Absolute Stress Detection Method and System for Concrete Bridges

Abstract

The present invention relates to the technical field of stress detection, specifically a method and system for detecting the absolute stress of a concrete bridge, which includes the following steps: obtaining the stress data of the bridge main girder, bearings, box girders and main towers, collecting the data of wind speed and wind direction sensors, calculating the wind load gradient value, extracting the primary and secondary influence areas of wind load and the transfer buffer area, and generating a wind load area stress data set. In the present invention, through environmental factors and stress data, the influence of wind load on the structural force is identified to ensure the comprehensiveness of the data. By calculating the wind load gradient change rate and extracting the stress mutation area, the ability to identify weak points of the structure is improved. Time series analysis quantifies the stress fluctuation trend and deduces the cumulative change rate, making the fatigue damage prediction more accurate. The identification of abnormal points combined with the deviation ratio analysis corrects the measurement data and improves the analysis reliability. Based on the stress attenuation characteristics, fatigue damage information is extracted to optimize the local fatigue assessment, accurately lock the damaged area, and improve the accuracy of structural health monitoring.

Description

Technical Field

[0001] The present invention relates to the technical field of stress detection, and particularly to a method and system for detecting the absolute stress of a concrete bridge. Background Art

[0002] The technical field of stress detection includes measuring, analyzing, and evaluating the stress of materials, structures, or components under a stressed state. The core content of this technical field includes using various measurement methods, such as resistance strain gauges, fiber Bragg gratings, acoustic emission, ultrasonic waves, etc., to obtain stress information, and determining the stress distribution through signal acquisition, transmission, and computational analysis. Stress detection is widely used in industries such as civil engineering, aerospace, and mechanical manufacturing to ensure the structural safety and reliability. The development of this technical field involves sensor technology, data acquisition technology, optimization of stress calculation models, and improvement of experimental verification methods, enabling it to be applicable to stress analysis under different working conditions and complex structures.

[0003] Among them, the method for detecting the absolute stress of a concrete bridge refers to measuring the stress changes at key parts of the bridge structure for a specific stressed state of the concrete bridge, so as to accurately analyze the stress conditions of the bridge under different loads. The subject of this patent covers the method of measuring the surface strain of concrete based on resistance strain gauges, and calculating the internal stress distribution of the bridge structure in combination with the stress-strain relationship. The specific method includes arranging strain gauges at key stress-bearing positions of the bridge, collecting data using a strain gauge, and calculating the absolute stress based on the mechanical properties of the concrete material. In addition, temperature compensation technology is also used to reduce the influence of environmental temperature on the measurement results, and the measurement data is calculated through a data analysis model to obtain the accurate value of the bridge's stress state.

[0004] Traditional stress detection methods mainly rely on single-point or local measurements, making it difficult to comprehensively reflect the overall stress state of the bridge structure under different wind loads, resulting in limitations in identifying key stress-bearing areas. Due to the lack of refined analysis of the gradient change of wind loads, it is difficult to accurately extract stress mutation areas, resulting in a lag in identifying structural weak points and affecting the timeliness of safety assessment. When dealing with the stress fluctuation trend, existing methods often lack the support of time-series data, making it difficult to accurately describe the stress accumulation effect, resulting in deviations in fatigue damage assessment and affecting the accuracy of long-term health monitoring. In addition, the correction of abnormal stress data mainly relies on empirical judgment, lacking the support of deviation ratio analysis, which easily leads to inaccurate data correction and affects the reliability of measurement results. The method for identifying fatigue damage is relatively rough, lacking accurate extraction of local damaged areas, making it difficult to effectively monitor key stress-bearing parts and affecting the accuracy of structural health management. Summary of the Invention

[0005] The purpose of the present invention is to solve the drawbacks existing in the prior art, and to propose a method and system for detecting the absolute stress of a concrete bridge.

[0006] To achieve the above object, the present invention adopts the following technical solution: an absolute stress detection method for a concrete bridge, comprising the following steps:

[0007] S1: Obtain the stress data of the bridge main girder, bearings, box girders and main towers, collect the data of wind speed, wind direction and temperature sensors, calculate the wind load gradient value, extract the main and secondary influence areas of wind load and the transfer buffer area, and generate a wind load area stress data set;

[0008] S2: Based on the wind load area stress data set, calculate the wind load gradient change rate, screen the peak area affected by wind pressure, extract the stress sensor nodes, measure the stress change rate and time delay ratio, analyze the force path and determine the stress concentration point, evaluate the stress mutation rate, extract the wind vibration coupling influence area, analyze the force change trend, and obtain the distribution information of local stress concentration points;

[0009] S3: According to the distribution information of the local stress concentration points, calculate the stress change amount of the time series, study the stress fluctuation period, deduce the cumulative change rate, compare the stress threshold range, screen the stress mutation interval, and generate local stress cumulative influence data;

[0010] S4: Combine the local stress cumulative influence data, trace back the stress data, calculate the stress fluctuation rate of the abnormal points, analyze the characteristics of the stress fluctuation trend curve, calculate and compare the deviation ratio of the abnormal points according to the normal stress interval, adjust the stress value of the abnormal points, and obtain the abnormal stress correction value.

[0011] As a further solution of the present invention, the wind load area stress data set includes main girder stress data, bearing stress data, box girder stress data, main tower stress data, wind speed data, wind direction data, temperature data, wind load gradient value, main wind load influence area, secondary wind load influence area, wind load transfer buffer area, and the distribution information of the local stress concentration points includes wind load gradient change rate, peak area affected by wind pressure, stress sensor nodes, stress change rate, time delay ratio, force path, stress concentration point, stress mutation rate, wind vibration coupling influence area, force change trend, and the local stress cumulative influence data includes stress change amount of the time series, stress fluctuation period, cumulative change rate, stress threshold range, stress mutation interval, and the abnormal stress correction value includes abnormal point stress fluctuation rate, stress fluctuation trend curve characteristics, abnormal point deviation ratio, normal stress interval, abnormal point stress adjustment value.

[0012] As a further solution of the present invention, the specific steps of S1 are:

[0013] S101: Obtain the stress data of the bridge main girder, bearings, box girders and main towers. At the same time, collect the data of wind speed and wind direction sensors, record the values of the sensors at different time nodes, align the wind speed and wind direction data with the bridge structure stress data according to time, calculate the instantaneous stress increment of the monitoring points under the action of wind load, and statistically analyze the stress change trend of the measuring points at different times to obtain the stress increment data under the action of wind load;

[0014] S102: Based on the stress increment data under the action of the wind load, calculate the wind load gradient value of the monitoring points, determine the stress response rate in different wind speed intervals, calculate the stress ratio of the monitoring points under the action of the wind load, summarize the wind load change trend of the structural parts, and calculate the wind load action intensity of the overall structure in combination with the wind speed and wind direction data to obtain the wind load gradient value distribution data;

[0015] S103: According to the wind load gradient value distribution data, calculate the wind load influence value of the monitoring points, summarize the stress change areas of the structural parts, divide the main wind load influence area, secondary influence area and transfer buffer area according to the stress response rate, calculate the contribution of the wind load to the structural stress in the area, collect the wind load influence data of the area, and generate the wind load area stress data set.

[0016] As a further solution of the present invention, the specific steps of S2 are as follows:

[0017] S201: Based on the wind load area stress data set, calculate the wind load change rate of the sensor nodes at different time points, perform differential calculation on the time series to obtain the wind load gradient change rate, screen the areas where the wind load change rate exceeds the set wind load change threshold according to the amplitude of the change rate, and extract the stress sensor nodes in the area to obtain the wind load gradient change rate and stress sensor node data;

[0018] S202: Combine the wind load gradient change rate and stress sensor node data, calculate the stress change rate of the stress sensor nodes, and perform correlation analysis on the time series of the wind load gradient change rate and the stress change rate to measure the time delay ratio under the influence of the wind load to obtain the stress change rate and time delay ratio data;

[0019] S203: Based on the stress change rate and time delay ratio data, analyze the stress transfer path between the sensor nodes, calculate the stress accumulation degree of the transfer path, and determine the stress concentration point according to the cumulative gradient change situation to obtain the local stress concentration point distribution information.

[0020] As a further solution of the present invention, the specific calculation formula for calculating the stress accumulation degree of the transfer path is:

[0021] ;

[0022] Calculate the stress accumulation degree , determine the stress concentration points according to the cumulative gradient change situation, and obtain the distribution information of local stress concentration points;

[0023] Among them, represents the stress accumulation degree of the transmission path, represents the stress change amount at the th moment, represents the time interval at the th moment, represents the stress weight of the th node, represents the total number of sensor nodes, represents the stress value of the th sensor node, represents the stress weight factor of the th node, represents the number of effective nodes in the transmission path.

[0024] As a further solution of the present invention, the specific steps of S3 are:

[0025] S301: Obtain the distribution information of the local stress concentration points, extract the stress data at the time points, calculate the stress change amount between adjacent time points, construct time series data based on the stress change amount, extract the periodic fluctuation characteristics in the time series, compare the stress change trends in the change intervals in the time series, and generate a stress change trend analysis result;

[0026] S302: Based on the stress change trend analysis result, calculate the cumulative change amount of stress in different time periods, obtain the change rate on the time series, analyze the change characteristics of the change rate in different time intervals, compare the differences in the cumulative change rates of different time periods, and generate a stress cumulative change rate;

[0027] S303: According to the stress cumulative change rate, compare the preset stress threshold range, screen the intervals with stress mutations, calculate the amplitude and duration of the stress change in the mutation intervals, extract the abnormal fluctuation characteristics of the local stress, and generate local stress cumulative influence data.

[0028] As a further solution of the present invention, the specific steps of S4 are:

[0029] S401: Based on the local stress cumulative influence data, obtain the stress change amount at a moment, calculate the fluctuation amplitude in combination with the stress value in a time period, and calculate the stress fluctuation rate of the abnormal point according to the difference between the stress value of the abnormal point and the stress values of adjacent time points;

[0030] S402: According to the stress fluctuation rate of the abnormal point, compare the stress change data, calculate the slope and inflection point of the stress fluctuation trend curve, calculate the deviation ratio of the abnormal point according to the degree to which the fluctuation rate of the abnormal point deviates from the normal trend interval, and obtain the deviation ratio value of the abnormal point;

[0031] S403: Based on the deviation ratio value of the abnormal point, compare the change amplitude of the normal stress interval, calculate the correction value of the abnormal point, and adjust the stress value of the abnormal point according to the ratio of the original stress value of the abnormal point to the correction value to obtain the abnormal stress correction value.

[0032] As a further solution of the present invention, the specific calculation formula for comparing the change amplitude of the normal stress interval is:

[0033] ;

[0034] Calculate the stress change amplitude , based on the deviation ratio value of the abnormal point, calculate the correction value of the abnormal point, and adjust the stress value of the abnormal point according to the ratio of the original stress value of the abnormal point to the correction value to obtain the abnormal stress correction value;

[0035] Among them, represents the stress change amplitude, represents the th stress value of the measuring point, represents the total number of measuring points, represents the th stress value of the measuring point within the normal stress interval, represents the number of measuring points within the normal stress interval.

[0036] As a further solution of the present invention, the method further includes:

[0037] S5: Based on the abnormal stress correction value, calculate the fatigue damage ratio of the local area, analyze the stress change trend, deduce the fatigue damage accumulation amount, set the fatigue damage threshold, screen the fatigue damage overrun area according to the fatigue damage threshold, extract the stress attenuation characteristics of the damaged area, and obtain the fatigue damage distribution information;

[0038] The fatigue damage distribution information includes the fatigue damage ratio of the local area, the stress change trend, the fatigue damage accumulation amount, the fatigue damage threshold, the fatigue damage overrun area, and the stress attenuation characteristics;

[0039] The specific steps of S5 are:

[0040] S501: Based on the abnormal stress correction value, classify the stress data of the local area, screen the area where the stress exceeds the set reference value, calculate the fatigue damage ratio of the area, and compare the ratio data with the set fatigue damage threshold to obtain the fatigue damage overrun area data;

[0041] S502: Calculate the stress change amplitude at different time points based on the data of the fatigue damage over-limit area, judge the stress attenuation trend of the local area, calculate the cumulative fatigue damage value, and conduct zonal aggregation, extract the stress attenuation characteristics of the area to obtain the local stress attenuation trend.

[0042] S503: Based on the local stress attenuation trend, calculate the cumulative fatigue damage amount of the area, call the data of the fatigue damage over-limit area, calculate the overall fatigue damage distribution data, and combine with the regional stress change trend to conduct aggregation of the fatigue damage distribution to obtain the fatigue damage distribution information.

[0043] The absolute stress detection system for concrete bridges includes:

[0044] The wind load stress monitoring module is used to obtain the stress data of the bridge main girder, bearings, box girders and main towers, collect the data of the wind speed and wind direction sensors, calculate the wind load gradient value, identify the wind load action area, extract the stress change data of the area, calculate the wind load stress distribution, and obtain the wind load area stress data set.

[0045] The stress concentration point extraction module is used to calculate the wind load gradient change rate based on the wind load area stress data set, analyze the stress change rate and time delay ratio, identify the force path, and calculate the local stress concentration point distribution information.

[0046] The stress mutation interval identification module is used to calculate the stress change amount in the time series, analyze the stress fluctuation period, deduce the cumulative change trend, calculate the local stress change amplitude, and generate the local stress cumulative influence data according to the local stress concentration point distribution information.

[0047] The abnormal stress correction module is used to calculate the stress offset of the abnormal point, analyze the stress fluctuation trend, calculate the abnormal point deviation ratio, adjust the stress value of the abnormal point, and obtain the abnormal stress correction value based on the local stress cumulative influence data.

[0048] The fatigue damage assessment module is used to calculate the local area fatigue damage ratio, deduce the cumulative fatigue damage amount, calculate the stress attenuation rate of the damaged area, and obtain the fatigue damage distribution information based on the abnormal stress correction value. Description of the Drawings

[0049] Figure 1 It is the step flow schematic diagram of the present invention;

[0050] Figure 2 It is the system module diagram of the present invention. Detailed Embodiment

[0051] In order to make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0052] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the accompanying drawings. It is 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 should not be construed as a limitation to the present invention. In addition, in the description of the present invention, the meaning of "a plurality" is two or more unless otherwise specifically defined.

[0053] Please refer to Figure 1 , the absolute stress detection method for concrete bridges, including the following steps:

[0054] S1: Obtain the stress data of the bridge main girder, bearings, box girders and main towers, collect the data of wind speed and wind direction sensors, calculate the wind load gradient value, extract the main influence area, secondary influence area and transfer buffer area of the wind load, and generate the wind load area stress data set;

[0055] S2: Based on the wind load area stress data set, calculate the wind load gradient change rate, screen the peak area affected by wind pressure, extract the stress sensor nodes, measure the stress change rate and time delay ratio, analyze the force path and determine the stress concentration points, evaluate the stress mutation rate, extract the wind vibration coupling influence area, analyze the force change trend, and obtain the distribution information of local stress concentration points;

[0056] S3: According to the distribution information of local stress concentration points, calculate the time series stress change amount of the stress concentration points, study the stress fluctuation period, deduce the cumulative change rate, compare the stress threshold range, screen the stress mutation interval, and generate the local stress cumulative influence data;

[0057] S4: Combine the local stress cumulative influence data, trace back the stress data, calculate the stress fluctuation rate of the abnormal points, analyze the characteristics of the stress fluctuation trend curve, measure the deviation ratio of the abnormal points, compare the deviation ratio with the normal stress interval, adjust the stress value of the abnormal points, and obtain the abnormal stress correction value;

[0058] S5: Based on the abnormal stress correction value, calculate the fatigue damage ratio of the local area, analyze the stress change trend, deduce the cumulative amount of fatigue damage, set the fatigue damage threshold, screen the fatigue damage overrun area according to the fatigue damage threshold, extract the stress attenuation characteristics of the damaged area, and obtain the fatigue damage distribution information.

[0059] The wind load regional stress data set includes main girder stress data, support stress data, box girder stress data, main tower stress data, wind speed data, wind direction data, temperature data, wind load gradient value, main wind load influence area, secondary wind load influence area, wind load transfer buffer zone. The local stress concentration point distribution information includes wind load gradient change rate, peak area affected by wind pressure, stress sensor nodes, stress change rate, time delay ratio, force path, stress concentration points, stress mutation rate, wind vibration coupling influence area, force change trend. The local stress cumulative influence data includes time series stress change amount, stress fluctuation period, cumulative change rate, stress threshold range, stress mutation interval. The abnormal stress correction value includes abnormal point stress fluctuation rate, characteristics of stress fluctuation trend curve, abnormal point deviation ratio, normal stress interval, abnormal point stress adjustment value. The fatigue damage distribution information includes local area fatigue damage ratio, stress change trend, cumulative fatigue damage amount, fatigue damage threshold, fatigue damage overrun area, stress attenuation characteristics.

[0060] The specific steps of S1 are as follows:

[0061] S101: Obtain the stress data of the bridge main girder, support, box girder and main tower. At the same time, collect the data of wind speed and wind direction sensors, record the values of the sensors at different time nodes, align the wind speed and wind direction data with the bridge structure stress data according to time, calculate the instantaneous stress increment of the monitoring points under the action of wind load, and statistically analyze the stress change trend of the measuring points at different times to obtain the stress increment data under the action of wind load;

[0062] The bridge structure monitoring equipment first obtains stress data from structural parts such as the main girder, bearings, box girder, and main tower. At the same time, it collects data from wind speed, wind direction, and temperature sensors. The measuring equipment regularly collects various data through sensors deployed at different parts of the bridge. For example, the stress at the main girder can be measured using strain gauges, the bearing capacity change at the bearings can be obtained using displacement sensors, the temperature difference inside and outside the box girder is measured by temperature sensors, and the wind speed and wind direction can be recorded by meteorological sensors on the bridge. The values of all sensors need to be calibrated according to the time stamp and stored in the database for time alignment. Suppose at a certain moment t1, the main girder stress σ1 = 35 MPa, the wind speed v1 = 12 m / s, and the temperature T1 = 15 °C, while at t2, σ2 = 38 MPa, v2 = 14 m / s, and T2 = 16 °C. Then, the instantaneous stress increment Δσ = σ2 - σ1 = 3 MPa under the action of wind load. Similarly, this process is repeated at all monitoring points to obtain stress data at different time nodes and establish a data table. Then, according to the time series, the stress change trend of each measuring point is statistically analyzed, and the stress change amplitude under different wind speeds, wind directions, and temperature changes is analyzed. The stress change curve is fitted using the linear regression or moving average method. For example, if the stress increment trend fitted from multiple groups of data is Δσ = f(v, T), where f(v, T) represents the relationship function between the stress increment and wind speed and temperature, then the stress increment data under the action of wind load can be obtained through statistics.

[0063] S102: Based on the stress increment data under the action of wind load, calculate the wind load gradient value of the monitoring point, determine the stress response rate in the differential wind speed interval, calculate the stress ratio of the monitoring point under the action of wind load, summarize the wind load change trend of the structural part, and calculate the wind load action intensity of the overall structure in combination with wind speed, wind direction, and temperature data to obtain the wind load gradient value distribution data;

[0064] Based on the stress increment data under wind load, it is first necessary to calculate the wind load gradient value of the monitoring points. In the data processing stage, different wind speed intervals can be selected, such as low wind speed (0 - 5 m / s), medium wind speed (5 - 15 m / s), and high wind speed (above 15 m / s). Calculate the stress response rate in these intervals, that is, the ratio of the stress increment Δσ to the wind speed change Δv. Suppose the stress increment Δσ1 = 2 MPa and the wind speed change Δv1 = 3 m / s at a certain monitoring point in the low wind speed interval, then the stress response rate R1 = Δσ1 / Δv1 = 0.67 MPa / (m / s). In the high wind speed interval, Δσ2 = 5 MPa and Δv2 = 4 m / s, then R2 = Δσ2 / Δv2 = 1.25 MPa / (m / s). Then calculate the stress ratio under wind load, that is, the proportion of the stress increment of each monitoring point in the total stress change, summarize the wind load change trend of the structural parts, and calculate the wind load action intensity of the wind speed, wind direction and temperature data on the overall structure. For example, in a certain wind speed interval, calculate the average value of the stress increments of different monitoring points to obtain the wind load gradient value distribution data of the overall structure.

[0065] S103: According to the wind load gradient value distribution data, calculate the wind load influence value of the monitoring points, summarize the stress change area of the structural parts, divide the main wind load influence area, secondary influence area and transfer buffer area according to the stress response rate, calculate the contribution of the wind load to the structure stress in the area, collect the wind load influence data of the area, and generate the wind load area stress data set;

[0066] According to the wind load gradient value distribution data, calculate the wind load influence value of the monitoring points, that is, the stress increment contribution value of each monitoring point in a specific wind speed interval, summarize the stress change area of the structural parts, and divide the main wind load influence area, secondary influence area and transfer buffer area by using the stress response rate. For example, if the stress response rate in the main beam area is higher than 1 MPa / (m / s), it is designated as the main influence area. If the stress response rate in the support area is between 0.5 - 1 MPa / (m / s), it is the secondary influence area, and the area below 0.5 MPa / (m / s) is designated as the transfer buffer area. Calculate the contribution of the wind load to the structure stress in each area. For example, the stress increment of a certain measuring point in the main influence area is Δσ3 = 4 MPa, the secondary influence area is Δσ4 = 2 MPa, and the transfer buffer area is Δσ5 = 1 MPa. Then calculate the wind load influence data of each area respectively and summarize them to generate the wind load area stress data set.

[0067] The specific steps of S2 are as follows:

[0068] S201: Based on the wind load regional stress dataset, calculate the wind load change rate of the sensor nodes at different time points, perform differential calculation on the time series, obtain the wind load gradient change rate, screen the regions where the wind load change rate exceeds the set wind load change threshold according to the magnitude of the change rate, extract the stress sensor nodes within the regions, and obtain the wind load gradient change rate and the stress sensor node data;

[0069] Based on the wind load regional stress dataset, first extract the wind load values of each sensor node at different time points, calculate its wind load change rate, obtain the increment of the wind load through the time series difference method, and smooth the data to reduce noise interference. Subsequently, calculate the wind load gradient change rate, that is, perform a second difference on the change rate data, and screen the regions where the wind load change rate exceeds the set threshold. For example, in a wind load monitoring system of a high-rise building, the wind load time series data is successively recorded on sensors A, B, and C. Suppose the wind load values at five consecutive moments at point A are 5.1, 5.8, 6.3, 7.1, and 7.9 (unit: kN / m²) respectively. After calculating the wind load change rate, we get 0.7, 0.5, 0.8, and 0.8. Then, perform gradient calculation on the change rate data and find that the change is obvious at some moments. Set the wind load change threshold to 0.2 kN / m². Comparing the calculation results, if the change rate at some moments exceeds this threshold, then extract the stress sensor data corresponding to that time point. Finally, obtain the wind load gradient change rate and the relevant sensor node data.

[0070] S202: Combine the wind load gradient change rate and the stress sensor node data, calculate the stress change rate of the stress sensor nodes, perform a correlation analysis on the time series of the wind load gradient change rate and the stress change rate, measure the time delay ratio under the influence of the wind load, and obtain the stress change rate and the time delay ratio data;

[0071] Combine the wind load gradient change rate and the stress sensor node data, analyze the change of stress over time, calculate the stress change rate, perform a correlation analysis with the wind load gradient change rate, use statistical methods to calculate the correlation degree between the two, and perform time delay analysis to obtain the time delay ratio of the influence of wind load change on stress change. In actual engineering applications, assume that the sensor monitoring data on a bridge structure records the wind load gradient change rate and the stress change rate at multiple moments. Calculate the correlation between the two and find that there is a strong correlation between them. Then, further analyze the lag time of the wind load on the stress change. For example, the peak of the wind load change rate of a certain sensor node appears at 5 seconds, and the peak of the stress change rate appears at 7 seconds. Then, the calculated time delay ratio is 40%. Through multi-point analysis, obtain the overall stress change rate and the time delay ratio data.

[0072] S203: Analyze the stress transfer path between sensor nodes based on the stress change rate and time delay ratio data, calculate the stress accumulation degree of the transfer path, and determine the stress concentration points according to the cumulative gradient change situation to obtain the local stress concentration point distribution information;

[0073] The specific calculation formula for calculating the stress accumulation degree of the transfer path is:

[0074] ;

[0075] Calculate the stress accumulation degree , and determine the stress concentration points according to the cumulative gradient change situation to obtain the local stress concentration point distribution information;

[0076] Among them, represents the stress accumulation degree of the transfer path, represents the stress change amount at the th moment, represents the time interval at the th moment, represents the stress weight of the th node, represents the total number of sensor nodes, represents the th stress value of the sensor node, represents the stress weight factor of the th node, represents the number of effective nodes in the transfer path;

[0077] Calculate the weighted absolute value sum of the stress change rate:

[0078] Stress change amount (Δσ): The stress difference between adjacent time points measured by the sensor. Assume that at time t1 and t2, the stress values measured by the sensor are 50 MPa and 55 MPa respectively, then Δσ = 55 MPa - 50 MPa = 5 MPa.

[0079] Time interval (Δt): The time difference between adjacent stress measurement values. Assume t1 = 10 s, t2 = 12 s, then Δt = 12 s - 10 s = 2 s.

[0080] Stress change rate (Δσ / Δt): The ratio of the stress change amount to the time interval, indicating the rate of stress change. For the above values, Δσ / Δt = 5 MPa / 2 s = 2.5 MPa / s.

[0081] Stress weight (w): Reflects the importance of each node in the stress transfer path. The weight is set according to factors such as the position of the node in the structure and material properties. Assume that a certain node has a higher importance and w = 1.2 is set.

[0082] Calculate the weighted absolute value: Multiply the absolute value of the stress change rate by the corresponding weight. For the above values, |Δσ / Δt|×w = |2.5 MPa / s|×1.2 = 3 MPa / s.

[0083] Accumulate the weighted absolute values of all nodes: Sum up the weighted stress change rates of all n nodes to obtain the result of the first part.

[0084] Calculate the square root of the weighted sum of the squared stresses:

[0085] Node stress value (σ): The stress value measured by the sensor at each node. Assume the stress value at a certain node is 60 MPa.

[0086] Stress weight factor (k): Used to adjust the influence degree of the stress value at each node, and is set according to factors such as the elastic modulus and cross-sectional area of the node material. Assume k = 0.8 for this node.

[0087] Calculate the weighted value of the squared stress: Multiply the squared stress value by the corresponding weight factor. For the above values, k×σ 2 = 0.8×(60 MPa) 2 = 0.8×3600 (MPa) 2 = 2880 (MPa) 2 .

[0088] Accumulate the weighted squared stress values of all valid nodes: Sum up the weighted squared stress values of all m valid nodes.

[0089] Take the square root: Take the square root of the accumulated result to obtain the result of the second part.

[0090] Sum to obtain the stress accumulation degree (S a cc):

[0091] Add the above two parts of the results to obtain the stress accumulation degree S a cc.

[0092] Example calculation:

[0093] Suppose there are 3 nodes, and their stress measurement data are as follows:

[0094] Node 1: σ1 = 50 MPa, Δσ1 = 5 MPa, Δt1 = 2 s, w1 = 1.0, k1 = 0.9;

[0095] Node 2: σ2 = 55 MPa, Δσ2 = 4 MPa, Δt2 = 1.5 s, w2 = 1.1, k2 = 0.85;

[0096] Node 3: σ3 = 60 MPa, Δσ3 = 6 MPa, Δt3 = 2.5 s, w3 = 1.2, k3 = 0.8;

[0097] Calculation process:

[0098] Calculate the weighted absolute value sum of the stress change rate:

[0099] Node 1: |Δσ1 / Δt1|×w1 = |5 MPa / 2 s|×1.0 = 2.5 MPa / s;

[0100] Node 2: |Δσ2 / Δt2|×w2 = |4 MPa / 1.5 s|×1.1 ≈ 2.933 MPa / s;

[0101] Node 3: |Δσ3 / Δt3|×w3 = |6 MPa / 2.5 s|×1.2 = 2.88 MPa / s;

[0102] Accumulated result: 2.5 + 2.933 + 2.88 ≈ 8.313 MPa / s;

[0103] Calculate the square root of the weighted sum of the squared stresses:

[0104] Node 1: k1×σ1 2 = 0.9×(50 MPa) 2 = 0.9×2500 = 2250 (MPa) 2

[0105] Node 2: k2×σ2 2 = 0.85×(55 MPa) 2 = 0.85×3025 ≈ 2571.25 (MPa) 2

[0106] Node 3: k3×σ3 2 = 0.8×(60 MPa) 2 = 0.8×3600 = 2880 (MPa) 2

[0107] Accumulated result: 2250 + 2571.25 + 2880 ≈ 7701.25 (MPa) 2

[0108] Take the square root: ≈ 87.75 MPa;

[0109] Calculate the stress accumulation degree (S a cc):

[0110] S a cc = 8.313 MPa / s + 87.75 MPa ≈ 96.063 MPa

[0111] Result description:

[0112] The calculated stress accumulation degree S a cc is 96.063 MPa. This result indicates that, considering the weighted influence of the stress change rate and the nodal stress value comprehensively, the stress accumulation degree of the transmission path is 96.063 MPa. This value can be used to evaluate the risk degree of the stress concentration area in the structure.

[0113] The specific steps of S3 are as follows:

[0114] S301: Obtain the distribution information of local stress concentration points, extract the stress data at time points, calculate the stress change amount between adjacent time points, construct time series data based on the stress change amount, extract the periodic fluctuation characteristics in the time series, compare the stress change trends in the change intervals in the time series, and generate the stress change trend analysis result;

[0115] First, based on finite element analysis software such as Abaqus or ANSYS, perform a force analysis on the target structure, establish a three-dimensional mesh model and apply corresponding boundary conditions and loads, calculate the stress distribution data at each mesh node, screen out the areas with higher stress through stress nephogram or data extraction methods, and analyze the local stress concentration points based on the stress gradient change. Subsequently, extract the stress data at multiple time points, calculate the difference between the stress values of every two adjacent time points to obtain the stress change amount, construct time series data, adopt time series analysis methods such as wavelet transform or Fourier transform to extract the periodic fluctuation characteristics, analyze the stress increase and decrease in each time period by comparing the stress change trends in different time windows in the time series. For example, if the stress value increases by 10 MPa at a certain moment compared with the previous moment and then decreases by 5 MPa, the stress trend in this interval shows an initial increase and then a decrease. Summarize and organize the analyzed trend information to form the stress change trend analysis result.

[0116] S302: Based on the stress change trend analysis result, calculate the cumulative change amount of stress in different time periods, obtain the change rate on the time series, analyze the change characteristics of the change rate in different time intervals, compare the differences in the cumulative change rates of different time periods, and generate the stress cumulative change rate;

[0117] Based on the analysis results of the stress change trend, calculate the cumulative stress change amount within different time periods. First, select a time interval and calculate the sum of all stress change values within this interval to quantify the cumulative stress change. At the same time, calculate the average change rate within this interval by dividing the total stress change within the interval by the time span to obtain the average stress change rate per unit time. Calculate this index for different time intervals respectively to judge the differences in the stress change trend. For example, if the cumulative stress change is 50 MPa within the first 5 seconds and 20 MPa within the next 5 seconds, the stress change rate in the previous time period is higher. Further compare the cumulative change rates of different time periods to observe whether there is an obvious change pattern. Use methods such as data clustering or principal component analysis to classify the change rate data to more clearly show the law of stress change, and finally obtain the cumulative stress change rate.

[0118] S303: According to the cumulative stress change rate, compare with the preset stress threshold range, screen the intervals with stress mutations, calculate the amplitude and duration of the stress change within the mutation intervals, extract the abnormal fluctuation characteristics of the local stress, and generate local stress cumulative impact data;

[0119] According to the cumulative stress change rate, compare with the preset stress threshold range, screen the intervals with stress mutations. First, set the threshold range for stress mutations. For example, if the stress change rate within a certain time period exceeds the set threshold, it is marked as a mutation interval. Further analyze the stress change amplitude within the mutation interval, that is, calculate the difference between the maximum stress value and the minimum stress value within this interval. At the same time, record the duration of the mutation interval. For example, within a certain interval, the stress drops from 100 MPa to 60 MPa instantaneously and lasts for 2 seconds, then this area belongs to the stress mutation area. Subsequently, extract the abnormal fluctuation characteristics of the local stress and analyze the impact of these abnormal points on the overall structure. For example, use data classification methods to distinguish between the mutation area and the normal area, and summarize the distribution of the mutation stress points, and finally generate local stress cumulative impact data.

[0120] The specific steps of S4 are as follows:

[0121] S401: Based on the local stress cumulative impact data, obtain the stress change amount at a moment, calculate the fluctuation amplitude in combination with the stress values of the time period, and calculate the stress fluctuation rate of the abnormal points according to the difference between the stress values of the abnormal points and the stress values of adjacent time points.

[0122] First, it is necessary to collect the stress data of the material at different time points and record its historical changes. A stress sensor is used to measure the stress at a predetermined position and store the data in the monitoring system. After the data is recorded, it is necessary to calculate the stress change between adjacent time points. Usually, the difference calculation is used, that is, by comparing the stress values of the two adjacent time points, the change amount is obtained. If the time interval is short, the stress fluctuation with time can be more accurately reflected. On this basis, a time range needs to be selected, such as one minute, ten minutes or one hour, etc., and the maximum and minimum stress values are found within this time range, and then the difference between them is calculated to obtain the stress fluctuation amplitude within this time period, so as to effectively evaluate the overall stress fluctuation with time. Then, it is necessary to screen out the stress abnormal points. Usually, a statistical-based method is used, such as calculating the average value and standard deviation of all the collected stress data and setting a reasonable abnormal determination range, such as the average value plus or minus three times the standard deviation. The points outside this range are abnormal points. Once the abnormal points are determined, the next step is to calculate the stress fluctuation rate of these abnormal points, that is, to compare the stress value of the abnormal point with the stress value of the previous time point and calculate the rate in combination with the time interval. This can help identify the situations where the stress changes violently. In practical applications, for example, in the process of structural health monitoring of a bridge, stress sensors can be arranged at positions such as the bridge deck and bridge piers, and data is collected and the stress fluctuation rate of the abnormal points is calculated according to the above method for subsequent further analysis and adjustment of the stress values of the abnormal points.

[0123] S402: According to the stress fluctuation rate of the abnormal points, compare the stress change data, calculate the slope and inflection point of the stress fluctuation trend curve, and calculate the abnormal point deviation ratio according to the degree of deviation of the fluctuation rate of the abnormal points from the normal trend interval to obtain the abnormal point deviation ratio value;

[0124] According to the stress fluctuation rate of the abnormal points, it is necessary to further analyze the overall change trend of stress over time. First, historical stress data can be used to plot the stress change curve and calculate the slope of the curve. The slope reflects the stress change rate. By calculating the average slope between multiple time points, the overall stress trend can be obtained. On this basis, it is necessary to find the inflection points, that is, the positions where the stress change trend changes significantly. It can be judged which time points have obvious inflection points by comparing the stress change rates in adjacent time periods. For example, if the stress change rate at a certain time point changes suddenly compared with the previous and subsequent time periods, this point can be considered an inflection point. After identifying the inflection points, it is necessary to calculate the deviation degree between the fluctuation rate of the abnormal points and the overall trend. Usually, it is by comparing the rate of the abnormal points and the rate of the normal trend and calculating the deviation ratio between the two. This ratio can reflect whether the fluctuation of the abnormal points is far from the overall stress change trend. For example, during the operation of mechanical equipment, if it is found that the stress change rate of a certain component is much higher than the overall trend, it indicates that there may be abnormal wear or overload of this component. After calculation, the deviation ratio value of the abnormal points can be obtained, and further determine which abnormal points need to be adjusted.

[0125] S403: Based on the deviation ratio value of the abnormal points, compare the change amplitude of the normal stress range, calculate the correction value of the abnormal points, and adjust the stress value of the abnormal points according to the ratio of the original stress value of the abnormal points to the correction value to obtain the corrected abnormal stress value;

[0126] The specific calculation formula for comparing the change amplitude of the normal stress range is:

[0127] ;

[0128] Calculate the stress change amplitude , based on the deviation ratio value of the abnormal points, calculate the correction value of the abnormal points, and adjust the stress value of the abnormal points according to the ratio of the original stress value of the abnormal points to the correction value to obtain the corrected abnormal stress value;

[0129] Among them, represents the stress change amplitude, represents the stress value of the th measurement point, represents the total number of measurement points, represents the stress value of the th measurement point within the normal stress range, represents the number of measurement points within the normal stress range,

[0130] Parameter acquisition method:

[0131] Stress value ( and ):By arranging sensors such as strain gauges on the surface of the structure, measuring the strain values at each measuring point, and then using the elastic modulus ( ) and Poisson's ratio ( ) of the material, the stress value is calculated according to Hooke's law.

[0132] Number of measuring points ( and ): Determined by the number of actually arranged sensors. Among them, the number of measuring points in the normal stress range needs to be determined according to the measurement results and the preset normal stress range.

[0133] Specific example:

[0134] Suppose 10 measuring points are arranged on a certain structure (i.e., ), and through measurement and calculation, the stress values of each measuring point are as follows (unit: MPa):

[0135] ;

[0136] Step 1: Calculate ;

[0137] First, calculate the sum of the absolute values of the stress values of all measuring points:

[0138] ;

[0139] Then, calculate the average value:

[0140] ;

[0141] Step 2: Determine the normal stress range and calculate ;

[0142] Suppose the normal stress range is 12 MPa to 15 MPa, so the stress values of the measuring points that meet this range are:

[0143] ;

[0144] The number of measuring points corresponding to these values is .

[0145] Calculate the sum of the squares of the stress values of these measuring points:

[0146] ;

[0147] Then, calculate the average value and take the square root:

[0148] ;

[0149] Step 3: Calculate the stress change amplitude

[0150] Substitute the above results into the formula:

[0151] ;

[0152] Result analysis:

[0153] The calculated stress change amplitude MPa. This result indicates that the product of the average absolute value of the measured point stress value and the square average value of the stress values within the normal stress range is 186.54 MPa. This value can be used to evaluate the stress distribution of the structure, and further provide a reference for subsequent abnormal point correction and stress adjustment.

[0154] The specific steps of S5 are as follows:

[0155] S501: Based on the abnormal stress correction value, classify the stress data in the local area, screen the areas where the stress exceeds the set reference value, calculate the fatigue damage ratio of the area, compare the ratio data with the set fatigue damage threshold, and obtain the data of the fatigue damage overrun area;

[0156] Based on the abnormal stress correction value, it is first necessary to classify the stress data in the local area to ensure that the stress levels in different areas can reasonably reflect their true stress conditions. Specifically, statistical analysis can be carried out according to the stress history data of different areas, for example, classification can be carried out according to the ranges of the maximum stress, minimum stress and average stress for subsequent processing. Then, based on engineering experience or experimental data, the abnormal stress values are corrected to reduce the influence of data deviation on the calculation. For example, if the stress value in a certain area is abnormally high or low, the stress data of adjacent areas can be referred to for reasonable correction; after the correction is completed, a reference value needs to be set to evaluate the stress conditions in each area. The setting of the reference value can refer to the yield strength, fatigue limit of the material or historical monitoring data. For example, for a certain specific metal material, its fatigue limit may be about 250 MPa, so 250 MPa can be set as the stress reference value of this material. Subsequently, the stress data of all local areas are compared, the areas exceeding the reference value are screened out, and the fatigue damage ratio of these areas is further calculated. The calculation of fatigue damage usually follows the cumulative damage theory, that is, considering the relationship between the number of cycles and the fatigue life of a certain area under different stress levels. For example, if a certain area has endured 5000 cycles at a stress level of 100 MPa, and the fatigue life at this stress level is 20000 cycles, then the fatigue damage ratio of this area is 0.25. After calculating the damage ratios of all areas using a similar method, they are classified and sorted, and compared with the set fatigue damage threshold to determine which areas have fatigue damage exceeding the safe range. For example, if the set fatigue damage threshold is 0.3, then all areas with a damage ratio greater than 0.3 are determined as areas with excessive fatigue damage, and finally the data of areas with excessive fatigue damage are obtained.

[0157] S502: According to the data of areas with excessive fatigue damage, calculate the stress change amplitude at different time points, judge the stress attenuation trend of the local area, calculate the cumulative fatigue damage value, and conduct zonal aggregation to extract the stress attenuation characteristics of the area, so as to obtain the local stress attenuation trend;

[0158] After obtaining the data of the fatigue damage over-limit areas, it is necessary to further analyze the variation of stress in these areas over time to determine whether there is a stress attenuation trend. Specifically, the stress data of these areas can be collected at multiple time points, and the stress change amplitude between each time point can be calculated. The stress change amplitude can be calculated as the difference between the maximum stress and the minimum stress. For example, in a certain area, the maximum stress value within a certain time period is 120 MPa, and the minimum stress value is 90 MPa, then the stress change amplitude is 30 MPa. By comparing the stress data at multiple time points, the stress change situation in this area can be observed; after obtaining the stress change data at different time points, it is necessary to further determine the stress attenuation trend in the local area. The analysis of the stress attenuation trend can adopt the data fitting method, such as observing whether the change of long-term stress data shows a downward trend. If the stress level in a certain area has been continuously decreasing in the recent month, for example, from 120 MPa to 100 MPa, and the decreasing trend is stable, it can be determined that there is stress attenuation in this area. Subsequently, the cumulative fatigue damage value is calculated based on these data, and the areas with similar stress attenuation characteristics are classified and sorted. For example, if the stress attenuation rate in a certain area is 2 MPa / day, while the attenuation rate in another area is 1.8 MPa / day, they can be classified into the same category for subsequent processing. Finally, through data collection and trend extraction, the stress attenuation trend information of the local area is obtained.

[0159] S503: Based on the local stress attenuation trend, calculate the cumulative fatigue damage of the area, call the data of the fatigue damage over-limit areas, calculate the overall fatigue damage distribution data, and combine the regional stress change trend to collect the fatigue damage distribution to obtain the fatigue damage distribution information;

[0160] Based on the local stress attenuation trend, it is necessary to further calculate the fatigue damage accumulation amount in each area. The calculation of the fatigue damage accumulation amount is still based on the cumulative damage theory and combines the data in the areas where the fatigue damage exceeds the limit to deduce the overall fatigue damage distribution. During the calculation process, it is necessary to collect the fatigue damage ratios of all areas and consider the weight factors of each area. For example, when the fatigue damage ratios in multiple areas are different, it is necessary to perform weighted processing according to the area, stress level or usage conditions of each area to obtain the overall fatigue damage distribution. For example, if the fatigue damage ratio of a certain area is 0.25 and the weight is 0.4, and the damage ratio of another area is 0.35 and the weight is 0.6, the overall fatigue damage ratio can be calculated as 0.31 by the weighted average method; after calculating the overall fatigue damage distribution data, it is also necessary to classify and organize it in combination with the stress change trend of the area. The stress change trend of the area can be classified according to different change rates. For example, a standard can be set to define the area with a stress change rate lower than 1 MPa / day as the low change area, the area with a stress change rate of 1 - 5 MPa / day as the medium change area, and the area with a stress change rate higher than 5 MPa / day as the high change area. Through this classification method, the overall fatigue damage data can be effectively classified, making the fatigue damage distribution in different areas clearer. Finally, organize and output the fatigue damage distribution information for subsequent analysis and processing.

[0161] Please refer to Figure 2 , the absolute stress detection system for concrete bridges, including:

[0162] The wind load stress monitoring module obtains the stress data of the bridge main girder, bearings, box girders and main towers, collects the data of the wind speed and wind direction sensors, calculates the wind load gradient value, identifies the wind load acting area, extracts the stress change data of the area, calculates the wind load stress distribution, and obtains the wind load area stress data set;

[0163] The stress concentration point extraction module calculates the wind load gradient change rate based on the wind load area stress data set, analyzes the stress change rate and time delay ratio, identifies the force path, and calculates the local stress concentration point distribution information;

[0164] The stress mutation interval identification module calculates the time series stress change amount according to the local stress concentration point distribution information, analyzes the stress fluctuation period, deduces the cumulative change trend, calculates the local stress change amplitude, and generates the local stress cumulative influence data;

[0165] The abnormal stress correction module calculates the stress offset amount of the abnormal point based on the local stress cumulative influence data, analyzes the stress fluctuation trend, calculates the abnormal point deviation ratio, adjusts the stress value of the abnormal point, and obtains the abnormal stress correction value;

[0166] The fatigue damage assessment module calculates the fatigue damage ratio of the local area, derives the cumulative amount of fatigue damage, calculates the stress attenuation rate of the damaged area, and obtains the fatigue damage distribution information based on the abnormal stress correction value.

[0167] The above are only the preferred embodiments of the present invention, and do not limit the present invention in other forms. Any person skilled in the art may use the technical content disclosed above to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, as long as it does not depart from the technical solution content of the present invention, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A method for detecting absolute stress of a concrete bridge, characterized in that: The following steps are involved: S1: Obtain stress data of bridge main beams, supports, box beams and main towers, collect wind speed and wind direction sensor data, calculate wind load gradient values, extract wind load main influence area, secondary influence area and transfer buffer zone, and generate wind load regional stress data set; S2: Based on the stress data set of the wind load area, calculate the wind load gradient change rate, screen the peak area of ​​wind pressure influence, extract stress sensor nodes, measure the stress change rate and time delay ratio, analyze the force path and determine the stress concentration point, evaluate the stress mutation rate, extract the wind-vibration coupling influence area, analyze the force change trend, and obtain the local stress concentration point distribution information; S3: According to the distribution information of the local stress concentration points, calculate the time series stress change, study the stress fluctuation period, derive the stress cumulative change gradient, compare the stress threshold range, screen the stress mutation interval, and generate local stress cumulative impact data; S4: combining the local stress cumulative impact data, tracing back the stress data, calculating the stress fluctuation rate of the abnormal point, analyzing the characteristics of the stress fluctuation trend curve, calculating and comparing the abnormal point deviation ratio according to the normal stress interval, adjusting the abnormal point stress value, and obtaining the abnormal stress correction value; The specific steps of S2 are: S201: Based on the wind load regional stress data set, the wind load change rate of the sensor node at the difference time point is calculated, and the time series is differentially calculated to obtain the wind load gradient change rate, and the area where the wind load gradient change rate exceeds the set wind load change threshold is screened according to the amplitude of the wind load gradient change rate, and the stress sensor nodes in the area are extracted to obtain the wind load change rate gradient and stress sensor node data; S202: Calculate the stress change rate of the stress sensor node in combination with the wind load change rate gradient and the stress sensor node data, perform correlation analysis on the time series of the wind load gradient change rate and the stress change rate, determine the time delay ratio under the influence of the wind load, and obtain the stress change rate and time delay ratio data; S203: Based on the stress change rate and time delay ratio data, analyzing the stress transmission path between the sensor nodes, calculating the stress accumulation degree of the transmission path, and determining the stress concentration point according to the cumulative gradient change, and obtaining the local stress concentration point distribution information; The specific calculation formula for calculating the stress accumulation degree of the transfer path is: ； Calculate the degree of stress accumulation , according to the cumulative gradient change, the stress concentration point is determined and the distribution information of the local stress concentration point is obtained; in, Represents the degree of stress accumulation in the transfer path, Representative The stress variation of each node is Representative The time interval between nodes, Representative The stress weight of each node, represents the total number of sensor nodes, Representative The stress value of each sensor node, Representative The stress weight factor of each node is Represents the number of valid nodes in the transfer path.

2. The method for detecting absolute stress of a concrete bridge according to claim 1, characterized in that: The wind load area stress data set includes main beam stress data, support stress data, box beam stress data, main tower stress data, wind speed data, wind direction data, temperature data, wind load gradient value, wind load main influence area, secondary influence area and transfer buffer zone; the local stress concentration point distribution information includes wind load gradient change rate, wind pressure influence peak area, stress sensor node, stress change rate, time delay ratio, force path, stress concentration point, stress mutation rate, wind-vibration coupling influence area, and force change trend; the local stress cumulative influence data includes time series stress change amount, stress fluctuation period, cumulative change rate, stress threshold range, and stress mutation interval; the abnormal stress correction value includes abnormal point stress fluctuation rate, stress fluctuation trend curve characteristics, abnormal point deviation ratio, normal stress interval, and abnormal point stress adjustment value.

3. The method for detecting absolute stress of a concrete bridge according to claim 1, characterized in that: The specific steps of S1 are: S101: Obtain stress data of the bridge main beam, support, box beam and main tower, collect wind speed and wind direction sensor data at the same time, record the sensor values ​​at different time nodes, align the wind speed and wind direction with the bridge structure stress data in time, calculate the instantaneous stress increment of the monitoring point under the wind load, and count the stress change trend of the measuring point at different times to obtain the stress increment data under the wind load; S102: Based on the stress increment data under the wind load, the wind load gradient value of the monitoring point is calculated, the stress response rate under the differential wind speed range is determined, the wind load stress ratio of the monitoring point is calculated, the wind load change trend of the structural part is summarized, and the wind load intensity of the whole structure is calculated in combination with the wind speed and wind direction data to obtain the wind load gradient value distribution data; S103: Calculate the wind load impact value of the monitoring point according to the wind load gradient value distribution data, summarize the stress change area of ​​the structural part, divide the wind load main impact area, secondary impact area and transfer buffer area according to the stress response rate, calculate the contribution of the wind load in the area to the structural stress, collect the wind load impact data of the area, and generate a wind load area stress data set.

4. The method for detecting absolute stress of a concrete bridge according to claim 3, characterized in that: The specific steps of S3 are: S301: Obtain the distribution information of the local stress concentration point, extract the stress data at the time point, and calculate the stress change between adjacent time points, construct time series data based on the stress change, extract the periodic fluctuation characteristics in the time series, compare the stress change trend of the change interval in the time series, and generate a stress change trend analysis result; S302: Based on the stress change trend analysis result, the cumulative change of stress in the difference time period is calculated, and the cumulative change rate in the time series is obtained, and the change characteristics of the cumulative change rate in the difference time interval are analyzed, and the difference of the cumulative change rate in the time period is compared to generate the stress cumulative change gradient; S303: According to the stress accumulation change gradient, a preset stress threshold range is compared, a stress mutation interval is screened, the amplitude and duration of stress change in the stress mutation interval are calculated, abnormal fluctuation characteristics of local stress are extracted, and local stress accumulation influence data is generated.

5. The method for detecting absolute stress of a concrete bridge according to claim 4, characterized in that: The specific steps of S4 are: S401: Based on the local stress cumulative impact data, the stress change at each moment is obtained, the fluctuation amplitude is calculated in combination with the stress value of the time period, and the stress fluctuation rate of the abnormal point is calculated according to the difference between the stress value of the abnormal point and the stress value of the adjacent time point; S402: Compare stress change data according to the stress fluctuation rate of the abnormal point, calculate the slope and inflection point of the stress fluctuation trend curve, calculate the abnormal point deviation ratio according to the degree to which the fluctuation rate of the abnormal point deviates from the normal trend interval, and obtain the abnormal point deviation ratio value; S403: Based on the abnormal point deviation ratio value, the abnormal point stress adjustment value is calculated by comparing the change range of the normal stress interval, and the abnormal point stress value is adjusted according to the ratio of the abnormal point original stress value to the abnormal point stress adjustment value to obtain the abnormal stress correction value.

6. The method for detecting absolute stress of a concrete bridge according to claim 5, characterized in that: The specific calculation formula for the change range compared to the normal stress interval is: ； Calculate the stress change amplitude , based on the deviation ratio value of the abnormal point, the correction value of the abnormal point is calculated, and the stress value of the abnormal point is adjusted according to the ratio of the original stress value of the abnormal point to the correction value to obtain the abnormal stress correction value; in, represents the stress variation amplitude, Representative The stress value of each measuring point, Represents the total number of measurement points, Represents the normal stress range The stress value of each measuring point, Represents the number of measuring points within the normal stress range.

7. The method for detecting absolute stress of a concrete bridge according to claim 5, characterized in that: The method further comprises: S5: Based on the abnormal stress correction value, calculate the fatigue damage ratio of the local area, analyze the stress change trend, derive the fatigue damage accumulation, set the fatigue damage threshold, screen the fatigue damage over-limit area according to the fatigue damage threshold, extract the stress attenuation characteristics of the damaged area, and obtain the fatigue damage distribution information; The fatigue damage distribution information includes fatigue damage ratio of local area, stress change trend, fatigue damage accumulation, fatigue damage threshold, fatigue damage over-limit area, and stress attenuation characteristics; The specific steps of S5 are: S501: Based on the abnormal stress correction value, the stress data of the local area is classified, the area where the stress exceeds the set reference value is screened, the fatigue damage ratio of the area is calculated, and the fatigue damage ratio data is compared with the set fatigue damage threshold to obtain fatigue damage excess area data; S502: Calculate the stress change amplitude at the difference time point according to the fatigue damage over-limit area data, judge the stress attenuation trend of the local area, calculate the cumulative fatigue damage value, and perform partitioning and grouping to extract the stress attenuation characteristics of the area to obtain the local stress attenuation trend; S503: Based on the local stress attenuation trend, the fatigue damage accumulation of the region is calculated, and the fatigue damage excess region data is called to calculate the overall fatigue damage distribution data. Combined with the regional stress change trend, the fatigue damage distribution is aggregated to obtain fatigue damage distribution information. 8.Concrete bridge absolute stress detection system, characterized in that: According to the method for detecting absolute stress of a concrete bridge according to any one of claims 1 to 7, the system comprises: Wind load stress monitoring module, used to obtain stress data of bridge main beams, supports, box beams and main towers, collect wind speed and wind direction sensor data, calculate wind load gradient values, identify wind load action areas, extract regional stress change data, calculate wind load stress distribution, and obtain wind load regional stress data sets; A stress concentration point extraction module is used to calculate the wind load gradient change rate, analyze the stress change rate and time delay ratio, identify the force path, and calculate the local stress concentration point distribution information based on the wind load area stress data set; A stress mutation interval identification module is used to calculate the time series stress change amount, analyze the stress fluctuation period, deduce the cumulative change trend, calculate the local stress change amplitude, and generate local stress cumulative impact data according to the local stress concentration point distribution information; An abnormal stress correction module is used to calculate the stress offset of the abnormal point based on the local stress cumulative influence data, analyze the stress fluctuation trend, calculate the abnormal point deviation ratio, adjust the abnormal point stress value, and obtain the abnormal stress correction value; The fatigue damage assessment module is used to calculate the fatigue damage ratio of the local area based on the abnormal stress correction value, derive the fatigue damage accumulation, calculate the stress decay rate of the damaged area, and obtain the fatigue damage distribution information.

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