A nondestructive testing method and system for asphalt pavement

Abstract

The present invention relates to the field of ground detection technology, and discloses a nondestructive detection method and system for asphalt pavement, wherein the system includes a ground detection module, an area determination module, and a status warning module. The ground detection module collects the stress-strain state and temperature information of the asphalt pavement around the clock through fiber grating sensors and thermocouple sensors, and sends it to a data analysis unit for preliminary defect judgment. The area determination module divides the pavement into a plurality of preset areas and numbers them, determines the defective areas according to the defect information, and sends the information to the status warning module. The status warning module obtains the stress-strain state of the defective area, determines the defect information again, and matches the warning signal and sends it to the user. The system realizes comprehensive and accurate detection and timely warning of pavement defects by comprehensively analyzing the stress-strain state and temperature information, thereby ensuring road safety and service life.

Description

Technical Field

[0001] The present invention relates to the field of ground detection technology, and in particular to a nondestructive detection method and system for asphalt pavement. Background Art

[0002] With the acceleration of urbanization, asphalt pavement is an important part of urban transportation infrastructure, and its quality and safety are directly related to the efficiency and safety of transportation. However, due to the long-term influence of factors such as vehicle load, climate change, and material aging, asphalt pavement is prone to cracks, voids, uneven settlement and other defects, which not only affect the service life of the pavement, but may also lead to traffic accidents. Therefore, regular inspection and maintenance of asphalt pavement is particularly important.

[0003] Traditional asphalt pavement inspection methods mainly include manual inspection and mechanical inspection. Manual inspection relies on the experience and judgment of the inspectors, which is inefficient and easily affected by subjective factors. Although mechanical inspection is more efficient, it usually requires closing roads, causing inconvenience to traffic and high inspection costs. In addition, most of these methods are destructive inspections, which may cause secondary damage to the road surface during the inspection process.

[0004] In recent years, with the development of sensor technology, data analysis technology and communication technology, non-destructive testing technology has gradually been applied to the detection of asphalt pavement. Non-destructive testing technology buries sensors in the pavement to collect the stress-strain state and temperature information of the pavement in real time, and processes and analyzes the collected data through a data analysis unit to determine whether there are defects in the pavement. This method can not only achieve all-weather detection, but also will not cause damage to the pavement, and has a high application value. Summary of the invention

[0005] In view of this, the present invention proposes a nondestructive testing method and system for asphalt pavement, aiming to solve the problems of low efficiency and high testing cost of traditional asphalt pavement testing methods in current technology.

[0006] On the one hand, the present invention provides a nondestructive testing system for asphalt pavement, comprising:

[0007] A ground detection module, the ground detection module includes a data acquisition unit buried in the asphalt pavement, a power supply unit connected to the data acquisition unit through a power line, and a data analysis unit connected through a data line; the data acquisition unit includes a fiber grating sensor and a thermocouple sensor; the fiber grating sensor is used to detect the stress and strain state of the asphalt pavement, and the thermocouple sensor is used to detect the temperature of the asphalt pavement; the data acquisition unit is configured to collect the stress and strain state and temperature information of the asphalt pavement around the clock, and send the stress and strain state and temperature information of the asphalt pavement to the data analysis unit, the data analysis unit determines whether the asphalt pavement has defects according to the temperature information, and sends the defect information to the area determination module for secondary correction;

[0008] The area determination module is configured to divide the asphalt pavement into a plurality of preset areas of equal size, number the preset areas respectively, determine the preset area number where the defect is located according to the defect information received from the data analysis unit, and send the preset area number and defect information to the status warning module;

[0009] The status warning module is configured to obtain the stress-strain state of a defective preset area, re-determine the defect information based on the stress-strain state, match a preset warning signal based on the determined defect information, and send the warning signal to the user.

[0010] Optionally, the thermocouple sensor is used to detect the temperature of the asphalt pavement and further comprises: recording the temperature changes in different time periods and sending them to the data analysis unit;

[0011] The data analysis unit also includes generating a temperature change curve according to the temperature change in different time periods of the same preset area, and generating a road surface temperature distribution map according to the temperature of different preset areas at the same time.

[0012] Optionally, the data analysis unit determines whether the asphalt pavement has defects according to the temperature information, specifically including:

[0013] The heat conduction process is analyzed according to the temperature diffusion function and the thermal diffusivity; and the thermal diffusion characteristics of the asphalt pavement are simulated to analyze the local temperature gradient changes, and whether there are defects is determined by comparing the local temperature gradient change value with the simulated value.

[0014] Optionally, the heat conduction process is analyzed by a heat conduction equation, which is:

[0015] ;

[0016] ;

[0017] in, represents the temperature at position (x, y, z) and time t; It represents the rate of change of temperature with time; is the thermal diffusivity; represents the Laplace operator.

[0018] Optionally, the analyzing the local temperature gradient change specifically includes:

[0019] Solving the heat conduction equation predicts ; and calculate the temperature change according to the local temperature gradient change formula; the local temperature change formula is:

[0020]

[0021] Among them, the represents the local temperature change, represents the current temperature detected by the thermocouple sensor, Represents the predicted temperature calculated from the heat equation.

[0022] Optionally, the data analysis unit determines whether the asphalt pavement has defects according to the temperature information, specifically including:

[0023] The defect type of the asphalt pavement is judged according to the local temperature change. When the local temperature change is greater than 5°C, it means that the asphalt pavement has large cracks or voids; when the local temperature change is greater than 1°C and less than 5°C, it means that the asphalt pavement has small cracks or is uneven; when the local temperature change is a positive number, it means that the temperature measurement is greater than the predicted temperature, and the asphalt pavement may face aging or insufficient drainage problems; when the local temperature change is a negative number, it means that the temperature measurement is less than the predicted temperature, indicating that the asphalt pavement has underground voids or cracks or low local density problems.

[0024] Optionally, re-determining the defect information according to the stress-strain state specifically includes:

[0025] When the strain exceeds 0.2%, it is judged that there are cracks or voids in the preset area; when the stress is concentrated, it is judged that there is structural discontinuity; when the stress-strain curve formed by the stress-strain state is nonlinear, it is judged that fatigue damage has occurred in the preset area.

[0026] Optionally, the stress-strain curve is drawn as follows:

[0027] The stress and strain data of the preset area under different pressure conditions are recorded, and a stress-strain curve is drawn according to the stress and strain data.

[0028] Optionally, the status warning module is also used to: when the defect judged based on the local temperature change is the same as the defect judged based on the stress-strain state, determine that the defect exists and send a primary warning report to the user; when one of the defect judged based on the local temperature change and the defect judged based on the stress-strain state is judged as a defect and the other is judged as not existing, obtain historical data for re-determination, when there is a historical defect in the preset area, judge that there is a defect, and when there is no historical defect in the preset area, judge that there is no defect; when the defect judged based on the local temperature change is different from the defect type judged based on the stress-strain state, send an advanced warning report to the user.

[0029] Among them, the primary warning can include determining the presence of [specific defect type] in the area based on the analysis of local temperature changes and stress-strain states; and recommending further detailed inspection and maintenance to prevent the defect from further expanding. Arrange professionals to conduct on-site surveys, develop detailed maintenance and repair plans, and regularly monitor the conditions of the area to ensure that potential problems are discovered and handled in a timely manner.

[0030] Advanced warning can find that the defect types determined by the two methods are inconsistent based on the analysis of local temperature changes and stress-strain states, and judge that there may be complex defects that require further detailed testing and analysis. Immediately arrange for professionals to conduct on-site inspections. Use multiple detection methods (such as ultrasonic testing, infrared thermal imaging, etc.) for comprehensive analysis. Develop detailed maintenance and repair plans to ensure that potential problems are dealt with in a timely manner.

[0031] On the other hand, the present invention also proposes a non-destructive testing method for the above-mentioned asphalt pavement, the method comprising:

[0032] Collect stress-strain state and temperature information of the asphalt pavement around the clock, and send the stress-strain state and temperature information of the asphalt pavement to a data analysis unit, the data analysis unit determines whether the asphalt pavement has defects according to the temperature information, and sends the defect information to the area determination module for secondary correction;

[0033] Divide the asphalt pavement into a plurality of preset areas of the same size, number the preset areas respectively, determine the preset area number where the defect is located according to the defect information received from the data analysis unit, and send the preset area number and defect information to the status warning module;

[0034] The stress-strain state of the defective preset area is obtained, the defect information is re-determined according to the stress-strain state, and a preset warning signal is matched according to the determined defect information, and the warning signal is sent to the user.

[0035] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention provides a nondestructive testing system and method for asphalt pavement. The system can collect stress-strain state and temperature information of the pavement around the clock through a data acquisition unit buried in the asphalt pavement, which is not affected by weather and time, ensuring the continuity and real-time nature of the detection. The system uses fiber grating sensors and thermocouple sensors for data acquisition, which will not cause any damage to the pavement, avoiding the secondary damage that may be caused by traditional detection methods. The system can accurately determine whether there are defects in the pavement by processing and analyzing the collected data through the data analysis unit, and make secondary corrections according to temperature changes and stress-strain states, thereby improving the accuracy of detection. Regional management: The system divides the asphalt pavement into multiple preset areas of the same size, and numbers each area, which is convenient for locating and managing defects and improving the efficiency of maintenance. The status warning module re-determines the defect information based on the stress-strain state and temperature information, and sends it to the user according to the preset warning signal, thereby realizing timely warning and processing of pavement defects. The system can not only analyze the stress-strain state of the road surface, but also generate temperature change curves and road surface temperature distribution maps based on temperature changes, providing multi-dimensional data support and helping to fully understand the health of the road surface. The system can re-determine defect information based on historical data, improve the reliability of judgment, and avoid misjudgment and missed judgment. The system sends different levels of early warning reports based on the severity of the defect to ensure that users can take corresponding maintenance measures in a timely manner to ensure the safety and service life of the road surface. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0037] Figure 1 A schematic diagram of a nondestructive testing system for asphalt pavement provided by the present invention;

[0038] Figure 2 A flow chart of the nondestructive testing method for asphalt pavement provided by the present invention. DETAILED DESCRIPTION

[0039] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0040] Traditional asphalt pavement inspection methods mainly include manual inspection and mechanical inspection. Manual inspection relies on the experience and judgment of the inspectors, which is inefficient and easily affected by subjective factors. Although mechanical inspection is more efficient, it usually requires closing roads, causing inconvenience to traffic and high inspection costs. In addition, most of these methods are destructive inspections, which may cause secondary damage to the road surface during the inspection process.

[0041] In recent years, with the development of sensor technology, data analysis technology and communication technology, non-destructive testing technology has gradually been applied to the detection of asphalt pavement. Non-destructive testing technology buries sensors in the pavement to collect the stress-strain state and temperature information of the pavement in real time, and processes and analyzes the collected data through a data analysis unit to determine whether there are defects in the pavement. This method can not only achieve all-weather detection, but also will not cause damage to the pavement, and has a high application value.

[0042] like Figure 1 As shown, it is a schematic diagram of a nondestructive testing system for asphalt pavement provided by the present invention. It can be seen that a nondestructive testing system for asphalt pavement proposed by the present invention includes:

[0043] A ground detection module, the ground detection module includes a data acquisition unit buried in the asphalt pavement, a power supply unit connected to the data acquisition unit through a power line, and a data analysis unit connected through a data line; the data acquisition unit includes a fiber grating sensor and a thermocouple sensor; the fiber grating sensor is used to detect the stress and strain state of the asphalt pavement, and the thermocouple sensor is used to detect the temperature of the asphalt pavement; the data acquisition unit is configured to collect the stress and strain state and temperature information of the asphalt pavement around the clock, and send the stress and strain state and temperature information of the asphalt pavement to the data analysis unit, the data analysis unit determines whether there is a defect in the asphalt pavement according to the temperature information, and sends the defect information to the area determination module for secondary correction;

[0044] an area determination module, configured to divide the asphalt pavement into a plurality of preset areas of equal size, number the preset areas respectively, determine the preset area number where the defect is located according to the defect information received from the data analysis unit, and send the preset area number and the defect information to the status warning module;

[0045] The status warning module is configured to obtain the stress-strain state of a preset defective area, re-determine the defect information based on the stress-strain state, match the preset warning signal based on the determined defect information, and send the warning signal to the user.

[0046] It is understandable that the system can collect the stress-strain state and temperature information of the road surface all day long through the data acquisition unit buried in the asphalt pavement, which is not affected by weather and time, ensuring the continuity and real-time nature of the detection. The system uses fiber grating sensors and thermocouple sensors for data acquisition, which will not cause any damage to the road surface, avoiding the secondary damage that may be caused by traditional detection methods. Through the data analysis unit to process and analyze the collected data, the system can accurately determine whether there are defects in the road surface, and make secondary corrections according to temperature changes and stress-strain states, thereby improving the accuracy of detection. Regional management: The system divides the asphalt pavement into multiple preset areas of the same size, and numbers each area, which is convenient for locating and managing defects and improving the efficiency of maintenance. The status warning module re-determines the defect information based on the stress-strain state and temperature information, and sends it to the user according to the preset warning signal, realizing timely warning and processing of road surface defects. The system can not only analyze the stress-strain state of the road surface, but also generate temperature change curves and road surface temperature distribution maps based on temperature changes, providing multi-dimensional data support, which helps to fully understand the health of the road surface. The system can re-determine defect information based on historical data, improving the reliability of judgment and avoiding misjudgment and missed judgment. The system sends different levels of early warning reports according to the severity of the defect, ensuring that users can take corresponding maintenance measures in time to ensure the safety and service life of the road surface.

[0047] In this preferred embodiment, the thermocouple sensor is used to detect the temperature of the asphalt pavement and further comprises: recording the temperature changes in different time periods and sending them to the data analysis unit;

[0048] The data analysis unit also includes generating a temperature change curve according to the temperature change in different time periods of the same preset area, and generating a road surface temperature distribution map according to the temperature of different preset areas at the same time.

[0049] It is understandable that the thermocouple sensor is not only used to detect the real-time temperature of the asphalt pavement, but also has the function of recording the temperature changes in different time periods. This design enables the system to obtain more comprehensive and detailed temperature data, thereby providing richer information support for subsequent data analysis. Specifically, the thermocouple sensor continuously records the temperature changes in different time periods and sends these data to the data analysis unit. After receiving these data, the data analysis unit can generate a temperature change curve based on the temperature changes in the same preset area in different time periods. This temperature change curve can intuitively show the temperature fluctuations in a specific area over a period of time, which is helpful for analyzing the temperature change trends and laws in the area. In addition, the data analysis unit can also generate a road surface temperature distribution map based on the temperature data of different preset areas at the same time. This distribution map can show the temperature distribution of the entire asphalt pavement at a specific moment, which helps to identify the temperature abnormality area, so as to determine whether there are potential defects or problem areas. In this way, the system can not only monitor the temperature of the asphalt pavement in real time, but also provide more comprehensive and in-depth temperature information through historical data and distribution map analysis, providing more reliable data support for the detection and early warning of pavement defects.

[0050] In this preferred embodiment, the data analysis unit determines whether the asphalt pavement has defects according to the temperature information, specifically including:

[0051] The heat conduction process is analyzed based on the temperature diffusion function and thermal diffusivity; the thermal diffusion characteristics of the asphalt pavement are simulated, the local temperature gradient changes are analyzed, and the presence of defects is determined by comparing the local temperature gradient change values ​​with the simulated values. The data analysis unit first uses the temperature diffusion function and thermal diffusivity to analyze the heat conduction process. The temperature diffusion function describes the law of temperature propagation in the material, while the thermal diffusivity reflects the material's ability to conduct heat.

[0052] It is understandable that the data analysis unit determines whether there are defects in the asphalt pavement by comprehensively analyzing the stress-strain state and temperature information. Specifically, the data analysis unit first uses the temperature diffusion function and thermal diffusivity to analyze the heat conduction process. The temperature diffusion function describes the propagation law of temperature in the material, while the thermal diffusivity reflects the ability of the material to conduct heat. Through these two parameters, the data analysis unit can simulate the thermal diffusion characteristics of the asphalt pavement. During the simulation process, the data analysis unit will focus on the change of the local temperature gradient. The local temperature gradient refers to the rate of change of temperature in a specific area, which can reflect the heat conduction situation in the area. The data analysis unit will calculate the change value of the local temperature gradient based on the actual collected temperature data and compare it with the simulated value. By comparing the actual value and the simulated value, the data analysis unit can determine whether there are defects. If the change value of the local temperature gradient is significantly different from the simulated value, it means that the thermal conduction characteristics of the area are inconsistent with the normal situation, and there may be cracks, voids or other defects. This difference is usually manifested as an abnormal increase or decrease in temperature, which indicates that there are potential problems in the pavement. In this way, the data analysis unit can use temperature information and thermal conduction characteristics to accurately detect defects in the asphalt pavement, thereby improving the accuracy and reliability of detection.

[0053] In this preferred embodiment, the heat conduction process is analyzed by the heat conduction equation, which is:

[0054] ;

[0055] ;

[0056] in, represents the temperature at position (x, y, z) and time t; It represents the rate of change of temperature with time; is the thermal diffusivity; represents the Laplace operator.

[0057] In this preferred embodiment, analyzing the local temperature gradient change specifically includes:

[0058] Solving the heat conduction equation predicts (x, y, z, t); and calculate the temperature change according to the local temperature gradient change formula; the local temperature change formula is:

[0059]

[0060] in, represents the local temperature change, Indicates the current temperature detected by the thermocouple sensor. Represents the predicted temperature calculated from the heat equation.

[0061] In this preferred embodiment, the data analysis unit determines whether there are defects in the asphalt pavement according to the temperature information, specifically including:

[0062] The defect type of the asphalt pavement is judged according to the local temperature change. When the local temperature change is greater than 5°C, it means that the asphalt pavement has large cracks or voids; when the local temperature change is greater than 1°C and less than 5°C, it means that the asphalt pavement has small cracks or is uneven; when the local temperature change is a positive number, it means that the temperature measurement is greater than the predicted temperature, and the asphalt pavement may face aging or insufficient drainage problems; when the local temperature change is a negative number, it means that the temperature measurement is less than the predicted temperature, indicating that the asphalt pavement has underground voids or cracks or low local density problems.

[0063] It is understandable that the data analysis unit determines the defect type of the asphalt pavement by analyzing the local temperature change. Specifically, the data analysis unit compares the actual collected temperature data with the predicted temperature and calculates the local temperature change. According to the size and positive and negative of this change, different defect types can be inferred. When the local temperature change is significantly higher than the normal range, it indicates that there may be large cracks or voids in the area. These defects will cause abnormal heat conduction, causing the temperature change to increase abnormally. When the local temperature change is small but there is still a certain difference, it indicates that there may be small cracks or uneven settlement in the area. Although these defects have little effect on heat conduction, they can still be reflected by the temperature change. When the local temperature change is a positive number, it means that the actual measured temperature is higher than the predicted temperature. This situation may indicate that the asphalt pavement is facing aging or insufficient drainage. Aging will cause the material performance to decline and affect heat conduction; insufficient drainage may cause water retention and affect temperature distribution. When the local temperature change is a negative number, it means that the actual measured temperature is lower than the predicted temperature. This situation may indicate that there are underground voids, cracks or low local density in the asphalt pavement. These defects can cause thermal anomalies, causing temperature measurements to be lower than predicted.

[0064] In this way, the data analysis unit can accurately determine the defect type of the asphalt pavement based on the local temperature change, thus providing a scientific basis for subsequent maintenance and repair. This method not only improves the accuracy of detection, but also enables the adoption of corresponding treatment measures for different types of defects to ensure the safety and service life of the pavement.

[0065] In this preferred embodiment, re-determining the defect information according to the stress-strain state specifically includes:

[0066] When the strain exceeds 0.2%, it is judged that there are cracks or voids in the preset area; when the stress is concentrated, it is judged that there is structural discontinuity; when the stress-strain curve formed by the stress-strain state is nonlinear, it is judged that fatigue damage has occurred in the preset area.

[0067] It is understandable that the data analysis unit not only determines the defect type of the asphalt pavement based on the temperature information, but also reconfirms the defect information in combination with the stress-strain state. Specifically, the data analysis unit analyzes the stress-strain state to further verify and refine the judgment of the defect. When the strain value is significantly higher than the normal range, it indicates that there may be cracks or voids in the preset area. These defects will cause abnormal deformation of the material when subjected to force, resulting in an abnormal increase in the strain value. When stress is concentrated in a specific area, it indicates that there is structural discontinuity in the area. Stress concentration is usually caused by defects or unevenness inside the material, which can cause abnormal stress increases in local areas. When the stress-strain curve formed by the stress-strain state presents nonlinear characteristics, it indicates that fatigue damage has occurred in the preset area. Fatigue damage refers to the damage that gradually accumulates in the material during repeated loading and unloading. This damage will cause the mechanical properties of the material to deteriorate, causing the stress-strain curve to deviate from a linear relationship.

[0068] By combining the analysis of stress-strain state, the data analysis unit can verify and refine the defect type determined by temperature information. For example, if the temperature information indicates that there are cracks or voids in a certain area, and the stress-strain state also shows that the strain in the area is too large, then it can be further confirmed that there are indeed cracks or voids in the area. Similarly, if the stress-strain curve is nonlinear, combined with the change in temperature information, it can be determined that fatigue damage has occurred in the area.

[0069] In this preferred embodiment, the method for drawing the stress-strain curve is:

[0070] The stress and strain data of the preset area under different pressure conditions are recorded, and a stress-strain curve is drawn based on the stress and strain data.

[0071] In this preferred embodiment, when the defect judged based on the local temperature change is the same as the defect judged based on the stress-strain state, it is determined that the defect exists and a primary warning report is sent to the user; when one of the defect judged based on the local temperature change and the defect judged based on the stress-strain state is judged to be a defect and the other is judged to be non-defective, historical data is obtained for re-determination, and when there is a historical defect in the preset area, it is judged to be a defect, and when there is no historical defect in the preset area, it is judged to be non-defective; when the defect judged based on the local temperature change is different from the defect type judged based on the stress-strain state, an advanced warning report is sent to the user.

[0072] It is understood that in a preferred embodiment, the data analysis unit determines the defects of the asphalt pavement by comprehensively analyzing the local temperature variation and the stress-strain state, and sends corresponding warning reports according to different situations. The specific process is as follows: When the defect determined according to the local temperature variation is the same as the defect determined according to the stress-strain state, the data analysis unit determines that the defect exists and sends a primary warning report to the user. When one of the defects determined according to the local temperature variation and the defect determined according to the stress-strain state is judged to exist and the other is judged to not exist, the data analysis unit will obtain historical data for re-determination. If there is a historical defect in the preset area, it is judged to exist; if there is no historical defect in the preset area, it is judged to not exist. When the defect determined according to the local temperature variation is different from the defect type determined according to the stress-strain state, the data analysis unit sends an advanced warning report to the user. In this way, the data analysis unit can send corresponding warning reports according to different situations to ensure that the user or maintenance team can understand the condition of the asphalt pavement in a timely manner and take corresponding measures for maintenance and repair.

[0073] Among them, the primary warning can include determining the specific defect type in the area based on the analysis of local temperature changes and stress-strain states, and recommending further detailed inspections and maintenance to prevent the defects from further expanding. Arrange professionals to conduct on-site surveys, develop detailed maintenance and repair plans, and regularly monitor the conditions of the area to ensure that potential problems are discovered and handled in a timely manner.

[0074] Advanced warning can find that the defect types determined by the two methods are inconsistent based on the analysis of local temperature changes and stress-strain states, and judge that there may be complex defects that require further detailed testing and analysis. Immediately arrange for professionals to conduct on-site inspections. Use multiple detection methods (such as ultrasonic testing, infrared thermal imaging, etc.) for comprehensive analysis. Develop detailed maintenance and repair plans to ensure that potential problems are dealt with in a timely manner.

[0075] In summary, the system can collect the stress-strain state and temperature information of the road surface all day long through the data acquisition unit buried in the asphalt pavement, which is not affected by weather and time, ensuring the continuity and real-time nature of the detection. The system uses fiber grating sensors and thermocouple sensors for data acquisition, which will not cause any damage to the road surface, avoiding the secondary damage that may be caused by traditional detection methods. Through the data analysis unit to process and analyze the collected data, the system can accurately determine whether there are defects in the road surface, and make secondary corrections according to temperature changes and stress-strain states, thereby improving the accuracy of detection. Regional management: The system divides the asphalt pavement into multiple preset areas of the same size, and numbers each area, which is convenient for locating and managing defects and improving the efficiency of maintenance. The status warning module re-determines the defect information based on the stress-strain state and temperature information, and sends it to the user according to the preset warning signal, realizing timely warning and processing of road surface defects. The system can not only analyze the stress-strain state of the road surface, but also generate temperature change curves and road surface temperature distribution maps based on temperature changes, providing multi-dimensional data support, which helps to fully understand the health of the road surface. The system can re-determine defect information based on historical data, improving the reliability of judgment and avoiding misjudgment and missed judgment. The system sends different levels of early warning reports according to the severity of the defect, ensuring that users can take corresponding maintenance measures in time to ensure the safety and service life of the road surface.

[0076] like Figure 2 As shown, the embodiment of the present invention also provides a nondestructive testing method for asphalt pavement, comprising:

[0077] S1: Collect the stress-strain state and temperature information of the asphalt pavement around the clock, and send the stress-strain state and temperature information of the asphalt pavement to the data analysis unit. The data analysis unit determines whether there are defects in the asphalt pavement according to the temperature information, and sends the defect information to the area determination module for secondary correction;

[0078] S2: Divide the asphalt pavement into a plurality of preset areas of the same size, number the preset areas respectively, determine the preset area number where the defect is located according to the defect information received from the data analysis unit, and send the preset area number and defect information to the status warning module;

[0079] S3: Obtain the stress-strain state of the preset defective area, re-determine the defect information according to the stress-strain state, match the preset warning signal according to the determined defect information, and send the warning signal to the user.

[0080] It can be understood that the embodiment of the present invention provides a nondestructive testing method for asphalt pavement, which collects stress-strain state and temperature information of asphalt pavement around the clock, and sends this information to the data analysis unit for preliminary defect judgment. The data analysis unit judges whether there is a defect in the asphalt pavement according to the temperature information, and sends the defect information of the preliminary judgment to the area determination module for secondary correction. Subsequently, the asphalt pavement is divided into a plurality of preset areas of the same size, and each preset area is numbered. According to the defect information received from the data analysis unit, the preset area number where the defect is located is determined, and the preset area number and defect information are sent to the status warning module. Then, the stress-strain state of the preset area with defects is obtained, and the defect information is re-determined according to the stress-strain state. According to the determined defect information, the preset warning signal is matched, and the matched warning signal is sent to the user. Through this series of steps, the embodiment of the present invention can realize comprehensive and accurate detection of asphalt pavement defects, and send warning signals in time, so as to ensure that the management user or maintenance team can take measures quickly to ensure the safety and service life of the road. In addition, the method also has the ability of all-weather monitoring, can work continuously under various weather conditions, and improves the reliability and efficiency of detection. By comprehensively analyzing stress-strain state and temperature information, the embodiments of the present invention can more accurately identify and locate road surface defects, providing powerful technical support for road maintenance.

[0081] In summary, the system can collect the stress-strain state and temperature information of the road surface all day long through the data acquisition unit buried in the asphalt pavement, which is not affected by weather and time, ensuring the continuity and real-time nature of the detection. The system uses fiber grating sensors and thermocouple sensors for data acquisition, which will not cause any damage to the road surface, avoiding the secondary damage that may be caused by traditional detection methods. Through the data analysis unit to process and analyze the collected data, the system can accurately determine whether there are defects in the road surface, and make secondary corrections according to temperature changes and stress-strain states, thereby improving the accuracy of detection. Regional management: The system divides the asphalt pavement into multiple preset areas of the same size, and numbers each area, which is convenient for locating and managing defects and improving the efficiency of maintenance. The status warning module re-determines the defect information based on the stress-strain state and temperature information, and sends it to the user according to the preset warning signal, realizing timely warning and processing of road surface defects. The system can not only analyze the stress-strain state of the road surface, but also generate temperature change curves and road surface temperature distribution maps based on temperature changes, providing multi-dimensional data support, which helps to fully understand the health of the road surface. The system can re-determine defect information based on historical data, improving the reliability of judgment and avoiding misjudgment and missed judgment. The system sends different levels of early warning reports according to the severity of the defect, ensuring that users can take corresponding maintenance measures in time to ensure the safety and service life of the road surface.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A nondestructive testing system for asphalt pavement, characterized in that: include: A ground detection module, the ground detection module includes a data acquisition unit buried in the asphalt pavement, a power supply unit connected to the data acquisition unit through a power line, and a data analysis unit connected through a data line; the data acquisition unit includes a fiber grating sensor and a thermocouple sensor; the fiber grating sensor is used to detect the stress and strain state of the asphalt pavement, and the thermocouple sensor is used to detect the temperature of the asphalt pavement; the data acquisition unit is configured to collect the stress and strain state and temperature information of the asphalt pavement around the clock, and send the stress and strain state and temperature information of the asphalt pavement to the data analysis unit, the data analysis unit determines whether the asphalt pavement has defects according to the temperature information, and sends the defect information to the area determination module for secondary correction; The area determination module is configured to divide the asphalt pavement into a plurality of preset areas of equal size, number the preset areas respectively, determine the preset area number where the defect is located according to the defect information received from the data analysis unit, and send the preset area number and defect information to the status warning module; A status warning module is configured to obtain the stress-strain state of a preset defective area, re-determine the defect information according to the stress-strain state, match a preset warning signal according to the determined defect information, and send the warning signal to a user; The state warning module is also used for: when the defect judged according to the local temperature change is the same as the defect judged according to the stress-strain state, determining that the defect exists and sending a primary warning report to the user; when one of the defect judged according to the local temperature change and the defect judged according to the stress-strain state is judged to be a defect and the other is judged not to be a defect, obtaining historical data for re-determination, when there is a historical defect in the preset area, judging that the defect exists, and when there is no historical defect in the preset area, judging that the defect does not exist; when the defect judged according to the local temperature change is different from the defect type judged according to the stress-strain state, sending an advanced warning report to the user; When the thermocouple sensor is used to detect the temperature of the asphalt pavement, it also includes: recording the temperature changes in different time periods and sending them to the data analysis unit; The data analysis unit further comprises generating a temperature change curve according to the temperature changes in different time periods of the same preset area, and generating a road surface temperature distribution map according to the temperatures of different preset areas in the same time period; The data analysis unit determines whether the asphalt pavement has defects according to the temperature information, specifically including: The heat conduction process is analyzed according to the temperature diffusion function and the thermal diffusivity; and the thermal diffusion characteristics of the asphalt pavement are simulated to analyze the local temperature gradient changes, and whether there are defects is determined by comparing the local temperature gradient change value with the simulated value.

2. A nondestructive testing system for asphalt pavement according to claim 1, characterized in that: The analytical heat conduction process is performed by the heat conduction equation, which is: ； ； in, represents the temperature at position (x, y, z) and time t; It represents the rate of change of temperature with time; is the thermal diffusivity; represents the Laplace operator.

3. A nondestructive testing system for asphalt pavement according to claim 2, characterized in that: The analysis of local temperature gradient changes specifically includes: Solving the heat conduction equation predicts ; and calculate the temperature change according to the local temperature gradient change formula; the local temperature change formula is: ； Among them, the represents the local temperature change, represents the current temperature detected by the thermocouple sensor, Represents the predicted temperature calculated from the heat equation.

4. A nondestructive testing system for asphalt pavement according to claim 3, characterized in that: The data analysis unit determines whether the asphalt pavement has defects according to the temperature information specifically including: The defect type of the asphalt pavement is judged according to the local temperature change. When the local temperature change is greater than 5°C, it means that the asphalt pavement has large cracks or voids; when the local temperature change is greater than 1°C and less than 5°C, it means that the asphalt pavement has small cracks or is uneven; when the local temperature change is a positive number, it means that the temperature measurement is greater than the predicted temperature, and the asphalt pavement may face aging or insufficient drainage problems; when the local temperature change is a negative number, it means that the temperature measurement is less than the predicted temperature, indicating that the asphalt pavement has underground voids or cracks or low local density problems.

5. A nondestructive testing system for asphalt pavement according to claim 4, characterized in that: The re-determining the defect information according to the stress-strain state specifically includes: When the strain exceeds 0.2%, it is judged that there are cracks or voids in the preset area; when the stress is concentrated, it is judged that there is structural discontinuity; when the stress-strain curve formed by the stress-strain state is nonlinear, it is judged that fatigue damage has occurred in the preset area.

6. A nondestructive testing system for asphalt pavement according to claim 5, characterized in that: The method for drawing the stress-strain curve is: The stress and strain data of the preset area under different pressure conditions are recorded, and a stress-strain curve is drawn according to the stress and strain data.

7. A nondestructive testing method for asphalt pavement, applied to the nondestructive testing system for asphalt pavement according to any one of claims 1 to 6, characterized in that: The method comprises: Collect stress-strain state and temperature information of the asphalt pavement around the clock, and send the stress-strain state and temperature information of the asphalt pavement to a data analysis unit, the data analysis unit determines whether the asphalt pavement has defects according to the temperature information, and sends the defect information to the area determination module for secondary correction; Divide the asphalt pavement into a plurality of preset areas of the same size, number the preset areas respectively, determine the preset area number where the defect is located according to the defect information received from the data analysis unit, and send the preset area number and defect information to the status warning module; The stress-strain state of the defective preset area is obtained, the defect information is re-determined according to the stress-strain state, and a preset warning signal is matched according to the determined defect information, and the warning signal is sent to the user.

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