Bridge regional distributed stiffness identification method, system and storage medium based on distributed long-gauge strain envelope sensing concept considering support constraints

Abstract

The present application discloses a method, system and storage medium for identifying regional distributed stiffness of a bridge based on the concept of distributed long-gauge strain envelope sensing and considering support constraints, including the following contents: strain sensors are arranged at the bottom of the test bridge, and the calibrated moving load passes through the test bridge, and the strain sensors measure the strain influence line of the gauge unit; the strain influence line is double-integrated in time and space scales to obtain the output space-time envelope area; the real moment influence line of the gauge unit of the test bridge is obtained by superimposing and deducing according to the moment influence line of the support constraint and the moment influence line caused by the moving load, and the input space-time envelope area is obtained by double-integrating in time and space scales; the regional distributed stiffness of the gauge unit is obtained by the ratio of the input space-time envelope area to the output space-time envelope area. The present application is fast and convenient to measure, has good robustness and high precision, and can especially effectively identify the regional distributed stiffness of simply supported beams with end constraints caused by support defects.

Description

Technical Field

[0001] The present application belongs to the technical field of bridge structure health monitoring, and specifically relates to a method, system and storage medium for identifying regional distributed stiffness of bridges based on the concept of distributed long-gauge strain envelope sensing taking into account support constraints. Background Art

[0002] Bridges are important infrastructure in modern transportation networks, providing a convenient way for people to travel and transport logistics. However, bridges are exposed to harsh service environments for a long time, including climatic conditions (such as sunlight, rain, ice and snow, freeze-thaw cycles, etc.), corrosion factors (such as salt spray erosion in coastal areas), overloaded transportation, and special environmental influences such as earthquakes and strong winds, which are prone to structural damage. Bridge damage will not only shorten the service life, but may also cause serious safety accidents, resulting in loss of life and property, and economic losses. For example, bridge collapse interrupts traffic, hinders logistics transportation and emergency rescue, and may also cause environmental pollution. In order to ensure the safe service of bridges, it is of great significance to accurately evaluate the actual structural performance of bridges.

[0003] For the evaluation of the real performance of bridges, the current focus is on bridge damage identification, which evaluates the current service status of bridges by locating and quantifying the damage. Bridge damage identification mainly focuses on the following aspects: sensor-based monitoring methods, including monitoring the changes in natural frequency, vibration mode and damping ratio through vibration method, measuring stress and deformation using equipment such as strain gauges and displacement meters, and using acoustic emission method to detect crack extension or local damage inside the material; non-contact methods based on image processing, such as using high-resolution cameras for image recognition technology and drones to obtain high-definition images of inaccessible parts; data-driven intelligent recognition methods, including the application of machine learning algorithms (such as support vector machines and random forests) and deep learning algorithms (such as convolutional neural networks); and methods based on physical models and numerical simulations, using finite element analysis combined with measured data to evaluate damage status. However, these methods still have many problems in practical applications: insufficient deployment density of sensor monitoring systems may lead to the omission of local damage, and the long-term stability and durability of the equipment are challenged; image processing methods are easily disturbed by environmental factors such as light and weather, and drone detection has poor adaptability in complex environments; data-driven methods are highly dependent on training data, and are not effective in the case of small samples or noisy data, and the black box characteristics of the model make the results lack interpretability; the complexity of damage caused by multi-factor coupling makes it difficult for a single method to identify coupled damage, and non-damage factors such as environmental noise and temperature effects can easily lead to false alarms or omissions; analysis based on physical models is limited by simplified assumptions and is inconsistent with the complex state of the actual structure.

[0004] The above studies are mainly aimed at damage identification, and the main purpose is to locate damage. However, for the need to quantify damage, the accuracy and stability of the above existing technologies are relatively poor. Based on this, some scholars have carried out research on bridge stiffness identification. The research methods of bridge stiffness identification mainly focus on the analysis of bridge response under vehicle load. The researchers used strain influence line theory, fiber optic sensor technology and influence line identification method to explore the relationship between bridge stiffness and vehicle dynamic load. By establishing a bridge-vehicle system model, the influence of different vehicle speeds, weights and axles on bridge stiffness was studied, and a method of using long strain history to calculate the bridge stiffness coefficient to evaluate the degree of damage was proposed. These methods can not only effectively monitor the stiffness state of the bridge, but also be used for damage identification. In practical applications, experimental studies based on fiber optic sensors and vehicle-bridge coupling systems have verified the effectiveness of these methods. Further studies have shown that the influence line theory can simplify the model of the bridge structure and help to perform more accurate stiffness identification in complex environments. However, current research still faces some challenges, such as how to further improve the accuracy and adaptability of the model, and how to deal with environmental factors and the complex interaction between vehicles and bridges. Summary of the invention

[0005] In response to the problems existing in the prior art, this application proposes a method, system and storage medium for identifying the regional distributed stiffness of a bridge based on the concept of distributed long-scale strain envelope sensing that takes into account support constraints. The method has the advantages of fast and convenient measurement, good robustness and high accuracy, and is especially capable of effectively identifying the regional distributed stiffness of simply supported beams with end constraints caused by support defects.

[0006] In a first aspect, the present application provides a method for identifying regional distributed stiffness of a bridge based on the concept of distributed long-gauge strain envelope sensing taking into account support constraints, comprising the following steps:

[0007] S1, a distributed long-gauge strain sensor is arranged at the bottom of the test bridge, and a calibrated moving load passes through the test bridge; the distributed long-gauge strain sensor monitors multiple gauge units in the monitoring area of ​​the test bridge, and measures the strain influence line of each gauge unit;

[0008] S2, perform double integration of the strain influence line of the measured gauge length unit in the position interval of the gauge length unit in time scale and space scale to obtain the output space-time envelope area of ​​each gauge length unit;

[0009] S3, according to the design stiffness of both ends of the test bridge, the height of the neutral axis and the strain influence line of the corresponding gauge unit, the support constraint moment influence line is inverted, combined with the moment influence line caused by the moving load, the real moment influence line of the gauge unit of the test bridge is obtained by superposition and deduction, and the double integration of the time scale and space scale is performed again within the position interval of the gauge unit to obtain the input time and space envelope area of ​​each gauge unit;

[0010] S4, the regional distribution stiffness of all gauge length units is obtained by the ratio of the input space-time envelope area to the output space-time envelope area.

[0011] In a possible implementation manner of the first aspect, step S1 calculates the strain influence line of the gauge length unit using the following sub-steps:

[0012] S11, arranging distributed long gauge length strain sensors along the bottom of the test bridge, dividing the length of the gauge length unit according to the bridge test accuracy requirements; the gauge length unit includes a start node and an end node, and the start node and the end node constitute the position interval of the gauge length unit; defining the position of the start node of the i-th gauge length unit as x i , the position of the final node is x i+1 , the number of gauge units is M, i∈[1,M];

[0013] S12, the calibrated moving load passes through the test bridge;

[0014] S13, measuring and obtaining the strain influence line of each gauge length unit.

[0015] In a possible implementation manner of the first aspect, in step S11, the lengths of the gauge units at both ends of the test bridge are less than 200 mm.

[0016] In a possible implementation manner of the first aspect, in step S11, the distributed long gauge length strain sensors of the gauge length units at both ends of the test bridge are pre-stretched.

[0017] In a possible implementation of the first aspect, in step S12, the ratio of the moving load to the bridge mass is not less than 5%.

[0018] In a possible implementation of the first aspect, step S2 calculates the output spatiotemporal envelope area of ​​the gauge unit using the following sub-steps:

[0019] S21, spatial scale integration of the strain influence line of the gauge length unit:

[0020] ;

[0021] in, represents the spatial envelope area of ​​the strain influence line, and x represents the interval [x i , xi+1 ] within the position variable, represents the strain influence line corresponding to position x, Indicates the gauge unit length;

[0022] S22, yes Perform time scale integration to obtain the output space-time envelope area:

[0023] ;

[0024] in, represents the output space-time envelope area, , T represents the time for the moving load to pass through the bridge, t∈[0,T].

[0025] In a possible implementation manner of the first aspect, step S3 uses the following sub-steps to deduce the input space-time envelope area of ​​the gauge unit:

[0026] S31, inversion to obtain the support constraint moment influence line:

[0027] ;

[0028] ;

[0029] in, , Respectively represent the bearing restraint bending moment influence lines at the left and right ends of the bridge; , Respectively represent the design stiffness of the left and right ends of the bridge; , They represent the strain influence lines of the gage length units at the left and right ends of the bridge respectively; , Respectively represent the neutral axis heights of the left and right ends of the bridge;

[0030] S32, obtain the true bending moment influence line of the i-th gauge unit of the test bridge through the superposition principle:

[0031] ;

[0032] in, represents the true bending moment influence line of the i-th gauge unit of the test bridge, l represents the span of the bridge, represents the influence line of the bending moment caused by the moving load p;

[0033] ;

[0034] p represents the weight of the moving load;

[0035] S33, the spatial scale integration of the real bending moment influence line of the i-th gauge unit of the test bridge is obtained:

[0036] ;

[0037] in, Represents the spatial envelope area of ​​the true bending moment influence line, x t represents the position of the moving load at time t; represents the distributed strain influence line at the left end of the bridge, Indicates the distributed strain influence line at the right end of the bridge;

[0038] S34, yes Perform time scale integration and rearrange the formula to obtain the input space-time envelope area:

[0039] ;

[0040] in, represents the input space-time envelope area in gauge units, represents the input space-time envelope area caused by the moving load, represents the input space-time envelope area caused by the support constraint at the left end of the bridge, represents the input space-time envelope area caused by the support constraint at the right end of the bridge;

[0041] ;

[0042] , ;

[0043] , .

[0044] In a possible implementation of the first aspect, step S4 calculates the regional distribution stiffness of each gauge length unit using the following formula:

[0045] EI i = { [ A s , t I ] 1 [ A s , t o ] 1 ...... [ A s , t I ] i [ A s , t o ] i ...... [ A s , t I ] M [ A s , t o ] M } .

[0046] In a second aspect, the present application provides a system for executing the bridge regional distributed stiffness identification method, comprising:

[0047] Distributed long gauge length strain sensors are arranged at the bottom of the test bridge to monitor multiple gauge length units within the monitoring area of ​​the test bridge and measure the strain influence line of each gauge length unit;

[0048] The output space-time envelope area calculation unit performs double integration of the time scale and space scale on the strain influence line of the measured gauge length unit within the position interval of the gauge length unit to obtain the output space-time envelope area of ​​each gauge length unit;

[0049] Input the space-time envelope area calculation unit, calculate the bearing constraint moment influence line according to the design stiffness of both ends of the test bridge, the neutral axis height and the strain influence line of the corresponding gauge unit, combine the moment influence line caused by the moving load, and superimpose and deduce the real moment influence line of the gauge unit of the test bridge. Perform double integration of the time scale and space scale again within the position interval of the gauge unit to obtain the input space-time envelope area of ​​each gauge unit;

[0050] The regional distribution stiffness calculation unit calculates the input space-time envelope area and the output space-time envelope area of ​​all the gauge length units of the test bridge in turn, and obtains the regional distribution stiffness of all the gauge length units through the ratio of the input space-time envelope area to the output space-time envelope area.

[0051] In a third aspect, the present application provides a computer-readable storage medium having computer program instructions stored thereon, and the computer program instructions, when executed by a processor, implement the bridge area distributed stiffness identification method.

[0052] Compared with the prior art, this application has the following beneficial effects:

[0053] 1. This application has the advantages of full bridge coverage, convenient measurement, good stability, and strong anti-interference ability to the external environment. It can not only accurately locate the damage, but also quantify the damage. It has a good prospect of being widely used in the identification of actual bridge stiffness.

[0054] 2. This application takes into account the semi-rigid constraints caused by bearing anomalies, and is particularly suitable for evaluating the safe service status of bridges that have been in service for many years. It can accurately estimate the true structural performance of the bridge under abnormal end bearing conditions, thereby ensuring the safe service status of the bridge. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A flow chart of a bridge regional distribution stiffness identification method provided for an embodiment of the present application;

[0056] Figure 2 A three-dimensional numerical model for identifying regional distributed stiffness of a bridge provided in an embodiment of the present application;

[0057] Figure 3 A distributed strain-displacement time history curve provided in an embodiment of the present application;

[0058] Figure 4 An end constraint strain-displacement time history curve provided in an embodiment of the present application;

[0059] Figure 5 An end restraint bending moment time history curve provided in an embodiment of the present application;

[0060] Figure 6 The bending stiffness identification result of each gauge length unit under a healthy working condition provided in an implementation manner of the present application;

[0061] Figure 7 The bending stiffness identification result error of each gauge length unit under a healthy working condition provided by an implementation method of the present application;

[0062] Figure 8 A noise sensitivity error analysis of the bending stiffness identification results of each gauge length unit under a healthy working condition provided in an embodiment of the present application;

[0063] Fig. 9 The present application provides an embodiment of the present invention provides a bending stiffness identification result of each gauge length unit under a damage condition. DETAILED DESCRIPTION

[0064] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings.

[0065] It should be clear that the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0066] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application are also intended to include plural forms, unless the context clearly indicates other meanings.

[0067] In a first aspect, the present application provides a method for identifying regional distributed stiffness of a bridge based on the concept of distributed long-gauge strain envelope sensing taking into account support constraints, comprising the following steps:

[0068] S1, a distributed long gauge strain sensor is firmly laid out at the bottom of the test bridge, and a calibrated moving load passes slowly and uniformly through the test bridge; the strain sensor monitors the gauge unit in the monitoring area of ​​the test bridge, and measures the strain influence line of the gauge unit; the specific steps are as follows:

[0069] S11, firmly adhere and arrange distributed long gauge length strain sensors along the entire length of the bottom of the bridge; divide the length of the gauge length unit according to the bridge test accuracy requirements, and the gauge length unit includes a start node and an end node, which constitute the position interval of the gauge length unit; define the position of the start node of the i-th gauge length unit as xi , the position of the final node is x i+1 , the number of gauge units is M, i∈[1,M]; preferably, the length of the gauge units at both ends of the bridge should be less than 200 mm, and the sensors of the gauge units at both ends should be appropriately pre-stretched;

[0070] S12, the calibrated moving load passes through the test bridge slowly and uniformly; preferably, the vehicle-bridge mass ratio of the moving load weight to the bridge weight is not less than 5%, and the vehicle speed is less than 5 km / h;

[0071] S13, measuring the strain influence line of the gauge unit of the test bridge; illustratively, the strain influence line of the gauge unit is obtained by using a grating demodulator in combination with a data acquisition terminal.

[0072] S2, double integration of the strain influence line of the measured gauge unit in time scale and space scale within the position interval of the gauge unit to obtain the output space-time envelope area of ​​the gauge unit; specifically including the following contents:

[0073] S21, spatial scale integration of the strain influence line of the gauge length unit:

[0074] ;

[0075] in, represents the spatial envelope area of ​​the strain influence line, and x represents the interval [x i , x i+1 ] within the position variable, represents the strain influence line at position x, Indicates the gauge unit length;

[0076] S22, yes Perform time scale integration to obtain the output space-time envelope area:

[0077] ;

[0078] in, represents the output space-time envelope area, , T represents the time for the moving load to pass through the bridge, t∈[0,T].

[0079] S3, according to the design stiffness of the two ends of the test bridge, the height of the neutral axis and the strain influence line of the corresponding gauge unit, the support constraint moment influence line is inverted, combined with the moment influence line caused by the moving load, the real moment influence line of the gauge unit of the test bridge is obtained by superposition and deduction, and the double integration of the time scale and space scale is performed again within the position interval of the gauge unit to obtain the input time and space envelope area of ​​the gauge unit; specifically, it includes the following contents:

[0080] S31, the support constraint moment influence line is obtained by inversion using the following two equations:

[0081] ;

[0082] ;

[0083] in, , Respectively represent the bearing restraint bending moment influence lines at the left and right ends of the bridge; , Respectively represent the design stiffness of the left and right ends of the bridge; , They represent the strain influence lines of the gage length units at the left and right ends of the bridge respectively; , Respectively represent the neutral axis heights of the left and right ends of the bridge;

[0084] S32, based on the above-mentioned bearing constraint bending moment influence line, combined with the bending moment influence line caused by the moving load, the real bending moment influence line of the starting node of the i-th gauge length unit is obtained by superposition principle as the real bending moment influence line of the i-th gauge length unit of the test bridge:

[0085] ;

[0086] in, represents the true bending moment influence line of the i-th gauge unit of the test bridge, l represents the span of the bridge, represents the influence line of the bending moment caused by the moving load p;

[0087] ;

[0088] p represents the weight of the moving load;

[0089] S33, the spatial scale integration of the gauge length unit by the bending moment influence line is obtained:

[0090] ;

[0091] in, represents the space envelope area of ​​the true bending moment influence line, x t represents the position of the moving load p at time t; Indicates the distributed strain influence line at the left end, Indicates the distributed strain influence line at the right end;

[0092] S34, yes Integrate over time to get the input space-time envelope area:

[0093] ;

[0094] in, represents the input space-time envelope area in gauge units; represents the input space-time envelope area caused by the moving load, ; represents the input space-time envelope area caused by the left end support constraint, ( ); represents the input space-time envelope area caused by the right end support constraint,

[0095] ( ).

[0096] S4, through the above steps S1-S3, the input time-space envelope area and the output time-space envelope area of ​​all the gauge units of the test bridge are calculated in sequence, and the regional distribution stiffness of all the gauge units is obtained by the ratio of the input time-space envelope area to the output time-space envelope area; specifically, the following contents are included:

[0097] The regional distribution stiffness of each gauge length unit is calculated using the following formula:

[0098] EI i = { [ A s , t I ] 1 [ A s , t o ] 1 ...... [ A s , t I ] i [ A s , t o ] i ...... [ A s , t I ] M [ A s , t o ] M } ;

[0099] Where i represents the number of the gauge unit.

[0100] In a second aspect, the present application provides a system for executing the bridge regional distributed stiffness identification method, comprising:

[0101] Distributed long gauge length strain sensors are arranged at the bottom of the test bridge to monitor multiple gauge length units within the monitoring area of ​​the test bridge and measure the strain influence line of each gauge length unit;

[0102] The output space-time envelope area calculation unit performs double integration of the time scale and space scale on the strain influence line of the measured gauge length unit within the position interval of the gauge length unit to obtain the output space-time envelope area of ​​each gauge length unit;

[0103] Input the space-time envelope area calculation unit, calculate the bearing constraint moment influence line according to the design stiffness of both ends of the test bridge, the neutral axis height and the strain influence line of the corresponding gauge unit, combine the moment influence line caused by the moving load, and superimpose and deduce the real moment influence line of the gauge unit of the test bridge. Perform double integration of the time scale and space scale again within the position interval of the gauge unit to obtain the input space-time envelope area of ​​each gauge unit;

[0104] The regional distribution stiffness calculation unit calculates the input space-time envelope area and the output space-time envelope area of ​​all the gauge length units of the test bridge in turn, and obtains the regional distribution stiffness of all the gauge length units through the ratio of the input space-time envelope area to the output space-time envelope area.

[0105] It should be understood that the division of the processing units in the above system is only a division of logical functions, and in actual implementation, they can be fully or partially integrated into one physical entity, or they can be physically separated. In addition, the processing units in the system can be implemented in the form of a processor calling software; for example, the system includes a processor, the processor is connected to a memory, and instructions are stored in the memory. The processor calls the instructions stored in the memory to implement any of the above methods or implement the functions of the processing units of the system, wherein the processor is a general-purpose processor, such as a central processing unit or a microprocessor, and the memory is a memory within the system or a memory outside the system.

[0106] In a third aspect, the present application provides a computer-readable storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement the steps of the bridge regional distributed stiffness identification method;

[0107] For example, the above can be achieved Figure 1 The steps of the bridge regional distributed stiffness identification method shown in .

[0108] Computer readable storage media can be tangible devices that can hold and store instructions used by instruction execution devices. Computer readable storage media can be, for example, but not limited to, electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the above.

[0109] The computer program instructions used to perform the operations of the present application may be source code or object code written in any combination of one or more programming languages, and the computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server.

[0110] The anti-interference capability of this application is mainly reflected at the sensor level and algorithm level;

[0111] Sensor level: Distributed long-gauge strain sensors demonstrate significant anti-interference capabilities against external responses and environmental factors through their continuity and distributed measurement characteristics. This technology uses optical fiber sensing along the line to achieve multi-point data collection, reducing the impact of local environmental changes on the overall measurement results. At the same time, it relies on optical signal transmission to avoid electromagnetic interference problems and can still operate stably in strong interference environments. In addition, the excellent weather resistance and corrosion resistance of optical fiber materials, as well as the application of sensitivity adjustment and signal processing technology, enable it to effectively distinguish the effects of external load responses and coupling with environmental factors;

[0112] Algorithm level: The interference of the external environment on the monitoring signal is mainly manifested as the superposition of random noise, including the combined influence of complex factors such as temperature gradient, humidity change and electromagnetic fluctuation; the noise reduction method based on spatiotemporal envelope processing proposed in this application constructs a random noise suppression mechanism in the form of double integration by smoothing in the time domain and combining multi-point signal fusion in the spatial domain; effectively utilizes the redundant information of the signal in the time and space dimensions to achieve deep suppression of noise interference, thereby significantly improving the accuracy and robustness of signal extraction.

[0113] In order to verify the feasibility and effectiveness of the present application, the following embodiment uses a three-dimensional numerical model to simulate the identification of the regional distribution stiffness of the bridge. The span of the bridge model in this embodiment is 4 meters, which is divided into 20 sub-segments, each with a length of 0.2 meters. Figure 2 As shown, the test section is the middle 14 sections, numbered 1 to 14, and these test units are used to evaluate the performance of the bridge in healthy and damaged states.

[0114] The cross section of the bridge adopts a wing-expanded box structure, with specific dimensions of 0.2 meters in width, 0.1 meters in height, 0.025 meters in web thickness, and 0.025 meters in flange thickness. In order to ensure the rationality and applicability of the structure, the material of this bridge model is steel with an elastic modulus of 206,000 MPa. In order to simulate the actual boundary conditions, an unknown constrained bending moment is applied to one end of the bridge model, which simulates the actual constraint on the rotation of the bridge at the end of the bridge. In addition, a moving load of 6000N is applied to the bridge model to simulate the stress condition of the bridge. Figure 3 is the distributed strain-displacement time history curve of a typical test unit in this embodiment, Figure 4 is the end constraint strain-displacement time history curve, Figure 5 is the end restraint moment displacement time history curve obtained by inversion; it should be noted that, Figure 3 and Figure 4 In the figure, the vertical axis "strain" is a dimensionless physical quantity. Since the strain is small, Figure 3 and Figure 4 They were scaled down respectively.

[0115] During the numerical analysis, in order to make the simulation results more consistent with the actual situation, 3%, 5%, 10% and 15% random noise were added to the simulation model. The introduction of this noise effectively improves the robustness of the model and better simulates the error range of the actual bridge during the monitoring process. The test was carried out under two conditions: the first condition is the healthy state of the bridge, that is, the stiffness of all units remains at the original value; the second condition is the bridge in the damaged state, in which the stiffness loss of the 8th gauge unit reaches 20%. Through the tests of these two conditions, it is shown that the stiffness identification method of this application can effectively evaluate the performance of the bridge in the healthy state and the damaged state respectively.

[0116] The data analysis results are as follows Figures 6 to 9 As shown in the figure, the analysis shows that the method proposed in this application can accurately identify the health status and damage status of the bridge. In all test cases, the identification error is controlled within 4%, which verifies the high accuracy and reliability of the method in bridge performance evaluation. Therefore, the method has broad application prospects and can provide effective technical support for the structural health monitoring and maintenance of actual bridges.

Claims

1. A bridge regional distributed stiffness identification method based on the concept of distributed long-gauge strain envelope sensing considering support constraints, characterized in that: The following steps are involved: S1, a distributed long-gauge strain sensor is arranged at the bottom of the test bridge, and a calibrated moving load passes through the test bridge; the distributed long-gauge strain sensor monitors multiple gauge units in the monitoring area of ​​the test bridge, and measures the strain influence line of each gauge unit; S2, perform double integration of the strain influence line of the measured gauge length unit in the position interval of the gauge length unit in time scale and space scale to obtain the output space-time envelope area of ​​each gauge length unit; S3, according to the design stiffness of both ends of the test bridge, the height of the neutral axis and the strain influence line of the corresponding gauge unit, the support constraint moment influence line is inverted, combined with the moment influence line caused by the moving load, the real moment influence line of the gauge unit of the test bridge is obtained by superposition and deduction, and the double integration of the time scale and space scale is performed again within the position interval of the gauge unit to obtain the input time and space envelope area of ​​each gauge unit; S4, the regional distribution stiffness of all gauge length units is obtained by the ratio of the input space-time envelope area to the output space-time envelope area.

2. The bridge regional distribution stiffness identification method according to claim 1, characterized in that: In step S1, the strain influence line of the gauge length unit is calculated using the following sub-steps: S11, arranging distributed long gauge length strain sensors along the bottom of the test bridge, dividing the length of the gauge length unit according to the bridge test accuracy requirements; the gauge length unit includes a start node and an end node, and the start node and the end node constitute the position interval of the gauge length unit; defining the position of the start node of the i-th gauge length unit as x i , the position of the final node is x i+1 ; i∈[1,M], M represents the number of gauge units; S12, the calibrated moving load passes through the test bridge; S13, measuring and obtaining the strain influence line of each gauge length unit.

3. The bridge regional distribution stiffness identification method according to claim 2 is characterized in that: In step S11, the length of the gauge units at both ends of the test bridge is less than 200 mm.

4. The bridge regional distribution stiffness identification method according to claim 2, characterized in that: In step S11, the distributed long gauge length strain sensors of the gauge length units at both ends of the test bridge are pre-stretched.

5. The method for identifying regional distribution stiffness of a bridge according to claim 2, characterized in that: In step S12, the ratio of the moving load to the bridge mass is not less than 5%.

6. The method for identifying regional distribution stiffness of a bridge according to claim 1, characterized in that: In step S2, the output space-time envelope area of ​​the gauge unit is calculated using the following sub-steps: S21, spatial scale integration of the strain influence line of the gauge length unit: ； in, represents the spatial envelope area of ​​the strain influence line, and x represents the interval [x i , x i+1 ] within the position variable, represents the strain influence line corresponding to position x, Indicates the gauge unit length; S22, yes Perform time scale integration to obtain the output space-time envelope area: ； in, represents the output space-time envelope area, , T represents the time for the moving load to pass through the bridge, t∈[0,T].

7. The method for identifying regional distribution stiffness of a bridge according to claim 6, characterized in that: In step S3, the input space-time envelope area of ​​the gauge unit is derived using the following sub-steps: S31, inversion to obtain the support constraint moment influence line: ； ； in, , Respectively represent the bearing restraint bending moment influence lines at the left and right ends of the bridge; , Respectively represent the design stiffness of the left and right ends of the bridge; , They represent the strain influence lines of the gage length units at the left and right ends of the bridge respectively; , Respectively represent the neutral axis heights of the left and right ends of the bridge; S32, obtain the true bending moment influence line of the i-th gauge unit of the test bridge through the superposition principle: ； in, represents the true bending moment influence line of the i-th gauge unit of the test bridge, l represents the span of the bridge, represents the influence line of the bending moment caused by the moving load p; ； p represents the weight of the moving load; S33, the spatial scale integration of the real bending moment influence line of the i-th gauge unit of the test bridge is obtained: ； in, Represents the spatial envelope area of ​​the true bending moment influence line, x t represents the position of the moving load at time t; represents the distributed strain influence line at the left end of the bridge, Indicates the distributed strain influence line at the right end of the bridge; S34, yes Perform time scale integration and rearrange the formula to obtain the input space-time envelope area: ； in, represents the input space-time envelope area of ​​the gauge unit, represents the input space-time envelope area caused by the moving load, represents the input space-time envelope area caused by the support constraint at the left end of the bridge, represents the input space-time envelope area caused by the support constraint at the right end of the bridge; ； ， ； ， 。 8. The method for identifying regional distribution stiffness of a bridge according to claim 7, characterized in that: Step S4 uses the following formula to calculate the regional distribution stiffness of each gauge unit: 。 9. A system for executing the bridge regional distribution stiffness identification method according to any one of claims 1 to 8, characterized in that: include: Distributed long gauge length strain sensors are arranged at the bottom of the test bridge to monitor multiple gauge length units within the monitoring area of ​​the test bridge and measure the strain influence line of each gauge length unit; The output space-time envelope area calculation unit performs double integration of the time scale and space scale on the strain influence line of the measured gauge length unit within the position interval of the gauge length unit to obtain the output space-time envelope area of ​​each gauge length unit; Input the space-time envelope area calculation unit, calculate the bearing constraint moment influence line according to the design stiffness of both ends of the test bridge, the neutral axis height and the strain influence line of the corresponding gauge unit, combine the moment influence line caused by the moving load, and superimpose and deduce the real moment influence line of the gauge unit of the test bridge. Perform double integration of the time scale and space scale again within the position interval of the gauge unit to obtain the input space-time envelope area of ​​each gauge unit; The regional distribution stiffness calculation unit calculates the input space-time envelope area and the output space-time envelope area of ​​all the gauge length units of the test bridge in turn, and obtains the regional distribution stiffness of all the gauge length units through the ratio of the input space-time envelope area to the output space-time envelope area.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the method for identifying the regional distributed stiffness of a bridge as described in any one of claims 1 to 8 is implemented.

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