A pavement disease influence range detection device and evaluation method

Abstract

The present invention relates to the technical field of road disease detection, and particularly to a device and an evaluation method for detecting the influence range of road surface diseases. The device includes a traffic vehicle, a laser dynamic deflection meter, a road surface damage detection mechanism, and a processor; the laser dynamic deflection meter is fixed on the vehicle and is used for detecting the deflection data of the road surface; the road surface damage detection mechanism includes a camera, which is fixed on the traffic vehicle and is used for taking pictures of the road surface image; the processor is fixed inside the traffic vehicle and is electrically connected to the laser dynamic deflection meter and the road surface damage detection mechanism; the processor is used for: obtaining the deflection data and damage data of the road section; marking the stake numbers for the road surface damage data, and recording the deflection data on both sides of the damaged road surface. The present invention realizes the separate analysis and evaluation of the influences of the disease areas and non-disease areas, can more pertinently formulate treatment plans for road sign damage diseases, can improve the maintenance efficiency and save maintenance funds.

Description

Technical Field

[0001] The present invention relates to the technical field of road disease detection, and in particular to a device and evaluation method for detecting the influence range of road surface diseases. Background Art

[0002] Road surface diseases refer to various damages and deformations that occur on the road surface after a period of traffic, and common diseases include cracks, potholes, ruts, subsidence, etc.; with the rapid development of the road construction industry, the demand for road surface maintenance is also increasing continuously, and when formulating a road surface maintenance plan, road surface disease detection data is required as a support;

[0003] In the related art, a deflectometer is mostly used to detect the road surface. However, when using a deflectometer for detection, the detection results mostly evaluate the entire road surface. The inventor found that when implementing the above solution, the existing deflection data of the detection cannot distinguish the deflection data at the disease location from the deflection data at the non-disease location, and the influence range of the disease on the road surface is not clear, and accurate data support cannot be provided for road surface maintenance. Summary of the Invention

[0004] In view of at least one of the above technical problems, the present invention provides a device and evaluation method for detecting the influence range of road surface diseases to improve the detection accuracy of the influence range of road surface diseases.

[0005] According to a first aspect of the present invention, there is provided a device for detecting the influence range of road surface diseases, including:

[0006] Including a traffic vehicle, a laser dynamic deflectometer, a road surface damage detection mechanism, and a processor;

[0007] The laser dynamic deflectometer is fixed on the vehicle and is used for detecting the deflection data of the road surface;

[0008] The road surface damage detection mechanism includes a camera, which is fixed on the traffic vehicle and is used for taking pictures of the road surface image;

[0009] The processor is fixed inside the traffic vehicle and is electrically connected to the laser dynamic deflectometer and the road surface damage detection mechanism;

[0010] The processor is used for:

[0011] Obtaining the deflection data and damage data of the road section;

[0012] Marking the stake numbers for the road surface damage data and recording the deflection data on both sides of the damaged road surface.

[0013] In some embodiments of the present invention, the laser dynamic deflectometer is fixed in the middle of the traffic vehicle, and the road surface damage detection mechanism is fixed at the tail of the traffic vehicle. The distance between the laser dynamic deflectometer and the road surface damage detection mechanism is D.

[0014] In some embodiments of the present invention, when the processor marks the stake number for the road surface damage data, when the detection direction is upstream, the stake number position of the detection result is increased by D, and when the detection direction is downstream, the stake number position of the detection result is decreased by D.

[0015] In some embodiments of the present invention, the road surface damage detection mechanism uses a deep learning model to determine the defect category and location.

[0016] In some embodiments of the present invention, the traffic vehicle is an automobile or a truck.

[0017] According to the second aspect of the present invention, there is also provided a method for evaluating the influence range of road surface diseases, including the following steps:

[0018] Obtain the road surface deflection data and at the same time obtain the road surface damage data;

[0019] Integrate the road surface deflection data and the damage data, mark the stake number of the road surface damage data and the deflection data on both sides of the stake number;

[0020] Obtain the deflection data on both sides with the disease stake number position as the center, calculate the deflection standard deviation at equal intervals from the center to both sides. When the deflection standard deviation of consecutive set points is less than the set value, the range from the center to the outermost point that meets the conditions is the influence range of the road surface disease structural strength.

[0021] In some embodiments of the present invention, the deflection standard deviation of consecutive set points being less than the set value means that the deflection standard deviation of five consecutive points is less than 5%.

[0022] In some embodiments of the present invention, the road surface deflection data is measured using a laser dynamic deflectometer.

[0023] In some embodiments of the present invention, the road surface damage data is identified using a machine learning model with a camera.

[0024] In some embodiments of the present invention, after determining the influence range of the road surface disease structural strength, a range mark is made on the damage data image.

[0025] The beneficial effects of the present invention are as follows: By means of the laser dynamic deflection detection technology and the pavement damage detection technology, the present invention realizes accurate one-to-one positioning between the surface damage diseases and the laser dynamic deflection, so as to be able to evaluate the influence of the damage on the pavement structure strength, realizes the separate analysis and evaluation of the influences of the damaged parts and the non-damaged parts, and by determining the influence range of the diseases and evaluating the severity of the diseases, the present invention can formulate a treatment plan for the road sign damage diseases more pertinently, and can improve the maintenance efficiency and save the maintenance funds. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0027] Figure 1 It is a schematic structural diagram of a pavement disease influence range detection device in an embodiment of the present invention;

[0028] Figure 2 It is a step flow chart of a pavement disease influence range evaluation method in an embodiment of the present invention;

[0029] Figure 3 It is a schematic diagram of the pavement disease influence range in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0031] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly on the other element or there can also be a middle element. When an element is considered to be "connected" to another element, it can be directly connected to the other element or there may be a middle element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are only for the purpose of illustration and do not represent the only implementation manner.

[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs. The terms used in the description of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0033] As Figure 1 shown in the pavement disease influence range detection device, including a traffic vehicle 1, a laser dynamic deflection meter 2, a pavement damage detection mechanism 3 and a processor 4; it can be understood that in the embodiment of the present invention, the traffic vehicle 1 has various forms, which can be a car, a truck or an autonomous vehicle;

[0034] The laser dynamic deflection meter is fixed on the vehicle and is used for detecting the pavement deflection data. In the embodiment of the present invention, the laser dynamic deflection meter 2 is used to measure the pavement deflection data, and the accuracy is in the order of micrometers;

[0035] The pavement damage detection mechanism 3 includes a camera, which is fixed on the traffic vehicle 1 and is used for taking pictures of the pavement; there are various ways to detect pavement damage, which can be carried out by manual post-recognition of photos, or can be trained by a deep learning model. The pavement damage data obtained through this method can be displayed in the form of coordinate information or image information; the deep learning model is a prior art, and its principle and training method will not be described in detail here.

[0036] The processor 4 is fixed inside the traffic vehicle 1 and is electrically connected to the laser dynamic deflection meter 2 and the pavement damage detection mechanism 3. In the embodiment of the present invention, the processor 4 is used to: obtain the deflection data and damage data of the road section; mark the pile number of the pavement damage data, and record the deflection data on both sides of the damaged pavement. In this way, by the movement of the traffic vehicle 1, the deflection data of the pavement, the pile number of the pavement damage and the deflection data on both sides of the pile number can be obtained synchronously. In this way, it is convenient for the staff to accurately control the condition of the pavement, distinguish the deflection data of the disease and the non-disease part of the pavement, and thus provide more accurate data support for pavement maintenance.

[0037] On the basis of the above embodiment, in some specific embodiments of the present invention, as Figure 1 shown, the laser dynamic deflection meter 2 is fixed in the middle of the traffic vehicle 1, and the pavement damage detection mechanism 3 is fixed at the tail of the traffic vehicle 1. The distance between the laser dynamic deflection meter 2 and the pavement damage detection mechanism 3 is D. By this fixing method, on the one hand, the stability of the laser dynamic deflection meter 2 can be ensured, and on the other hand, it can also ensure that the camera can clearly take pictures of the pavement. By recording the distance D between the two, it is convenient for the later data processing.

[0038] Specifically, when the processor 4 marks the pile number of the pavement damage data, when the detection direction is upward, the pile number position of the detection result is increased by D, and when the detection direction is downward, the pile number position of the detection result is decreased by D. By this setting method, it can be ensured that the data at the damaged pavement is the same as the pavement deflection data, improving the accuracy of the detection.

[0039] In an embodiment of the present invention, a method for evaluating the influence range of pavement diseases is further provided. By applying the above pavement disease influence range detection device, as Figure 2 shown in the following steps:

[0040] Obtain pavement deflection data and at the same time obtain pavement damage data. It can be understood that those skilled in the art can understand the specific methods of obtaining pavement deflection data and damage data by reading the above description of the specification part;

[0041] Integrate the pavement deflection data and damage data, and mark the station number of the pavement damage data and the deflection data on both sides of the station number. Here, the integration is the calculation of the distance D between the laser dynamic deflection meter 2 and the pavement damage detection mechanism 3 during the up and down travel as described above, and the combination of the two data by adding or subtracting D;

[0042] Obtain the deflection data on both sides with the disease station number position as the center, calculate the standard deviation of the deflection at equal intervals from the center to both sides. When the standard deviation of the deflection at continuously set points is less than the set value, the range from the center to the outermost point that meets the conditions is the influence range of the pavement disease structural strength.

[0043] Specifically, as Figure 3 shown in the present invention, in some embodiments of the present invention, the standard deviation of the deflection at continuously set points being less than the set value means that the standard deviation of the deflection between five consecutive points is less than 5%. Here, the five points refer to the detection points with equal intervals. For example, in some embodiments of the present invention, the distance between two adjacent monitoring points is 20 cm, then five consecutive points are 80 cm. In this way, please continue to refer to Figure 3 , and at this time, the disease influence range is the range from the disease center to the outermost point of five consecutive points.

[0044] In an embodiment of the present invention, the pavement deflection data is measured by a laser dynamic deflection meter 2. It can be understood that the pavement damage data is identified by a machine learning model using a camera. For details, reference can be made to the above description and will not be elaborated here.

[0045] Based on the above embodiments, in some embodiments of the present invention, after determining the influence range of the pavement disease structural strength, a range mark is made on the damage data image. When specifically marking, it can be marked in the form of combining the range influence distance with the deflection data at specific coordinate points; or directly marked in the form of an image, so as to improve the accuracy of understanding the road conditions and the reliability when formulating the pavement maintenance plan.

[0046] Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification only illustrates the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for evaluating the influence range of pavement diseases, characterized in that, Apply a detection device for the influence range of pavement diseases, which includes a traffic vehicle, a laser dynamic deflection meter, a pavement damage detection mechanism, and a processor; The laser dynamic deflection meter is fixed on the vehicle and is used for detecting pavement deflection data; The pavement damage detection mechanism includes a camera, which is fixed on the traffic vehicle and is used for taking pavement images; The processor is fixed inside the traffic vehicle and is electrically connected to the laser dynamic deflection meter and the pavement damage detection mechanism; The processor is used to: obtain the deflection data and damage data of a road section; mark the stake number of the pavement damage data and record the deflection data on both sides of the damaged pavement; The method includes the following steps: Obtain pavement deflection data and at the same time obtain pavement damage data; Integrate the pavement deflection data and damage data, mark the stake number of the pavement damage data and the deflection data on both sides of the stake number; Obtain the deflection data on both sides centered on the stake number of the disease, calculate the deflection standard deviation at equal intervals from the center to both sides. When the deflection standard deviation of consecutive set points is less than the set value, the range from the center to the outermost point that meets the conditions is the influence range of the pavement disease structural strength.

2. The method for evaluating the influence range of pavement diseases according to claim 1, wherein The laser dynamic deflection meter is fixed in the middle of the traffic vehicle, and the pavement damage detection mechanism is fixed at the tail of the traffic vehicle. The distance between the laser dynamic deflection meter and the pavement damage detection mechanism is D.

3. The method for evaluating the influence range of pavement diseases according to claim 2, characterized in that When the processor marks the stake number of the pavement damage data, when the detection direction is upward, the stake number position of the detection result is increased by D, and when the detection direction is downward, the stake number position of the detection result is decreased by D.

4. The method for evaluating the influence range of pavement diseases according to claim 1, wherein, The pavement damage detection mechanism uses a deep learning model to determine the defect category and location.

5. The method for evaluating the influence range of pavement diseases according to claim 1, wherein, The traffic vehicle is an automobile.

6. The method for evaluating the influence range of pavement diseases according to claim 1, characterized in that, The continuous set point deflection standard deviation being less than the set value means that the deflection standard deviation between five consecutive points is less than 5%.

7. The method for evaluating the influence range of pavement diseases according to claim 1, characterized in that The pavement deflection data is measured by a laser dynamic deflection meter.

8. The method for evaluating the influence range of pavement diseases according to claim 1, characterized in that The pavement damage data is identified by a camera using a machine learning model.

9. The method for evaluating the influence range of pavement diseases according to claim 8, characterized in that, After determining the influence range of the pavement disease structural strength, mark the range on the damaged data image.

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