GNSS-based rail viaduct deformation monitoring method and system

Abstract

A GNSS-based rail viaduct deformation monitoring method and system, specifically comprising the following steps: Step 1: deploying GNSS reference point equipment along the rail viaduct; Step 2: installing the mobile GNSS measuring point equipment on the first empty train of rail transit; Step 3: obtaining the real-time position of the empty train and deformation response data of the rail viaduct at the corresponding moment when the first empty train passes through the rail viaduct; Step 4: transmitting the deformation monitoring data to the monitoring system, analyzing and processing the data to evaluate the safety of the bridge structure.

Description

Technical Field

[0001] The present invention relates to the technical field of bridge monitoring, and in particular to a method and system for monitoring deformation of a track viaduct based on GNSS. Background Art

[0002] Rail viaducts are extensive, long-distance, long-standing, and operate in harsh environments, posing significant safety risks to traffic. Currently, there is a lack of effective, low-cost inspection and monitoring methods for comprehensive, real-time assessment of their condition. Furthermore, rail transit experiences short daily downtimes, requiring manual inspections, which are labor-intensive, time-consuming, and costly, and also present blind spots and operational safety risks. Therefore, new, convenient, fast, and reliable monitoring and assessment technologies are urgently needed. These technologies, integrated into monitoring systems, can achieve periodic, full-coverage monitoring of rail viaducts, ensuring their proper operation and providing crucial technical support for the safe operation of rail transit.

[0003] The Global Navigation Satellite System (GNSS), also known as the Global Navigation Satellite System, is an airborne radio navigation and positioning system that can provide users with all-weather three-dimensional coordinates, velocity, and time information at any location on the Earth's surface or in near-Earth space. The International Committee on Global Navigation Satellite Systems (ICG) has announced the world's four major satellite navigation system suppliers, including China's BeiDou Navigation Satellite System (BDS), the United States' Global Positioning System (GPS), Russia's GLONASS, and the European Union's Galileo Navigation Satellite System (GALILEO). Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention proposes a GNSS-based method and system for monitoring the deformation of railway viaducts using a GNSS system to measure the structural deformation of railway viaducts. This method obtains real-time deformation information of the bridge structure affected by train loads, transmits the collected data to a monitoring system for integration, processing, and display, establishes a reliable assessment method for evaluating bridge safety, sets early warning standards or models, and ensures the safe operation of rail transit. The specific technical solution is as follows:

[0005] A GNSS-based method for monitoring deformation of a track viaduct comprises the following specific steps:

[0006] Step 1: Deploy GNSS reference point equipment in open areas along the railway viaduct;

[0007] Step 2: The mobile GNSS measurement point equipment is installed on the first empty rail transit train;

[0008] Step 3: The first empty train passes through the track viaduct, and the real-time position of the first empty train and the deformation response data of the track viaduct at the corresponding moment are obtained;

[0009] Step 4: Transmit the deformation monitoring data to the monitoring system and analyze and process the data to evaluate the safety of the bridge structure.

[0010] Preferably, the GNSS monitoring device selects a measurement frequency of 20 Hz or more and a measurement accuracy of less than 1 mm.

[0011] Preferably, the GNSS reference point device and the mobile GNSS measuring point device are Beidou devices.

[0012] As a preference: the step three is specifically as follows:

[0013] 3.1. GNSS base station measurement observation value: The base station receives satellite signals and measures its own position information;

[0014] 3.2. Mobile GNSS device measurement observation value: The mobile GNSS device receives satellite signals and measures its own position information;

[0015] 3.3. Differential calculation: The observation values ​​of the mobile GNSS device are differentially calculated with the observation values ​​of the reference station to eliminate errors, including satellite clock error and ionospheric error;

[0016] 3.4. Calculate relative coordinates: Finally calculate the relative coordinates of the mobile GNSS device relative to the base station;

[0017] 3.5. Calculate absolute coordinates: Since the location of the base station is known, the accurate absolute coordinates of the mobile GNSS device are calculated using relative coordinates;

[0018] 3.6. The collected monitoring data is sent to the control center through the Internet of Things. After gross error elimination and resolution, the control center obtains the corrected monitoring data, thereby obtaining more accurate location information and monitoring data.

[0019] As an example, the step 4 is as follows:

[0020] First, a safety envelope evaluation method is used. Based on real-time monitoring data of bridges, the principle of data envelopment analysis is used to extract characteristic indicators of load effect changes that represent the structural state. These indicators are then compared with the threshold envelope interval composed of theoretically calculated values ​​of the corresponding structural physical parameters to achieve bridge structural safety evaluation.

[0021] Use monitoring data to conduct vehicle-bridge coupled vibration analysis, determine traffic impact evaluation indicators, set deformation thresholds under train action or constant load, and implement traffic impact evaluation of rail transit bridges;

[0022] The specification requires that the vertical deflection of the beam caused by the vertical static and live loads of the train should not be greater than 1 / 600 of the calculated span. If the measured change in deflection is less than the calculated deflection under the most unfavorable superposition of live load and temperature load, it means that the structure is in a safe state. The vertical deformation takes into account the influence of live load and temperature, and the load effect envelope limit is carried out according to the following formula:

[0023] L max1 =L 列车max +L 温度max

[0024] L min1 =L 列车min +L 温度min

[0025] Among them, L max1 is the upper limit of the envelope; L min1 is the lower limit of the envelope; L 列车max is the maximum deflection value caused by train load; L 列车min is the minimum deflection value caused by train load; L 温度max is the maximum deflection value caused by temperature; L 温度min is the minimum deflection value caused by temperature;

[0026] Based on historical bridge monitoring data, long-term deflection changes are predicted in the future, thereby providing reliable warning thresholds for graded warnings. By integrating the rail train loads and position information borne by the bridge, integrating real-time environmental conditions, and considering structural performance degradation, the graded warning thresholds for deflection are determined in conjunction with threshold setting specifications. This graded warning is used to limit the safety assessment of rail viaduct bridges.

[0027] L max2 =L max1 *α

[0028] L min2 =L min1 *α

[0029] α=η+x

[0030] Among them, L max2 L is the upper limit of the graded warning threshold; min2 is the lower limit of the graded warning threshold; α is the safety factor, which is determined by the verification coefficient and considering a certain redundancy; η is the verification coefficient; x is the redundancy;

[0031] Secondly, a calibration safety factor is introduced to conduct statistical analysis and assess the safety of bridge structures. The first empty train is used to conduct a rapid load test on the bridge to obtain the bridge's calibration factor. If the calibration factor is stable, it indicates that the bridge is stable and the structural performance has not significantly degraded. If the calibration factor continues to decrease or suddenly changes, it indicates that the structural performance has significantly degraded or other unexpected conditions have occurred, requiring further on-site inspection. A rapid load test plan for the first empty train is designed, and the bridge's calibration factor is calculated based on the structural deformation response.

[0032]

[0033] Where: η-calibration coefficient; S e -Deformation value measured under the action of the first empty train; S s - Theoretical calculated deformation value under the action of the first empty train; S s is the theoretical calculated value of the displacement of the control section under static load, and the measured S e It is the measured displacement value at a certain moment during the train's travel. Therefore, we statistically analyze the calibration coefficients obtained during the train's travel to test their stability and thus assess the safety status of the bridge.

[0034] Based on the accumulation of long-term monitoring data, a system is established based on the actual monitoring load conditions. The calibration coefficients at different times and locations are statistically analyzed and compared. The system automatically analyzes whether the calibration coefficients are stable to evaluate the structural degradation under long-term loads.

[0035] As a preferred option: establish a reliable assessment method based on the data analysis, safety assessment and early warning modules in the monitoring system, set early warning standards or models, and enter reasonable thresholds calculated based on various factors into the database. When the sensor data is transmitted to the monitoring system in real time, it is compared with the threshold and the calibration coefficient is checked. When the early warning threshold is reached or the calibration coefficient is abnormal, an alarm will be automatically triggered to notify relevant personnel, helping them make reasonable maintenance and management decisions in a timely manner to ensure the safe operation of the rail viaduct. The early warning content includes: issuing, adjusting and canceling early warning information, real-time and automatic early warning methods, and a multi-indicator and multi-level early warning system;

[0036] During the bridge's operational phase, by setting early warning values ​​for various control indicators, automated bridge safety checks and assessments are implemented based on monitoring data. This system also implements closed-loop management of early warning information through daily management mechanisms. Data statistics and chart reports are automatically generated based on monitoring, testing, early warning, and maintenance management.

[0037] A GNSS-based railway viaduct deformation monitoring system is provided with a sensor module for measuring bridge load parameters, environmental parameters, and structural response;

[0038] A data acquisition and transmission module is provided to synchronously collect and transmit sensor data, ensuring data quality and no distortion;

[0039] A data processing and management module is provided for processing, querying, storing and managing bridge monitoring data;

[0040] A data analysis, safety warning and evaluation module is set up for real-time online data display, data analysis, safety warning and evaluation.

[0041] Preferably, the sensor module is composed of load and environment monitoring, overall structural static and dynamic response monitoring, and local structural response monitoring sensors; the data acquisition and transmission module is composed of data acquisition equipment, data transmission equipment and cables, and data acquisition and transmission software; the data processing and management module is composed of data preprocessing, a central database, and a data query and management software system.

[0042] The beneficial effects of the present invention are as follows: It is usually necessary to monitor deformation at multiple measuring points on a railway viaduct for analysis, which requires multiple GNSS monitoring devices to perform measurements. When the first empty train on the track with fixed GNSS monitoring devices passes through the railway viaduct, N measuring points that require analysis can be selected for monitoring data extraction and analysis. This is equivalent to simplifying the N GNSS monitoring devices fixed on the bridge into a single mobile GNSS monitoring device, plus a reference point device, achieving low-cost monitoring.

[0043] The deformation information of the bridge structure affected by train loads is obtained in real time, and the collected data is transmitted to the monitoring system for integration, processing and display. An assessment method is established to evaluate the safety of the bridge, and an early warning is sent when the structure is abnormal to ensure the safe operation of rail transit. The method of the present invention is used to achieve accurate analysis and precise assessment results. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a schematic diagram of the structure of the present invention;

[0045] Figure 2 It is a schematic diagram of the process of the present invention;

[0046] Figure 3 This is a functional diagram of the deformation monitoring system interface in the present invention;

[0047] Figure 4 This is a graded warning diagram of the mid-span section deflection of a certain span of the track viaduct in the present invention. DETAILED DESCRIPTION

[0048] The preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby making a clearer and more precise definition of the protection scope of the present invention.

[0049] like Figure 1 and Figure 2 Figure 1 shows a GNSS-based movable deformation monitoring method for a railway viaduct, with the following specific steps:

[0050] Step 1: GNSS reference point equipment was deployed in open areas along the railway viaduct to ensure stable signal data transmission, such as building rooftops. This provides better signal reception and improved measurement accuracy. To ensure monitoring accuracy, GNSS requires a measurement frequency of at least 20Hz and an accuracy of less than 1mm. To meet these requirements while ensuring data security, the Beidou satellite navigation system was selected.

[0051] Step 2: The mobile GNSS measuring point equipment is fixedly installed at the front of the first empty rail transit train. The measuring point must be reliable and stable. Given the daily empty train test run of the first empty train, a clear train load can be determined. This first empty train test is equivalent to a rapid load test. Leveraging the high precision and real-time performance of Beidou GNSS, the real-time position of the first empty train and the deformation response of the viaduct at that moment under the load of the first empty train can be determined.

[0052] Step 3: GNSS (Global Navigation Satellite System) RTK (Real-Time Kinematic) positioning technology is a very effective high-precision positioning and measurement method. By calculating the difference between the mobile GNSS device and the base station, some errors can be eliminated to obtain more accurate position information. The specific steps include:

[0053] 3.1. Base station measurement observation values: The base station also receives satellite signals and measures its own position information.

[0054] 3.2. Mobile GNSS device measurement observation value: Mobile GNSS device receives satellite signals and measures its own position information.

[0055] 3.3. Differential calculation: The observation values ​​of the mobile GNSS device are differentially calculated with the observation values ​​of the base station to eliminate some errors, such as satellite clock error and ionospheric error.

[0056] 3.4. Calculate relative coordinates: Finally calculate the relative coordinates of the mobile GNSS device relative to the base station.

[0057] 3.5. Calculate absolute coordinates: Since the location of the base station is known, the accurate absolute coordinates of the mobile GNSS device can be calculated using the relative coordinates.

[0058] The collected monitoring data is sent to the control center via the Internet of Things. After eliminating gross errors and solving the problems, the control center obtains the corrected monitoring data, thereby obtaining more accurate location information and monitoring data. It is usually necessary to monitor the deformation of multiple measuring points on the track viaduct for analysis, which requires multiple GNSS monitoring devices to perform the measurements. When the first empty train on the track with fixed GNSS monitoring equipment passes through the track viaduct, the N measuring points that need to be analyzed can be selected for monitoring data extraction and analysis. This is equivalent to simplifying the N GNSS monitoring devices fixed on the bridge into one mobile GNSS monitoring device, plus a reference point device. This "1+N" model can achieve low-cost monitoring.

[0059] Step 4: Transmit the collected deformation monitoring data to the monitoring system via the mobile communication network.

[0060] The monitoring system adopts BIM information collaboration technology with data sharing, statistical analysis, data mining and other functions. Figure 3 , integrating multi-dimensional information data. To establish a BIM-based monitoring system, we first need to establish a BIM model, clarify the model level, coding rules, and splitting principles, and establish a three-dimensional refined BIM model of the bridge, which mainly includes the bridge structure model and the sensor model, both of which are established through Revit families. Then, through the shared parameter settings of the family, the actual physical information and geometric information of the bridge structure and sensors are input into the BIM model for association. After that, in the monitoring system, various data such as the bridge structure and sensors are integrated into a unified model. Based on the Autodesk Forge software platform, a JAVA program is used to develop a visualization platform that integrates the display of BIM models, loading monitoring points, and linking real-time monitoring data, realizing three-dimensional visualization management and information retrieval of monitoring information.

[0061] The API interface is used to realize the interaction between the finite element software and the monitoring system. The train load, position and other information are extracted from the monitoring system and input into the finite element software through the API interface. The theoretical deformation of the bridge at the corresponding moment when the first empty train passes through the track viaduct is simulated and calculated in real time. After the calculation is completed, the results are fed back to the monitoring system. The safety of the bridge is evaluated by comparing the structural response of the clear real-time position of the first empty train with the calculation results of the finite element software simulation. Based on the correlation between information and model in BIM information collaboration technology, the finite element software verification analysis results and distribution characteristics can also be visualized in the BIM model in the form of cloud maps, so as to further intuitively understand the local and overall structural performance and health status of the bridge.

[0062] By analyzing the data collected by sensors and generating chart reports, the combination of chart reports and 3D visualization can provide more comprehensive and efficient support for the formulation of next steps such as bridge monitoring, early warning, maintenance, and resource management.

[0063] Furthermore, a reliable evaluation method is established in the data analysis, safety warning and evaluation modules of the monitoring system, and the evaluation method is divided into two guarantees.

[0064] The first is to adopt the safety envelope evaluation method: 1. Based on the real-time monitoring data of the bridge, using the principle of data envelopment analysis, extract the characteristic index of the load effect change that characterizes the structural state, and compare it with the threshold envelope interval composed of the theoretical calculated values ​​of the corresponding structural physical parameters to achieve the safety evaluation of the bridge structure. The monitoring data can also be used to conduct vehicle-bridge coupling vibration analysis, determine the driving impact evaluation index, set the threshold value of deformation under the action of the train or the action of the constant load, and realize the driving impact evaluation of the rail transit bridge. The specification requires that the vertical deflection of the beam caused by the vertical static and live loads of the train should not be greater than 1 / 600 of the calculated span. If the measured change in deflection is less than the most unfavorable calculated deflection under the action of live load and temperature load, it means that the structure is in a safe state. The vertical deformation mainly considers the influence of live load and temperature, and the load effect envelope limit is carried out according to the following formula:

[0065] L max1 =L 列车max +L 温度max

[0066] L min1 =L 列车min +L 温度min

[0067] Among them, L max1 is the upper limit of the envelope; L min1 is the lower limit of the envelope; L 列车max is the maximum deflection value caused by train load; L 列车min is the minimum deflection value caused by train load; L 温度max is the maximum deflection value caused by temperature; L 温度min is the minimum deflection value caused by temperature.

[0068] 2. Based on the historical monitoring data of the bridge, the long-term deflection change in the future can be predicted, thereby providing a reliable warning threshold for graded warning. The threshold calculated by superimposing the envelopes of each most unfavorable working condition is almost impossible to achieve in actual conditions. Therefore, it is necessary to determine the graded warning threshold of deflection based on the rail train load and position information borne by the bridge, the real-time environmental conditions, and the structural performance degradation, combined with the threshold setting specifications. The safety assessment of the rail viaduct bridge is limited by the graded warning (see Figure 4 ).

[0069] L max2 =L max1 *α

[0070] L min2 =L min1 *α

[0071] α=η+x

[0072] Among them, L max2 L is the upper limit of the graded warning threshold; min2 is the lower limit of the graded warning threshold; α is the safety factor, which is determined by the verification coefficient and considering a certain redundancy; η is the verification coefficient; and x is the redundancy.

[0073] Secondly, a calibration coefficient is introduced to statistically analyze and assess bridge structural safety. Rail transit viaducts have more specific load inputs than municipal or highway bridges. The first unloaded train rapid load test of the bridge was conducted to obtain the bridge's calibration coefficient. A stable calibration coefficient indicates a stable bridge state and no significant structural degradation. A continuously decreasing or sudden change in the calibration coefficient indicates significant structural degradation or other unforeseen circumstances, necessitating further on-site inspection. A plan was designed for the first unloaded train rapid load test, and the calibration coefficient of the bridge was calculated based on the structural deformation response.

[0074]

[0075] Where: η-calibration coefficient; S e -Deformation value measured under the action of the first empty train; S s - Theoretical calculated deformation value under the action of the first empty train; S s is the theoretical calculated value of the displacement of the control section under static load, and the measured S e It is the measured displacement value at a certain moment during the train's travel. Therefore, we statistically analyze the calibration coefficients obtained during the train's travel to test their stability and thus assess the safety status of the bridge.

[0076] Based on the accumulation of long-term monitoring data, a system is established based on the actual monitoring load conditions. The calibration coefficients at different times and locations are statistically analyzed and compared. The system automatically analyzes whether the calibration coefficients are stable to evaluate the structural degradation under long-term loads.

[0077] Furthermore, a reliable evaluation method is established based on the data analysis, safety assessment and early warning modules in the monitoring system, early warning standards or models are set, and reasonable thresholds calculated based on various factors are entered into the database. When the sensor data is transmitted to the monitoring system in real time, it is compared with the threshold and the calibration coefficient is checked. If the early warning threshold is reached or the calibration coefficient is abnormal, an alarm will be automatically issued to notify relevant personnel, helping them make reasonable maintenance and management decisions in a timely manner to ensure the safe operation of the rail viaduct. The early warning content mainly includes:

[0078] Release, adjust and cancel early warning information, real-time and automatic early warning methods, multi-indicator and multi-level early warning system.

[0079] Refer to the post-warning processing flow Figure 2 During the bridge's operational phase, by setting early warning values ​​for various control indicators, automated bridge safety checks and assessments are implemented based on monitoring data. This system also implements closed-loop management of early warning information through daily management mechanisms. Data statistics and chart reports are automatically generated based on monitoring, testing, early warning, and maintenance management.

[0080] The GNSS-based movable deformation monitoring system for rail viaducts adopted in this implementation is equipped with a sensor module, a data acquisition and transmission module, a data processing and management module, and a data analysis and safety warning and evaluation module.

[0081] The sensor module is composed of load and environment monitoring, overall structural static and dynamic response monitoring, and local structural response monitoring sensors, which can measure bridge load parameters, environmental parameters, and structural responses.

[0082] The data acquisition and transmission module is composed of data acquisition equipment, data transmission equipment and cables, and data acquisition and transmission software, which can realize the synchronous acquisition and transmission of sensor data, and ensure data quality and no distortion; the data processing and management module is composed of data preprocessing, central database, data query and management software and hardware, which can realize the processing, query, storage and management of bridge monitoring data; the data analysis and safety warning and evaluation module can realize the functions of real-time online display of data, data analysis, safety warning and evaluation. The data at this stage can include automated monitoring data and manual inspection data, see Figure 2 .

[0083] Example 1

[0084] In order to illustrate the technical effect of the present invention, the present invention uses a certain elevated rail dedicated bridge as the monitoring object for long-term monitoring of deflection. The project team intends to use the Beidou satellite navigation system to monitor the deformation of the bridge. The deformation monitoring section selects the monitoring section in the middle of a span. Taking the five-day data from February 20, 2024 to February 24, 2024 as an example, the maximum deflection deformation measured by the GNSS equipment when the first empty train of each day passes through the middle section of a span of the rail bridge is extracted from the monitoring system. The train load, position, and ambient temperature at the corresponding time are input into the finite element software through the API interface to automatically calculate and feedback the theoretical calculation results, as follows:

[0085]

[0086] Tiered warning threshold setting: The first-level warning threshold is calculated by superimposing the envelopes of each most unfavorable operating condition. However, this scenario is often impossible in reality, so this project uses a tiered warning system to limit bridge safety assessments. The second-level warning threshold is set by combining a verification coefficient with reference to threshold setting standards, while also considering structural performance degradation and providing a certain amount of redundancy.

[0087] In this project, [L min1 , L max1 ] Calculated by the theoretical model, it is [-24.8, 17.6]. The average value of the five-day verification coefficient data is about 0.74, the sample standard deviation is about 0.03, and the redundancy x is 5% of the verification coefficient η.

[0088] L max2 =L max1 *(η+x)=13.8

[0089] L min2 =L min1 *(η+x)=-19.4

[0090] The standard deviation of the calibration coefficient samples is approximately 0.03. In the present invention, when the standard deviation of the calibration coefficient is less than 0.05, the calibration coefficient is considered to be stable. The above measured values ​​are all within the graded warning threshold range, and the calibration coefficient is stable, so it can be judged that the bridge is in a safe state.

Claims

1. A method for monitoring deformation of a railway viaduct based on GNSS, characterized in that: The specific steps are: Step 1: Deploy GNSS reference point equipment in open areas along the railway viaduct; Step 2: The mobile GNSS measurement point equipment is installed on the first empty rail transit train; Step 3: The first empty train passes through the track viaduct, and the real-time position of the first empty train and the deformation response data of the track viaduct at the corresponding moment are obtained; 3.

1. GNSS base station measurement observation value: The base station receives satellite signals and measures its own position information; 3.

2. Mobile GNSS device measurement observation value: The mobile GNSS device receives satellite signals and measures its own position information; 3.

3. Differential calculation: The observation values ​​of the mobile GNSS device are differentially calculated with the observation values ​​of the reference station to eliminate errors, including satellite clock error and ionospheric error; 3.

4. Calculate relative coordinates: Finally calculate the relative coordinates of the mobile GNSS device relative to the base station; 3.

5. Calculate absolute coordinates: Since the location of the base station is known, the accurate absolute coordinates of the mobile GNSS device are calculated using relative coordinates; 3.

6. The collected monitoring data is sent to the control center through the Internet of Things. After gross error elimination and resolution, the control center obtains the corrected monitoring data, thereby obtaining more accurate location information and monitoring data. Step 4: Transmit the deformation monitoring data to the monitoring system and analyze and process the data to assess the safety of the bridge structure; First, a safety envelope evaluation method is used. Based on real-time monitoring data of bridges, the principle of data envelopment analysis is used to extract characteristic indicators of load effect changes that represent the structural state. These indicators are then compared with the threshold envelope interval composed of theoretically calculated values ​​of the corresponding structural physical parameters to achieve bridge structural safety evaluation. Use monitoring data to conduct vehicle-bridge coupled vibration analysis, determine traffic impact evaluation indicators, set deformation thresholds under train action or constant load, and implement traffic impact evaluation of rail transit bridges; The specification requires that the vertical deflection of the beam caused by the vertical static and live loads of the train should not be greater than 1 / 600 of the calculated span. If the measured change in deflection is less than the calculated deflection under the most unfavorable superposition of live load and temperature load, it means that the structure is in a safe state. The vertical deformation takes into account the influence of live load and temperature, and the load effect envelope limit is carried out according to the following formula: L max1 =L 列车max +L 温度max L min1 =L 列车min +L 温度min Among them, L max1 is the upper limit of the envelope; L min1 is the lower limit of the envelope; L 列车max is the maximum deflection value caused by train load; L 列车min is the minimum deflection value caused by train load; L 温度max is the maximum deflection value caused by temperature; L 温度min is the minimum deflection value caused by temperature; Based on historical bridge monitoring data, long-term deflection changes are predicted in the future, thereby providing reliable warning thresholds for graded warnings. By integrating the rail train loads and position information borne by the bridge, integrating real-time environmental conditions, and considering structural performance degradation, the graded warning thresholds for deflection are determined in conjunction with threshold setting specifications. This graded warning is used to limit the safety assessment of rail viaduct bridges. L max2 =L max1 *a L min2 =L min1 *a a=n+ x Among them, L max2 L is the upper limit of the graded warning threshold; min2 is the lower limit of the graded warning threshold; α is the safety factor, which is determined by the verification coefficient and considering a certain redundancy; η is the verification coefficient; x is the redundancy; Secondly, a calibration safety factor is introduced to conduct statistical analysis and assess the safety of bridge structures. The first empty train is used to conduct a rapid load test on the bridge to obtain the bridge's calibration factor. If the calibration factor is stable, it indicates that the bridge is stable and the structural performance has not significantly degraded. If the calibration factor continues to decrease or suddenly changes, it indicates that the structural performance has significantly degraded or other unexpected conditions have occurred, requiring further on-site inspection. A rapid load test plan for the first empty train is designed, and the bridge's calibration factor is calculated based on the structural deformation response. Where: η-calibration coefficient; S e -Deformation values ​​measured under the action of the first empty train; S s -Theoretically calculated deformation value under the action of the first empty train; S s is the theoretical calculated value of the displacement of the control section under static load, and the measured S e It is the measured displacement value at a certain moment during the train's travel. Therefore, we statistically analyze the calibration coefficients obtained during the train's travel to test their stability and thus assess the safety status of the bridge. Based on the accumulation of long-term monitoring data, a system is established based on the actual monitoring load conditions. The calibration coefficients at different times and locations are statistically analyzed and compared. The system automatically analyzes whether the calibration coefficients are stable to evaluate the structural degradation under long-term loads.

2. The GNSS-based railway viaduct deformation monitoring method according to claim 1, characterized in that: The GNSS measuring point equipment selects a measurement frequency of more than 20 Hz and a measurement accuracy within 1 mm.

3. The GNSS-based railway viaduct deformation monitoring method according to claim 1, characterized in that: The GNSS reference point equipment and mobile GNSS measuring point equipment are Beidou equipment.

4. The GNSS-based railway viaduct deformation monitoring method according to claim 1, characterized in that: Based on the data analysis, safety assessment and early warning modules in the monitoring system, a reliable assessment method is established, early warning standards or models are set, and reasonable thresholds calculated by integrating various factors are entered into the database. When the sensor data is transmitted to the monitoring system in real time, it is compared with the threshold and the calibration coefficient is checked. If the early warning threshold is reached or the calibration coefficient is abnormal, an alarm will be automatically triggered to notify relevant personnel, helping to make reasonable maintenance and management decisions in a timely manner to ensure the safe operation of the rail viaduct. The early warning content includes: issuing, adjusting and canceling early warning information, real-time and automatic early warning methods, and a multi-indicator and multi-level early warning system; During the bridge operation phase, by setting early warning values ​​for various control indicators, automated bridge safety inspection and assessment alarms are implemented based on monitoring data, and closed-loop management of early warning information is achieved based on daily management mechanisms. Based on monitoring, detection, early warning, and maintenance management, data statistical reports are automatically output and graphic reports are generated.

5. The system for monitoring deformation of a railway viaduct based on GNSS according to any one of claims 1 to 3, characterized in that: A sensor module is provided for measuring bridge load parameters, environmental parameters, and structural responses; A data acquisition and transmission module is provided to synchronously collect and transmit sensor data, ensuring data quality and no distortion; A data processing and management module is provided for processing, querying, storing and managing bridge monitoring data; A data analysis, safety warning and evaluation module is set up for real-time online data display, data analysis, safety warning and evaluation.

6. The system according to claim 5, characterized in that: The sensor module is composed of load and environment monitoring, overall structural static and dynamic response monitoring and local structural response monitoring sensors; the data acquisition and transmission module is composed of data acquisition equipment, data transmission equipment and cables, and data acquisition and transmission software; the data processing and management module is composed of data preprocessing, central database, and data query and management software system.

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