Space-time checking and reproduction method for bridge response information

Abstract

The invention provides a bridge response information space-time checking and reproducing method, which comprises the following steps of: obtaining a data correlation of each measuring point based on the fact that structural response data obtained by bridge detection has spatial completeness; measuring the bridge structure static response when the bridge is detected to be only subjected to dead load and temperature at the moment; acquiring a data trend baseline of the detection point between the current detection and the last detection; obtaining response time sequence data based on the fact that the structural response data obtained by bridge monitoring has time completeness; acquiring a data trend baseline of the monitoring point between the last detection moments; checking a baseline abnormal trend of the monitoring data; checking a monitoring base line; obtaining monitoring data after baseline correction; and data space-time reproduction of each detection point is carried out. The method aims at solving the technical problems that the time domain of detection data is incomplete and the space of monitoring data is incomplete, the limited bridge operation and maintenance data is utilized to the maximum extent to perceive response information of a bridge structure with the maximum efficiency, and the infrastructure management and maintenance capacity is enhanced.

Description

[Technical field]

[0001] The present invention relates to the technical field of intelligent bridge detection and monitoring, and in particular to a method for spatiotemporal verification and reproduction of bridge response information. [Background technology]

[0002] Bridge inspection and bridge health monitoring are two means of obtaining bridge structure response information. During bridge inspection, the measurement points for observing structural responses are relatively comprehensive, and the obtained structural response space has good completeness. However, the inspection is carried out in different periods with a long interval, and there is a time gap in the data between the two inspection moments, that is, the inspection data has time incompleteness.

[0003] Bridge monitoring involves installing sensors and data storage systems at response measuring points, which can continuously collect structural response information of the measuring points. However, bridge monitoring needs to consider hardware costs and data storage scale, resulting in limited monitoring points. The monitoring data is difficult to reflect the spatial characteristics of the structural response, that is, the detection data is spatially incomplete, and the monitoring data may be affected by various factors, resulting in abnormal changes in long-term trends, causing data errors.

[0004] Obviously, only by coupling the detection data with the monitoring data can the complete spatiotemporal reproduction of the bridge structure response be achieved and the service status of the bridge be effectively grasped. Therefore, two problems must be solved:

[0005] (1) Use the detection data to correct the possible long-term abnormal trends in the monitoring data;

[0006] (2) Using the spatial correlation principle of bridge response, the time-intermittent data at different measuring points are reproduced in a coherent time series. [Summary of the invention]

[0007] The purpose of the present invention is to overcome the deficiencies of the above-mentioned prior art and to provide a method for spatiotemporal verification and reproduction of bridge response information, which aims to solve the technical problems in the prior art that detection data needs to be corrected relative to detection data and different measuring points cannot be reproduced coherently.

[0008] To achieve the above object, the present invention proposes a method for spatiotemporal verification and reproduction of bridge response information, comprising the following steps:

[0009] S1: The structural response data obtained based on bridge inspection has spatial completeness, and the data correlation relationship of each measuring point can be obtained;

[0010] S2: Determine the static response of the bridge structure when the bridge is tested at this moment and is only subjected to constant load and temperature without other loads; obtain the static response of the bridge structure when the bridge was tested last time and was only subjected to constant load and temperature without other loads;

[0011] S3: Obtain the data trend baseline of the detection point in step S2 between the current detection and the last detection;

[0012] S4: The structural response data obtained based on bridge monitoring is time-complete, and the response time series data with time continuity at a certain structural measurement point can be obtained;

[0013] S5: Obtain the data trend baseline of the monitoring point between the current detection time and the last detection time;

[0014] S6: Check the abnormal trend of the baseline of the monitoring data. If there is a long-term abnormal change trend in the monitoring baseline, it is necessary to determine whether the monitoring trend baseline needs to be checked based on the detection trend baseline;

[0015] S7: Perform monitoring baseline calibration to obtain the calibrated monitoring response data under constant load-temperature and the monitoring response data under constant load-temperature of the last test;

[0016] S8: Obtain monitoring data after baseline correction;

[0017] S9: Using the structural response data of a certain monitoring point and the response correlation coefficients between the measurement points, the time and space reproduction of each detection measurement point is performed.

[0018] As a preferred method, the measurement points of bridge detection in S1 are relatively complete, usually covering the measurement points of the monitoring system, which can express the spatial law of the bridge section. The load experiment in bridge detection can obtain the response information of each measurement point with spatial completeness. Select a certain detection and monitoring overlapping measurement point A, and perform regression analysis on the data of other detection measurement points with it to obtain the correlation coefficient vector [A 1 ,A 2 ,A 3 ,...,A n-1 ,A n ].

[0019] As a preferred embodiment, the static response of the bridge structure when the bridge is tested in S2 and S3 and subjected only to the constant load and temperature without other loads is determined, and the static response C of the test at this moment is taken as b Compared with the static response C measured in the last test s Connect the data by straight lines to obtain the data baseline between the two detection periods. According to the sampling interval of the bridge health monitoring system, construct the data points on the detection data baseline. If the constructed point plus the two end points C s and C b There are m data points in total, denoted by C s C 1 , remember C b C m , then the data vector C of the detection baseline = [C 1 ,C2 ,C 3 ,...,C m-1 ,C m ].

[0020] As a preference, the monitoring data vector M in this period in S4 and S5 is M=[M 1 ,M 2 ,M 3 ,...,M m-1 ,M m ], the constant load-temperature response formed by the constant load and temperature of the monitoring data during this period is extracted using a digital signal processing algorithm as H = [H 1 ,H 2 ,H 3 ,...,H m-1 ,H m ], the monitoring static response H at this moment m Compared with the monitoring static response H at the last detection 1 Connect the data by straight lines to obtain the monitoring data baseline for the period. According to the sampling interval of the bridge health monitoring system, construct the data points on the monitoring data baseline. If the constructed points plus the two end points H 1 and H m There are m data points in total, denoted by H 1 For J 1 , note H m For J m , then the data vector of the monitoring baseline is J = [J 1 ,J 2 ,J 3 ,...,J m-1 ,J m ].

[0021] Preferably, in S6, the detection baseline C is taken as the actual value, and the monitoring baseline J is taken as the value to be evaluated, and the relative average error E between the two is calculated. If the relative average error does not exceed x%, it means that the monitoring baseline does not need to be calibrated. If the relative average error exceeds x%, it means that calibration is required.

[0022] As a preferred embodiment, in S7, the detection static response C at this moment is b Compared with the monitoring static response H at the last detection 1 Connect the data by straight lines to obtain the corrected baseline of the monitoring data for this period. According to the sampling interval of the bridge health monitoring system, construct the data points on the baseline of the monitoring data. If the constructed points plus the two end points H 1 and C b There are m data points in total, denoted by H 1 For X 1 , remember C b For X m, then the modified monitoring baseline data vector is X=[X 1 ,X 2 ,X 3 ,...,X m-1 ,X m ].

[0023] As a preferred embodiment, in S8, the original monitoring data vector M is first subtracted from the constant load-temperature response H in the monitoring data before verification to obtain a zero-mean fluctuation data vector B=MH=[M 1 -H 1 ,M 2 -H 2 ,M 3 -H 3 ,...,M m-1 -H m-1 ,M m -H m ]=[B 1 ,B 2 ,B 3 ,...,B m-1 ,B m ]; then subtract the baseline J before correction from the constant load-temperature response H to obtain the baseline-free static response Q = HJ = [H 1 -J 1 ,H 2 -J 2 ,H 3 -J 3 ,...,H m-1 -J m-1 ,H m -J m ]=[Q 1 ,Q 2 ,Q 3 ,...,Q m-1 ,Q m ]; Finally, superimpose B, Q and the corrected baseline X to obtain the corrected monitoring data h = [h 1 ,h 2 ,h 3 ,...,h m-1 ,h m ].

[0024] As a preferred embodiment, if the monitoring data of the detection and monitoring overlap measurement point A in S9 is h=[h 1 ,h 2 ,h 3 ,...,h m-1 ,h m ], the data of the remaining detection points are h and [A 1 ,A 2 ,A 3 ,...,An-1 ,A n ]The coefficients are multiplied together, that is, A 1 h,A 2 h,A 3 h,...,A n-1 h,A n h.

[0025] Preferably, the calculation formula of the relative average error E is:

[0026]

[0027] Compared with the prior art, the method for spatiotemporal verification and reproduction of bridge response information provided by the present invention has the following beneficial effects:

[0028] (1) Reproduction of the spatiotemporal characteristics of bridge response: By combining the spatial completeness of bridge inspection data and the temporal continuity of monitoring data, the present invention can reconstruct spatiotemporal complete bridge response data, which can more comprehensively reflect the working status of the bridge and is the key to intelligent bridge maintenance based on inspection and monitoring data;

[0029] (2) Good technical applicability: The present invention is not limited to a specific regression method, interpolation method or signal processing method, and can adapt to the differential response laws caused by differences in bridge structure, material, environment and other factors. It can flexibly select the corresponding sub-method according to specific needs and has wide applicability;

[0030] (3) Information multiplication of limited measuring point information is achieved: the present invention can spread the time continuity of the response information of a limited number of monitoring measuring points to the entire spatial cross section, so that the missing time-series coherent data can be filled, and the utilization efficiency of bridge operation and maintenance information can be maximized based on the fusion of inspection and monitoring data.

[0031] The features and advantages of the present invention will be described in detail through embodiments in conjunction with the accompanying drawings.

Brief Description of the Drawings

[0032] Figure 1 The figure is a flow chart of the algorithm of the method of the present invention.

[0033] Figure 2 The present invention provides detection and monitoring points for obtaining bridge structure response information.

[0034] Figure 3 This is a schematic diagram of the data correlation between two detection measurement points and one detection monitoring overlapping measurement point.

[0035] Figure 4 It is the detection baseline and monitoring baseline of the same measuring point.

[0036] Figure 5To detect the monitoring overlap points, the monitoring data of the previous detection moment is covered.

[0037] Figure 6 In order to detect the monitoring overlap points, the monitoring data at the time of this detection is covered.

[0038] Figure 7 It is the monitoring data of the coincident measuring point between two detection times.

[0039] Figure 8 It is the time series data of another measuring point supplemented based on the coincident measuring point data and the correlation between the measuring points.

[0040] Fig. 9 It is the time series data of another measuring point supplemented based on the coincident measuring point data and the correlation between the measuring points. [Specific implementation method]

[0041] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is further described in detail below through the accompanying drawings and embodiments. However, it should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the scope of the present invention. In addition, in the following description, the description of known structures and technologies is omitted to avoid unnecessary confusion of the concept of the present invention.

[0042] In the description of the present invention, it should be noted that when an element is referred to as being "fixed to" or "disposed on" another element, it may be directly on the other element or indirectly on the other element. When an element is referred to as being "connected to" another element, it may be directly connected to the other element or indirectly connected to the other element.

[0043] In the description of the present invention, it should be noted that the terms "center", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, or the positions or positional relationships in which the invention product is usually placed when in use, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", "third" and the like are only used to distinguish descriptions, and cannot be understood as indicating or implying relative importance. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined. "Several" means one or more, unless otherwise clearly and specifically defined.

[0044] In the description of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0045] See also Figures 1 to 9 , the technical solution of the present invention is described in detail.

[0046] The present invention is a method for spatiotemporal verification and reproduction of bridge response information based on detection and monitoring data coupling, and the method specifically comprises the following steps:

[0047] Step 1: Obtain the data correlation between each measuring point. The measuring points of bridge inspection are relatively complete, usually covering the measuring points of the monitoring system, which can express the spatial law of the bridge section. The load experiment in bridge inspection can obtain the response information of each measuring point with spatial completeness. Select a certain overlapping measuring point A for inspection and monitoring, and perform regression analysis on the data of other inspection measuring points with it to obtain the correlation coefficient vector [A 1 ,A 2 ,A 3 ,...,A n-1 ,A n ].

[0048] In step 1, the regression analysis is not limited to a certain regression formula or regression method. In step 1, only the proportional correlation between measuring points is taken as an example. The correlation parameters between different measuring points are treated specifically for different bridges and different regression modeling methods in actual work.

[0049] Step 2: Obtain the data trend baseline of the test point between the current test and the last test. Determine the static response of the bridge structure when the bridge is tested without other loads and only subjected to constant load and temperature. b Compared with the static response C measured in the last test s Connect the data by straight lines to obtain the data baseline between the two detection periods. According to the sampling interval of the bridge health monitoring system, construct the data points on the detection data baseline. If the constructed point plus the two end points C s and C b There are m data points in total, denoted by C s C 1 , remember C b C m , then the data vector C of the detection baseline = [C1 ,C 2 ,C 3 ,...,C m-1 ,C m ].

[0050] Among them, in step 2, linear interpolation is used to reconstruct the data points so that the data baseline is not distorted due to the interpolation function.

[0051] Step 3: Obtain the data trend baseline of the monitoring point between the current detection time and the last detection time. The monitoring data vector M in this period is [M 1 ,M 2 ,M 3 ,...,M m-1 ,M m ], and the constant load-temperature response (static response) formed by the constant load and temperature of the monitoring data during this period is extracted using a digital signal processing algorithm as H = [H 1 ,H 2 ,H 3 ,...,H m-1 ,H m ], the monitoring static response H at this moment m Compared with the monitoring static response H at the last detection 1 Connect the data by straight lines to obtain the monitoring data baseline for the period. According to the sampling interval of the bridge health monitoring system, construct the data points on the monitoring data baseline. If the constructed points plus the two end points H 1 and H m There are m data points in total, denoted by H 1 For J 1 , note H m For J m , then the data vector of the monitoring baseline is J = [J 1 ,J 2 ,J 3 ,...,J m-1 ,J m ].

[0052] In step 3, linear interpolation is used for data point reconstruction, so that the data baseline is not distorted due to the interpolation function. The method for extracting static response of monitoring data is not limited to a specific signal processing method, and wavelet, EMD or other methods can be used.

[0053] Step 4: Check the abnormal trend of the baseline of the monitoring data. The monitoring baseline may have a long-term abnormal change trend. It is necessary to determine whether the monitoring baseline needs to be checked based on the detection baseline. The detection baseline C is taken as the actual value and the monitoring baseline J is taken as the value to be evaluated. The relative average error E between the two is calculated. If the relative average error does not exceed x%, it means that the monitoring baseline does not need to be checked. If the relative average error exceeds x%, it means that it needs to be checked.

[0054] In step 4, the relative average error E is calculated as:

[0055]

[0056] Step 5: Perform monitoring baseline calibration (i.e., monitoring data needs to be corrected). b Compared with the monitoring static response H at the last detection 1 Connect the data by straight lines to obtain the corrected baseline of the monitoring data for this period. According to the sampling interval of the bridge health monitoring system, construct the data points on the baseline of the monitoring data. If the constructed points plus the two end points H 1 and C b There are m data points in total, denoted by H 1 For X 1 , remember C b For X m , then the modified monitoring baseline data vector is X=[X 1 ,X 2 ,X 3 ,...,X m-1 ,X m ].

[0057] Among them, in step 5, linear interpolation is used for data point reconstruction so that the data baseline is not distorted due to the interpolation function.

[0058] Step 6: Obtain the baseline-corrected monitoring data. First, subtract the constant load-temperature response H in the monitoring data before calibration from the original monitoring data vector M to obtain the zero-mean fluctuation data vector B = MH = [M 1 -H 1 ,M 2 -H 2 ,M 3 -H 3 ,...,M m-1 -H m-1 ,M m -H m ]=[B 1 ,B 2 ,B 3 ,...,B m-1 ,B m]; then subtract the baseline J before correction from the constant load-temperature response H to obtain the baseline-free static response Q = HJ = [H 1 -J 1 ,H 2 -J 2 ,H 3 -J 3 ,...,H m-1 -J m-1 ,H m -J m ]=[Q 1 ,Q 2 ,Q 3 ,...,Q m-1 ,Q m ]; Finally, superimpose B, Q and the corrected baseline X to obtain the corrected monitoring data h = [h 1 ,h 2 ,h 3 ,...,h m-1 ,h m ].

[0059] Step 7: Reproduce the data space of each detection point. If the monitoring data of the detection and monitoring overlap point A is h = [h 1 ,h 2 ,h 3 ,...,h m-1 ,h m ], the data of the remaining detection points are h and [A 1 ,A 2 ,A 3 ,...,A n-1 ,A n ]The coefficients are multiplied together, that is, A 1 h,A 2 h,A 3 h,...,A n-1 h,A n h.

[0060] In step 7, the recovery results of the detection points are only examples, and the final calculation results shall be based on the actual correlation.

[0061] The above method is used specifically:

[0062] Taking the strain monitoring data of the mid-span section of the main span of a certain long-span continuous beam bridge structure health monitoring system in Guangdong Province and the strain detection data of the mid-span section of the main span obtained by two detections as examples, the specific implementation process of the present invention is explained.

[0063] like Figure 2The following is a schematic diagram of the layout of the detection and monitoring points of the mid-span section of the main span of the bridge. There are 12 strain detection points, named C1 to C12, distributed on the top and bottom of the top plate, the left and right webs, and the bottom of the bottom plate; there are 2 strain monitoring points, named J1 to J2. Among them, C3 and J1 are overlapping nodes, and C11 and J2 are overlapping measurement points. The strain response time series data of C2 and C11 are reproduced by using the correlation between C3, C2 and C11, and the monitoring data of the J1 measurement point overlapping with the C3 measurement point. The steps are as follows:

[0064] (1) A load test was conducted during the first inspection. After the fleet passed the test, Figure 3 As shown, the correlation between the strain data of the C3 measuring point and the strain data of the C2 measuring point, and the correlation between the strain data of the C3 measuring point and the strain data of the C11 measuring point are obtained. If the data of the C3 measuring point (also the data of the J1 measuring point) is x, and the data of the other two measuring points are y, then the relationship between the C3 (J1) data and the C2 data is y = 1.104x + 22.946, and the relationship between the C3 (J1) data and the C11 data is y = 1.229x + 56.673. These two relationship equations can be considered as the "correlation coefficient" described in this patent.

[0065] (2) For the C3 measuring point, the static strain at a certain moment in the last test was -15 microstrain. During this test, the static strain at a certain moment in the current test was -26 microstrain. The baseline during this period is as follows: Figure 4 As shown, the linear interpolation function of the baseline is y=-11x-4.

[0066] (3) For the J1 measuring point, the static strain caused by the constant load and temperature in the monitoring data was extracted using the wavelet method during the last test. The monitoring system data curve is as follows: Figure 5 At the same time when the static strain was measured by the detection, the monitoring system measured the static strain to be -14.5 microstrain; during this test, the static strain caused by the constant load-temperature in the monitoring data was extracted using the wavelet method, and the monitoring system data curve is as follows Figure 6 At the same time when the static strain was measured by the detection system, the static strain was -27 microstrain. The baseline during this period is Figure 4 As shown, the linear interpolation function of the baseline is y=-12.5x-2.

[0067] (4) The error between the detection baseline and the monitoring baseline that needs to be corrected is set to 5%. The calculated error is 3.2%, which is lower than 5%. Therefore, no baseline correction is required.

[0068] (5) The monitoring data of the J1 measuring point between the two detection times is as follows Figure 7As shown, according to the relationship y = 1.104x + 22.946, and y = 1.229x + 56.673, Figure 7 The monitoring data obtained in is used as x to be substituted into the two relational equations. The output result y of the relational equations is the time series reproduction data of the C3 and C11 measurement points. Figure 8 and Fig. 9 shown.

[0069] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modification, equivalent substitution or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for spatiotemporal verification and reproduction of bridge response information, characterized in that: The following steps are involved: S1: The structural response data obtained based on bridge inspection has spatial completeness, and the data correlation relationship of each measuring point can be obtained; S2: Determine the static response of the bridge structure when the bridge is tested at this moment and is only subjected to constant load and temperature without other loads; obtain the static response of the bridge structure when the bridge was tested last time and was only subjected to constant load and temperature without other loads; S3: Obtain the data trend baseline of the detection point in step S2 between the current detection and the last detection; S4: The structural response data obtained based on bridge monitoring is time-complete, and the response time series data with time continuity at a certain structural measurement point can be obtained; S5: Obtain the data trend baseline of the monitoring point between the current detection time and the last detection time; S6: Check the abnormal trend of the baseline of the monitoring data. If there is a long-term abnormal change trend in the monitoring baseline, it is necessary to determine whether the monitoring trend baseline needs to be checked based on the detection trend baseline; S7: Perform monitoring baseline calibration to obtain the calibrated monitoring response data under constant load-temperature and the monitoring response data under constant load-temperature of the last test; S8: Obtain monitoring data after baseline correction; S9: Using the structural response data of a certain monitoring point and the response correlation coefficients between the measurement points, the time and space reproduction of each detection measurement point is performed.

2. A method for spatiotemporal verification and reproduction of bridge response information as claimed in claim 1, characterized in that: The measurement points of bridge detection in S1 are relatively complete, usually covering the measurement points of the monitoring system, which can express the spatial law of the bridge section. The load experiment in bridge detection can obtain the response information of each measurement point with spatial completeness. Select a certain detection and monitoring overlapping measurement point A, and perform regression analysis on the data of other detection measurement points with it to obtain the correlation coefficient vector [A1, A2, A3, ..., A n-1 ,A n ].

3. A method for spatiotemporal verification and reproduction of bridge response information as claimed in claim 1, characterized in that: In S2 and S3, the static response of the bridge structure is determined when the bridge is tested without other loads and only subjected to constant load and temperature. The static response C b Compared with the static response C measured in the last test s Connect the data by straight lines to obtain the data baseline between the two detection periods. According to the sampling interval of the bridge health monitoring system, construct the data points on the detection data baseline. If the constructed point plus the two end points C s and C b There are m data points in total, denoted by C s is C1, and C b C m , then the data vector of the detection baseline is C=[C1,C2,C3,...,C m-1 ,C m ].

4. A method for spatiotemporal verification and reproduction of bridge response information as claimed in claim 1, characterized in that: The monitoring data vector M in this period in S4 and S5 is [M1, M2, M3, ..., M m-1 ,M m ], and the constant load-temperature response formed by the constant load and temperature of the monitoring data during this period is extracted using a digital signal processing algorithm as H = [H1, H2, H3, ..., H m-1 ,H m ], the monitoring static response H at this moment m Connect the static response H1 of the last test to obtain the monitoring data baseline of the period. According to the sampling interval of the bridge health monitoring system, construct the data points on the monitoring data baseline. If the constructed point plus the two end points H1 and H m There are m data points in total, record H1 as J1, record H m For J m , then the data vector of the monitoring baseline is J = [J1, J2, J3, ..., J m-1 ,J m ].

5. A method for spatiotemporal verification and reproduction of bridge response information as claimed in claim 1, characterized in that: In S6, the detection baseline C is taken as the actual value and the monitoring baseline J is taken as the value to be evaluated, and the relative average error E between the two is calculated. If the relative average error does not exceed x%, it means that the monitoring baseline does not need to be calibrated. If the relative average error exceeds x%, it means that calibration is required.

6. A method for spatiotemporal verification and reproduction of bridge response information as claimed in claim 1, characterized in that: In S7, the detection static response C at this moment b Connect the static response H1 of the last test to obtain the corrected baseline of the monitoring data of this period. According to the sampling interval of the bridge health monitoring system, construct the data points on the baseline of the monitoring data. If the constructed point plus the two end points H1 and C b There are m data points in total, let H1 be X1, and let C be b For X m , then the modified monitoring baseline data vector is X=[X1,X2,X3,...,X m-1 ,X m ].

7. A method for spatiotemporal verification and reproduction of bridge response information as claimed in claim 1, characterized in that: In S8, the original monitoring data vector M is first subtracted from the constant load-temperature response H in the monitoring data before verification to obtain the zero-mean fluctuation data vector B=MH=[M1-H1,M2-H2,M3-H3,...,M m-1 -H m-1 ,M m -H m ]=[B1,B2,B3,...,B m-1 ,B m ]; then subtract the baseline J before correction from the constant load-temperature response H to obtain the baseline-free static response Q = HJ = [H1-J1, H2-J2, H3-J3, ..., H m-1 -J m-1 ,H m -J m ]=[Q1,Q2,Q3,...,Q m-1 ,Q m ]; Finally, superimpose B, Q and the corrected baseline X to obtain the corrected monitoring data h=[h1,h2,h3,...,h m-1 ,h m ]。 8. A method for spatiotemporal verification and reproduction of bridge response information as claimed in claim 1, characterized in that: In S9, if the monitoring data of the detection monitoring coincidence measurement point A is h=[h1,h2,h3,...,h m-1 ,h m ], then the data of the remaining detection points are h and [A1, A2, A3, ..., A n-1 ,A n ] where each coefficient is multiplied, i.e. A1h, A2h, A3h, ..., A n-1 h,A n h.

9. A method for spatiotemporal verification and reproduction of bridge response information as claimed in claim 5, characterized in that: The calculation formula of relative average error E is:

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