dam deformation monitoring networks for their small areas. During the course of past data processing, the adjustment under WGS-84 coordinate system for independent networks or networks with several fixed points is often firstly made. Then, the trans

6、formation from WGS-84 coordinate system to local(or independent) coordinate systems is done. For GPS deformation monitoring networks with repetitive observation data, the obvious change of datum marks coordinates under the two different coordinate systems can be brought by the tiny deformation of da

7、tum marks among different periods of observation. And the greater error can be made during the coordinate transformation. If a local Gauss coordinate system is chosen, the projection distortions can also be produced by the transformation itself. For the reasons above, the station orthogonal coordina

8、te system is chosen as the reference coordinate system for data processing of GPS dam deformation networks. And the mathematical model is put forward and deduced.2.Data processing model based on the station orthogonal coordinate system for three-dimension GPS deformation monitoring networks2.1 Coord

9、inate systemThe station orthogonal coordinate system is a left-hand coordinate system. Its origin is set at one of the GPS monitoring points. The E(X) axis points at the meridian passing the origin. It is on the tangent plane of the origin. And the right north is taken as forward direction. The H(Z)

10、 axis is on the normal line of WGS-84 ellipsoid at the point and takes outward as forward direction . The E(Y) axis is also on the tangent plane of the origin and uses east for forward direction.If the position vector of the station orthogonal coordinate system origin P0 in WGS-84 is expressed as= ,

11、 according to the geodetic latitude and longitude （，）, the position vector in the station orthogonal coordinate system origin of a random point can be got through the translation and rotation of its WGS-84 position vector =H（-）（1）In the above equation, H can be written asH=（2） If the baseline vector

12、s of the two random pointsand in WGS-84 coordinate system and the the station orthogonal coordinate system are written asrespectively, the expression can be easily gained as followsThen, the relation equation between the two baseline vectors is expressed asThere are two steps in the GPS observation

13、data processing course. They are baseline calculation and network adjustment. The baseline vectors in WGS-84 can be firstly got using baseline calculation. Secondly, the baseline vector transformation from WGS-84 to the station orthogonal coordinate system can be done with (3). At last, the adjustme

14、nt of GPS deformation monitoring networks in the station orthogonal coordinate system can be successfully finished.2.2 Adjustment method and mathematical modelDeformation monitoring networks usually require higher precision. And if several fixed points are adopted for datum, the observation precisio

15、n can be greatly reduced, because the known datas precision is often lower than the required precision and the beginning points displacement can make annexe effect to observation data especially during the course of repetitive observation. So the classical adjustment method, which has some given poi

16、nts, is generally not used. But it is important to choose the reference points with stable physical status as datum of deformation monitoring networks. Considering the above two cases, the quasi-stable adjustment can be employed to make the more stable unknown data( the coordinates of relatively sta

17、ble points away from the dam) match their stable values. Then, there are no distortion of surveying result and relatively stable datum. And the goal to monitor the deformation can be reached well. The adjustment model of GPS rank-deficient networks can be written asWith the least square method, the

18、normal equation is expressed asNX=W （5）where N equals PA and W equals PLAnd the equation can be got as followsR(N)=R(A)=rwhere A denotes the rank-deficient matrix，whose rank-deficient number d is (n-r).If S is a set of radical of zero space N(A) and R(S) denotes d, the equation is written asAS=0 （6）

19、When the inner product space is defined as (X,Y)=RY and R(R) d, under the constraint condition RX=min, the following equation can be gotRX=0 (7)With (5) and (7), the solution equation of weighting rank-deficient networks can be expressed asWhere denotes. When R is a diagonal matrix and its value is

20、1 or 0, （8）canbecome the model of quasi-stable adjustment. The S matrix can be given according to the condition AS=0. And the S matrix of GPS 3-dimensional deformation monitoring networks is written as2.3 Mathematical model of calculating quasi-stable points relative stability with clustering analys

21、is For GPS dam deformation monitoring networks, the stability of datum marks must be firstly tested in the observation data processing. Though the relatively stable area is chosen for building datum marks when GPS dam deformation monitoring networks are designed, the deformation of datum marks can c

22、ome into being. Even if the quasi-stable adjustment method is used, the stability test needs to be made, too. The quasi-stable points(quasi-stable points or datum marks in design scheme) with marked deformation should be eliminated. The mathematical model of calculating quasi-stable points(or datum

23、marks) relative stability with clustering analysis in fuzzy mathematics is put forward to ensure the stable quasi-stable points(or datum marks) in GPS observation data processing. One characteristic of quasi-stable adjustment is that the correction value V of observation dataafter adjustment is inva

24、riable. So the adjusted value L of observation data is also invariable. And it is shown that the network shape after adjustment is unchanged. The observation data of GPS networks adjustment is baseline vectors(coordinate differences in 3 coordinate axis directions). Then, after the quasi-stable adju

25、stment of two periods of observation data, the differences of coordinate differences of two random quasi-stable points in 3 coordinate axis directions between the two periods are invariable. So, these values cant be changed with different choices. And work can be finished once for ado to avoid the t

26、rouble of some methods calculating step by step. and denote the coordinate differences of two random quasi-stable points (i and j) after two periods observation data adjustment. is the difference of coordinate differences betweentwo periods. And equations are as followsStatistic is written asIf the

27、change of between two periods is caused by the accidental error of GPS observation, it is expressed asThe fuzzy membership grade of the relative stability of the two random quasi-stable points (i and j) is defined asThat is to say, the fuzzy relation of the relative stability of quasi-stable points

28、is the probability densityvalue of standard normal distribution about.To , it can be defined as =0 for supplement. It is also as followsAnd the fuzzy relation of relative stability of quasi-stable points defined by (12) and (13) only satisfiesthe symmetry of equivalence fuzzy relation. The reflexivi

29、ty can be standardized. And ,is re-defined asThe fuzzy relation R has met the first two conditions of fuzzy equivalence relation. Then R is a fuzzy similar matrix. To transitivity, the fuzzy similar matrix can be changed to a fuzzy equivalence matrix with the help of the transitive closed package t(

30、R). And the fuzzy analysis can be done.The sorted index parameter of clustering analysis is computed with the statistic hypothesis method.If the change of between two periods is caused by the accidental error of GPS observation, it is expressed asFor the given conspicuous level , there is a critical

31、 value. With, the corresponding value can be got from (14). And is the sorted index parameter of clustering analysis of quasi-stable points relative stability. Tab.1 below shows the values of and .Obviously should be changed in the practice. It is concluded that a larger should be chosen according t

32、o the operation rule in clustering analysis. And it can be recommended that and should use 5 %and 0 .1465respectively. 3.A computation example and result analysis The computation example was chosen from the GPS deformation monitoring network of some rock and soil gravity dam. There were 3 periods of

33、 observation data in total. The observation dates were Mar.4 to 7, Jun. 4 to 11, and Aug.31 to Sept.4 in 2001. There were 75 GPS monitoring points in this network. And 6 of the total were in the relatively stable area of the lower river of the dam. The other 69 points were at the dam body. All the m

34、onitoring points were built on observation piers and had compulsive centering equipment. And all the observation was finished by 6 Ashtech Z-Surveyor dual-frequency receivers. The periods of all the points were more than an hour. The baseline solution of GPS observation data was gained by the Ashtec

35、h associated software Solution 2.5. For every period, everyday observation data was processed singly. The periods of timewith bad signals were first eliminated. If they were still not eligible, the observation data was deleted. Then, with everyday qualified baselines, the network adjustment was prep

36、ared. The baseline solutionprecision is listed in Tab.1.6 monitoring points in the relatively stable area of dam lower river banks were used as fixed initial datum. And the adjustment with fixed points was done. With the adjustment result being analyzed, it was shown that the displacement among 6 in

37、itial points could reach about 23mm. Andthe monitoring points precision after the adjustment with 6 fixed points was 12 times larger than the precision using quasi-stable adjustment. The result also explained the displacement of initial points. Because fixed initial datum could react on observation

38、data for compulsive fixing, the precision was bad. In order to test the stability of quasi-stable points, the mathematical model of clustering analysis method was employed. It was found that the quasi-stable point KL3 in Y direction was obviouslydifferent from the other 5 points when the second peri

39、od of observation was compared with the first.And KL3 in Y and Z directions was distinctly different from the others when the third was compared with the first. Then, KL3 was eliminated after integrating the clustering analysis result of the second and the third periods. At last, KL1、KL2、KL7、KR1 and KR3 were taken as quasi-stable points. Because there was no quasi-stable adjustment function in GPS associated software of GPS manufacturers at home or in foreign countries, the network adjustment software was designed for GPS deformation monitoring ne