Method and device for refining quasi-geoid in strip area, electronic equipment, and medium

Abstract

The present disclosure relates to the field of strip-area elevation measurement for line engineering projects, and provides a strip-area quasi-geoid refinement method and device, electronic equipment, and medium. The method comprises: determining actual elevation anomalies of a plurality of measurement control points on the pipeline line centerline; determining model elevation anomalies of each measurement control point using the EGM2008 gravity field model, and then determining elevation anomaly differences of each measurement control point; determining elevation anomaly differences of a plurality of interpolated points of each measurement control point on the line centerline; determining elevation anomaly differences of a plurality of external measurement points on both sides of the line centerline; determining refined elevation anomalies of each measurement control point, interpolated point, and external measurement point; generating elevation anomaly grid data of the target strip-area, and then generating a quasi-geoid model. The method solves the problems of high cost, high difficulty, long cycle time, low accuracy, and poor consistency of results of traditional elevation measurement methods.

Description

Technical Field

[0001] The present disclosure relates to the technical field of strip area elevation measurement in line engineering, and in particular to a strip area quasi-geoid refinement method and device, electronic equipment, and medium. Background Art

[0002] Long-distance pipeline projects are long and span vast distances, often exceeding thousands of kilometers in length, yet typically require a short construction period. Completing elevation control surveys within this timeframe requires not only sufficient human and equipment resources but also the use of elevation measurement methods and technologies tailored to the specific characteristics of long-distance pipeline projects.

[0003] Currently, Global Navigation Satellite System (GNSS) positioning measurement methods are widely used. The establishment of the Continuously Operating Reference Stations (CORS) network, in particular, has made it very easy to obtain accurate geodetic heights. Therefore, if a high-precision quasi-geoid model of the long-distance pipeline survey area can be obtained, the normal height of the pipeline's target point can be directly calculated.

[0004] Among existing methods for measuring long-distance oil and gas pipelines, elevation control measurements are typically completed using methods such as GNSS elevation fitting, total station triangulation, and GNSS real-time kinematic (RTK) elevation measurement. Elevation control networks are typically implemented according to the principle of hierarchical layout and step-by-step control. Before conducting topographic map surveys, elevation control points that meet accuracy requirements must be laid out in advance. To ensure accuracy, both GNSS elevation fitting and total station triangulation require stringent requirements for the number and distribution of elevation control points. Total station triangulation also requires the use of opposite-direction observations, which is time-consuming and labor-intensive. In hilly and mountainous areas, when the number of known elevation control points is insufficient or poorly distributed, leveling is required to transfer elevations, making the entire elevation measurement process even more difficult.

[0005] In general, the existing long-distance pipeline measurement methods have the following disadvantages in elevation measurement:

[0006] 1. Poor consistency of results: In line projects, control and other important units are generally measured in advance. The elevation control points arranged at different times may have systematic inconsistencies in their elevations, resulting in inconsistent elevations on later drawings, which has a significant impact on design and construction.

[0007] 2. Low efficiency: When conducting leveling or trigonometric height measurement in mountainous areas, the operation is difficult and time-consuming, resulting in long construction period and low efficiency.

[0008] 3. High cost: The density of traditional elevation control points is generally 5km / pair, and the layout density is high. The burial and measurement of on-site benchmark points require a lot of material, manpower and other related resource costs.

[0009] 4. Low accuracy: When using the GNSS height fitting measurement method, it is necessary to perform height fitting on the obtained geodetic height. If the selected fitting points and fitting methods are inappropriate, the fitting accuracy will be greatly reduced, making it difficult to meet relevant specifications.

[0010] 5. Difficulty in Maintenance: Traditional elevation measurement methods rely on on-site elevation control benchmarks. The design and construction cycle for long-distance pipelines is relatively long, often lasting several years. Furthermore, these on-site buried elevation control benchmarks are easily damaged by economic development activities and other construction activities. During use, damaged elevation control benchmarks must be re-buried and re-measured, making maintenance extremely difficult. Summary of the Invention

[0011] The present disclosure aims to solve at least one of the problems existing in the prior art and provides a method and device, electronic equipment, and medium for refining a quasi-geoid in a strip area.

[0012] One aspect of the present disclosure provides a method for refining a quasi-geoid in a strip region, the method comprising:

[0013] Selecting a number of measurement control points along the pipeline centerline and determining the actual elevation anomaly value of each measurement control point; wherein each measurement control point is evenly distributed along the pipeline centerline and conforms to the topographic change trend of the pipeline centerline;

[0014] Using the EGM2008 gravity field model, the model elevation anomaly value of each of the measurement control points is determined;

[0015] Determining the elevation anomaly difference corresponding to each of the measurement control points according to the actual elevation anomaly value and the model elevation anomaly value;

[0016] According to the terrain change trend, a plurality of interpolation points of each of the measurement control points are selected from the center line of the line at a first preset distance, and the elevation anomaly difference corresponding to each of the interpolation points is determined;

[0017] Selecting a plurality of external measurement points within a second preset distance on both sides of the line centerline, and determining the elevation anomaly difference corresponding to each of the external measurement points;

[0018] Using the EGM2008 gravity field model, determining the model elevation anomaly values corresponding to each of the interpolation points and each of the external measurement points;

[0019] Adding the elevation anomaly differences corresponding to each of the survey control points, each of the interpolation points, and each of the external survey points to the corresponding model elevation anomaly values to obtain the refined elevation anomaly values corresponding to each of the survey control points, each of the interpolation points, and each of the external survey points;

[0020] Generating elevation outlier grid data of the target strip area where the line centerline is located according to the refined elevation outlier values;

[0021] A quasi-geoid model of the target strip area is generated based on the elevation outlier grid data.

[0022] Optionally, respectively determining the actual elevation anomaly value of each of the measurement control points includes:

[0023] Obtaining the geodetic height and normal height of each of the measurement control points;

[0024] The actual elevation anomaly value of each measurement control point is obtained by subtracting its normal height from its geoid height.

[0025] Optionally, determining the elevation anomaly difference corresponding to each of the interpolation points includes:

[0026] The quadratic polynomial moving curve fitting algorithm and the least squares algorithm are adopted to fit the elevation anomaly differences corresponding to the interpolation points using the elevation anomaly differences corresponding to the measurement control points.

[0027] Optionally, the adopting of a quadratic polynomial moving curve fitting algorithm and a least squares algorithm to fit the elevation anomaly differences corresponding to the interpolation points using the elevation anomaly differences corresponding to the measurement control points includes:

[0028] Select several measurement control points from the upstream and downstream of each interpolation point as the reference points corresponding to each interpolation point, and calculate the mileage difference between each interpolation point and its corresponding reference points according to the following formula:

[0029] ;

[0030] in, represents the mileage difference between the interpolated point p and its corresponding i-th benchmark point; represents the mileage of the interpolation point p; represents the mileage of the i-th benchmark point corresponding to the interpolation point p; i represents the benchmark point number and i=1,2,…,t; t represents the total number of benchmark points corresponding to the interpolation point p;

[0031] A fitting curve is determined and expressed as:

[0032] ;

[0033] in, represents the elevation anomaly difference matrix and , They represent the elevation anomaly differences of the 1st, 2nd, …, tth benchmark points corresponding to the interpolation point p respectively; represents the mileage difference matrix and , They represent the mileage difference between the interpolation point p and its corresponding 1st, 2nd, ..., tth benchmark points respectively; 、 、 Represent the first coefficient, the second coefficient, and the third coefficient respectively;

[0034] The weights of the reference points corresponding to the interpolation points are calculated according to the following formula:

[0035] ;

[0036] in, represents the weight of the i-th reference point corresponding to the interpolation point p; represents the natural logarithm; represents a constant;

[0037] Let the coefficient matrix , solve the coefficient matrix according to the following formula :

[0038] ;

[0039] in, represents the parameter matrix and , represents the weight matrix and ;

[0040] make , and compare it with the solved 、 、 Substitute into the fitting curve , get the elevation anomaly difference corresponding to the interpolation point p ;in, Represents the mileage difference between the interpolated point p and itself.

[0041] Optionally, determining the elevation anomaly differences corresponding to the external measurement points includes:

[0042] Projecting each of the external measurement points onto the center line of the line to obtain corresponding projection points;

[0043] The elevation anomaly difference corresponding to each of the projection points is used as the elevation anomaly difference corresponding to the external measurement point corresponding to each of the projection points.

[0044] Optionally, generating elevation outlier value grid data of a target strip area where the line centerline is located based on the refined elevation outlier value includes:

[0045] Gridding the target strip area according to a preset grid point interval;

[0046] Determine a minimum rectangle covering the target strip area, and obtain a grid range corresponding to the target strip area; wherein the longitude and latitude corresponding to each side of the minimum rectangle meet a preset accuracy requirement;

[0047] Within the grid range, the coordinates of each grid point are calculated in sequence, and the refined elevation anomaly value corresponding to each grid point is determined to obtain the elevation anomaly value grid data.

[0048] Optionally, after determining the elevation anomaly differences corresponding to the respective measurement control points based on the actual elevation anomaly values and the model elevation anomaly values, the method further comprises:

[0049] Select N consecutively arranged measurement control points as a control point group, fit them with a quadratic polynomial, and obtain the corresponding expression: ;

[0050] in, Indicates the elevation anomaly difference of the measurement control point. Indicates the mileage difference between the measurement control point and the measurement reference point on the center line of the line, 、 、 are the coefficients of the quadratic polynomial to be solved;

[0051] Solving the coefficients of a quadratic polynomial using the least squares method 、 、 And the residuals of the selected N measurement control points are used to calculate the residual sum of squares of the control point group according to the following formula:

[0052] ;

[0053] in, represents the residual sum of squares of the control point group, represents the number of the survey control point in the control point group and , Indicates the number of the measurement control point, Indicates the The elevation anomaly of the survey control points is different. Indicates the The mileage difference between a measurement control point and the measurement reference point;

[0054] Updating step: removing the measured control point arranged at the front from the current control point group, and adding the next measured control point arranged at the back of the current control point group to the control point group to obtain a new control point group, and calculating the residual sum of squares of the new control point group;

[0055] Using the new control point group as the current control point group, and repeating the updating step until no more measured control points are added to the control point group;

[0056] If the sum of squares of the residuals of all the control point groups where a certain survey control point is located is higher than the target multiple of the standard deviation of the elevation anomaly differences of all the survey control points, the survey control point will be eliminated.

[0057] Another aspect of the present disclosure provides a device for refining a quasi-geoid in a strip region, the device comprising:

[0058] A first determination module is configured to select a plurality of measurement control points from the pipeline centerline and determine the actual elevation anomaly value of each of the measurement control points; wherein the measurement control points are evenly distributed along the pipeline centerline and conform to the topographic change trend of the pipeline centerline;

[0059] The second determination module is used to determine the model elevation anomaly value of each of the measurement control points using the EGM2008 gravity field model;

[0060] A third determining module is used to determine the elevation anomaly difference corresponding to each of the measurement control points according to the actual elevation anomaly value and the model elevation anomaly value;

[0061] A fourth determination module is configured to select, based on the terrain change trend and at a first preset distance, a plurality of interpolation points of each of the measurement control points from the center line of the line, and determine an elevation anomaly difference corresponding to each of the interpolation points;

[0062] a fifth determining module, configured to select a plurality of external measurement points within a second preset distance from both sides of the line centerline, and determine an elevation anomaly difference corresponding to each of the external measurement points;

[0063] a sixth determination module, configured to determine the model elevation anomaly values corresponding to each of the interpolation points and each of the external measurement points, respectively, using the EGM2008 gravity field model;

[0064] A refinement module is used to add the elevation anomaly differences corresponding to each of the survey control points, each of the interpolation points, and each of the external measurement points to the corresponding model elevation anomaly values to obtain the refined elevation anomaly values corresponding to each of the survey control points, each of the interpolation points, and each of the external measurement points;

[0065] A first generating module is used to generate elevation outlier value grid data of a target strip area where the line centerline is located according to the refined elevation outlier value;

[0066] The second generating module is used to generate a quasi-geoid model of the target strip area according to the elevation outlier grid data.

[0067] Optionally, the device further includes a rejection module; the rejection module is configured to, after the third determination module determines the elevation anomaly differences corresponding to the respective measurement control points, perform the following steps:

[0068] Select N consecutively arranged measurement control points as a control point group, fit them with a quadratic polynomial, and obtain the corresponding expression: ;

[0069] in, Indicates the elevation anomaly difference of the measurement control point. Indicates the mileage difference between the measurement control point and the measurement reference point on the center line of the line, 、 、 are the coefficients of the quadratic polynomial to be solved;

[0070] Solving the coefficients of a quadratic polynomial using the least squares method 、 、 And the residuals of the selected N measurement control points are used to calculate the residual sum of squares of the control point group according to the following formula:

[0071] ;

[0072] in, represents the residual sum of squares of the control point group, represents the number of the survey control point in the control point group and , Indicates the number of the measurement control point, Indicates the The elevation anomaly of the survey control points is different. Indicates the The mileage difference between a measurement control point and the measurement reference point;

[0073] Updating step: removing the measured control point arranged at the front from the current control point group, and adding the next measured control point arranged at the back of the current control point group to the control point group to obtain a new control point group, and calculating the residual sum of squares of the new control point group;

[0074] Using the new control point group as the current control point group, and repeating the updating step until no more measured control points are added to the control point group;

[0075] If the sum of squares of the residuals of all the control point groups where a certain survey control point is located is higher than the target multiple of the standard deviation of the elevation anomaly differences of all the survey control points, the survey control point will be eliminated.

[0076] Another aspect of the present disclosure provides an electronic device, comprising:

[0077] at least one processor; and,

[0078] a memory communicatively connected to at least one processor; wherein,

[0079] The memory stores instructions that can be executed by at least one processor. The instructions are executed by the at least one processor to enable the at least one processor to perform the strip-shaped area quasi-geoid refinement method described above.

[0080] Another aspect of the present disclosure provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the aforementioned method for refining the quasi-geoid in a strip area.

[0081] Compared to existing technologies, the present disclosure provides the pipeline design industry with an efficient, economical, safe, and environmentally friendly elevation measurement solution. By combining GNSS technology for elevation measurement, the present disclosure addresses the high cost, difficulty, long cycle time, low accuracy, and inconsistent results associated with traditional elevation measurement methods. This solution improves the flexibility and efficiency of elevation measurement work, and through the resulting quasi-geoid model, provides full lifecycle availability for design, construction, and operation, adapting to the owner's more stringent standards and requirements. This effectively guarantees the quality of elevation results and promotes the development of pipeline measurement towards a ground-free control benchmark. Furthermore, the strip-area quasi-geoid refinement method provided by the present disclosure also improves elevation measurement accuracy and reduces elevation measurement costs, effectively enhancing enterprise competitiveness and promoting sustainable development. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] One or more embodiments are exemplarily illustrated by pictures in the corresponding drawings, and these exemplifications do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0083] Figure 1 A flowchart of a method for refining a quasi-geoid in a strip region provided in one embodiment of the present disclosure;

[0084] Figure 2 A schematic diagram of a fitting curve provided for another embodiment of the present disclosure;

[0085] Figure 3 A flowchart of a method for refining a quasi-geoid in a strip region provided in accordance with another embodiment of the present disclosure;

[0086] Figure 4 A schematic structural diagram of a device for refining a quasi-geoid in a strip region provided by another embodiment of the present disclosure;

[0087] Figure 5 A schematic structural diagram of an electronic device provided in another embodiment of the present disclosure. DETAILED DESCRIPTION

[0088] In order to make the purpose, technical solutions and advantages of the embodiments of the present disclosure clearer, the embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. However, it will be understood by those skilled in the art that in each embodiment of the present disclosure, many technical details are provided to enable readers to better understand the present disclosure. However, even without these technical details and various changes and modifications based on the following embodiments, the technical solutions claimed in the present disclosure can be implemented. The division of the following embodiments is for the convenience of description and should not constitute any limitation on the specific implementation of the present disclosure. The various embodiments can be combined and referenced with each other under the premise that there is no contradiction.

[0089] One embodiment of the present disclosure relates to a method for refining a quasi-geoid in a strip region, the process of which is as follows: Figure 1 As shown, it includes steps S110 to S190.

[0090] Step S110, selecting a number of measurement control points from the pipeline centerline, and determining the actual elevation anomaly value of each measurement control point; wherein each measurement control point is evenly distributed along the centerline and conforms to the terrain change trend of the centerline.

[0091] Specifically, the pipeline centerline refers to the geometric central axis along the pipeline's path. This pipeline can be any type of long-distance pipeline. Long-distance pipelines are systems used to transport oil, gas, water, or other fluids over long distances. These pipelines often span hundreds or even thousands of kilometers. Therefore, when selecting measurement control points, it's important to fully consider the topographical variations along the pipeline centerline to adapt to these changes and improve accuracy.

[0092] Exemplarily, in step S110, the actual elevation anomaly value of each survey control point is determined respectively, including: obtaining the geoid height and normal height of each survey control point; subtracting the normal height of each survey control point from the geoid height to obtain the actual elevation anomaly value of each survey control point.

[0093] Specifically, when obtaining the geoid height and normal height of each measurement control point, the geoid height H and normal height h of the measurement control point can be obtained by performing GNSS static observation on the measurement control point, and the actual elevation anomaly value of the measurement control point is recorded as ξ, then ξ=Hh.

[0094] Step S120: using the EGM2008 gravity field model, determine the model elevation anomaly value of each measurement control point.

[0095] Specifically, the EGM2008 gravity model is a global gravity model designed to provide high-precision gravity field information for the Earth's surface and its surrounding areas. Therefore, step S120 can first determine the corresponding point of the survey control point in the EGM2008 gravity model based on its longitude and latitude. Then, the elevation anomaly value of the corresponding point in the EGM2008 gravity model is extracted and used as the model elevation anomaly value for the corresponding survey control point.

[0096] For example, measuring model elevation outliers at control points It can be expressed as:

[0097] .

[0098] Where T represents the disturbance bit. Indicates the normal gravity value of the survey control point. Represents the gravitational constant. They represent the geocentric radial, colatitude and longitude of the measurement control point respectively. represents the order of the EGM2008 gravity field model, Indicates the number of times. Represents the major radius of the ellipsoid. They represent the first fully normalized bit coefficient and the second fully normalized bit coefficient respectively. represents the fully normalized association function.

[0099] Step S130: determining the elevation anomaly difference corresponding to each measurement control point according to the actual elevation anomaly value and the model elevation anomaly value.

[0100] Specifically, the actual elevation anomaly value of the measurement control point is subtracted from its model elevation anomaly value to obtain the elevation anomaly difference corresponding to the measurement control point. In other words, when the actual elevation anomaly value of the measurement control point is ξ and the model elevation anomaly value of the measurement control point is When the elevation anomaly difference corresponding to the measurement control point is That is, =ξ- .

[0101] In particular, in order to further improve the model accuracy, after step S130, the strip area quasi-geoid refinement method also includes a process of removing abnormal measurement control points to reduce the impact of abnormal measurement control points on the model accuracy.

[0102] The process of eliminating abnormal measurement control points mainly includes the following steps.

[0103] Select N consecutively arranged measurement control points as the control point group, fit them with a quadratic polynomial, and obtain the corresponding expression: .in, Indicates the abnormal difference in elevation of the measurement control point. Indicates the mileage difference between the measurement control point and the measurement benchmark point on the line centerline. 、 、 are the coefficients of the quadratic polynomial to be solved. The specific value of N can be selected and set according to actual needs. For example, the value of N can be 3, 4, 5, etc. The preferred value of N is 4.

[0104] Solving the coefficients of a quadratic polynomial using the least squares method 、 、 And the residuals of the selected N measurement control points are used to calculate the residual sum of squares of the control point group according to the following formula:

[0105] .

[0106] in, represents the residual sum of squares for the control point group, Represents the number of the survey control point in the control point group and , Indicates the number of the measurement control point, Indicates the The elevation anomaly of the survey control points is different. Indicates the The mileage difference between a survey control point and a survey benchmark point.

[0107] Update step: remove the first measured control point from the current control point group, add the next measured control point of the last measured control point in the current control point group to the control point group to obtain a new control point group, and calculate the residual sum of squares of the new control point group.

[0108] Use the new control point group as the current control point group and repeat the update steps until no more measured control points are added to the control point group.

[0109] If the sum of squared residuals for all control point groups in which a given control point is located is higher than a target multiple of the standard deviation of the elevation anomaly differences of all control points, the control point is removed. The target multiple can be set according to actual needs. For example, the target multiple is preferably 3, that is, if the sum of squared residuals for all control point groups in which a given control point is located is higher than 3 times the standard deviation of the elevation anomaly differences of all control points, the control point is removed.

[0110] The standard deviation of the elevation anomaly of all the measurement control points can be calculated according to the existing standard deviation calculation formula. For example, when the total number of the measurement control points selected in step S110 is L, The elevation anomaly difference of the measurement control points is When , we can first calculate the average value of the elevation anomaly difference of L measurement control points ,in, On this basis, the standard deviation of the elevation anomaly of L measurement control points can be obtained .

[0111] For example, assuming L=8, the 8 measurement control points are , select As a control point group, four control point groups can be obtained according to the sliding window method, namely: The control point group composed of The control point group composed of The control point group composed of Assume that The sum of squares of the residuals of all control point groups is higher than that of all measured control points. to 3 times the standard deviation of the elevation anomaly, then Remove and no longer used in subsequent steps .

[0112] Step S140 , according to the terrain change trend, select a plurality of interpolation points of each measurement control point from the line center line at a first preset distance, and determine the elevation anomaly difference corresponding to each interpolation point.

[0113] Specifically, in order to further increase the density of points on the line centerline and improve the precision of the model, it is necessary to select several interpolation points. The first preset distance can be determined according to actual conditions to meet the accuracy requirements.

[0114] Illustratively, in step S140, determining the elevation anomaly difference corresponding to each interpolation point includes: using a quadratic polynomial moving curve fitting algorithm and a least squares algorithm to fit the elevation anomaly difference corresponding to each interpolation point using the elevation anomaly difference corresponding to each measurement control point.

[0115] By using the quadratic polynomial moving curve fitting algorithm and the least squares algorithm to fit the elevation anomaly differences corresponding to each interpolation point, the elevation anomaly differences obtained by fitting can be made closer to the actual elevation anomaly differences of the interpolation points, greatly improving the fitting accuracy.

[0116] Exemplarily, a quadratic polynomial moving curve fitting algorithm and a least squares algorithm are used to fit the elevation anomaly differences corresponding to each interpolation point using the elevation anomaly differences corresponding to each survey control point, including: selecting a number of survey control points from upstream and downstream of each interpolation point as the respective reference points corresponding to each interpolation point, and calculating the mileage difference between each interpolation point and its corresponding reference points according to the following formula: .

[0117] in, Represents the mileage difference between the interpolated point p and its corresponding i-th benchmark point. represents the mileage of the interpolated point p. The mileage of the i-th benchmark corresponding to the interpolated point p. i represents the benchmark number and i = 1, 2, …, t. t represents the total number of benchmarks corresponding to the interpolated point p.

[0118] Determine the fitting curve and express the fitting curve as: .

[0119] in, represents the elevation anomaly difference matrix and , They represent the elevation anomaly differences of the 1st, 2nd, …, tth benchmark points corresponding to the interpolation point p respectively. represents the mileage difference matrix and , They represent the mileage difference between the interpolation point p and its corresponding 1st, 2nd, ..., tth benchmark points respectively. 、 、 Represent the first coefficient, the second coefficient, and the third coefficient respectively.

[0120] For example, according to Figure 2 The interpolation point p shown corresponds to the 1st, 2nd, 3rd, and tth reference points , the corresponding fitting curve can be obtained. Among them, Represent the interpolation point p and the reference point respectively The mileage difference, Represents the reference points The elevation is abnormally poor.

[0121] Calculate the weight of each reference point corresponding to each interpolation point according to the following formula: .

[0122] in, Represents the weight of the i-th reference point corresponding to the interpolation point p. Represents the natural logarithm. Represents a constant.

[0123] Let the coefficient matrix , solve the coefficient matrix according to the following formula : .

[0124] in, represents the parameter matrix and . represents the weight matrix and .

[0125] make , and compare it with the solved 、 、 Substitute into the fitting curve , get the elevation anomaly difference corresponding to the interpolation point p .in, Represents the mileage difference between the interpolated point p and itself.

[0126] For example, if Figure 2 As shown, let , and compare it with the solved 、 、 Substitute the reference point The corresponding fitting curve , we can get the elevation anomaly difference corresponding to the interpolation point p .

[0127] Step S150 : selecting a plurality of external measurement points within a second preset distance from both sides of the line centerline, and determining the elevation anomaly differences corresponding to the respective external measurement points.

[0128] Specifically, after obtaining the elevation anomaly differences of each measurement control point and each interpolation point on the line centerline, it is also necessary to determine the elevation anomaly differences of several external measurement points other than the line centerline in the target strip area where the line centerline is located, so as to fully understand the terrain characteristics and gravity field changes of the target strip area, and further improve the accuracy of the quasi-geoid model of the target strip area finally obtained.

[0129] Exemplarily, in step S150, the elevation anomaly difference corresponding to each external measurement point is determined, including: projecting each external measurement point onto the center line of the line to obtain corresponding projection points; and using the elevation anomaly difference corresponding to each projection point as the elevation anomaly difference corresponding to the external measurement point corresponding to each projection point.

[0130] Specifically, if the projection point corresponding to the external measurement point is a measurement control point or an interpolation point, the elevation anomaly difference corresponding to the measurement control point or the interpolation point can be directly used as the elevation anomaly difference corresponding to the projection point, and then as the elevation anomaly difference corresponding to the external measurement point. If the projection point corresponding to the external measurement point is neither a measurement control point nor an interpolation point, the projection point can be used as a new interpolation point, and the elevation anomaly difference corresponding to the new interpolation point can be obtained using the same method as step S140. The elevation anomaly difference corresponding to the new interpolation point is used as the elevation anomaly difference corresponding to the projection point, and then as the elevation anomaly difference corresponding to the external measurement point.

[0131] By using the projection points of each external measurement point to obtain the elevation anomaly difference corresponding to each external measurement point, the elevation anomaly difference corresponding to the external measurement point can be made closer to its actual elevation anomaly difference, which can further improve the accuracy of the quasi-geoid model of the target strip area finally obtained.

[0132] Step S160: using the EGM2008 gravity field model, determine the model elevation anomaly values corresponding to each interpolation point and each external measurement point.

[0133] Specifically, similar to step S120, step S160 can first determine the corresponding points of the interpolation point and the external measurement point in the EGM2008 gravity field model according to the longitude and latitude, and then extract the elevation anomaly value of the corresponding point in the EGM2008 gravity field model, and use the elevation anomaly value as the model elevation anomaly value of the corresponding interpolation point or external measurement point.

[0134] In step S170, the elevation anomaly differences corresponding to each survey control point, each interpolation point, and each external survey point are added to their corresponding model elevation anomaly values to obtain the refined elevation anomaly values corresponding to each survey control point, each interpolation point, and each external survey point.

[0135] Specifically, by using the elevation anomaly difference to refine the model elevation anomaly values corresponding to each measurement control point, each interpolation point, and each external measurement point, the accuracy of the quasi-geoid model of the target strip area can be further improved.

[0136] Step S180: Generate elevation outlier grid data of the target strip area where the line centerline is located based on the refined elevation outlier values.

[0137] Exemplarily, step S180 includes: gridding the target strip area according to a preset grid point interval; determining the minimum rectangle covering the target strip area to obtain a grid range corresponding to the target strip area; wherein the longitude and latitude corresponding to each side of the minimum rectangle meet the preset accuracy requirements; within the grid range, calculating the coordinates of each grid point in turn, and determining the refined elevation anomaly value corresponding to each grid point to obtain elevation anomaly grid data.

[0138] Specifically, the preset grid point interval can be set based on the actual accuracy requirements. For example, the preset grid point interval can be determined based on the units of longitude and latitude, such as degrees, minutes, and seconds. For example, to balance the accuracy requirements and the amount of computation, the preset grid point interval can be set to 1 minute × 1 minute, that is, the longitude and latitude intervals of the grid points are both 1 minute.

[0139] To ensure that the grid points fully cover the entire target strip, after determining the minimum rectangle covering the target strip, the minimum rectangle must be updated according to the preset grid point interval so that the updated minimum rectangle meets the preset accuracy requirements. For example, when the preset grid point interval is set to 1 minute × 1 minute, if the longitude and latitude corresponding to an initial side of the minimum rectangle covering the target strip is not an integer multiple of 1 minute, the initial side must be translated to the nearest integer longitude or latitude line away from the center of the minimum rectangle. At the same time, the two sides adjacent to the initial side must be extended to intersect with the initial side, thereby updating the minimum rectangle so that the updated minimum rectangle meets the preset accuracy requirements.

[0140] When determining the refined elevation anomaly value corresponding to each grid point, if the grid point corresponds to a survey control point, interpolation point, or external measurement point, the refined elevation anomaly value of the survey control point, interpolation point, or external measurement point can be directly used as the refined elevation anomaly value of the grid point. If the grid point does not correspond to a survey control point, interpolation point, or external measurement point, the grid point can be used as a new interpolation point and the refined elevation anomaly value of the grid point can be obtained using the same method as step S140.

[0141] Step S190: generating a quasi-geoid model of the target strip area based on the elevation outlier grid data.

[0142] Specifically, step S190 can utilize the Grid Factory software tool to generate a quasi-geoid model in the GGF format based on the elevation outlier grid data, so as to facilitate the use of the GNSS static adjustment software.

[0143] The method for refining the quasi-geoid in a strip area provided by the embodiments of the present disclosure provides an efficient, economical, safe, and environmentally friendly elevation measurement solution for the pipeline design industry compared to existing technologies. Combining GNSS technology for elevation measurement solves the problems of high cost, difficulty, long cycle time, low accuracy, and poor consistency of results in traditional elevation measurement methods, improving the flexibility and efficiency of elevation measurement work. The resulting quasi-geoid model provides full lifecycle availability for design, construction, and operation, adapting to the owner's more stringent standard requirements, effectively ensuring the quality of elevation results, and promoting the development of pipeline measurement in the direction of no ground control benchmark. At the same time, the method for refining the quasi-geoid in a strip area provided by the embodiments of the present disclosure also improves elevation measurement accuracy and reduces elevation measurement costs, effectively enhancing corporate competitiveness and promoting sustainable development.

[0144] In order to enable those skilled in the art to better understand the above embodiment, a specific example is provided below for description.

[0145] Combined Figure 3 , a method for refining a quasi-geoid in a strip area, comprising the following steps.

[0146] The geodetic height H and normal height h of the survey control point are known: perform GNSS static observation on the survey control point to obtain the geodetic height H and normal height h of the survey control point.

[0147] The control point elevation anomaly value ξ=Hh: Subtract the normal height h from the geoid height H of each measurement control point to obtain the actual elevation anomaly value ξ of each measurement control point, that is, ξ=Hh.

[0148] Extract the elevation anomaly value ξ(EGM) of the control point: Use the EGM2008 gravity field model to determine the model elevation anomaly value ξ(EGM) of each measurement control point.

[0149] The elevation anomaly difference of the control point is calculated as the elevation anomaly value of the control point - the elevation anomaly value is extracted by the EGM2008 model: the actual elevation anomaly value of the measured control point is subtracted from its model elevation anomaly value to obtain the elevation anomaly difference corresponding to the measured control point.

[0150] Fitting to determine the elevation anomaly differences for all points on the route centerline and on the grid: Based on the terrain trend, interpolate several points from each survey control point along the route centerline at a first preset distance. Using a quadratic polynomial moving curve fitting algorithm and a least squares algorithm, fit the elevation anomaly differences corresponding to each survey control point to the elevation anomaly differences corresponding to each interpolated point. Select several external survey points within a second preset distance on both sides of the route centerline and project them onto the route centerline to obtain their corresponding projected points. The elevation anomaly differences corresponding to each projected point are used as the elevation anomaly differences corresponding to the external survey points corresponding to each projected point.

[0151] Extract the elevation anomaly values of all points on the line centerline and the grid: Use the EGM2008 gravity field model to determine the model elevation anomaly values corresponding to each interpolation point and each external measurement point.

[0152] Obtain the refined elevation anomaly of all grid points after refinement: add the elevation anomaly differences corresponding to each survey control point, each interpolation point, and each external survey point with their corresponding model elevation anomaly values to obtain the refined elevation anomaly values corresponding to each survey control point, each interpolation point, and each external survey point.

[0153] Generate elevation anomaly grid data of the target area: Generate elevation anomaly grid data of the target strip area where the line centerline is located based on the refined elevation anomaly values.

[0154] Generate a geoid model in GGF format: Use the Grid Factory software tool to generate a quasi-geoid model in GGF format based on the elevation anomaly grid data.

[0155] Another embodiment of the present disclosure relates to a device for refining a quasi-geoid in a strip region, such as Figure 4 As shown, it includes a first determination module 410, a second determination module 420, a third determination module 430, a fourth determination module 440, a fifth determination module 450, a sixth determination module 460, a refinement module 470, a first generation module 480, and a second generation module 490.

[0156] The first determination module 410 is used to select a number of measurement control points from the pipeline centerline and determine the actual elevation anomaly value of each measurement control point; wherein the measurement control points are evenly distributed along the centerline and conform to the terrain change trend of the centerline.

[0157] The second determination module 420 is used to determine the model elevation anomaly value of each measurement control point using the EGM2008 gravity field model.

[0158] The third determination module 430 is used to determine the elevation anomaly difference corresponding to each measurement control point according to the actual elevation anomaly value and the model elevation anomaly value.

[0159] The fourth determining module 440 is used to select a plurality of interpolation points of each measurement control point from the line center line according to the terrain change trend and the first preset distance, and determine the elevation anomaly difference corresponding to each interpolation point.

[0160] The fifth determining module 450 is configured to select a plurality of external measurement points within a second preset distance from both sides of the line centerline, and determine the elevation anomaly difference corresponding to each external measurement point.

[0161] The sixth determination module 460 is used to determine the model elevation anomaly values corresponding to each interpolation point and each external measurement point using the EGM2008 gravity field model.

[0162] The refinement module 470 is used to add the elevation anomaly differences corresponding to each survey control point, each interpolation point, and each external survey point to their corresponding model elevation anomaly values to obtain the refined elevation anomaly values corresponding to each survey control point, each interpolation point, and each external survey point.

[0163] The first generating module 480 is used to generate elevation outlier value grid data of the target strip area where the line centerline is located based on the refined elevation outlier values.

[0164] The second generating module 490 is used to generate a quasi-geoid model of the target strip area based on the elevation outlier grid data.

[0165] Exemplarily, the strip-shaped region quasi-geoid refinement device further includes a rejection module.

[0166] The elimination module is used to perform the following steps after the third determination module determines the elevation anomaly differences corresponding to each measurement control point.

[0167] Select N consecutively arranged measurement control points as the control point group, fit them with a quadratic polynomial, and obtain the corresponding expression: .

[0168] in, Indicates the abnormal difference in elevation of the measurement control point. Indicates the mileage difference between the measurement control point and the measurement benchmark point on the line centerline. 、 、 are the coefficients of the quadratic polynomial to be solved.

[0169] Solving the coefficients of a quadratic polynomial using the least squares method 、 、 And the residuals of the selected N measurement control points are used to calculate the residual sum of squares of the control point group according to the following formula:

[0170] .

[0171] in, represents the residual sum of squares for the control point group, Represents the number of the survey control point in the control point group and , Indicates the number of the measurement control point, Indicates the The elevation anomaly of the survey control points is different. Indicates the The mileage difference between a survey control point and a survey benchmark point.

[0172] Update step: remove the first measured control point from the current control point group, add the next measured control point of the last measured control point in the current control point group to the control point group to obtain a new control point group, and calculate the residual sum of squares of the new control point group.

[0173] Use the new control point group as the current control point group and repeat the update steps until no more measured control points are added to the control point group.

[0174] If the sum of squares of the residuals of all control point groups in which a certain measurement control point is located is higher than the target multiple of the standard deviation of the elevation anomaly of all measurement control points, the measurement control point will be eliminated.

[0175] The specific implementation method of the strip area quasi-geoid refinement device provided in the embodiment of the present disclosure can be found in the strip area quasi-geoid refinement method provided in the embodiment of the present disclosure, and will not be repeated here.

[0176] The strip-shaped area quasi-geoid refinement device provided by the disclosed embodiment provides an efficient, economical, safe, and environmentally friendly elevation measurement solution for the pipeline design industry compared to existing technologies. Combining GNSS technology for elevation measurement solves the problems of high cost, difficulty, long cycle time, low accuracy, and poor consistency of results in traditional elevation measurement methods, improving the flexibility and efficiency of elevation measurement work. The resulting quasi-geoid model provides full lifecycle availability for design, construction, and operation, adapting to the owner's more stringent standard requirements, effectively ensuring the quality of elevation results, and promoting the development of pipeline measurement in the direction of no ground control benchmark. At the same time, the strip-shaped area quasi-geoid refinement method provided by the disclosed embodiment also improves elevation measurement accuracy and reduces elevation measurement costs, effectively enhancing corporate competitiveness and promoting sustainable development.

[0177] Another embodiment of the present disclosure relates to an electronic device, such as Figure 5 As shown, including:

[0178] at least one processor 501; and,

[0179] A memory 502 in communication with at least one processor 501; wherein,

[0180] The memory 502 stores instructions that can be executed by at least one processor 501. The instructions are executed by the at least one processor 501 so that the at least one processor 501 can perform the strip area quasi-geoid refinement method described in the above embodiment.

[0181] The memory and processor are connected using a bus, which can include any number of interconnected buses and bridges. The bus connects various circuits of one or more processors and memories. The bus can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits. These are all well known in the art and are therefore not described further herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be a single component or multiple components, such as multiple receivers and transmitters, providing a unit for communicating with various other devices over a transmission medium. Data processed by the processor is transmitted over a wireless medium via an antenna. Furthermore, the antenna receives data and transmits it to the processor.

[0182] The processor is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. Memory can be used to store data used by the processor when performing operations.

[0183] Another embodiment of the present disclosure relates to a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method for refining the quasi-geoid in a strip area as described in the above embodiment.

[0184] That is, those skilled in the art will understand that all or part of the steps in the methods described in the above embodiments can be implemented by instructing related hardware through a program. The program is stored in a storage medium and includes a number of instructions for causing a device (such as a microcontroller or chip) or a processor to execute all or part of the steps in the methods described in the various embodiments of the present disclosure. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0185] Those skilled in the art will appreciate that the above-mentioned embodiments are specific embodiments for implementing the present disclosure, and that in actual applications, various changes may be made thereto in form and detail without departing from the spirit and scope of the present disclosure.

Claims

1. A method for refining a quasi-geoid in a strip region, characterized in that: The method comprises: Selecting a number of measurement control points along the pipeline centerline and determining the actual elevation anomaly value of each measurement control point; wherein each measurement control point is evenly distributed along the pipeline centerline and conforms to the topographic change trend of the pipeline centerline; Using the EGM2008 gravity field model, the model elevation anomaly value of each of the measurement control points is determined; Determining the elevation anomaly difference corresponding to each of the measurement control points according to the actual elevation anomaly value and the model elevation anomaly value; According to the terrain change trend, a plurality of interpolation points of each of the measurement control points are selected from the center line of the line at a first preset distance, and the elevation anomaly difference corresponding to each of the interpolation points is determined; Selecting a plurality of external measurement points within a second preset distance on both sides of the line centerline, and determining the elevation anomaly difference corresponding to each of the external measurement points; Using the EGM2008 gravity field model, determining the model elevation anomaly values corresponding to each of the interpolation points and each of the external measurement points; Adding the elevation anomaly differences corresponding to each of the survey control points, each of the interpolation points, and each of the external survey points to the corresponding model elevation anomaly values to obtain the refined elevation anomaly values corresponding to each of the survey control points, each of the interpolation points, and each of the external survey points; Generating elevation outlier grid data of the target strip area where the line centerline is located according to the refined elevation outlier values; A quasi-geoid model of the target strip area is generated based on the elevation outlier grid data.

2. The method according to claim 1, characterized in that The step of respectively determining the actual elevation anomaly value of each of the measurement control points comprises: Obtaining the geodetic height and normal height of each of the measurement control points; The actual elevation anomaly value of each measurement control point is obtained by subtracting its normal height from its geoid height.

3. The method according to claim 1, characterized in that Determining the elevation anomaly differences corresponding to the interpolation points includes: The quadratic polynomial moving curve fitting algorithm and the least squares algorithm are adopted to fit the elevation anomaly differences corresponding to the interpolation points using the elevation anomaly differences corresponding to the measurement control points.

4. The method according to claim 3, characterized in that The method adopts a quadratic polynomial moving curve fitting algorithm and a least squares algorithm to fit the elevation anomaly differences corresponding to the interpolation points using the elevation anomaly differences corresponding to the measurement control points, including: Select several measurement control points from the upstream and downstream of each interpolation point as the reference points corresponding to each interpolation point, and calculate the mileage difference between each interpolation point and its corresponding reference points according to the following formula: ； in, represents the mileage difference between the interpolated point p and its corresponding i-th benchmark point; represents the mileage of the interpolation point p; represents the mileage of the i-th benchmark point corresponding to the interpolation point p; i represents the benchmark point number and i=1,2,…,t; t represents the total number of benchmark points corresponding to the interpolation point p; A fitting curve is determined and expressed as: ； in, represents the elevation anomaly difference matrix and , They represent the elevation anomaly differences of the 1st, 2nd, …, tth benchmark points corresponding to the interpolation point p respectively; represents the mileage difference matrix and , They represent the mileage difference between the interpolation point p and its corresponding 1st, 2nd, ..., tth benchmark points respectively; 、 、 Represent the first coefficient, the second coefficient, and the third coefficient respectively; The weights of the reference points corresponding to the interpolation points are calculated according to the following formula: ； in, represents the weight of the i-th reference point corresponding to the interpolation point p; represents the natural logarithm; represents a constant; Let the coefficient matrix , solve the coefficient matrix according to the following formula : ； in, represents the parameter matrix and , represents the weight matrix and ; make , and compare it with the solved 、 、 Substitute into the fitting curve , get the elevation anomaly difference corresponding to the interpolation point p ;in, Represents the mileage difference between the interpolated point p and itself.

5. The method according to claim 1, wherein Determining the elevation anomaly differences corresponding to the external measurement points includes: Projecting each of the external measurement points onto the center line of the line to obtain corresponding projection points; The elevation anomaly difference corresponding to each of the projection points is used as the elevation anomaly difference corresponding to the external measurement point corresponding to each of the projection points.

6. The method according to claim 1, wherein Generating elevation outlier value grid data of a target strip area where the line centerline is located based on the refined elevation outlier value includes: Gridding the target strip area according to a preset grid point interval; Determine a minimum rectangle covering the target strip area, and obtain a grid range corresponding to the target strip area; wherein the longitude and latitude corresponding to each side of the minimum rectangle meet a preset accuracy requirement; Within the grid range, the coordinates of each grid point are calculated in sequence, and the refined elevation anomaly value corresponding to each grid point is determined to obtain the elevation anomaly value grid data.

7. The method according to any one of claims 1 to 6, characterized in that After determining the elevation anomaly differences corresponding to the respective measurement control points based on the actual elevation anomaly values and the model elevation anomaly values, the method further includes: Select N consecutively arranged measurement control points as a control point group, fit them with a quadratic polynomial, and obtain the corresponding expression: ; in, Indicates the elevation anomaly difference of the measurement control point. Indicates the mileage difference between the measurement control point and the measurement reference point on the center line of the line, 、 、 are the coefficients of the quadratic polynomial to be solved; Solving the coefficients of a quadratic polynomial using the least squares method 、 、 And the residuals of the selected N measurement control points are used to calculate the residual sum of squares of the control point group according to the following formula: ； in, represents the residual sum of squares of the control point group, represents the number of the survey control point in the control point group and , Indicates the number of the measurement control point, Indicates the The elevation anomaly of the survey control points is different. Indicates the The mileage difference between a measurement control point and the measurement reference point; Updating step: removing the measured control point arranged at the front from the current control point group, and adding the next measured control point arranged at the back of the current control point group to the control point group to obtain a new control point group, and calculating the residual sum of squares of the new control point group; Using the new control point group as the current control point group, and repeating the updating step until no more measured control points are added to the control point group; If the sum of squares of the residuals of all the control point groups where a certain survey control point is located is higher than the target multiple of the standard deviation of the elevation anomaly differences of all the survey control points, the survey control point will be eliminated.

8. A device for refining the quasi-geoid in a strip area, characterized in that: The device comprises: A first determination module is configured to select a plurality of measurement control points from the pipeline centerline and determine the actual elevation anomaly value of each of the measurement control points; wherein the measurement control points are evenly distributed along the pipeline centerline and conform to the topographic change trend of the pipeline centerline; The second determination module is used to determine the model elevation anomaly value of each of the measurement control points using the EGM2008 gravity field model; A third determining module is used to determine the elevation anomaly difference corresponding to each of the measurement control points according to the actual elevation anomaly value and the model elevation anomaly value; A fourth determination module is configured to select, based on the terrain change trend and at a first preset distance, a plurality of interpolation points of each of the measurement control points from the center line of the line, and determine an elevation anomaly difference corresponding to each of the interpolation points; a fifth determining module, configured to select a plurality of external measurement points within a second preset distance from both sides of the line centerline, and determine an elevation anomaly difference corresponding to each of the external measurement points; a sixth determination module, configured to determine the model elevation anomaly values corresponding to each of the interpolation points and each of the external measurement points, respectively, using the EGM2008 gravity field model; A refinement module is used to add the elevation anomaly differences corresponding to each of the survey control points, each of the interpolation points, and each of the external measurement points to the corresponding model elevation anomaly values to obtain the refined elevation anomaly values corresponding to each of the survey control points, each of the interpolation points, and each of the external measurement points; A first generating module is used to generate elevation outlier value grid data of a target strip area where the line centerline is located according to the refined elevation outlier value; The second generating module is used to generate a quasi-geoid model of the target strip area according to the elevation outlier grid data.

9. An electronic device, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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