Method for monitoring settlement deformation of existing railway area

Abstract

The present invention discloses an existing railway area settlement deformation monitoring method, which comprises the following steps: S1, carrying out suitability evaluation on a site selection area, and determining the installation mileage of a deformation monitoring device; s2, taking the installation mileage determined in the step S1 as a monitoring point, and installing the deformation monitoring device; s3, on the basis of an E-ADOP adaptive cut-off elevation angle rapid satellite selection algorithm, the calculation satellites are screened, and an optimal combination of the calculation satellites is obtained; s4, constructing a multi-path error model sequence of the deformation monitoring device based on a fixed star daily filtering method of a single-difference residual error, and further obtaining the geodetic height of the monitoring point; and S5, performing manual leveling on the monitoring point, and calculating an assumed elevation abnormal value to realize settlement monitoring of the monitoring point. According to the method, the Beidou positioning precision in the railway complex environment is improved, the workload of manual leveling measurement is greatly reduced, and the production cost is saved.

Description

Technical Field

[0001] The invention relates to the field of railway deformation monitoring, and in particular to a method for monitoring regional settlement deformation of an existing railway. Background Art

[0002] With the continuous growth of my country's operating mileage, the pressure of operation and maintenance is also increasing. Due to factors such as poor geological conditions, falling groundwater levels, poor railway construction quality, and long-term train operation, large-scale regional settlement along the railway or differential settlement of railway bridges and roadbeds and other structures has occurred. Long-term regional settlement will cause the rails to bear additional stress, resulting in bending, deformation or damage. On the one hand, it will limit the speed of trains, and in severe cases, it will increase the risk of train derailment, seriously threatening the safety of passengers' lives and property. In order to cope with the hidden dangers of track deformation and structural damage caused by regional settlement, the railway department needs to regularly monitor the railway infrastructure and frequently repair and maintain the tracks. Traditional manual leveling is limited by manpower, time and measuring tools, and the monitoring range is relatively small. Monitoring of large areas requires a lot of manpower and time, which greatly increases the maintenance cost.

[0003] Global Navigation Satellite System (GNSS) technology has been widely used in deformation monitoring and early warning of structures because of its all-weather and high-precision advantages and the ability to obtain three-dimensional deformation information of monitoring points in real time. With the completion of the global networking of my country's Beidou-3 satellite navigation system, Beidou satellite high-precision positioning technology has been continuously promoted in the railway industry. Beidou / GNSS deformation monitoring is a point monitoring method. By reasonably arranging the locations of Beidou monitoring stations, deformation monitoring of a larger area can be achieved. For existing railway lines, multiple Beidou monitoring equipment needs to be deployed on structures such as railway bridges and roadbeds in regional settlement areas. Usually, the site selection of Beidou monitoring equipment mainly depends on the on-site survey and evaluation of experts. The site selection is based on their own experience, historical settlement conditions and on-site conditions. Then the construction personnel transport the monitoring equipment and accessories to the installation location, complete the construction and installation on site, and realize the monitoring of railway foundation structures.

[0004] However, there are facilities such as contact network poles, sound barriers, slag walls and fences along the railway. The contact network carries high voltage current, and the railway has complex environments such as strong electromagnetic interference and strong shielding, which causes the quality of satellite observation data to decline and the multipath effect error to increase, seriously affecting the accuracy of Beidou positioning. At the same time, there are strict requirements for the installation of trackside equipment along the railway. If the installation location is unreasonable or it is damaged during use, it will interfere with the operation of the train. Summary of the invention

[0005] In order to solve the technical problems that the site selection of Beidou monitoring stations depends on on-site surveys by experts in the background technology, and the Beidou positioning accuracy is low and cannot be promoted on a large scale due to the complex railway environment, the present invention provides a method for monitoring the settlement and deformation of existing railway areas.

[0006] To this end, the present invention adopts the following technical solutions:

[0007] A method for monitoring the settlement and deformation of an existing railway area comprises the following steps:

[0008] S1, quantifying the site selection factors of the site selection location of the deformation monitoring device in the site selection area, using the hierarchical analysis decision method and the site selection factors to calculate the site suitability, and determining the installation mileage of the deformation monitoring device, wherein the deformation monitoring device includes a Beidou reference station and a Beidou monitoring station;

[0009] The site selection factors include: historical artificial leveling data, historical SAR data, geological conditions, water well distribution and railway site conditions;

[0010] S2, taking the installation mileage determined in S1 as a monitoring point and installing the deformation monitoring device;

[0011] S3, screening the satellites involved in the solution to obtain the optimal combination of satellites involved in the solution;

[0012] S4, constructing a multipath error model sequence of the deformation monitoring device based on a sidereal day filtering method of a single difference residual, and then obtaining the geodetic height of the monitoring point;

[0013] S5, performing manual leveling measurement on the monitoring point, calculating a hypothetical elevation anomaly value based on the result of S4, and realizing settlement monitoring of the monitoring point.

[0014] The historical artificial leveling data are settlement observations or CPIII measurement data along the railway line in the past 1 to 2 years;

[0015] The historical SAR data are historical archived image data within 2 years, which are used to reflect the surface deformation of the site selection area; the values ​​of the historical artificial leveling data and the historical SAR data are based on the real values;

[0016] The geological conditions are divided into 10 types according to the hardness of the strata, namely, silt layer, silty clay layer, silt layer, fine sand layer, medium sand layer, coarse sand layer, strongly weathered granite layer, medium weathered granite layer, slightly weathered granite layer and basalt layer. Values ​​are assigned according to the hardness of the strata, and the greater the hardness of the strata, the greater the value assigned.

[0017] The distribution of the water wells is as follows: according to the straight-line distance from the site to the water well, an interval is divided into 10 intervals of [0, 100], (100, 200] to (900, 1000], and the distribution of the water wells is assigned a value according to the interval. The smaller the distance represented by the interval, the larger the corresponding value.

[0018] The railway site conditions are the sum of the values ​​corresponding to the contact network poles, sound barriers, fences and fixed ends, where:

[0019] According to the distance between the selected site and the nearest contact network pole, three intervals are divided: [0,5], (5,10] and (10,15]; the greater the distance corresponding to the contact network pole distance interval, the greater the value assigned;

[0020] According to the shortest distance between the selected location and the sound barrier, there are five intervals: [0,5], (5,10], (10,15], (15,20] and (20,∞]. The larger the distance corresponding to the sound barrier distance interval, the larger the value assigned.

[0021] According to the shortest distance between the selected site and the fence, three distance intervals are divided: [0, 0.5], (0.5, 1.5], and (1.5, 3]. The larger the distance corresponding to the fence distance interval, the larger the value assigned;

[0022] Depending on whether the site selection location is at the fixed end of the bridge, if so, a value > 0 is assigned, otherwise no value is assigned or a value of 0 is assigned.

[0023] The siting factors corresponding to the geological conditions are assigned values ​​of [1 to 10] according to the hardness of the strata; if the geological conditions are other than the 10 types, they are re-arranged and assigned values ​​according to their hardness; the siting factors corresponding to the distance intervals of the water well distribution are assigned values ​​of [10 to 1] in sequence; the siting factors corresponding to the distance intervals of the contact network poles are assigned values ​​of [1, 3, 5]; the siting factors corresponding to the distance intervals of the sound barriers are assigned values ​​of [1, 2, 3, 4, 5] in sequence; the siting factors corresponding to the distance intervals of the fences are assigned values ​​of [1, 3, 5] in sequence; if the siting location is at the fixed end of the bridge, the corresponding siting factor is assigned a value of 5.

[0024] In S1, the hierarchical analysis decision method is used to compare the relative importance of multiple site selection factors, and then the relative weights are obtained, and then the site suitability S of the site selection location is calculated. p ,have:

[0025]

[0026] Where p represents the site number of the Beidou monitoring station or Beidou reference station, x i,p is the value corresponding to the i-th location factor of location p, 0≤i≤n; wi is the relative weight of the ith location factor, determined using the analytic hierarchy process; r p The value of is 0 or 1, which is used to control whether to calculate the site suitability of the site location;

[0027] S p The larger the value is, the more suitable the site location p is for placing the Beidou monitoring station. Conversely, it is suitable for placing the Beidou reference station. The Beidou monitoring station is deployed within the coverage range of the Beidou reference station.

[0028] In S3, the optimal combination of satellites involved in the solution is selected by the following formula:

[0029] E-ADOP = α·(β+ψ);

[0030] Where E-ADOP represents the extended ambiguity precision factor; α = 1 / (mT), m represents the total number of satellites; T represents the number of reference satellites; ω S is the observation weight of satellite S, ω S =sin 2 (θ S ), θ s is the altitude angle of satellite S, 1≤S≤m; j represents the satellite frequency number, 1≤j≤J; σ pj and σ φj represent the standard deviation of the satellite's carrier phase and undifferenced pseudorange, respectively.

[0031] S4 includes the following sub-steps:

[0032] S41, determining a time shift of a multipath period relative to a whole day according to orbital parameters of the satellite ephemeris in the optimal combination;

[0033] S42, obtaining the first period of GNSS data through the optimal combination determined in S3, and constructing an observation equation; then obtaining multiple periods of GNSS data for one week to calculate the mean of the baseline vector, bringing it back to the observation equation as a known solution to perform ambiguity backcalculation and rounding to obtain the integer ambiguity, and then bringing the baseline vector mean and the integer ambiguity back to the observation equation to backcalculate the first period of phase double difference observation residual dd;

[0034] S43, adding a zero mean assumption to the phase double difference observation value residual dd to perform single difference residual reconstruction, and obtaining the phase single difference observation value residual sd;

[0035] S44, use the KF-RTSS filtering method to extract the first phase multipath error model sequence sd of each satellite from the phase single difference observation residual sd obtained in S43 1 ;

[0036] S45, adjusting the time series of the multipath error model of the first period according to the time shift ΔT in S41 to obtain the multipath error model sd of the Nth period N , N>1, and then through the transformation matrix D, it is transformed from the single-difference multipath error model sequence sd of the Nth period N Converted to the Nth period double difference multipath error model sequence dd N ;

[0037] S46, obtain the Nth period of GNSS data through the deformation monitoring device set in S2, calculate the corresponding phase double difference observation value residual using the method of S42, and use the double difference multipath error model sequence dd obtained in S45 N The multipath error is eliminated; the LAMBDA algorithm is then used to solve the single-frequency single-epoch baseline to obtain the three-dimensional coordinates of the monitoring point, including: the longitude of the monitoring point, the latitude of the monitoring point and the geodetic height of the monitoring point.

[0038] The ΔT is calculated by the following formula:

[0039] ΔT = n1 × 2π / v-n2 × 86400;

[0040] Where v represents the angular velocity of the satellite, n2 represents the repetition period of the GNSS satellite, and n1 represents the number of orbits completed in n2 days.

[0041] sd is calculated by the following formula:

[0042] sd=[ω1,ω2,ω t …ω T , D] -1 [0, 0, ... 0; dd];

[0043] Among them, ω t is the observation weight of satellite t in the optimal combination, 1≤t≤T, D represents the transformation matrix, and T represents the number of reference satellites.

[0044] In S5, the settlement deformation of the monitoring point is obtained by subtracting the geodetic heights of the monitoring point at different periods obtained in step S4, thereby realizing settlement monitoring of the monitoring point.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] (1) The method of the present invention uses a hierarchical analysis decision method to evaluate the suitability of the site selection area of ​​Beidou monitoring stations and reference stations, and provides an adaptive deformation monitoring device for different types of railway structures.

[0047] (2) The method of the present invention is aimed at the complex surrounding environment of railways. Based on the E-ADOP adaptive cutoff altitude angle fast star selection algorithm, Beidou / GNSS solution satellites are selected; based on the single-difference residual sidereal day filtering method, a Beidou base station and monitoring station multipath error model is constructed to improve Beidou high-precision positioning.

[0048] (3) The method of the present invention changes the traditional site selection method that relies on on-site surveys by experts, as well as the traditional working method that requires manual large-scale leveling measurements, making the Beidou site selection more accurate and scientific. Through the deformation monitoring device, it realizes all-weather automated and intelligent Beidou safe operation monitoring, improves the Beidou positioning accuracy in complex railway environments, greatly reduces the workload of manual leveling measurements, and saves production costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 is a flow chart of the present invention;

[0050] Figure 2 Schematic diagram of site selection for BeiDou reference and monitoring stations;

[0051] Figure 3 It is a schematic diagram of a deformation monitoring device at a railway bridge in the present invention;

[0052] Figure 4 It is a schematic diagram of a deformation monitoring device at a railway roadbed in the present invention;

[0053] Figure 5 It is a flow chart of the sidereal day filtering method of the single difference residual in the present invention;

[0054] Figure 6 is a flow chart of step S4 in the present invention;

[0055] Figure 7 A schematic diagram of the result of using the method of the present invention to observe the subsidence;

[0056] Figure 8 The figure is a schematic diagram of the results of settlement observation and manual leveling verification comparison using the method of the present invention.

[0057] In the picture, 1. Beidou base station, 2. Beidou monitoring station, 3. agricultural water well, 4. settlement observation mark of bridge pier, 5. level mark. DETAILED DESCRIPTION

[0058] The present invention is further described in detail below through the accompanying drawings and embodiments.

[0059] like Figure 1 As shown, the existing railway area settlement deformation monitoring method of the present invention comprises the following steps:

[0060] S1, determine the installation mileage of the deformation monitoring device:

[0061] Quantify the site selection factors of the deformation monitoring device in the site selection area, calculate the site suitability using the analytic hierarchy process and the site selection factors, and determine the installation mileage of the deformation monitoring device;

[0062] like Figure 2 The site selection factors in a railway shown include: historical artificial leveling data, historical SAR data, geological conditions, water well distribution and railway site conditions. The deformation monitoring device includes Beidou reference station 1 and Beidou monitoring station 2.

[0063] The analytic hierarchy process (AHP) is used to compare and evaluate the relative importance of multiple site selection factors, obtain relative weights, and then calculate the site suitability S of the site selection location. p ,have:

[0064]

[0065] Where p represents the site number of the Beidou monitoring station or Beidou reference station, x i,p is the value corresponding to the i-th location factor of location p, 0≤i≤n; w i is the relative weight of the i-th location factor, determined using the analytic hierarchy process (AHP); r p The value is 0 or 1, which is used to control whether to calculate the site suitability of the site location.

[0066] S p The larger the value of is, the more suitable the site location p is for placing a Beidou monitoring station. Conversely, it is suitable for placing a Beidou reference station. The Beidou monitoring station should be located within the coverage of the Beidou reference station. When the site selection area contains multiple site selection locations, a site selection suitability comparison chart can also be constructed to intuitively reflect the site selection suitability of different site selection locations within the site selection area.

[0067] x i,p Determined by using the actual values ​​measured and the assignment method, specifically:

[0068] The historical artificial leveling data are settlement observations or CPIII measurement data along the railway line in the past 1 to 2 years;

[0069] The historical SAR data should be historical archived image data from the past 1 to 2 years, which are used to accurately reflect the recent surface deformation of the site selection area; the values ​​of historical artificial leveling data and historical SAR data shall be based on the actual values.

[0070] The geological conditions are divided into 10 types according to the hardness of the strata, including silt layer, silty clay layer, silt layer, fine sand layer, medium sand layer, coarse sand layer, strongly weathered granite layer, medium weathered granite layer, slightly weathered granite layer and basalt layer. Values ​​are assigned according to their ranking positions. The greater the hardness, the greater the value assigned, such as [1 to 10] in order. If the geological conditions are not the above 10 types, they are re-ranked and assigned according to their hardness.

[0071] The distribution of the water wells is as follows: according to the straight-line distance from the selected location to the water well 3, an interval is divided every 100 meters, and a total of 10 intervals are divided, namely [0, 100], (100, 200] to (900, 1000], and the distribution of the water wells is assigned values ​​according to the intervals. The closer the distance represented by the interval, the larger the corresponding value, such as assigning values ​​in order [10 to 1].

[0072] The railway site conditions are the sum of the values ​​corresponding to the contact network poles, sound barriers, fences and fixed ends, where:

[0073] According to the distance between the site and the nearest contact network pole, the site is divided into intervals of 5 meters, specifically divided into three intervals [0,5], (5,10] and (10,15], and the intervals are assigned values ​​[1, 3, 5] in sequence;

[0074] According to the shortest distance between the selected site and the sound barrier, an interval is divided into 5 intervals of [0,5], (5,10], (10,15], (15,20] and (20,∞], and the intervals are assigned values ​​of [1, 2, 3, 4, 5] in order;

[0075] According to the shortest distance between the site and the fence, three distance intervals are divided: [0, 0.5], (0.5, 1.5], and (1.5, 3], and the intervals are assigned values ​​[1, 3, 5] in order;

[0076] Depending on whether the site selection location is at the fixed end of the bridge, if so, a value of 5 is assigned, otherwise, a value of 0 is assigned.

[0077] Relative weight w i Use the analytic hierarchy process to determine.

[0078] In one embodiment of the present invention, the values ​​corresponding to the above five site selection factors are as follows: historical manual leveling data is 7, historical SAR data is 7, geological conditions is 3, water well distribution is 1 and railway site conditions is 5, then the size of the relative weight judgment matrix A is 5×5, and:

[0079]

[0080] In the formula, the matrix element P included in the judgment matrix A isik Indicates the importance of location factor i compared to location factor k, 0≤k≤n; In order to ensure the consistency of the judgment matrix, P ik ·P ki = 1. Then the relative weights of the five location factors are calculated to be 0.375, 0.375, 0.076, 0.027 and 0.147 respectively.

[0081] S2, for different types of railway structures, deformation monitoring devices are installed as monitoring points at the installation mileages determined in S1:

[0082] The BeiDou reference station and the BeiDou monitoring station are used to receive signals from BeiDou / GNSS solution satellites. According to the requirements for railway safety operation, the BeiDou monitoring device must be installed outside the railway bridge fence or on the ballast foot of the roadbed.

[0083] In an embodiment of the present invention:

[0084] like Figure 3 At the railway bridge location shown, the receiving antenna of the deformation monitoring device is installed outside the railway bridge fence at the installation mileage to receive Beidou / GNSS satellite signals;

[0085] The receiver of the deformation monitoring device is installed in the box girder of the railway bridge, connected to the receiving antenna through a satellite feeder, and also connected to the solar panel through a cable. The receiver is used to store Beidou / GNSS satellite data and transmit it back to the data processing center through the 4G network. The solar panel is set on the ground to provide power;

[0086] like Figure 4 The position of the railway ballast foot shown in the figure, the deformation monitoring device integrates the Beidou antenna, satellite feeder and receiver, and is installed at the railway ballast foot to receive Beidou / GNSS satellite signals and store satellite data, and then transmit it back to the data processing center through the 4G network. It is connected to the solar panel through a cable;

[0087] The solar panels are installed at the foot of the slope on the east or south side of the railway embankment, facing due south, and are used to provide power for the Beidou monitoring integrated receiver.

[0088] S3, based on the E-ADOP adaptive cut-off altitude angle fast satellite selection algorithm, screens the solution satellites to obtain the optimal combination of satellites involved in the solution;

[0089] Facing the complex surrounding environment of railways, the E-ADOP adaptive cutoff altitude angle fast satellite selection algorithm is used to select the Beidou / GNSS satellites involved in positioning solution in complex environments. Specifically, it reduces the number of visible satellites to improve the single epoch positioning efficiency and ambiguity fixation success rate, and improves the reliability and positioning accuracy of the positioning system.

[0090] E-ADOP = α·(β+ψ);

[0091] Where E-ADOP represents the extended ambiguity precision factor. The smaller its value is, the more satellites are involved in the solution and the larger the satellite elevation angle is, which means the higher the positioning accuracy of the satellite is. α = 1 / (mT), m represents the total number of satellites; T represents the number of reference satellites. ω S is the observation weight of satellite S, ω S =sin 2 (θ S ), θ s is the altitude angle of satellite S, 1≤S≤m; j represents the satellite frequency number, 1≤j≤J. σ pj and σ φj represent the standard deviation of the satellite's carrier phase and undifferenced pseudorange, respectively.

[0092] In one embodiment of the present invention, taking the L2 frequency of GPS and the B2 frequency of Beidou as examples to solve ψ, the standard deviations of the carrier phase and the non-difference pseudorange of the L2 frequency of GPS are respectively: and The corresponding values ​​of Beidou's B2 frequency are and The corresponding values ​​of B2 / L2 frequencies of dual-system Beidou / GPS are and From the above parameter values, we can get: G =14.05,ψ C =14.36 and ψ G+C =14.21, where the superscript “C” represents Beidou satellite and “G” represents GPS satellite.

[0093] S4, constructing a multipath error model sequence of the deformation monitoring device based on a sidereal day filtering method of a single difference residual, and then obtaining the geodetic height of the monitoring point;

[0094] The multipath error is caused by the fact that the Beidou monitoring receiver receives the satellite signal reflected by the surrounding reflectors such as railway sound barriers, contact network poles and fences while receiving the direct satellite signal. The two interact to form a multipath effect, which seriously affects the satellite positioning accuracy. Since the surrounding environment of the Beidou monitoring station or Beidou reference station is stable, the multipath error will fluctuate periodically with the regular operation of the satellite relative to the Beidou monitoring station or Beidou reference station; Figure 5 As shown, S4 specifically includes the following steps:

[0095] S41, determining the time shift of the multipath period relative to the whole day according to the orbital parameters of the satellite ephemeris in the optimal combination, and the time shift ΔT is calculated as follows:

[0096] ΔT = n1 × 2π / v-n2 × 86400;

[0097] Where v represents the angular velocity of the satellite, n2 represents the repetition period of the GNSS satellite, and n1 represents the number of orbits completed in n2 days.

[0098] S42, obtaining the first period of GNSS data through the optimal combination determined in S3, and constructing an observation equation; then obtaining multiple periods of GNSS data for one week to calculate the mean of the baseline vector, bringing it back to the observation equation as a known solution to perform ambiguity backcalculation and rounding to obtain the integer ambiguity, and then bringing the baseline vector mean and the integer ambiguity back to the observation equation to backcalculate the first period of phase double difference observation residual dd;

[0099] S43, add the zero mean assumption to the phase double difference observation residual dd to reconstruct the single difference residual, and obtain the phase single difference observation residual sd, which is:

[0100] sd=[ω1,ω2,ω t …ω T , D] -1 [0, 0, ... 0; dd]

[0101] Among them, ω t is the observation weight of satellite t in the optimal combination, 1≤t≤T, and D represents the transformation matrix.

[0102] S44, using the KF-RTSS filtering method, extracts the multipath error model sequence of the first period of each satellite from the phase single difference observation residual sd obtained in S43, as Figure 6 As shown, the process of KF-RTSS filtering is as follows:

[0103] S441, input phase single difference observation residual sd: [Z0, Z1, …Z l-1 , Z l ];

[0104] S442, forward denoising is performed through KF filtering to obtain [x0, x1, ...x l-1 , x l ]sequence;

[0105] S443, with x l The reverse smoothing is performed first, and the smoothing value of each step is constrained by the filtering value of the corresponding step, and the multipath error model sequence sd of the first period is obtained. 1 :

[0106] S45, adjusting the time series of the multipath error model of the first period according to the time shift ΔT in S41 to obtain the multipath error model sd of the Nth period N , N>1, and then through the transformation matrix D, it is transformed from the single-difference multipath error model sequence sd of the Nth period N Converted to the Nth period double difference multipath error model sequence dd N ,have:

[0107] dd N =D·sd N ;

[0108] S46, obtain the Nth period of GNSS data through the Beidou reference station or Beidou monitoring station set in S2, use the method of S42 to calculate the corresponding phase double difference observation value residual, and use the double difference multipath error model sequence dd obtained in S45 N Eliminate multipath errors;

[0109] The LAMBDA algorithm is then used to solve the single-frequency single-epoch baseline to obtain the three-dimensional coordinates of the monitoring point, including: the longitude of the monitoring point, the latitude of the monitoring point and the geodetic height of the monitoring point.

[0110] S5, conduct manual leveling measurement on the monitoring points, calculate the assumed elevation anomaly values, and realize settlement monitoring of the monitoring points.

[0111] refer to Figure 3 and Figure 4 The manual leveling measurement is carried out according to the second-class leveling measurement accuracy, and the measurement object is the settlement observation mark 4 of the bridge pier where the deformation monitoring device is located or the level mark 5 of the common pile of the railway roadbed deformation monitoring device.

[0112] The assumed elevation anomaly value is due to the fact that the monitoring point and the deformation monitoring device are not strictly co-pointed. The elevation anomaly value of the difference between the geodetic height obtained by the deformation monitoring device and the normal height obtained by the second-order leveling measurement is assumed, and the value is a constant. 假定，p The calculation formula is as follows:

[0113] ζ 假定，p =H 监测点大地高 , p -h 二等水准测量正常高，p ;

[0114] like Figure 7 As shown in the figure, by subtracting the geodetic heights of monitoring points at different periods, the settlement deformation of the monitoring point can be obtained, thus realizing the automatic settlement monitoring of the monitoring point. The calculation formula for the settlement deformation value of the monitoring point is as follows:

[0115]

[0116] Where N, M represent the number of periods of deformation monitoring, Δh N,M Represents the settlement deformation of the monitoring point between two periods.

[0117] In one embodiment of the present invention,

[0118] like Figure 8 As shown, the settlement deformation of the Beidou monitoring station using the method of the present invention was checked by manual second-class leveling. The comparison results showed that the average value of the difference between the two was 1.48 mm, indicating that the method has high accuracy.

Claims

1. A method for monitoring the settlement and deformation of an existing railway area, characterized in that: The following steps are involved: S1, quantifying the site selection factors of the site selection location of the deformation monitoring device in the site selection area, using the hierarchical analysis decision method and the site selection factors to calculate the site suitability, and determining the installation mileage of the deformation monitoring device, wherein the deformation monitoring device includes a Beidou reference station and a Beidou monitoring station; The site selection factors include: historical artificial leveling data, historical SAR data, geological conditions, water well distribution and railway site conditions; S2, taking the installation mileage determined in S1 as a monitoring point and installing the deformation monitoring device; S3, screening the satellites involved in the solution to obtain the optimal combination of satellites involved in the solution; S4, constructing a multipath error model sequence of the deformation monitoring device based on a sidereal day filtering method of a single difference residual, and then obtaining the geodetic height of the monitoring point; S5, performing manual leveling measurement on the monitoring point, calculating a hypothetical elevation anomaly value based on the result of S4, and realizing settlement monitoring of the monitoring point.

2. The method for monitoring the settlement and deformation of an existing railway area according to claim 1, characterized in that: The historical artificial leveling data are settlement observations or CPIII measurement data along the railway line in the past 1 to 2 years; The historical SAR data are historical archived image data within 2 years, which are used to reflect the surface deformation of the site selection area; the values ​​of the historical artificial leveling data and the historical SAR data shall be based on the actual values.

3. The method for monitoring the settlement and deformation of an existing railway area according to claim 1, characterized in that: The geological conditions are divided into 10 types according to the hardness of the strata, namely, silt layer, silty clay layer, silt layer, fine sand layer, medium sand layer, coarse sand layer, strongly weathered granite layer, medium weathered granite layer, slightly weathered granite layer and basalt layer. Values ​​are assigned according to the hardness of the strata, and the greater the hardness of the strata, the greater the value assigned. The distribution of the water wells is as follows: according to the straight-line distance from the site to the water well, an interval is divided into 10 intervals of [0, 100], (100, 200] to (900, 1000], and the distribution of the water wells is assigned a value according to the interval. The smaller the distance represented by the interval, the larger the corresponding value. The railway site conditions are the sum of the values ​​corresponding to the contact network poles, sound barriers, fences and fixed ends, where: According to the distance between the selected site and the nearest contact network pole, three intervals are divided: [0,5], (5,10] and (10,15]; the greater the distance corresponding to the contact network pole distance interval, the greater the value assigned; According to the shortest distance between the selected location and the sound barrier, there are five intervals: [0,5], (5,10], (10,15], (15,20] and (20,∞]. The larger the distance corresponding to the sound barrier distance interval, the larger the value assigned. According to the shortest distance between the selected site and the fence, three distance intervals are divided: [0, 0.5], (0.5, 1.5], and (1.5, 3]. The larger the distance corresponding to the fence distance interval, the larger the value assigned; Depending on whether the site selection location is at the fixed end of the bridge, if so, a value > 0 is assigned, otherwise no value is assigned or a value of 0 is assigned.

4. The method for monitoring the settlement and deformation of an existing railway area according to claim 3 is characterized by: The siting factors corresponding to the geological conditions are assigned values ​​of [1 to 10] according to the hardness of the strata; if the geological conditions are other than the 10 types, they are re-arranged and assigned values ​​according to their hardness; the siting factors corresponding to the distance intervals of the water well distribution are assigned values ​​of [10 to 1] in sequence; the siting factors corresponding to the distance intervals of the contact network poles are assigned values ​​of [1, 3, 5]; the siting factors corresponding to the distance intervals of the sound barriers are assigned values ​​of [1, 2, 3, 4, 5] in sequence; the siting factors corresponding to the distance intervals of the fences are assigned values ​​of [1, 3, 5] in sequence; if the siting location is at the fixed end of the bridge, the corresponding siting factor is assigned a value of 5.

5. The method for monitoring the settlement and deformation of an existing railway area according to claim 1, characterized in that: In S1, the hierarchical analysis decision method is used to compare the relative importance of multiple site selection factors, thereby obtaining relative weights, and then calculating the site suitability S of the site selection location. p ,have: Where p represents the site number of the Beidou monitoring station or Beidou reference station, x i，p is the value corresponding to the i-th location factor of the location p, 0≤i≤n; w i is the relative weight of the ith location factor, determined using the analytic hierarchy process; r p The value of is 0 or 1, which is used to control whether to calculate the site suitability of the site location; S p The larger the value is, the more suitable the site location p is for placing the Beidou monitoring station. Conversely, it is suitable for placing the Beidou reference station. The Beidou monitoring station is deployed within the coverage range of the Beidou reference station.

6. The method for monitoring the settlement and deformation of an existing railway area according to claim 1, characterized in that: In S3: The optimal combination of satellites involved in the solution is selected through the following formula: E-ADOP = α·(β+ψ); Where E-ADOP represents the extended ambiguity precision factor; α = 1 / (mT), m represents the total number of satellites; T represents the number of reference satellites; ω S is the observation weight of satellite S, ω S =sin 2 (θ S ), θ s is the altitude angle of satellite S, 1≤S≤m; j represents the satellite frequency number, 1≤j≤J; σ pj and σ φj represent the standard deviation of the satellite's carrier phase and undifferenced pseudorange, respectively.

7. The method for monitoring the settlement and deformation of an existing railway area according to claim 1 is characterized by: S4 includes the following sub-steps: S41, determining a time shift of a multipath period relative to a whole day according to orbital parameters of the satellite ephemeris in the optimal combination; S42, acquiring the first period of GNSS data through the optimal combination determined in S3, and constructing the observation equation; Then obtain multiple periods of GNSS data for one week to calculate the baseline vector mean, bring it back to the observation equation as a known solution to perform ambiguity backcalculation and round it to obtain the integer ambiguity, then bring the baseline vector mean and the integer ambiguity back to the observation equation to backcalculate the first period of phase double difference observation residual dd; S43, adding a zero mean assumption to the phase double difference observation value residual dd to perform single difference residual reconstruction, and obtaining the phase single difference observation value residual sd; S44, use the KF-RTSS filtering method to extract the first phase multipath error model sequence sd of each satellite from the phase single difference observation residual sd obtained in S43 1 ; S45, adjusting the time series of the multipath error model of the first period according to the time shift ΔT in S41 to obtain the multipath error model sd of the Nth period N , N>1, and then through the transformation matrix D, it is transformed from the single-difference multipath error model sequence sd of the Nth period N Converted to the Nth period double difference multipath error model sequence dd N ; S46, obtain the Nth period of GNSS data through the deformation monitoring device set in S2, calculate the corresponding phase double difference observation value residual using the method of S42, and use the double difference multipath error model sequence dd obtained in S45 N Eliminate multipath errors; The LAMBDA algorithm is then used to solve the single-frequency single-epoch baseline to obtain the three-dimensional coordinates of the monitoring point, including: the longitude of the monitoring point, the latitude of the monitoring point, and the geodetic height of the monitoring point.

8. The method for monitoring the settlement and deformation of an existing railway area according to claim 7 is characterized by: The ΔT is calculated by the following formula: ΔT = n1 × 2π / v-n2 × 86400; Where v represents the angular velocity of the satellite, n2 represents the repetition period of the GNSS satellite, and n1 represents the number of orbits completed in n2 days.

9. The method for monitoring regional settlement and deformation of existing railways according to claim 7, characterized in that: In S43, sd is calculated by the following formula: sd=[ω1,ω2,ω t …oh T ,D] -1 ·[0,0,…0;dd]; Among them, ω t is the observation weight of satellite t in the optimal combination, 1≤t≤T, D represents the transformation matrix, and T represents the number of reference satellites.

10. The method for monitoring the settlement and deformation of an existing railway area according to claim 1, characterized in that: In S5, the settlement deformation of the monitoring point is obtained by subtracting the geodetic heights of the monitoring point at different periods obtained in step S4, thereby realizing settlement monitoring of the monitoring point.

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