A bridge prestress loss measurement system based on acoustic emission technology

Abstract

The invention relates to the technical field of bridge detection, and specifically discloses a bridge prestress loss measurement system based on acoustic emission technology, comprising an emission signal acquisition module, a sound source positioning module, an environment monitoring module, a prestress loss measurement module and a data analysis module; the acoustic emission signal acquisition module collects acoustic emission signals in the process of bridge prestress loss; the sound source positioning module is responsible for helping to accurately locate the specific location where the prestress loss occurs; the environment monitoring module collects and detects environmental data of the bridge; the prestress loss measurement module measures the prestress loss of the bridge; and the data analysis module analyzes the environmental data acquired by the sensor together with the acoustic emission signal.

Description

Technical Field

[0001] The present invention relates to the technical field of bridge detection, and more specifically, to a bridge prestress loss measurement system based on acoustic emission technology. Background Art

[0002] At present, the main methods for measuring prestress loss of bridges include tension test, reaction plate method and strain gauge method. These traditional methods can reflect the prestress loss of bridges to a certain extent. The tension test measures the degree of prestress loss by directly tensioning the prestressed steel bars. Although this method is relatively direct, it is usually only used in the initial construction or individual inspections due to its cumbersome operation and the need for destructive intervention in the bridge structure, and cannot achieve continuous monitoring.

[0003] The reaction plate method tests the prestress of the bridge by arranging reaction plates. It is suitable for the measurement of large-span bridges and can provide relatively accurate test data at key parts of the bridge structure. However, this method also has certain limitations: on the one hand, it requires a lot of manual operations by on-site construction workers, and the construction process is complicated and time-consuming; on the other hand, the test can only be carried out at a specific time point, and it is impossible to monitor the long-term changes of the bridge in real time;

[0004] The strain gauge method is a commonly used measurement method. By installing strain gauges on the prestressed steel bars of the bridge, the strain changes generated by the steel bars during tensioning and use are measured to deduce the magnitude of the prestress loss. Although this method can perform stress analysis on local areas, its measurement results are greatly affected by environmental factors, and it is difficult to accurately obtain long-term changes;

[0005] The above methods generally have problems such as insufficient measurement accuracy and delayed data acquisition. In addition, existing technologies often require a large number of on-site staff to conduct long-term monitoring, which increases project costs and construction periods. In addition, due to human factors and equipment failures, errors or data delays are prone to occur during the monitoring process. Therefore, how to improve the measurement accuracy of bridge prestress loss and realize real-time and rapid detection has become a key technical issue that needs to be urgently solved in the current field of bridge health monitoring. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art, the present invention provides a bridge prestress loss measurement system based on acoustic emission technology, which is achieved by arranging acoustic emission sensors at key positions of the bridge, collecting acoustic emission signals, and establishing a prestress loss measurement model, so as to realize real-time and rapid measurement of the bridge prestress loss. At the same time, considering that environmental parameters will affect the measurement results, the acoustic emission signals are combined with the environmental parameters for analysis, and the prestress loss measurement error caused by the environmental parameters is corrected, thereby improving the measurement accuracy of the bridge prestress loss, so as to solve the problems raised in the above-mentioned background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A bridge prestress loss measurement system based on acoustic emission technology comprises an acoustic emission signal acquisition module, a sound source positioning module, an environmental monitoring module, a prestress loss measurement module and a data analysis module; the acoustic emission signal acquisition module acquires acoustic emission signals in the process of bridge prestress loss; the sound source positioning module captures acoustic emission signals at different positions and angles through acoustic emission sensors arranged at the span of the bridge, and uses the acoustic emission signals acquired by the acoustic emission signal acquisition module to establish a sound source position model to locate the specific position where the prestress loss occurs; the environmental monitoring module acquires and detects environmental data of the bridge; the prestress loss measurement module establishes a prestress loss measurement model based on the information of the signal strength, frequency and duration in the acoustic emission signal, and measures the prestress loss of the bridge, and the formula of the prestress loss measurement model is:

[0009] ,

[0010] Where: is the measured value of bridge prestress loss, The number of acoustic emission sensors to obtain acoustic emission signals, For the The acoustic emission signal intensity collected by the acoustic emission sensor, For the The frequency of the acoustic emission signal collected by the acoustic emission sensor, is the standard frequency response of the bridge structure in the case of prestress loss, is the coefficient of acoustic emission signal attenuation, For the The duration of an acoustic emission signal, is the standard duration of the acoustic emission signal in the case of prestress loss, is the coefficient of bridge structure damage degree, is a coefficient related to the time delay in the propagation of the acoustic emission signal.

[0011] The data analysis module combines environmental data and acoustic emission signal data to establish a correction model to correct the prestress loss measurement error caused by environmental data.

[0012] As a further solution of the present invention, the acoustic emission signal acquisition module collects the acoustic emission signal during the prestress loss process of the bridge, including the following specific contents:

[0013] The acoustic emission signal acquisition module is responsible for real-time acquisition of the acoustic emission signals of the bridge during the prestress loss process. The acoustic emission signals refer to high-frequency elastic waves or sound waves generated when the material is subjected to external stress or internal changes. In the bridge structure, especially during the prestress loss process, a series of acoustic emission phenomena will be generated due to the stress changes, cracking, slippage, etc. of the steel strands or concrete;

[0014] The acoustic emission signal acquisition module uses an acoustic emission sensor, which is arranged at the span of the bridge to monitor the acoustic emission signal generated by the bridge in real time during the stress process. The acoustic emission sensor is an ultrasonic sensor that can detect tiny sound wave changes and convert the signal into an electrical signal.

[0015] As a further solution of the present invention, the sound source localization module is responsible for locating the specific location where the prestress loss occurs, including the following specific contents:

[0016] By arranging the acoustic emission sensors at the span of the bridge, the sound source positioning module can capture the acoustic emission signals at different positions and angles. Using the signals collected by the acoustic emission sensors, the sound source positioning module establishes a sound source position model to locate the specific position where the prestress loss occurs. The formula of the sound source position model is:

[0017] ,

[0018] Where: For sound source The three-dimensional spatial coordinates of the prestress loss, i.e., the specific location where the prestress loss occurs. is the sound source in three-dimensional space The horizontal axis coordinate of is the sound source in three-dimensional space The vertical axis coordinate, is the sound source in three-dimensional space The depth coordinate of is the number of acoustic emission sensors, For the first acoustic emission sensor to the sound source The distance For the AE sensor to the sound source The distance is the speed of sound waves in air, For the The time difference between the first acoustic emission sensor receiving the signal and the time difference between the first acoustic emission sensor receiving the signal.

[0019] The sound source localization module converts the three-dimensional spatial coordinates of the specific location where the prestress loss occurs into intuitive graphics, helping engineers and maintenance personnel to better understand the health of the bridge structure. The three-dimensional coordinates of the sound source position are presented through three-dimensional modeling software, and the location of the sound source can be directly marked on the structural diagram of the bridge.

[0020] As a further solution of the present invention, the environmental monitoring module collects and detects the environmental data of the bridge, including the following specific contents: the health status of the bridge is not only affected by the structure itself, but also by the external environmental parameters, such as temperature, pressure, wind speed and precipitation. The environmental parameters will directly or indirectly affect the propagation characteristics of the acoustic emission signal and the accuracy of the measurement. In order to ensure the accuracy and reliability of the measurement of the prestress loss of the bridge, the environmental factors are monitored and considered in real time. The effect of temperature on the propagation of sound waves is the most significant, especially in the bridge structure with a larger span. The increase in temperature will cause the expansion of the material, thereby affecting the propagation speed of the sound wave. For this reason, the temperature sensor is arranged in the span of the bridge to obtain the bridge in real time. The temperature data of the surface; the air pressure mainly affects the stress and material deformation behavior of the bridge. The change of air pressure is related to the structural vibration of the bridge or the formation of microcracks. The pressure sensor arranged at the span of the bridge is used to obtain the stress data of the bridge in real time; when the wind speed is high, the vibration in the air will produce a certain background noise, which will interfere with the signal collection of the acoustic emission sensor. Therefore, it is necessary to obtain the wind speed data through the wind speed sensor installed on the bridge deck; the precipitation will affect the wetness of the bridge surface and the stress distribution of the bridge, especially in heavy rain. The action of water flow will have a local impact on the prestressed steel strands of the bridge, changing its stress state. The precipitation is monitored in real time through the rainfall sensor installed upstream of the bridge.

[0021] As a further solution of the present invention, the data analysis module analyzes the environmental data obtained by the sensor together with the acoustic emission signal, including the following specific contents: due to the thermal expansion characteristics of the steel strands on the bridge, temperature changes will directly affect their stress state, resulting in changes in prestress loss. In winter or summer, especially when the temperature difference between day and night is large, temperature fluctuations will cause relative deformation between the steel strands and concrete, thereby affecting the structural stability of the bridge. The temperature sensor monitors the temperature changes of the anchor points of the prestressed steel strands of the bridge, the surface of the bridge, etc. in real time, and can provide environmental temperature information; the anchor points of the prestressed steel strands of the bridge, the span beams and the piers are under huge pressure loads. Changes in the external environment, such as fluctuations in atmospheric pressure, will affect the stress state of the bridge. Pressure sensors are installed at these key locations to monitor the pressure state of the bridge in real time, especially under high or low pressure weather conditions. The pressure data can Provide useful information about the stress distribution of the bridge, and the acoustic emission signal often varies with the change of the stress state; strong wind or storm weather has an important impact on the stress and vibration characteristics of the bridge structure. Changes in wind speed will cause the vibration of the bridge and cause the stress state of the prestressed steel strands to change, which in turn affects the propagation mode of the acoustic emission signal. When the bridge vibrates excessively under strong wind conditions, a pseudo acoustic emission signal will be generated. By coordinating with wind speed data, non-structural signals can be identified and excluded to ensure the accuracy of the measurement results; in the rainy season, precipitation will cause fluctuations in the surface temperature and humidity of the bridge, thereby affecting the stress state of the structure, especially the change in moisture in the concrete material. Changes in precipitation will cause local water accumulation in the structure, thereby affecting the propagation characteristics of sound waves in the bridge structure. For example, strong precipitation may cause slippery local areas, change the propagation path of sound waves, and generate unreal signals.

[0022] The data analysis module combines and analyzes the temperature data obtained by the temperature sensor, the pressure data obtained by the pressure sensor, the wind speed data obtained by the wind speed sensor, the precipitation data obtained by the rainfall sensor, and the acoustic emission signal data obtained by the acoustic emission sensor to establish a correction model to correct the prestress loss measurement error caused by the temperature data, pressure data, wind speed data, and precipitation data. The formula of the correction model is:

[0023] ,

[0024] Where: is the measured value of prestress loss after correction; is the prestress loss measurement value measured by acoustic emission signal; is the change in temperature data, satisfy ,in, is the current ambient temperature. is the average temperature value one month ago; is the correction coefficient corresponding to the ambient temperature, which indicates the influence of temperature data on the measurement error of prestress loss; is the change in pressure data, satisfy ,in, is the current ambient air pressure value, is the standard air pressure value; is the correction coefficient corresponding to pressure, which indicates the influence of pressure data on the measurement error of prestress loss; is the change in wind speed data, satisfy ,in, is the current wind speed, is the average wind speed one month ago; is the correction coefficient corresponding to the wind speed, which indicates the influence of wind speed data on the measurement error of prestress loss; is the change in precipitation data, satisfy ,in, is the current precipitation, is the average precipitation one month ago; is the correction coefficient corresponding to the precipitation, which indicates the influence of precipitation data on the measurement error of prestress loss.

[0025] As a further solution of the present invention, the correction coefficient corresponding to the ambient temperature The correction coefficient corresponding to the pressure is obtained by long-term measurement of the prestress loss of the bridge at different temperatures; Derived from the statistical effect of air pressure fluctuations on the internal stress of the bridge; the correction coefficient corresponding to the wind speed Adjust according to the interference degree of wind speed on the collection of acoustic emission signals; the correction coefficient corresponding to the precipitation The data analysis of the effects of precipitation on the slipperiness and stress state of bridges shows that, in bridge structures, temperature changes will affect the expansion and contraction of materials, while changes in air pressure will further affect the stress state of materials; changes in wind speed will bring about temperature changes, and strong winds will accelerate heat exchange, causing more dramatic changes in bridge surface temperature; an increase in wind speed will change the direction of precipitation, affecting the distribution of rainwater on the bridge, thereby changing the slipperiness of local areas, and further affecting the stress state of the bridge and the propagation characteristics of acoustic emission signals; low air pressure will affect the stress state of the bridge structure, and a drop in air pressure will cause local deformation of the bridge, while precipitation will change the humidity of the bridge material, further affecting the stress state; and Negatively correlated, and is positively correlated, and is positively correlated, and Negatively correlated.

[0026] As a further solution of the present invention, the sound source localization module is connected to the acoustic emission signal acquisition module, the environmental monitoring module is connected to the sound source localization module, the prestress loss measurement module is connected to the environmental monitoring module, and the data analysis module is connected to the prestress loss measurement module.

[0027] The technical effects and advantages of the bridge prestress loss measurement system based on acoustic emission technology of the present invention are as follows: combining the emission signal acquisition module, the sound source positioning module, the environmental monitoring module, the prestress loss measurement module and the data analysis module, it is possible to monitor the prestress loss of the bridge in real time and efficiently, and accurately locate the specific location where the loss occurs; by arranging acoustic emission sensors at key parts of the bridge, collecting acoustic emission signals, establishing a prestress loss measurement model, measuring the prestress loss of the bridge, and correcting the acoustic emission signals with temperature, pressure, wind speed and precipitation, eliminating the interference of the external environment on the measurement results, and ensuring the accuracy of the prestress loss measurement; in addition, the specific location of the prestress loss is converted into an intuitive three-dimensional coordinate graph through the sound source positioning module, which helps engineering personnel to clearly understand the health status of the bridge; compared with the traditional bridge prestress measurement method, the present invention has the advantages of no need for large-scale on-site construction, no need for destructive intervention, no need for long-term manual monitoring, etc., which greatly improves the measurement efficiency and accuracy, reduces maintenance costs, and improves the safety and service life of the bridge. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a schematic diagram of a sensor of a bridge prestress loss measurement system based on acoustic emission technology installed on a bridge span. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] The embodiment of the present invention provides a bridge prestress loss measurement system based on acoustic emission technology, comprising an acoustic emission signal acquisition module, a sound source positioning module, an environmental monitoring module, a prestress loss measurement module and a data analysis module; the acoustic emission signal acquisition module collects acoustic emission signals in the process of bridge prestress loss; the sound source positioning module is responsible for locating the specific location where the prestress loss occurs; the environmental monitoring module collects and detects environmental data of the bridge; the prestress loss measurement module measures the prestress loss of the bridge; and the data analysis module analyzes the environmental data obtained by the sensor together with the acoustic emission signal.

[0031] In this embodiment, see Figure 1 As shown in the schematic diagram, acoustic emission sensors are arranged at key parts of the bridge to collect acoustic emission signals in real time during the prestress loss process. The key parts include the bridge part, the anchor end and the vicinity of the pier. Environmental monitoring sensors are also included on the bridge, including: temperature sensor, wind speed sensor and rainfall sensor.

[0032] Furthermore, the acoustic emission signal acquisition module acquires the acoustic emission signals during the prestress loss process of the bridge, including the following specific contents: the acoustic emission signal acquisition module is responsible for real-time acquisition of the acoustic emission signals of the bridge during the prestress loss process, and the acoustic emission signals refer to the high-frequency elastic waves or sound waves generated by the material when it is subjected to external stress or internal changes. In the bridge structure, especially in the process of prestress loss, a series of acoustic emission phenomena will be generated due to the stress changes, cracking, slippage, etc. of the steel strands or concrete; the acoustic emission signal acquisition module uses an acoustic emission sensor, which is arranged in the span of the bridge to monitor the acoustic emission signals generated by the bridge during the stress process in real time. The acoustic emission sensor is an ultrasonic sensor that can detect tiny sound wave changes and convert the signal into an electrical signal.

[0033] Furthermore, the sound source localization module is responsible for locating the specific location where the prestress loss occurs, including the following specific contents: through the acoustic emission sensor arranged at the span of the bridge, the sound source localization module can capture the acoustic emission signals at different positions and angles, and use the signals collected by the acoustic emission sensor to establish a sound source location model to locate the specific location where the prestress loss occurs. The formula of the sound source location model is:

[0034] ,

[0035] Where: For sound source The three-dimensional spatial coordinates of the prestress loss, i.e., the specific location where the prestress loss occurs. is the sound source in three-dimensional space The horizontal axis coordinate of is the sound source in three-dimensional space The vertical axis coordinate, is the sound source in three-dimensional space The depth coordinate of is the number of acoustic emission sensors, For the first acoustic emission sensor to the sound source The distance For the AE sensor to the sound source The distance is the speed of sound waves in air, For the The time difference between the first acoustic emission sensor receiving the signal and the time difference between the first acoustic emission sensor receiving the signal.

[0036] The sound source localization module converts the three-dimensional spatial coordinates of the specific location where the prestress loss occurs into intuitive graphics, helping engineers and maintenance personnel to better understand the health of the bridge structure. The three-dimensional coordinates of the sound source position are presented through three-dimensional modeling software, and the location of the sound source can be directly marked on the structural diagram of the bridge.

[0037] Furthermore, the environmental monitoring module collects and detects the environmental data of the bridge, including the following specific contents: the health status of the bridge is not only affected by the structure itself, but also by the external environmental parameters, such as temperature, pressure, wind speed and precipitation. The environmental parameters will directly or indirectly affect the propagation characteristics of the acoustic emission signal and the accuracy of the measurement. In order to ensure the accuracy and reliability of the measurement of the prestress loss of the bridge, the environmental factors are monitored and considered in real time. The effect of temperature on the propagation of sound waves is the most significant, especially in the bridge structure with a larger span. The increase in temperature will cause the expansion of the material, thereby affecting the propagation speed of the sound wave. For this reason, the temperature sensor is arranged in the span of the bridge to obtain the surface temperature of the bridge in real time. Temperature data; air pressure mainly affects the stress and material deformation behavior of the bridge. The change in air pressure is related to the structural vibration of the bridge or the formation of microcracks. The pressure sensor arranged at the span of the bridge is used to obtain the stress data of the bridge in real time; when the wind speed is high, the vibration in the air will produce a certain background noise, which will interfere with the signal collection of the acoustic emission sensor. Therefore, it is necessary to obtain wind speed data through a wind speed sensor installed on the bridge deck; precipitation will affect the wetness of the bridge surface and the stress distribution of the bridge, especially in heavy rain. The action of water flow will have a local impact on the prestressed steel strands of the bridge, changing its stress state. The precipitation is monitored in real time through a rain sensor installed upstream of the bridge.

[0038] Furthermore, the prestress loss measurement module measures the prestress loss of the bridge, including the following specific contents: the prestress loss measurement module is responsible for measuring the prestress loss of the bridge during use. The prestress loss of the bridge is usually caused by a variety of factors, such as the slippage of the steel strand, the compression of the concrete and the increase in the service life of the bridge, which leads to a gradual decrease in the bearing capacity and stability of the bridge structure. The acoustic emission signal acquisition module collects the acoustic emission signals caused by prestress loss or structural damage in real time through sensors arranged at different parts of the bridge. The acoustic emission signals contain information on the intensity, frequency and duration of the signal. This information exhibits different characteristics as the microstructure changes in the steel strand or concrete. By extracting features and processing signals from this information, a prestress loss measurement model is established to measure the prestress loss of the bridge. The formula of the prestress loss measurement model is:

[0039] ,

[0040] Where: is the measured value of bridge prestress loss, The number of acoustic emission sensors to obtain acoustic emission signals, For the The acoustic emission signal intensity collected by the acoustic emission sensor, For the The frequency of the acoustic emission signal collected by the acoustic emission sensor, is the standard frequency response of the bridge structure in the case of prestress loss, is the coefficient of acoustic emission signal attenuation, For the The duration of an acoustic emission signal, is the standard duration of the acoustic emission signal in the case of prestress loss, is the coefficient of bridge structure damage degree, is a coefficient related to the time delay in the propagation of the acoustic emission signal.

[0041] Furthermore, the data analysis module analyzes the environmental data acquired by the sensor together with the acoustic emission signal, including the following specific contents:

[0042] Due to the thermal expansion characteristics of the steel strands on the bridge, temperature changes will directly affect their stress state, resulting in changes in prestress loss. In winter or summer, especially when the temperature difference between day and night is large, temperature fluctuations will cause relative deformation between the steel strands and concrete, thereby affecting the structural stability of the bridge. The temperature sensor monitors the temperature changes of the anchor points of the prestressed steel strands of the bridge, the surface of the bridge, etc. in real time, and can provide environmental temperature information; the anchor points of the prestressed steel strands of the bridge, the span beams and the piers are under huge pressure loads. Changes in the external environment, such as fluctuations in atmospheric pressure, will affect the stress state of the bridge. Pressure sensors are installed at these key locations to monitor the pressure state of the bridge in real time, especially under high or low pressure weather conditions. The pressure data can provide useful information about the force distribution of the bridge, and the acoustic emission signal is often The wind speed changes will usually vary with the change of stress state; strong wind or storm weather has an important impact on the stress and vibration characteristics of the bridge structure. The change of wind speed will cause the vibration of the bridge and cause the stress state of the prestressed steel strand to change, which in turn affects the propagation mode of the acoustic emission signal. When the bridge vibrates excessively under strong wind conditions, a pseudo acoustic emission signal will be generated. By coordinating with wind speed data, non-structural signals can be identified and excluded to ensure the accuracy of the measurement results; in the rainy season, precipitation will cause fluctuations in the temperature and humidity of the bridge surface, thereby affecting the stress state of the structure, especially the change of moisture in the concrete material. The change of precipitation will cause local water accumulation in the structure, thereby affecting the propagation characteristics of the sound wave in the bridge structure. For example, strong precipitation may cause slippery local areas, change the propagation path of the sound wave, and generate unreal signals;

[0043] The data analysis module combines and analyzes the temperature data obtained by the temperature sensor, the pressure data obtained by the pressure sensor, the wind speed data obtained by the wind speed sensor, the precipitation data obtained by the rainfall sensor, and the acoustic emission signal data obtained by the acoustic emission sensor to establish a correction model to correct the prestress loss measurement error caused by the temperature data, pressure data, wind speed data, and precipitation data. The formula of the correction model is:

[0044] ,

[0045] Where: is the measured value of prestress loss after correction; is the prestress loss measurement value measured by acoustic emission signal; is the change in temperature data, satisfy ,in, is the current ambient temperature. is the average temperature value one month ago; is the correction coefficient corresponding to the ambient temperature, which indicates the influence of temperature data on the measurement error of prestress loss; is the change in pressure data, satisfy ,in, is the current ambient air pressure value, is the standard air pressure value; is the correction coefficient corresponding to pressure, which indicates the influence of pressure data on the measurement error of prestress loss; is the change in wind speed data, satisfy ,in, is the current wind speed, is the average wind speed one month ago; is the correction coefficient corresponding to the wind speed, which indicates the influence of wind speed data on the measurement error of prestress loss; is the change in precipitation data, satisfy ,in, is the current precipitation, is the average precipitation one month ago; is the correction coefficient corresponding to the precipitation, which indicates the influence of precipitation data on the measurement error of prestress loss.

[0046] Furthermore, the correction coefficient corresponding to the ambient temperature is The correction coefficient corresponding to the pressure is obtained by long-term measurement of the prestress loss of the bridge at different temperatures; Derived from the statistical effect of air pressure fluctuations on the internal stress of the bridge; the correction coefficient corresponding to the wind speed Adjust according to the interference degree of wind speed on the collection of acoustic emission signals; the correction coefficient corresponding to the precipitation The data analysis of the effects of precipitation on the slipperiness and stress state of bridges shows that, in bridge structures, temperature changes will affect the expansion and contraction of materials, while changes in air pressure will further affect the stress state of materials; changes in wind speed will bring about temperature changes, and strong winds will accelerate heat exchange, causing more dramatic changes in bridge surface temperature; an increase in wind speed will change the direction of precipitation, affecting the distribution of rainwater on the bridge, thereby changing the slipperiness of local areas, and further affecting the stress state of the bridge and the propagation characteristics of acoustic emission signals; low air pressure will affect the stress state of the bridge structure, and a drop in air pressure will cause local deformation of the bridge, while precipitation will change the humidity of the bridge material, further affecting the stress state; and Negatively correlated, and is positively correlated, and is positively correlated, and Negatively correlated.

[0047] In this embodiment, the arrangement of the wind speed sensor, pressure sensor and other sensors is optimized according to their detection characteristics and the stress characteristics of the bridge structure. Among them, the wind speed sensor is mainly arranged on the windward side of the bridge span to ensure that the influence of the wind speed change on the prestress loss can be accurately captured; the pressure sensor is arranged on the piers, bearings and key bearing parts to monitor the stress state of the bridge structure under different load and air pressure conditions. In order to ensure the accurate matching of the sensor data corresponding to the prestress loss measurement value, the system automatically screens and matches the nearest sensor data that is least affected by the environment based on the spatial coordinates of the measurement point and the structural stress distribution model of the bridge during data analysis. For example, when the prestress loss value is measured at a certain point, the system will give priority to the wind speed sensor with the least wind speed influence around the measurement point and the pressure sensor with the closest air pressure fluctuation to the point, and correct the measurement error caused by the uneven distribution of sensors through the spatial interpolation technology of environmental data, so as to ensure that the final calculated prestress loss value has high accuracy and stability.

[0048] In this embodiment, the sound source localization module is connected to the acoustic emission signal acquisition module, the environmental monitoring module is connected to the sound source localization module, the prestress loss measurement module is connected to the environmental monitoring module, and the data analysis module is connected to the prestress loss measurement module.

[0049] The present invention combines an emission signal acquisition module, a sound source positioning module, an environmental monitoring module, a prestress loss measurement module and a data analysis module, and can monitor the prestress loss of a bridge in real time and efficiently, and accurately locate the specific location where the loss occurs. By arranging acoustic emission sensors at key locations of the bridge, collecting acoustic emission signals, establishing a prestress loss measurement model, measuring the prestress loss of the bridge, and correcting the acoustic emission signals with temperature, pressure, wind speed and precipitation, the interference of the external environment on the measurement results is eliminated, and the accuracy of the prestress loss measurement is ensured. In addition, the specific location of the prestress loss is converted into an intuitive three-dimensional coordinate graph through the sound source positioning module, which helps engineering personnel to clearly understand the health status of the bridge. Compared with traditional bridge prestress measurement methods, the present invention has the advantages of no need for large-scale on-site construction, no need for destructive intervention, and no need for long-term manual monitoring, which greatly improves the measurement efficiency and accuracy, reduces maintenance costs, and improves the safety and service life of the bridge.

[0050] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present 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.

[0051] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A bridge prestress loss measurement system based on acoustic emission technology, characterized in that: The system comprises an acoustic emission signal acquisition module, a sound source positioning module, an environmental monitoring module, a prestress loss measurement module and a data analysis module; the acoustic emission signal acquisition module acquires the acoustic emission signal during the prestress loss process of the bridge; the sound source positioning module uses the acoustic emission signal acquired by the acoustic emission signal acquisition module to establish a sound source position model to locate the specific location where the prestress loss occurs; the environmental monitoring module acquires and detects the environmental data of the bridge; the prestress loss measurement module establishes a prestress loss measurement model according to the intensity, frequency and duration of the acoustic emission signal, which is used to measure the prestress loss of the bridge, and the formula of the prestress loss measurement model is: ， Where: is the measured value of bridge prestress loss, The number of acoustic emission sensors to obtain acoustic emission signals, For the The acoustic emission signal intensity collected by the acoustic emission sensor, For the The frequency of the acoustic emission signal collected by the acoustic emission sensor, is the standard frequency response of the bridge structure in the case of prestress loss, is the coefficient of acoustic emission signal attenuation, For the The duration of an acoustic emission signal, is the standard duration of the acoustic emission signal in the case of prestress loss, is the coefficient of bridge structure damage degree, is the coefficient related to the time delay in the propagation of the acoustic emission signal; The data analysis module combines the environmental data and the acoustic emission signal data to establish a correction model to correct the prestress loss measurement error caused by the environmental data.

2. According to claim 1, a bridge prestress loss measurement system based on acoustic emission technology is characterized in that: The sound source localization module is responsible for locating the specific location where the prestress loss occurs. By arranging the acoustic emission sensors at the span of the bridge, the sound source localization module can capture the acoustic emission signals at different positions and angles. Using the signals collected by the acoustic emission sensors, the sound source localization module establishes a sound source location model to locate the specific location where the prestress loss occurs. The formula of the sound source location model is: ， Where: For sound source The three-dimensional spatial coordinates of the prestress loss, i.e., the specific location where the prestress loss occurs, is the sound source in three-dimensional space The horizontal axis coordinate of is the sound source in three-dimensional space The vertical axis coordinate, is the sound source in three-dimensional space The depth coordinate of is the number of acoustic emission sensors, For the first acoustic emission sensor to the sound source The distance For the AE sensor to the sound source The distance is the speed of sound waves in air, For the The time difference between the first acoustic emission sensor receiving the signal and the time difference between the first acoustic emission sensor receiving the signal.

3. The bridge prestress loss measurement system based on acoustic emission technology according to claim 1 is characterized in that: The data analysis module combines and analyzes the temperature data obtained by the temperature sensor, the pressure data obtained by the pressure sensor, the wind speed data obtained by the wind speed sensor, the precipitation data obtained by the rain sensor, and the acoustic emission signal data obtained by the acoustic emission sensor to establish a correction model to correct the prestress loss measurement error caused by the temperature data, pressure data, wind speed data, and precipitation data. The formula of the correction model is: ， Where: is the measured value of prestress loss after correction; is the prestress loss measurement value obtained by acoustic emission signal; is the change in temperature data, satisfy ,in, is the current ambient temperature. is the average temperature value one month ago; is the correction coefficient corresponding to the ambient temperature, which indicates the influence of temperature data on the measurement error of prestress loss; is the change in pressure data, satisfy ,in, is the current ambient air pressure value, is the standard air pressure value; is the correction coefficient corresponding to pressure, which indicates the influence of pressure data on the measurement error of prestress loss; is the change in wind speed data, satisfy ,in, is the current wind speed, is the average wind speed one month ago; is the correction coefficient corresponding to the wind speed, which indicates the influence of wind speed data on the measurement error of prestress loss; is the change in precipitation data, satisfy ,in, is the current precipitation, is the average precipitation one month ago; is the correction coefficient corresponding to the precipitation, which indicates the influence of precipitation data on the measurement error of prestress loss.

4. The bridge prestress loss measurement system based on acoustic emission technology according to claim 3 is characterized in that: The correction factor corresponding to the ambient temperature The correction coefficient corresponding to the pressure is obtained by long-term measurement of the prestress loss of the bridge at different temperatures; Derived from the statistical effect of air pressure fluctuations on the internal stress of the bridge; the correction coefficient corresponding to the wind speed Adjust according to the interference degree of wind speed on the collection of acoustic emission signals; the correction coefficient corresponding to the precipitation The data analysis of the effects of precipitation on the slipperiness and stress state of bridges shows that, in bridge structures, temperature changes will affect the expansion and contraction of materials, while changes in air pressure will further affect the stress state of materials; changes in wind speed will bring about temperature changes, and strong winds will accelerate heat exchange, causing more dramatic changes in bridge surface temperature; an increase in wind speed will change the direction of precipitation, affecting the distribution of rainwater on the bridge, thereby changing the slipperiness of local areas, and further affecting the stress state of the bridge and the propagation characteristics of acoustic emission signals; low air pressure will affect the stress state of the bridge structure, and a drop in air pressure will cause local deformation of the bridge, while precipitation will change the humidity of the bridge material, further affecting the stress state; and Negatively correlated, and is positively correlated, and is positively correlated, and Negatively correlated.

5. The bridge prestress loss measurement system based on acoustic emission technology according to claim 1 is characterized in that: The acoustic emission signal acquisition module adopts an acoustic emission sensor, which is arranged in the span of the bridge to monitor the acoustic emission signal generated by the bridge during the stress process in real time. The acoustic emission sensor is an ultrasonic sensor that converts the detected sound wave changes into electrical signals.

6. The bridge prestress loss measurement system based on acoustic emission technology according to claim 1 is characterized in that: The environmental monitoring module includes a temperature sensor, a pressure sensor, a wind speed sensor and a rainfall sensor, which are arranged at the span of the bridge and are used to obtain temperature data, pressure data, wind speed data and rainfall data of the bridge in real time.

7. The bridge prestress loss measurement system based on acoustic emission technology according to claim 1 is characterized in that: Acoustic emission sensors are arranged at the span of the bridge to collect in real time the acoustic emission signals generated by the bridge during the prestress loss process. The acoustic emission signals are high-frequency elastic waves or sound waves generated by the bridge structure under stress changes, cracking and slippage.

8. The bridge prestress loss measurement system based on acoustic emission technology according to claim 1 is characterized in that: The sound source localization module is connected to the acoustic emission signal acquisition module, the environment monitoring module is connected to the sound source localization module, the prestress loss measurement module is connected to the environment monitoring module, and the data analysis module is connected to the prestress loss measurement module.

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