A bridge deformation monitoring method during bridge construction

Abstract

The present invention relates to the technical field of data processing, and in particular to a method for monitoring bridge deformation during bridge construction, comprising: collecting initial vibration signals at all connection structures of a bridge main body to obtain time series data of the initial vibration signals; analyzing the time series data of the initial vibration signals, respectively obtaining the main probability of the bridge structure and the bridge deformation degradation degree coefficient of all monitored parts, and correspondingly constructing a first sequence and a second sequence; determining the signal component complexity factor of the monitored part by combining the first sequence and the second sequence, and calculating the real-time clutter signal intensity factor of the monitored part; obtaining an initial decomposition interval scale based on the time series data of the initial vibration signal, correcting the initial decomposition interval scale, decomposing the initial vibration signal, and obtaining a real vibration signal; monitoring the health status of all connection structures of the bridge main body in real time according to the real vibration signal; and ensuring the accuracy of the bridge deformation monitoring result.

Description

Technical Field

[0001] The invention relates to the technical field of data processing, and in particular to a method for monitoring bridge deformation during bridge construction. Background Art

[0002] During the bridge construction process, due to the influence of external pressure or construction accuracy, the bridge may have safety hazards such as tiny cracks or deformation. In order to ensure the safety of the bridge, regular deformation monitoring must be carried out, which includes monitoring the deformation during the construction and operation stages of the bridge. Regular deformation monitoring helps managers to promptly discover the changing trends of the bridge structure and take necessary maintenance and reinforcement measures to ensure the safe operation of the bridge. Therefore, bridge deformation monitoring is an indispensable safety management method in bridge engineering, and it is also a key technical support for improving bridge operation efficiency and extending service life. It is of great significance to ensure public transportation safety and promote economic development.

[0003] At present, deformation monitoring during bridge construction mainly relies on radar sensors to obtain high-precision vibration amplitude and frequency of bridge vibration signals, and then evaluate the current deformation health of the bridge. However, during the monitoring process, the distance between the monitoring point and the deformation area is far, or the reflected signal is weak. In addition, the clutter generated in the construction environment (such as vibration caused by construction vehicles and personnel activities) is mixed with the bridge vibration signal, resulting in deviations in clutter estimation and increased errors in deformation extraction, which affects the accurate extraction of bridge vibration parameters. Summary of the invention

[0004] In order to solve the technical problem that interference factors in the monitoring process lead to deviations and errors in the monitoring data, affecting the extraction of vibration parameters, the purpose of the present invention is to provide a bridge deformation monitoring method during bridge construction. The technical scheme adopted is as follows:

[0005] Collecting initial vibration signals at all connection structures of the main part of the bridge, and performing preprocessing to obtain time series data of the initial vibration signals, wherein the connection structures are monitoring parts;

[0006] Analyze the time series data of the initial vibration signal, obtain the main probability of the bridge structure and the bridge deformation degradation coefficient of all monitored parts, and construct the first sequence and the second sequence accordingly; combine the first sequence and the second sequence to determine the signal component complexity factor of the monitored part, and calculate the real-time clutter signal intensity factor of the monitored part;

[0007] The initial decomposition interval scale is obtained based on the time series data of the initial vibration signal, and the initial decomposition interval scale is corrected by the main probability of the bridge structure, the coefficient of the bridge deformation degradation degree and the real-time clutter signal intensity factor. The initial vibration signal is re-decomposed using the corrected initial decomposition interval scale to obtain the real vibration signal;

[0008] The health status of all connection structures in the main part of the bridge is monitored in real time based on the real vibration signal.

[0009] Preferably, all connection structures of the main part of the bridge include but are not limited to main beams, cables, piers, bridge towers, anchors and abutments; and the preprocessing methods include but are not limited to denoising, data interpolation and filtering.

[0010] Preferably, the time series data of the initial vibration signal is analyzed to obtain the main probability of the bridge structure and the bridge deformation degradation degree coefficient of all monitoring parts respectively, and the first sequence and the second sequence are constructed accordingly, including:

[0011] The vibration coupling coefficient of all monitoring locations is determined by calculating the Pearson correlation coefficient of any two monitoring locations, the variance of the corresponding initial vibration signal amplitude set data is obtained based on the time series data of the initial vibration signal of each monitoring location, the main probability of the bridge structure of all monitoring locations is calculated, and the first sequence is constructed by sorting;

[0012] Based on the time series data of the initial vibration signal, each monitoring location is divided into windows by signal sampling points to generate a window area. The periodicity of the initial vibration signal and the mean distance between the initial vibration signal peaks in the window area corresponding to all signal sampling points in all monitoring locations are obtained. The bridge deformation degradation degree coefficients of all monitoring locations are calculated and sorted to construct the second sequence.

[0013] Preferably, the main probability of the bridge structure at the monitoring location is calculated, and the corresponding calculation formula is:

[0014]

[0015] in, Indicates Monitoring sites; Indicates The variance of the amplitude aggregate data of the initial vibration signal of each monitoring part; Indicates The vibration coupling coefficient of each monitoring part; Indicates The main probability of the bridge structure at each monitoring location; Represents a correction parameter used to prevent the denominator from being zero.

[0016] Preferably, the bridge deformation deterioration coefficient of the monitored part is calculated, and the corresponding calculation formula is:

[0017]

[0018] in, Indicates A set of the number of signal sampling points of the initial vibration signal of each monitoring part; Indicates The first of the initial vibration signals of the monitoring parts signal sampling points; Indicates The first sampling point in front of sampling points; Indicates The mean value of the peak distance of the initial vibration signal in the window area corresponding to each signal sampling point; Indicates The mean value of the peak distance of the initial vibration signal in the window area corresponding to each signal sampling point; Indicates The periodicity of the initial vibration signal in the window area corresponding to each signal sampling point; Indicates The bridge deformation deterioration degree coefficient of each monitoring location.

[0019] Preferably, the signal component complexity factor of the monitoring part is determined by combining the first sequence and the second sequence, and the real-time clutter signal intensity factor of the monitoring part is calculated, including:

[0020] Determine the ranking number of each monitoring site in the first sequence and the second sequence respectively, and obtain the ranking difference as the signal component complexity factor of the monitoring site;

[0021] Based on the time series data of the initial vibration signal, the occurrence probability of each signal maximum point in each monitoring part in the initial vibration signal and the slope at each signal maximum point are obtained respectively, and the real-time clutter signal intensity factor of the monitoring part is calculated.

[0022] Preferably, the real-time clutter signal strength factor of the monitoring part is calculated, and the corresponding calculation formula is:

[0023]

[0024] in, Indicates Complexity factor of signal components in each monitoring site; Indicates The number of all signal maximum points in the initial vibration signal of each monitoring part; Indicates The serial number of the signal maximum point; Indicates The probability of occurrence of a signal maximum point in the initial vibration signal; Indicates The slope at the maximum point of the signal; Indicates The real-time clutter signal strength factor of each monitoring location.

[0025] Preferably, the initial decomposition interval scale is corrected by the main probability of the bridge structure, the coefficient of bridge deformation degradation degree and the real-time clutter signal intensity factor, and the corresponding calculation formula is:

[0026]

[0027] in, Indicates The bridge deformation deterioration degree coefficient of each monitoring location; Indicates The main probability of the bridge structure at each monitoring location; Indicates Real-time clutter signal intensity factor of each monitoring location; Indicates The initial decomposition interval scale of each signal stage in the initial vibration signal of each monitoring part; Indicates The initial decomposition interval scale after correction of each signal stage in the initial vibration signal of each monitoring part.

[0028] Preferably, the initial vibration signal is re-decomposed using the modified initial decomposition interval scale to obtain the real vibration signal, including: re-decomposing the initial vibration signal using the modified initial decomposition interval scale to obtain all component signals, sorting all component signals from small to large according to the variance of the amplitudes of the component signals, selecting several component signals with small variances for reconstruction, and obtaining the real vibration signal.

[0029] Preferably, the health status of all connection structures in the main part of the bridge is monitored in real time based on the real vibration signal, including: monitoring the amplitude of the real vibration signal based on each monitoring part, setting a judgment threshold, and if the amplitude exceeds the judgment threshold, the monitoring part is abnormal.

[0030] The present invention has the following beneficial effects:

[0031] This technical solution analyzes the vibration coupling effect and deformation degradation degree between all the connecting structures of the main part of the bridge, and determines whether the current monitoring part is interfered by the noise signal according to the changes in the corresponding sequence rankings of the two. Then, the noise signal strength of the initial vibration signal of the current monitoring part is analyzed to determine the adaptive decomposition strength to obtain the real vibration signal of the current monitoring part. The health status of each monitoring part is monitored in real time based on the real vibration signal to ensure the accuracy of the subsequent bridge deformation monitoring results. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0033] Figure 1 A method flow chart of a method for monitoring bridge deformation during bridge construction provided by one embodiment of the present invention;

[0034] Figure 2 A flow chart of the steps of a method for monitoring bridge deformation during bridge construction provided by one embodiment of the present invention;

[0035] Figure 3 A schematic diagram of the radar vibration monitoring principle of a bridge deformation monitoring method during bridge construction provided by one embodiment of the present invention;

[0036] Figure 4 A schematic diagram of a monitoring scenario of a radar sensor on a main part of a bridge in a method for monitoring bridge deformation during bridge construction provided by an embodiment of the present invention;

[0037] Figure 5 A schematic diagram of a radar sensor collecting initial vibration signals of a bridge in a bridge deformation monitoring method during bridge construction provided by an embodiment of the present invention;

[0038] Figure 6 This is a RLMD signal decomposition diagram of a bridge deformation monitoring method during bridge construction provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0039] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the bridge deformation monitoring method during bridge construction proposed by the present invention, its specific implementation method, structure, characteristics and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0040] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0041] The specific scheme of the bridge deformation monitoring method during bridge construction provided by the present invention is described in detail below with reference to the accompanying drawings.

[0042] Please combine Figure 1 and Figure 2 , which respectively show a system flow chart and a step flow chart of a bridge deformation monitoring method during bridge construction provided by an embodiment of the present invention, the method comprising:

[0043] Step S1: collecting initial vibration signals at all connection structures of the main part of the bridge, and preprocessing to obtain time series data of the initial vibration signals, where the connection structures are the monitoring parts;

[0044] Step S2: Analyze the time series data of the initial vibration signal, obtain the main probability of the bridge structure and the bridge deformation degradation coefficient of all monitored parts respectively, and construct the first sequence and the second sequence accordingly; determine the signal component complexity factor of the monitored part by combining the first sequence and the second sequence, and calculate the real-time clutter signal intensity factor of the monitored part;

[0045] Step S3: obtaining an initial decomposition interval scale based on the time series data of the initial vibration signal, correcting the initial decomposition interval scale by the main probability of the bridge structure, the coefficient of the bridge deformation degradation degree and the real-time clutter signal intensity factor, and re-decomposing the initial vibration signal using the corrected initial decomposition interval scale to obtain a real vibration signal;

[0046] Step S4: Monitor the health status of all connection structures of the main part of the bridge in real time according to the real vibration signal.

[0047] As an optional implementation, a traditional bridge deformation monitoring system includes a radar sensor system, a data acquisition and processing unit, a deformation analysis and algorithm module, a status monitoring and alarm module, and a data storage and management system; in this embodiment, the traditional bridge deformation monitoring system is used to analyze and process the monitoring data; it can be understood that when the various systems, modules and units in the traditional bridge deformation monitoring system are in operation, it is necessary to utilize a bridge deformation monitoring method during bridge construction provided by an embodiment of the present invention. Therefore, whether the radar sensor system, data acquisition and processing unit, deformation analysis and algorithm module, status monitoring and alarm module, and data storage and management system are integrated or different hardware is configured to produce functions similar to the effects achieved by the present invention, they all fall within the protection scope of the present invention.

[0048] Among them, the radar sensor system is used to capture the tiny deformation and displacement of the bridge in real time; the data acquisition and processing unit is used to collect data from the radar sensor and perform preliminary processing; the deformation analysis and algorithm module uses complex algorithms to conduct in-depth analysis of the data to identify potential structural problems; the status monitoring and alarm module, when abnormal deformation is detected, the module will immediately issue an alarm to remind relevant personnel to take measures; the data storage and management system is responsible for the long-term preservation of monitoring data to facilitate subsequent analysis and historical data comparison. Through the collaborative work of these components, the efficient operation of the bridge deformation monitoring system is ensured, providing a strong guarantee for the safety of the bridge.

[0049] See also Figure 3 , which shows a radar vibration monitoring principle diagram of a bridge deformation monitoring method during bridge construction provided by an embodiment of the present invention. For better explanation, the radar sensor A transmits a high-frequency electromagnetic wave signal to the monitoring part on the bridge. , i.e. radar wave, the signal will propagate along a straight line and be reflected back to radar sensor A when it encounters a vibration point P, where the vibration point is a bridge cable, a viaduct, a supporting structure of a large building, etc.; radar sensor A receives the radar wave signal reflected from the bridge surface , the distance between the radar sensor and the vibration point P is calculated in real time to obtain the real-time vibration signal of the vibration point P.

[0050] Based on the above, it can be seen that when existing radar sensors collect vibration signals at the monitored location, they are easily affected by the complex external environment, including but not limited to weather changes, traffic flow, the influence of surrounding buildings, etc., resulting in a large amount of noise components in the collected vibration signals, which in turn affects the quality of the vibration signals. Therefore, based on the bridge deformation monitoring method during bridge construction proposed in this application, the technical solution is optimized to obtain a more accurate real vibration signal of the bridge.

[0051] Please combine Figure 4and Figure 5 , which respectively show a schematic diagram of a radar sensor monitoring scene of a bridge main body part of a bridge deformation monitoring method during bridge construction provided by an embodiment of the present invention and a schematic diagram of a radar sensor collecting an initial vibration signal of a bridge; further, in step S1, all connecting structures of the bridge main body part include but are not limited to main beams, cables, piers, bridge towers, anchors and abutments; preprocessing methods include but are not limited to denoising, data interpolation and filtering.

[0052] Specifically, the initial vibration signals of all connecting structures of the main part of the bridge are collected, including but not limited to the main beam, cables, piers, bridge towers, anchors and abutments, that is, the radar sensor is installed at the monitoring location, and the direction and angle of the radar sensor are adjusted according to the structure and design of the bridge itself, so that it can effectively monitor the initial vibration signals of all monitoring parts of the bridge every day; and preprocessing such as denoising, data interpolation and filtering are performed to obtain the time series data of the initial vibration signal, among which denoising is to eliminate unnecessary noise components in the signal and improve the purity of the signal; data interpolation is to fill in the missing data points in the initial vibration signal to ensure the continuity and integrity of the time series data; filtering is to remove the interference components in the initial vibration signal through a specific algorithm and retain useful information. Based on the preprocessing, the accuracy and reliability of the time series data of the initial vibration signal can be ensured.

[0053] Understandably, under normal circumstances, a bridge is a complex structural system whose various parts are closely connected and jointly bear huge loads and stresses. Therefore, any structural deformation of any part, whether small or significant, will affect the stress distribution and vibration characteristics of other connecting structural parts to a certain extent. Therefore, when an abnormal deformation occurs in a certain part of the bridge, its abnormal situation usually further affects the overall stability of the entire bridge connection structure through the interaction and coupling effect between the structures; that is, the local abnormal deformation of the bridge will affect the vibration mode of the entire bridge connection through the coupling effect between the bridge structures, which may lead to a decrease in the bearing capacity and safety of the entire bridge, especially in the main part of the bridge. The main part of the bridge not only has to bear the static load from the weight of the bridge itself, but also has to deal with the dynamic load brought by the traffic flow, and has more connecting structures. This effect is particularly significant; and any tiny structural deformation may be amplified under the action of these complex stresses and vibrations, ultimately affecting the overall performance and service life of the bridge.

[0054] Furthermore, in step S2, the time series data of the initial vibration signal is analyzed to obtain the main probability of the bridge structure and the bridge deformation degradation degree coefficient of all monitored parts respectively, and the first sequence and the second sequence are constructed accordingly, including:

[0055] Step S211: Determine the vibration coupling coefficient of all monitoring locations by calculating the Pearson correlation coefficient of any two monitoring locations, obtain the variance of the amplitude set data of the corresponding initial vibration signal based on the time series data of the initial vibration signal of each monitoring location, calculate the main probability of the bridge structure of all monitoring locations, and sort them to construct the first sequence.

[0056] Specifically, based on the time series data of the initial vibration signal, that is, the initial vibration signals of all monitoring parts of the bridge every day, the set of initial vibration signal amplitudes of each monitoring part every day is obtained; the vibration coupling coefficient of all monitoring parts is determined by calculating the Pearson correlation coefficient of any two monitoring parts, that is, any monitoring part is defined as the target part, and all remaining monitoring parts are non-target parts, and the Pearson correlation coefficient of the target part's daily initial vibration signal amplitude set and the non-target part's daily initial vibration signal amplitude set is calculated. The Pearson correlation coefficient is a statistical indicator for measuring the degree of linear correlation between two variables, and its value is between -1 and 1. When the coefficient is 1, it indicates that the two variables are completely positively correlated; when the coefficient is -1, it indicates that the two variables are completely negatively correlated; and when the coefficient is 0, it indicates that there is no linear correlation between the two variables.

[0057] The Pearson correlation coefficient is used to determine the co-trend of the two sets of initial vibration signal amplitudes of the target part and the non-target part every day to measure the vibration coupling effect between the two monitoring parts of the bridge, and then the mean value of the coupling effect between different monitoring parts is obtained. The mean value is recorded as the vibration coupling coefficient of the target part, which is used to determine whether the target part is affected by the vibration of other monitoring parts. The larger the value, the greater the possibility that the target part is determined to be the main part of the bridge.

[0058] It can be explained that due to the large amount of construction vibration during bridge construction, there are significant differences in the vibration characteristics of different monitoring parts; for example, the main beams and piers of the bridge usually have higher structural stability, so their vibration signals are relatively stable, with lower noise components and higher signal-to-noise ratios; in contrast, the structural stability of parts such as the bridge cables is poor, and external influences will introduce more noise, making the signal-to-noise ratio of the vibration signal higher; therefore, if only the co-trend of the initial vibration signals between the two monitoring parts is analyzed, it cannot effectively reflect the extent to which the target part of the bridge is affected by the vibration of other monitoring parts, that is, the probability of the main body of the bridge structure.

[0059] Then, the corresponding variance is obtained based on the set of initial vibration signal amplitudes of the target part every day. The larger the value, the more chaotic the initial vibration signal amplitude of the target part is, indicating that the target part may be a part such as a cable with unstable structure in the bridge.

[0060] Furthermore, in step S211, the main probability of the bridge structure at the monitoring location is calculated, and the corresponding calculation formula is:

[0061]

[0062] in, Indicates Monitoring sites; Indicates The variance of the amplitude aggregate data of the initial vibration signal of each monitoring part; Indicates The vibration coupling coefficient of each monitoring part; Indicates The main probability of the bridge structure at each monitoring location; Represents a correction parameter used to prevent the denominator from being zero.

[0063] To illustrate, in this embodiment, ; The vibration coupling coefficient of the target part is corrected according to the structural stability of the target part of the bridge. The target part shows a higher vibration signal stability. Even if it is affected by the vibration coupling effect of other monitored parts, its data change is still small, showing a higher vibration steady-state characteristic, indicating that the target part is more likely to be the main part of the bridge, that is, the probability of the main part of the bridge structure is higher. The larger the value is, the smaller the amplitude of the initial vibration signal of the same monitoring part is. It can be explained that there are usually differences in the amplitude set data of the initial vibration signal of the same monitoring part, and the variance is greater than 0. At the same time, the vibration coupling coefficient is a quantitative indicator that describes the degree of coupling between different vibration modes, and its value range is Therefore, the absolute value is set to map it to the positive range to ensure its rationality in the correction of the target part and avoid the negative impact that may be introduced by the negative value.

[0064] Based on the above thinking logic, under the current construction progress, the main probability of the bridge structure of all monitoring parts is obtained in the same way, and the values ​​are sorted from large to small to construct the first sequence. Specifically, assuming that the first The probability of the main body of the bridge structure at the monitoring position is the largest, and the probability sequence of the main body of the bridge structure at different monitoring positions of the bridge is the first sequence, which is recorded as ,in, Indicates Monitoring sites, Indicates the requested The probability of the main body of the bridge structure at the monitoring location is the smallest.

[0065] Step S212: Each monitoring location is divided into windows based on the time series data of the initial vibration signal using signal sampling points to generate a window area, and the periodicity of the initial vibration signal and the average distance between the initial vibration signal peaks in the window area corresponding to all signal sampling points in all monitoring locations are obtained. The bridge deformation degradation degree coefficients of all monitoring locations are calculated and sorted to construct a second sequence.

[0066] It can be understood that during the construction process, the deformation process experienced by the bridge is a gradual accumulation process; in the initial stage of construction, the specific parts of the bridge will cause corresponding changes in the periodicity and periodic frequency of its initial vibration signal due to the changes in the load and structure they bear.

[0067] Specifically, each monitoring part is divided into windows based on the time series data of the initial vibration signal and the signal sampling points to generate a window area. For the initial vibration signal of each monitoring part of the bridge, the window is divided according to its signal sampling points, that is, based on the initial vibration signal obtained every day, every minute is used as a signal sampling point within 0-24 hours; each signal sampling point and the 9 signal sampling points between it are regarded as a window area. If the number is less than 10, all the remaining signal sampling points are recorded as a window area to ensure that each part of the initial vibration signal can be fully analyzed to avoid omissions and to capture the local characteristics of the initial vibration signal more comprehensively.

[0068] The periodicity of the initial vibration signal in the window area corresponding to all signal sampling points in all monitoring locations and the average distance between the peaks of the initial vibration signal are obtained, that is, all the peaks of the initial vibration signal of each monitoring location of the bridge are obtained by using the peak detection technology, and the periodicity of all window areas of the initial vibration signal is obtained by using the autocorrelation function. Among them, the peak detection technology can accurately identify the local maximum point in the initial vibration signal, that is, the peak, to obtain important information on the intensity and frequency of the initial vibration signal; the autocorrelation function can measure the similarity between the initial vibration signal and itself under different time delays, and determine the periodicity of all window areas of the initial vibration signal, that is, the temporal repetition pattern of the initial vibration signal, so as to confirm the vibration behavior of the bridge in different time periods.

[0069] Furthermore, in step S212, the bridge deformation degradation coefficient of the monitored part is calculated, and the corresponding calculation formula is:

[0070]

[0071] in, Indicates A set of the number of signal sampling points of the initial vibration signal of each monitoring part; Indicates The first of the initial vibration signals of the monitoring parts signal sampling points; Indicates The first sampling point in front of sampling points; Indicates The mean value of the peak distance of the initial vibration signal in the window area corresponding to each signal sampling point; Indicates The mean value of the peak distance of the initial vibration signal in the window area corresponding to each signal sampling point; Indicates The periodicity of the initial vibration signal in the window area corresponding to each signal sampling point; Indicates The bridge deformation deterioration degree coefficient of each monitoring location.

[0072] It is understandable that when the main part of the bridge is subjected to a large load or undergoes significant structural changes, the physical properties such as mass distribution and stiffness of these parts change, causing the structure to exhibit nonlinear behavior, resulting in a corresponding change in the period of the initial vibration signal. By comprehensively considering the parameters such as the local signal periodicity at each signal sampling point and the frequency of the peak occurrence, the possibility of the bridge appearing in the real-time vibration signal can be measured to measure the early deformation characteristics, and then the deformation degradation coefficient of the bridge can be evaluated. , in order to reflect the health status of each monitored part of the bridge, discover potential problems in time, and facilitate the adoption of corresponding maintenance and repair measures.

[0073] Based on the above logic, under the current construction progress, the bridge deformation deterioration coefficients of all monitored parts are obtained in the same way, and sorted from large to small based on the values ​​to construct the second sequence. Specifically, it is still assumed that the required The bridge deformation degradation coefficient of the monitoring position is the largest, and the bridge deformation degradation coefficient sequence of different monitoring positions of the bridge is the second sequence, which is recorded as ,in, Indicates Monitoring sites, Indicates the requested The bridge deformation deterioration coefficient at the monitoring location is the smallest.

[0074] It is understandable that during the bridge construction process, there is a large amount of electromagnetic interference generated by construction machines in the complex construction environment, which leads to different degrees of electromagnetic noise interference when the initial vibration signal is collected at the bridge monitoring part. It is necessary to determine whether the initial vibration signal of each monitoring part of the bridge is affected by the noise.

[0075] Furthermore, in step S2, the signal component complexity factor of the monitoring part is determined by combining the first sequence and the second sequence, and the real-time clutter signal strength factor of the monitoring part is calculated, including:

[0076] Step S221: Determine the ranking number of each monitoring site in the first sequence and the second sequence respectively, and obtain the ranking difference as the signal component complexity factor of the monitoring site.

[0077] It can be explained that based on the ideal state of bridge construction, that is, without noise interference, the greater the probability of the main body of the bridge structure, that is, the greater the possibility that the monitored part is determined to be the main part of the bridge, the stronger its structural stability is, and the smaller the degree of deformation and deterioration is, that is, the same monitoring part is in the first sequence The ranking number and the second sequence in The ranking numbers in the sequence are one-to-one corresponding to each other in the opposite direction. For example, if the ranking number of the current monitoring location in the first sequence is 1, then its ranking number in the second sequence is , which is the last one.

[0078] When there is a difference in the sequence ranking number of the same bridge monitoring part in the two sequences, it means that the initial vibration signal of the bridge monitoring part is interfered by external electromagnetic interference, which makes the initial vibration signal have a large amount of noise components. Then the ranking difference is regarded as the signal component complexity factor of the monitoring part. For example, the current monitoring part is ranked 1 in the first sequence and ranked 2 in the second sequence. , which is two ranking numbers different from its ideal state, that is, the signal component complexity factor of the current monitoring location is 2.

[0079] Step S222: Based on the time series data of the initial vibration signal, the occurrence probability of each signal maximum point in each monitoring part in the initial vibration signal and the slope at each signal maximum point are respectively obtained, and the real-time clutter signal strength factor of the monitoring part is calculated.

[0080] It is explained that when the monitoring part of the bridge is deformed or affected by external environmental noise, instantaneous irregular vibration will be introduced, and its initial vibration signal may have a large number of high-frequency burr signals, that is, abnormal signal amplitude; the burr signal is the manifestation of the high-frequency components of these abnormal conditions, which usually reflects the instantaneous surge or instability of the initial vibration signal. By analyzing the performance of the burr signal in the initial vibration signal of the bridge monitoring part, the influence of the noise signal contained in the initial vibration signal can be effectively measured; based on the time series data of the initial vibration signal, the probability of occurrence of each signal maximum point in each monitoring part in the initial vibration signal and the slope at each signal maximum point are obtained respectively, so as to more accurately capture the abnormal characteristics of the initial vibration signal and provide more reliable data support for the safety monitoring of the bridge.

[0081] Furthermore, in step S222, the real-time clutter signal strength factor of the monitoring part is calculated, and the corresponding calculation formula is:

[0082]

[0083] in, Indicates Complexity factor of signal components in each monitoring site; Indicates The number of all signal maximum points in the initial vibration signal of each monitoring part; Indicates The serial number of the signal maximum point; Indicates The probability of occurrence of a signal maximum point in the initial vibration signal; Indicates The slope at the maximum point of the signal; Indicates The real-time clutter signal strength factor of each monitoring location.

[0084] It can be explained that in step S3, the initial decomposition interval scale is obtained based on the time series data of the initial vibration signal. Specifically, based on the traditional RLMD (Relevant Local Mean Decomposition) signal decomposition algorithm, the local mean in the sliding window of each signal sampling point in the initial vibration signal is calculated. In this embodiment, the sliding window is customized to 20 signal sampling points; the initial decomposition interval scale is obtained according to the change of the local mean in the initial vibration signal. , reflecting the initial change characteristics of the initial vibration signal on different time scales.

[0085] Furthermore, in step S3, the initial decomposition interval scale is corrected by the main probability of the bridge structure, the coefficient of bridge deformation degradation degree and the real-time clutter signal intensity factor, and the corresponding calculation formula is:

[0086]

[0087] in, Indicates The bridge deformation deterioration degree coefficient of each monitoring location; Indicates The main probability of the bridge structure at each monitoring location; Indicates Real-time clutter signal intensity factor of each monitoring location; Indicates The initial decomposition interval scale of each signal stage in the initial vibration signal of each monitoring part; Indicates The initial decomposition interval scale after correction of each signal stage in the initial vibration signal of each monitoring part.

[0088] To explain, Indicates The ratio of the bridge deformation degradation coefficient of each monitoring part to the main probability of the bridge structure is used to comprehensively evaluate the health status and structural stability of the bridge. The larger the ratio, the more serious the deformation of the bridge, or the higher the probability of structural failure. The real-time clutter signal strength factor is introduced. , to compensate and correct the clutter in the initial vibration signal, eliminate or reduce the influence of external interference, and improve the analysis accuracy; based on the The initial decomposition interval scale of each signal stage in the initial vibration signal of each monitoring part adjusts the response of the initial vibration signal in different frequency bands, so that the initial vibration signal of each stage can better reflect the actual health status of the bridge, and then obtain the corrected initial decomposition interval scale, thereby improving the assessment accuracy and reliability of the health status of the bridge.

[0089] See also Figure 6 , which shows a RLMD signal decomposition diagram of a bridge deformation monitoring method during bridge construction provided by an embodiment of the present invention.

[0090] Further, in step S3, the initial vibration signal is re-decomposed using the modified initial decomposition interval scale to obtain a real vibration signal, including:

[0091] The initial vibration signal is decomposed again using the modified initial decomposition interval scale to obtain all component signals. All component signals are sorted from small to large according to the variance of the amplitude, and several component signals with small variance are selected for reconstruction to obtain the real vibration signal.

[0092] Specifically, the initial decomposition interval scale after correction of the monitoring part is re-decomposed to obtain all component signals, that is, all component signals obtained by optimizing the RLMD signal decomposition algorithm, each component signal represents the specific frequency and amplitude characteristics of the initial vibration signal, and the variance of the amplitudes of all component signals are sorted from small to large, that is, they are sorted from high to low according to their importance, and several component signals with small variance are selected for reconstruction. It can be explained that the smaller the variance, the higher the importance of the component signal in the overall vibration signal; preferably, in this embodiment, the first three component signals with the smallest variance are selected for reconstruction to obtain the real vibration signal.

[0093] Furthermore, step S4 includes: monitoring the amplitude of the real vibration signal based on each monitored part, setting a judgment threshold, and if the amplitude exceeds the judgment threshold, an abnormality occurs in the monitored part.

[0094] As an optional implementation, in this embodiment, the judgment threshold is 0.5. Specifically, based on the aforementioned status monitoring and alarm module, the amplitude of the real vibration signal of each monitored part is monitored. If the amplitude exceeds the judgment threshold, the monitored part is abnormal, an alarm is issued, and relevant personnel are notified in time or an emergency response is automatically triggered according to a preset emergency response mechanism to minimize potential losses and risks. On the contrary, if the amplitude is less than the judgment threshold, the monitored part is in good health and operating normally. At this time, the status monitoring and alarm module will not issue an alarm, and relevant personnel can continue to maintain normal operation and monitoring without taking additional emergency measures.

[0095] It can be understood that this technical solution analyzes the vibration coupling effect and deformation degradation degree between all the connecting structures of the main part of the bridge, and determines whether the current monitoring part is interfered by the noise signal according to the changes in the corresponding sequence rankings of the two. Then, the noise signal intensity of the initial vibration signal of the current monitoring part is analyzed to determine the adaptive decomposition intensity to obtain the real vibration signal of the current monitoring part, and monitor the health status of each monitoring part in real time based on the real vibration signal to ensure the accuracy of the subsequent bridge deformation monitoring results.

[0096] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0097] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for monitoring bridge deformation during bridge construction, characterized in that: The method comprises: Collecting initial vibration signals at all connection structures of the main part of the bridge, and performing preprocessing to obtain time series data of the initial vibration signals, wherein the connection structures are monitoring parts; Analyze the time series data of the initial vibration signal, obtain the main probability of the bridge structure and the bridge deformation degradation coefficient of all monitored parts, and construct the first sequence and the second sequence accordingly; combine the first sequence and the second sequence to determine the signal component complexity factor of the monitored part, and calculate the real-time clutter signal intensity factor of the monitored part; The initial decomposition interval scale is obtained based on the time series data of the initial vibration signal, and the initial decomposition interval scale is corrected by the main probability of the bridge structure, the coefficient of the bridge deformation degradation degree and the real-time clutter signal intensity factor. The initial vibration signal is re-decomposed using the corrected initial decomposition interval scale to obtain the real vibration signal; Monitor the health status of all connection structures in the main part of the bridge in real time based on real vibration signals; Analyze the time series data of the initial vibration signal, obtain the main probability of the bridge structure and the bridge deformation degradation coefficient of all monitored parts, and construct the first sequence and the second sequence accordingly, including: The vibration coupling coefficient of all monitoring locations is determined by calculating the Pearson correlation coefficient of any two monitoring locations. The variance of the corresponding amplitude set data of the initial vibration signal is obtained based on the time series data of the initial vibration signal of each monitoring location. The main probability of the bridge structure of all monitoring locations is calculated based on the vibration coupling coefficient and variance, and the first sequence is constructed by sorting. Based on the time series data of the initial vibration signal, each monitoring location is divided into windows by signal sampling points to generate a window area. The periodicity of the initial vibration signal and the mean distance between the initial vibration signal peaks in the window area corresponding to all signal sampling points in all monitoring locations are obtained. According to the periodicity and the mean distance, the bridge deformation degradation degree coefficients of all monitoring locations are calculated and sorted to construct the second sequence.

2. A method for monitoring bridge deformation during bridge construction as claimed in claim 1, characterized in that: All connection structures of the main part of the bridge include main beams, cables, piers, bridge towers, anchors and abutments.

3. A method for monitoring bridge deformation during bridge construction as claimed in claim 1, characterized in that: Calculate the main probability of the bridge structure at the monitoring location, and the corresponding calculation formula is: in, Indicates Monitoring sites; Indicates The variance of the amplitude aggregate data of the initial vibration signal of each monitoring part; Indicates The vibration coupling coefficient of each monitoring part; Indicates The main probability of the bridge structure at each monitoring location; Represents a correction parameter used to prevent the denominator from being zero.

4. A method for monitoring bridge deformation during bridge construction as claimed in claim 1, characterized in that: Calculate the bridge deformation deterioration coefficient of the monitored part, and the corresponding calculation formula is: in, Indicates A set of the number of signal sampling points of the initial vibration signal of each monitoring part; Indicates The first of the initial vibration signals of the monitoring parts signal sampling points; Indicates The first sampling point in front of sampling points; Indicates The mean value of the peak distance of the initial vibration signal in the window area corresponding to each signal sampling point; Indicates The mean value of the peak distance of the initial vibration signal in the window area corresponding to each signal sampling point; Indicates The periodicity of the initial vibration signal in the window area corresponding to each signal sampling point; Indicates The bridge deformation deterioration degree coefficient of each monitoring location.

5. The method for monitoring bridge deformation during bridge construction as claimed in claim 1, characterized in that: The signal component complexity factor of the monitoring part is determined by combining the first sequence and the second sequence, and the real-time clutter signal intensity factor of the monitoring part is calculated, including: Determine the ranking number of each monitoring site in the first sequence and the second sequence respectively, and obtain the ranking difference as the signal component complexity factor of the monitoring site; Based on the time series data of the initial vibration signal, the occurrence probability of each signal maximum point in each monitoring part in the initial vibration signal and the slope at each signal maximum point are obtained respectively, and the real-time clutter signal intensity factor of the monitoring part is calculated.

6. A method for monitoring bridge deformation during bridge construction as claimed in claim 5, characterized in that: Calculate the real-time clutter signal strength factor of the monitored part. The corresponding calculation formula is: in, Indicates Complexity factor of signal components in each monitoring site; Indicates The number of all signal maximum points in the initial vibration signal of each monitoring part; Indicates The serial number of the signal maximum point; Indicates The probability of occurrence of a signal maximum point in the initial vibration signal; Indicates The slope at the maximum point of the signal; Indicates The real-time clutter signal strength factor of each monitoring location.

7. A method for monitoring bridge deformation during bridge construction as claimed in claim 5, characterized in that: The initial decomposition interval scale is corrected by the main probability of the bridge structure, the coefficient of bridge deformation degradation and the real-time clutter signal intensity factor. The corresponding calculation formula is: in, Indicates The bridge deformation deterioration degree coefficient of each monitoring location; Indicates The main probability of the bridge structure at each monitoring location; Indicates Real-time clutter signal intensity factor of each monitoring location; Indicates The initial decomposition interval scale of each signal stage in the initial vibration signal of each monitoring part; Indicates The initial decomposition interval scale after correction of each signal stage in the initial vibration signal of each monitoring part.

8. A method for monitoring bridge deformation during bridge construction as claimed in claim 7, characterized in that: The initial vibration signal is re-decomposed using the modified initial decomposition interval scale to obtain the real vibration signal, including: re-decomposing the initial vibration signal using the modified initial decomposition interval scale to obtain all component signals, sorting all component signals from small to large according to the variance of the amplitudes of the component signals, selecting several component signals with small variance for reconstruction, and obtaining the real vibration signal.

9. The method for monitoring bridge deformation during bridge construction as claimed in claim 1, characterized in that: The health status of all connection structures in the main part of the bridge is monitored in real time based on the real vibration signal, including: monitoring the amplitude of the real vibration signal based on each monitoring part, setting a judgment threshold, and if the amplitude exceeds the judgment threshold, the monitoring part is abnormal.

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