A method for condition monitoring of a bridge structure

Abstract

The application discloses a kind of state monitoring methods for bridge structure, belong to bridge measurement monitoring technical field, comprising: obtaining the original data set of bridge main tower inclination angle and cable tension, analysis signal time characteristic factor, linear interpolation adjustment information determination is carried out;Based on original data set, analysis cable tension update value then analysis cable tension residual error and interpolation adjustment effect label, signal reconstruction effect determination is carried out.The application can continuously monitor bridge structure, whether linear interpolation adjustment information determination is carried out by analyzing signal time characteristic factor to avoid waste of computing power by adjusting, by linear interpolation adjustment analysis cable tension update value, cable tension is aligned with main tower inclination time stamp, analysis cable tension update value eliminates cross-sensor clock asynchronous error, by analyzing frequency coherence factor, signal is classified and processed, classification processing avoids mutual interference of different frequency components in wideband signal, significantly improves the precision of structural health monitoring.

Description

Technical Field

[0001] This invention relates to the field of measurement and monitoring technology, and in particular to a method for monitoring the condition of bridge structures. Background Technology

[0002] During their service life, bridges are subjected to various adverse effects from the environment, vehicles, and other factors. Over long-term operation, the materials themselves will inevitably degrade, leading to varying degrees of damage and deterioration in different parts of the structure. In recent years, bridge structural condition monitoring methods based on sensor technology, signal processing, and intelligent algorithms have developed rapidly. Sensors such as fiber optic sensors, strain gauges, and accelerometers enable real-time acquisition of structural responses; vibration analysis and modal recognition technologies can assess the dynamic characteristics of the structure; and machine learning and deep learning algorithms can mine data features and predict structural damage trends.

[0003] For example, the invention patent announcement CN118758377B discloses a bridge structural health monitoring and early warning system, which includes: by deploying a variety of high-precision sensors and advanced monitoring equipment, it can comprehensively cover all key structures of the bridge, thereby ensuring real-time, accurate and comprehensive understanding of the bridge's health status. This not only improves the accuracy and reliability of the data, but also lays a solid foundation for subsequent early warning and maintenance work. It fully considers the uniqueness and differences of each bridge, and sets personalized safety thresholds and early warning levels based on the actual situation and historical data of the bridge, which can more accurately reflect the unique health status of each bridge in the city, thereby improving the pertinence and effectiveness of the early warning.

[0004] For example, the invention patent announcement CN107687872B, which discloses a method and system for monitoring the health status of bridge structures based on dynamic model updates, includes: acquiring sensor data of the main body of the bridge structure obtained based on a distributed computing method; performing modal identification based on the acquired sensor data to obtain corresponding modal parameters; the modal parameters include the intrinsic frequencies and the mode shapes of the corresponding orders; updating the benchmark model equations of the bridge structure constructed based on Bayesian principles according to the obtained modal parameters to obtain the error value of the updated model equations; and analyzing and judging the error value to obtain the health monitoring status of the bridge structure.

[0005] However, in the process of implementing the inventive technical solution in the embodiments of this application, it was found that the above-mentioned technology has at least the following technical problems:

[0006] Due to differences in hardware clocks or data transmission delays, various sensors may experience timestamp discrepancies in their acquired data. This issue can cause time alignment failures across sensor data, leading to errors in timing correlation analysis under critical operating conditions. In severe cases, it may even mask subtle early structural damage signals. Furthermore, in traditional signal processing workflows, the lack of a specific mechanism for preserving the energy of high-frequency signal bands makes it easy to lose effective high-frequency information containing structural dynamic characteristics during filtering, interpolation, and other processing. This loss of information can reduce the monitoring system's ability to identify early faults such as abnormal structural vibrations and localized fatigue damage. Summary of the Invention

[0007] This invention provides a method for monitoring the condition of bridge structures, comprising the following steps: continuously monitoring the bridge structure, obtaining the original datasets of the bridge main tower tilt angle and the bridge cable tension, analyzing the signal time characteristic characterization factors, and thereby determining the linear interpolation adjustment information.

[0008] When the linear interpolation adjustment information determination result is the required linear interpolation adjustment, the updated cable tension value is analyzed based on the original dataset of the bridge main tower tilt angle and the bridge cable tension.

[0009] Analyze the cable tension residual and the interpolation adjustment effect label to determine the execution requirements of quadratic linear interpolation adjustment.

[0010] The system receives the signal after linear interpolation adjustment is completed, analyzes the energy fidelity of the frequency band, determines the validity of the high-frequency signal data, analyzes the signal reconstruction requirement information, and determines the signal reconstruction effect after receiving the signal reconstruction completion information.

[0011] Furthermore, the signal time characteristic characterization factors are analyzed, and the specific analysis methods are as follows:

[0012] The timestamp columns for the inclination angle of the main tower and the tension of the bridge cables are obtained from the original dataset of the inclination angle of the main tower and the tension of the bridge cables, and the time characterization parameters of the data signals are obtained from the analysis.

[0013] The time characterization parameters of data signals include the sampling rate difference, the cross-correlation coefficient of the signal, and the difference in the rate of change of the signal amplitude.

[0014] Analyze the time characteristic characterization factors based on the time characterization parameters of the data signal.

[0015] The signal time characteristic characterization factor is a quantitative indicator of the difference in signal time characteristics, which is jointly expressed by the cross-correlation coefficient of the signal, the difference in the rate of change of the signal amplitude, and the difference in the sampling rate. The specific analysis process is as follows: The collected cross-correlation coefficient of the signal, the difference in the rate of change of the signal amplitude, and the difference in the sampling rate are compared with the corresponding reference values. The results of each comparison are coupled with the corresponding measurement factors to obtain the signal time characteristic characterization factor.

[0016] Furthermore, the linear interpolation adjustment information is determined, and the specific analysis process is as follows:

[0017] Extract the preset threshold values ​​of signal time feature representation factors from the database.

[0018] If the signal time feature characterization factor is less than the signal time feature characterization factor threshold, then the linear interpolation adjustment information determination result is recorded as demand linear interpolation adjustment.

[0019] If the signal time feature characterization factor is greater than or equal to the signal time feature characterization factor threshold, then the linear interpolation adjustment information determination result is recorded as no linear interpolation adjustment is required.

[0020] Furthermore, the updated cable tension values ​​were analyzed, and the specific analysis process is as follows:

[0021] The timestamp column of the bridge's main tower tilt angle is divided into pre-defined clusters in the database. The time cluster corresponding to the maximum tilt angle is obtained and recorded as the target time cluster.

[0022] Within the target time cluster, the peak value of the target time cluster is recorded as the main tower tilt angle timestamp reference point.

[0023] Extract the two tension data timestamps adjacent to the main tower tilt angle reference point from the timestamp sequence of bridge cable tension, and record them as the preceding point and the following point, respectively, thereby obtaining the radius of the time interval.

[0024] The length of the time interval is obtained based on the radius of the time interval.

[0025] Extract the cable tension values ​​corresponding to the preceding and following points.

[0026] The timestamp deviation factor is obtained by subtracting the main tower tilt angle timestamp reference point from the adjacent point.

[0027] The time scale coefficient is obtained based on the timestamp deviation factor and the time interval length analysis.

[0028] The total value of the cable tension data is obtained by analyzing the preceding and following points of the cable tension data.

[0029] The updated cable tension value is obtained by combining the total cable tension data with the time scaling factor.

[0030] Furthermore, the interpolation adjustment effect labels are analyzed to determine the execution requirement of quadratic linear interpolation adjustment. The specific analysis process is as follows:

[0031] Extract the two adjacent timestamp values ​​of the cable tension update value from the original dataset, and then extract the corresponding timestamps within the time interval, which are denoted as the first preceding point and the first following point, respectively.

[0032] Subtract the updated cable tension value from the first preceding point value and the first following point value respectively to obtain the cable tension update difference between the first preceding point value and the cable tension update difference between the first following point value.

[0033] If the absolute value of the difference between the numerical cable tension update values ​​at the first preceding point is less than or equal to the absolute value of the difference between the numerical cable tension update values ​​at the first following point, then the first preceding point is recorded as the timestamp corresponding to the cable tension update value.

[0034] If the absolute value of the difference between the numerical cable tension update values ​​at the first preceding point is greater than the absolute value of the difference between the numerical cable tension update values ​​at the first following point, then the first following point is recorded as the timestamp corresponding to the cable tension update value.

[0035] The cable tension timestamp residual is obtained by subtracting the timestamp reference point of the main tower tilt angle from the timestamp point corresponding to the updated cable tension value.

[0036] Extract the cable tension timestamp residual range stored in the database.

[0037] If the cable tension timestamp residual is less than the lower limit of the cable tension timestamp residual interval, the interpolation adjustment effect is recorded as successful adjustment, and the requirement for secondary linear interpolation adjustment is recorded as no secondary linear interpolation adjustment is needed. Simultaneously, a linear interpolation adjustment completion signal is generated.

[0038] If the cable tension timestamp residual is within the cable tension timestamp residual range, the interpolation adjustment effect is recorded as effective adjustment, and the quadratic linear interpolation adjustment execution requirement is recorded as demand quadratic linear interpolation adjustment.

[0039] If the cable tension timestamp residual is greater than the upper limit of the cable tension timestamp residual interval, the interpolation adjustment effect will be recorded as an adjustment anomaly, and the requirement for quadratic linear interpolation adjustment will be recorded as no quadratic linear interpolation adjustment is needed, and a warning message will be generated simultaneously.

[0040] Further, the quadratic linear interpolation adjustment is analyzed in detail as follows:

[0041] The difference between the timestamp corresponding to the updated cable tension value and the timestamp reference point of the main tower tilt angle is processed and recorded as the time ratio correction deviation coefficient.

[0042] The direction of quadratic linear interpolation adjustment is analyzed based on the time ratio correction deviation coefficient.

[0043] If the adjustment direction is forward, the timestamp corresponding to the updated cable tension value will be subtracted from the cable tension timestamp residual and then linearly interpolated again.

[0044] If the adjustment direction is backward, the timestamp corresponding to the updated cable tension value will be added to the cable tension timestamp residual and then linearly interpolated again.

[0045] After adjustment, the cable tension timestamp residual is reacquired. If the reacquired cable tension timestamp residual is greater than or equal to the lower limit of the cable tension timestamp residual interval, an early warning message is generated.

[0046] If the reacquired cable tension timestamp residual is less than the lower limit of the cable tension timestamp residual, a linear interpolation adjustment completion signal is generated.

[0047] Furthermore, the energy fidelity of the frequency band is analyzed, and the specific analysis process is as follows:

[0048] After receiving the signal after linear interpolation adjustment, acquire signal quality data for key frequency bands, including frequency band energy concentration, signal-to-noise ratio, and bandwidth ratio.

[0049] Frequency band energy fidelity is analyzed based on key frequency band signal quality data.

[0050] Frequency band energy fidelity is a quantitative indicator of the proportion of energy in key frequency bands in a signal, which is jointly quantified by frequency band energy concentration, signal-to-noise ratio, and bandwidth ratio. The specific analysis process is as follows: The collected frequency band energy concentration, signal-to-noise ratio, and bandwidth ratio are compared with the corresponding reference values. The comparison results are then coupled with the corresponding metric factors to obtain the frequency band energy fidelity.

[0051] Furthermore, the validity of high-frequency signal data is determined, and the signal reconstruction requirement information is analyzed accordingly. The specific analysis process is as follows:

[0052] Extract the frequency band energy fidelity threshold stored in the database.

[0053] If the frequency band energy fidelity is greater than or equal to the frequency band energy fidelity threshold, then the high-frequency signal data is recorded as valid data, and the signal reconstruction requirement information is recorded as no signal reconstruction adjustment is required.

[0054] If the frequency band energy fidelity is less than the frequency band energy fidelity threshold, the high-frequency signal data will be recorded as invalid data, and the signal reconstruction requirement information will be recorded as the requirement signal reconstruction adjustment.

[0055] Furthermore, the demand signal is restructured and adjusted, and the specific adjustment process is as follows:

[0056] After completing the linear interpolation adjustment, within the preset time window, the tilt angle of the main tower and the tension signal of the bridge cables are continuously collected, and the average frequency coherence factor is analyzed.

[0057] Extract the frequency coherence factor threshold stored in the database.

[0058] If the frequency coherence factor is greater than or equal to the frequency coherence factor threshold, the spectrum is divided into multiple sub-bands to generate a composite signal containing all key frequency bands.

[0059] If the frequency coherence factor is less than the frequency coherence factor threshold, the frequency coherence factor is subtracted from the frequency coherence factor threshold to obtain the frequency coherence deviation score.

[0060] Extract the frequency coherence first adjustment value corresponding to each frequency coherence deviation score interval stored in the database, and map the extracted frequency coherence first adjustment value corresponding to the interval in which the frequency coherence deviation score is located, denoted as the frequency coherence first adjustment value of the bridge structure.

[0061] The first frequency coherence adjustment value of the bridge structure is the bandwidth adjustment value.

[0062] Extract the first coherent adjustment value of the current frequency.

[0063] Demand signal reconstruction adjustment is performed based on the current frequency coherence first adjustment value and the frequency coherence first adjustment value of the bridge structure.

[0064] Further, the signal reconstruction effect is evaluated, and the specific analysis steps are as follows:

[0065] The energy fidelity of the reconstructed frequency band is denoted as the energy fidelity of the first frequency band.

[0066] The frequency band energy fidelity correction factor is extracted based on the energy fidelity of the first frequency band.

[0067] The energy fidelity correction index for the first frequency band is obtained based on the energy fidelity of the first frequency band and the energy fidelity correction factor of the frequency band.

[0068] If the energy fidelity correction index of the first frequency band is greater than or equal to the energy fidelity threshold of the frequency band, the signal reconstruction effect is recorded as a valid reconstruction.

[0069] If the energy fidelity correction index of the first frequency band is less than the energy fidelity threshold of the frequency band, the signal reconstruction effect will be recorded as invalid reconstruction, and an early warning message will be generated.

[0070] One or more technical solutions provided in this invention have at least the following technical effects or advantages:

[0071] 1. This invention provides a method for monitoring the condition of bridge structures, which enables continuous monitoring of bridge structures. It determines whether adjustment is needed by analyzing signal time characteristic factors and performing linear interpolation adjustment information, avoiding wasted computing power. Linear interpolation adjustment aligns cable tension with the main tower tilt timestamp. Analysis of cable tension update values ​​eliminates cross-sensor clock asynchronous errors. Analysis of cable tension residuals verifies the effectiveness of linear interpolation adjustment and performs secondary adjustments to dynamically correct errors and improve data accuracy. Analysis of frequency band energy fidelity determines signal reconstruction requirements and whether the signal is valid, avoiding resource waste. Analysis of frequency coherence factors classifies the signal, preventing interference between different frequency components in broadband signals and significantly improving the accuracy of structural health monitoring.

[0072] 2. This invention verifies the linear interpolation adjustment effect and performs secondary adjustments by analyzing the cable tension residuals. It can dynamically quantify the accuracy deviation of the interpolation adjustment, thereby improving the time synchronization accuracy of cross-sensor data. Specifically, the adjustment status can be accurately identified through a residual interval determination mechanism: when the residual is less than a threshold, the adjustment is confirmed as successful and a completion signal is generated; when the residual is within the interval, a secondary correction is initiated to further reduce the timestamp deviation; when the residual exceeds the limit, an anomaly is immediately warned. This preserves the temporal characteristics of abnormal structural vibrations, avoids distortion of early damage signals caused by clock asynchrony, and provides more reliable and accurate time-series correlation data for bridge condition monitoring.

[0073] 3. This invention uses frequency band energy fidelity to screen for frequency bands with sufficient energy in key frequency bands during signal reconstruction, ensuring that the identified signal is the true dynamic response of the structure rather than noise or interference, thus guaranteeing data validity from the source. By using frequency coherence factor to divide the input and output signals into two categories for targeted processing, the effectiveness and accuracy of the signals are improved. This ensures that the energy retention of key frequency bands in high-correlation frequency bands is maximized, while low-coherence frequency bands are optimized to avoid noise accumulation and interference. Attached Figure Description

[0074] Figure 1 This is a flowchart of a method for monitoring the condition of a bridge structure, provided in an embodiment of this application.

[0075] Figure 2 This application provides a diagram showing the layout of measuring points for the tilt angle of the main beam in a method for monitoring the condition of a bridge structure.

[0076] Figure 3 This application provides a software system display interface for a method of monitoring the condition of bridge structures.

[0077] Figure 4 A flowchart of a method for monitoring the condition of a bridge structure provided in this application embodiment.

[0078] Figure 5 A flowchart of the quadratic linear adjustment provided in the embodiments of this application. Detailed Implementation

[0079] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0080] like Figure 4 As shown in the flowchart of the method for monitoring the condition of a bridge structure provided in this application embodiment, the method includes first determining the linear interpolation adjustment information; if linear interpolation adjustment is required, analyzing the updated cable tension value; then analyzing the cable tension residual; analyzing the interpolation adjustment effect label; thereby determining the need for secondary linear interpolation adjustment; then determining the validity of high-frequency signal data; and analyzing the signal reconstruction requirement information to determine the signal reconstruction effect.

[0081] Reference Figure 1 As shown, the present invention provides a method for monitoring the condition of bridge structures, including the following steps: continuously monitoring the bridge structure, obtaining the original datasets of the bridge main tower tilt angle and the bridge cable tension, analyzing the signal time characteristic characterization factor, and thereby determining the linear interpolation adjustment information.

[0082] Furthermore, the signal time characteristic characterization factors are analyzed, and the specific analysis methods are as follows:

[0083] The timestamp columns for the inclination angle of the main tower and the tension of the bridge cables are obtained from the original dataset of the inclination angle of the main tower and the tension of the bridge cables, and the time characterization parameters of the data signals are obtained from the analysis.

[0084] The time characterization parameters of data signals include the sampling rate difference, the cross-correlation coefficient of the signal, and the difference in the rate of change of the signal amplitude.

[0085] It should be noted that the sampling rate difference is the difference in time axis resolution between the tilt angle and the cable tension. The sampling rate difference is obtained by collecting the frequency parameters of the tilt angle and the cable tension and performing difference processing. The signal amplitude change rate difference is the difference in the dynamic response speed of two signals, and the signal cross-correlation coefficient is the time correlation between two signals.

[0086] It should be noted that the sampling rate difference is obtained by subtracting the sampling rates obtained by taking the reciprocal of the timestamp intervals of the two signals. The signal cross-correlation coefficient is used to evaluate the correlation between the two signals (tilt angle and cable tension) through the Pearson coefficient. The specific process is as follows: first, read the timestamps, the main tower tilt angle, and the main beam cable tension; then calculate the time interval and sampling rate; finally, calculate the Pearson correlation coefficient. In a specific embodiment, the calculation formula can be: Where P represents the cross-correlation coefficient of the signals, n represents the number of signals, and i represents the signal number, i=1,2,3,...,n,x i Let y represent the tilt angle of the i-th main tower, a represent the average tilt angle of the main tower, and y represent the average tilt angle of the main tower. i Let represent the tension of the i-th cable, and b represent the average tension of the cables.

[0087] The difference in the rate of change of signal amplitude can be obtained by calculating the amplitude difference between adjacent sampling points of the signal.

[0088] It should be noted that when the sampling rate difference is large, the sampling point positions of the two signals in the time domain are significantly different, which will lead to a decrease in the cross-correlation coefficient of the two signals. A large sampling rate difference will also make it impossible to accurately capture rapid changes in amplitude, thus increasing the difference between the two when calculating the difference in amplitude change rate.

[0089] Analyze the time characteristic characterization factors based on the time characterization parameters of the data signal.

[0090] Extract the preset sampling rate difference measurement factor, signal cross-correlation coefficient measurement factor, and signal amplitude change rate difference measurement factor from the database.

[0091] Extract the preset reference values ​​for sampling rate difference, signal cross-correlation coefficient, and signal amplitude change rate difference from the database.

[0092] It should be added that the values ​​of the sampling rate difference metric, the signal cross-correlation coefficient metric, and the signal amplitude change rate difference metric all range from 0 to 1, and the sum of these three metrics is 1. When using these metrics, pre-defined values ​​can be directly extracted from the database. For example, the sampling rate difference, signal cross-correlation coefficient, and signal amplitude change rate difference are mapped one-to-one with their corresponding sampling rate difference metric, signal cross-correlation coefficient metric, and signal amplitude change rate difference metric. When using these metrics, the real-time acquired sampling rate difference, signal cross-correlation coefficient, and signal amplitude change rate difference are input into their respective mapping sets to extract the sampling rate difference metric, signal cross-correlation coefficient metric, and signal amplitude change rate difference metric.

[0093] Extract the preset reference values ​​for sampling rate difference, signal cross-correlation coefficient, and signal amplitude change rate difference from the database.

[0094] The signal time characteristic characterization factor is a quantitative index of the differences in signal time characteristics, which is jointly expressed by the signal cross-correlation coefficient, the difference in the rate of change of signal amplitude, and the difference in sampling rate. The specific analysis process is as follows: The cross-correlation coefficient of the collected signal is compared with the corresponding reference value. The reference values ​​corresponding to the difference in the rate of change of signal amplitude and the difference in sampling rate are compared with the difference in the rate of change of signal amplitude and the difference in sampling rate, respectively. The results of each ratio processing are coupled with the corresponding metric factor to obtain the signal time characteristic characterization factor.

[0095] In a specific embodiment, the current signal time feature characterization factor is specifically expressed as follows:

[0096] ,

[0097] Among them, F x The following are the time characteristic representation factors of the current signal: I represents the sampling rate difference, I0 represents the sampling rate difference reference value, c represents the sampling rate difference measurement factor, Q represents the signal amplitude change rate difference, Q0 represents the signal amplitude change rate difference reference value, d represents the signal amplitude change rate difference measurement factor, P represents the signal cross-correlation coefficient, P0 represents the signal cross-correlation coefficient reference value, and s represents the signal cross-correlation coefficient measurement factor.

[0098] Furthermore, the linear interpolation adjustment information is determined, and the specific analysis process is as follows:

[0099] Extract the preset threshold values ​​of signal time feature representation factors from the database.

[0100] If the signal time feature characterization factor is less than the signal time feature characterization factor threshold, then the linear interpolation adjustment information determination result is recorded as demand linear interpolation adjustment.

[0101] If the signal time feature characterization factor is greater than or equal to the signal time feature characterization factor threshold, then the linear interpolation adjustment information determination result is recorded as no linear interpolation adjustment is required.

[0102] It should be explained that if the signal time feature characterization factor is less than the signal time feature characterization factor threshold, it indicates that the signal time alignment is poor and the time interval is uneven, which will lead to the inability to provide timely warnings of abnormal states. In this case, linear interpolation adjustment is required to improve the signal time alignment accuracy and ensure the accuracy of signal processing and analysis.

[0103] If the signal time feature characterization factor is greater than or equal to the signal time feature characterization factor threshold, it indicates that the current signal time alignment is good and the time interval between the signal sampling points is uniform and stable. In this case, the current data can be used to continue running without linear interpolation adjustment.

[0104] When the linear interpolation adjustment information determination result is the required linear interpolation adjustment, the updated cable tension value is analyzed based on the original dataset of the bridge main tower tilt angle and the bridge cable tension.

[0105] Furthermore, the updated cable tension values ​​were analyzed, and the specific analysis process is as follows:

[0106] The timestamp column of the bridge's main tower tilt angle is divided into hourly clusters. The time cluster corresponding to the maximum tilt angle is obtained and recorded as the target time cluster.

[0107] Within the target time cluster, the peak value of the target time cluster is recorded as the main tower tilt angle timestamp reference point.

[0108] Extract the two tension data timestamps adjacent to the main tower tilt angle reference point from the timestamp sequence of bridge cable tension, and record them as the preceding point and the following point, respectively, to obtain the length of the time interval.

[0109] It should be noted that the specific length of the time interval is: the radius of the time interval is obtained by subtracting the preceding point of the cable tension from the subsequent point of the cable tension.

[0110] The length of the time interval is obtained based on the radius of the time interval.

[0111] It should be noted that, based on the radius of the time interval, a circle is drawn using the preceding and following points. After intersecting the circle with the timestamp sequence of the bridge cable tension, two tension data timestamps are obtained, excluding the preceding and following points. The difference between the two timestamps is then used to obtain the length of the time interval.

[0112] Extract the cable tension values ​​corresponding to the preceding and following points.

[0113] The timestamp deviation factor is obtained by subtracting the main tower tilt angle timestamp reference point from the adjacent point.

[0114] The time scale coefficient is obtained based on the timestamp deviation factor and the time interval length analysis.

[0115] It should be noted that the time scale coefficient is obtained by comparing the timestamp deviation factor with the time interval length.

[0116] The total value of the cable tension data is obtained by analyzing the preceding and following points of the cable tension data.

[0117] It should be noted that the total value of the cable tension data is obtained by subtracting the value of the preceding cable tension data from the value of the following cable tension data.

[0118] The updated cable tension value is obtained by combining the total cable tension data with the time scaling factor.

[0119] It should be noted that the updated cable tension value is obtained by multiplying the total cable tension data with the time scaling factor.

[0120] Analyze the cable tension residual and the interpolation adjustment effect label to determine the execution requirements of quadratic linear interpolation adjustment.

[0121] The further detailed analysis process is as follows:

[0122] Extract the two adjacent timestamp values ​​of the cable tension update value from the original dataset, and then extract the corresponding timestamps within the time interval, which are denoted as the first preceding point and the first following point, respectively.

[0123] Subtract the updated cable tension value from the first preceding point value and the first following point value respectively to obtain the cable tension update difference between the first preceding point value and the cable tension update difference between the first following point value.

[0124] If the absolute value of the difference between the numerical cable tension update values ​​at the first preceding point is less than or equal to the absolute value of the difference between the numerical cable tension update values ​​at the first following point, then the first preceding point is recorded as the timestamp corresponding to the cable tension update value.

[0125] It should be noted that if the absolute value of the difference between the cable tension update values ​​at the first preceding point is less than or equal to the absolute value of the difference between the cable tension update values ​​at the first following point, it means that the updated cable tension value is closer to the value at the first preceding point, and its cable tension timestamp is closer to the first preceding point. This means that it can more accurately reflect the time-varying characteristics of the current tension. Therefore, the first preceding point is preferred as the timestamp point corresponding to the updated cable tension value.

[0126] If the absolute value of the difference between the numerical cable tension update values ​​at the first preceding point is greater than the absolute value of the difference between the numerical cable tension update values ​​at the first following point, then the first following point is recorded as the timestamp corresponding to the cable tension update value.

[0127] It should be noted that if the absolute value of the difference between the cable tension update values ​​at the first preceding point is greater than the absolute value of the difference between the cable tension update values ​​at the first following point, it means that the updated cable tension value is closer to the value at the first following point, and that its cable tension timestamp is closer to the first following point. This means that it can more accurately reflect the time-varying characteristics of the current tension. Therefore, the first following point is preferred as the timestamp point corresponding to the updated cable tension value.

[0128] The cable tension timestamp residual is obtained by subtracting the timestamp reference point of the main tower tilt angle from the timestamp point corresponding to the updated cable tension value.

[0129] Extract the cable tension timestamp residual range stored in the database.

[0130] If the cable tension timestamp residual is less than the lower limit of the cable tension timestamp residual interval, the interpolation adjustment effect is recorded as successful adjustment, and the requirement for secondary linear interpolation adjustment is recorded as no secondary linear interpolation adjustment is needed. Simultaneously, a linear interpolation adjustment completion signal is generated.

[0131] It should be noted that if the cable tension timestamp residual is less than the lower limit of the cable tension timestamp residual interval, it means that the difference between the updated cable tension value and the subsequent point value of the cable tension data obtained by linear interpolation is very small. The cable tension data has achieved good alignment and matching on the time axis, and can accurately reflect the actual tension change of the cable, reaching a relatively ideal level. No secondary linear interpolation adjustment is required. Therefore, the interpolation adjustment effect is recorded as successful adjustment, and the secondary linear interpolation adjustment execution requirement is recorded as no secondary linear interpolation adjustment is required. A linear interpolation adjustment completion signal is generated simultaneously.

[0132] If the cable tension timestamp residual is within the cable tension timestamp residual range, the interpolation adjustment effect is recorded as effective adjustment, and the quadratic linear interpolation adjustment execution requirement is recorded as demand quadratic linear interpolation adjustment.

[0133] It should be noted that if the cable tension residual is within the cable tension residual range, it means that the difference between the updated cable tension value and the critical point value of the cable tension data obtained by linear interpolation is relatively large. This indicates that the adjustment measures have had a certain effect, reducing the cable tension residual, but still not reaching the ideal state. At this time, a second linear interpolation adjustment is needed to adjust the data more finely and further reduce the cable tension residual, thereby improving the accuracy and reliability of the cable tension data. Therefore, the effect of interpolation adjustment is recorded as effective adjustment, and the execution requirement of second linear interpolation adjustment is recorded as demand second linear interpolation adjustment.

[0134] If the cable tension timestamp residual is greater than the upper limit of the cable tension timestamp residual interval, the interpolation adjustment effect will be recorded as an adjustment anomaly, and the requirement for quadratic linear interpolation adjustment will be recorded as no quadratic linear interpolation adjustment is needed, and a warning message will be generated simultaneously.

[0135] It should be noted that if the cable tension residual is greater than the upper limit of the cable tension residual interval, it means that the difference between the updated cable tension value and the critical point value of the cable tension data obtained by linear interpolation is very large. This indicates that the adjustment effect is not ideal, the data deviates from expectations, and the abnormal data may be due to various factors, such as sensor failure, external interference, etc. Continuing to perform secondary linear interpolation adjustment may not solve the problem. Therefore, the interpolation adjustment effect is recorded as an adjustment anomaly, and the secondary linear interpolation adjustment execution requirement is recorded as no secondary linear interpolation adjustment is required, and a warning message is generated simultaneously.

[0136] It should be added that, in this embodiment, the warning message can be: "Warning! Abnormality has occurred in linear interpolation adjustment".

[0137] like Figure 5 As shown in the flowchart of a secondary linear adjustment provided in this application, the process includes first performing a difference calculation between the timestamp point corresponding to the cable tension update value and the reference timestamp point of the main tower tilt angle, denoted as a time ratio correction deviation coefficient. The direction of the secondary linear interpolation adjustment is analyzed based on the time ratio correction deviation coefficient. If the adjustment direction is forward, the cable tension timestamp residual is subtracted from the timestamp point corresponding to the cable tension update value, and linear interpolation adjustment is performed again. If the adjustment direction is backward, the cable tension timestamp residual is added to the timestamp point corresponding to the cable tension update value, and linear interpolation adjustment is performed again. After adjustment, the cable tension timestamp residual is re-acquired. If the re-acquired cable tension timestamp residual is greater than or equal to the lower limit of the cable tension timestamp residual interval, a warning message is generated. If the re-acquired cable tension timestamp residual is less than the lower limit of the cable tension timestamp residual, a linear interpolation adjustment completion signal is generated.

[0138] Further, the quadratic linear interpolation adjustment is analyzed in detail as follows:

[0139] The difference between the timestamp corresponding to the updated cable tension value and the timestamp reference point of the main tower tilt angle is processed and recorded as the time ratio correction deviation coefficient.

[0140] The direction of quadratic linear interpolation adjustment is analyzed based on the time ratio correction deviation coefficient.

[0141] It should be noted that if the time ratio correction deviation coefficient is greater than zero, it means the timestamp corresponding to the cable tension update value is greater than the reference timestamp for the main tower's tilt angle. In this case, the timestamp corresponding to the cable tension update value needs to be adjusted forward to bring it closer to the reference timestamp for the main tower's tilt angle. If the time ratio correction deviation coefficient is less than zero, it means the timestamp corresponding to the cable tension update value is less than the reference timestamp for the main tower's tilt angle. In this case, the timestamp corresponding to the cable tension update value needs to be adjusted backward to bring it closer to the reference timestamp for the main tower's tilt angle. If the time ratio correction deviation coefficient is equal to zero, it means the timestamp corresponding to the cable tension update value is equal to the reference timestamp for the main tower's tilt angle, and no adjustment of the timestamp corresponding to the cable tension update value is needed.

[0142] If the adjustment direction is forward, the time ratio correction deviation coefficient is subtracted from the timestamp corresponding to the updated cable tension value to obtain the cable tension correction residual value, and linear interpolation adjustment is performed again.

[0143] If the adjustment direction is backward, the time ratio correction deviation coefficient is added to the timestamp corresponding to the updated cable tension value to obtain the cable tension correction residual value, and linear interpolation adjustment is performed again.

[0144] It should be noted that the linear interpolation adjustment is performed by processing the difference between the values ​​of the preceding and following points to the ratio of the difference between the preceding and following points, and recording it as the linear ratio of the cable tension.

[0145] The cable tension correction value is obtained by multiplying the cable tension correction residual by the linear ratio of the cable tension.

[0146] After adjustment, the cable tension timestamp residual is reacquired. If the reacquired cable tension timestamp residual is greater than or equal to the lower limit of the cable tension timestamp residual interval, an early warning message is generated.

[0147] If the reacquired cable tension timestamp residual is less than the lower limit of the cable tension timestamp residual, a linear interpolation adjustment completion signal is generated.

[0148] If the re-acquired cable tension timestamp residual is greater than or equal to the lower limit of the cable tension timestamp residual interval, an early warning message will be generated.

[0149] It should be noted that if the reacquired cable tension timestamp residual is greater than or equal to the lower limit of the cable tension timestamp residual interval, it means that the deviation between the timestamp corresponding to the cable tension correction value and the theoretical or target value is still large. This indicates that the quadratic linear interpolation adjustment has failed to effectively reduce the residual value to the ideal range, the adjustment effect is poor, and the accuracy and reliability of the cable tension data still have problems. In this case, a warning message will be generated.

[0150] In this embodiment, the warning message could be: "Warning! An error has occurred in the quadratic linear interpolation adjustment."

[0151] If the reacquired cable tension timestamp residual is less than the lower limit of the cable tension residual, a linear interpolation adjustment completion signal is generated.

[0152] It should be noted that if the re-acquired cable tension timestamp residual is less than the lower limit of the cable tension timestamp residual, it means that the difference between the timestamp corresponding to the cable tension correction value and the reference point of the main tower tilt angle timestamp is small, indicating that the quadratic linear interpolation adjustment effect is good, and the timestamp corresponding to the cable tension correction value has been adjusted to the ideal state. To ensure the reliability of subsequent data analysis and structural evaluation, a linear interpolation adjustment completion signal should be generated at this time.

[0153] The system receives the signal after linear interpolation adjustment is completed, analyzes the energy fidelity of the frequency band, determines the validity of the high-frequency signal data, analyzes the signal reconstruction requirement information, and determines the signal reconstruction effect after receiving the signal reconstruction completion information.

[0154] This invention verifies the effectiveness of linear interpolation adjustment by analyzing cable tension residuals and performs secondary adjustments. It dynamically quantifies the accuracy deviation of interpolation adjustment, thereby improving the time synchronization accuracy of cross-sensor data. Specifically, a residual interval determination mechanism accurately identifies the adjustment status: when the residual is less than a threshold, the adjustment is confirmed successful and a completion signal is generated; when the residual is within the interval, a secondary correction is initiated to further reduce timestamp deviation; when the residual exceeds the limit, an anomaly is immediately warned. This preserves the temporal characteristics of abnormal structural vibrations, avoiding distortion of early damage signals caused by clock asynchrony, and providing more reliable and accurate time-series correlation data for bridge condition monitoring.

[0155] Furthermore, the energy fidelity of the frequency band is analyzed, and the specific analysis process is as follows:

[0156] After receiving the signal after linear interpolation adjustment, acquire signal quality data for key frequency bands, including frequency band energy concentration, signal-to-noise ratio, and bandwidth ratio.

[0157] It should be noted that the frequency band energy concentration can be obtained by using the Fourier transform time-frequency analysis method to map the signal to the time-frequency domain, calculate the energy proportion of each frequency component, and thus obtain the frequency band energy concentration.

[0158] The signal-to-noise ratio (SNR) is calculated by converting the signal to the frequency domain using Fourier transform, calculating the power spectral density of the signal and the power spectral density of the noise, and then determining their ratio.

[0159] The bandwidth ratio is obtained by using Fourier transform to obtain the signal spectrum, determining the main energy distribution range of the signal, i.e., the bandwidth, and then comparing it with the width of the entire spectrum or a certain reference bandwidth to obtain the bandwidth ratio.

[0160] It should be noted that the higher the frequency band energy concentration, the more concentrated the signal energy is within a specific frequency band, resulting in less noise interference and a correspondingly higher signal-to-noise ratio. A narrower bandwidth means that the signal energy is more concentrated, and the impact of noise is relatively smaller, thus improving the signal-to-noise ratio. When the signal energy is concentrated in a smaller frequency band, its bandwidth is naturally relatively narrow.

[0161] Frequency band energy fidelity is analyzed based on key frequency band signal quality data.

[0162] Extract the preset frequency band energy concentration measurement factor, signal-to-noise ratio measurement factor, and bandwidth ratio measurement factor from the database.

[0163] Extract the reference values ​​corresponding to the frequency band energy concentration, signal-to-noise ratio, and bandwidth ratio from the database.

[0164] It should be noted that the values ​​of the band energy concentration metric, signal-to-noise ratio metric, and bandwidth ratio metric all range from 0 to 1, and the sum of these three metrics is 1. Pre-defined values ​​can be directly extracted from the database. For example, a one-to-one mapping set can be constructed between the band energy concentration, signal-to-noise ratio, and bandwidth ratio metric and their corresponding metric. When using these metrics, the real-time acquired values ​​are input into the corresponding mapping set to extract the band energy concentration metric, signal-to-noise ratio metric, and bandwidth ratio metric.

[0165] Frequency band energy fidelity is a quantitative indicator of the proportion of energy in key frequency bands in a signal, which is jointly quantified by frequency band energy concentration, signal-to-noise ratio, and bandwidth ratio. The specific analysis process is as follows: The collected frequency band energy concentration, signal-to-noise ratio, and bandwidth ratio are compared with the corresponding reference values. The comparison results are then coupled with the corresponding metric factors to obtain the frequency band energy fidelity.

[0166] In a specific embodiment, the frequency band energy fidelity is analyzed as follows:

[0167] ,

[0168] Among them, F u The values ​​represent frequency band energy fidelity, D represents frequency band energy concentration, D0 represents the reference value of frequency band energy concentration, m represents the frequency band energy concentration measurement factor, G represents signal-to-noise ratio, G0 represents the reference value of signal-to-noise ratio, r represents the signal-to-noise ratio measurement factor, H represents bandwidth ratio, H0 represents the reference value of bandwidth ratio, and w represents the bandwidth ratio measurement factor.

[0169] Furthermore, the validity of high-frequency signal data is determined, and the signal reconstruction requirement information is analyzed accordingly. The specific analysis process is as follows:

[0170] Extract the frequency band energy fidelity threshold stored in the database.

[0171] If the frequency band energy fidelity is greater than or equal to the frequency band energy fidelity threshold, then the high-frequency signal data is recorded as valid data, and the signal reconstruction requirement information is recorded as no signal reconstruction adjustment is required.

[0172] It should be noted that if the frequency band energy fidelity is greater than or equal to the frequency band energy fidelity threshold, it means that the main energy of the signal is concentrated in the key frequency band, and the characteristics and information of the signal are fully preserved in this frequency band. Therefore, the high-frequency signal data is recorded as valid data, and the signal reconstruction requirement information is recorded as no signal reconstruction adjustment is required.

[0173] If the frequency band energy fidelity is less than the frequency band energy fidelity threshold, the high-frequency signal data will be recorded as invalid data, and the signal reconstruction requirement information will be recorded as the requirement signal reconstruction adjustment.

[0174] It should be noted that if the frequency band energy fidelity is less than the frequency band energy fidelity threshold, it means that the energy of the signal in the critical frequency band is small, and a large amount of energy is dispersed in the non-critical frequency band. This may result in a lot of noise interference in the signal, causing signal distortion and affecting the signal quality and availability. Therefore, the valid determination of high-frequency signal data is recorded as invalid data, and the signal reconstruction requirement information is recorded as demand signal reconstruction adjustment.

[0175] Furthermore, the demand signal is restructured and adjusted, and the specific adjustment process is as follows:

[0176] After completing the linear interpolation adjustment, within the preset time window, the tilt angle of the main tower and the tension signal of the bridge cables are continuously collected, and the average frequency coherence factor is analyzed.

[0177] It should be noted that within one cycle, the bridge main tower tilt angle and bridge cable tension signals are continuously collected. Time-frequency analysis is performed on each signal to calculate the frequency coherence factor at each frequency point. Then, the frequencies are averaged to obtain the average frequency coherence factor.

[0178] Extract the standard values ​​of frequency coherence factors stored in the database.

[0179] It should be noted that the standard value of the frequency coherence factor is 1.

[0180] The frequency coherence factor deviation value is obtained by subtracting the frequency coherence factor from the standard value of the frequency coherence factor.

[0181] Extract the frequency coherence factor deviation value threshold stored in the database.

[0182] If the frequency coherence factor deviation is less than the frequency coherence factor threshold, the spectrum is divided into multiple sub-bands to generate a composite signal containing all key frequency bands.

[0183] It should be noted that if the frequency coherence factor is greater than or equal to the frequency coherence factor threshold, it indicates that the two have high coherence. In this case, Fourier transform is used to convert the signal from the time domain to the frequency domain, thereby obtaining the signal spectrum. The spectrum is divided into several sub-bands according to the frequency coherence factor for amplification. The processed sub-band signals are then directly added in the time domain to form a composite signal.

[0184] It needs to be explained that by frequency domain decomposition, the signal is divided into multiple sub-bands based on coherence, and then each sub-band is amplified independently, which can enhance the frequency components with higher coherence in the signal, and finally synthesize an enhanced time-domain signal.

[0185] If the frequency coherence factor deviation value is greater than or equal to the frequency coherence factor threshold, the frequency coherence factor is subtracted from the frequency coherence factor threshold to obtain the frequency coherence deviation score.

[0186] Extract the frequency coherence first adjustment value corresponding to each frequency coherence deviation score interval stored in the database, and map the extracted frequency coherence first adjustment value corresponding to the interval in which the frequency coherence deviation score is located, denoted as the frequency coherence first adjustment value of the bridge structure.

[0187] The first frequency coherence adjustment value for the bridge structure is the dispersion adjustment value.

[0188] It should be noted that a frequency coherence factor less than the frequency coherence factor threshold may be due to dispersion. After passing through a dispersive medium, different frequency components propagate at different speeds, resulting in different arrival times at the same location, which leads to a decrease in frequency coherence. Dispersion compensation is performed to realign the different frequencies in phase and restore frequency coherence.

[0189] Extract the first coherent adjustment value of the current frequency.

[0190] Demand signal reconstruction adjustment is performed based on the current frequency coherence first adjustment value and the frequency coherence first adjustment value of the bridge structure.

[0191] It should be noted that the current frequency coherence first adjustment value represents the dispersion value of the signal at the current frequency, and the frequency coherence first adjustment value of the bridge structure represents the degree of dispersion adjustment when performing signal reconstruction adjustment. The current frequency coherence first adjustment value and the frequency coherence first adjustment value of the bridge structure are added together to complete the signal reconstruction adjustment.

[0192] Further, the signal reconstruction effect is evaluated, and the specific analysis steps are as follows:

[0193] The energy fidelity of the reconstructed frequency band is denoted as the energy fidelity of the first frequency band.

[0194] The frequency band energy fidelity threshold correction factor is extracted based on the energy fidelity of the first frequency band.

[0195] The energy fidelity correction value for the first frequency band is obtained based on the energy fidelity of the first frequency band and the energy fidelity threshold correction factor of the frequency band.

[0196] It should be noted that the first frequency band energy fidelity threshold correction value is obtained by adding the first frequency band energy fidelity threshold and the frequency band energy fidelity threshold correction factor.

[0197] If the frequency band energy fidelity is greater than or equal to the frequency band energy fidelity threshold correction value, the signal reconstruction effect is recorded as a valid reconstruction.

[0198] It should be noted that if the frequency band energy fidelity is greater than or equal to the frequency band energy fidelity threshold correction value, it means that the frequency band energy fidelity of the adjusted signal is high and the adjusted signal is more complete, indicating that the adjustment effect is good. Therefore, the signal reconstruction effect is recorded as effective reconstruction.

[0199] If the frequency band energy fidelity is less than the frequency band energy fidelity threshold correction value, the signal reconstruction effect will be recorded as invalid reconstruction, and an early warning message will be generated.

[0200] It should be noted that if the frequency band energy fidelity is less than the frequency band energy fidelity threshold correction value, it means that the frequency band energy fidelity of the adjusted signal is low and the adjusted signal is more dispersed, indicating that the adjustment effect is poor. Therefore, the signal reconstruction effect is recorded as invalid reconstruction and a warning message is generated.

[0201] It should be added that, in this embodiment, the warning message can be: "Warning! An error has occurred in the signal reconstruction adjustment".

[0202] This invention uses frequency band energy fidelity to screen for frequency bands with sufficient energy in key frequency bands during signal reconstruction, ensuring that the identified signal is the true dynamic response of the structure rather than noise or interference, thus guaranteeing data validity from the source. By using frequency coherence factor to divide input and output signals into two categories for targeted processing, the effectiveness and accuracy of the signals are improved. This ensures that the energy retention of key frequency bands in high-correlation frequency bands is maximized, while low-coherence frequency bands are optimized to avoid noise accumulation and interference.

[0203] This invention also includes a sensor module, a data analysis system, and a software display system. The above description pertains to the data analysis system, which processes signals from the sensor system. Additionally, the main tower tilt angle monitoring indicators and the arrangement of measuring points are as follows: Figure 2As shown; the aforementioned warning information is uploaded to the cloud via sensors. If the cloud detects zero warning information, the software system displays a Level 1 bridge health status; if the cloud detects one warning information, the software system displays a Level 3 alarm; if the cloud detects two warning information, the software system displays a Level 2 alarm; if the cloud detects multiple warning information, the software system displays a Level 1 alarm. The software display system interface is shown below. Figure 3 .

[0204] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0205] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0206] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0207] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0208] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0209] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for monitoring the condition of bridge structures, characterized in that, Includes the following steps: S1. Continuously monitor the bridge structure, obtain the original dataset of the bridge main tower tilt angle and bridge cable tension, analyze the signal time characteristic characterization factor, and then determine the linear interpolation adjustment information. S2, when the linear interpolation adjustment information determination result is the required linear interpolation adjustment, analyze the updated value of the cable tension based on the original dataset of the bridge main tower tilt angle and the bridge cable tension; S3, analyze the cable tension residual, analyze the interpolation adjustment effect label, and thus determine the execution requirement of quadratic linear interpolation adjustment; S4: Receive the linear interpolation adjustment completion signal, analyze the frequency band energy fidelity, thereby determine the validity of high-frequency signal data, analyze the signal reconstruction requirement information, and determine the signal reconstruction effect after receiving the signal reconstruction completion information. The timestamp columns of the bridge main tower tilt angle and the bridge cable tension are obtained from the original dataset of the bridge main tower tilt angle and the bridge cable tension, and the time characterization parameters of the data signal are obtained by analysis. The data signal time characterization parameters include sampling rate difference, signal cross-correlation coefficient, and signal amplitude change rate difference; Analyze the signal time characteristic representation factors based on the data signal time characterization parameters; The signal time characteristic characterization factor is a quantitative index of the difference in signal time characteristics jointly expressed by the signal cross-correlation coefficient, the difference in the rate of change of signal amplitude, and the difference in sampling rate. The specific analysis process is as follows: the collected signal cross-correlation coefficient, the difference in the rate of change of signal amplitude, and the difference in sampling rate are compared with the corresponding reference values, and the results of each comparison are coupled with the corresponding measurement factors to obtain the signal time characteristic characterization factor.

2. The method for monitoring the condition of bridge structures as described in claim 1, characterized in that: The specific analysis process for determining the linear interpolation adjustment information is as follows: Extract the preset threshold values ​​of signal time feature representation factors from the database; If the signal time feature characterization factor is less than the signal time feature characterization factor threshold, then the linear interpolation adjustment information determination result is recorded as demand linear interpolation adjustment; If the signal time feature characterization factor is greater than or equal to the signal time feature characterization factor threshold, then the linear interpolation adjustment information determination result is recorded as no linear interpolation adjustment is required.

3. The method for monitoring the condition of bridge structures as described in claim 1, characterized in that: The analysis process for updating the cable tension value is as follows: The timestamp column of the bridge's main tower tilt angle is clustered according to the preset clustering rules in the database, and the time cluster corresponding to the maximum tilt angle is obtained and recorded as the target time cluster. Within the target time cluster, the peak value of the target time cluster is recorded as the main tower tilt angle timestamp reference point; Extract the two tension data timestamps adjacent to the main tower tilt angle reference point from the timestamp sequence of bridge cable tension, and record them as the preceding point and the following point respectively, thereby obtaining the radius of the time interval; The length of the time interval is obtained based on the radius of the time interval. Extract the cable tension values ​​corresponding to the preceding and following points; The timestamp deviation factor is obtained by subtracting the main tower tilt angle timestamp reference point from the adjacent point. The time proportion coefficient is obtained based on the analysis of timestamp deviation factor and time interval length; The total value of the cable tension data is obtained by analyzing the preceding and following points of the cable tension data. The updated cable tension value is obtained by combining the total cable tension data with the time scaling factor.

4. The method for monitoring the condition of bridge structures as described in claim 1, characterized in that: The analysis of the interpolation adjustment effect labels determines the need for quadratic linear interpolation adjustment. The specific analysis process is as follows: Extract the two adjacent timestamp values ​​of the cable tension update value from the original dataset, and then extract the corresponding timestamps within the time interval, which are denoted as the first preceding point and the first following point, respectively. Subtract the updated cable tension value from the first preceding point value and the first following point value respectively to obtain the cable tension update difference between the first preceding point value and the cable tension update difference between the first following point value. If the absolute value of the cable tension update difference at the first preceding point is less than or equal to the absolute value of the cable tension update difference at the first following point, then the first preceding point is recorded as the timestamp point corresponding to the cable tension update value. If the absolute value of the difference between the numerical cable tension update values ​​at the first preceding point is greater than the absolute value of the difference between the numerical cable tension update values ​​at the first following point, then the first following point is recorded as the timestamp corresponding to the cable tension update value. Subtracting the timestamp reference point of the main tower tilt angle from the timestamp point corresponding to the updated cable tension value yields the cable tension timestamp residual. Extract the cable tension timestamp residual range stored in the database; If the cable tension timestamp residual is less than the lower limit of the cable tension timestamp residual interval, the interpolation adjustment effect is recorded as successful adjustment, and the second linear interpolation adjustment execution requirement is recorded as no second linear interpolation adjustment is required, and a linear interpolation adjustment completion signal is generated simultaneously. If the cable tension timestamp residual is within the cable tension timestamp residual range, the interpolation adjustment effect is recorded as effective adjustment, and the quadratic linear interpolation adjustment execution requirement is recorded as demand quadratic linear interpolation adjustment. If the cable tension timestamp residual is greater than the upper limit of the cable tension timestamp residual interval, the interpolation adjustment effect will be recorded as an adjustment anomaly, and the requirement for quadratic linear interpolation adjustment will be recorded as no quadratic linear interpolation adjustment is needed, and a warning message will be generated simultaneously.

5. The method for monitoring the condition of bridge structures as described in claim 4, characterized in that: The specific analysis process for the quadratic linear interpolation adjustment is as follows: The difference between the timestamp corresponding to the updated cable tension value and the timestamp reference point of the main tower tilt angle is recorded as the time ratio correction deviation coefficient. The direction of quadratic linear interpolation adjustment is analyzed based on the time-proportion correction deviation coefficient. If the adjustment direction is forward, the timestamp corresponding to the updated cable tension value will be subtracted from the cable tension timestamp residual and then linearly interpolated again. If the adjustment direction is backward, the timestamp corresponding to the updated cable tension value will be added to the cable tension timestamp residual and then linearly interpolated again. After adjustment, the cable tension timestamp residual is reacquired. If the reacquired cable tension timestamp residual is greater than or equal to the lower limit of the cable tension timestamp residual interval, an early warning message is generated. If the reacquired cable tension timestamp residual is less than the lower limit of the cable tension timestamp residual, a linear interpolation adjustment completion signal is generated.

6. The method for monitoring the condition of bridge structures as described in claim 1, characterized in that: The energy fidelity of the analyzed frequency band is analyzed in the following specific process: After receiving the signal after linear interpolation adjustment, acquire signal quality data for key frequency bands, including frequency band energy concentration, signal-to-noise ratio, and bandwidth ratio. Analysis of frequency band energy fidelity based on key frequency band signal quality data; The frequency band energy fidelity is a quantitative indicator of the proportion of key frequency band energy in a signal, which is jointly expressed by the frequency band energy concentration, signal-to-noise ratio, and bandwidth ratio. The specific analysis process is as follows: The collected frequency band energy concentration, signal-to-noise ratio, and bandwidth ratio are compared with the corresponding reference values. The comparison results are then coupled with the corresponding metric factors to obtain the frequency band energy fidelity.

7. The method for monitoring the condition of bridge structures as described in claim 1, characterized in that: The process of determining the validity of high-frequency signal data and analyzing signal reconstruction requirements is as follows: Extract the frequency band energy fidelity threshold stored in the database; If the frequency band energy fidelity is greater than or equal to the frequency band energy fidelity threshold, then the high-frequency signal data is recorded as valid data, and the signal reconstruction requirement information is recorded as no signal reconstruction adjustment is required. If the frequency band energy fidelity is less than the frequency band energy fidelity threshold, the high-frequency signal data will be recorded as invalid data, and the signal reconstruction requirement information will be recorded as the requirement signal reconstruction adjustment.

8. The method for monitoring the condition of bridge structures as described in claim 7, characterized in that: The specific adjustment process for the demand signal reconstruction is as follows: After completing the linear interpolation adjustment, within the preset time window, the tilt angle of the main tower and the tension signal of the bridge cables are continuously collected, and the average frequency coherence factor is analyzed. Extract the frequency coherence factor threshold stored in the database; If the frequency coherence factor is greater than or equal to the frequency coherence factor threshold, the spectrum is divided into multiple sub-bands to generate a composite signal containing all key frequency bands. If the frequency coherence factor is less than the frequency coherence factor threshold, the frequency coherence factor is subtracted from the frequency coherence factor threshold to obtain the frequency coherence deviation score. Extract the frequency coherence first adjustment value corresponding to each frequency coherence deviation score interval stored in the database, and map the extracted frequency coherence first adjustment value corresponding to the interval where the frequency coherence deviation score is located, and denot it as the frequency coherence first adjustment value of the bridge structure. The frequency coherence first adjustment value of the bridge structure is the bandwidth adjustment value; Extract the first coherent adjustment value of the current frequency; Demand signal reconstruction adjustment is performed based on the current frequency coherence first adjustment value and the frequency coherence first adjustment value of the bridge structure.

9. The condition monitoring method for bridge structures as described in claim 1, characterized in that: The specific analysis steps for determining the signal reconstruction effect are as follows: The energy fidelity of the reconstructed frequency band is denoted as the energy fidelity of the first frequency band. Extract the band energy fidelity correction factor based on the energy fidelity of the first band; The energy fidelity correction index for the first frequency band is obtained based on the energy fidelity of the first frequency band and the energy fidelity correction factor of the frequency band. If the energy fidelity correction index of the first frequency band is greater than or equal to the energy fidelity threshold of the frequency band, the signal reconstruction effect is recorded as a valid reconstruction. If the energy fidelity correction index of the first frequency band is less than the energy fidelity threshold of the frequency band, the signal reconstruction effect will be recorded as invalid reconstruction, and an early warning message will be generated.

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