Road disease radar detection method and system based on sewer pipe GIS navigation

Abstract

The application discloses a kind of road disease radar detection method and system based on drainage pipeline GIS navigation belongs to road disease detection technical field.The method includes: S1.data preparation: obtain the original data of city drainage pipe network GIS system, establish navigation reference database based on the plane coordinate information and pipeline attribute data therein;S2.multisource positioning fusion: based on GPS satellite signal, CORS virtual reference station correction data, INS initial attitude data obtain multisource fusion real-time positioning data;S3.path planning: based on navigation reference database and real-time positioning data detection path planning, obtain the required detection path;S4.accurate detection: the reflected echo data, with the same time high-precision real-time positioning data is time stamp level one-to-one correspondence and binding, obtain the radar detection data frame with accurate coordinates.The present application can realize the accurate early warning and efficient detection of urban road collapse hazard.

Description

Technical Field

[0001] This invention belongs to the field of road defect detection technology, specifically relating to a road defect radar detection method and system based on drainage pipeline GIS navigation. Background Technology

[0002] With the rapid urbanization in my country, urban road collapses are occurring frequently, seriously threatening public transportation safety and the lives and property of the people. According to industry statistics, there were over 1,200 urban road collapses in China in 2023. Research on the formation mechanism of urban road collapses shows that road collapses do not occur randomly, but follow a gradual evolutionary chain: "drainage pipe damage → soil erosion → roadbed voiding → road collapse." During long-term use, drainage pipes are damaged due to corrosion, wear, uneven settlement, and other factors. Water seeps into the pipes, eroding the surrounding soil, gradually forming and expanding voids within the roadbed, eventually leading to collapse under vehicle loads or external stimuli.

[0003] Currently, ground-penetrating radar (GPR) technology is mainly used for detecting roadbed defects both domestically and internationally. This technology identifies roadbed defects by transmitting high-frequency electromagnetic pulses into the ground and receiving reflected signals from the interface. However, existing technologies generally suffer from the following drawbacks in practical applications: First, blind full-width detection is inefficient. Current detection methods involve continuous radar scanning of the entire road surface, typically covering the entire lane or even the entire road surface. This results in a large detection range and a large amount of data, but the actual detected defects are often concentrated in localized areas above drainage pipes. A large amount of detection data corresponds to normal roadbed areas, leading to severely low detection efficiency. According to industry practice, the width of a typical urban arterial road with two lanes in one direction is about 7.5 meters, while the width of drainage pipes is only about 0.5 to 1.5 meters. The effective detection area in traditional full-width detection is less than 10%.

[0004] Second, the detection cost remains high. Due to low detection efficiency, the detection time per unit kilometer of road is long, equipment wear and tear is significant, labor costs are high, and the large amount of redundant data generated increases the workload and economic burden of subsequent processing and analysis.

[0005] Third, the detection is not targeted. Traditional full-width detection lacks targeted attention to key areas of defects, and it is difficult to quickly locate defect risk points along the drainage pipeline during the post-processing stage of detection data, which easily leads to the omission or delay in identifying high-risk void areas.

[0006] Fourth, insufficient positioning accuracy. Urban environments are filled with tall buildings, which severely obstruct satellite signals. Traditional GPS positioning accuracy is insufficient to meet the needs of precise detection, and the lack of a precise time synchronization mechanism between detection data and positioning data results in limited spatial positioning accuracy of the detection results.

[0007] In summary, existing technologies lack the concept of "guided detection based on the mechanism of disease formation (i.e., the spatial distribution pattern of collapse caused by pipeline damage)," and fail to intelligently generate and dynamically guide detection paths to address the linear distribution of collapse damage along drainage pipelines.

[0008] Therefore, there is an urgent need for a road damage radar detection system and method that is highly targeted, efficient, low-cost, and accurate in positioning, for early warning and detection of potential urban road collapse hazards. Summary of the Invention

[0009] The present invention aims to at least partially solve one of the technical problems in the aforementioned related technologies.

[0010] Therefore, the purpose of this invention is to provide a road defect radar detection method based on drainage pipeline GIS navigation, which can achieve accurate early warning and efficient detection of potential urban road collapse hazards, and solve the technical problems of low efficiency, high cost, poor targeting and insufficient positioning accuracy of existing blind full-width detection.

[0011] To solve the above-mentioned technical problems, the present invention is implemented as follows: This invention provides a method for radar detection of road defects based on GIS navigation for drainage pipelines, the method comprising: S1. Data preparation: Obtain the raw data of the urban drainage network GIS system, and establish a navigation reference database based on the plane coordinate information and pipeline attribute data therein; S2. Multi-source positioning fusion: Real-time positioning data is obtained by fusing multiple sources based on GPS satellite signals, CORS virtual reference station correction data, and INS initial attitude data; S3. Path planning: Based on the navigation reference database of S1 and the real-time positioning data of S2, a detection path is planned to obtain a narrow strip detection path that is not full-width along the surface area above the underground extension direction of the drainage pipe. S4. Precise Detection: Each reflected echo data collected by the ground-penetrating radar along the narrow detection path is matched and bound one-to-one with the high-precision real-time positioning data continuously output by S2 at the same time, at the timestamp level, to obtain radar detection data frames with precise coordinates.

[0012] In addition, the road defect radar detection method based on drainage pipeline GIS navigation according to the present invention may also have the following additional technical features: In some embodiments, the method further includes: S5. Output Results: Based on the radar detection data frames with precise coordinates in S4, the data is visualized and overlaid onto the drainage pipeline GIS map. Combined with road defect identification, a thematic map of road defect distribution is obtained.

[0013] In some implementations, step S2 includes the following process: Real-time positioning is obtained by the GPS-RTK unit integrated into the detection system. When the satellite signal is blocked by tall buildings in the city, the system automatically switches to the urban virtual reference station enhanced real-time dynamic positioning mode. The virtual reference station correction data is obtained by using the urban CORS continuously operating reference station network, thereby obtaining enhanced positioning correction data. Simultaneously, it integrates inertial navigation technology, employs fiber optic gyroscopes or MEMS inertial measurement units, and fuses the obtained enhanced positioning correction data with the extended Kalman filter algorithm to maintain continuous high-precision navigation during brief signal interruptions. The signal interruption duration is independently estimated to be no less than 30 seconds, and the accuracy loss is no more than 5 centimeters.

[0014] In some implementations, step S3 includes generating a precise detection path directly above the drainage pipe based on the GIS coordinate data and real-time positioning data of the drainage pipe. The width of this narrow detection path extends 0.5 to 2 meters to both sides based on the centerline of the pipe, covering only a small local area above the pipe. Compared with traditional full-width detection, the detection coverage area is reduced to 5% to 15% of the original.

[0015] In some implementations, step S4 includes the following process: The detection system establishes a unified timestamp mechanism, using the system clock as a reference, to perform millisecond-level time synchronization between radar detection echo data and GPS-RTK positioning data, or between radar detection echo data and enhanced real-time dynamic positioning data from urban virtual reference stations.

[0016] In some implementations, the time synchronization enables each radar data point to precisely correspond to a unique geographic coordinate, and ensures accurate alignment and matching of detection and navigation data on the time axis.

[0017] In some implementations, the specific content of the road defect identification includes: identifying hyperbolic abnormal reflection areas in the probe data frame based on a deep learning semantic segmentation network, and determining and marking the location, range, and severity of the risk areas of voiding and collapse.

[0018] This invention also provides a road defect radar detection system based on drainage pipeline GIS navigation, used to implement the road defect radar detection method based on drainage pipeline GIS navigation as described in any of the preceding claims, the system comprising: The GIS data interface module is configured to import GIS planar coordinate data of drainage pipelines to obtain navigation reference data, and import pipeline attribute data as an auxiliary reference for path planning. The multi-source positioning fusion module is configured to integrate GPS-RTK, urban VRS+RTK and inertial navigation INS, and uses extended Kalman filtering to fuse multi-source data to output high-precision real-time positioning data. The path planning module is configured to generate a narrow detection path along the surface above the drainage pipe based on the navigation reference. The radar detection module is configured to transmit ground-penetrating radar signals to a local area directly above the drainage pipe along the detection path and receive reflected echo data from the underground medium; it employs a multi-frequency antenna array, in which the low-frequency antenna is used to detect large-scale cavitation in deep layers, and the high-frequency antenna is used to detect fine cracks in shallow layers. The spatiotemporal synchronization module is configured to introduce a unified timestamp to bind each echo data of the radar detection module with the high-precision real-time position output by the multi-source positioning fusion module at the same time, thereby achieving millisecond-level time synchronization of multi-source data; thus embedding the corresponding coordinate data frame into the radar detection echo data to achieve a one-to-one correspondence between each radar data and precise geographic coordinates. The detection results visualization module is configured to overlay the detection results of road defects with precise coordinates onto the GIS map of drainage pipelines, generate thematic maps of road defect distribution, and mark the location, range, and severity of suspected voiding and collapse risk areas.

[0019] In addition, the road defect radar detection system based on drainage pipeline GIS navigation according to the present invention may also have the following additional technical features: In some of these implementations, the multi-source positioning fusion module uses GPS-RTK in open urban areas and automatically switches to urban VRS+RTK when tall buildings obstruct the view; and uses inertial navigation INS for independent calculation when the signal is interrupted.

[0020] In some implementations, the path planning module can generate a precise detection path directly above the drainage pipe based on GIS planar coordinates and real-time positioning data, with the detection width extending 0.5 to 2 meters to both sides of the pipe centerline; a path deviation threshold is set, and when the deviation exceeds the deviation threshold, an alert is issued and the local path is replanned to guide the detection equipment to correct its direction.

[0021] Compared with the prior art, the present invention has at least the following beneficial effects: In this embodiment of the invention, the road defect radar detection method based on drainage pipeline GIS navigation can significantly improve detection efficiency: the accurate detection coverage area is only 5% to 15% of that of traditional full-width detection, the detection time per kilometer is greatly shortened, and the detection operation efficiency is significantly improved. In this embodiment of the invention, the road defect radar detection method based on drainage pipeline GIS navigation significantly reduces detection costs: the detection range is greatly reduced, equipment wear, data processing volume, and labor costs are reduced simultaneously, and the detection cost per unit kilometer is greatly reduced. In this embodiment of the invention, the road defect radar detection method based on drainage pipe GIS navigation provides the following: it ensures the effectiveness of the detection by accurately detecting the core cause of collapse, namely the void above the drainage pipe, ensuring that high-risk defect areas are not missed, and has high detection targeting and detection rate. In this embodiment of the invention, the road defect radar detection method based on drainage pipeline GIS navigation provides high-precision positioning and spatiotemporal alignment: VRS+RTK centimeter-level positioning accuracy combined with inertial navigation ensures continuity, and millisecond-level spatiotemporal alignment ensures spatial accuracy of detection data, supporting accurate defect location; In this embodiment of the invention, the road defect radar detection method based on drainage pipeline GIS navigation provides support for refined maintenance decision-making: the defect thematic map is overlaid with drainage pipeline GIS to intuitively display the spatial distribution of defects, assisting maintenance departments in implementing precise policies and handling them in a tiered manner.

[0022] Furthermore, the various technical features of this invention do not exist in isolation, but rather form an organic technical synergy: First, the synergy between GIS data (prior knowledge) and real-time fusion positioning (dynamic perception) enables dynamic and precise following of narrow-band paths. The system not only plans the path but also continuously corrects it based on real-time positioning results, ensuring that the radar antenna is always precisely aligned with the top of the pipeline, overcoming the shortcomings of traditional methods where "planning is one thing, walking is another."

[0023] Second, the synergy between narrowband detection path and spatiotemporal synchronization: Since only key areas are detected, invalid radar data is greatly reduced, resulting in a higher signal-to-noise ratio; at the same time, precise spatiotemporal synchronization assigns centimeter-level coordinates to each valid data point. The combination of the two achieves the outstanding effect of "less data, more accurate positioning, and faster disease identification".

[0024] Third, the synergy between VRS+RTK and inertial navigation INS: VRS+RTK solves the problem of short-term signal obstruction in urban high-rise environments, while INS solves the problem of continuous positioning in completely unlocked scenarios such as tunnels and under elevated roads. The integration of the two achieves centimeter-level positioning in all scenarios without interruption. This is the fundamental guarantee for the continuous and accurate execution of narrowband detection paths. No single technology can complete this task independently in the complex urban environment.

[0025] The road defect radar detection system based on drainage pipeline GIS navigation of the present invention includes the aforementioned road defect radar detection method based on drainage pipeline GIS navigation, and therefore possesses at least all the features and advantages of the aforementioned road defect radar detection method based on drainage pipeline GIS navigation, which will not be repeated here. Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0026] Figure 1 This is a flowchart of a road defect radar detection method based on drainage pipeline GIS navigation, as disclosed in one embodiment of the present invention. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and specific examples and application scenarios.

[0029] In some embodiments of the present invention, a road defect radar detection method based on drainage pipeline GIS navigation is provided, comprising: Importing GIS Coordinates and Establishing Navigation Baselines for Drainage Pipelines: The GIS planar coordinate information of urban drainage pipelines (including pipeline centerline coordinates, pipeline direction, pipeline boundaries, etc.) is pre-imported into the detection system as navigation baseline data. The GIS data format supports ShapeFile or GeoJSON standard formats. Simultaneously, pipeline attribute data (material, burial depth, pipe diameter, laying year, etc.) can be imported as auxiliary references for detection path planning.

[0030] Multi-source positioning fusion and signal blockage mitigation: The detection system integrates a GPS-RTK real-time dynamic positioning unit. When satellite signals are blocked by tall buildings in the city, it automatically switches to the urban VRS+RTK (virtual reference station enhanced real-time dynamic positioning) mode. It utilizes the city's CORS continuously operating reference station network to obtain virtual reference station correction data, improving positioning accuracy to the centimeter level. Simultaneously, it integrates inertial navigation technology (INS), employing fiber optic gyroscopes or MEMS inertial measurement units. Through an extended Kalman filter algorithm, it fuses GPS-RTK / VRS+RTK positioning information to maintain continuous high-precision navigation during brief signal interruptions. The independently calculated duration of the signal interruption is no less than 30 seconds, with an accuracy loss of no more than 5 centimeters.

[0031] Precise Path Planning and Guidance: Based on the GIS coordinate information and real-time positioning information of the drainage pipeline, the path planning module automatically generates a precise detection operation path along the top of the drainage pipeline. The width of this narrow detection path extends 0.5 to 2 meters to both sides based on the center line of the pipeline, covering only a small local area above the pipeline. Compared with traditional full-width detection, the detection coverage area is reduced to 5% to 15% of the original.

[0032] Precise spatiotemporal alignment and data matching: The detection system establishes a unified timestamp mechanism, using the system clock as a reference, to perform millisecond-level time synchronization between radar detection echo data and GPS-RTK / VRS+RTK positioning data, so as to achieve precise correspondence between each radar data and a unique geographic coordinate, as well as precise alignment and matching between detection data and navigation data on the time axis.

[0033] Visualization of road defects and thematic output: The detection results visualization module overlays the detection data of road defects with precise coordinates onto the GIS map of drainage pipelines, automatically generates thematic maps of road defect distribution, identifies hyperbolic abnormal reflection areas in the detection data frames based on deep learning semantic segmentation network, and determines and marks the location, range and severity of void and collapse risk areas to support subsequent refined maintenance decisions.

[0034] In some embodiments of the present invention, such as Figure 1 As shown, the steps of this method include: S1. Data preparation: Obtain the raw data of the urban drainage network GIS system, and establish a navigation reference database based on the plane coordinate information and pipeline attribute data therein; S2. Multi-source positioning fusion: Real-time positioning data is obtained by fusing multiple sources based on GPS satellite signals, CORS virtual reference station correction data, and INS initial attitude data; S3. Path planning: Based on the navigation reference database of S1 and the real-time positioning data of S2, a detection path is planned to obtain a narrow strip detection path that is not full-width along the surface area above the underground extension direction of the drainage pipe. S4. Precise Detection: Each reflected echo data collected by the ground-penetrating radar along the narrow detection path is matched and bound one-to-one with the high-precision real-time positioning data continuously output by S2 at the same time, at the timestamp level, to obtain radar detection data frames with precise coordinates.

[0035] Example 1: This embodiment provides a road defect radar detection system based on drainage pipeline GIS navigation, which is suitable for accurate detection of road defects above drainage pipelines in general urban road environments.

[0036] The system in this embodiment includes a drainage pipeline GIS coordinate import module 1, a multi-source positioning fusion module 2, a path planning module 3, a radar detection module 4, a spatiotemporal alignment module 5, and a detection result visualization module 6. All modules are installed on the detection vehicle.

[0037] The drainage pipeline GIS coordinate import module 1 imports GIS data of drainage pipelines in a central urban area of ​​a city through a standard GIS data interface (ShapeFile or GeoJSON format). This includes the centerline coordinate sequence, pipe diameter, burial depth, pipe material, and laying year information of the drainage pipelines. Among them, the drainage pipeline centerline coordinate sequence serves as the core navigation reference data, the pipe burial depth information is used to assist in the selection of detection parameters, and the pipe material and laying year serve as auxiliary parameters for disease risk assessment.

[0038] The multi-source positioning fusion module 2 includes a GPS-RTK positioning unit 21, an urban VRS+RTK positioning unit 22, and an inertial navigation INS unit 23. The GPS-RTK positioning unit 21 uses a dual-frequency GNSS receiver, equipped with a base station and a rover, to calculate carrier phase difference in real time, achieving centimeter-level positioning accuracy. In open road sections in the urban suburbs of this embodiment, the GPS-RTK signal is good, and the GPS-RTK positioning result is used as the primary navigation source. The inertial navigation INS unit 23 uses a MEMS inertial measurement unit, including a three-axis gyroscope and a three-axis accelerometer, which is fused with the GPS-RTK positioning information using an extended Kalman filter algorithm to output a high-precision navigation solution. When the GPS-RTK positioning unit 21 experiences a positioning interruption due to signal obstruction, the inertial navigation INS unit 23 automatically enters an independent calculation mode to maintain navigation continuity, with an accuracy maintenance time of no less than 30 seconds and a cumulative error not exceeding 5 centimeters.

[0039] The path planning module 3 generates a precise detection path directly above the drainage pipeline based on the GIS plane coordinates of the drainage pipeline and the real-time location information output by the multi-source positioning fusion module 2. Specifically, using the pipeline centerline as a reference, it automatically offsets 1 meter to each side to generate detection edges, with a total detection coverage width of 2 meters. The system compares the real-time position of the detection vehicle with the preset path in real time. When the deviation exceeds 0.3 meters, it issues an alert and provides path correction suggestions to guide the detection vehicle back to the correct path.

[0040] Radar detection module 4 is installed at the bottom of the exploration vehicle and includes one set each of a low-frequency ground-penetrating radar antenna with a center frequency of 400MHz and a high-frequency ground-penetrating radar antenna with a center frequency of 1000MHz. The exploration vehicle travels along a precise exploration path at a speed of 5 km / h to 15 km / h. The low-frequency antenna has a detection depth of 3 to 5 meters and is used to detect large-scale cavities in deep layers; the high-frequency antenna has a detection depth of 0.5 to 1.5 meters and is used to detect shallow fine cracks and small cavities.

[0041] The spatiotemporal alignment module 5 establishes a unified timestamp mechanism. The GPS-RTK positioning unit 21 outputs positioning data 10 times per second (10Hz), and the radar detection module 4 samples at a frequency of 512Hz (one data point every approximately 1.95 milliseconds). The spatiotemporal alignment module 5 assigns a unified timestamp to each radar detection data frame and embeds the corresponding real-time positioning coordinates (latitude, longitude, and elevation) within the same data frame, achieving precise binding between radar detection data and spatial coordinates. During subsequent data processing, the corresponding detection location coordinates can be accurately queried based on the timestamp of any radar data channel.

[0042] The detection results visualization module 6 imports the spatiotemporally aligned detection data into the post-processing software, automatically identifies abnormal reflection areas in the radar image, determines the location, extent, and depth of voids and cracks, and generates a road defect detection report. Simultaneously, the defect detection results are overlaid onto the drainage pipeline GIS map as a vector layer, outputting a thematic map of road defect distribution. Different colors mark risk areas of varying severity, supporting maintenance decisions.

[0043] This embodiment conducted a comparative verification test on a 2-kilometer section of a main urban road. The results show that, using the precise detection scheme of this invention, the detection coverage area is only about 12% of that of traditional full-width detection, the detection time per kilometer is reduced to about 20% of the original, and the detection efficiency is improved by about 5 times; the detection cost per unit kilometer is reduced by about 70%; in the detected suspected void areas, core drilling verification confirmed that the detection accuracy rate is over 80%, which is comparable to the detection accuracy of the traditional full-width method, but the cost and efficiency advantages are significant.

[0044] Example 2: This embodiment provides an application of a road defect radar detection method based on drainage pipeline GIS navigation in densely populated high-rise areas of urban core business districts. It is suitable for complex urban environments with severe obstruction from high-rise buildings and poor quality of traditional GPS positioning signals.

[0045] In densely populated high-rise buildings in the city's core business districts, the average height of the buildings exceeds 80 meters, and the narrow spacing between buildings severely obstructs satellite signals. Traditional GPS-RTK positioning often has fewer than four usable satellites, which cannot meet the accuracy requirements of fixed-solution positioning. This embodiment has been adapted to this special environment.

[0046] During the data preparation phase, GIS data of drainage pipelines in the target road section is exported from the urban drainage network GIS system, including pipeline centerline coordinates, pipe diameter, burial depth, and historical pipeline health assessment data, and then imported into the detection system of this invention. Considering that the drainage pipelines in the commercial area were constructed relatively early, and some pipelines have been laid for a long time with a high degree of aging and a correspondingly increased risk of damage, the system incorporates this parameter into the path planning weight and prioritizes the detection sequence.

[0047] During the positioning initialization phase, the system automatically detects the number of GNSS satellites and signal quality. When fewer than 6 available satellites are detected or the HDOP value is greater than 2.5, it is determined to be a signal-blocked environment, and the system automatically switches to the urban VRS+RTK virtual reference station positioning mode. This embodiment connects to the urban CORS continuously operating reference station system, which consists of multiple reference stations evenly distributed throughout the urban area, covering the entire target city, and can provide users with virtual reference station correction data. In densely populated areas with tall buildings, the probe vehicle can still achieve centimeter-level positioning accuracy through VRS+RTK mode, effectively overcoming the positioning difficulties caused by tall buildings.

[0048] The inertial navigation (INS) unit employs a fiber optic gyroscope (FOG) to handle frequent signal interruptions in densely populated high-rise areas. The FOG boasts zero-drift stability better than 0.01 degrees / hour. Combined with high-precision odometer information, the independently calculated duration of signal interruption is no less than 30 seconds, and the position estimation error does not exceed 5 centimeters. The extended Kalman filter algorithm uses GPS-RTK / VRS+RTK positioning as the primary control variable and the INS as an auxiliary variable, dynamically adjusting the filter weights to achieve smooth, high-precision navigation output.

[0049] When the detection vehicle operates in the core section of the commercial area, the detection path advances directly above the drainage pipe, with a detection width of 1 meter on each side of the pipe's centerline, totaling 2 meters. Given the high volume of pedestrian and vehicular traffic and limited operating window in the commercial area, this embodiment employs a rapid, multiple-round-scan strategy. The radar antenna scans repeatedly each time it passes the same pipe section to improve the data signal-to-noise ratio and the reliability of anomaly detection.

[0050] The spatiotemporal alignment module embeds corresponding VRS+RTK coordinate data frames into the radar detection echo data, achieving a one-to-one correspondence between each radar data point and precise geographic coordinates. When the VRS+RTK signal is briefly interrupted due to entering or exiting building shadow areas, the spatiotemporal alignment module assigns interpolated coordinates to the radar data for the corresponding time period based on the calculation results of the inertial navigation INS unit, and marks the positioning accuracy level for that time period in the data for reference by the post-processing software.

[0051] The detection results visualization module overlays a 3D building model base map onto the business district environment, intuitively displaying the relative positional relationship between the detection results and surrounding buildings. This assists management departments in quickly locating the fault points and formulating emergency response plans. This embodiment was validated through detection along a 1.5-kilometer stretch in the core area of ​​the business district. The detection of suspected voided areas was effective, verifying the applicability and effectiveness of the method in densely populated urban environments.

[0052] To further verify the technical effectiveness of the present invention, a comparative verification test was conducted. On a 2-kilometer section of the same urban main road, the traditional full-width detection scheme (Scheme A, using ordinary GPS + differential positioning, full lane scanning) and the scheme of the present invention (Scheme B) were respectively used.

[0053] The test results are shown in Table 1.

[0054] Table 1

[0055] All parts of this invention not described in detail herein can be referred to in the prior art or are known to those skilled in the art. This embodiment does not limit these aspects and will not describe them in detail here.

[0056] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of the present invention.

Claims

1. A road defect radar detection method based on drainage pipeline GIS navigation, characterized in that, The method includes: S1. Data preparation: Obtain the raw data of the urban drainage network GIS system, and establish a navigation reference database based on the plane coordinate information and pipeline attribute data therein; S2. Multi-source positioning fusion: Real-time positioning data is obtained by fusing multiple sources based on GPS satellite signals, CORS virtual reference station correction data, and INS initial attitude data; S3. Path planning: Based on the navigation reference database of S1 and the real-time positioning data of S2, a detection path is planned to obtain a narrow strip detection path that is not full-width along the surface area above the underground extension direction of the drainage pipe. S4. Precise Detection: Each reflected echo data collected by the ground-penetrating radar along the narrow detection path is matched and bound one-to-one with the high-precision real-time positioning data continuously output by S2 at the same time, at the timestamp level, to obtain radar detection data frames with precise coordinates.

2. The road defect radar detection method based on drainage pipeline GIS navigation according to claim 1, characterized in that, The method further includes: S5. Output Results: Based on the radar detection data frames with precise coordinates in S4, the data is visualized and overlaid onto the drainage pipeline GIS map. Combined with road defect identification, a thematic map of road defect distribution is obtained.

3. The road defect radar detection method based on drainage pipeline GIS navigation according to claim 1, characterized in that, The processing steps in step S2 include: Real-time positioning is obtained by the GPS-RTK unit integrated into the detection system. When the satellite signal is blocked by tall buildings in the city, the system automatically switches to the urban virtual reference station enhanced real-time dynamic positioning mode. The virtual reference station correction data is obtained by using the urban CORS continuously operating reference station network, thereby obtaining enhanced positioning correction data. Simultaneously, it integrates inertial navigation technology, employs fiber optic gyroscopes or MEMS inertial measurement units, and fuses the obtained enhanced positioning correction data with the extended Kalman filter algorithm to maintain continuous high-precision navigation during brief signal interruptions. The signal interruption duration is independently estimated to be no less than 30 seconds, and the accuracy loss is no more than 5 centimeters.

4. The road defect radar detection method based on drainage pipeline GIS navigation according to claim 1, characterized in that, The processing steps in step S3 include: generating a precise detection path along the top of the drainage pipeline based on the GIS coordinate data and real-time positioning data of the drainage pipeline. The width of this narrow detection path extends 0.5 to 2 meters to both sides based on the centerline of the pipeline, covering only a small local area above the pipeline.

5. The road defect radar detection method based on drainage pipeline GIS navigation according to claim 1, characterized in that, The processing procedure in step S4 includes: The detection system establishes a unified timestamp mechanism, using the system clock as a reference, to perform millisecond-level time synchronization between radar detection echo data and GPS-RTK positioning data, or between radar detection echo data and enhanced real-time dynamic positioning data from urban virtual reference stations.

6. The road defect radar detection method based on drainage pipeline GIS navigation according to claim 5, characterized in that, Through the aforementioned time synchronization, each radar data point can be precisely matched with a unique geographic coordinate, and the detection data and navigation data can be accurately aligned and matched on the time axis.

7. The road defect radar detection method based on drainage pipeline GIS navigation according to claim 2, characterized in that, The specific content of the road defect identification includes: identifying hyperbolic abnormal reflection areas in the detection data frames based on a deep learning semantic segmentation network, and determining and marking the location, range, and severity of the risk areas of voiding and collapse.

8. A road defect radar detection system based on drainage pipeline GIS navigation, characterized in that, The system for implementing the road defect radar detection method based on drainage pipeline GIS navigation as described in any one of claims 1-7 comprises: The GIS data interface module is configured to import GIS planar coordinate data of drainage pipelines to obtain navigation reference data, and import pipeline attribute data as an auxiliary reference for path planning. The multi-source positioning fusion module is configured to integrate GPS-RTK, urban VRS+RTK and inertial navigation INS, and uses extended Kalman filtering to fuse multi-source data to output high-precision real-time positioning data. The path planning module is configured to generate a narrow detection path along the surface above the drainage pipe based on the navigation reference. The radar detection module is configured to transmit ground-penetrating radar signals to a local area directly above the drainage pipe along the detection path and receive reflected echo data from the underground medium; it employs a multi-frequency antenna array, in which the low-frequency antenna is used to detect large-scale cavitation in deep layers, and the high-frequency antenna is used to detect fine cracks in shallow layers. The spatiotemporal synchronization module is configured to introduce a unified timestamp to bind each echo data of the radar detection module with the high-precision real-time position output by the multi-source positioning fusion module at the same time, thereby achieving millisecond-level time synchronization of multi-source data; thus embedding the corresponding coordinate data frame into the radar detection echo data to achieve a one-to-one correspondence between each radar data and precise geographic coordinates. The detection results visualization module is configured to overlay the detection results of road defects with precise coordinates onto the GIS map of drainage pipelines, generate thematic maps of road defect distribution, and mark the location, range, and severity of suspected voiding and collapse risk areas.

9. The road defect radar detection system based on drainage pipeline GIS navigation according to claim 8, characterized in that, In the multi-source positioning fusion module, GPS-RTK is used in open urban areas, and automatically switches to urban VRS+RTK when tall buildings obstruct the view; when the signal is interrupted, inertial navigation INS is used for independent calculation.

10. The road defect radar detection system based on drainage pipeline GIS navigation according to claim 8, characterized in that, The path planning module can generate a precise detection path directly above the drainage pipe based on GIS plane coordinates and real-time positioning data. The detection width extends 0.5 to 2 meters to both sides of the pipe centerline. A path deviation threshold is set. When the deviation exceeds the deviation threshold, an alert is issued and the local path is replanned to guide the detection equipment to correct its direction.

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