Road detection method and system based on ground penetrating radar

Abstract

The invention relates to the technical field of road detection, in particular to a road detection method and system based on a ground penetrating radar. The method comprises the following steps: acquiring radar image data of a to-be-detected road area; analyzing radar image data, and determining crack vertical features and filling area features; determining the type of the crack according to the vertical characteristics of the crack; calculating the upward reflection degree of the crack according to the characteristics of the filling area and the crack type; and generating a road state evaluation result according to the upward reflection degree. The false signal influence of crack development covered by the filling material is avoided, and the detection reliability is improved. The distortion influence of the filling material on the signal is reduced, underestimation or overestimation of the upward reflection degree caused by unintegrated filling area characteristics and crack types is avoided, and the accuracy of signal propagation evaluation is improved. The road state misjudgment caused by the upward reflection degree error is eliminated, and the practicability of road safety assessment is enhanced.

Description

Technical Field

[0001] The present application relates to the technical field of road detection, and in particular to a road detection method and system based on ground penetrating radar. Background Art

[0002] Road inspection is crucial for ensuring traffic safety and extending road life, especially for the early identification and assessment of road cracks. Ground-penetrating radar, a non-destructive inspection technology, has been widely used to detect the internal structure of roads.

[0003] However, existing road inspection methods based on ground-penetrating radar mostly focus on the hollowing problem of the road surface and can only identify surface anomalies. There are currently significant limitations in deep detection, which leads to misjudgment or missed detection, affecting the accurate assessment of road structure safety. Summary of the Invention

[0004] The present application provides a road detection method and system based on ground penetrating radar to solve the above problems.

[0005] In a first aspect, the present application provides a road detection method based on ground penetrating radar, the method comprising: Acquire radar image data of the road area to be detected; Analyzing the radar image data to determine vertical characteristics of the crack and characteristics of the filling area; determining the type of crack according to the vertical characteristics of the crack; Calculating the upward reflection degree of the crack according to the characteristics of the filling area and the type of the crack; A road condition assessment result is generated according to the upward reflection degree.

[0006] This solution acquires radar image data of the road area to be inspected, ensuring a reliable and complete raw data foundation and avoiding overall analysis bias caused by missing or distorted data. Radar image data is analyzed to determine the vertical characteristics of cracks and the characteristics of the infilled area. This reduces the misjudgment or missed detection of complex defects caused by ignoring vertical characteristics, avoids the impact of false signals caused by infill materials masking crack development, and improves detection reliability. Based on the vertical characteristics of the cracks, the crack type is determined, eliminating misjudgments of crack type caused by ignoring interference from the infilled area. This ensures that crack classification is consistent with the actual road structure and provides a basis for calculating the degree of upward reflection. Based on the characteristics of the infilled area and the crack type, the degree of upward reflection of the crack is calculated, reducing the signal distortion caused by the infilled material and avoiding underestimation or overestimation of the degree of upward reflection caused by not integrating the characteristics of the infilled area and the crack type, thereby improving the accuracy of signal propagation assessment. Based on the degree of upward reflection, a road condition assessment result is generated, eliminating misjudgments of road condition caused by errors in the degree of upward reflection and enhancing the practicality of road safety assessments.

[0007] Optionally, analyzing the radar image data to determine vertical characteristics of the crack and characteristics of the filling area includes: analyzing the radar image data to determine a dielectric constant distribution; spatially arranging and imaging the radar image data to obtain a radar cross-sectional view; Analyzing the radar cross-section to determine the strip-shaped strong reflection area and the continuity of the event axis; Determining the vertical characteristics of the crack based on the continuity of the event axis and the strip-shaped strong reflection area; According to the dielectric constant distribution, the filling area characteristics are determined.

[0008] This solution analyzes radar image data, determines the dielectric constant distribution, and avoids dielectric constant miscalculation. Spatially arranging and imaging the radar image data yields a radar cross-section that enhances the contrast of strip-shaped strong reflection areas and highlights the continuity of the event axis, eliminating the difficulty of directly analyzing radar image data. Analyzing the radar cross-section, the strip-shaped strong reflection areas and event axis continuity are determined, avoiding misjudgment of cracks due to ignoring event axis continuity and improving defect identification accuracy. Based on event axis continuity and strip-shaped strong reflection areas, the vertical characteristics of the crack are determined, eliminating the problem of being unable to determine the vertical characteristics of the crack and ensuring that the crack development path is accurately captured. Based on the dielectric constant distribution, the characteristics of the infill area are determined to avoid signal distortion caused by the infill material covering the crack.

[0009] Optionally, determining the crack type according to the vertical characteristics of the crack includes: Determining the fracture reflection layer according to the radar cross-section diagram; Analyzing the dielectric constant distribution based on the fracture reflection layer to determine the waveform phase characteristics; determining a phase polarity according to the waveform phase characteristic; The fracture type of the fracture reflection layer is determined according to the phase polarity.

[0010] This solution identifies crack reflection layers based on radar cross-sections, ensuring the crack's location within the road structure is extracted, supporting further analysis of the crack's vertical characteristics. Based on the crack reflection layers, the dielectric constant distribution is analyzed, waveform phase characteristics are determined, and the signal properties at the crack location are quantified, providing input data for phase polarity analysis. This ensures signal characteristics characterizing the crack, thereby distinguishing the electromagnetic response of the cracked area from that of the normal road medium. Based on the waveform phase characteristics, phase polarity is determined, simplifying the directional analysis of the crack signal and ensuring effective encoding of the crack's reflection behavior. Based on the phase polarity, the crack type of the crack reflection layer is determined, providing standardized output for road assessment and ensuring reliable identification of the crack type.

[0011] Optionally, the calculating the upward reflection degree of the crack according to the filling area characteristics and the crack type includes: Determining a dielectric constant gradient change of the filled area according to the characteristics of the filled area; determining the penetration depth of the filling material according to the dielectric constant gradient change; Analyzing the road area to be detected to determine the depth of the reflection layer; Calculating the vertical distance between the filling area and the crack according to the depth of the reflection layer; Analyzing the radar cross-section to determine waveform amplitude intensity; determining a signal attenuation difference between the filling material and the road surface based on the waveform amplitude strength; The upward reflection degree of the crack is calculated based on the vertical distance and the signal attenuation difference.

[0012] This solution determines the dielectric constant gradient within the infill area based on its characteristics, revealing the interference pattern of the infill material on the radar signal. This ensures a precise description of the infill material's three-dimensional profile and avoids signal distortion caused by unquantified gradient variations. The dielectric constant gradient is used to determine the infill material's penetration depth, reducing assessment bias caused by inaccurate penetration depth. The road area to be inspected is analyzed to determine the reflective layer depth, ensuring that distance calculations are based on the actual crack location rather than an estimate, thereby improving vertical distance accuracy. Based on the reflective layer depth, the vertical distance between the infill area and the crack is calculated, providing a path length parameter for calculating the upward reflection level, which influences the estimation of signal propagation attenuation. Radar cross-sections are analyzed to determine waveform amplitude, ensuring that attenuation calculations are based on actual reflection data rather than simulated values. Based on waveform amplitude, the difference in signal attenuation between the infill material and the road surface is determined, revealing the interference level of the infill material on the signal and avoiding intensity miscalculations caused by unquantified attenuation. Based on the vertical distance and signal attenuation difference, the upward reflection level of the crack is calculated to assess crack severity and potential risk.

[0013] Optionally, calculating the vertical distance between the filling area and the crack according to the depth of the reflective layer includes: Determining a reference plane according to the crack type; Based on the reference plane and according to the bit depth of the reflection layer, the vertical distance between the strip-shaped strong reflection area and the crack is calculated.

[0014] This solution determines a reference plane based on crack type, eliminating reference point inconsistencies caused by differences in crack type and reducing misjudgments. Based on the reference plane, the vertical distance between the strong reflective strip and the crack is calculated based on the depth of the reflection layer, preventing underestimation or overestimation of the upward reflection level and ensuring reliable road condition assessment results.

[0015] Optionally, determining the penetration depth of the filling material according to the dielectric constant gradient change includes: Analyzing the dielectric constant gradient change to determine the dielectric constant mutation interface between the filled area and the original road surface; Acquiring sampling information of the road area to be detected; obtaining a sampling point distribution of the dielectric constant along the depth direction based on the sampling information; The penetration depth of the filling material is determined according to the sudden interface and the distribution of the sampling points.

[0016] This solution analyzes dielectric constant gradient variations and identifies the interface where the dielectric constant abruptly changes between the filled area and the original pavement, thus avoiding depth misjudgments caused by blurred boundaries. Sampling information is obtained from the road area to be inspected, providing sufficient data support for generating a continuous distribution. Based on this sampling information, the dielectric constant sampling point distribution along the depth direction is determined, highlighting the transition characteristics from the filled area to the original pavement. Based on the abrupt interface and sampling point distribution, the penetration depth of the filling material is determined, eliminating the problem of filling masking cracks.

[0017] Optionally, determining the penetration depth of the filling material according to the sudden interface and the sampling point distribution includes: Obtaining road construction records, analyzing the road construction records, and determining the mixing parameters of the original filling material; Analyze radar cross-sections to determine event distortion patterns; Determining the curing shrinkage rate of the filling material according to the event axis distortion shape; Constructing a permeation attenuation function that takes material aging into consideration based on the mix ratio parameters and the curing shrinkage rate of the filling material; Establishing a three-dimensional penetration profile model of the filling material according to the attenuation function, the sudden interface and the sampling point distribution; The penetration depth of the filling material is determined based on the three-dimensional penetration profile model.

[0018] This solution obtains and analyzes road construction records to determine the original filler mix parameters, ensuring that penetration depth calculations are based on the actual material composition and avoiding model deviations caused by inaccurate mix ratios. Radar cross-sections are analyzed to determine the event distortion pattern and capture the signal interference characteristics of the filler material in actual road conditions. Based on the event distortion pattern, the filler material's curing shrinkage is determined, quantifying the physical changes caused by aging and providing parameters for constructing a penetration attenuation function. Based on the mix parameters and the filler material's curing shrinkage, a penetration attenuation function that accounts for material aging is constructed. This simulates the effects of aging on the filler material's penetration process, providing a dynamic calculation basis for a three-dimensional penetration profile model and ensuring that penetration depth assessments more closely reflect actual material degradation. A three-dimensional penetration profile model of the filler material is constructed based on the attenuation function, abrupt interfaces, and sampling point distribution. This model integrates aging effects with measured data, providing a visual framework for penetration depth extraction. Based on the three-dimensional penetration profile model, the filler material's penetration depth is determined, ensuring that the penetration depth value is based on comprehensive model data rather than simply sampling points.

[0019] Optionally, calculating the vertical distance between the filling area and the crack according to the depth of the reflective layer includes: Acquiring ground information of the road area to be detected; analyzing the ground information to determine the wheel track and lane center; determining, based on the radar cross-section image, a difference in asphalt thickness between the wheel track and the center of the lane; analyzing the wheel track to determine the wheel rut depth; The vertical distance between the filling area and the crack is calculated according to the crack type, the asphalt thickness difference, and the rutting depth.

[0020] This solution obtains ground information about the road area to be inspected, ensuring a reliable data source for identifying wheel tracks and lane centers. Ground information is analyzed to determine the wheel tracks and lane centers, providing a positioning reference for calculating asphalt thickness differences and eliminating the impact of positional errors. Based on the radar cross-section, the asphalt thickness difference between the wheel track and lane center is determined, correcting for deviations in the reflective layer depth caused by this thickness difference. The wheel track is analyzed to determine the rutting depth, reflecting road surface deformation and reducing signal propagation path errors. Based on the crack type, asphalt thickness difference, and rutting depth, the vertical distance between the filled area and the crack is calculated, eliminating deviations caused by structural inhomogeneities and improving the accuracy of the distance between the filled area and the crack.

[0021] Optionally, calculating the upward reflection degree of the crack according to the vertical distance and the signal attenuation difference includes: Performing time-frequency analysis on the radar cross-section diagram, and determining an energy attenuation ratio based on the time-frequency analysis results; constructing a multiple reflection path model based on the filling material penetration depth and the vertical distance; Calculating the shielding coefficient of the padded area for the upward reflected signal according to the multiple reflection path model; determining a dielectric constant gradient correction factor based on the signal attenuation difference; Based on the dielectric constant gradient correction factor, the upward reflection degree of the crack is calculated according to the shielding coefficient and the energy attenuation ratio.

[0022] This solution performs time-frequency analysis on radar cross-sections. Based on the results, the energy attenuation ratio is determined, eliminating the inability to determine the energy attenuation ratio due to a lack of time-frequency analysis of radar cross-sections. This also avoids underestimation or overestimation of the upward reflection level due to ignoring frequency offset. A multiple reflection path model is constructed based on the infill material penetration depth and vertical distance, eliminating the problem of ignoring the three-dimensional penetration profile of the infill material or failing to construct the multiple reflection path model, thereby improving the accuracy of shielding coefficient calculations. Based on the multiple reflection path model, the shielding coefficient of the infill area for the upward reflected signal is calculated, quantifying the degree of interference caused by the infill material on the upward reflected signal. This eliminates the problem of not quantifying the shielding effect of the infill material on the signal and avoiding distortion of the reflected signal caused by ignoring sudden changes in the dielectric constant of the infill material. A dielectric constant gradient correction factor is determined based on signal attenuation differences, eliminating the problem of not considering signal attenuation differences and failing to accurately determine the infill material penetration depth, thereby reflecting the actual road unevenness. Based on the dielectric constant gradient correction factor, the degree of upward reflection of the crack is calculated according to the shielding coefficient and energy attenuation ratio, eliminating the problems of erroneous upward reflection judgment and failure to integrate the characteristics of the filling area and the crack type, providing reliable road condition assessment and avoiding resource waste or safety accidents caused by not considering thickness differences and signal attenuation.

[0023] In a second aspect, the present application provides a road detection system based on ground penetrating radar, the system comprising: A data acquisition module, used to acquire radar image data of the road area to be detected scanned by the ground penetrating radar; A data analysis module, configured to analyze the radar image data to determine vertical crack characteristics and pipeline reflection characteristics; A crack analysis module, used to predict the development state of the crack and the degree of upward reflection based on the vertical characteristics of the crack; The pipeline analysis module is used to determine the pipeline damage location and damage type based on the pipeline reflection characteristics.

[0024] Optionally, the road detection system based on ground penetrating radar further includes a feature determination module, which is used to: analyzing the radar image data to determine a dielectric constant distribution; spatially arranging and imaging the radar image data to obtain a radar cross-sectional view; Analyzing the radar cross-section to determine the strip-shaped strong reflection area and the continuity of the event axis; Determining the vertical characteristics of the crack based on the continuity of the event axis and the strip-shaped strong reflection area; According to the dielectric constant distribution, the filling area characteristics are determined.

[0025] Optionally, the road detection system based on ground penetrating radar further includes a type determination module, which is used to: Determining the fracture reflection layer according to the radar cross-section diagram; Analyzing the dielectric constant distribution based on the fracture reflection layer to determine the waveform phase characteristics; determining a phase polarity according to the waveform phase characteristic; The fracture type of the fracture reflection layer is determined according to the phase polarity.

[0026] Optionally, the road detection system based on ground penetrating radar further includes a degree calculation module, which is used to: Determining a dielectric constant gradient change of the filled area according to the characteristics of the filled area; determining the penetration depth of the filling material according to the dielectric constant gradient change; Analyzing the road area to be detected to determine the depth of the reflection layer; Calculating the vertical distance between the filling area and the crack according to the depth of the reflection layer; Analyzing the radar cross-section to determine waveform amplitude intensity; determining a signal attenuation difference between the filling material and the road surface based on the waveform amplitude strength; The upward reflection degree of the crack is calculated based on the vertical distance and the signal attenuation difference.

[0027] Optionally, when the degree calculation module calculates the vertical distance between the filling area and the crack according to the depth of the reflection layer, it is used to: Determining a reference plane according to the crack type; Based on the reference plane and according to the bit depth of the reflection layer, the vertical distance between the strip-shaped strong reflection area and the crack is calculated.

[0028] Optionally, when determining the penetration depth of the filling material according to the dielectric constant gradient change, the degree calculation module is used to: Analyzing the dielectric constant gradient change to determine the dielectric constant mutation interface between the filled area and the original road surface; Acquiring sampling information of the road area to be detected; obtaining a sampling point distribution of the dielectric constant along the depth direction based on the sampling information; The penetration depth of the filling material is determined according to the sudden interface and the distribution of the sampling points.

[0029] Optionally, when determining the penetration depth of the filling material according to the sudden interface and the sampling point distribution, the degree calculation module is used to: Obtaining road construction records, analyzing the road construction records, and determining the mixing parameters of the original filling material; Analyze radar cross-sections to determine event distortion patterns; Determining the curing shrinkage rate of the filling material according to the event axis distortion shape; Constructing a permeation attenuation function that takes material aging into consideration based on the mix ratio parameters and the curing shrinkage rate of the filling material; Establishing a three-dimensional penetration profile model of the filling material according to the attenuation function, the sudden interface and the sampling point distribution; The penetration depth of the filling material is determined based on the three-dimensional penetration profile model.

[0030] Optionally, when the degree calculation module calculates the vertical distance between the filling area and the crack according to the depth of the reflection layer, it is used to: Acquiring ground information of the road area to be detected; analyzing the ground information to determine the wheel track and lane center; determining, based on the radar cross-section image, a difference in asphalt thickness between the wheel track and the center of the lane; analyzing the wheel track to determine the wheel rut depth; The vertical distance between the filling area and the crack is calculated according to the crack type, the asphalt thickness difference, and the rutting depth.

[0031] Optionally, when the degree calculation module calculates the upward reflection degree of the crack according to the vertical distance and the signal attenuation difference, it is configured to: Performing time-frequency analysis on the radar cross-section diagram, and determining an energy attenuation ratio based on the time-frequency analysis results; constructing a multiple reflection path model based on the filling material penetration depth and the vertical distance; Calculating the shielding coefficient of the padded area for the upward reflected signal according to the multiple reflection path model; determining a dielectric constant gradient correction factor based on the signal attenuation difference; Based on the dielectric constant gradient correction factor, the upward reflection degree of the crack is calculated according to the shielding coefficient and the energy attenuation ratio. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0033] Figure 1 A schematic diagram of an application scenario provided in one embodiment of the present application; Figure 2 A flow chart of a road detection method based on ground penetrating radar provided in one embodiment of the present application; Figure 3 A schematic structural diagram of a road detection system based on ground penetrating radar provided in one embodiment of the present application. DETAILED DESCRIPTION

[0034] To make the purpose, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0035] In this document, the term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document, unless otherwise specified, generally indicates an "or" relationship between the related objects.

[0036] The embodiments of the present application are described in further detail below with reference to the accompanying drawings.

[0037] Existing road inspection methods based on ground-penetrating radar mostly focus on the hollowing problem of the road surface and can only identify surface anomalies. There are currently significant limitations in deep detection, which leads to misjudgments or missed detections, affecting the accurate assessment of road structure safety.

[0038] For example, it can provide effective detection for road surfaces without other impurities, but if there are traces of repairs in certain areas, it is difficult to correctly determine whether there are new cracks or incomplete repairs.

[0039] Based on this, the present application provides a road detection method and system based on ground-penetrating radar, which obtains radar image data of the road area to be detected, ensures a reliable and complete original data foundation, and avoids overall analysis deviations caused by missing or distorted data. The radar image data is analyzed to determine the vertical characteristics of the cracks and the characteristics of the filling area, reduce the misjudgment or missed detection of composite defects caused by ignoring the vertical characteristics, avoid the influence of false signals caused by the filling material covering the development of cracks, and improve detection reliability. According to the vertical characteristics of the cracks, the crack type is determined, and the misjudgment of the crack type caused by ignoring the interference of the filling area is eliminated, ensuring that the crack classification is consistent with the actual structure of the road, and providing a basis for calculating the upward reflection degree. According to the filling area characteristics and crack type, the upward reflection degree of the crack is calculated, reducing the distortion effect of the filling material on the signal, avoiding the underestimation or overestimation of the upward reflection degree caused by not integrating the filling area characteristics and crack type, and improving the accuracy of signal propagation assessment. According to the upward reflection degree, a road status assessment result is generated, eliminating the misjudgment of the road status caused by the error in the upward reflection degree, and enhancing the practicality of road safety assessment.

[0040] Figure 1 This is a schematic diagram of an application scenario provided by this application. When performing road detection, the method provided by this application is applied.

[0041] Specifically, the method provided in the present application is applied to any server, and the server interacts with the built-in camera device of the ground-penetrating radar equipment to obtain radar image data of the road area to be detected through the built-in camera device of the ground-penetrating radar equipment. The radar image data is analyzed to determine the vertical characteristics of the crack and the characteristics of the filling area. According to the vertical characteristics of the crack, the type of crack is determined. According to the characteristics of the filling area and the type of crack, the upward reflection degree of the crack is calculated to reduce the distortion effect of the filling material on the signal, avoid underestimation or overestimation of the upward reflection degree due to the failure to integrate the filling area characteristics and the crack type, and improve the accuracy of the signal propagation assessment. According to the upward reflection degree, a road status assessment result is generated to eliminate the misjudgment of the road status caused by the error in the upward reflection degree, thereby enhancing the practicality of the road safety assessment.

[0042] For specific implementation methods, please refer to the following embodiments.

[0043] Figure 2 This is a flow chart of a road detection method based on ground penetrating radar provided in one embodiment of the present application. The method of this embodiment can be applied to the server in the above scenario. Figure 2 As shown, the method includes: S201, obtaining radar image data of a road area to be detected; The road area to be detected may be a road area that requires ground penetrating radar detection.

[0044] Radar image data may be image data formed by reflection of electromagnetic waves.

[0045] Specifically, a scanning path is set in the road area; then, the ground-penetrating radar device is started to collect data on the road area to be inspected; then, the original electromagnetic wave signal is converted into analyzable radar image data through the built-in processor of the ground-penetrating radar device.

[0046] S202, analyzing radar image data to determine vertical characteristics of the crack and characteristics of the filling area; The vertical characteristic of the crack may be a signal characteristic of the crack in the vertical direction.

[0047] The filling area feature may be a signal feature of the filling material in the radar image.

[0048] Specifically, radar image data is analyzed and signal processing algorithms are used to identify areas of high reflection intensity within the image data. Whether vertical stripes are present is detected, and the continuity of the event axis is evaluated to determine the vertical characteristics of the crack. Variations in the reflection amplitude of the radar image data are simultaneously analyzed to infer the dielectric constant distribution. Simultaneously, the dielectric constant gradient is calculated. Finally, the dielectric constant distribution and dielectric constant gradient are integrated to determine the characteristics of the infilled area.

[0049] S203, determining the crack type based on the vertical characteristics of the crack; Crack types can be classified based on the vertical characteristics of the cracks.

[0050] Specifically, based on the vertical characteristics of the cracks, classification and judgment are performed through the rule engine to determine the crack type.

[0051] S204, calculating the upward reflection degree of the crack according to the characteristics of the filling area and the crack type; Cracks can be breaks in the road structure.

[0052] The degree of upward reflection can be an indicator of the strength of the upward propagation of the crack signal.

[0053] Specifically, based on the characteristics of the filled area, a signal attenuation model is constructed by simulating the propagation and attenuation of electromagnetic waves in the filling material. Then, the signal attenuation model is adjusted in combination with the crack type. Subsequently, the actual road factors extracted from the radar image data are integrated to quantify the signal shielding effect through multiple reflection path simulation. Finally, the degree of upward reflection of the crack is calculated.

[0054] S205: Generate a road condition assessment result based on the degree of upward reflection.

[0055] The road state evaluation result may be an evaluation result generated based on the degree of upward reflection.

[0056] Specifically, based on the upward reflection degree interval distribution characteristics of historical detection data statistics, a threshold rule is applied to match the upward reflection degree to the state category, thereby generating a road state assessment result.

[0057] This solution acquires radar image data of the road area to be inspected, ensuring a reliable and complete raw data foundation and avoiding overall analysis bias caused by missing or distorted data. Radar image data is analyzed to determine the vertical characteristics of cracks and the characteristics of the infilled area. This reduces the misjudgment or missed detection of complex defects caused by ignoring vertical characteristics, avoids the impact of false signals caused by infill materials masking crack development, and improves detection reliability. Based on the vertical characteristics of the cracks, the crack type is determined, eliminating misjudgments of crack type caused by ignoring interference from the infilled area. This ensures that crack classification is consistent with the actual road structure and provides a basis for calculating the degree of upward reflection. Based on the characteristics of the infilled area and the crack type, the degree of upward reflection of the crack is calculated, reducing the signal distortion caused by the infilled material and avoiding underestimation or overestimation of the degree of upward reflection caused by not integrating the characteristics of the infilled area and the crack type, thereby improving the accuracy of signal propagation assessment. Based on the degree of upward reflection, a road condition assessment result is generated, eliminating misjudgments of road condition caused by errors in the degree of upward reflection and enhancing the practicality of road safety assessments.

[0058] In some embodiments, radar image data is analyzed to determine the dielectric constant distribution; the radar image data is spatially arranged and image-processed to obtain a radar cross-sectional view; the radar cross-sectional view is analyzed to determine the strip-shaped strong reflection area and the continuity of the phase axis; based on the continuity of the phase axis and the strip-shaped strong reflection area, the vertical characteristics of the crack are determined; based on the dielectric constant distribution, the characteristics of the filling area are determined.

[0059] The dielectric constant distribution may be a distribution of dielectric constant values in different regions of the road material.

[0060] The radar cross section diagram can be a two-dimensional visualization image generated through spatial arrangement and imaging processing.

[0061] The strip-shaped strong reflection area may be a strip-shaped area with high reflection intensity in the radar cross section.

[0062] Event continuity can be the continuity of the radar signal phase in the vertical direction.

[0063] Specifically, the signal amplitude and phase values of each data point are extracted from the radar image data. Then, using a pre-defined electromagnetic wave propagation model based on the theory of electromagnetic wave propagation in road media, the dielectric constant value of each sampling point on the road is inverted and calculated. The dielectric constant values are then mapped to spatial coordinates to determine the dielectric constant distribution. Furthermore, the radar image data is spatially arranged according to the acquisition location, and each data point is mapped onto a two-dimensional grid array based on its horizontal and vertical coordinates on the road. This two-dimensional grid array is then subjected to image processing, such as signal intensity normalization and grayscale conversion, to generate a radar cross-section. Based on the radar cross-section, an image analysis algorithm is used to identify strip-shaped areas of strong reflection. Phase information is extracted from the radar cross-section, and the vertical continuity of the reflected signal is examined to determine the event continuity. The vertical distribution of the strip-shaped areas of strong reflection is then compared with the locations of the interruptions in the event continuity to calculate the depth, range, and direction of the cracks, thereby determining their vertical characteristics. Finally, a region segmentation algorithm is used to locate abnormal areas of dielectric constant distribution. Characteristic parameters of these abnormal areas are then extracted and identified as the filling area features.

[0064] This solution analyzes radar image data, determines the dielectric constant distribution, and avoids dielectric constant miscalculation. Spatially arranging and imaging the radar image data yields a radar cross-section that enhances the contrast of strip-shaped strong reflection areas and highlights the continuity of the event axis, eliminating the difficulty of directly analyzing radar image data. Analyzing the radar cross-section, the strip-shaped strong reflection areas and event axis continuity are determined, avoiding misjudgment of cracks due to ignoring event axis continuity and improving defect identification accuracy. Based on event axis continuity and strip-shaped strong reflection areas, the vertical characteristics of the crack are determined, eliminating the problem of being unable to determine the vertical characteristics of the crack and ensuring that the crack development path is accurately captured. Based on the dielectric constant distribution, the characteristics of the infill area are determined to avoid signal distortion caused by the infill material covering the crack.

[0065] In some embodiments, the crack reflection layer is determined based on the radar cross-section; based on the crack reflection layer, the dielectric constant distribution is analyzed to determine the waveform phase characteristics; based on the waveform phase characteristics, the phase polarity is determined; based on the phase polarity, the crack type of the crack reflection layer is determined.

[0066] The fracture reflection layer may be a reflection position of the fracture in a radar cross section.

[0067] The waveform phase feature may be a phase characteristic of the radar signal.

[0068] Phase polarity can be a positive or negative attribute of the phase.

[0069] Specifically, a radar cross-section image is loaded, and each pixel is traversed. A preset threshold is established based on electromagnetic wave reflection theory. Continuous strips with reflection intensities exceeding the preset threshold are detected. Then, using a connected domain analysis algorithm, the geometric center coordinates and vertical depth range of the continuous strips are extracted as the fracture reflection layer. Subsequently, the dielectric constant distribution is queried based on the coordinates of the fracture reflection layer to determine the dielectric constant. Furthermore, based on the raw phase record of the radar image data, the phase values of the corresponding data points in the fracture reflection layer are extracted. Based on the phase values, the waveform phase characteristics are determined. Furthermore, based on the waveform phase characteristics, the sign or direction of the phase values is analyzed to determine the phase polarity. Finally, based on the phase polarity, a preset mapping rule is established based on the correspondence between the radar signal phase sign and the fracture reflection behavior to experimentally determine the fracture type of the fracture reflection layer.

[0070] This solution identifies crack reflection layers based on radar cross-sections, ensuring the crack's location within the road structure is extracted, supporting further analysis of the crack's vertical characteristics. Based on the crack reflection layers, the dielectric constant distribution is analyzed, waveform phase characteristics are determined, and the signal properties at the crack location are quantified, providing input data for phase polarity analysis. This ensures signal characteristics characterizing the crack, thereby distinguishing the electromagnetic response of the cracked area from that of the normal road medium. Based on the waveform phase characteristics, phase polarity is determined, simplifying the directional analysis of the crack signal and ensuring effective encoding of the crack's reflection behavior. Based on the phase polarity, the crack type of the crack reflection layer is determined, providing standardized output for road assessment and ensuring reliable identification of the crack type.

[0071] In some embodiments, based on the characteristics of the filled area, the dielectric constant gradient change of the filled area is determined; based on the dielectric constant gradient change, the penetration depth of the filling material is determined; the road area to be inspected is analyzed to determine the depth of the reflection layer; based on the depth of the reflection layer, the vertical distance between the filled area and the crack is calculated; the radar cross-sectional view is analyzed to determine the waveform amplitude intensity; based on the waveform amplitude intensity, the signal attenuation difference between the filling material and the road surface is determined; based on the vertical distance and the signal attenuation difference, the upward reflection degree of the crack is calculated.

[0072] A filled area may be an area of a roadway covered with fill material.

[0073] The dielectric constant gradient variation may be the spatial rate of change of the dielectric constant.

[0074] The filling material penetration depth may be a depth value of the filling material penetrating into the inside of the road.

[0075] The reflection layer depth may be the vertical depth of the fracture reflection layer in the radar cross section.

[0076] The vertical distance may be the vertical separation distance between the filled area and the crack.

[0077] The waveform amplitude strength may be the strength magnitude of the radar signal.

[0078] Filling material can be the material used to repair cracks in roads.

[0079] The road surface may be the normal surface area of a road.

[0080] The signal attenuation difference may be the difference in attenuation degree between the filling material and the road surface in signal propagation.

[0081] Specifically, the method analyzes the characteristics of the infill area and extracts the dielectric constants of consecutive sampling points within the infill area by querying the dielectric constant distribution. The dielectric constant difference between adjacent sampling points is then calculated to determine the dielectric constant gradient. Based on the dielectric constant gradient, locations with significant gradient changes are identified, corresponding to the infill material penetration boundary. The vertical depth is then extracted from the depth coordinates of the radar cross-section image as the infill material penetration depth. Furthermore, the crack reflection layer is located based on the radar cross-section image of the road area to be inspected. The geometric center coordinates are then extracted using a connected domain analysis algorithm. The vertical depth is then read from the geometric center coordinates as the reflection layer depth. Based on the infill material penetration depth and the reflection layer depth, the difference between the infill material penetration depth and the reflection layer depth is calculated, representing the vertical distance between the infill area and the crack. The original radar cross-section image is then queried based on the coordinates of the crack reflection layer. The corresponding waveform amplitude is then extracted to determine the amplitude strength. Next, based on the waveform amplitude intensity, the reference amplitude values of the road surface extracted from the filled area and the unaffected area of the radar cross-section are compared. The amplitude intensity ratio is then calculated to determine the difference in signal attenuation between the filling material and the road surface. Finally, the degree of upward reflection from the crack is calculated using a preset weighting, combining the vertical distance and the difference in signal attenuation.

[0082] This solution determines the dielectric constant gradient within the infill area based on its characteristics, revealing the interference pattern of the infill material on the radar signal. This ensures a precise description of the infill material's three-dimensional profile and avoids signal distortion caused by unquantified gradient variations. The dielectric constant gradient is used to determine the infill material's penetration depth, reducing assessment bias caused by inaccurate penetration depth. The road area to be inspected is analyzed to determine the reflective layer depth, ensuring that distance calculations are based on the actual crack location rather than an estimate, thereby improving vertical distance accuracy. Based on the reflective layer depth, the vertical distance between the infill area and the crack is calculated, providing a path length parameter for calculating the upward reflection level, which influences the estimation of signal propagation attenuation. Radar cross-sections are analyzed to determine waveform amplitude, ensuring that attenuation calculations are based on actual reflection data rather than simulated values. Based on waveform amplitude, the difference in signal attenuation between the infill material and the road surface is determined, revealing the interference level of the infill material on the signal and avoiding intensity miscalculations caused by unquantified attenuation. Based on the vertical distance and signal attenuation difference, the upward reflection level of the crack is calculated to assess crack severity and potential risk.

[0083] In some embodiments, a reference plane is determined according to the type of crack; based on the reference plane, the vertical distance between the strip-shaped strong reflection area and the crack is calculated according to the depth of the reflection layer.

[0084] The datum plane may be a reference plane determined based on the crack type.

[0085] Specifically, based on the crack type, the crack type is mapped to the corresponding reference plane using preset rules. Then, based on the reference plane and radar cross-section, the reflector depth of the strip-shaped strong reflection area is extracted. The difference between the reference plane and the reflector depth is then calculated as the vertical distance between the strip-shaped strong reflection area and the crack.

[0086] This solution determines a reference plane based on crack type, eliminating reference point inconsistencies caused by differences in crack type and reducing misjudgments. Based on the reference plane, the vertical distance between the strong reflective strip and the crack is calculated based on the depth of the reflection layer, preventing underestimation or overestimation of the upward reflection level and ensuring reliable road condition assessment results.

[0087] In some embodiments, the dielectric constant gradient change is analyzed to determine the dielectric constant mutation interface between the filled area and the original road surface; sampling information of the road area to be inspected is obtained; based on the sampling information, the sampling point distribution of the dielectric constant along the depth direction is obtained; based on the mutation interface and the sampling point distribution, the penetration depth of the filling material is determined.

[0088] Native pavement may be the original road material that has not been filled.

[0089] The dielectric constant mutation interface can be the depth location where the dielectric constant between the filled area and the original pavement changes significantly.

[0090] The sampling information may be point data obtained from ground penetrating radar data.

[0091] The depth direction may be a direction perpendicular to the road surface.

[0092] The dielectric constant may be a dielectric characteristic parameter.

[0093] The sampling point distribution may be a sequence of dielectric constant sampling points distributed along the depth direction.

[0094] Specifically, a preset threshold is set based on the empirical value of the dielectric constant difference between the infill material and the original pavement in electromagnetic wave reflection theory. Next, the depth location where the dielectric constant gradient exceeds the preset threshold is identified and marked as the dielectric constant abrupt change interface between the infill area and the original pavement. A ground-penetrating radar antenna is then moved across the road surface of the road to be inspected, transmitting electromagnetic waves and receiving reflected signals. The depth location and corresponding dielectric constant of each sampling point are recorded to form sampling information. The sampling points in this sampling information are then sorted in ascending order by depth value. Interpolation is then used to process the sorted sampling points to generate a depth-wise dielectric constant sampling point distribution. Based on the sampling point distribution, the depth location of the dielectric constant abrupt change interface is located. Based on the depth location, the sampling point distribution is scanned downward until the dielectric constant stabilizes at a typical value for the original pavement. Finally, the difference between the abrupt change interface depth and the typical value is calculated as the infill material penetration depth.

[0095] This solution analyzes dielectric constant gradient variations and identifies the interface where the dielectric constant abruptly changes between the filled area and the original pavement, thus avoiding depth misjudgments caused by blurred boundaries. Sampling information is obtained from the road area to be inspected, providing sufficient data support for generating a continuous distribution. Based on this sampling information, the dielectric constant sampling point distribution along the depth direction is determined, highlighting the transition characteristics from the filled area to the original pavement. Based on the abrupt interface and sampling point distribution, the penetration depth of the filling material is determined, eliminating the problem of filling masking cracks.

[0096] In some embodiments, road construction records are obtained and analyzed to determine the proportion parameters of the original filling material; radar cross-sectional images are analyzed to determine the distortion morphology of the event axis; based on the distortion morphology of the event axis, the curing shrinkage rate of the filling material is determined; based on the proportion parameters and the curing shrinkage rate of the filling material, a penetration attenuation function that takes into account material aging is constructed; based on the attenuation function, the mutation interface and the sampling point distribution, a three-dimensional penetration profile model of the filling material is established; based on the three-dimensional penetration profile model, the penetration depth of the filling material is determined.

[0097] The road construction record may be a construction record in a historical road maintenance database.

[0098] The original filler material may be the initial filling material used for road crack repair.

[0099] The ratio parameter may be a weight percentage parameter of each component in the filling material.

[0100] The event axis distortion may be a distortion characteristic of the electromagnetic wave reflection signal.

[0101] The curing shrinkage rate of the filling material may be the ratio of the volume shrinkage of the filling material during the curing process.

[0102] Material aging can be the process by which a filling material degrades over time.

[0103] The permeation attenuation function may be a mathematical function that describes the attenuation of the permeation characteristics of the filling material due to aging.

[0104] The three-dimensional infiltration profile model may be a model of the three-dimensional distribution of the filling material in the road.

[0105] Specifically, road construction records were extracted from a road maintenance database. A data query tool was then used to query the mix table fields within the records and extract the mix parameters of the original filling material. Furthermore, based on radar cross-sectional images, an image processing algorithm was applied to identify the event distortion morphology. This event distortion morphology was then mapped to the curing shrinkage of the filling material. Based on the mix parameters and the curing shrinkage of the filling material, the material aging effect was integrated to construct a permeation attenuation function that simulates the effect of material aging on the dielectric constant. This permeation attenuation function was then applied to adjust the dielectric constant in the sampling point distribution. Based on the depth position of the abrupt interface, a spatial interpolation method was used to expand the adjusted sampling point distribution into three dimensions, thereby establishing a three-dimensional permeation profile model of the filling material. Finally, based on the three-dimensional permeation profile model, the model was scanned downward along the depth direction according to the depth position of the dielectric constant abrupt interface to determine the penetration depth of the filling material.

[0106] This solution obtains and analyzes road construction records to determine the original filler mix parameters, ensuring that penetration depth calculations are based on the actual material composition and avoiding model deviations caused by inaccurate mix ratios. Radar cross-sections are analyzed to determine the event distortion pattern and capture the signal interference characteristics of the filler material in actual road conditions. Based on the event distortion pattern, the filler material's curing shrinkage is determined, quantifying the physical changes caused by aging and providing parameters for constructing a penetration attenuation function. Based on the mix parameters and the filler material's curing shrinkage, a penetration attenuation function that accounts for material aging is constructed. This simulates the effects of aging on the filler material's penetration process, providing a dynamic calculation basis for a three-dimensional penetration profile model and ensuring that penetration depth assessments more closely reflect actual material degradation. A three-dimensional penetration profile model of the filler material is constructed based on the attenuation function, abrupt interfaces, and sampling point distribution. This model integrates aging effects with measured data, providing a visual framework for penetration depth extraction. Based on the three-dimensional penetration profile model, the filler material's penetration depth is determined, ensuring that the penetration depth value is based on comprehensive model data rather than simply sampling points.

[0107] In some embodiments, ground information of the road area to be inspected is obtained; the ground information is analyzed to determine the wheel track and lane center; the asphalt thickness difference between the wheel track and lane center is determined based on the radar cross-sectional diagram; the wheel track is analyzed to determine the rutting depth; and the vertical distance between the filling area and the crack is calculated based on the crack type, asphalt thickness difference, and rutting depth.

[0108] The ground information may be surface data of the road area to be detected.

[0109] Wheel tracks may be areas of the road surface that are depressed by vehicle loads.

[0110] The lane center may be the centerline location of a road lane.

[0111] Asphalt thickness difference can be the difference in reflective layer depth between the wheel track and the center of the lane.

[0112] The rut depth can be the difference between the average surface elevation and the lowest point elevation within the wheel track area.

[0113] Specifically, the scanning device is moved along the road surface of the road area to be inspected, recording surface elevation, coordinate location, and texture information in real time to generate ground information. Preset thresholds are then established for the sunken areas of the road surface identified using this ground information. Wheel tracks are then marked based on the preset thresholds. Lane centers are then determined using a lane recognition algorithm. Image analysis tools are then used to locate the corresponding reflective layer depths of the wheel tracks and lane centers in the radar cross-section image. The asphalt thickness difference is then determined based on the reflective layer depths of the wheel tracks and the lane center. The rutting depth is then calculated as the difference between the average surface elevation and the lowest point within the wheel track coordinate range. Finally, based on the crack type, asphalt thickness differences, and rutting depth, a predefined formula developed using a physical propagation model of electromagnetic wave reflection and attenuation from ground-penetrating radar is used to calculate the vertical distance between the filled area and the crack.

[0114] This solution obtains ground information about the road area to be inspected, ensuring a reliable data source for identifying wheel tracks and lane centers. Ground information is analyzed to determine the wheel tracks and lane centers, providing a positioning reference for calculating asphalt thickness differences and eliminating the impact of positional errors. Based on the radar cross-section, the asphalt thickness difference between the wheel track and lane center is determined, correcting for deviations in the reflective layer depth caused by this thickness difference. The wheel track is analyzed to determine the rutting depth, reflecting road surface deformation and reducing signal propagation path errors. Based on the crack type, asphalt thickness difference, and rutting depth, the vertical distance between the filled area and the crack is calculated, eliminating deviations caused by structural inhomogeneities and improving the accuracy of the distance between the filled area and the crack.

[0115] In some embodiments, a time-frequency analysis is performed on the radar cross-section diagram, and the energy attenuation ratio is determined based on the time-frequency analysis results; a multiple reflection path model is constructed based on the penetration depth and vertical distance of the filling material; based on the multiple reflection path model, the shielding coefficient of the filling area for the upward reflected signal is calculated; based on the signal attenuation difference, the dielectric constant gradient correction factor is determined; based on the dielectric constant gradient correction factor, the degree of upward reflection of the crack is calculated according to the shielding coefficient and the energy attenuation ratio.

[0116] The time-frequency analysis result may be a time-frequency spectrum diagram generated after performing time-frequency analysis on the radar cross-section diagram.

[0117] The energy attenuation ratio may be a percentage value of the signal energy loss rate.

[0118] The multiple reflection path model may be a road medium layered structure model used to simulate multiple reflection paths of signals between filling material layers, crack layers, and road surface layers.

[0119] The upward reflected signal may be an electromagnetic wave reflected signal that propagates from the road crack position toward the ground surface.

[0120] The shielding coefficient can be a dimensionless value that characterizes the degree to which the padded area absorbs or scatters the upward reflected signal.

[0121] The dielectric constant gradient correction factor can be used to adjust the calculated slope of the dielectric constant change with depth.

[0122] Specifically, the signal's time series data is extracted from radar cross-sections. A time-frequency analysis algorithm is then used to decompose the signal into time-frequency domain components, generating a time-frequency spectrum. Signal energy values within each frequency band are then extracted from the time-frequency spectrum. The energy intensity difference between the signal at the GPR source location and the crack reflection location is then compared to determine the energy attenuation ratio. An electromagnetic wave propagation simulation tool is then used to construct a multiple reflection path model based on the infill material penetration depth and vertical distance. Based on this multiple reflection path model, electromagnetic wave propagation formulas are applied, incorporating the known attenuation characteristics of the infill material, to calculate the signal intensity loss for each path. The losses from these multiple paths are then integrated to calculate the shielding coefficient of the infill area against upwardly reflected signals. Furthermore, the signal attenuation differences are analyzed to extract the dielectric constant gradient variation corresponding to the infill material penetration depth. Based on empirical correlations, a dielectric constant gradient correction factor is then calculated using interpolation. Finally, the dielectric constant gradient correction factor is used to correct the dielectric constant gradient and, combined with the shielding coefficient and energy attenuation ratio, the degree of upward reflection is determined using a weighted sum calculation.

[0123] This solution performs time-frequency analysis on radar cross-sections. Based on the results, the energy attenuation ratio is determined, eliminating the inability to determine the energy attenuation ratio due to a lack of time-frequency analysis of radar cross-sections. This also avoids underestimation or overestimation of the upward reflection level due to ignoring frequency offset. A multiple reflection path model is constructed based on the infill material penetration depth and vertical distance, eliminating the problem of ignoring the three-dimensional penetration profile of the infill material or failing to construct the multiple reflection path model, thereby improving the accuracy of shielding coefficient calculations. Based on the multiple reflection path model, the shielding coefficient of the infill area for the upward reflected signal is calculated, quantifying the degree of interference caused by the infill material on the upward reflected signal. This eliminates the problem of not quantifying the shielding effect of the infill material on the signal and avoiding distortion of the reflected signal caused by ignoring sudden changes in the dielectric constant of the infill material. A dielectric constant gradient correction factor is determined based on signal attenuation differences, eliminating the problem of not considering signal attenuation differences and failing to accurately determine the infill material penetration depth, thereby reflecting the actual road unevenness. Based on the dielectric constant gradient correction factor, the degree of upward reflection of the crack is calculated according to the shielding coefficient and energy attenuation ratio, eliminating the problems of erroneous upward reflection judgment and failure to integrate the characteristics of the filling area and the crack type, providing reliable road condition assessment and avoiding resource waste or safety accidents caused by not considering thickness differences and signal attenuation.

[0124] Figure 3A schematic diagram of a road detection system based on ground penetrating radar is provided in one embodiment of the present application. Figure 3 As shown, the road detection system 300 based on the ground penetrating radar of this embodiment includes: a data acquisition module 301 , a data analysis module 302 , a crack analysis module 303 , and a pipeline analysis module 304 .

[0125] The data acquisition module 301 is used to acquire radar image data of the road area to be detected scanned by the ground penetrating radar; A data analysis module 302 is used to analyze the radar image data to determine the vertical characteristics of the crack and the reflection characteristics of the pipeline; The crack analysis module 303 is used to predict the development state and upward reflection degree of the crack according to the vertical characteristics of the crack; The pipeline analysis module 304 is used to determine the pipeline damage location and damage type based on the pipeline reflection characteristics.

[0126] Optionally, the road detection system based on ground penetrating radar further includes a feature determination module 305, which is used to: analyzing the radar image data to determine a dielectric constant distribution; spatially arranging and imaging the radar image data to obtain a radar cross-sectional view; Analyzing the radar cross-section to determine the strip-shaped strong reflection area and the continuity of the event axis; Determining the vertical characteristics of the crack based on the continuity of the event axis and the strip-shaped strong reflection area; According to the dielectric constant distribution, the filling area characteristics are determined.

[0127] Optionally, the ground penetrating radar-based road detection system further includes a type determination module 306, configured to: Determining the fracture reflection layer according to the radar cross-section diagram; Analyzing the dielectric constant distribution based on the fracture reflection layer to determine the waveform phase characteristics; determining a phase polarity according to the waveform phase characteristic; The fracture type of the fracture reflection layer is determined according to the phase polarity.

[0128] Optionally, the road detection system based on ground penetrating radar further includes a degree calculation module 307 for: Determining a dielectric constant gradient change of the filled area according to the characteristics of the filled area; determining the penetration depth of the filling material according to the dielectric constant gradient change; Analyzing the road area to be detected to determine the depth of the reflection layer; Calculating the vertical distance between the filling area and the crack according to the depth of the reflection layer; Analyzing the radar cross-section to determine waveform amplitude intensity; determining a signal attenuation difference between the filling material and the road surface based on the waveform amplitude strength; The upward reflection degree of the crack is calculated based on the vertical distance and the signal attenuation difference.

[0129] Optionally, when the degree calculation module 307 calculates the vertical distance between the filling area and the crack according to the depth of the reflection layer, it is used to: Determining a reference plane according to the crack type; Based on the reference plane and according to the bit depth of the reflection layer, the vertical distance between the strip-shaped strong reflection area and the crack is calculated.

[0130] Optionally, when determining the penetration depth of the filling material according to the dielectric constant gradient change, the degree calculation module 307 is used to: Analyzing the dielectric constant gradient change to determine the dielectric constant mutation interface between the filled area and the original road surface; Acquiring sampling information of the road area to be detected; obtaining a sampling point distribution of the dielectric constant along the depth direction based on the sampling information; The penetration depth of the filling material is determined according to the sudden interface and the distribution of the sampling points.

[0131] Optionally, when determining the penetration depth of the filling material according to the sudden interface and the sampling point distribution, the degree calculation module 307 is used to: Obtaining road construction records, analyzing the road construction records, and determining the mixing parameters of the original filling material; Analyze radar cross-sections to determine event distortion patterns; Determining the curing shrinkage rate of the filling material according to the event axis distortion shape; Constructing a permeation attenuation function that takes material aging into consideration based on the mix ratio parameters and the curing shrinkage rate of the filling material; Establishing a three-dimensional penetration profile model of the filling material according to the attenuation function, the sudden interface and the sampling point distribution; The penetration depth of the filling material is determined based on the three-dimensional penetration profile model.

[0132] Optionally, when the degree calculation module 307 calculates the vertical distance between the filling area and the crack according to the depth of the reflection layer, it is used to: Acquiring ground information of the road area to be detected; analyzing the ground information to determine the wheel track and lane center; determining, based on the radar cross-section image, a difference in asphalt thickness between the wheel track and the center of the lane; analyzing the wheel track to determine the wheel rut depth; The vertical distance between the filling area and the crack is calculated according to the crack type, the asphalt thickness difference, and the rutting depth.

[0133] Optionally, when calculating the upward reflection degree of the crack based on the vertical distance and the signal attenuation difference, the degree calculation module 307 is configured to: Performing time-frequency analysis on the radar cross-section diagram, and determining an energy attenuation ratio based on the time-frequency analysis results; constructing a multiple reflection path model based on the filling material penetration depth and the vertical distance; Calculating the shielding coefficient of the padded area for the upward reflected signal according to the multiple reflection path model; determining a dielectric constant gradient correction factor based on the signal attenuation difference; Based on the dielectric constant gradient correction factor, the upward reflection degree of the crack is calculated according to the shielding coefficient and the energy attenuation ratio.

[0134] The system of this embodiment can be used to execute the method of any of the above embodiments. Its implementation principles and technical effects are similar and will not be described in detail here.

Claims

1. A road detection method based on ground penetrating radar, characterized in that: include: Acquire radar image data of the road area to be detected; Analyzing the radar image data to determine vertical characteristics of the crack and characteristics of the filling area; determining the type of crack according to the vertical characteristics of the crack; Calculating the upward reflection degree of the crack according to the characteristics of the filling area and the type of the crack; A road condition assessment result is generated according to the upward reflection degree.

2. The method according to claim 1, characterized in that The analyzing the radar image data to determine the vertical characteristics of the crack and the filling area characteristics includes: analyzing the radar image data to determine a dielectric constant distribution; spatially arranging and imaging the radar image data to obtain a radar cross-sectional view; Analyzing the radar cross-section to determine the strip-shaped strong reflection area and the continuity of the event axis; Determining the vertical characteristics of the crack based on the continuity of the event axis and the strip-shaped strong reflection area; According to the dielectric constant distribution, the filling area characteristics are determined.

3. The method according to claim 2, characterized in that Determining the crack type according to the vertical characteristics of the crack includes: Determining the fracture reflection layer according to the radar cross-section diagram; Analyzing the dielectric constant distribution based on the fracture reflection layer to determine the waveform phase characteristics; determining a phase polarity according to the waveform phase characteristic; The fracture type of the fracture reflection layer is determined according to the phase polarity.

4. The method according to claim 3, characterized in that The calculating the upward reflection degree of the crack according to the filling area characteristics and the crack type includes: Determining a dielectric constant gradient change of the filled area according to the characteristics of the filled area; determining the penetration depth of the filling material according to the dielectric constant gradient change; Analyzing the road area to be detected to determine the depth of the reflection layer; Calculating the vertical distance between the filling area and the crack according to the depth of the reflection layer; Analyzing the radar cross-section to determine waveform amplitude intensity; determining a signal attenuation difference between the filling material and the road surface based on the waveform amplitude strength; The upward reflection degree of the crack is calculated based on the vertical distance and the signal attenuation difference.

5. The method according to claim 4, characterized in that Calculating the vertical distance between the filling area and the crack according to the depth of the reflective layer includes: Determining a reference plane according to the crack type; Based on the reference plane and according to the bit depth of the reflection layer, the vertical distance between the strip-shaped strong reflection area and the crack is calculated.

6. The method according to claim 4, characterized in that Determining the penetration depth of the filling material according to the dielectric constant gradient change includes: Analyzing the dielectric constant gradient change to determine the dielectric constant mutation interface between the filled area and the original road surface; Acquiring sampling information of the road area to be detected; obtaining a sampling point distribution of the dielectric constant along the depth direction based on the sampling information; The penetration depth of the filling material is determined according to the sudden interface and the distribution of the sampling points.

7. The method according to claim 6, characterized in that The step of determining the penetration depth of the filling material according to the sudden interface and the sampling point distribution includes: Obtaining road construction records, analyzing the road construction records, and determining the mixing parameters of the original filling material; Analyze radar cross-sections to determine event distortion patterns; Determining the curing shrinkage rate of the filling material according to the event axis distortion shape; Constructing a permeation attenuation function that takes material aging into consideration based on the mix ratio parameters and the curing shrinkage rate of the filling material; Establishing a three-dimensional penetration profile model of the filling material according to the attenuation function, the sudden interface and the sampling point distribution; The penetration depth of the filling material is determined based on the three-dimensional penetration profile model.

8. The method according to claim 4, characterized in that Calculating the vertical distance between the filling area and the crack according to the depth of the reflective layer includes: Acquiring ground information of the road area to be detected; analyzing the ground information to determine the wheel track and lane center; determining, based on the radar cross-section image, a difference in asphalt thickness between the wheel track and the center of the lane; analyzing the wheel track to determine the wheel rut depth; The vertical distance between the filling area and the crack is calculated according to the crack type, the asphalt thickness difference, and the rutting depth.

9. The method according to claim 4, characterized in that Calculating the upward reflection degree of the crack according to the vertical distance and the signal attenuation difference includes: Performing time-frequency analysis on the radar cross-section diagram, and determining an energy attenuation ratio based on the time-frequency analysis results; constructing a multiple reflection path model based on the filling material penetration depth and the vertical distance; Calculating the shielding coefficient of the padded area for the upward reflected signal according to the multiple reflection path model; determining a dielectric constant gradient correction factor based on the signal attenuation difference; Based on the dielectric constant gradient correction factor, the upward reflection degree of the crack is calculated according to the shielding coefficient and the energy attenuation ratio.

10. A road detection system based on ground penetrating radar, characterized in that: The method as claimed in any one of claims 1 to 9 comprises: A data acquisition module, used to acquire radar image data of the road area to be detected scanned by the ground penetrating radar; A data analysis module, configured to analyze the radar image data to determine vertical crack characteristics and pipeline reflection characteristics; A crack analysis module, used to predict the development state of the crack and the degree of upward reflection based on the vertical characteristics of the crack; The pipeline analysis module is used to determine the pipeline damage location and damage type based on the pipeline reflection characteristics.

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