Dynamic monitoring method and system for service condition of bridge pier

Abstract

The invention provides a dynamic monitoring method and system for the service condition of a bridge pier, and relates to the technical field of bridge detection. The monitoring method comprises the following steps: acquiring first acceleration sensing time sequence data and second acceleration sensing time sequence data of a to-be-detected pier; performing data preprocessing according to the first acceleration sensing time sequence data and the second acceleration sensing time sequence data to obtain first acceleration preprocessing data and second acceleration preprocessing data; generating a cross-correlation function according to the first acceleration preprocessing data and the second acceleration preprocessing data; determining time offset data based on the cross-correlation function; performing offset processing on the first acceleration preprocessing data and the second acceleration preprocessing data according to the time offset data to obtain first acceleration offset data and second acceleration offset processing data; and obtaining a health condition evaluation result of the to-be-detected pier based on the first acceleration offset data and the second acceleration offset processing data.

Description

Technical Field

[0001] The present application relates to the technical field of bridge detection, and in particular to a method and system for dynamic monitoring of the service status of bridge piers. Background Art

[0002] With the rapid development of highways and high-speed railways, a large number of elevated bridges have been built in various places. The safety of the bridge substructure (bridge piers) is the top priority in bridge technology; therefore, monitoring the health of the built bridge is a necessary measure to ensure the safety and stability of the bridge. Bridge piers are at risk of collapse due to impact, scouring and other factors, endangering the safety and durability of the bridge.

[0003] Generally, bridge piers are the weakest part of small and medium span bridges. Most non-major bridges require low-cost, automatic observation and monitoring methods to ensure the safety of the bridge substructure. In the prior art, patent document CN115828393B discloses a bridge information management method, system, electronic equipment and medium. Based on the structural parameters of the corrugated steel web bridge, including bridge elevation data, bridge material, prestressed steel bundle data, channel friction data and bridge temperature data, an initial finite element model is established to determine the simulated stress data group of the corrugated steel web bridge. According to the difference between the simulated stress data and the corresponding measured stress data, the initial finite element model is corrected to obtain an optimized finite element model, so that the optimized finite element model is close to the actual bridge condition and the accuracy of the further evaluation data is guaranteed. According to the optimized finite element model and the preset bridge load-bearing early warning model, the corrugated steel web bridge is warned and damaged to obtain an early warning evaluation result.

[0004] However, bridge piers are usually bulky and have weak responses, and the monitoring methods in the existing technology are difficult to implement at low cost. Moreover, the monitoring methods in the existing technology require modeling and complex modal analysis, and the number of sensors is large, making it difficult to reduce monitoring costs. In addition, there are problems such as untimely feedback of monitoring results and difficulty in achieving vehicle warnings. Summary of the invention

[0005] The purpose of this application is to provide a method, system, electronic device and computer-readable storage medium for dynamic monitoring of the service condition of bridge piers, which can achieve the technical effect of reducing bridge inspection costs and improving bridge inspection efficiency.

[0006] In a first aspect, the present application provides a method for dynamic monitoring of the service condition of a bridge pier, comprising:

[0007] Acquire first acceleration sensor time series data and second acceleration sensor time series data of a bridge pier to be detected, wherein the bridge pier to be detected is provided with a first acceleration sensor and a second acceleration sensor at different positions respectively;

[0008] Performing data preprocessing according to the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data;

[0009] generating a cross-correlation function according to the first acceleration pre-processed data and the second acceleration pre-processed data;

[0010] determining time offset data based on the cross-correlation function;

[0011] Performing offset processing on the first acceleration preprocessed data and the second acceleration preprocessed data according to the time offset data to obtain first acceleration offset data and second acceleration offset processed data;

[0012] A health status assessment result of the bridge pier to be inspected is obtained based on the first acceleration offset data and the second acceleration offset processing data.

[0013] In the above implementation process, the dynamic monitoring method for the service condition of the bridge piers is provided with a first acceleration sensor and a second acceleration sensor at different positions of the bridge pier to be detected, and the first acceleration sensor time series data and the second acceleration sensor time series data monitored by the two acceleration sensors are obtained for processing, and the time offset data is determined based on the cross-correlation function. According to the first acceleration offset data and the second acceleration offset processed data after the offset processing, the health condition of the bridge can finally be monitored and evaluated, and the health condition evaluation result of the bridge pier to be detected can be obtained; therefore, the dynamic monitoring method for the service condition of the bridge piers only needs to set two acceleration sensors on the bridge piers to be detected, and the health condition of the bridge piers can be monitored at a low cost, which can achieve the technical effect of reducing the cost of bridge detection and improving the efficiency of bridge detection.

[0014] Further, the step of performing data preprocessing according to the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data includes:

[0015] De-averaging is performed on the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data.

[0016] In the above implementation process, by performing de-averaging processing on the first acceleration sensor time series data and the second acceleration sensor time series data, the influence of low-frequency components on the phase difference calculation can be effectively reduced, thereby improving the accuracy of the health status assessment results of the bridge pier to be tested.

[0017] Further, in the step of generating a cross-correlation function according to the first acceleration preprocessing data and the second acceleration preprocessing data, the cross-correlation function is:

[0018]

[0019] Among them, R xy (τ) represents the cross-correlation function, τ represents the delay time, x(t) represents the first acceleration preprocessing data, y(t) represents the second acceleration preprocessing data, N represents the total number of x(t) or x(t) data, and t represents the time series.

[0020] Further, the step of determining the time offset data based on the cross-correlation function comprises:

[0021] Performing maximum value calculation based on the cross-correlation function to obtain maximum delay time data corresponding to when the cross-correlation function is at the maximum value;

[0022] Determine phase difference data based on the maximum delay time data;

[0023] Time offset data is determined based on the phase difference data.

[0024] Furthermore, the step of obtaining a health status assessment result of the bridge pier to be inspected based on the first acceleration offset data and the second acceleration offset processing data includes:

[0025] Performing ratio processing based on the first acceleration offset data and the second acceleration offset processing data to obtain ratio time series data;

[0026] A significance statistical test is performed based on a preset ratio threshold and the ratio time series data to obtain a health status assessment result of the bridge pier to be tested.

[0027] Furthermore, before the step of performing data preprocessing according to the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data, the method further includes:

[0028] Performing maximum-minimum processing on the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first difference data and second difference data;

[0029] If the first difference data or the second difference data is greater than a preset difference threshold, a step of performing data preprocessing according to the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data is performed;

[0030] If the first difference data and the second difference data are both smaller than or equal to a preset difference threshold, a health status assessment result of the bridge pier to be inspected is obtained based on the first difference data and the second difference data.

[0031] In the above implementation process, only when the difference between the maximum value and the minimum value of a certain sensor signal exceeds the preset difference threshold, the health status of the bridge is evaluated based on the first acceleration sensor time series data and the second acceleration sensor time series data; if the difference between the maximum value and the minimum value of the sensor signal does not exceed the preset difference threshold, it means that the health status of the pier to be detected is good, and the health status evaluation result of the pier to be detected can be directly obtained based on the first difference data and the second difference data, that is, the health status evaluation result is judged to be good.

[0032] Further, after the step of obtaining a health status assessment result of the bridge pier to be inspected based on the first acceleration offset data and the second acceleration offset processing data, the method further includes:

[0033] generating an alarm message according to the health status assessment result;

[0034] The alarm information is transmitted to the sound and light alarm device, and the sound and light alarm device issues an alarm and reminds passing vehicles to slow down or stop according to the alarm information.

[0035] In a second aspect, the present application provides a dynamic monitoring system for the service status of a bridge pier, comprising:

[0036] An acquisition module, used for acquiring first acceleration sensing time series data and second acceleration sensing time series data of a bridge pier to be detected, wherein the bridge pier to be detected is provided with a first acceleration sensor and a second acceleration sensor at different positions respectively;

[0037] A preprocessing module, used for performing data preprocessing according to the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data;

[0038] A cross-correlation module, configured to generate a cross-correlation function according to the first acceleration pre-processed data and the second acceleration pre-processed data;

[0039] an offset module, configured to determine time offset data based on the cross-correlation function;

[0040] an offset processing module, configured to perform offset processing on the first acceleration preprocessing data and the second acceleration preprocessing data according to the time offset data, so as to obtain first acceleration offset data and second acceleration offset processing data;

[0041] An evaluation module is used to obtain a health status evaluation result of the bridge pier to be detected based on the first acceleration offset data and the second acceleration offset processing data.

[0042] Furthermore, the preprocessing module is specifically used for:

[0043] De-averaging is performed on the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data.

[0044] Furthermore, the cross-correlation module is specifically used for:

[0045] Performing maximum value calculation based on the cross-correlation function to obtain maximum delay time data corresponding to when the cross-correlation function is at the maximum value;

[0046] Determine phase difference data based on the maximum delay time data;

[0047] Time offset data is determined based on the phase difference data.

[0048] Furthermore, the evaluation module is specifically used for:

[0049] Performing ratio processing based on the first acceleration offset data and the second acceleration offset processing data to obtain ratio time series data;

[0050] A significance statistical test is performed based on a preset ratio threshold and the ratio time series data to obtain a health status assessment result of the bridge pier to be tested.

[0051] Furthermore, the dynamic monitoring system for the service condition of the bridge pier further comprises a difference module, and the difference module is specifically used for:

[0052] Performing maximum-minimum processing on the first acceleration sensing time series data and the second acceleration sensing time series data to obtain difference data;

[0053] If the difference data is greater than a preset difference threshold, a step of performing data preprocessing according to the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data is performed;

[0054] If the difference data is less than or equal to a preset difference threshold, a health status assessment result of the bridge pier to be inspected is obtained based on the difference data.

[0055] In a third aspect, the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method described in any one of the first aspects when executing the computer program.

[0056] In a fourth aspect, the present application provides a computer-readable storage medium, on which instructions are stored. When the instructions are executed on a computer, the computer executes the method as described in any one of the first aspects.

[0057] In a fifth aspect, the present application provides a computer program product, which, when running on a computer, enables the computer to execute the method as described in any one of the first aspects.

[0058] Other features and advantages disclosed in the present application will be described in the following description, or some features and advantages can be inferred or determined without doubt from the description, or can be learned by implementing the above-mentioned technology disclosed in the present application.

[0059] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0061] Figure 1 A schematic diagram of the structure of a bridge provided in an embodiment of the present application;

[0062] Figure 2 A schematic flow chart of a method for dynamic monitoring of the service condition of a bridge pier provided in an embodiment of the present application;

[0063] Figure 3 A schematic flow chart of another method for dynamic monitoring of the service condition of a bridge pier provided in an embodiment of the present application;

[0064] Figure 4 A structural block diagram of a dynamic monitoring system for the service status of a bridge pier provided in an embodiment of the present application;

[0065] Figure 5 A structural block diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0066] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0067] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0068] The embodiments of the present application provide a method, system, electronic device and computer-readable storage medium for dynamic monitoring of the service condition of bridge piers, which can be applied to the process of monitoring the health status of bridge piers; the method for dynamic monitoring of the service condition of bridge piers respectively sets a first acceleration sensor and a second acceleration sensor at different positions of the bridge pier to be detected, obtains the first acceleration sensing time series data and the second acceleration sensing time series data monitored by the two acceleration sensors for processing, determines the time offset data based on the cross-correlation function, and finally monitors and evaluates the health status of the bridge according to the first acceleration offset data and the second acceleration offset processed data after the offset processing, and obtains the health status evaluation result of the bridge pier to be detected; thus, the method for dynamic monitoring of the service condition of bridge piers only needs to set two acceleration sensors on the bridge pier to be detected, can monitor the health status of the bridge pier at a low cost, and can achieve the technical effect of reducing the cost of bridge detection and improving the efficiency of bridge detection.

[0069] See also Figure 1 , Figure 1 A schematic diagram of the structure of a bridge provided in an embodiment of the present application; Figure 1 As shown, the bridge includes a bridge deck 10 and a plurality of bridge piers 11. The bottoms of the plurality of bridge piers 11 are installed on a riverbed 20, and the bridge deck 10 is supported by the plurality of bridge piers 11. One of the bridge piers 11 is used as a bridge pier to be detected, and a first acceleration sensor 31 and a second acceleration sensor 32 are installed. Vibration information of the bridge pier to be detected is monitored by the first acceleration sensor 31 and the second acceleration sensor 32.

[0070] Optionally, two acceleration sensors can be arranged on the bridge piers that are most susceptible to scouring. The sensors are arranged on the opposite side of the water flow to avoid direct scouring by the water flow.

[0071] For example, after the pier is scoured, the mechanical state changes, the vibration of the pier intensifies, and the lower part vibrates significantly; the information processing device 33 collects data from the acceleration sensors (the first acceleration sensor 31 and the second acceleration sensor 32) at intervals, and by analyzing and processing the data from the acceleration sensors, it can intelligently identify whether the pier has the risk of excessive scour;

[0072] In some implementations, the first acceleration sensor 31 and the second acceleration sensor 32 are arranged at two third points of the bridge pier to be detected; wherein the third points refer to one third of the length of the bridge pier to be detected.

[0073] Exemplarily, the sensor data collected by the first acceleration sensor 31 and the second acceleration sensor 32 are transmitted to the information processing device 33 by wired or wireless means; after the information processing device 33 processes the information, it can feed back the information to the monitoring system of the bridge;

[0074] Optionally, after the early warning conditions are met, the information is directly sent to a traffic safety information display system near the bridge, which can be used to warn vehicles to pay attention to safety.

[0075] Optionally, the acceleration sensor provided in the embodiment of the present application is sensitive to low frequencies, and the high-frequency signals caused by the impact of river water do not contribute much to the signal amplitude of the sensor; in addition, the acceleration sensor adopts a waterproof layout and is buried on the downstream side of the bridge pier on the water-facing surface of the bridge to reduce direct scouring by the water flow.

[0076] Optionally, a single bridge can have multiple piers equipped with accelerometers. If only one pier is equipped with an accelerometer, that pier can be the one with the greatest water depth. Figure 2 , Figure 2 A schematic flow chart of a method for dynamic monitoring of the service condition of a bridge pier provided in an embodiment of the present application, wherein the method for dynamic monitoring of the service condition of a bridge pier comprises the following steps:

[0077] S100: Acquire first acceleration sensor time series data and second acceleration sensor time series data of a bridge pier to be detected, wherein the bridge pier to be detected is provided with a first acceleration sensor and a second acceleration sensor at different positions respectively;

[0078] Exemplarily, the first acceleration sensor and the second acceleration sensor can collect signals at a preset frequency; in the embodiment of the present application, the sampling frequency of the first acceleration sensor and the second acceleration sensor is f s ;

[0079] S200: performing data preprocessing according to the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data;

[0080] Exemplarily, data preprocessing is performed on the first acceleration sensing time series data and the second acceleration sensing time series data to reduce the influence of low-frequency components on the phase difference calculation.

[0081] S300: generating a cross-correlation function according to the first acceleration preprocessing data and the second acceleration preprocessing data;

[0082] S400: Determine time offset data based on a cross-correlation function;

[0083] Exemplarily, the cross-correlation function may be used to represent the similarity between the first acceleration preprocessed data and the second acceleration preprocessed data at different delay times; thus, based on the similarity, the delay time corresponding to the maximum value of the cross-correlation function may be determined to determine the time offset data.

[0084] S500: performing offset processing on the first acceleration preprocessed data and the second acceleration preprocessed data according to the time offset data to obtain first acceleration offset data and second acceleration offset processed data;

[0085] S600: Obtaining a health status assessment result of the bridge pier to be inspected based on the first acceleration offset data and the second acceleration offset processing data.

[0086] In some embodiments, the method for dynamic monitoring of the service condition of bridge piers is provided with a first acceleration sensor and a second acceleration sensor at different positions of the bridge pier to be detected, and the first acceleration sensing time series data and the second acceleration sensing time series data monitored by the two acceleration sensors are obtained and processed, and the time offset data is determined based on the cross-correlation function. The health status of the bridge can finally be monitored and evaluated according to the first acceleration offset data and the second acceleration offset processed data after the offset processing, and the health status evaluation result of the bridge pier to be detected is obtained; thus, the method for dynamic monitoring of the service condition of bridge piers only needs to set two acceleration sensors on the bridge pier to be detected, and the health status of the bridge pier can be monitored at a low cost, which can achieve the technical effect of reducing the cost of bridge detection and improving the efficiency of bridge detection.

[0087] See also Figure 3 , Figure 3 A schematic flow chart of another method for dynamic monitoring of the service condition of a bridge pier provided in an embodiment of the present application.

[0088] Exemplarily, S200: performing data preprocessing according to the first acceleration sensing time series data and the second acceleration sensing time series data to obtain the first acceleration preprocessing data and the second acceleration preprocessing data, comprises:

[0089] S210: Performing a de-averaging process on the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data.

[0090] Exemplarily, by performing de-averaging processing on the first acceleration sensor time series data and the second acceleration sensor time series data, the influence of low-frequency components on the phase difference calculation can be effectively reduced, thereby improving the accuracy of the health status assessment result of the bridge pier to be tested.

[0091] Exemplarily, in the step of generating a cross-correlation function according to the first acceleration pre-processed data and the second acceleration pre-processed data, the cross-correlation function is:

[0092]

[0093] Among them, R xy (τ) represents the cross-correlation function, τ represents the delay time, x(t) represents the first acceleration preprocessing data, y(t) represents the second acceleration preprocessing data, N represents the total number of x(t) or x(t) data, and t represents the time series.

[0094] Exemplarily, S400: the step of determining time offset data based on the cross-correlation function includes:

[0095] S410: Calculate the maximum value based on the cross-correlation function to obtain the maximum delay time data corresponding to the cross-correlation function being at the maximum value;

[0096] S420: Determine phase difference data based on the maximum delay time data;

[0097] S430: Determine time offset data according to the phase difference data.

[0098] Exemplarily, S600: the step of obtaining a health status assessment result of the bridge pier to be inspected based on the first acceleration offset data and the second acceleration offset processing data includes:

[0099] S610: performing ratio processing based on the first acceleration offset data and the second acceleration offset processing data to obtain ratio time series data;

[0100] S620: Perform a statistical significance test based on a preset ratio threshold and ratio time series data to obtain a health status assessment result of the bridge pier to be tested.

[0101] Exemplarily, before the step of performing data preprocessing according to the first acceleration sensing time series data and the second acceleration sensing time series data in S200 to obtain the first acceleration preprocessing data and the second acceleration preprocessing data, the method further includes:

[0102] S110: performing maximum-minimum processing on the first acceleration sensor time series data and the second acceleration sensor time series data to obtain first difference data and second difference data;

[0103] S120: Determine whether the first difference data or the second difference data is greater than a preset difference threshold;

[0104] If the first difference data or the second difference data is greater than the preset difference threshold, executing S200: performing data preprocessing according to the first acceleration sensing time series data and the second acceleration sensing time series data to obtain the first acceleration preprocessing data and the second acceleration preprocessing data;

[0105] If both the first difference data and the second difference data are less than or equal to the preset difference threshold, S130 is executed: obtaining a health status assessment result of the bridge pier to be inspected based on the first difference data and the second difference data.

[0106] Exemplarily, only when the difference between the maximum value and the minimum value of a certain sensor signal exceeds the preset difference threshold, the health status of the bridge is assessed based on the first acceleration sensor time series data and the second acceleration sensor time series data; if the difference between the maximum value and the minimum value of the sensor signal does not exceed the preset difference threshold, it means that the health status of the pier to be detected is good, and the health status assessment result of the pier to be detected can be directly obtained based on the first difference data and the second difference data, that is, the health status assessment result is judged to be good.

[0107] In some embodiments, the maximum-minimum processing provided in the embodiments of the present application refers to identifying the difference between the maximum and minimum values ​​of the signal recorded in the first acceleration sensor time series data within a certain observation period, so as to obtain the first difference data corresponding to the first acceleration sensor time series data; similarly, the second difference data corresponding to the second acceleration sensor time series data can be obtained.

[0108] Exemplarily, after the step of obtaining a health status assessment result of the bridge pier to be inspected based on the first acceleration offset data and the second acceleration offset processing data, the method further includes:

[0109] Generate alarm information based on health status assessment results;

[0110] The alarm information is transmitted to the sound and light alarm device, which sounds an alarm and reminds passing vehicles to slow down or stop according to the alarm information.

[0111] In some implementation scenarios, combined with Figures 1 to 3 The dynamic monitoring method for the service condition of the bridge pier shown in the figure has the following specific implementation steps:

[0112] 1. Data collection of two signal sensors: the first acceleration sensor and the second acceleration sensor, the recorded signals are recorded as x a (t), y a(t); the signal processing device uses the time range T as the observation period, and the number of signal samples recorded by each signal sensor in one observation period T is N;

[0113] The signal processing device keeps monitoring the two signal sensors, and identifies the difference between the maximum value and the minimum value of the recorded signal within a certain observation period T; when the difference between the maximum value and the minimum value of the signal of a certain signal sensor exceeds a preset difference threshold, the signal processing device activates the vibration difference recognition module, thereby evaluating the health status of the bridge based on the first acceleration sensor time series data and the second acceleration sensor time series data;

[0114] Optionally, the signals within the activated observation period are transmitted back to the monitoring system of the bridge for storage;

[0115] 2. Data preprocessing:

[0116] In order to reduce the influence of low-frequency components on the phase difference calculation, the two signals x can be a (t), y a (t) Perform mean removal processing:

[0117] x a (t)-x'→x(t);

[0118] y a (t)-y'→y(t);

[0119] Where x' represents x a (t), y' represents the average value of y a (t); thereby obtaining the first acceleration preprocessing data x(t) and the second acceleration preprocessing data y(t);

[0120] 3. Calculate the cross-correlation function:

[0121] Cross-correlation function R xy (τ) represents the similarity between signals x(t) and y(t) at different delay times τ. The calculation formula is as follows:

[0122]

[0123] Among them, R xy (τ) represents the cross-correlation function, τ represents the delay time, x(t) represents the first acceleration preprocessing data, y(t) represents the second acceleration preprocessing data, N represents the total number of data of x(t) or x(t), and t represents the time series;

[0124] Optionally, in practical applications, FFT (Fast Fourier Transform) can be used to efficiently calculate the cross-correlation function R xy(τ);

[0125] 4. Find the maximum cross-correlation:

[0126] Find the cross-correlation function R xy The maximum value of (τ) corresponds to the delay time τ max ;

[0127]

[0128] 5. Calculate the phase difference:

[0129] Phase Difference The maximum cross-correlation function R xy (τ) corresponds to the delay time τ max It is calculated that if the sampling frequency of the signal is f s , then the phase difference for:

[0130]

[0131] 6. Determine the time offset:

[0132] According to the calculated phase difference The time shift τ required for the signal can be determined p ;

[0133] Then the number of samples that the signal needs to shift is: τ p ×f s , τ p A positive value indicates that the y(t) signal is shifted forward, τ p A negative value indicates that the signal y(t) is shifted backward;

[0134] After the signal y(t) is offset, the data of the time overlap of the two signals x(t) and y(t) are extracted and recorded as x and m (t), y m (t), p(t) = |x m (t)| / |y m (t)|;

[0135] 7. Monitoring and evaluation of health status:

[0136] Based on p(t) = |x m (t)| / |y m (t)|Monitor and evaluate the health status of the bridge piers to be inspected;

[0137] When m (t)| has a value less than 5% y m (t) maxWhen the numerical calculation deviation is large, the ratio time series data p(t) obtained by the above formula is discarded; where y m (t) max Represents y m The maximum value in (t);

[0138] Set the threshold of the ratio time series data p(t) to G;

[0139] A statistical test is performed on the hypothesis that the contrast value time series data p(t) is significantly greater than G. At the significance level α = 0.05, if the hypothesis test passes, it indicates that the lower part of the pier is vibrating heavily and there is a risk of overturning, and the system alarms. If the hypothesis test fails, the health status is assessed to be good and the system does not respond.

[0140] At the same time, the system records the time series of this cycle and its calculation result p(t) to facilitate tracking changes in the health status of the bridge.

[0141] See also Figure 4 , Figure 4 This is a structural block diagram of a dynamic monitoring system for the service condition of a bridge pier provided in an embodiment of the present application. The dynamic monitoring system for the service condition of a bridge pier includes:

[0142] The acquisition module 100 is used to acquire first acceleration sensor time series data and second acceleration sensor time series data of the bridge pier to be detected, wherein the bridge pier to be detected is respectively provided with a first acceleration sensor and a second acceleration sensor at different positions;

[0143] A preprocessing module 200, configured to perform data preprocessing according to the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data;

[0144] A cross-correlation module 300, configured to generate a cross-correlation function according to the first acceleration pre-processed data and the second acceleration pre-processed data;

[0145] An offset module 400 for determining time offset data based on a cross-correlation function;

[0146] An offset processing module 500 is used to perform offset processing on the first acceleration preprocessing data and the second acceleration preprocessing data according to the time offset data to obtain first acceleration offset data and second acceleration offset processing data;

[0147] The evaluation module 600 is used to obtain a health status evaluation result of the bridge pier to be inspected based on the first acceleration offset data and the second acceleration offset processing data.

[0148] Exemplarily, the preprocessing module 200 is specifically used for:

[0149] De-averaging is performed on the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data.

[0150] Exemplarily, the cross-correlation module 300 is specifically used for:

[0151] Perform maximum value calculation based on the cross-correlation function to obtain maximum delay time data corresponding to when the cross-correlation function is at its maximum value;

[0152] determining phase difference data based on the maximum delay time data;

[0153] The time offset data is determined based on the phase difference data.

[0154] Exemplarily, the evaluation module 600 is specifically used for:

[0155] Performing ratio processing based on the first acceleration offset data and the second acceleration offset processing data to obtain ratio time series data;

[0156] A significance statistical test is performed based on the preset ratio threshold and ratio time series data to obtain the health status assessment results of the bridge pier to be tested.

[0157] Exemplarily, the dynamic monitoring system for the service condition of a bridge pier further includes a difference module, which is specifically used for:

[0158] Performing maximum-minimum processing on the first acceleration sensor time series data and the second acceleration sensor time series data to obtain difference data;

[0159] If the difference data is greater than a preset difference threshold, a step of performing data preprocessing according to the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data is performed;

[0160] If the difference data is less than or equal to a preset difference threshold, an assessment result of the health status of the bridge pier to be inspected is obtained based on the difference data.

[0161] It should be noted that the dynamic monitoring system for the service condition of the bridge pier provided in the embodiment of the present application is Figures 1 to 3 The method embodiments shown correspond to each other and will not be described again here to avoid repetition.

[0162] This application also provides an electronic device, see Figure 5 , Figure 5A block diagram of an electronic device provided in an embodiment of the present application. The electronic device may include a processor 510, a communication interface 520, a memory 530, and at least one communication bus 540. The communication bus 540 is used to realize direct connection and communication between these components. The communication interface 520 of the electronic device in the embodiment of the present application is used to communicate signaling or data with other node devices. The processor 510 may be an integrated circuit chip with signal processing capabilities.

[0163] The processor 510 mentioned above can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor 510 can also be any conventional processor, etc.

[0164] The memory 530 may be, but is not limited to, a random access memory (RAM), a read only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electric erasable programmable read-only memory (EEPROM), etc. The memory 530 stores computer-readable instructions. When the computer-readable instructions are executed by the processor 510, the electronic device can execute the above-mentioned Figures 1 to 3 The method embodiment involves various steps.

[0165] Optionally, the electronic device may further include a storage controller and an input / output unit.

[0166] The memory 530, storage controller, processor 510, peripheral interface, input and output unit components are directly or indirectly electrically connected to each other to achieve data transmission or interaction. For example, these components can be electrically connected to each other via one or more communication buses 540. The processor 510 is used to execute executable modules stored in the memory 530, such as software function modules or computer programs included in the electronic device.

[0167] The input and output unit is used to provide users with the task creation and to create a start optional time period or preset execution time for the task to realize the interaction between the user and the server. The input and output unit can be, but is not limited to, a mouse and a keyboard.

[0168] Understandably, Figure 5 The structure shown is for illustration only, and the electronic device may also include Figure 5 More or fewer components as shown, or with Figure 5 Different configurations are shown. Figure 5 Each component shown in the figure can be implemented by hardware, software or a combination thereof.

[0169] An embodiment of the present application further provides a storage medium having instructions stored thereon. When the instructions are run on a computer, the computer program is executed by a processor to implement the method described in the method embodiment. To avoid repetition, the method will not be described here.

[0170] The present application also provides a computer program product, which, when executed on a computer, enables the computer to execute the method described in the method embodiment.

[0171] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0172] In addition, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0173] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0174] The above description is only an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application. It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings.

[0175] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0176] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

Claims

1. A method for dynamic monitoring of the service condition of a bridge pier, characterized in that: include: Acquire first acceleration sensor time series data and second acceleration sensor time series data of a bridge pier to be detected, wherein the bridge pier to be detected is provided with a first acceleration sensor and a second acceleration sensor at different positions respectively; Performing data preprocessing according to the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data; generating a cross-correlation function according to the first acceleration pre-processed data and the second acceleration pre-processed data; determining time offset data based on the cross-correlation function; Performing offset processing on the first acceleration preprocessed data and the second acceleration preprocessed data according to the time offset data to obtain first acceleration offset data and second acceleration offset processed data; A health status assessment result of the bridge pier to be inspected is obtained based on the first acceleration offset data and the second acceleration offset processing data.

2. The method for dynamic monitoring of the service condition of a bridge pier according to claim 1, characterized in that: The step of performing data preprocessing according to the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data comprises: De-averaging is performed on the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data.

3. The method for dynamic monitoring of the service condition of a bridge pier according to claim 1 or 2, characterized in that: In the step of generating a cross-correlation function according to the first acceleration pre-processed data and the second acceleration pre-processed data, the cross-correlation function is: Among them, R xy (τ) represents the cross-correlation function, τ represents the delay time, x(t) represents the first acceleration preprocessing data, y(t) represents the second acceleration preprocessing data, N represents the total number of x(t) or x(t) data, and t represents the time series.

4. The method for dynamic monitoring of the service condition of a bridge pier according to claim 1, characterized in that: The step of determining time offset data based on the cross-correlation function comprises: Performing maximum value calculation based on the cross-correlation function to obtain maximum delay time data corresponding to when the cross-correlation function is at the maximum value; Determine phase difference data based on the maximum delay time data; Time offset data is determined based on the phase difference data.

5. The method for dynamic monitoring of the service condition of a bridge pier according to claim 1 or 4, characterized in that: The step of obtaining a health status assessment result of the bridge pier to be inspected based on the first acceleration offset data and the second acceleration offset processing data comprises: Performing ratio processing based on the first acceleration offset data and the second acceleration offset processing data to obtain ratio time series data; A significance statistical test is performed based on a preset ratio threshold and the ratio time series data to obtain a health status assessment result of the bridge pier to be tested.

6. The method for dynamic monitoring of the service condition of a bridge pier according to claim 1, characterized in that: Before the step of performing data preprocessing according to the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data, the method further includes: Performing maximum-minimum processing on the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first difference data and second difference data; If the first difference data or the second difference data is greater than a preset difference threshold, a step of performing data preprocessing according to the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data is performed; If the first difference data and the second difference data are both smaller than or equal to a preset difference threshold, a health status assessment result of the bridge pier to be inspected is obtained based on the first difference data and the second difference data.

7. The method for dynamic monitoring of the service condition of a bridge pier according to claim 1, characterized in that: After the step of obtaining a health status assessment result of the bridge pier to be inspected based on the first acceleration offset data and the second acceleration offset processing data, the method further includes: generating an alarm message according to the health status assessment result; The alarm information is transmitted to the sound and light alarm device, and the sound and light alarm device issues an alarm and reminds passing vehicles to slow down or stop according to the alarm information.

8. A dynamic monitoring system for the service condition of a bridge pier, characterized in that: include: An acquisition module, used for acquiring first acceleration sensing time series data and second acceleration sensing time series data of a bridge pier to be detected, wherein the bridge pier to be detected is provided with a first acceleration sensor and a second acceleration sensor at different positions respectively; A preprocessing module, used for performing data preprocessing according to the first acceleration sensing time series data and the second acceleration sensing time series data to obtain first acceleration preprocessing data and second acceleration preprocessing data; A cross-correlation module, configured to generate a cross-correlation function according to the first acceleration pre-processed data and the second acceleration pre-processed data; an offset module, configured to determine time offset data based on the cross-correlation function; an offset processing module, configured to perform offset processing on the first acceleration preprocessing data and the second acceleration preprocessing data according to the time offset data, so as to obtain first acceleration offset data and second acceleration offset processing data; An evaluation module is used to obtain a health status evaluation result of the bridge pier to be detected based on the first acceleration offset data and the second acceleration offset processing data.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the method for dynamic monitoring of the service condition of a bridge pier as claimed in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed on a computer, the computer is enabled to execute the method for dynamic monitoring of the service condition of a bridge pier according to any one of claims 1 to 7.

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