Method and system for detecting absolute stress of concrete bridge

Abstract

The invention relates to the technical field of stress detection, in particular to an absolute stress detection method and system for a concrete bridge, and the method comprises the following steps: obtaining stress data of a bridge girder, a support, a box girder and a main tower, collecting wind speed and wind direction sensor data, calculating a wind load gradient value, and extracting wind load primary and secondary influence regions and a transmission buffer region. And generating a wind load area stress data set. According to the method, through environmental factors and stress data, the influence of wind load on structure stress is identified, data comprehensiveness is ensured, through wind load gradient change rate calculation and stress sudden change area extraction, the structure weak point identification capability is improved, the stress fluctuation trend is quantified through time sequence analysis, and the cumulative change rate is deduced, so that fatigue damage prediction is more accurate; abnormal point identification is combined with deviation ratio analysis, measurement data is corrected, analysis reliability is improved, fatigue damage information is extracted based on stress attenuation features, local fatigue evaluation is optimized, a damaged area is accurately locked, and the accuracy of structural health monitoring is improved.

Description

Technical Field

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

[0002] The field of stress detection technology involves measuring, analyzing and evaluating the stress of materials, structures or components under stress. The core content of this technology field includes obtaining stress information by various measurement methods, such as resistance strain gauges, fiber gratings, acoustic emission, ultrasound, etc., and determining the stress distribution through signal acquisition, transmission and computational analysis. Stress detection is widely used in civil engineering, aerospace, machinery manufacturing and other industries to ensure structural safety and reliability. The development of this technology field involves sensor technology, data acquisition technology, optimization of stress calculation models and improvement of experimental verification methods, so that it can be applied to stress analysis of different working conditions and complex structures.

[0003] Among them, the absolute stress detection method of concrete bridges refers to the specific stress state of the concrete bridge structure, by measuring the stress changes in the key parts of the bridge, 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 positions of the bridge, collecting data using strain gauges, and calculating absolute stress based on the mechanical properties of concrete materials. In addition, temperature compensation technology is used to reduce the impact of ambient temperature on the measurement results, and the measured data is calculated through a data analysis model to obtain the exact value of the stress state of the bridge.

[0004] Traditional stress detection methods mainly rely on single-point or local measurements, which are difficult to fully reflect the overall stress state of the bridge structure under different wind loads, resulting in limitations in the identification of key stress areas. Due to the lack of detailed analysis of wind load gradient changes, it is difficult to accurately extract stress mutation areas, resulting in delayed identification of structural weak points, affecting the timeliness of safety assessments. Existing methods often lack time series data support when dealing with stress fluctuation trends, making it difficult to accurately characterize the cumulative effect of stress, resulting in deviations in fatigue damage assessments and affecting the accuracy of long-term health monitoring. In addition, the correction of abnormal stress data mainly relies on empirical judgments and lacks support for deviation ratio analysis, which can easily lead to inaccurate data correction and affect the reliability of measurement results. The identification method of fatigue damage is relatively extensive, lacks accurate extraction of local damaged areas, and is difficult to achieve effective monitoring of key stress-bearing parts, affecting the accuracy of structural health management. Summary of the invention

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

[0006] In order to achieve the above object, the present invention adopts the following technical solution: A method for detecting absolute stress of a concrete bridge comprises the following steps: S1: Obtain stress data of bridge main beams, supports, box beams and main towers, collect wind speed, wind direction and temperature sensor data, calculate wind load gradient values, extract primary and secondary wind load influence areas and transfer buffer zones, and generate wind load regional stress data sets; 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 stress change in the time series, study the stress fluctuation period, derive the cumulative change rate, compare the stress threshold range, screen the stress mutation interval, and generate the local stress cumulative impact data; S4: In combination with the local stress cumulative impact data, the stress data is traced back to calculate the stress fluctuation rate of the abnormal point, analyze the characteristics of the stress fluctuation trend curve, calculate and compare the deviation ratio of the abnormal point according to the normal stress interval, adjust the stress value of the abnormal point, and obtain the abnormal stress correction value.

[0007] As a further solution of the present invention, 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, wind load secondary influence area, and wind load 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.

[0008] As a further solution of the present invention, 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 values ​​of the sensors at different time nodes, align the wind speed and wind direction data 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 the different time 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.

[0009] As a further solution of the present invention, 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 change rate exceeds the set wind load change threshold is selected according to the amplitude of the change rate, and the stress sensor nodes in the area are extracted to obtain the wind load gradient change rate and stress sensor node data; S202: Calculate the stress change rate of the stress sensor node in combination with the wind load gradient change rate 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 stress change rate and time delay ratio data; S203: Based on the stress change rate and time delay ratio data, analyze the stress transfer path between sensor nodes, calculate the stress accumulation degree of the transfer path, and determine the stress concentration point according to the cumulative gradient change to obtain the local stress concentration point distribution information.

[0010] As a further solution of the present invention, 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 change at each moment is Representative The time interval of a moment, 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.

[0011] As a further solution of the present invention, 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 change rate in the time series is obtained, the change characteristics of the 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 rate; S303: According to the stress cumulative change rate, compare with a preset stress threshold range, screen the stress mutation interval, calculate the amplitude and duration of the stress change in the mutation interval, extract the abnormal fluctuation characteristics of the local stress, and generate local stress cumulative impact data.

[0012] As a further solution of the present invention, 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 change range of the normal stress interval is compared to calculate the correction value of the abnormal point, and the abnormal point stress value 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.

[0013] As a further solution of the present invention, the specific calculation formula for the change range compared with 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.

[0014] As a further embodiment of the present invention, 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 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.

[0015] Concrete bridge absolute stress detection system, including: 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the steps of the present invention; Figure 2 It is a system module diagram of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with 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 intended to limit the present invention.

[0018] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0019] See also Figure 1 , the absolute stress detection method of concrete bridge includes the following steps: 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 wind load regional stress data set, calculate the wind load gradient change rate, screen the wind pressure impact peak area, 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 impact area, analyze the force change trend, and obtain the local stress concentration point distribution information; S3: According to the distribution information of local stress concentration points, calculate the stress change amount of the time series of stress concentration points, study the stress fluctuation cycle, derive the cumulative change rate, compare the stress threshold range, screen the stress mutation interval, and generate local stress cumulative impact data; S4: Combine the local stress cumulative impact data, trace back the stress data, calculate the stress fluctuation rate of the abnormal point, analyze the characteristics of the stress fluctuation trend curve, calculate the deviation ratio of the abnormal point, compare the deviation ratio with the normal stress range, adjust the stress value of the abnormal point, and obtain the abnormal stress correction value; 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 excess area according to the fatigue damage threshold, extract the stress attenuation characteristics of the damaged area, and obtain the fatigue damage distribution information.

[0020] 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, wind load secondary influence area, and wind load 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. The fatigue damage distribution information includes local area fatigue damage ratio, stress change trend, fatigue damage accumulation, fatigue damage threshold, fatigue damage overlimit area, and stress attenuation characteristics.

[0021] 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 values ​​of the sensors at different time nodes, align the wind speed and wind direction data 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 the different time to obtain the stress increment data under the wind load; The bridge structure monitoring equipment first obtains stress data from structural parts such as the main beam, support, box beam and main tower, and collects wind speed, wind direction and temperature sensor data at the same time. The measuring equipment regularly collects various data through sensors installed in different parts of the bridge. For example, the stress at the main beam can be measured by strain gauges, and the bearing capacity change can be obtained by displacement sensors at the support. The temperature difference between the inside and outside of the box beam 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 timestamp and stored in the database for time alignment. Assume that at a certain time t1, the main beam stress σ1=35MPa, the wind speed v1=12m / s, the temperature T1=15°C, and at time t2 σ2= 38MPa, v2=14m / s, T2=16°C, then the instantaneous stress increment under wind load is Δσ=σ2-σ1=3MPa. Similarly, repeat this process at all monitoring points to obtain stress data at different time nodes and establish a data table. Then, statistically analyze the stress change trend of each measuring point according to the time series, analyze the stress change amplitude under different wind speeds, wind directions and temperature changes, and use linear regression or sliding mean method to fit the stress change curve. For example, if the stress increment trend fitted by multiple sets of data is Δσ=f(v,T), where f(v,T) represents the relationship function between stress increment and wind speed and temperature, then the stress increment data under wind load can be obtained by statistics.

[0022] 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, wind direction and temperature data to obtain the wind load gradient value distribution data; Based on the stress increment data under wind load, the wind load gradient value of the monitoring point needs to be calculated first. In the data processing stage, different wind speed intervals can be selected, such as low wind speed (0-5m / s), medium wind speed (5-15m / s), and high wind speed (above 15m / s). The stress response rate in these intervals is calculated, that is, the ratio of the stress increment Δσ to the wind speed change Δv. Assuming that the stress increment Δσ1 of a monitoring point in the low wind speed interval is 2MPa and the wind speed change Δv1 is 3m / s, the stress response rate R1=Δσ1 / Δv1=0 .67MPa / (m / s) In the high wind speed range, Δσ2=5MPa, Δv2=4m / s, then R2=Δσ2 / Δv2=1.25MPa / (m / s). Then calculate the stress ratio of wind load, that is, the proportion of stress increment of each monitoring point to the total stress change, summarize the wind load change trend of the structural parts, and calculate the wind load intensity of the overall structure based on wind speed, wind direction and temperature data. For example, in a certain wind speed range, find the average of the stress increments of different monitoring points to obtain the wind load gradient value distribution data of the overall structure.

[0023] 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; According to the distribution data of wind load gradient value, the wind load impact value of the monitoring point is calculated, that is, the stress increment contribution value of each monitoring point in a specific wind speed range, the stress change area of ​​the structural part is summarized, and the stress response rate is used to divide the main influence area, secondary influence area and transfer buffer zone of the wind load. For example, if the stress response rate of the main beam area is higher than 1MPa / (m / s), it is defined as the main influence area. If the stress response rate of the support area is between 0.5-1MPa / (m / s), it is the secondary influence area, and the area below 0.5MPa / (m / s) is defined as the transfer buffer zone. The contribution of wind load to structural stress in each area is calculated. For example, if the stress increment of a measuring point in the main influence area is Δσ3=4MPa, Δσ4=2MPa in the secondary influence area, and Δσ5=1MPa in the transfer buffer zone, the wind load impact data of each area is calculated respectively, and the wind load area stress data set is generated by summarizing.

[0024] 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 change rate exceeds the set wind load change threshold is selected according to the amplitude of the change rate, and the stress sensor nodes in the area are extracted to obtain the wind load gradient change rate and stress sensor node data; Based on the wind load regional stress data set, the wind load values ​​of each sensor node at different time points are first extracted, and the wind load change rate is calculated. The wind load increment is obtained by the time series difference method, and the data is smoothed to reduce noise interference. Then the wind load gradient change rate is calculated, that is, the change rate data is secondarily differentiated to screen the areas where the wind load change rate exceeds the set threshold. For example, in a high-rise building wind load monitoring system, the wind load time series data are recorded on sensors A, B, and C in turn. Suppose point A is at five consecutive time points. The wind load values ​​at each moment were 5.1, 5.8, 6.3, 7.1, and 7.9 (unit: kN / m²). After calculating the wind load change rate, we got 0.7, 0.5, 0.8, and 0.8. Then we performed gradient calculation on the change rate data, and found that the changes at some moments were more obvious. We set the wind load change threshold to 0.2kN / m², and compared the calculation results. We found that the change rate at some moments exceeded the threshold. Then we extracted the stress sensor data of the area corresponding to the time point, and finally obtained the wind load gradient change rate and related sensor node data.

[0025] S202: combining the wind load gradient change rate and the stress sensor node data, calculating the stress change rate of the stress sensor node, and performing a correlation analysis on the time series of the wind load gradient change rate and the stress change rate, determining the time delay ratio under the influence of the wind load, and obtaining the stress change rate and time delay ratio data; Combined with the wind load gradient change rate and stress sensor node data, the stress change over time is analyzed, the stress change rate is calculated, and the correlation analysis is performed with the wind load gradient change rate. The statistical method is used to calculate the correlation between the two, and a time delay analysis is performed to obtain the time delay ratio of the wind load change affecting the stress change. In actual engineering applications, it is assumed that the sensor monitoring data on a bridge structure records the wind load gradient change rate and stress change rate at multiple times, and the correlation between the two is calculated. It is found that there is a strong correlation between the two, and the lag time of the wind load on the stress change is further analyzed. For example, the peak of the wind load change rate of a sensor node occurs at 5 seconds, and the peak of the stress change rate occurs at 7 seconds. The time delay ratio is calculated to be 40%. The overall stress change rate and time delay ratio data are obtained through multi-point analysis.

[0026] S203: Based on the stress change rate and time delay ratio data, analyze the stress transmission path between the sensor nodes, calculate the stress accumulation degree of the transmission path, and determine the stress concentration point according to the cumulative gradient change to obtain 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 change at each moment is Representative The time interval of a moment, 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 transmission path; Calculate the weighted sum of the absolute values ​​of the stress change rates: Stress change (Δσ): The stress difference between adjacent time points measured by the sensor. Assuming that at time t1 and t2, the stress values ​​measured by the sensor are 50MPa and 55MPa respectively, then Δσ=55MPa-50MPa=5MPa.

[0027] Time interval (Δt): The time difference between adjacent stress measurements. Assuming t1=10s, t2=12s, then Δt=12s-10s=2s.

[0028] Stress change rate (Δσ / Δt): The ratio of stress change to time interval, indicating the rate of stress change. For the above values, Δσ / Δt=5MPa / 2s=2.5MPa / s.

[0029] Stress weight (w): reflects the importance of each node in the stress transfer path. The weight is set based on factors such as the position of the node in the structure and material properties. Assuming that a certain node is more important, set w=1.2.

[0030] 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=|2.5MPa / s|×1.2=3MPa / s.

[0031] Accumulate the weighted absolute values ​​of all nodes: Sum the weighted stress change rates of all n nodes to get the result of the first part.

[0032] Calculate the square root of the weighted sum of the squared stresses: Node stress value (σ): The stress value measured by the sensor at each node. Assume that the stress value of a node is 60MPa.

[0033] Stress weight factor (k): used to adjust the influence of stress value of each node, and is set according to factors such as elastic modulus and cross-sectional area of ​​the node material. Assume that k of this node is 0.8.

[0034] Calculate the weighted value of the square of the stress: square the stress value and multiply it by the corresponding weight factor. For the above values, k×σ 2 =0.8×(60MPa) 2 =0.8×3600(MPa) 2 =2880(MPa) 2 .

[0035] Accumulate the weighted square stress values ​​of all valid nodes: sum the weighted square stress values ​​of all m valid nodes.

[0036] Take the square root: Take the square root of the accumulated result to get the result of the second part.

[0037] The sum of the stress accumulation degree (S a cc): Add the above two results to get the stress accumulation degree S a cc.

[0038] Example calculation: Assume there are 3 nodes and their stress measurement data are as follows: Node 1: σ1=50MPa, Δσ1=5MPa, Δt1=2s, w1=1.0, k1=0.9; Node 2: σ2=55MPa, Δσ2=4MPa, Δt2=1.5s, w2=1.1, k2=0.85; Node 3: σ3=60MPa, Δσ3=6MPa, Δt3=2.5s, w3=1.2, k3=0.8; Calculation process: Calculate the weighted sum of the absolute values ​​of the stress change rates: Node 1: |Δσ1 / Δt1|×w1=|5MPa / 2s|×1.0=2.5MPa / s; Node 2: |Δσ2 / Δt2|×w2=|4MPa / 1.5s|×1.1≈2.933MPa / s; Node 3: |Δσ3 / Δt3|×w3=|6MPa / 2.5s|×1.2=2.88MPa / s; Cumulative result: 2.5+2.933+2.88≈8.313MPa / s; Calculate the square root of the weighted sum of the squared stresses: Node 1: k1×σ1 2=0.9×(50MPa) 2 =0.9×2500=2250(MPa) 2 Node 2: k2×σ2 2 =0.85×(55MPa) 2 =0.85×3025≈2571.25(MPa) 2 Node 3: k3×σ3 2 =0.8×(60MPa) 2 =0.8×3600=2880(MPa) 2 Cumulative result: 2250+2571.25+2880≈7701.25 (MPa) 2 Take the square root: ≈87.75MPa; Calculate the stress accumulation degree (S a cc): S a cc=8.313MPa / s+87.75MPa≈96.063MPa Result description: The calculated stress accumulation degree S a cc is 96.063MPa. This result shows that considering the weighted influence of stress change rate and node stress value, the stress accumulation degree of the transfer path is 96.063MPa. This value can be used to assess the risk level of stress concentration areas in the structure.

[0039] The specific steps of S3 are: S301: Obtaining distribution information of local stress concentration points, extracting stress data at time points, and calculating stress changes between adjacent time points, constructing time series data based on stress changes, extracting periodic fluctuation characteristics in the time series, comparing stress change trends in the change intervals in the time series, and generating stress change trend analysis results; First, based on finite element analysis software, such as Abaqus or ANSYS, the force analysis of the target structure is carried out, a three-dimensional grid model is established, and the corresponding boundary conditions and loads are applied. The stress distribution data at each grid node is calculated, and the areas with higher stress are screened out through stress cloud maps or data extraction methods. The local stress concentration points are analyzed according to the stress gradient change. Then, the stress data of multiple time points are extracted, and the stress values ​​of every two adjacent time points are subtracted to obtain the stress change amount. The time series data is constructed, and the time series analysis methods, such as wavelet transform or Fourier transform, are used to extract the periodic fluctuation characteristics. By comparing the stress change trends of different time windows in the time series, the stress increase and decrease in each time period are analyzed. For example, at a certain moment, the stress value increases by 10MPa compared with the previous moment, and then decreases by 5MPa. The stress trend of this interval is first increased and then decreased. The trend information obtained by the analysis is summarized and sorted to form the stress change trend analysis results.

[0040] S302: Based on the stress change trend analysis result, the cumulative change of stress in the difference time period is calculated, and the change rate in the time series is obtained, the change characteristics of the 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 rate; Based on the results of stress change trend analysis, the cumulative stress change in the difference period is calculated. First, the time interval is selected, and the sum of all stress change values ​​in the interval is counted to quantify the cumulative stress change. At the same time, the average change rate in the interval is calculated. The method is to take the total stress change in the interval and divide it by the time span to obtain the average stress change rate per unit time. The index is calculated in different time intervals to determine the difference in stress change trends. For example, the cumulative stress change in the first 5 seconds is 50 MPa, and in the next 5 seconds it is 20 MPa. The stress change rate in the previous period is higher. The cumulative change rates in different time periods are further compared to observe whether there is an obvious change pattern. The change rate data is classified and processed by methods such as data clustering or principal component analysis to more clearly show the law of stress change and finally obtain the stress cumulative change rate.

[0041] S303: According to the stress cumulative change rate, the preset stress threshold range is compared, the stress mutation interval is screened, the amplitude and duration of the stress change in the mutation interval are calculated, the abnormal fluctuation characteristics of the local stress are extracted, and the local stress cumulative impact data is generated; According to the cumulative change rate of stress, the preset stress threshold range is compared to screen the stress mutation interval. First, the threshold range of stress mutation is set. For example, if the stress change rate in a certain time period exceeds the set threshold, it is marked as a mutation interval. The stress change amplitude in the mutation interval is further analyzed, that is, the difference between the maximum stress value and the minimum stress value in the interval is calculated, and the duration of the mutation interval is recorded. For example, in a certain interval, the stress drops from 100MPa to 60MPa instantly and lasts for 2 seconds. This area belongs to the stress mutation area. Subsequently, the abnormal fluctuation characteristics of local stress are extracted, and the impact of these abnormal points on the overall structure is analyzed. For example, data classification methods are used to distinguish between mutation areas and normal areas, and the distribution of mutation stress points is summarized to finally generate local stress accumulation impact data.

[0042] 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; First, it is necessary to collect stress data of the material at different time points and record its historical changes. Use stress sensors to measure stress at predetermined locations and store the data in the monitoring system. After the data is recorded, it is necessary to calculate the stress changes between adjacent time points. Usually, the difference calculation is used, that is, by comparing the stress values ​​at two points in time, the change amount is obtained. If the interval is short, it can more accurately reflect the fluctuation of stress over time. On this basis, it is necessary to select a time range, such as one minute, ten minutes or one hour, and find the maximum and minimum stress values ​​within the time range, and then calculate the difference between them to obtain the stress fluctuation amplitude within the time period. This can effectively evaluate the overall fluctuation of stress over time. Next, it is necessary to To screen out abnormal stress points, statistical methods are usually used, such as calculating the mean and standard deviation of all collected stress data, and setting a reasonable abnormal judgment range, such as the mean plus or minus three times the standard deviation. 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 situations where stress changes are more drastic. In practical applications, such as during the structural health monitoring of bridges, stress sensors can be arranged at locations such as bridge decks and piers. Data can be collected and the stress fluctuation rate of abnormal points can be calculated according to the above method, so as to further analyze and adjust the stress value of the abnormal point.

[0043] 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; According to the stress fluctuation rate of the abnormal point, it is necessary to further analyze the overall change trend of stress over time. First, the historical stress data can be used to draw a stress change curve and calculate the slope of the curve. The slope reflects the change rate of stress. The overall stress trend can be obtained by calculating the average slope between multiple time points. On this basis, it is necessary to find the inflection point, that is, the position where the stress change trend changes significantly. The stress change rates of adjacent time periods can be compared to determine which time points have obvious inflection points. For example, if the stress change rate at a certain time point changes suddenly compared with the previous and next time periods, then this point can be considered as an inflection point. After identifying the inflection point, it is necessary to calculate the degree of deviation between the fluctuation rate of the abnormal point and the overall trend. It is usually achieved by comparing the rate of the abnormal point with the rate of the normal trend and calculating the deviation ratio between the two. This ratio can reflect whether the fluctuation of the abnormal point is far away from the overall stress change trend. For example, during the operation of mechanical equipment, if the stress change rate of a component is found to be much higher than the overall trend, it means that the component may have abnormal wear or overload. After calculation, the deviation ratio value of the abnormal point can be obtained, and it can be further determined which abnormal points need to be adjusted.

[0044] S403: Based on the deviation ratio value of the abnormal point, the change range of the normal stress interval is compared, and 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; The specific calculation formula for the change range compared to the normal stress range 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, Parameter acquisition method: Stress value ( and ): By arranging strain gauges and other sensors on the surface of the structure, the strain value of each measuring point is measured, and then the elastic modulus of the material ( ) and Poisson's ratio ( ), and the stress value is calculated according to Hooke's law.

[0045] Number of measuring points( and ): Determined by the number of sensors actually arranged. Among them, the number of measuring points within the normal stress range It needs to be determined based on the measurement results and the preset normal stress range.

[0046] Specific calculation example: Assume that 10 measuring points are arranged on a structure (i.e. ), through measurement and calculation, the stress values ​​of each measuring point are as follows (unit: MPa): ; Step 1: Calculation ; First, calculate the sum of the absolute values ​​of stress at all measuring points: ; Then, calculate the average: ; Step 2: Determine the normal stress range and calculate ; Assuming that the normal stress range is 12MPa to 15MPa, the stress values ​​of the measuring points that meet this range are: ; The number of measurement points corresponding to these values ​​is .

[0047] Calculate the sum of the squares of the stress values ​​at these measurement points: ; Then, calculate the mean and take the square root: ; Step 3: Calculate the stress variation

[0048] Substituting the above results into the formula: ; Result analysis: Calculated stress variation MPa. The result shows that the product of the average absolute value of the stress value at the measuring point and the average square value of the stress value in the normal stress range is 186.54MPa. This value can be used to evaluate the stress distribution of the structure, and then provide a reference for the subsequent abnormal point correction and stress adjustment.

[0049] 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 ratio data is compared with the set fatigue damage threshold to obtain the fatigue damage limit area data; Based on the abnormal stress correction value, the stress data of the local area needs to be classified first to ensure that the stress levels of different areas can reasonably reflect their actual stress conditions. Specifically, statistical analysis can be performed based on the stress history data of different areas, such as classification according to the range of maximum stress, minimum stress and average stress for subsequent processing. Then, based on engineering experience or experimental data, the abnormal stress value is corrected to reduce the impact of data deviation on the calculation. For example, if the stress value of a certain area is abnormally high or low, the stress data of the adjacent area can be referred to for reasonable correction; after the correction is completed, a benchmark value needs to be set to evaluate the stress situation of each area. The setting of the benchmark value can refer to the yield strength, fatigue limit or historical monitoring data of the material. For example, for a certain metal material, its fatigue limit may be around 250MPa, so 250MPa can be set as the stress benchmark value of the material. Subsequently, the stress data of all local areas are compared, the areas exceeding the benchmark value are screened out, and their fatigue damage ratios are further calculated. The calculation of fatigue damage is usually based on the cumulative damage theory, that is, considering the relationship between the number of cycles and fatigue life of a certain area at different stress levels. For example, if a region is subjected to 5,000 cycles at a stress level of 100 MPa, and the fatigue life at this stress level is 20,000 times, the fatigue damage ratio of the region is 0.25. After calculating the damage ratios of all regions using a similar method, they are classified and compared with the set fatigue damage threshold to determine which regions have fatigue damage that exceeds the safety range. For example, if the fatigue damage threshold is set to 0.3, all regions with a damage ratio greater than 0.3 are judged as fatigue damage excess regions, and finally the data of fatigue damage excess regions are obtained.

[0050] S502: Calculate the stress change amplitude at the difference time point based on the fatigue damage over-limit area data, judge the stress decay trend of the local area, calculate the cumulative fatigue damage value, and perform partitioning and grouping to extract the stress decay characteristics of the area to obtain the local stress decay trend; After obtaining the fatigue damage over-limit area data, it is necessary to further analyze the stress changes 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 by the difference between the maximum stress and the minimum stress. For example, in a certain area, the maximum stress value in a certain period of time is 120MPa, and the minimum stress value is 90MPa, then the stress change amplitude is 30MPa. By comparing the stress data at multiple time points, the stress change in the area can be observed; after obtaining the stress change data at different time points, it is necessary to further determine the stress attenuation trend of the local area. The analysis of the stress attenuation trend can be carried out by data fitting methods, such as observing whether the change of long-term stress data shows a downward trend. If the stress level of a certain area continues to decline in the past month, for example, from 120MPa to 100MPa, and the downward trend is stable, it can be determined that there is stress attenuation in the 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 decay rate in one area is 2MPa / day, and the decay rate in another area is 1.8MPa / day, they can be classified into the same category for subsequent processing. Finally, through data collection and trend extraction, the stress decay trend information of the local area is obtained.

[0051] S503: Based on the local stress attenuation trend, the fatigue damage accumulation of the region is calculated, and the fatigue damage over-limit 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; Based on the trend of local stress attenuation, it is necessary to further calculate the cumulative amount of fatigue damage in each area. The calculation of the cumulative amount of fatigue damage is still based on the cumulative damage theory, and combined with the data of the fatigue damage over-limit area, the overall fatigue damage distribution is estimated. During the calculation process, the fatigue damage ratios of all areas need to be aggregated and the weight factors of each area need to be considered. For example, when the fatigue damage ratios of multiple areas are different, it is necessary to perform weighted processing according to the area, stress level or use 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 sort it out in combination with the regional stress change trend. The stress change trend of the region 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 1MPa / day as a low change area, the area with a stress change rate of 1-5MPa / day as a medium change area, and the area with a stress change rate higher than 5MPa / day as a 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, the fatigue damage distribution information is sorted and output for subsequent analysis and processing.

[0052] See also Figure 2 , Concrete bridge absolute stress detection system, including: The wind load stress monitoring module obtains the stress data of the bridge main beam, support, box beam and main tower, collects wind speed and wind direction sensor data, calculates the wind load gradient value, identifies the wind load action area, extracts the stress change data of the area, calculates the wind load stress distribution, and obtains the wind load area stress data set; 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 distribution information of local stress concentration points; The stress mutation interval identification module calculates the time series stress change, analyzes the stress fluctuation cycle, derives the cumulative change trend, calculates the local stress change amplitude, and generates the local stress cumulative impact data based on the distribution information of the local stress concentration points; The abnormal stress correction module calculates the stress offset of the abnormal point based on the local stress cumulative impact data, analyzes the stress fluctuation trend, calculates the deviation ratio of the abnormal point, adjusts the stress value of the abnormal point, and obtains the abnormal stress correction value; The fatigue damage assessment module calculates the fatigue damage ratio of the local area based on the abnormal stress correction value, derives the fatigue damage accumulation, calculates the stress decay rate of the damaged area, and obtains the fatigue damage distribution information. The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls 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 primary and secondary wind load influence areas and transfer buffer zones, and generate wind load regional stress data sets; 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 stress change in the time series, study the stress fluctuation period, derive the cumulative change rate, compare the stress threshold range, screen the stress mutation interval, and generate the local stress cumulative impact data; S4: In combination with the local stress cumulative impact data, the stress data is traced back to calculate the stress fluctuation rate of the abnormal point, analyze the characteristics of the stress fluctuation trend curve, calculate and compare the deviation ratio of the abnormal point according to the normal stress interval, adjust the stress value of the abnormal point, and obtain the abnormal stress correction value.

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, wind load secondary influence area, and wind load 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 1, characterized in that: 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 change rate exceeds the set wind load change threshold is selected according to the amplitude of the change rate, and the stress sensor nodes in the area are extracted to obtain the wind load gradient change rate and stress sensor node data; S202: Calculate the stress change rate of the stress sensor node in combination with the wind load gradient change rate 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 stress change rate and time delay ratio data; S203: Based on the stress change rate and time delay ratio data, analyze the stress transfer path between sensor nodes, calculate the stress accumulation degree of the transfer path, and determine the stress concentration point according to the cumulative gradient change to obtain the local stress concentration point distribution information.

5. The method for detecting absolute stress of a concrete bridge according to claim 4, characterized in that: 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 change at each moment is Representative The time interval of a moment, 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.

6. The method for detecting absolute stress of a concrete bridge according to claim 1, 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 change rate in the time series is obtained, the change characteristics of the 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 rate; S303: According to the stress cumulative change rate, compare with a preset stress threshold range, screen the stress mutation interval, calculate the amplitude and duration of the stress change in the mutation interval, extract the abnormal fluctuation characteristics of the local stress, and generate local stress cumulative impact data.

7. The method for detecting absolute stress of a concrete bridge according to claim 1, 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 change range of the normal stress interval is compared to calculate the correction value of the abnormal point, and the abnormal point stress value 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.

8. The method for detecting absolute stress of a concrete bridge according to claim 7, 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.

9. The method for detecting absolute stress of a concrete bridge according to claim 1, 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 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.

10. 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 9, 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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