阅读说明：本技术 一种变形监测方法及系统 (Deformation monitoring method and system ) 是由 韩军强 涂锐 卢晓春 何杨 张睿 范丽红 张鹏飞 洪菊 于 2021-10-08 设计创作，主要内容包括：本发明提供了一种变形监测方法及系统,方法包括获取待测物的监测站观测数据；监测站设置于待测物上；监测站数量为1；对监测站观测数据进行预处理,得到预处理后的监测站观测数据；基于预处理后的监测站观测数据建立法方程,利用最小二乘方法对法方程进行求解,得到待测物的形变量；根据待测物的形变量,确定待测物是否发生形变。本发明最小二乘方法对基于单个监测站观测数据建立的法方程进行求解,进而确定待测物是否形变,在减少了监测站数量的同时提高了监测的精度。(The invention provides a deformation monitoring method and a system, wherein the method comprises the steps of obtaining observation data of a monitoring station of an object to be detected; the monitoring station is arranged on the object to be detected; the number of monitoring stations is 1; preprocessing observation data of a monitoring station to obtain preprocessed observation data of the monitoring station; establishing a normal equation based on the preprocessed observation data of the monitoring station, and solving the normal equation by using a least square method to obtain the deformation quantity of the object to be detected; and determining whether the object to be detected deforms or not according to the deformation quantity of the object to be detected. The least square method solves the normal equation established based on the observation data of a single monitoring station, further determines whether the object to be detected is deformed, reduces the number of the monitoring stations and improves the monitoring precision.)

1. A method of deformation monitoring, the method comprising:

acquiring observation data of a monitoring station of an object to be detected; the monitoring station is arranged on the object to be detected; the number of the monitoring stations is 1;

preprocessing the observation data of the monitoring station to obtain preprocessed observation data of the monitoring station;

establishing a normal equation based on the preprocessed monitoring station observation data, and solving the normal equation by using a least square method to obtain the deformation quantity of the object to be detected;

and determining whether the object to be detected deforms or not according to the deformation quantity of the object to be detected.

2. The deformation monitoring method according to claim 1, wherein the preprocessing the observation data of the monitoring station to obtain the preprocessed observation data of the monitoring station specifically comprises:

decoding the observation data of the monitoring station to obtain the decoded observation data of the monitoring station;

carrying out interpolation processing on the decoded observation data of the monitoring station to obtain the observation data of the monitoring station after the interpolation processing;

judging whether abnormal data exist in the monitoring station observation data after the interpolation processing, and removing the abnormal data to obtain the monitoring station observation data after the removal processing;

and carrying out error correction processing on the monitoring station observation data after the elimination processing to obtain the monitoring station observation data of the preprocessed object to be detected.

3. The deformation monitoring method according to claim 1,

the normal equation is:

wherein: v_LRepresenting the residual vector of the phase observations, A_n×4Representing the coefficient matrix of unknown parameters, n is the number of satellites, expressing the X-direction deformation delta X coefficient of the object to be detected; k denotes the satellite number, the subscript 1 denotes the monitoring station number 1,representing the satellite-to-station distance; a coefficient of the amount of deformation in the Y direction of the object to be measured, expressing the Z-direction deformation quantity delta Z coefficient of the object to be measured; x is the number of_4×1Representing the unknown vector to be solved, x_4×1＝[δX δY δZ δT]^TDelta X, delta Y and delta Z respectively represent the deformation of the object to be measured in the X direction, the Y direction and the Z direction, and delta T represents the correction number of the receiver clock error; b is_n×nRepresenting an unknown ambiguity parameter coefficient vector; b is_n×nBiag (λ, …, λ), λ representing a wavelength; diag denotes a diagonal matrix; y is_n×1Representing the unknown ambiguity parameter vector(s), representing the ambiguity value of the whole circle from the survey station 1 to the satellite with the number k;representing a vector of phase observations; representing phase observations Represents a phase calculation value; v_PRepresenting a pseudorange observation residual vector,representing a pseudorange observation vector; a pseudo-range observation is represented,calculating a pseudo-range value; d_2n×2nRepresenting a random equation variance matrix with a matrix dimension of 2n x 2n, D_LRepresenting a variance matrix of phase observations, D_PRepresenting a pseudorange observation variance matrix.

4. The deformation monitoring method according to claim 3, wherein the determining whether the object to be measured is deformed according to the deformation amount of the object to be measured specifically comprises;

determining the three-dimensional vector distance between the object to be detected and the last observation according to the deformation quantity (delta X ) of the object to be detected;

judging whether the three-dimensional vector distance is smaller than a preset deformation threshold value or not to obtain a judgment result;

if the judgment result is yes, judging that the object to be detected is not deformed;

and if the judgment result is negative, judging that the object to be detected deforms.

5. A deformation monitoring system, the system comprising:

the monitoring station observation data acquisition module is used for acquiring monitoring station observation data of the object to be detected; the monitoring station is arranged on the object to be detected; the number of the monitoring stations is 1;

the preprocessing module is used for preprocessing the observation data of the monitoring station to obtain preprocessed observation data of the monitoring station;

the deformation quantity determining module is used for establishing a normal equation based on the preprocessed monitoring station observation data, and solving the normal equation by using a least square method to obtain the deformation quantity of the object to be detected;

and the deformation state determining module is used for determining whether the object to be detected deforms or not according to the deformation amount of the object to be detected.

6. The deformation monitoring system according to claim 5, wherein the preprocessing module specifically comprises:

the decoding unit is used for decoding the observation data of the monitoring station to obtain the decoded observation data of the monitoring station;

the interpolation processing unit is used for carrying out interpolation processing on the decoded observation data of the monitoring station to obtain the observation data of the monitoring station after the interpolation processing;

the rejecting processing unit is used for judging whether abnormal data exist in the monitoring station observation data after the interpolation processing, and rejecting the abnormal data to obtain the monitoring station observation data after the rejection processing;

and the correction processing unit is used for carrying out error correction processing on the monitoring station observation data after the elimination processing to obtain the monitoring station observation data of the preprocessed object to be detected.

7. The deformation monitoring system of claim 6,

the normal equation is:

wherein: v_LRepresenting phase observationsResidual vector, A_n×4Representing the coefficient matrix of unknown parameters, n is the number of satellites, expressing the X-direction deformation delta X coefficient of the object to be detected; k denotes the satellite number, the subscript 1 denotes the monitoring station number 1,representing the satellite-to-station distance; a coefficient of the amount of deformation in the Y direction of the object to be measured, expressing the Z-direction deformation quantity delta Z coefficient of the object to be measured; x is the number of_4×1Representing the unknown vector to be solved, x_4×1＝[δX δY δZ δT]^TDelta X, delta Y and delta Z respectively represent the deformation of the object to be measured in the X direction, the Y direction and the Z direction, and delta T represents the correction number of the receiver clock error; b is_n×nRepresenting an unknown ambiguity parameter coefficient vector; b is_n×n＝diag (λ, …, λ), λ representing a wavelength; diag denotes a diagonal matrix; y is_n×1Representing the unknown ambiguity parameter vector(s), representing the ambiguity value of the whole circle from the survey station 1 to the satellite with the number k;representing a vector of phase observations; representing phase observations Represents a phase calculation value; v_PRepresenting a pseudorange observation residual vector,representing a pseudorange observation vector; a pseudo-range observation is represented,calculating a pseudo-range value; d_2n×2nRepresenting a random equation variance matrix with a matrix dimension of 2n x 2n, D_LRepresenting a variance matrix of phase observations, D_PRepresenting a pseudorange observation variance matrix.

8. The deformation monitoring system according to claim 7, wherein the deformation state determination module specifically includes;

the three-dimensional vector distance determining unit is used for determining the three-dimensional vector distance between the object to be detected and the last observation according to the deformation quantity (delta X ) of the object to be detected;

the judging unit is used for judging whether the three-dimensional vector distance is smaller than a preset deformation threshold value or not to obtain a judging result; if the judgment result is yes, calling a first deformation state determining unit; if the judgment result is negative, calling a second deformation state determining unit;

the first deformation state determining unit is used for judging that the object to be detected is not deformed;

and the second deformation state determining unit is used for judging that the object to be detected deforms.

Technical Field

The invention relates to the technical field of deformation monitoring, in particular to a deformation monitoring method and system.

Background

Deformation hazards of dams, bridges, tailings and the like are serious, and body surface deformation is one of key judgment factors of deformation size. Conventional sensors currently available for deformation monitoring include crack gauges, displacement gauges, inclinometers, and the like. The pull rope type displacement meter is difficult to construct and high in construction cost; the inclinometer can only sense inclined deformation; with the rise of new perception technologies such as global satellite navigation technology and laser radar technology, deformation monitoring methods adopting the new perception technologies are gradually researched and applied. Laser radars are applied less at present due to high implementation difficulty and high monitoring cost. The global satellite navigation technology has the characteristics of all weather, all-time, high precision and the like. Currently, the satellite technology available for deformation monitoring is mainly real time differential positioning (RTK). The main principle of the real-time differential positioning monitoring technology is that a reference station and a monitoring station simultaneously observe the same satellite, main errors of a satellite clock, a receiver clock, an ionosphere, a troposphere and the like in an observed value are eliminated in a mode of inter-satellite difference and then inter-station difference, and deformation of the monitoring point is estimated by using a clean observed value.

Disclosure of Invention

The invention aims to provide a deformation monitoring method and system, which can monitor the deformation of a building to be monitored based on an independent monitoring station and ensure the monitoring precision.

In order to achieve the purpose, the invention provides the following scheme:

a method of deformation monitoring, comprising:

acquiring observation data of a monitoring station of an object to be detected; the monitoring station is arranged on the object to be detected; the number of the monitoring stations is 1;

preprocessing the observation data of the monitoring station to obtain preprocessed observation data of the monitoring station;

establishing a normal equation based on the preprocessed monitoring station observation data, and solving the normal equation by using a least square method to obtain the deformation quantity of the object to be detected;

and determining whether the object to be detected deforms or not according to the deformation quantity of the object to be detected.

Optionally, the monitoring station observation data is preprocessed to obtain preprocessed monitoring station observation data, and the preprocessing method specifically includes:

decoding the observation data of the monitoring station to obtain the decoded observation data of the monitoring station;

carrying out interpolation processing on the decoded observation data of the monitoring station to obtain the observation data of the monitoring station after the interpolation processing;

judging whether abnormal data exist in the monitoring station observation data after the interpolation processing, and removing the abnormal data to obtain the monitoring station observation data after the removal processing;

and carrying out error correction processing on the monitoring station observation data after the elimination processing to obtain the monitoring station observation data of the preprocessed object to be detected.

Alternatively to this, the first and second parts may,

the normal equation is:

wherein: v_LRepresenting the residual vector of the phase observations, A_n×4Representing the coefficient matrix of unknown parameters, n is the number of satellites, expressing the X-direction deformation delta X coefficient of the object to be detected; k denotes the satellite number, the subscript 1 denotes the monitoring station number 1,representing the satellite-to-station distance;(Y^k-Y₁)，k＝(1，…，n)，a coefficient of the amount of deformation in the Y direction of the object to be measured, expressing the Z-direction deformation quantity delta Z coefficient of the object to be measured; x is the number of_4×1Representing the unknown vector to be solved, x_4×1＝[δX δY δZ δT]^TDelta X, delta Y and delta Z respectively represent the deformation of the object to be measured in the X direction, the Y direction and the Z direction, and delta T represents the correction number of the receiver clock error; b is_n×nRepresenting an unknown ambiguity parameter coefficient vector; b is_n×nBiag (λ, …, λ), λ representing a wavelength; diag denotes a diagonal matrix; y is_n×1Representing the unknown ambiguity parameter vector(s), representing the ambiguity value of the whole circle from the survey station 1 to the satellite with the number k;representing a vector of phase observations; representing phase observations Represents a phase calculation value; v_PRepresenting a pseudorange observation residual vector,representing a pseudorange observation vector; a pseudo-range observation is represented,calculating a pseudo-range value; d_2n×2nRepresenting a random equation variance matrix with a matrix dimension of 2n x 2n, D_LRepresenting a variance matrix of phase observations, D_PRepresenting a pseudorange observation variance matrix.

Optionally, determining whether the object to be measured deforms according to the deformation amount of the object to be measured specifically includes;

determining the three-dimensional vector distance between the object to be detected and the last observation according to the deformation quantity (delta X ) of the object to be detected;

judging whether the three-dimensional vector distance is smaller than a preset deformation threshold value or not to obtain a judgment result;

if the judgment result is yes, judging that the object to be detected is not deformed;

and if the judgment result is negative, judging that the object to be detected deforms.

A deformation monitoring system comprising:

the monitoring station observation data acquisition module is used for acquiring monitoring station observation data of the object to be detected; the monitoring station is arranged on the object to be detected; the number of the monitoring stations is 1;

the preprocessing module is used for preprocessing the observation data of the monitoring station to obtain preprocessed observation data of the monitoring station;

the deformation quantity determining module is used for establishing a normal equation based on the preprocessed monitoring station observation data, and solving the normal equation by using a least square method to obtain the deformation quantity of the object to be detected;

and the deformation state determining module is used for determining whether the object to be detected deforms or not according to the deformation amount of the object to be detected.

Optionally, the preprocessing module specifically includes:

the decoding unit is used for decoding the observation data of the monitoring station to obtain the decoded observation data of the monitoring station;

the interpolation processing unit is used for carrying out interpolation processing on the decoded observation data of the monitoring station to obtain the observation data of the monitoring station after the interpolation processing;

the rejecting processing unit is used for judging whether abnormal data exist in the monitoring station observation data after the interpolation processing, and rejecting the abnormal data to obtain the monitoring station observation data after the rejection processing;

and the correction processing unit is used for carrying out error correction processing on the monitoring station observation data after the elimination processing to obtain the monitoring station observation data of the preprocessed object to be detected.

Alternatively to this, the first and second parts may,

the normal equation is:

wherein: v_LRepresenting the residual vector of the phase observations, A_n×4Representing the coefficient matrix of unknown parameters, n is the number of satellites, expressing the X-direction deformation delta X coefficient of the object to be detected; k denotes the satellite number, the subscript 1 denotes the monitoring station number 1,representing the satellite-to-station distance; a coefficient of the amount of deformation in the Y direction of the object to be measured, expressing the Z-direction deformation quantity delta Z coefficient of the object to be measured; x is the number of_4×1Representing the unknown vector to be solved, x_4×1＝[δX δY δZ δT]^TDelta X, delta Y and delta Z respectively represent the deformation of the object to be measured in the X direction, the Y direction and the Z direction, and delta T represents the correction number of the receiver clock error; b is_n×nRepresenting an unknown ambiguity parameter coefficient vector; b is_n×nBiag (λ, …, λ), λ representing a wavelength; diag denotes a diagonal matrix; y is_n×1Representing the unknown ambiguity parameter vector(s), representing the ambiguity value of the whole circle from the survey station 1 to the satellite with the number k;representing a vector of phase observations; representing phase observations Represents a phase calculation value; v_PRepresenting a pseudorange observation residual vector,representing a pseudorange observation vector; a pseudo-range observation is represented,calculating a pseudo-range value; d_2n×2nRepresenting a random equation variance matrix with a matrix dimension of 2n x 2n, D_LRepresenting a variance matrix of phase observations, D_PRepresenting a pseudorange observation variance matrix.

Optionally, the deformation state determining module specifically includes;

the three-dimensional vector distance determining unit is used for determining the three-dimensional vector distance between the object to be detected and the last observation according to the deformation quantity (delta X ) of the object to be detected;

the judging unit is used for judging whether the three-dimensional vector distance is smaller than a preset deformation threshold value or not to obtain a judging result; if the judgment result is yes, calling a first deformation state determining unit; if the judgment result is negative, calling a second deformation state determining unit;

the first deformation state determining unit is used for judging that the object to be detected is not deformed;

and the second deformation state determining unit is used for judging that the object to be detected deforms.

According to the specific embodiment provided by the invention, the invention discloses the following technical effects:

the invention provides a deformation monitoring method and a system, wherein the method comprises the steps of obtaining observation data of a monitoring station of an object to be detected; the monitoring station is arranged on the object to be detected; the number of monitoring stations is 1; preprocessing observation data of a monitoring station to obtain preprocessed observation data of the monitoring station; establishing a normal equation based on the preprocessed observation data of the monitoring station, and solving the normal equation by using a least square method to obtain the deformation quantity of the object to be detected; and determining whether the object to be detected deforms or not according to the deformation quantity of the object to be detected. The least square method solves the normal equation established based on the observation data of a single monitoring station, further determines whether the object to be detected is deformed, reduces the number of the monitoring stations and improves the monitoring precision.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.

FIG. 1 is a flow chart of a deformation monitoring method according to an embodiment of the present invention;

FIG. 2 is a flow chart of a method for monitoring high-precision positioning deformation based on a Precision Point Positioning (PPP) technique according to an embodiment of the present invention;

fig. 3 is a schematic structural diagram of a deformation monitoring system according to an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The invention aims to provide a deformation monitoring method and system, which can monitor the deformation of a building to be monitored based on an independent monitoring station and ensure the monitoring precision.

In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.

Fig. 1 is a flowchart of a deformation monitoring method in an embodiment of the present invention, and as shown in fig. 1, the present invention provides a deformation monitoring method, including:

step 101: acquiring observation data of a monitoring station of an object to be detected; the monitoring station is arranged on the object to be detected; the number of monitoring stations is 1;

step 102: preprocessing observation data of a monitoring station to obtain preprocessed observation data of the monitoring station;

step 103: establishing a normal equation based on the preprocessed observation data of the monitoring station, and solving the normal equation by using a least square method to obtain the deformation quantity of the object to be detected;

step 104: and determining whether the object to be detected deforms or not according to the deformation quantity of the object to be detected.

Step 102, specifically comprising:

decoding the observation data of the monitoring station to obtain the decoded observation data of the monitoring station;

carrying out interpolation processing on the decoded observation data of the monitoring station to obtain the observation data of the monitoring station after the interpolation processing;

judging whether abnormal data exist in the monitoring station observation data after interpolation processing, and removing the abnormal data to obtain the monitoring station observation data after removal processing;

and performing error correction processing on the monitoring station observation data after the elimination processing to obtain the monitoring station observation data of the object to be detected after the pretreatment.

In particular, the method comprises the following steps of,

the normal equation is:

wherein: v_LRepresenting the residual vector of the phase observations, A_n×4Representing the coefficient matrix of unknown parameters, n is the number of satellites, expressing the X-direction deformation delta X coefficient of the object to be detected; k denotes the satellite number, the subscript 1 denotes the monitoring station number 1,representing the satellite-to-station distance; a coefficient of the amount of deformation in the Y direction of the object to be measured, expressing the Z-direction deformation quantity delta Z coefficient of the object to be measured; x is the number of_4×1Representing the unknown vector to be solved, x_4×1＝[δX δY δZ δT]^TDelta X, delta Y and delta Z respectively represent the deformation of the object to be measured in the X direction, the Y direction and the Z direction, and delta T represents the correction number of the receiver clock error; b is_n×nRepresenting an unknown ambiguity parameter coefficient vector; b is_n×nBiag (λ, …, λ), λ representing a wavelength; diag denotes a diagonal matrix; y is_n×1Representing the unknown ambiguity parameter vector(s), representing the ambiguity value of the whole circle from the survey station 1 to the satellite with the number k;representing a vector of phase observations; representing phase observations Represents a phase calculation value; v_PRepresenting a pseudorange observation residual vector,representing a pseudorange observation vector; a pseudo-range observation is represented,calculating a pseudo-range value; d_2n×2nRepresenting a random equation variance matrix with a matrix dimension of 2n x 2n, D_LRepresenting a variance matrix of phase observations, D_PRepresenting a pseudorange observation variance matrix.

Step 104, specifically comprising;

determining the three-dimensional vector distance between the object to be detected and the last observation according to the deformation quantity (delta X ) of the object to be detected;

judging whether the three-dimensional vector distance is smaller than a preset deformation threshold value or not to obtain a judgment result;

if the judgment result is yes, judging that the object to be detected is not deformed;

if the judgment result is no, the deformation of the object to be detected is judged.

Specifically, aiming at a high-precision positioning deformation monitoring method and system based on PPP technology, the method is realized by the contents of RTCM data of a real-time monitoring station, broadcast ephemeris, a precision orbit, precision clock error, earth rotation parameters and the like; the system implementation comprises modules of real-time data decoding, observed value error correction, monitoring station position estimation, result verification and the like, so that the centimeter-level or even millimeter-level precision of a monitoring point is obtained. In order to minimize power consumption of the terminal, the sampling interval of the terminal is generally set to 15 seconds or 30 seconds. The specific implementation flow is shown in fig. 2.

The first step is as follows: receiving real-time stream data of observation from an independent monitoring station of a deformation carrier and real-time stream products such as orbit, clock, earth rotation parameters and the like from a local server resolving center (the data is satellite-related real-time information already possessed by a resolving platform), and decoding according to an international RTCM-SC104 standard data protocol;

the second step is that: the integrity of the observed data is checked by adopting the existing method, the original observed value is subjected to gross error identification and elimination by adopting the existing cycle slip and clock slip detection method, and errors such as orbit, clock, ionosphere, troposphere, earth rotation parameters and the like in the observed value are corrected to obtain clean observed data;

in the formula (I), the compound is shown in the specification,andrespectively representing a phase observed value and a pseudo-range observed value of a satellite k observed at a receiving moment t of a receiver i; ρ represents the distance between the satellite and the station, since a separate monitoring station is used, i is 1;andrespectively representing atmospheric-related ionospheric and tropospheric delay errors experienced by the signal as it propagates from satellite k to receiver i; d_erpRepresenting earth rotation errors; λ refers to the carrier wavelength;represents the unknown integer ambiguity between the carrier phase from satellite k to receiver i;andrespectively representing the carrier phase noise error and the pseudorange measurement residual between the satellite k and the receiver i. Sigma²Indicating the precision factor, E the satellite altitude, and sin the sine function.

The third step: establishing a normal equation by using the clean data acquired in the last step, and estimating the position of the monitoring station by using a least square method;

V_L＝Ax+By-l_L， (2.5)

V_P＝Ax+By-l_P， (2.6)

D_2n×2n＝diag(D_L，D_P)， (2.7)

in the formula, V_LRepresenting the residual vector of the phase observation, V_PRepresenting pseudorange observations residual vectors, D representing a random equation variance matrix, D_LRepresenting a variance matrix of phase observations, D_PRepresents the pseudorange observations variance matrix, and 2n × 2n represents the matrix dimensions.

A_n×4Representing an unknown parameter coefficient matrix, and n multiplied by 4 represents n rows and 4 columns; represents the unknown parameter deltaX coefficient;representing the coefficient of the unknown parameter deltay,representing the unknown parameter δ Z coefficient; wherein the upper right corner mark k represents the satellite number, and the lower right corner mark represents the monitoring station number 1;

x_4×1＝[δX δY δZ δT]^Tx represents the vector to be solved of the unknown number, δ X, δ Y, δ Z represent the three-dimensional position correction number of the receiver respectively, δ T represents the clock error correction number of the receiver,

B_n×nb denotes an unknown ambiguity parameter coefficient vector, λ denotes wavelength; diag denotes a diagonal matrix;

y denotes the unknown ambiguity parameter vector,representing the ambiguity value of the whole circle from the observation station 1 to the satellite with the number of 1, and so on;

l_La vector of phase observations is represented,representing phase observationsSubtracting the phase calculation value;

l_Pa vector of pseudorange observations is represented,representing pseudorange observationsSubtracting the pseudo-range calculated value;

a vector of calculated values of the phase is represented,

a vector of calculated values of the pseudoranges is represented,

the distance between the satellite and the station is shown,

n represents the number of observations, X, Y, Z represent the three-dimensional coordinates of CGCS2000 in the earth-fixed coordinate system, X^k、Y^kAnd Z^kRefers to the antenna three-dimensional position of satellite k; x₁、Y₁And Z₁Indicating a three-dimensional position parameter of a receiver of a monitoring station; diag denotes a diagonal matrix.The estimated model matrix form of the parameters can be expressed as:

in the formula

Representing the phase observation equation to a weight matrix,

representing the pseudorange observation equations with a weight matrix,

the position parameters can be obtained by the conventional least square method (note that (X, Y, Z) can be (0, 0, 0) in the initial epoch solution).

(X_i，Y_i，Z_i)＝(X_i-1，Y_i-1，Z_i-1)+(δX_i，δY_i，δZ_i)

The fourth step: and (5) correcting and outputting the monitoring result estimated in the last step. The validation rules are as follows:

|(δX_i，δY_i，δZ_i)|＜0.001m

namely, if the three-dimensional vector distance of the two operations is less than 0.001m, the result is considered to be qualified, otherwise, the result is unqualified, and the next operation is carried out.

The fifth step: analysis of the results of solution (X)_i，Y_i，Z_i) And judging the deformation of the deformation body along with the change of time.

Fig. 3 is a schematic structural diagram of a deformation monitoring system according to an embodiment of the present invention, and as shown in fig. 3, the present invention further provides a deformation monitoring system, including:

the monitoring station observation data acquisition module 301 is used for acquiring monitoring station observation data of an object to be detected; the monitoring station is arranged on the object to be detected; the number of monitoring stations is 1;

the preprocessing module 302 is configured to preprocess observation data of the monitoring station to obtain preprocessed observation data of the monitoring station;

the deformation quantity determining module 303 is used for establishing a normal equation based on the preprocessed monitoring station observation data, and solving the normal equation by using a least square method to obtain the deformation quantity of the object to be detected;

and a deformation state determining module 304, configured to determine whether the object to be measured deforms according to the deformation amount of the object to be measured.

Wherein, the preprocessing module specifically includes:

the decoding unit is used for decoding the observation data of the monitoring station to obtain the decoded observation data of the monitoring station;

the interpolation processing unit is used for carrying out interpolation processing on the decoded observation data of the monitoring station to obtain the observation data of the monitoring station after the interpolation processing;

the rejecting processing unit is used for judging whether abnormal data exist in the monitoring station observation data after interpolation processing, and rejecting the abnormal data to obtain the monitoring station observation data after rejection processing;

and the correction processing unit is used for carrying out error correction processing on the monitoring station observation data after the elimination processing to obtain the monitoring station observation data of the object to be detected after the pretreatment.

In particular, the method comprises the following steps of,

the normal equation is:

wherein: v_LRepresenting the residual vector of the phase observations, A_n×4Representing the coefficient matrix of unknown parameters, n is the number of satellites, expressing the X-direction deformation delta X coefficient of the object to be detected; k denotes the satellite number, the subscript 1 denotes the monitoring station number 1,representing the satellite-to-station distance; a coefficient of the amount of deformation in the Y direction of the object to be measured, expressing the Z-direction deformation quantity delta Z coefficient of the object to be measured; x is the number of_4×1Representing the unknown vector to be solved, x_4×1＝[δX δY δZ δT]^TDelta X, delta Y and delta Z respectively represent the deformation of the object to be measured in the X direction, the Y direction and the Z direction, and delta T represents the correction number of the receiver clock error; b is_n×nRepresenting an unknown ambiguity parameter coefficient vector; b is_n×nBiag (λ, …, λ), λ representing a wavelength; diag denotes a diagonal matrix; y is_n×1Representing the unknown ambiguity parameter vector(s), representing the ambiguity value of the whole circle from the survey station 1 to the satellite with the number k;representing a vector of phase observations; representing phase observations Represents a phase calculation value; v_PRepresenting a pseudorange observation residual vector,representing a pseudorange observation vector; a pseudo-range observation is represented,calculating a pseudo-range value; d_2n×2nRepresenting a random equation variance matrix with a matrix dimension of 2n x 2n, D_LRepresenting a variance matrix of phase observations, D_PRepresenting a pseudorange observation variance matrix.

Preferably, the deformation state determination module specifically includes;

the three-dimensional vector distance determining unit is used for determining the three-dimensional vector distance between the object to be detected and the last observation according to the deformation quantity (delta X ) of the object to be detected;

the judging unit is used for judging whether the three-dimensional vector distance is smaller than a preset deformation threshold value or not to obtain a judging result; if the judgment result is yes, calling a first deformation state determining unit; if the judgment result is negative, calling a second deformation state determining unit;

the first deformation state determining unit is used for judging that the object to be detected is not deformed;

and the second deformation state determining unit is used for judging that the object to be detected deforms.

The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.

The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.