Non-contact airport runway settlement and slab staggering automatic monitoring method

Abstract

The invention relates to the technical field of tunnel excavation construction under an airport, and provides a non-contact type airport runway settlement and slab staggering automatic monitoring method which comprises the following steps: S1, arranging an automatic monitoring high platform beside a monitoring area, a total station is installed on the automatic monitoring high platform; s2, dividing the monitoring area into plate grids to obtain two-dimensional coordinates of angular points of each grid; s3, scanning the monitoring area through a total station, and calculating three-dimensional coordinates of a plurality of monitoring points; s4, fitting the obtained coordinates of the monitoring points into a plane by using a linear least square method, and identifying and eliminating abnormal values in observation data through a data detection method; and S5, calculating the elevation values of the midpoint of the grid and the midpoints of the four sides of the grid based on the step S4 so as to monitor the settlement and slab staggering variation. According to the invention, real and reliable monitoring data can be provided for tunneling of the under-penetrating shield tunneling machine.

Description

Technical Field

[0001] The present application relates to the technical field of tunnel construction under an airport, and particularly to a non-contact automatic monitoring method for runway settlement and offset of an airport. Background Art

[0002] At present, the monitoring of airport runways mainly relies on manual methods. To ensure the normal operation of the airport during the process of a shield machine passing through the taxiway of the airport, it is necessary to monitor the runway settlement and offset conditions at any time. However, due to the particularity of the airport, the construction monitoring of shield propulsion is difficult. In the restricted area of the airport, there are many restrictive conditions: only at night and with the consent of the airport, can one enter the monitoring area and set up monitoring points accompanied by a special person, and the time is limited to 3 - 4 hours; no protrusions or reflective sheets shall be buried on the surface of the airport runway and taxiway to ensure the safety of aircraft takeoff and landing; there is a height limit control within a range of 70 m along the axis of the main runway and 48.5 m within the taxiway; as a key route for aircraft to pass through, the taxiway prohibits personnel unrelated to aircraft from approaching for safety and anti-terrorism considerations. The above conditions restrict the manual monitoring means and cannot provide all-weather, true and reliable monitoring data for the tunneling of the shield machine under the airport. Summary of the Invention

[0003] In order to help solve the above technical problems, the present application provides a non-contact automatic monitoring method for runway settlement and offset of an airport, and adopts the following technical solutions:

[0004] A non-contact automatic monitoring method for runway settlement and offset of an airport, wherein the method includes:

[0005] Step S1: Taking the area within N times the shield diameter range of the airport tunnel excavation face as the monitoring area, setting up an automatic monitoring high platform beside the monitoring area, and installing a total station on the automatic monitoring high platform, where N is a positive integer;

[0006] Step S2: Dividing the monitoring area into plate grids to obtain the two-dimensional coordinates of the corner points of each grid;

[0007] Step S3: Scanning the monitoring area through the total station to establish a control network, dividing the points in the control network into reference points and working stations corresponding to the automatic monitoring high platform and obtaining the coordinates of the reference points and working stations, and calculating the three-dimensional coordinates of several monitoring points through the full-circle observation method in combination with the two-dimensional coordinates, reference point coordinates and working station coordinates in Step S2;

[0008] Step S4: Using the linear least squares method to fit a plane to the obtained monitoring point coordinates, and identifying and removing the outliers in the observed data through the data detection method;

[0009] Step S5: Calculating the elevation values of the midpoints of the grids and the midpoints of the four sides of the grids based on Step S4 to monitor the settlement and offset change amounts.

[0010] Preferably, the step S1 includes: N is 3 and the height of the platform is automatically monitored to be within the height limit of the airport.

[0011] Preferably, the step S1 comprises: the size of the grid is 5m×5m, and the two-dimensional coordinates of each grid corner point are derived through the South CASS on the total station.

[0012] Preferably, the step S3 comprises: checking the stability of the reference point by:

[0013] Step S31: After the benchmark point network is re-measured, all benchmark points are combined in pairs to calculate the difference between the height difference data after adjustment in this period and the height difference data after adjustment in the previous period;

[0014] Step S32: When all calculated height differences are not greater than the tolerance calculated by the following formula, all reference points are considered stable:

[0015]

[0016] Among them: δ represents the height difference limit; μ represents the mean error of the height difference of the corresponding accuracy level; n represents the number of observation stations between two reference points, σ h represents the standard deviation of elevation;

[0017] Step S33: When a difference exceeds the tolerance limit, the unstable point should be found through statistical testing method.

[0018] Preferably, the step S4 includes: the least squares method of plane fitting calculation method is as follows:

[0019] The general expression of the plane equation is formula 1: Ax+By+Cz+D=0 (C≠0);

[0020] Formula 2:

[0021] Formula 3:

[0022] Substituting equation 3 into equation 2, we can get equation 4:

[0023] z=a 0 x+a 1 y+a 2 ;

[0024] For a series of n points: (x i ,y i ,z i ), use the n points to fit the plane equation, n is a positive integer greater than or equal to 3, i is an integer greater than or equal to 0 and less than or equal to n-1, that is:

[0025] Formula Five:

[0026] Take the partial derivatives of both sides of Formula Four with respect to a 0 , a 1 , a 2 to minimize S, and set the partial derivative function to zero, i.e., Formula Six:

[0027]

[0028] Rewrite it in matrix form as Formula Seven:

[0029]

[0030] Solve to obtain the parameters a 0 , a 1 , a 2 , and substitute a 0 , a 1 , a 2 into Formula Four to solve for the plane equation.

[0031] Preferably, the step S4 includes:

[0032] In the data detection method, the original hypothesis is H 0 : E(V i ) = 0, assuming that there are no gross errors in the observed value L i , and consider as the standard normal distribution statistic:

[0033]

[0034] Conduct a u-test. If |u| ≥ u α / 2 , and α is taken as 0.05, then reject the original hypothesis H 0 , and assume that L i may have gross errors. Among them, v i represents the residual, σ 0 2 Q vivi represents the variance, σ o represents the standard deviation, and Q vivi represents the weight reciprocal of the observed value L i .

[0035] Preferably, the step S5 includes:

[0036] The elevation value of each plate grid is the Z value of the midpoint coordinate of the plate grid section;

[0037] The settlement change amount ΔZ for this time = the current coordinate Z - the previous coordinate Z;

[0038] The cumulative settlement change amount ΔZ = the current coordinate Z - the initial coordinate Z;

[0039] The difference in elevation at the midpoints of adjacent sides of adjacent plate grids is the step value;

[0040] The current step change = the current step value - the previous step value;

[0041] The cumulative step change = the current step value - the initial step value.

[0042] In summary, the present application makes up for the deficiencies of manual monitoring and provides a detection method for monitoring the settlement of the airport surface during the construction of the tunnel under the airport, which can provide true and reliable monitoring data for the tunneling of the shield machine under the airport. Description of the Drawings

[0043] Figure 1 It is a schematic flow chart of an embodiment of a non-contact automatic monitoring method for runway settlement and step of the present application;

[0044] Figure 2 It is a schematic principle diagram of step S5 of the present application;

[0045] Figure 3 It is a schematic diagram of the monitoring platform applied by the monitoring method of the present application. Detailed Embodiment

[0046] The present application will be further described below with reference to the drawings. The structure and principle of the present application are very clear to those skilled in the art. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0047] Figure 1 It is a schematic flow chart of an embodiment of a non-contact automatic monitoring method for runway settlement and step of the present application; Figure 2 It is a schematic principle diagram of step S5 of the present application.

[0048] Combined with Figure 1 、 Figure 2 and Figure 3 It can be understood that the method includes:

[0049] Step S1: Take the area within N times the shield diameter of the airport tunnel excavation face as the monitoring area. Set up an automatic monitoring high platform beside the monitoring area and install a total station on the automatic monitoring high platform. N is a positive integer. In this embodiment, N can be 3, and the height of the automatic monitoring high platform is within the airport height limit.

[0050] Step S2: Divide the monitoring area into plate grids to obtain the two-dimensional coordinates of the corner points of each grid. In this embodiment, the size of the grid is 5m×5m, and the two-dimensional coordinates of the corner points of each grid are exported through the South CASS on the total station.

[0051] Step S3: Scan the monitoring area with a total station, establish a control network, divide the points in the control network into reference points and work stations corresponding to the automatic monitoring platform, and obtain the coordinates of the reference points and work stations. Calculate the three-dimensional coordinates of several monitoring points through the full-circle observation method and in combination with the two-dimensional coordinates in step S2, the reference point coordinates and the work station coordinates.

[0052] In step S3, the stability of the reference point needs to be checked as follows:

[0053] Step S31: After the benchmark point network is re-measured, all benchmark points are combined in pairs to calculate the difference between the height difference data after adjustment in this period and the height difference data after adjustment in the previous period;

[0054] Step S32: When all calculated height differences are not greater than the tolerance calculated by the following formula, all reference points are considered stable:

[0055]

[0056] Among them: δ represents the height difference limit; μ represents the mean error of the height difference of the corresponding accuracy level; n represents the number of observation stations between two benchmarks;

[0057] Step S33: When a difference exceeds the limit, the unstable point should be found through analysis and judgment.

[0058] Step S4: Fit the obtained monitoring point coordinates to a plane using the linear least squares method, and identify and eliminate outliers in the observed data using the data detection method.

[0059] Step S4 includes: the least squares method of plane fitting calculation method is as follows:

[0060] The general expression of the plane equation is formula 1: Ax+By+Cz+D=0 (C≠0);

[0061] Formula 2:

[0062] Formula 3:

[0063] Substituting equation 3 into equation 2, we can get equation 4:

[0064] z=a 0 x+a 1 y+a 2 ;

[0065] For a series of n points: (x i ,y i ,z i ), use the n points to fit the plane equation, n is a positive integer greater than or equal to 3, i is an integer greater than or equal to 0 and less than or equal to n-1, that is:

[0066] Formula Five:

[0067] Take the partial derivative of both sides of Formula Four with respect to a 0 , a 1 , a 2 to minimize S, and set the partial derivative function to zero, i.e., Formula Six:

[0068]

[0069] Rewrite it in matrix form as Formula Seven:

[0070]

[0071] Solve to obtain the parameters a 0 , a 1 , a 2 , and substitute a 0 , a 1 , a 2 into Formula Four to solve for the plane equation.

[0072] Step S4 also includes:

[0073] In the data detection method, the original hypothesis is H 0 : E(V i ) = 0, assuming that there is no gross error in the observed value L i , and consider as the standard normal distribution statistic:

[0074]

[0075] Conduct a u-test. If |u| ≥ u α / 2 , with α = 0.05, then reject the original hypothesis H 0 , and assume that L i may have a gross error.

[0076] Step S5: Based on the elevation values calculated in Step S4 for the midpoints of the grid and the midpoints of the four sides of the grid, monitor the settlement and offset change amounts. Step S5 includes:

[0077] The elevation value of each plate grid is the Z value of the midpoint coordinates of the plate grid section;

[0078] The current settlement change amount ΔZ = current coordinate Z - previous coordinate Z;

[0079] The cumulative settlement change amount ΔZ = current coordinate Z - initial coordinate Z;

[0080] The difference in the elevation of the midpoints of the adjacent sides of adjacent plate grids is the offset value;

[0081] The amount of change in the stepped surface this time = the value of the stepped surface this time - the value of the stepped surface last time;

[0082] The cumulative amount of change in the stepped surface = the value of the stepped surface this time - the initial value of the stepped surface.

[0083] Taking a monitoring project at an airport in Shanghai as an example, the specific implementation steps are as follows:

[0084] A. Set up an automatic monitoring high platform beside the monitoring area (using a cylindrical forced observation pier made of stainless steel, with a 30cm * 30cm square base at the bottom), and install a total station on the high platform (protected by a stainless steel rain cover);

[0085] In this measurement, the measuring robot is set up on the workstation. After setting the reference benchmark of the measuring robot, the robot automatically searches for the monitoring target for measurement. The Leica TS total station, a fully automatic measuring robot (nominal angular measurement accuracy of 0.5″, ranging accuracy of ±0.6mm + 1ppm * D), is used to measure the angles and distances of each monitoring point by the full-circle observation method. The total station used has an automatic observation data acquisition software for automatic acquisition, recording, and storage of field data. All observation data should be backed up and stored. Data such as control instructions and measurement results can be interactively transmitted with the instrument in real time through wireless connection (4G communication) technology, and at the same time, regular manual geometric leveling is used for comparative monitoring. After the acquisition is completed, the collected data is rigorously adjusted to calculate the three-dimensional coordinates of each monitoring point. This measurement method reduces the instrument setup frequency and improves the measurement accuracy;

[0086] Near the airport, it is required that the height of the instrument platform should not be higher than the height limit of the specific equipment by the airport. The total station with the longest nominal measuring range is used, and the monitoring range is generally not more than 200 meters;

[0087] B. Determine the monitoring area and divide it into block grids according to the actual situation;

[0088] First, determine the overall monitoring range of the airport runway (within 3 times the tunnel excavation surface), and measure the two-dimensional coordinates of 4 corner points. Then, divide the grid according to the runway concrete slabs (5m * 5m), and expand it in Southern CASS and finally export the two-dimensional coordinates of each grid corner point.

[0089] C. Scan the monitoring area at an interval of 0.1m to measure the three-dimensional coordinates of several monitoring points;

[0090] Considering the overburden, the area within 3D (D is the shield diameter) parallel to the tunnel excavation surface is used as the monitoring area.

[0091] Considering the construction area where the monitoring project is located, the observation frequency is high, the on-site construction conditions are complex, and there are many uncertain factors, this monitoring adopts the monitoring method of benchmark points plus workstations. The control network is established in the form of a corner network. Each point in the control network is divided into benchmark points and workstations according to its use function. All points are set outside the deformation influence area, and there are no less than three. The monitoring station is selected in a relatively stable and convenient location in the construction area, and the monitoring station can simultaneously communicate with the corresponding monitoring point.

[0092] Due to the limitations of terrain and site conditions, the control points of this project are arranged in areas on both sides of the shield construction that are not affected by the construction. The benchmark points of this project are planned to be set up at three points, namely G01-G03. The benchmark points use Leica high-precision circular prisms and are set up in stable locations around the construction area that are not affected by the construction.

[0093] The benchmark point is a known point that is far away from the deformation area and is stable and reliable. It is divided into elevation benchmark points and plane benchmark points. The benchmark point should be selected at a location with a stable foundation, easy to monitor and unaffected. There should be no less than 3 benchmark points in a survey area.

[0094] The role of the benchmark is to provide a reference point so that the position of other points can be determined. By comparing with the benchmark, we can calculate the coordinates and positions of other points. The benchmark can also be used to correct the errors of instruments and equipment to improve the accuracy and reliability of measurement.

[0095] Burying of benchmark points: The benchmark point standard circular prism is installed on the observation pier of the measuring point and firmly buried by forced centering the base. In order to prevent the point from being moved and to ensure that it is not damaged during the entire monitoring process, a protective box needs to be installed if necessary to protect the benchmark point.

[0096] The workstation is also called the monitoring station, which is the location where the total station is set up. It is a control point that is not far from the monitoring point and is less likely to change. Its position should be stable and easy to monitor. During the monitoring period, the stability of the working base point should be checked regularly. The benchmark point and the workstation are only involved in calculating the coordinates of the monitoring points in the monitoring area, while the calculations in steps D and E are based on the coordinates of the monitoring points and have no direct relationship with the benchmark point and the workstation.

[0097] The stability test and analysis of the settlement benchmark shall comply with the following provisions:

[0098] (1) After the benchmark network is resurveyed, all benchmark points should be combined in pairs to calculate the difference between the height difference data after the current adjustment and the height difference data after the previous adjustment;

[0099] (2) When all calculated height differences are not greater than the limit difference calculated by the following formula, all benchmarks are considered stable:

[0100]

[0101] Where: δ——Tolerance of elevation difference (mm);

[0102] σ h ——Standard deviation of elevation (mm);

[0103] μ——Mean square error of elevation difference between survey stations corresponding to the accuracy level (mm) (in this project, it is taken as 0.3 mm);

[0104] n——Number of survey stations between two reference points.

[0105] (3) When the difference exceeds the tolerance, unstable points should be identified through analysis and judgment.

[0106] 1) Stability inspection and analysis of displacement reference points:

[0107] a. When no more than 3 displacement reference points are set for observation, the coordinate differences of the reference points after adjustment can be calculated by pairwise combination, and the reference points with obvious changes can be identified;

[0108] b. When the number of set reference points is more than 4 and it is difficult to analyze and judge unstable points using the above method, stability analysis should be carried out through statistical test methods to identify the displacement reference points with significant changes;

[0109] 2). The treatment of unstable reference points should comply with the following regulations:

[0110] a. Tolerance investigation and analysis should be carried out. If it is confirmed that it is not suitable to continue as a reference point, it should be discarded, and new reference points should be promptly supplemented and laid out;

[0111] b. The deformation measurement results of each period related to the unstable reference points should be checked and analyzed, and after excluding the influence of the unstable reference points, data processing should be carried out again.

[0112] The control network uses automated Leica TM / TS series total stations (nominal angular measurement accuracy 0.5", ranging accuracy ±0.6 mm + 1 ppm * D) and their supporting prisms. Before observation, the total station is comprehensively inspected and calibrated, and the instrument is regularly inspected and calibrated during the operation process to ensure that the compensation system and axis system correction accuracy of the total station meet the requirements.

[0113] D. Fit the coordinates of the obtained monitoring points to a plane using the linear least squares method;

[0114] For each grid quadrilateral, a plane equation is fitted using the linear least squares method. The general form of the plane equation is `z = ax + by + d`, where `a`, `b`, and `d` are undetermined coefficients. By constructing a system of linear equations and solving them, these coefficients can be obtained.

[0115] The least squares fitting plane calculation method is as follows:

[0116] The general expression for the plane equation is:

[0117] Ax+By+Cz+D=0(C≠0) (1-1)

[0118] Right now:

[0119]

[0120] remember:

[0121]

[0122] Substituting formula (1-3) into (1-2) yields formula (1-4):

[0123] z=a 0 x+a 1 y+a 2 (1-4)

[0124] For a series of n points (n ≥ 3); (x i ,y i ,z i ),i=0,1,···,n-1, we need to use these n points to fit the plane equation, that is:

[0125]

[0126] To minimize S, both sides of equation (1-4) should be 0 ,a 1 ,a 2 Find the partial derivative and set the partial derivative function to zero.

[0127] Right now:

[0128]

[0129] Rewritten into matrix form:

[0130]

[0131] Solve to get parameter a 0 , a 1 , a 2 Substitute into (1-4) and solve to obtain the plane equation.

[0132] Observational data will inevitably have gross errors. If they are not eliminated before the least squares adjustment, the results will not be optimal. Therefore, data snooping must be used to identify and eliminate outliers in the observational data to improve the accuracy and precision of parameter estimation.

[0133] The null hypothesis of the data detection method is H 0 : E(V i ) = 0, that is, the observed value L i has no gross error. Considering as the standard normal distribution statistic:

[0134]

[0135] v i —— residual (correction); the larger v i is, the greater the possibility of gross error;

[0136] σ 0 2 Q vivi —— variance; σ o —— standard deviation;

[0137] Q vivi —— the weight reciprocal of the observed value L i Perform a u-test. If |u| ≥ u

[0138] (α is taken as 0.05), then reject H α / 2 , and there may be a gross error in L 0 . i

[0139] Assuming that there is only one gross error in an adjustment system is the premise of the data detection method. Only one gross error can be found in one detection. If another gross error is to be detected, the previously found gross error must be removed first, and then the adjustment and inspection are carried out again.

[0140] E. Calculate the elevation values of the midpoints of the plates and the midpoints of the four sides to monitor the settlement change amount.

[0141] The elevation value of each plate is the Z value of the midpoint coordinate of the plate section. See Appendix Figure 2 ;

[0142] The settlement change amount this time ΔZ = the current coordinate Z - the previous coordinate Z;

[0143] The cumulative settlement change amount ΔZ = the current coordinate Z - the initial coordinate Z;

[0144] The difference in the elevation of the midpoints of the adjacent sides of adjacent plates is the step value. See Appendix Figure 2 ;

[0145] The step change amount this time = the current step value - the previous step value;

[0146] The cumulative step change amount = the current step value - the initial step value.

[0147] Figure 3 ​Schematic diagram of the monitoring platform applied to the monitoring method of this application. The above total station is connected to a control terminal, which is a computer in this embodiment. It has at least the following four functions:

[0148] a. Command the operation of the data collector;

[0149] b. Receive and store the data sent back by the collector;

[0150] c. Use a dedicated program to organize and calculate the data to form a monitoring result, which can be stored or printed out;

[0151] d. Submit the results and organize and submit the settlement data in the form of a grid plan;

[0152] Data interaction with the total station is carried out through wireless connection, including transmitting control instructions and returning measurement results. After receiving the measurement results, the computer quickly analyzes and adjusts the shield construction parameters in the tunnel to ensure that the construction meets the requirements;

[0153] The above method can achieve high-frequency scanning. Combining with the actual situation of the project construction, it is necessary to provide real-time monitoring data 4 times a day to timely reflect the progress of the propulsion. Specifically as follows:

[0154] a. Within 100m before crossing the airport, during the shield propulsion process, carry out tracking monitoring, increase the monitoring frequency, timely provide monitoring data, and optimize the construction parameters;

[0155] b. The monitoring frequency is 4 times a day when the shield arrives under normal circumstances; 1-2 times a day when the shield arrives <30m before and after; 1 time every 1-2 days when the shield arrives <50m before and after; if there are abnormalities or mutations, the number of times will be increased;

[0156] C. Start monitoring each point 50 meters before the shield cutting edge arrives. After the measuring point leaves the shield tail, strengthen the tracking monitoring of the long-term settlement, and change the monitoring frequency to 1 time per week;

[0157] In this project, the maximum cumulative settlement of the subsidence under the airport runway is only -7.16mm, and the maximum cumulative amount of misalignment is within 7mm. It has not caused any impact on the operating environment within the airport area. At the same time, this monitoring method can carry out monitoring construction under various harsh conditions. Compared with general monitoring methods, it has more advantages, is not restricted by factors such as weather and environment. At the same time, this method uses automatic monitoring by instruments, reducing the capital investment in labor for the project.

Claims

1. A non-contact airport runway settlement and misalignment automatic monitoring method, characterized in that: The method comprises: Step S1: Taking the area within the range of N times the shield diameter of the airport tunnel excavation surface as the monitoring area, setting an automatic monitoring platform next to the monitoring area, and installing a total station on the automatic monitoring platform, where N is a positive integer; Step S2: Divide the monitoring area into plate grids to obtain the two-dimensional coordinates of the corner points of each grid; Step S3: Scan the monitoring area with a total station to establish a control network, divide the points in the control network into reference points and workstations corresponding to the automatic monitoring platform, and obtain the coordinates of the reference points and the workstations, and calculate the three-dimensional coordinates of several monitoring points by the full-circle observation method and combining the two-dimensional coordinates, reference point coordinates and workstation coordinates in step S2; Step S4: Fit the obtained monitoring point coordinates to a plane using the linear least squares method, and identify and eliminate outliers in the observed data using the data detection method; Step S5: Based on the step S4, the elevation values ​​of the midpoint of the grid and the midpoints of the four sides of the grid are calculated to monitor the changes in settlement and misalignment.

2. The non-contact airport runway subsidence and runway misalignment automatic monitoring method according to claim 1 is characterized in that: The step S1 includes: N is 3 and the height of the platform is automatically monitored to be within the airport height limit.

3. The non-contact airport runway subsidence and runway misalignment automatic monitoring method according to claim 1 is characterized in that: The step S2 includes: the size of the grid is 5m×5m, and the two-dimensional coordinates of each grid corner point are derived through the South CASS on the total station.

4. The non-contact airport runway subsidence and runway misalignment automatic monitoring method according to claim 1 is characterized in that: The step S3 includes: checking the stability of the reference point by: Step S31: After the benchmark point network is re-measured, all benchmark points are combined in pairs to calculate the difference between the height difference data after adjustment in this period and the height difference data after adjustment in the previous period; Step S32: When all calculated height differences are not greater than the tolerance calculated by the following formula, all reference points are considered stable: Among them: δ represents the height difference limit; μ represents the mean error of the height difference of the corresponding accuracy level; n represents the number of observation stations between the two reference points, σ h represents the standard deviation of elevation; Step S33: When a difference exceeds the tolerance limit, the unstable point should be found through statistical testing method.

5. The non-contact airport runway subsidence and runway misalignment automatic monitoring method according to claim 1 is characterized in that: The step S4 includes: the least squares method of plane fitting calculation method is as follows: The general expression of the plane equation is Formula 1: Ax+By+Cz+D=0 (C≠0); Formula 2: Formula 3: Substituting equation 3 into equation 2, we can get equation 4: z=a0x+a1y+a2; For a series of n points: (x i ,y i ,z i ), use the n points to fit the plane equation, n is a positive integer greater than or equal to 3, i is an integer greater than or equal to 0 and less than or equal to n-1, that is: Formula 5: Take partial derivatives of both sides of equation 4 with respect to a0, a1, a2 to minimize S, and set the partial derivative function to zero, which is equation 6: Rewritten into matrix form as formula 7: Solve to obtain the parameters a0, a1, and a2, and substitute a0, a1, and a2 into equation 4 to obtain the plane equation.

6. The non-contact airport runway subsidence and runway misalignment automatic monitoring method according to claim 5 is characterized in that: The step S4 comprises: In the data detection method, the null hypothesis is H0:E(V i )=0, it is considered that the observed value L i There is no gross error, considering As a standard normal distribution statistic: Perform u test, if |u|≥u α / 2 , α is 0.05, then the original hypothesis H0 is rejected, and it is believed that L i There may be gross errors, where v i represents the residual, σ0 2 Q vivi represents the variance, σ o represents the standard deviation, Q vivi Represents the observed value L i The reciprocal of .

7. The non-contact airport runway subsidence and runway misalignment automatic monitoring method according to claim 1, characterized in that: The step S5 comprises: The elevation value of each plate grid is the Z value of the coordinates of the midpoint of the plate grid section; The current change of settlement ΔZ = current coordinate Z-previous coordinate Z; Cumulative change of settlement ΔZ = current coordinate Z-initial coordinate Z; The difference in the midpoint elevations of each adjacent edge of the adjacent plate grid is the misalignment value; The change of this error = this error value - the previous error value; Cumulative error change = current error value - initial error value.

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