Bridge structure monitoring system and method incorporating active early warning

Abstract

The application provides a bridge structure monitoring system and method combined with active early warning, dynamic stress data and static stress data of each bridge monitoring point in a bridge section are acquired, a plurality of fatigue stress spectra are constructed according to the dynamic stress data at each bridge monitoring point, a damage accumulation coefficient of the bridge structure at each bridge monitoring point is determined according to the stress distribution difference between the fatigue stress spectra, a plurality of monitoring key points are extracted by combining all the damage accumulation coefficients with the dead load characteristics of the bridge section, the bridge structure stiffness corresponding to each monitoring key point is determined by the static stress data of each monitoring key point, a confidence interval for active early warning of the structural damage of the bridge section is determined by all the bridge structure stiffnesses, and the structural damage of the bridge section is early warned based on the confidence interval and the current bridge stress at each bridge monitoring point. The application can realize accurate early warning of the bridge structure damage under the influence of multi-dimensional load response.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of bridge monitoring, and more particularly to a bridge structure monitoring system and method combined with active early warning. BACKGROUND

[0002] With the rapid development of transportation infrastructure, the safety and durability of bridges have become an important concern in the engineering field. Bridge monitoring, as a key means to ensure the health of bridge structures, has developed rapidly in recent years. Traditional bridge monitoring mainly relies on manual inspection and periodic detection, but this method is inefficient and difficult to find potential problems in a timely manner. With the continuous progress of sensor technology, data acquisition and processing technology, modern bridge monitoring is gradually developing towards automation and intelligence, making the processing of monitoring data more efficient and enabling early warning and accurate diagnosis of bridge damage.

[0003] In existing bridge monitoring, bridge monitoring mainly involves laying a sensor network at key parts of the bridge to collect monitoring data in real time, and analyzing the monitoring data through a data analysis model to identify abnormalities and assess the health status of the bridge structure. In addition, the monitoring system can also achieve early bridge anomaly warning to provide a scientific basis for bridge maintenance and ensure its safe operation. However, in bridge structure monitoring, the bridge structure early warning system usually relies on a fixed threshold value. However, the bridge structure is affected by multi-dimensional load response, such as dynamic load response and static load response, making it difficult for the fixed threshold value to cover all possible damage scenarios, resulting in the bridge structure early warning system being unable to accurately warn of damage to the bridge structure. Therefore, how to accurately warn of damage to the bridge structure under the influence of multi-dimensional load response has become a difficult problem in the industry. SUMMARY

[0004] The present application provides a bridge structure monitoring system and method combined with active early warning, which can accurately warn of damage to the bridge structure under the influence of multi-dimensional load response.

[0005] In a first aspect, the present application provides a bridge structure monitoring method combined with active early warning, comprising the following steps:

[0006] Bridge monitoring points are arranged at different positions of the bridge section, and the bridge stress at each bridge monitoring point is monitored;

[0007] Dynamic stress data and static stress data at each bridge monitoring point are obtained, and a fatigue stress spectrum corresponding to each bridge monitoring point of the bridge section under the action of dynamic load is constructed based on the dynamic stress data at each bridge monitoring point;

[0008] According to the stress distribution difference between each fatigue stress spectrum, the bridge structure at each bridge monitoring point is analyzed to obtain the damage accumulation coefficient of the bridge structure at each bridge monitoring point, and a plurality of monitoring key points are extracted from all the bridge monitoring points by combining the dead load characteristics of the bridge section with all the damage accumulation coefficients;

[0009] The static stress data corresponding to each monitoring key point are used to determine the bridge structure stiffness corresponding to each monitoring key point during the static load action of the bridge section, and a confidence interval for the structural damage early warning of the bridge section is determined by all the bridge structure stiffnesses;

[0010] Based on the confidence interval and the current bridge stress at each bridge monitoring point, the structural damage of the bridge section is warned.

[0011] In some embodiments, the dynamic stress data at each bridge monitoring point are used to construct the fatigue stress spectrum corresponding to each bridge monitoring point during the dynamic load action of the bridge section, which specifically includes:

[0012] A bridge monitoring point is selected as a selected bridge monitoring point, the dynamic stress data of the selected bridge monitoring point are subjected to frequency domain transformation to obtain a dynamic stress spectrum;

[0013] A plurality of stress cycles of the dynamic stress spectrum are extracted, and the dynamic stress amplitude and cycle number of each stress cycle are counted;

[0014] A plurality of dynamic stress amplitude intervals are divided by all the dynamic stress amplitudes;

[0015] The fatigue stress spectrum corresponding to the selected bridge monitoring point during the dynamic load action of the bridge section is constructed by all the dynamic stress amplitude intervals and the cycle number corresponding to each dynamic stress amplitude interval;

[0016] The fatigue stress spectrum corresponding to the remaining bridge monitoring points during the dynamic load action of the bridge section is continuously determined.

[0017] In some embodiments, according to the stress distribution difference between each fatigue stress spectrum, the bridge structure at each bridge monitoring point is analyzed to obtain the damage accumulation coefficient of the bridge structure at each bridge monitoring point, which specifically includes:

[0018] The stress distribution characteristics of each fatigue stress spectrum are determined;

[0019] The stress distribution difference between each fatigue stress spectrum is calculated according to all the stress distribution characteristics;

[0020] The bridge damage increment corresponding to each bridge monitoring point is extracted from all the fatigue stress spectra;

[0021] The damage accumulation coefficient of the bridge structure at each bridge monitoring point is determined by all stress distribution differences, the bridge damage increment corresponding to each bridge monitoring point, and the life cycle of the bridge.

[0022] In some embodiments, extracting a plurality of monitoring key points from all bridge monitoring points by combining the damage accumulation coefficient of all bridge monitoring points with the dead load characteristics of the bridge section specifically comprises:

[0023] Obtaining the dead load characteristics of the bridge section and the damage accumulation coefficient of each bridge monitoring point;

[0024] Determining the load loss of each bridge monitoring point under the condition of the dead load characteristics;

[0025] Determining the damage sensitivity of each bridge monitoring point according to the damage accumulation coefficient and the load loss of each bridge monitoring point;

[0026] Comparing the damage sensitivity of each bridge monitoring point with the damage sensitivity threshold, and extracting a plurality of monitoring key points from all bridge monitoring points according to the comparison result.

[0027] In some embodiments, determining the bridge structure stiffness corresponding to each monitoring key point of the bridge section during the static load action by the static stress data corresponding to each monitoring key point specifically comprises:

[0028] Obtaining the displacement data of each monitoring key point of the bridge section during the static load action;

[0029] Determining the static stress characteristics at each monitoring key point according to the static stress data of each monitoring key point;

[0030] Determining the displacement response characteristics at each monitoring key point by the displacement data of each monitoring key point;

[0031] Selecting one monitoring key point as a selected monitoring key point, and determining the bridge structure stiffness corresponding to the selected monitoring key point of the bridge section during the static load action by the static stress characteristics and the displacement response characteristics corresponding to the selected monitoring key point;

[0032] Continuing to determine the bridge structure stiffness corresponding to the remaining monitoring key points of the bridge section during the static load action.

[0033] In some embodiments, the bridge section is the bottom region of the bridge.

[0034] In some embodiments, the bridge stress at each bridge monitoring point is monitored by a stress sensor.

[0035] In a second aspect, the application provides a bridge structure monitoring system combined with active early warning, comprising:

[0036] a monitoring module, configured to set bridge monitoring points at different positions of a bridge section and monitor bridge stress at each bridge monitoring point;

[0037] a processing module, configured to acquire dynamic stress data and static stress data at each bridge monitoring point, and construct a fatigue stress spectrum corresponding to each bridge monitoring point in the bridge section during dynamic load action based on the dynamic stress data at each bridge monitoring point;

[0038] The processing module is further configured to perform damage accumulation analysis on the bridge structure at each bridge monitoring point according to stress distribution differences between the fatigue stress spectra, obtain a damage accumulation coefficient of the bridge structure at each bridge monitoring point, and extract a plurality of monitoring key points from all the bridge monitoring points by combining all the damage accumulation coefficients with a dead load feature of the bridge section;

[0039] The processing module is further configured to determine bridge structure stiffness corresponding to each monitoring key point in the bridge section during static load action based on static stress data corresponding to each monitoring key point, and determine a confidence interval for active early warning of structural damage of the bridge section based on all the bridge structure stiffnesses;

[0040] an execution module, configured to perform structural damage early warning on the bridge section based on the confidence interval and current bridge stress at each bridge monitoring point.

[0041] In a third aspect, the application provides a computer device, comprising a memory and a processor, the memory stores a code, and the processor is configured to acquire the code and perform the bridge structure monitoring method combined with active early warning.

[0042] In a fourth aspect, the application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the bridge structure monitoring method combined with active early warning.

[0043] The technical scheme provided by the embodiments of the application has the following beneficial effects:

[0044] The bridge structure monitoring system and method provided by the application combine active early warning, first, bridge monitoring points are arranged at different positions of a bridge section, and bridge stresses at each bridge monitoring point are monitored; second, dynamic stress data and static stress data at each bridge monitoring point are obtained, a fatigue stress spectrum corresponding to each bridge monitoring point of the bridge section during dynamic load action is constructed based on the dynamic stress data at each bridge monitoring point; further, damage accumulation analysis is performed on the bridge structure at each bridge monitoring point according to stress distribution differences between each fatigue stress spectrum, a damage accumulation coefficient of the bridge structure at each bridge monitoring point is obtained, and a plurality of monitoring key points are extracted from all bridge monitoring points by combining all damage accumulation coefficients with constant load characteristics of the bridge section; then, bridge structure stiffness corresponding to each monitoring key point of the bridge section during static load action is determined from static stress data corresponding to each monitoring key point, all bridge structure stiffnesses are used to determine a confidence interval for active early warning of structural damage of the bridge section; finally, structural damage early warning of the bridge section is performed based on the confidence interval and current bridge stresses at each bridge monitoring point.

[0045] It can be seen that the application can realize accurate early warning of bridge structure damage under the influence of multi-dimensional load response. First, bridge monitoring points are arranged at different positions of the bridge section to effectively analyze the state of the bridge structure at different positions. Second, based on the dynamic stress data at each bridge monitoring point, a fatigue stress spectrum corresponding to each bridge monitoring point of the bridge section during dynamic load action is constructed to reflect the action distribution characteristics of the bridge structure under dynamic load, thereby providing a data basis for subsequent fatigue damage analysis. Further, damage accumulation analysis is performed on the bridge structure at each bridge monitoring point according to the stress distribution difference between the fatigue stress spectra, to obtain the damage accumulation coefficient of the bridge structure at each bridge monitoring point, so as to timely reflect the damaged state of the bridge structure and find potential damage of the bridge structure, thereby avoiding loss identification deviation caused by the bridge structure under dynamic load response, thereby improving the timeliness of the bridge monitoring system warning and preventing damage to the bridge structure. Further, a plurality of monitoring key points are extracted from all bridge monitoring points by combining the dead load characteristics of the bridge section with all damage accumulation coefficients to obtain the most sensitive area of the bridge structure change, thereby accurately reflecting the overall health status of the bridge structure according to the monitoring information of the monitoring key points, and timely finding early damage of the bridge structure, thereby improving the early warning accuracy of the bridge structure damage. Then, the confidence interval for the structure damage active warning of the bridge section is determined according to the bridge structure stiffness corresponding to each monitoring key point of the bridge section during static load action, to identify the abnormal state of the bridge structure, thereby avoiding loss identification interference caused by the bridge structure under static load response. Finally, the structure damage of the bridge section is warned based on the confidence interval and the current bridge stress at each bridge monitoring point. In summary, the technical scheme provided by the application can realize accurate early warning of bridge structure damage under the influence of multi-dimensional load response. BRIEF DESCRIPTION OF DRAWINGS

[0046] Figure 1 is an exemplary flowchart of a bridge structure monitoring method combined with active warning according to some embodiments of the application;

[0047] Figure 2 is an exemplary flowchart of determining a fatigue stress spectrum according to some embodiments of the application;

[0048] Figure 3 is an exemplary flowchart of determining a damage accumulation coefficient according to some embodiments of the application;

[0049] Figure 4 is a structural schematic diagram of a bridge structure monitoring system combined with active warning according to some embodiments of the application;

[0050] Figure 5is a structural schematic diagram of a computer device for implementing a bridge structure monitoring method combined with active early warning according to some embodiments of the present application. DETAILED DESCRIPTION

[0051] In order to better understand the technical solutions of the present application, the technical solutions of the present application will be described in detail below in combination with the drawings of the specification and specific embodiments.

[0052] Reference Figure 1 The figure is an exemplary flow chart of a bridge structure monitoring method combined with active early warning 100 according to some embodiments of the present application, which mainly includes the following steps:

[0053] In step 101, bridge monitoring points are arranged at different positions of a bridge section, and bridge stresses at each bridge monitoring point are monitored.

[0054] In specific implementation, bridge monitoring points are arranged at different positions of a bridge section, i.e., a setting interval of bridge monitoring points is set according to the length of the bridge section, and bridge monitoring points are arranged at different positions of the bridge section according to the setting interval, for example, when the length of the bridge section is 6 meters, the setting interval can be set to 1 meter, and the setting interval can be set according to actual requirements, which is not limited here.

[0055] In specific implementation, the bridge stresses at each bridge monitoring point can be monitored by a stress sensor, and in other embodiments, other monitoring sensors can also be used to monitor the bridge stresses at each bridge monitoring point, which is not limited here.

[0056] It should be noted that the bridge section in the present application is the bottom area of the bridge; the bridge monitoring point in the present embodiment represents the point for bridge monitoring; the bridge stress in the present application represents the magnitude of the force borne by the unit area of the bridge structure, and the bridge stress measures the stress state of the bridge under external load, and through monitoring of the bridge stress, favorable conditions can be effectively provided for identification and early warning of bridge structure damage.

[0057] In step 102, dynamic stress data and static stress data at each bridge monitoring point are obtained, and a fatigue stress spectrum corresponding to each bridge monitoring point of the bridge section during dynamic load action is constructed based on the dynamic stress data at each bridge monitoring point.

[0058] In practice, dynamic and static stress data at various bridge monitoring points can be obtained through a bridge monitoring database. The dynamic stress data represents the stress response of the bridge under external dynamic loads, containing multiple dynamic stress values ​​that reflect the instantaneous stress changes of the bridge structure under these loads. External dynamic loads include, but are not limited to, vehicles and wind. The static stress data represents the stress response of the bridge under external static loads, containing multiple static stress values ​​that reflect the stress of the bridge under these loads. External static loads include, but are not limited to, the bridge's own weight and vehicle static loads. Both dynamic and static stress data are typically closely related to the structure's dynamic behaviors such as vibration and deformation. Therefore, acquiring these data can effectively analyze the bridge's condition under varying loads, thereby improving the accuracy of bridge structural damage identification.

[0059] It should be noted that the bridge monitoring database in this embodiment is a system for storing, managing and analyzing bridge health monitoring data. The bridge monitoring database integrates bridge status information collected through various sensors (such as stress sensors, accelerometers, displacement gauges, temperature sensors, etc.), which can effectively analyze the structural health, operational status and safety of bridges. This bridge monitoring database not only stores a large amount of real-time and historical data, but also supports data processing, analysis and visualization in order to monitor and evaluate the performance of bridges.

[0060] In some embodiments, reference Figure 2 As shown in the figure, this is an exemplary flowchart for determining the fatigue stress spectrum according to some embodiments of this application. In this embodiment, the fatigue stress spectrum corresponding to each bridge monitoring point based on the dynamic stress data at each bridge monitoring point can be constructed by the following steps:

[0061] First, in step 1021, a bridge monitoring point is selected as the selected bridge monitoring point, and the dynamic stress data of the selected bridge monitoring point is transformed in the frequency domain to obtain the dynamic stress spectrum.

[0062] Secondly, in step 1022, multiple stress cycles of the dynamic stress spectrum are extracted, and the dynamic stress amplitude and cycle number of each stress cycle are statistically analyzed.

[0063] Furthermore, in step 1023, multiple dynamic stress amplitude intervals are obtained by dividing all dynamic stress amplitudes;

[0064] Then, in step 1024, the fatigue stress spectrum corresponding to the selected bridge monitoring point of the bridge section in the process of dynamic load action is constructed by all dynamic stress amplitude intervals and the cycle number corresponding to each dynamic stress amplitude interval.

[0065] Finally, in step 1025, the fatigue stress spectrum corresponding to the remaining bridge monitoring points of the bridge section in the process of dynamic load action is determined.

[0066] In specific implementation, first, a bridge monitoring point is selected as the selected bridge monitoring point, and the dynamic stress data of the selected bridge monitoring point is subjected to frequency domain transformation by using fast Fourier transform to obtain a dynamic stress spectrum, which will not be described herein again. The frequency domain transformation of the dynamic stress data can accurately reveal the stress amplitude distribution of the dynamic load at different frequencies. Second, a plurality of stress cycles of the dynamic stress spectrum are extracted by using the rainflow counting method, and the dynamic stress amplitude and cycle number of each stress cycle are counted. The rainflow counting method is a widely used fatigue analysis tool, which can effectively identify the closed stress cycles in the dynamic stress data and count the dynamic stress amplitude and cycle number of each closed stress cycle. Specifically, the rainflow counting algorithm determines the cycle start point and end point according to the local extreme value in the dynamic stress spectrum, and records the stress amplitude and corresponding cycle number of each stress cycle. Further, a plurality of dynamic stress amplitude intervals are divided by all dynamic stress amplitudes, that is, a set of equally spaced amplitude intervals are set, and all dynamic stress amplitudes are divided into a plurality of stress amplitude intervals according to the size by using the amplitude intervals. For example, the amplitude interval can be set as the interval of two dynamic stress amplitudes. In addition, in other embodiments, the amplitude interval can also be set according to actual needs, which will not be limited herein. The amplitude interval is the division size of the stress amplitude interval. Then, the fatigue stress spectrum corresponding to the selected bridge monitoring point of the bridge section in the process of dynamic load action is constructed by all dynamic stress amplitude intervals and the cycle number corresponding to each dynamic stress amplitude interval, that is, the cycle number in each stress amplitude interval is counted by constructing a histogram to generate the fatigue stress spectrum corresponding to the selected bridge monitoring point of the bridge section in the process of dynamic load action. Specifically, the horizontal axis of the histogram is the stress amplitude interval, and the vertical axis is the cycle number. Finally, the fatigue stress spectrum corresponding to the remaining bridge monitoring points of the bridge section in the process of dynamic load action is determined by the determination method of “constructing the fatigue stress spectrum corresponding to the selected bridge monitoring point of the bridge section in the process of dynamic load action by all dynamic stress amplitude intervals and the cycle number corresponding to each dynamic stress amplitude interval”, which will not be described herein again.

[0067] It should be noted that, in this embodiment, the dynamic stress spectrum represents the characteristic description of the stress distribution at the bridge monitoring point under dynamic loads. The dynamic stress spectrum reflects the distribution of dynamic stress at different frequency components and is the result obtained after frequency domain analysis of the time-domain dynamic stress. In this embodiment, stress cycling represents a complete change process experienced by the material structure under repeated external forces. Stress cycling is usually closely related to fatigue analysis and is used to describe the periodic change characteristics of stress over time. In this embodiment, the dynamic stress amplitude represents the intensity of the dynamic stress change. In this embodiment, the number of cycles represents the complete stress experienced by the monitoring point. The number of cycles is an important parameter in fatigue analysis, and together with the dynamic stress amplitude, it determines the degree of fatigue damage to the material. In this embodiment, the dynamic stress amplitude range refers to the range of amplitudes obtained by dividing the dynamic stress amplitude data. In this application, the fatigue stress spectrum represents a statistical representation of the stress variation characteristics of the bridge structure. It usually takes different stress amplitude ranges and their corresponding number of cycles as the main content, and is used to evaluate the fatigue damage and remaining life of the bridge structure. The fatigue stress spectrum represents the distribution law of dynamic load in each stress amplitude range. The fatigue stress spectrum not only reflects the distribution characteristics of dynamic load, but also provides basic data for subsequent fatigue damage analysis.

[0068] In step 103, damage accumulation analysis is performed on the bridge structure at each bridge monitoring point based on the stress distribution differences between each fatigue stress spectrum to obtain the damage accumulation coefficient of the bridge structure at each bridge monitoring point. Multiple key monitoring points are extracted from all bridge monitoring points by combining all damage accumulation coefficients with the dead load characteristics of the bridge section.

[0069] In some embodiments, reference Figure 3 As shown in the figure, this is an exemplary flowchart for determining the damage accumulation coefficient according to some embodiments of this application. In this embodiment, damage accumulation analysis is performed on the bridge structure at each bridge monitoring point based on the stress distribution differences between various fatigue stress spectra. The damage accumulation coefficient of the bridge structure at each bridge monitoring point can be obtained by the following steps:

[0070] First, in step 1031, the stress distribution characteristics of each fatigue stress spectrum are determined;

[0071] Secondly, in step 1032, the stress distribution differences between each fatigue stress spectrum are calculated based on all stress distribution characteristics;

[0072] Then, in step 1033, the bridge damage increment corresponding to each bridge monitoring point is extracted from all fatigue stress spectra;

[0073] Finally, in step 1034, the damage cumulative coefficient of the bridge structure at each bridge monitoring point is determined by all the stress distribution differences, the bridge damage increment corresponding to each bridge monitoring point, and the life cycle of the bridge.

[0074] In a specific implementation, first, the stress distribution characteristics of each fatigue stress spectrum are determined, that is, a fatigue stress spectrum is selected as a selected fatigue stress spectrum, the mean of all cycle times in the selected fatigue stress spectrum is calculated, and the mean calculation result is taken as the stress distribution characteristic of the selected fatigue stress spectrum, and the stress distribution characteristics of the remaining fatigue stress spectra are continuously determined. In addition, in other embodiments, other calculation methods can be used to calculate the stress distribution characteristics of each fatigue stress spectrum, which is not limited here. Second, the stress distribution differences between each two fatigue stress spectra are calculated according to all stress distribution characteristics, that is, for each two fatigue stress spectra, the absolute difference of the corresponding two stress distribution differences is calculated, and the absolute difference calculation result is taken as the stress distribution difference between the fatigue stress spectra, and then the stress distribution differences between each two fatigue stress spectra are obtained. In addition, in other embodiments, other calculation methods can be used to calculate the stress distribution differences between each two fatigue stress spectra, which is not limited here. Then, the bridge damage increments corresponding to each bridge monitoring point are extracted from all fatigue stress spectra, that is, according to the fatigue stress spectrum of each bridge monitoring point, the linear cumulative damage method is used to calculate the bridge damage increment of each bridge monitoring point, for example, the Miner linear cumulative damage method is used to calculate the bridge damage increment of each bridge monitoring point. Specifically, for each bridge monitoring point, the cycle times in each stress amplitude interval in the fatigue stress spectrum corresponding to the bridge monitoring point are divided by the fatigue life corresponding to the stress amplitude interval (which can be obtained from the S-N curve or experimental data of the material) to obtain the single damage contribution of the stress amplitude interval, then the single damage contributions of all stress amplitude intervals are accumulated to obtain the bridge damage increment corresponding to the bridge monitoring point, and then the bridge damage increments corresponding to each bridge monitoring point are obtained. The S-N curve describes the relationship between the fatigue life of the material under different stress amplitudes, which is usually measured by experiment and fitted by double logarithmic coordinates, which is not described here. Finally, the damage accumulation coefficients of the bridge structure at each bridge monitoring point are determined by all stress distribution differences, the bridge damage increment corresponding to each bridge monitoring point, and the service life of the bridge, that is, all stress distribution differences are normalized by using the maximum-minimum normalization, the mean of the normalized all stress distribution differences is calculated, and the mean calculation result is taken as the stress distribution fluctuation factor. For each bridge monitoring point, the product of the quotient of the bridge damage increment corresponding to the bridge monitoring point and the service life of the bridge and the stress distribution fluctuation factor is calculated, and the product calculation result is taken as the damage accumulation coefficient of the bridge structure at the bridge monitoring point, and then the damage accumulation coefficients of the bridge structure at each bridge monitoring point are obtained. In addition, in other embodiments, other calculation methods can be used to calculate the damage accumulation coefficients of the bridge structure at each bridge monitoring point, which is not limited here.

[0075] It should be noted that the stress distribution characteristics in the embodiment represent the distribution mode of the bridge stress in space, the stress distribution characteristics reflect the complexity and non-uniformity of the bridge structure stress, and are the basis for fatigue analysis, damage evaluation and health monitoring; the stress distribution difference in the application represents the deviation between different stress characteristics; the bridge damage increment in the embodiment represents the increase of the fatigue damage degree of the bridge structure caused by external load, and the bridge damage increment is a key parameter for describing the damage accumulation process of the bridge structure; the single damage contribution in the embodiment represents the contribution degree of the damage caused by single stress cycle of the bridge to the bridge material; the stress distribution fluctuation factor in the embodiment represents a quantitative index of the stress distribution fluctuation degree, and is used to evaluate the stress distribution stability and change range of the bridge structure under the action of load; the damage accumulation coefficient in the application represents an index for measuring the damage accumulation of the bridge structure under the action of multiple loads, and the damage accumulation coefficient is usually used to evaluate the fatigue damage accumulation of the bridge structure under the action of different loads; the damage accumulation coefficient is an important parameter for quantifying damage based on the fatigue characteristics of the material or structure under different loads and the stress cycles experienced by the material or structure; by determining the damage accumulation coefficient, the damaged state of the bridge structure can be reflected in real time, potential damage of the bridge structure can be found in time, and the timeliness of the early warning of the bridge monitoring system can be improved, so as to prevent the bridge structure from being damaged or suddenly failing.

[0076] In some embodiments, the following steps can be used to extract a plurality of monitoring key points from all bridge monitoring points by combining all damage accumulation coefficients with the dead load characteristics of the bridge section, that is:

[0077] Obtaining the dead load characteristics of the bridge section and the damage accumulation coefficients of each bridge monitoring point;

[0078] Determining the load loss of each bridge monitoring point under the condition of the dead load characteristics;

[0079] Determining the damage sensitivity of each bridge monitoring point according to the damage accumulation coefficient and the load loss of each bridge monitoring point;

[0080] Comparing the damage sensitivity of each bridge monitoring point with the damage sensitivity threshold, and extracting a plurality of monitoring key points from all bridge monitoring points according to the comparison result.

[0081] In a specific implementation, first, the constant load characteristic of the bridge section and the damage cumulative coefficient of each bridge monitoring point are obtained from the bridge monitoring database. The constant load characteristic can be set according to the design specification and operation condition of the bridge, which is not described herein. In the present embodiment, the constant load characteristic is the dead load of the bridge. Second, the load loss of each bridge monitoring point under the constant load characteristic condition is determined, that is, the actual load of each bridge monitoring point under the constant load characteristic condition is obtained. For each bridge monitoring point, the quotient of the actual load corresponding to the bridge monitoring point and the dead load corresponding to the constant load characteristic condition is taken as the load loss of the bridge monitoring point under the constant load characteristic condition. Furthermore, in other embodiments, other calculation methods can be used to obtain the load loss of each bridge monitoring point under the constant load characteristic condition, which is not limited herein. Then, the damage sensitivity of each bridge monitoring point is determined according to the damage cumulative coefficient and the load loss of each bridge monitoring point, that is, for each bridge monitoring point, the damage cumulative coefficient and the load loss corresponding to the bridge monitoring point are weighted and summed, and the weighted sum result is taken as the damage sensitivity of the bridge monitoring point. Furthermore, in other embodiments, other calculation methods can be used to obtain the damage sensitivity of each bridge monitoring point, which is not limited herein. The weight values of the damage cumulative coefficient and the load loss can be set between 0 and 1 by expert experience. Finally, the damage sensitivities of the bridge monitoring points are compared with the damage sensitivity threshold, and a plurality of monitoring key points are extracted from all the bridge monitoring points according to the comparison result, that is, the damage sensitivities of the bridge monitoring points are compared with the damage sensitivity threshold, and the bridge monitoring points with a damage sensitivity greater than the damage sensitivity threshold are extracted as monitoring key points, and then the plurality of monitoring key points are obtained. The damage sensitivity threshold can be set according to the safety level of the bridge, which is not described herein. For example, for a key bridge structure, a lower threshold can be set to increase the coverage of the monitoring points, thereby improving the comprehensiveness and accuracy of the monitoring.

[0082] The constant load feature in the embodiment represents the fixed load of the bridge itself; the load loss in the embodiment represents the loss amount of the load-carrying capacity of the bridge structure under the action of the load, the load loss reflects the change of the performance of the bridge structure from the design state to the current actual state, and is an important index in the bridge health monitoring and evaluation; the damage sensitivity in the embodiment represents the response sensitivity index of the bridge monitoring point in the bridge structure to the damage change, and the damage sensitivity reflects the influence ability of the bridge monitoring point to the change of the overall health state of the bridge; the monitoring key point in the application represents the point most sensitive to the damage change in the bridge structure, the monitoring key point can effectively reflect the change of the health state of the bridge, the monitoring key point is located in the area most sensitive to the structural change, and the state thereof can accurately reflect the overall health condition of the bridge structure, which is helpful for timely discovering early damage or potential hidden danger, thereby optimizing the monitoring efficiency of the bridge structure monitoring system and improving the early warning accuracy of the bridge structure damage.

[0083] In step 104, the bridge structure stiffness corresponding to each monitoring key point of the bridge section in the process of the action of the static load is determined by the static stress data corresponding to each monitoring key point, and the confidence interval for the active early warning of the structural damage of the bridge section is determined by all the bridge structure stiffnesses.

[0084] In some embodiments, the determination of the bridge structure stiffness corresponding to each monitoring key point of the bridge section in the process of the action of the static load by the static stress data corresponding to each monitoring key point can be realized by the following steps, that is:

[0085] Obtaining the displacement data of each monitoring key point of the bridge section in the process of the action of the static load;

[0086] Determining the static stress feature at each monitoring key point according to the static stress data of each monitoring key point;

[0087] Determining the displacement response feature at each monitoring key point by the displacement data of each monitoring key point;

[0088] Selecting one monitoring key point as a selected monitoring key point, and determining the bridge structure stiffness corresponding to the selected monitoring key point of the bridge section in the process of the action of the static load by the static stress feature and the displacement response feature corresponding to the selected monitoring key point;

[0089] Continuing to determine the bridge structure stiffness corresponding to the remaining monitoring key points of the bridge section in the process of the action of the static load.

[0090] In the specific implementation, first, the displacement data of each monitoring key point of the bridge section during the static load action is acquired by a high-precision displacement sensor; second, the static stress feature at each monitoring key point is determined according to the static stress data of each monitoring key point, that is, for each monitoring key point, the maximum static stress value and the minimum static stress value in the static stress data corresponding to the monitoring key point are extracted, the average of the maximum static stress value and the minimum static stress value is taken as the static stress feature at the monitoring key point, and then the static stress feature at each monitoring key point is obtained; in addition, in other embodiments, other calculation methods can also be used to calculate the static stress feature at each monitoring key point, which is not limited here; further, the displacement response feature at each monitoring key point is determined by the displacement data of each monitoring key point, that is, for each monitoring key point, the maximum displacement value and the minimum displacement value in the displacement data corresponding to the monitoring key point are extracted, the average of the maximum displacement value and the minimum displacement value is taken as the displacement response feature at the monitoring key point, and then the displacement response feature at each monitoring key point is obtained; in addition, in other embodiments, other calculation methods can also be used to calculate the displacement response feature at each monitoring key point, which is not limited here; then, one monitoring key point is selected as a selected monitoring key point, and the bridge structure stiffness corresponding to the selected monitoring key point during the static load action of the bridge section is determined by the static stress feature and the displacement response feature corresponding to the selected monitoring key point, that is, one monitoring key point is selected as a selected monitoring key point, and the quotient of the static stress feature and the displacement response feature corresponding to the selected monitoring key point is taken as the bridge structure stiffness corresponding to the selected monitoring key point during the static load action of the bridge section; in addition, in other embodiments, other calculation methods can also be used to calculate the bridge structure stiffness corresponding to the selected monitoring key point during the static load action of the bridge section, which is not limited here; finally, the bridge structure stiffness corresponding to the remaining monitoring key points during the static load action of the bridge section is determined by the determination method of “determining the bridge structure stiffness corresponding to the selected monitoring key point during the static load action of the bridge section by the static stress feature and the displacement response feature corresponding to the selected monitoring key point”, which is not described here again.

[0091] It should be noted that the static stress characteristic in the embodiment represents the stress distribution law of the structure such as the bridge under the action of constant load, and the static stress characteristic reflects the mechanical property and stress state of the bridge structure under the static load condition; the displacement response characteristic in the embodiment represents the displacement change law of the bridge structure under the action of external load, and the displacement response characteristic reflects the overall coordination of the bridge structure under different load conditions, and is one of important characteristics of the structural property and health state; the bridge structure stiffness in the application refers to the ability of the bridge structure to resist deformation under the action of external load, and is usually measured by the ratio between the deformation of the bridge and the applied load; the greater the bridge structure stiffness, the smaller the deformation of the structure under the action of load, and vice versa; by determining the bridge structure stiffness, the health state of the bridge structure can be effectively monitored, the bridge structure monitoring and early warning strategy can be optimized, and the long-term safety of the bridge structure can be ensured.

[0092] In some embodiments, the confidence interval for the active early warning of structural damage of the bridge section by all the bridge structure stiffnesses can be achieved by the following steps, that is:

[0093] An initial confidence interval for the active early warning of structural damage of the bridge section is obtained;

[0094] The stiffness fluctuation coefficient of the bridge section during the action of static load is determined according to all the bridge structure stiffnesses;

[0095] The initial confidence interval is corrected by the stiffness fluctuation coefficient to obtain the confidence interval for the active early warning of structural damage of the bridge section.

[0096] In a specific implementation, first, an initial confidence interval for the bridge section to perform structural damage active early warning is obtained from the bridge monitoring database, which can be set as a safety range at a certain probability level by statistical methods. For example, based on the assumption of normal distribution, the initial confidence interval can be set as a range of the mean value plus or minus twice the standard deviation of the historical bridge stress data. Then, the stiffness fluctuation coefficient of the bridge section under the action of static load is determined according to the stiffness of all bridge structures, that is, the standard deviation and the mean value of the stiffness of all bridge structures are calculated, and the ratio of the standard deviation to the mean value is taken as the stiffness fluctuation coefficient of the bridge section under the action of static load. In addition, in other embodiments, other calculation methods can also be used to calculate the stiffness fluctuation coefficient of the bridge section under the action of static load, which is not limited here. Finally, the initial confidence interval is corrected by the stiffness fluctuation coefficient to obtain the confidence interval for the bridge section to perform structural damage active early warning, that is, the linear superposition model is used to adjust the upper and lower bounds of the initial confidence interval by taking the stiffness fluctuation coefficient as a correction factor. Specifically, the interval width of the initial confidence interval can be increased by the stiffness fluctuation coefficient, that is, the upper bound of the initial confidence interval is added to the stiffness fluctuation coefficient and the lower bound is subtracted from the stiffness fluctuation coefficient. The stiffness fluctuation coefficient is a non-dimensional constant.

[0097] It should be noted that the initial confidence interval in the present embodiment represents the initially set interval range for performing bridge structure damage active early warning. The stiffness fluctuation coefficient in the present embodiment represents a degree quantity describing the stiffness change of the bridge structure under different load conditions. The stiffness fluctuation coefficient is used to represent the instability or fluctuation of the stiffness of the bridge structure. In the health monitoring of the bridge structure, the stiffness fluctuation coefficient reflects the fluctuation of the stiffness of the bridge structure under working conditions, which can effectively predict the possible damage of the bridge structure. The confidence interval in the present application represents the confidence interval range for performing bridge structure damage active early warning. By determining the confidence interval, the reliability of the bridge structure state can be evaluated to more accurately analyze the difference between the actual value and the predicted value of the bridge stress parameter. If the monitored bridge stress exceeds the confidence interval, it indicates that the bridge structure is in an abnormal state and there is a potential risk of damage, thereby issuing a loss warning signal, thereby reducing the false or missed reports of bridge damage.

[0098] In step 105, the bridge section is warned of structural damage based on the confidence interval and the current bridge stress at each bridge monitoring point.

[0099] In some embodiments, the bridge section can be warned of structural damage based on the confidence interval and the current bridge stress at each bridge monitoring point by the following steps, that is:

[0100] The current bridge stress of each bridge monitoring point is obtained.

[0101] comparing the current bridge stress of each bridge monitoring point with the confidence interval to determine whether the current bridge of each bridge monitoring point exceeds the upper limit or lower limit of the confidence interval;

[0102] If the current bridge stress of a bridge monitoring point exceeds the upper limit or lower limit of the confidence interval, the bridge monitoring point is marked as a bridge structure damage point, and all bridge structure damage points of the bridge section are obtained.

[0103] Based on all bridge structure damage points, an injury warning signal of the bridge section is sent.

[0104] In specific implementation, first, the current bridge stress of each bridge monitoring point is obtained; second, the current bridge stress of each bridge monitoring point is compared with the confidence interval to determine whether the current bridge of each bridge monitoring point exceeds the upper limit or lower limit of the confidence interval, then, if the current bridge stress of a bridge monitoring point exceeds the upper limit or lower limit of the confidence interval, the bridge monitoring point is marked as a bridge structure damage point, otherwise, the bridge monitoring point is not a bridge structure damage point, and all bridge structure damage points of the bridge section are obtained; finally, based on all bridge structure damage points, an injury warning signal of the bridge section is sent, that is, the total number of all bridge structure damage points is counted, and when the total number exceeds a preset total number, the bridge structure monitoring system automatically sends the injury warning signal of the bridge section, and the injury warning signal is sent through multiple channels, including short message and email.

[0105] It should be noted that the injury warning signal in the embodiment represents warning information that the bridge structure has a loss, and the injury warning signal is used to prompt the risk of damage of the bridge structure, so as to take timely maintenance, reinforcement or other emergency measures to prevent the bridge structure from further deterioration or safety accidents.

[0106] In addition, another aspect of the present application, in some embodiments, the present application provides a bridge structure monitoring system combined with active early warning, referring to Figure 4 The figure is a structural schematic diagram of a bridge structure monitoring system combined with active early warning according to some embodiments of the present application, which includes a monitoring module 201, a processing module 202 and an execution module 203, which are described as follows:

[0107] The monitoring module 201 is mainly used for setting bridge monitoring points at different positions of the bridge section and monitoring the bridge stress at each bridge monitoring point in the present application;

[0108] The processing module 202 is mainly used to acquire dynamic stress data and static stress data of each bridge monitoring point, and construct a fatigue stress spectrum corresponding to each bridge monitoring point in the process of dynamic load action of the bridge section based on the dynamic stress data of each bridge monitoring point.

[0109] The processing module 202 is also used to perform damage accumulation analysis on the bridge structure at each bridge monitoring point according to the stress distribution difference between each fatigue stress spectrum, obtain a damage accumulation coefficient of the bridge structure at each bridge monitoring point, and extract a plurality of monitoring key points from all bridge monitoring points by combining the dead load characteristics of the bridge section with all damage accumulation coefficients.

[0110] In addition, the processing module 202 is also used to determine the bridge structure stiffness corresponding to each monitoring key point in the process of static load action of the bridge section according to the static stress data corresponding to each monitoring key point, and determine a confidence interval for the structure damage active early warning of the bridge section by all bridge structure stiffnesses.

[0111] The execution module 203 is mainly used to perform structure damage early warning on the bridge section based on the confidence interval and the current bridge stress at each bridge monitoring point.

[0112] In addition, the present application also provides a computer device, which comprises a memory and a processor, the memory stores code, and the processor is configured to acquire the code and execute the above-mentioned bridge structure monitoring method combined with active early warning.

[0113] In some embodiments, with reference to Figure 5 The figure is a structural schematic diagram of a computer device for implementing the bridge structure monitoring method combined with active early warning according to some embodiments of the present application. The bridge structure monitoring method combined with active early warning in the above-mentioned embodiments can be implemented by the computer device shown in the figure, which is a computer device for implementing the bridge structure monitoring method combined with active early warning. Figure 5 The computer device 300 comprises at least one processor 301, a communication bus 302, a memory 303 and at least one communication interface 304.

[0114] The processor 301 can be a general central processing unit (CPU), an application-specific integrated circuit (ASIC) or one or more circuits for controlling the execution of the bridge structure monitoring method combined with active early warning in the present application.

[0115] The communication bus 302 can be used to transmit information between the above-mentioned components.

[0116] The memory 303 can be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM), or other type of dynamic storage device that can store information and instructions, and can be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disk storage, a magnetic disk or other magnetic storage device, or any other medium capable of storing instructions or data that can be accessed by a computer, but not limited to. The memory 303 can exist independently and be connected to the processor 301 through the communication bus 302. The memory 303 can also be integrated with the processor 301.

[0117] The memory 303 is configured to store program codes for implementing the solutions of the present application, and the processor 301 is configured to execute the program codes stored in the memory 303. The program codes can include one or more software modules. The determination of the bridge structure monitoring method combined with the active early warning in the above embodiments can be implemented by one or more software modules in the program codes of the processor 301 and the memory 303.

[0118] The communication interface 304 is configured to communicate with other devices or communication networks, such as an Ethernet, a radio access network (RAN), a wireless local area network (WLAN), etc., using any transceiver-like device.

[0119] In specific implementations, as an example, the computer device can include multiple processors, each of which can be a single-CPU processor or a multi-CPU processor. The processor herein can refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0120] The computer device described above can be a general-purpose computer device or a special-purpose computer device. In a specific implementation, the computer device can be a desktop computer, a laptop computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. The embodiments of the present application do not limit the type of the computer device.

[0121] In addition, the present application also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the bridge structure monitoring method combined with active early warning.

[0122] Although the preferred embodiments of the present application have been described, those skilled in the art who are familiar with the basic inventive concept can make additional changes and modifications to the embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0123] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application also intends to include these modifications and variations.

Claims

1. A bridge structure monitoring method incorporating active pre-warning, characterized by, The method comprises the following steps: bridge monitoring points are arranged at different positions of the bridge section, and bridge stresses at the bridge monitoring points are monitored; dynamic stress data and static stress data at the bridge monitoring points are acquired, and a fatigue stress spectrum corresponding to each bridge monitoring point during dynamic load action is constructed based on the dynamic stress data at the bridge monitoring point; damage accumulation analysis is performed on the bridge structure at each bridge monitoring point according to stress distribution differences between the fatigue stress spectra, to obtain a damage accumulation coefficient of the bridge structure at each bridge monitoring point, and a plurality of monitoring key points are extracted from all the bridge monitoring points by combining the damage accumulation coefficients with a dead load feature of the bridge section; bridge structure stiffness corresponding to each monitoring key point during static load action is determined from the static stress data corresponding to the monitoring key point, and a confidence interval for active early warning of structural damage of the bridge section is determined from all the bridge structure stiffnesses; structural damage of the bridge section is warned based on the confidence interval and current bridge stresses at the bridge monitoring points; The damage accumulation analysis on the bridge structure at each bridge monitoring point according to the stress distribution differences between the fatigue stress spectra comprises: stress distribution features of the fatigue stress spectra are determined; stress distribution differences between the fatigue stress spectra are calculated based on all the stress distribution features; bridge damage increments corresponding to the bridge monitoring points are extracted from all the fatigue stress spectra; the damage accumulation coefficient of the bridge structure at each bridge monitoring point is determined from all the stress distribution differences, the bridge damage increments corresponding to the bridge monitoring points and the service life of the bridge, specifically comprising: all the stress distribution differences are normalized by maximum-minimum normalization, and mean values of the normalized stress distribution differences are calculated, and the mean value calculation result is taken as a stress distribution fluctuation factor; for each bridge monitoring point, the product of the quotient of the bridge damage increment corresponding to the bridge monitoring point and the service life of the bridge and the stress distribution fluctuation factor is calculated, and the product calculation result is taken as the damage accumulation coefficient of the bridge structure at the bridge monitoring point, thereby obtaining the damage accumulation coefficient of the bridge structure at each bridge monitoring point, which represents an index for measuring damage accumulation of the bridge structure under multiple load actions; The extraction of the monitoring key points from all the bridge monitoring points by combining the damage accumulation coefficients with the dead load feature of the bridge section comprises: the dead load feature of the bridge section and the damage accumulation coefficients of the bridge monitoring points are acquired; The load bearing loss of each bridge monitoring point under the dead load characteristic condition is determined, specifically including: obtaining the actual load bearing of each bridge monitoring point under the dead load characteristic condition, for each bridge monitoring point, taking the quotient of the actual load bearing corresponding to the bridge monitoring point and the dead load corresponding to the dead load characteristic condition as the load bearing loss of the bridge monitoring point under the dead load characteristic condition, and then obtaining the load bearing loss of each bridge monitoring point under the dead load characteristic condition, the load bearing loss representing the loss amount of the load bearing capacity of the bridge structure under the action of the load; The damage sensitivity of each bridge monitoring point is determined according to the damage accumulation coefficient and the load bearing loss of each bridge monitoring point, specifically including: for each bridge monitoring point, the damage accumulation coefficient and the load bearing loss corresponding to the bridge monitoring point are weighted and summed, and the weighted sum result is taken as the damage sensitivity of the bridge monitoring point, and then the damage sensitivity of each bridge monitoring point is obtained, the damage sensitivity representing the response sensitivity index of the bridge monitoring point in the bridge structure to damage change; The damage sensitivities of the bridge monitoring points are compared with the damage sensitivity threshold, and a plurality of monitoring key points are extracted from all the bridge monitoring points according to the comparison result, specifically including: comparing the damage sensitivities of the bridge monitoring points with the damage sensitivity threshold, and extracting the bridge monitoring points with the damage sensitivity greater than the damage sensitivity threshold as the monitoring key points, and then the plurality of monitoring key points, the monitoring key points representing the monitoring points reflecting the change of the bridge health state; Wherein, the confidence interval of the bridge section for the active early warning of structural damage is determined by all the bridge structure stiffness, which is realized by the following steps, that is: An initial confidence interval of the bridge section for the active early warning of structural damage is obtained, the initial confidence interval representing the initially set interval range for the active early warning of bridge structure damage; The stiffness fluctuation coefficient of the bridge section during the static load action process is determined according to all the bridge structure stiffness; The initial confidence interval is corrected by the stiffness fluctuation coefficient to obtain the confidence interval of the bridge section for the active early warning of structural damage, the confidence interval representing the confidence interval range for the active early warning of bridge structure damage.

2. The method of claim 1, wherein, The fatigue stress spectrum corresponding to each bridge monitoring point of the bridge section during the dynamic load action process is constructed based on the dynamic stress data at each bridge monitoring point, specifically including: A bridge monitoring point is selected as a selected bridge monitoring point, the dynamic stress data of the selected bridge monitoring point is subjected to frequency domain transformation to obtain a dynamic stress spectrum; A plurality of stress cycles of the dynamic stress spectrum are extracted, and the dynamic stress amplitude and cycle number of each stress cycle are counted; A plurality of dynamic stress amplitude intervals are divided by all the dynamic stress amplitudes; The fatigue stress spectrum corresponding to the selected bridge monitoring point of the bridge section during the dynamic load action process is constructed by all the dynamic stress amplitude intervals and the cycle numbers corresponding to each dynamic stress amplitude interval; The fatigue stress spectrum corresponding to the remaining bridge monitoring points of the bridge section during the dynamic load action process is continuously determined.

3. The method of claim 1, wherein, The bridge structure stiffness corresponding to each monitoring key point of the bridge section under the static load is determined according to the static stress data corresponding to each monitoring key point. Obtain displacement data of each monitoring key point of the bridge section under the static load; Determine the static stress characteristics at each monitoring key point according to the static stress data of each monitoring key point; Determine the displacement response characteristics at each monitoring key point through the displacement data of each monitoring key point; Select a monitoring key point as a selected monitoring key point, and determine the bridge structure stiffness corresponding to the selected monitoring key point of the bridge section under the static load according to the static stress characteristics and the displacement response characteristics corresponding to the selected monitoring key point; Continue to determine the bridge structure stiffness corresponding to the remaining monitoring key points of the bridge section under the static load.

4. The method of claim 1, wherein, The bridge section is a bottom region of the bridge.

5. The method of claim 1, wherein, The bridge stress at each bridge monitoring point is monitored by a stress sensor.

6. A bridge structure monitoring system incorporating active early warning, which employs the method of any one of claims 1 to 5 for bridge structure monitoring, characterized by, The system comprises: A monitoring module for setting bridge monitoring points at different positions of the bridge section and monitoring the bridge stress at each bridge monitoring point; A processing module for obtaining dynamic stress data and static stress data at each bridge monitoring point, and constructing a fatigue stress spectrum corresponding to each bridge monitoring point of the bridge section under the dynamic load based on the dynamic stress data at each bridge monitoring point; The processing module is further configured to perform damage accumulation analysis on the bridge structure at each bridge monitoring point based on the stress distribution difference between each fatigue stress spectrum, obtain a damage accumulation coefficient of the bridge structure at each bridge monitoring point, and extract a plurality of monitoring key points from all bridge monitoring points by combining the damage accumulation coefficients with the dead load characteristics of the bridge section; The processing module is further configured to determine the bridge structure stiffness corresponding to each monitoring key point of the bridge section under the static load according to the static stress data corresponding to each monitoring key point, and determine a confidence interval for the structure damage active warning of the bridge section based on all bridge structure stiffnesses; An execution module for performing structure damage warning on the bridge section based on the confidence interval and the current bridge stress at each bridge monitoring point.

7. A computer device, comprising: The computer device comprises a memory and a processor, the memory stores a code, and the processor is configured to obtain the code and execute the bridge structure monitoring method combined with active warning according to any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, the computer-readable storage medium comprising: The computer program is executed by the processor to realize the bridge structure monitoring method combined with active warning according to any one of claims 1 to 5.

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