Method and system for automatically collecting highway pavement diseases

Abstract

The invention relates to a highway pavement disease automatic acquisition method and system, and relates to the technical field of road detection.The method comprises the steps that road detection information is acquired, and the road detection information comprises first data and second data; judging whether the road is abnormal or not according to the first data and the second data; and if the road has the abnormal condition, recording the abnormal condition, and giving an alarm according to the abnormal condition. The method has the effect of improving the road detection efficiency.

Description

Technical Field

[0001] This application relates to the technical field of road inspection, and in particular to an automatic method and system for collecting pavement defects on highways. Background Technology

[0002] As roads age and the number of vehicles increases dramatically and the frequency of use rises, various road defects occur, affecting the lifespan of roads. Common road defects include cracks, potholes, ruts, loosening, subsidence, bridge approach and culvert top slab ...

[0003] The road defect detection technology mainly relies on manual inspection. Relevant personnel collect road defect data by parking inspections, taking photos and recording data, and manual measurement. As such, the road defect detection technology suffers from low detection efficiency. Summary of the Invention

[0004] The purpose of this application is to provide an automatic method and system for collecting highway pavement defects, in order to solve the problem.

[0005] Firstly, this application provides an automatic method for collecting pavement defects on highways, which adopts the following technical solution: An automatic method for collecting pavement defects on highways includes: Obtain road detection information, which includes first data and second data; Based on the first data and the second data, determine whether there are any abnormalities in the road; If the road has the aforementioned abnormal situation, the abnormal situation is recorded, and an alarm is issued based on the abnormal situation.

[0006] By adopting the above technical solution, road detection information is collected and analyzed to determine whether there are any abnormalities on the road. When abnormalities are found, they can be recorded and alarms can be issued, thereby improving the efficiency of road detection.

[0007] Optionally, obtaining road detection information specifically includes: Install cameras and positioning devices on road inspection vehicles; The camera device acquires video of the road surface, and the positioning device acquires the first physical location corresponding to the video of the road surface. The road surface video is processed to obtain the first road surface image of the road.

[0008] By adopting the above technical solution, road surface video and the first physical location corresponding to the road surface video are collected, and then the road surface video is processed to easily obtain the first road surface image.

[0009] Optionally, processing the road surface video to obtain a first road surface image specifically includes: The video stream of the road surface is extracted to obtain at least one frame of image video stream; The first road surface image is obtained by filtering at least one frame image video stream according to preset rules.

[0010] By adopting the above technical solution, video streams of road surface videos are extracted to obtain frame image video streams. Then, the frame image video streams are filtered to obtain the first road surface image, thereby improving the clarity and completeness of the obtained first road surface image.

[0011] Optionally, obtaining road detection information specifically includes: Obtain the driving speed of the road inspection vehicle; The driving status of the road inspection vehicle is determined based on the driving speed. If the road inspection vehicle is traveling at high speed, the vibration parameters of the road inspection vehicle during the driving process are collected in real time; if the road inspection vehicle is traveling at low speed, the acceleration parameters of the road inspection vehicle during the driving process are collected in real time.

[0012] By adopting the above technical solution, the driving status of the road inspection vehicle is determined, and then different influencing parameters are collected according to the different driving statuses of the road inspection vehicle. Based on these different influencing parameters, it is easy to analyze whether there are road defects.

[0013] Optionally, determining whether there is an anomaly in the road based on the first data and the second data specifically includes: Based on the first road surface image, the vibration parameters, and the acceleration parameters, it is determined whether the road has any defects; if the road has defects, it is determined that the road has the abnormal condition. If the road does not exhibit the aforementioned defects, then the road is deemed to be free from the aforementioned abnormal conditions.

[0014] By adopting the above technical solution, the vibration parameters and acceleration parameters of the first road surface image and the road inspection vehicle are comprehensively analyzed to determine whether there are road defects, thereby improving the accuracy of the judgment.

[0015] Optionally, determining whether the road has defects based on the first road surface image specifically includes: Obtain the area in the first road surface image that is inconsistent with the preset road surface color; Extract labeled features based on the inconsistent regions; Determine whether the marked feature is the disease feature.

[0016] By adopting the above technical solution, by collecting areas in the first road surface image that are inconsistent with the preset road surface color, and extracting marking features from the inconsistent areas, it is easy to determine whether the marking features are defect features, thereby further improving the accuracy of the judgment.

[0017] Optionally, determining whether the road has defects based on the vibration parameters and the acceleration parameters specifically includes: When the vibration parameters change, the second physical position of the road corresponding to the change in vibration parameters is recorded, and a second road surface image of the road is acquired based on the second physical position; When the acceleration parameter changes, the third physical position of the road corresponding to the change in acceleration parameter is recorded, and a third road surface image of the road is acquired based on the third physical position; The presence of the road defects is determined based on the second road surface image and the third road surface image.

[0018] By adopting the above technical solution, when vibration parameters or acceleration parameters change, the second or third physical position corresponding to the change in parameters is collected. Then, a second road surface image is collected based on the second physical position, and a third road surface image is collected based on the third physical position. Finally, the second and third road surface images are combined to make a comprehensive judgment on whether there are road defects, thereby further improving the accuracy of road defect judgment.

[0019] Secondly, the automatic data acquisition system for highway pavement defects provided in this application adopts the following technical solution: An automatic data acquisition system for highway pavement defects includes: The acquisition module is used to acquire road detection information, which includes first data and second data; The judgment module is used to determine whether there is any abnormality in the road based on the first data and the second data; The execution module is used to record the abnormal situation when the abnormal situation exists on the road, and to issue an alarm based on the abnormal situation.

[0020] By adopting the above technical solution, the road detection information is collected by the acquisition module and analyzed. The judgment module determines whether there are any abnormalities in the road. When abnormalities are found, the execution module can record the abnormalities and issue alarms based on them, thereby improving the efficiency of road detection.

[0021] Thirdly, the terminal provided in this application adopts the following technical solution: A terminal includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein when the processor loads the computer program, it executes the method of the first aspect.

[0022] By adopting the above technical solution, the method of the first aspect generates a computer program and stores it in the memory so that it can be loaded and executed by the processor. In this way, the user can establish a connection with the system through the terminal and query the various contents processed by the system.

[0023] Fourthly, the computer-readable storage medium provided in this application adopts the following technical solution: A computer-readable storage medium storing a computer program that, when loaded by a processor, executes the method of the first aspect.

[0024] By adopting the above technical solution, the method of the first aspect is used to generate a computer program and stored in a computer-readable storage medium. After the computer-readable storage medium is loaded into any computer, the computer can execute the method of the first aspect. Attached Figure Description

[0025] Figure 1 This is a flowchart of steps S100-S300 in the embodiments of this application; Figure 2 This is a flowchart of steps S110-S130 in the embodiments of this application; Figure 3 This is a flowchart of steps S1301-S1302 in the embodiments of this application; Figure 4 This is a flowchart of steps S140-S170 in the embodiments of this application; Figure 5 This is a flowchart of steps S210-S230 in the embodiments of this application; Figure 6 This is a flowchart of steps S2101-S2103 in the embodiments of this application; Figure 7 This is a flowchart of steps S2104-S2106 in the embodiments of this application; Figure 8 This is a road cross-section diagram of the specific implementation of this application; Figure 9 This is a module framework diagram of the automatic highway pavement distress acquisition system in the embodiments of this application; In the diagram, 1 is the acquisition module; 2 is the judgment module; and 3 is the execution module. Detailed Implementation

[0026] The following is in conjunction with the appendix Figure 1 -Appendix Figure 9 This application will be described in further detail below.

[0027] An automatic method for collecting pavement defects on highways, referring to Figure 1 Specifically, it includes the following steps: S100: Obtain road detection information, which includes first data and second data.

[0028] In one embodiment of this application, reference is made to Figure 2 To obtain road detection information, the specific steps include: S110: Collect road surface video using a camera device and collect the first physical location corresponding to the road surface video using a positioning device.

[0029] In this embodiment, a high-definition CCD camera installed on a road inspection vehicle is used to collect road surface video in real time. Then, a GPS device installed on the road inspection vehicle is used to locate the location of the collected road surface video in real time, which is the first physical location in this embodiment. The first physical location in this embodiment can be displayed in the form of geographic coordinates.

[0030] S120: Process the road surface video to obtain the first road surface image.

[0031] In one embodiment of this application, reference is made to Figure 3 Step S130 specifically includes the following steps: S1201: Extract video stream from road surface video to obtain at least one frame of image video stream.

[0032] In this embodiment, the high-definition CCD camera integrates a video stream interception program, which is then used to intercept the acquired road video to obtain at least one frame image video stream, and each frame image video stream includes at least one frame image feature value.

[0033] In this embodiment, the image feature value is the road surface feature, such as the color and texture of the road surface.

[0034] S1202: Filter at least one frame image video stream according to preset rules to obtain the first road surface image.

[0035] In this embodiment, the high-definition CCD camera integrates an image filtering program. Based on at least one frame image feature value, the image filtering program filters at least one frame image video stream to obtain a first road surface image. This makes the obtained first road surface image more complete and higher definition. The obtained first road surface image is then sent to the back-end terminal in real time for staff to view and analyze.

[0036] In this embodiment, the first data is the first road surface image.

[0037] In one embodiment of this application, reference is made to Figure 4 Obtaining road inspection information may also include the following steps: S130: Obtain the speed of the road inspection vehicle.

[0038] In this embodiment, the current speed of the road inspection vehicle can be obtained by reading the speedometer data on the vehicle's speedometer.

[0039] S140: Determine the driving status of the road inspection vehicle based on its driving speed.

[0040] In this embodiment, since the road inspection vehicle is inspecting the highway, it is not limited by the speed limit on the highway. Therefore, the current driving state of the road inspection vehicle is determined based on the current driving speed. The driving state in this embodiment includes low-speed driving state and high-speed driving state. The low-speed driving state in this embodiment indicates that the driving speed of the road inspection vehicle is in the range of 0-30 km / h, and the high-speed driving state in this embodiment indicates that the driving speed of the road inspection vehicle is in the range of 30-60 km / h.

[0041] S150: If the road inspection vehicle is traveling at high speed, the vibration parameters of the road inspection vehicle during the driving process will be collected in real time.

[0042] In this embodiment, when the road inspection vehicle travels at a speed of 30-60 km / h, the suspension sensors on the road inspection vehicle collect vibration parameters in real time during the driving process, and send the collected vibration parameters to the back-end terminal in real time for staff to view and analyze. Thus, when the road inspection vehicle is traveling at high speed, the road surface defects can be determined by the real-time collected vibration parameters.

[0043] In this embodiment, the vibration curve of the road inspection vehicle during its operation can also be automatically generated based on the vibration parameters sent to the back-end terminal, which makes it easier for staff to determine whether there are road surface defects based on the vibration parameters of the road inspection vehicle.

[0044] For example, when the suspension sensors of a road inspection vehicle detect a change in vibration parameters, it indicates that there may be cracks or potholes on the road surface.

[0045] S160: If the road inspection vehicle is traveling at a low speed, the acceleration parameters of the road inspection vehicle during the driving process will be collected in real time.

[0046] In this embodiment, when the road inspection vehicle travels at a speed of 0-30 km / h, the acceleration sensor on the road inspection vehicle collects the acceleration parameters of the road inspection vehicle in real time during the travel process, and sends the collected acceleration parameters to the back-end terminal in real time for staff to view and analyze. Thus, when the road inspection vehicle travels at a low speed, the road surface can be judged to have defects by collecting the acceleration parameters in real time.

[0047] In this embodiment, the acceleration curve of the road inspection vehicle during its operation can also be automatically generated based on the acceleration parameters sent to the back-end terminal, which makes it easier for staff to determine whether there are road surface defects based on the acceleration parameters of the road inspection vehicle.

[0048] In this embodiment, the second data is the vibration parameters and / or acceleration parameters of the road inspection vehicle.

[0049] For example, when the acceleration parameters collected by the acceleration sensor of the road inspection vehicle change, it indicates that there may be cracks or potholes on the road surface. It should be noted that the acceleration parameters recorded in this embodiment mainly refer to negative acceleration; that is, when there are cracks or potholes on the road surface ahead, the speed of the road inspection vehicle will decrease, thereby generating negative acceleration.

[0050] S200: Determine whether there are any abnormalities in the road based on the first and second data.

[0051] In this embodiment, the presence of any abnormalities in the road can be determined based on the first road surface image, the vibration parameters of the road inspection vehicle, and the acceleration parameters of the road inspection vehicle.

[0052] In one embodiment of this application, reference is made to Figure 5 Step S200 specifically includes the following steps: S210: Determine whether there are any defects in the road surface based on the first road surface image, vibration parameters, and acceleration parameters.

[0053] In one embodiment of this application, reference is made to Figure 6 Determining whether the road surface has defects based on the first road surface image includes the following steps: S2101: Obtain the area in the first road surface image that is inconsistent with the preset road surface color.

[0054] In this embodiment, when cracks, potholes, or other defects appear on the road surface, the color of the cracked and pothole areas will become inconsistent with the color of the road surface; thus, based on the acquired first road surface image, the area in the first road surface image that is inconsistent with the preset road surface color can be identified.

[0055] S2102: Extract labeled features based on inconsistent regions.

[0056] In this embodiment, marking features can be extracted from inconsistent areas. In this embodiment, the marking features are those in the area that are inconsistent with the preset road surface color.

[0057] S2103: Determine whether the marking feature is a disease feature.

[0058] In this embodiment, it is determined whether a feature that is inconsistent with the preset road surface color is a defect feature. If the feature is a defect feature, it is marked with a first special mark. Otherwise, if the feature is not a defect feature, it is marked with a second special mark. Based on the first and second special marks, the feature can be viewed and analyzed by the staff.

[0059] In this embodiment, the first special mark and the second special mark can be marked with different colors. For example, the first special mark can be marked with yellow and the second special mark can be marked with green.

[0060] In one embodiment of this application, reference is made to Figure 7 Determining whether a road surface exhibits signs of distress based on vibration and / or acceleration parameters involves the following steps: S2104: When the vibration parameters change, record the second physical position of the road corresponding to the change in vibration parameters, and acquire the second road surface image based on the second physical position.

[0061] In this embodiment, when the vibration parameters of the road inspection vehicle change, it indicates that there may be defects on the road that the road inspection vehicle is traveling on. When the vibration parameters of the road inspection vehicle change during the driving process, the road inspection vehicle automatically records the second physical location of the road corresponding to the change in vibration parameters. Then, a second road surface image of the road can be acquired based on the second physical location. Thus, the presence of defects on the road can be further analyzed based on the second road surface image. If defects are indeed present on the road, the geographical location of the defects can be found through the second physical location, which facilitates the maintenance of road defects by the staff.

[0062] S2105: When the acceleration parameters change, record the third physical position of the road corresponding to the change in acceleration parameters, and acquire the third road surface image based on the third physical position.

[0063] In this embodiment, when the acceleration parameters of the road inspection vehicle change, specifically when the road inspection vehicle experiences negative acceleration, it indicates that there may be defects on the road that the road inspection vehicle is traveling on. Therefore, when the acceleration parameters of the road inspection vehicle change during its journey, the road inspection vehicle automatically records the third physical location of the road corresponding to the change in acceleration parameters. Then, it can collect a third road surface image based on the third physical location. Thus, it can further analyze whether there are defects on the road based on the third road surface image. If there are indeed defects on the road, the geographical location of the defects can be found through the third physical location, which facilitates the maintenance of the road by the staff.

[0064] S2106: Determine whether there are road defects based on the second and / or third road surface images.

[0065] In this embodiment, the presence of road defects can be further determined and analyzed based on the second road surface image and / or the third road surface image; and when defects are indeed present on the road, the defects can be located using the second physical location and / or the third physical location, thereby facilitating maintenance by staff.

[0066] S220: If the road surface shows signs of damage, the road is considered to be in an abnormal condition. S230: If the road does not show any signs of damage, then the road is considered to be in normal condition.

[0067] In this embodiment, through judgment and analysis, when the road surface has defects, it can be proven that the road is in an abnormal condition; conversely, when the road surface does not have defects, it can be proven that the road is not in an abnormal condition.

[0068] S300: If there are abnormal conditions on the road, record the abnormal conditions and issue an alarm based on the abnormal conditions.

[0069] In this embodiment, when there is an abnormality in the road, the abnormality can be recorded, and then an alarm can be issued based on the abnormality to remind staff to maintain the road defects as soon as possible.

[0070] In this embodiment, the alarm method can be either SMS notification or voice notification. Specifically, when using SMS notification, the abnormal situation can be sent to the staff's mobile terminal in real time via SMS; when using voice notification, the abnormal situation can be sent to the staff's mobile terminal in real time via voice, thereby facilitating the staff to maintain road defects as quickly as possible.

[0071] Among them, reference Figure 8 This is a road cross-section diagram for the specific implementation of this application.

[0072] Once it is determined whether there are any defects on the road surface, the damage status of these defects can be statistically summarized and a summary table can be generated.

[0073] The implementation principle of this application embodiment is as follows: road detection information is collected in real time by a road detection vehicle, and then the road detection information is analyzed to determine whether there are any abnormalities on the road. When there are abnormalities, the abnormalities can be recorded and alarms can be issued based on the abnormalities. Thus, on the one hand, the road conditions can be monitored in real time, and on the other hand, when there are abnormalities on the road, the abnormalities can be recorded and alarms can be issued based on the abnormalities, thereby improving the efficiency of road detection.

[0074] This application discloses an automatic data acquisition system for highway pavement defects, referring to... Figure 9 It includes an acquisition module 1, a judgment module 2, and an execution module 3. Specifically, the acquisition module 1 can acquire road detection information, which includes first data and second data. The judgment module 2 can determine whether there are any abnormalities in the road based on the first data and the second data. When there are abnormalities in the road, the execution module 3 can record the abnormalities and issue an alarm based on the abnormalities.

[0075] In this embodiment, the automatic highway pavement defect acquisition system uses the automatic highway pavement defect acquisition method. Therefore, the specific details of the automatic highway pavement defect acquisition system will not be repeated here.

[0076] This application discloses a terminal, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. When the processor executes the computer program, it performs the automatic collection method for highway pavement defects described in the above embodiment.

[0077] In one embodiment of this application, the terminal may be a desktop computer, a laptop computer, or a cloud server, and the terminal includes, but is not limited to, a processor and a memory. For example, the terminal may also include input / output devices, network access devices, and a bus.

[0078] In one embodiment of this application, the processor may be a central processing unit (CPU). Of course, depending on the actual use, other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. may also be used. The general-purpose processor may be a microprocessor or any conventional processor, etc., and this application does not limit it in this regard.

[0079] In one embodiment of this application, the memory can be an internal storage unit of the terminal, such as the terminal's hard disk or memory, or an external storage device of the terminal, such as a plug-in hard disk, smart memory card (SMC), secure digital card (SD), or flash memory card (FC) equipped on the terminal. The memory can also be a combination of the terminal's internal storage unit and external storage device. The memory is used to store computer programs and other programs and data required by the terminal. The memory can also be used to temporarily store data that has been output or will be output. This application does not limit this.

[0080] In this terminal, the automatic collection method for highway pavement defects described in the above embodiment is stored in the terminal's memory and loaded onto the terminal's processor. This allows the user to establish a connection with the system through the terminal and query the various contents processed by the system.

[0081] This application discloses a computer-readable storage medium storing a computer program, wherein when the computer program is loaded by a processor, it executes the automatic collection method for highway pavement defects described above.

[0082] In one embodiment of this application, the computer program may be stored in a computer-readable storage medium. The computer program includes computer program code, which may be in the form of source code, object code, executable file, or certain middleware. The computer-readable storage medium includes any entity or device capable of carrying computer program code, recording medium, USB flash drive, portable hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the computer-readable storage medium includes, but is not limited to, the above-mentioned components.

[0083] In this embodiment, the automatic collection method for highway pavement defects of the above embodiment is stored in the computer-readable storage medium and loaded and executed on the processor. After the computer-readable storage medium is loaded into any computer, any computer can execute the automatic collection method for highway pavement defects of the above embodiment.

[0084] The embodiments described in this specific implementation are preferred embodiments of this application and are not intended to limit the scope of protection of this application. Identical components are represented by the same reference numerals. Therefore, all equivalent changes made to the structure, shape, and principle of this application should be included within the scope of protection of this application.

Claims

1. A method for automatically collecting pavement defects on highways, characterized in that, include: Obtain road detection information, which includes first data and second data; Based on the first data and the second data, determine whether there are any abnormalities in the road; If the road has the aforementioned abnormal situation, the abnormal situation is recorded, and an alarm is issued based on the abnormal situation.

2. The automatic collection method for highway pavement defects according to claim 1, characterized in that, The acquisition of road detection information specifically includes: The camera device acquires video of the road surface, and the positioning device acquires the first physical location corresponding to the video of the road surface. The road surface video is processed to obtain the first road surface image of the road.

3. The automatic collection method for highway pavement defects according to claim 2, characterized in that, The process of processing the road surface video to obtain the first road surface image specifically includes: The video stream of the road surface is extracted to obtain at least one frame of image video stream; The first road surface image is obtained by filtering at least one frame image video stream according to preset rules.

4. The automatic collection method for highway pavement defects according to claim 2, characterized in that, The acquisition of road detection information specifically includes: Obtain the driving speed of the road inspection vehicle; The driving status of the road inspection vehicle is determined based on the driving speed. If the road inspection vehicle is traveling at high speed, the vibration parameters of the road inspection vehicle during the driving process are collected in real time. If the road inspection vehicle is traveling at a low speed, the acceleration parameters of the road inspection vehicle during the driving process are collected in real time.

5. The automatic collection method for highway pavement defects according to claim 4, characterized in that, The step of determining whether there is an anomaly in the road based on the first data and the second data specifically includes: Based on the first road surface image, the vibration parameters, and the acceleration parameters, it is determined whether the road has any defects. If the road exhibits signs of damage, then the road is deemed to be in an abnormal condition. If the road does not exhibit the aforementioned defects, then the road is deemed to be free from the aforementioned abnormal conditions.

6. The automatic collection method for highway pavement defects according to claim 5, characterized in that, The step of determining whether the road has defects based on the first road surface image specifically includes: Obtain the area in the first road surface image that is inconsistent with the preset road surface color; Extract labeled features based on the inconsistent regions; Determine whether the marked feature is the disease feature.

7. The automatic collection method for highway pavement defects according to claim 5, characterized in that, The step of determining whether the road has defects based on the vibration parameters and the acceleration parameters specifically includes: When the vibration parameters change, the second physical position of the road corresponding to the change in vibration parameters is recorded, and a second road surface image of the road is acquired based on the second physical position; When the acceleration parameter changes, the third physical position of the road corresponding to the change in acceleration parameter is recorded, and a third road surface image of the road is acquired based on the third physical position; The presence of the road defects is determined based on the second road surface image and the third road surface image.

8. An automatic data acquisition system for highway pavement defects, characterized in that, include: The acquisition module (1) is used to acquire road detection information, which includes first data and second data; The judgment module (2) is used to determine whether there is an abnormality in the road based on the first data and the second data; The execution module (3) is used to record the abnormal situation when the abnormal situation exists on the road, and to issue an alarm based on the abnormal situation.

9. A terminal, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, When the processor loads the computer program, it executes the method of any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is loaded by the processor, it executes the method of any one of claims 1-7.

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