CN113033368B - Dynamic monitoring method and system for compaction pass number of asphalt pavement - Google Patents
Dynamic monitoring method and system for compaction pass number of asphalt pavement Download PDFInfo
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- CN113033368B CN113033368B CN202110292764.2A CN202110292764A CN113033368B CN 113033368 B CN113033368 B CN 113033368B CN 202110292764 A CN202110292764 A CN 202110292764A CN 113033368 B CN113033368 B CN 113033368B
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- 238000000034 method Methods 0.000 title claims abstract description 33
- 238000012544 monitoring process Methods 0.000 title claims abstract description 32
- 238000005056 compaction Methods 0.000 title claims abstract description 29
- 239000010426 asphalt Substances 0.000 title claims abstract description 28
- 238000005096 rolling process Methods 0.000 claims abstract description 43
- 230000009471 action Effects 0.000 claims abstract description 25
- 238000010276 construction Methods 0.000 claims abstract description 15
- 238000012545 processing Methods 0.000 claims description 26
- 238000006073 displacement reaction Methods 0.000 claims description 14
- 238000010191 image analysis Methods 0.000 claims description 10
- 230000004927 fusion Effects 0.000 claims description 6
- 238000007499 fusion processing Methods 0.000 claims description 6
- 230000008569 process Effects 0.000 description 6
- 238000004458 analytical method Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 238000013461 design Methods 0.000 description 3
- 238000001514 detection method Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000009434 installation Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 239000011384 asphalt concrete Substances 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/25—Fusion techniques
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
- G06T7/246—Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/50—Depth or shape recovery
- G06T7/521—Depth or shape recovery from laser ranging, e.g. using interferometry; from the projection of structured light
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
- G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10028—Range image; Depth image; 3D point clouds
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30248—Vehicle exterior or interior
- G06T2207/30252—Vehicle exterior; Vicinity of vehicle
Abstract
The application discloses a dynamic monitoring method and a system for compaction pass number of an asphalt pavement, wherein the method comprises the following steps: the method comprises the steps that video images and three-dimensional laser point cloud data in a rolling working area are respectively collected in real time by using camera equipment and laser point cloud equipment which are arranged on a paver; establishing a three-dimensional laser point cloud coordinate system with a dynamically changed coordinate origin, and recording three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system to obtain three-dimensional laser point cloud models at different moments; performing machine vision identification and tracking on the video image, and determining the action range of each road roller at different moments; and respectively fusing and superposing the video image and the laser point cloud model image at the same moment to obtain data point coordinates in the working range of each road roller at different moments, and counting the times of occurrence of each coordinate point in the three-dimensional laser point cloud model in the working range of the road roller to obtain the compaction pass number of each coordinate point. By utilizing the application, the dynamic monitoring of the rolling construction condition can be realized.
Description
Technical Field
The application relates to the field of road engineering construction quality monitoring and detection, in particular to a dynamic monitoring method and system for compaction pass number of an asphalt pavement.
Background
Common asphalt concrete is a typical temperature sensitive material, and performing compaction at different temperatures will result in different structural characteristics, resulting in different strength and fatigue properties. The asphalt pavement needs to be rolled by a road roller in the construction process, and the compaction times under certain temperature conditions are important indexes for ensuring the compactness of the asphalt pavement, and directly influence the service performance and durability of the asphalt pavement structure in the operation process. At present, the rolling pass number of the road roller is still difficult to determine in specific construction, and mainly depends on subjective judgment of constructors to count the rolling times, but larger errors often exist in the construction process, accurate data are difficult to obtain, and overvoltage and undervoltage conditions are easy to cause.
With the development of informatization technology, satellite positioning, image processing and other technologies are gradually applied to determining the rolling times in the construction process. The detection or monitoring technology for the rolling pass number of the asphalt pavement at the present stage mainly relies on the acquisition and tracking of the position information of the road roller, but under the condition of weaker signals or no signals such as GPS and the like, obvious position deviation can occur, so that the statistical error of the rolling pass number is directly caused, and the rolling quality of the asphalt pavement is affected.
Disclosure of Invention
Aiming at the problems in the prior art, the application provides a dynamic monitoring method and a system for the compaction pass number of an asphalt pavement, which realize continuous online real-time monitoring on the road base compaction quality.
Therefore, the application provides the following technical scheme:
a method for dynamically monitoring compaction pass of an asphalt pavement, comprising the following steps:
the method comprises the steps that video images and three-dimensional laser point cloud data in a rolling working area are respectively collected in real time by using camera equipment and laser point cloud equipment which are arranged on a paver;
establishing a three-dimensional laser point cloud coordinate system with a dynamically changed coordinate origin, and recording the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system to obtain three-dimensional laser point cloud models at different moments;
performing machine vision identification and tracking on the video image, and determining the action range of each road roller at different moments;
respectively fusing and superposing the video image and the laser point cloud model image at the same moment to obtain data point coordinates in the action range of each road roller at different moments;
and counting the times of each coordinate point in the three-dimensional laser point cloud model in the working range of the road roller according to the data point coordinates in the working range of the road roller, and obtaining the compaction pass number of each coordinate point.
Optionally, the establishing a three-dimensional laser point cloud coordinate system with a dynamically changed origin of coordinates, and recording the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system, to obtain three-dimensional laser point cloud models at different moments includes:
establishing a three-dimensional laser point cloud coordinate system by taking the position of the laser point cloud equipment as a coordinate origin, and updating the coordinate origin according to the positions of the laser point cloud equipment at different moments;
determining coordinates of the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system according to displacement of the paver at different moments;
and recording the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system according to the coordinates of the three-dimensional laser point cloud data to obtain three-dimensional laser point cloud models at different moments.
Optionally, the method further comprises:
and acquiring the motion parameters of the paver in real time, and determining the displacement of the paver at different moments and the positions of the laser point cloud equipment at different moments according to the motion parameters.
Optionally, the method further comprises: pre-establishing an identification model;
the machine vision identification and tracking are carried out on the video image, and the determination of the action range of each road roller at different moments comprises the following steps:
identifying the video image by using the identification model, and tracking an identification object to obtain Mask information of each road roller at different moments;
and determining the action range of the road roller according to Mask information of the road roller at different moments.
Optionally, the image capturing apparatus is a pan-tilt camera with an anti-shake function.
A dynamic monitoring system for compaction passes of asphalt pavement, the system comprising: the system comprises an image pickup device and a laser point cloud device which are arranged on a paver, and a data processing device which is respectively connected with the image pickup device and the laser point cloud device; the data processing apparatus includes: the system comprises a point cloud model building module, an image analysis module, a fusion processing module and a statistics module;
the camera equipment is used for acquiring video images in the rolling working area in real time and transmitting the acquired video images to the data processing equipment;
the laser point cloud device is used for collecting three-dimensional laser point cloud data in a rolling working area in real time and transmitting the collected three-dimensional laser point cloud data to the data processing device;
the point cloud model building module is used for building a three-dimensional laser point cloud coordinate system with a coordinate origin dynamically changed, and recording the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system to obtain three-dimensional laser point cloud models at different moments;
the image analysis module is used for carrying out machine vision identification and tracking on the video image to determine the action range of each road roller at different moments;
the fusion processing module is used for respectively carrying out fusion superposition on the video image and the laser point cloud model image at the same moment to obtain data point coordinates in the action range of each road roller at different moments;
and the statistics module is used for counting the times of occurrence of each coordinate point in the three-dimensional laser point cloud model in the working range of the road roller according to the data point coordinates in the working range of the road roller, and obtaining the compaction pass number of each coordinate point.
Optionally, the point cloud model building module includes:
the coordinate system establishing unit is used for establishing a three-dimensional laser point cloud coordinate system by taking the position of the laser point cloud equipment as a coordinate origin, and updating the coordinate origin according to the positions of the laser point cloud equipment at different moments;
the point cloud data coordinate determining unit is used for determining coordinates of the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system according to displacement of the paver at different moments;
and the model generating unit is used for recording the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system according to the coordinates of the three-dimensional laser point cloud data to obtain three-dimensional laser point cloud models at different moments.
Optionally, the system further comprises: the vehicle-mounted equipment is arranged on the paver; the data processing apparatus further includes: a position determining module;
the vehicle-mounted equipment is used for acquiring the motion parameters of the paver in real time;
the position determining module is used for determining the displacement of the paver at different moments and the positions of the laser point cloud equipment at different moments according to the motion parameters.
Optionally, the data processing apparatus further comprises: the recognition model construction module is used for pre-building a recognition model;
the image analysis module comprises:
the image recognition unit is used for recognizing the video image by using the recognition model and tracking a recognition object to obtain Mask information of each road roller at different moments;
and the action range determining unit is used for determining the action range of the road roller according to Mask information of the road roller at different moments.
Optionally, the image capturing apparatus is a pan-tilt camera with an anti-shake function.
According to the dynamic monitoring method and system for the compaction pass number of the asphalt pavement, provided by the embodiment of the application, video images and three-dimensional laser point cloud data in a rolling working area are respectively acquired in real time by using the camera equipment and the laser point cloud equipment which are arranged on the paver; the paver is used as a movable coordinate origin to form a movable three-dimensional laser point cloud data set, the rolling condition of each road roller on the asphalt pavement is determined through image recognition, tracking and data fusion, dynamic monitoring of rolling construction conditions is achieved, accurate statistical results of rolling pass numbers are obtained, the fact that the rolling pass numbers of the asphalt pavement meet design index requirements is guaranteed, and compactness of a pavement structure is guaranteed.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments described in the present application, and other drawings may be obtained according to these drawings for a person having ordinary skill in the art.
FIG. 1 is a flow chart of a method for dynamically monitoring compaction passes of an asphalt pavement according to an embodiment of the present application;
fig. 2 is a block diagram of a dynamic monitoring system for compaction passes of an asphalt pavement according to an embodiment of the present application.
Detailed Description
In order to make the solution of the embodiment of the present application better understood by those skilled in the art, the embodiment of the present application is further described in detail below with reference to the accompanying drawings and embodiments.
As shown in fig. 1, the flow chart of the dynamic monitoring method for the compaction pass number of the asphalt pavement according to the embodiment of the application comprises the following steps:
and step 101, respectively acquiring video images and three-dimensional laser point cloud data in a rolling working area in real time by using camera equipment and laser point cloud equipment which are arranged on the paver.
Specifically, a special equipment support with a certain height can be arranged on the paver, high-definition monitoring camera equipment and high-precision laser point cloud equipment are respectively installed at the top end of the support, the high-definition monitoring camera equipment and the high-precision laser point cloud are subjected to nodding and rolling in a working area with a certain height, and the installation height of the equipment is controlled by covering the rolling working area behind the paver in a shooting range. For example, the height of the support can be 5-8 m according to practical situations, and the support needs to ensure that the shooting range of equipment can reach at least 100m or cover the range of a rolling construction work area.
The high-definition monitoring camera equipment is used for collecting video images in a rolling working area, and the resolution and the frame number of the high-definition monitoring camera equipment are not lower than 1080P and 30FPS so as to ensure that the photographed images are clear and effective. In order to reduce the influence of video image quality caused by operation shake of the paver and the like, a cradle head camera with an anti-shake function can be selected for shooting, and the shot video image can be transmitted to a site or a remote analysis computer for storage in real time.
The high-precision laser point cloud device is used for collecting three-dimensional laser point cloud data in a rolling working area, the collecting speed of the point cloud device is not lower than 240000 points per second, and the collected three-dimensional laser point cloud data can be transmitted to a site or a remote analysis computer for storage in real time.
The high-definition monitoring camera device and the high-precision laser point cloud device can be arranged at the same point so as to reduce data errors.
Step 102, a three-dimensional laser point cloud coordinate system with a dynamically changed coordinate origin is established, and the three-dimensional laser point cloud data are recorded in the three-dimensional laser point cloud coordinate system, so that three-dimensional laser point cloud models at different moments are obtained.
That is, three-dimensional laser point cloud data acquired at different times needs to be recorded in the three-dimensional laser point cloud coordinate system corresponding to the time.
Specifically, a three-dimensional laser point cloud coordinate system is established by taking the position of the laser point cloud device as a coordinate origin, and the coordinate origin is updated according to the positions of the laser point cloud device at different moments.
In addition, the coordinates of the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system are determined according to the displacement of the paver at different moments; and recording the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system according to the coordinates of the three-dimensional laser point cloud data to obtain three-dimensional laser point cloud models at different moments.
The displacement of the paver at different moments and the position of the laser point cloud device at different moments can be obtained according to the motion parameters of the paver, wherein the motion parameters comprise: movement azimuth and movement speed. In practical application, the motion parameters of the paver can be obtained in real time through the vehicle-mounted equipment of the paver, and the motion parameters are transmitted to the on-site or remote analysis computer in real time.
For each data point in the three-dimensional laser point cloud model at different moments, the coordinates of the data points belonging to the same point of the actual pavement structure can be determined according to the following method.
Assume that at an initial time, an initial coordinate of the origin of the coordinate system is (0, 0) and a coordinate of any point a in the three-dimensional laser point cloud model is (X a ，Y a ，Z a ). According to the displacement of the paver at the time t, is (l t ，m t ，n t ) The coordinates of any point a at this time are (X) a +l t ，Y a +m t ，Z a +n t ) The coordinate information of all three-dimensional laser point cloud data points in the rolling working range at different moments can be shown in the following table:
table 1 data point coordinates of Rolling working range of three-dimensional laser point cloud model
And 103, performing machine vision identification and tracking on the video image, and determining the action range of each road roller at different moments.
In the embodiment of the application, the received video data in the rolling working range can be processed in real time by a site or remote computer, the positions of the road rollers at different moments in the video data are identified by an artificial intelligent machine vision technology, the positions are numbered and tracked, mask information of the real-time positions of the road rollers is formed, and the working range of the road rollers at the moment can be determined according to the Mask information of the road rollers at different moments.
Specifically, a YOLO V3 algorithm framework may be previously adopted to build an identification model, and the identification model may be used to identify the road roller in the video image. And the MOT SORT algorithm can be adopted for tracking the position of the road roller so as to achieve the purpose of dynamically obtaining Mask information of each road roller.
And 104, respectively fusing and superposing the video image at the same moment and the laser point cloud model image to obtain the data point coordinates in the action range of each road roller at different moments.
For example, the video image and the three-dimensional laser point cloud model image after identification are extracted respectively at the frequency of 1s, the video image with the same time and the three-dimensional laser point cloud model image are fused and overlapped, laser point cloud data in the three-dimensional laser point cloud model at the corresponding moment is determined through Mask information obtained by identifying the video image at different moments, and therefore data points in the action range of each road roller at different moments are obtained.
The data points in the action range of the road roller are all data points overlapped with the Mask information in the three-dimensional laser point cloud model image.
Specifically, in practical application, the high-definition monitoring camera and the high-precision laser point cloud device can be calibrated to obtain internal parameters and external parameters, including parameters such as focal length, pixel size, position and direction, and then three-dimensional point cloud data are projected into the two-dimensional identification video image according to the internal parameters and the external parameters, so that three-dimensional space coordinates corresponding to pixel points in each two-dimensional identification video image can be obtained.
And 105, counting the times of each coordinate point in the three-dimensional laser point cloud model in the working range of the road roller according to the data point coordinates in the working range of the road roller, and obtaining the compaction pass number of each coordinate point.
And counting the times of occurrence of each coordinate point in the three-dimensional laser point cloud model at different moments in the working range of the road roller, wherein the times are compaction pass numbers of the coordinate points.
According to the dynamic monitoring method for the compaction pass number of the asphalt pavement, provided by the embodiment of the application, video images and three-dimensional laser point cloud data in a rolling working area are respectively acquired in real time by using camera equipment and laser point cloud equipment which are arranged on a paver; the paver is used as a movable coordinate origin to form a movable three-dimensional laser point cloud data set, the rolling condition of each road roller on the asphalt pavement is determined through image recognition, tracking and data fusion, dynamic monitoring of rolling construction conditions is achieved, accurate statistical results of rolling pass numbers are obtained, the fact that the rolling pass numbers of the asphalt pavement meet design index requirements is guaranteed, and compactness of a pavement structure is guaranteed.
Correspondingly, the embodiment of the application also provides a dynamic monitoring system for the compaction pass number of the asphalt pavement, which is shown in fig. 2 and is a structural block diagram of the system.
In this embodiment, the system comprises: an image pickup apparatus 21 and a laser point cloud apparatus 22 mounted on the paver 20, and a data processing apparatus 30 connected to the image pickup apparatus 21 and the laser point cloud apparatus 22, respectively. Wherein:
the camera device 21 is used for collecting video images in a rolling working area in real time and transmitting the collected video images to the data processing device 30;
the laser point cloud device 22 is configured to collect three-dimensional laser point cloud data in the rolling working area in real time, and transmit the collected three-dimensional laser point cloud data to the data processing device 30.
In practical application, a special equipment support with a certain height can be arranged on the paver 10, a high-definition monitoring camera device and a high-precision laser point cloud device are respectively installed at the top end of the support, the high-definition monitoring camera device and the high-precision laser point cloud are subjected to nodding and rolling in a certain height, and the installation height of the equipment is determined by covering a rolling working area behind the paver with a shooting range. In order to reduce the influence of the quality of the video image caused by the shake of the paver, the camera device 21 may be a pan-tilt camera with an anti-shake function.
The image capturing device 21 and the laser point cloud device 22 may be connected to the data processing device 30 in a wired manner (such as a data line), or may be connected in a wireless manner, which is not limited to the embodiment of the present application. The video image captured by the image capturing apparatus 21 and the three-dimensional laser point cloud data acquired by the laser point cloud apparatus 22 may be transmitted in real time to the data processing apparatus 30 provided on site or remotely for storage.
It should be noted that the data processing device 30 may be a mobile terminal, a computer, a tablet device, a personal digital assistant, or the like. The data processing device 30 may include one or more processors, memory; the memory is used for storing computer executable instructions, and the processor is used for executing the computer executable instructions so as to realize the storage and analysis processing of the video image and the three-dimensional laser point cloud data.
In the embodiment of the present application, the data processing device 30 includes: the system comprises a point cloud model establishment module 31, an image analysis module 32, a fusion processing module 33 and a statistics module 34. Wherein:
the point cloud model building module 31 is configured to build a three-dimensional laser point cloud coordinate system with a dynamically changed origin of coordinates, and record the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system to obtain three-dimensional laser point cloud models at different moments;
the image analysis module 32 performs machine vision recognition and tracking on the video image to determine the action range of each road roller at different moments;
the fusion processing module 33 is configured to respectively perform fusion and superposition on a video image and a laser point cloud model image at the same moment, so as to obtain coordinates of data points in the action range of each road roller at different moments;
and the statistics module 34 is used for counting the times of occurrence of each coordinate point in the three-dimensional laser point cloud model in the working range of the road roller according to the data point coordinates in the working range of the road roller, and obtaining the compaction pass number of each coordinate point.
The above-mentioned point cloud model building module 31 may specifically include the following units:
the coordinate system establishing unit is used for establishing a three-dimensional laser point cloud coordinate system by taking the position of the laser point cloud equipment as a coordinate origin, and updating the coordinate origin according to the positions of the laser point cloud equipment at different moments;
the point cloud data coordinate determining unit is used for determining coordinates of the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system according to displacement of the paver at different moments;
and the model generating unit is used for recording the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system according to the coordinates of the three-dimensional laser point cloud data to obtain three-dimensional laser point cloud models at different moments.
In practical application, the displacement of the paver at different moments and the positions of the laser point cloud device at different moments can be obtained according to the motion parameters of the paver, wherein the motion parameters comprise: movement azimuth and movement speed.
Accordingly, an in-vehicle device (not shown) may be installed on the paving machine 20 to acquire the motion parameters of the paving machine in real time and transmit the motion parameters to the data processing device 30 in real time.
Accordingly, the data processing device 30 may further include: and the position determining module (not shown) is used for determining the displacement of the paver at different moments and the positions of the laser point cloud equipment at different moments according to the motion parameters.
In practice, the image analysis module 32 may identify the road roller in the video image using a pre-established identification model. And the MOT SORT algorithm can be adopted for tracking the position of the road roller so as to achieve the purpose of dynamically obtaining Mask information of each road roller.
The recognition model may be constructed by a corresponding recognition model construction module (not shown), which may be part of the data processing apparatus 30 or may be independent of the data processing apparatus 30, which is not limited to this embodiment of the present application.
Correspondingly, the image analysis module specifically may include the following units:
the image recognition unit is used for recognizing the video image by using the recognition model and tracking a recognition object to obtain Mask information of each road roller at different moments;
and the action range determining unit is used for determining the action range of the road roller according to Mask information of the road roller at different moments.
The dynamic monitoring system for the compaction passes of the asphalt pavement provided by the embodiment of the application utilizes the camera equipment and the laser point cloud equipment which are arranged on the paver to respectively acquire video images and three-dimensional laser point cloud data in a rolling working area in real time; the paver is used as a movable coordinate origin to form a movable three-dimensional laser point cloud data set, the rolling condition of each road roller on the asphalt pavement is determined through image recognition, tracking and data fusion, dynamic monitoring of rolling construction conditions is achieved, accurate statistical results of rolling pass numbers are obtained, the fact that the rolling pass numbers of the asphalt pavement meet design index requirements is guaranteed, and compactness of a pavement structure is guaranteed.
According to the method and the system for dynamically monitoring the compaction pass number of the asphalt pavement, provided by the embodiment of the application, the laser point cloud equipment is adopted to construct a three-dimensional dynamic model in the construction process, the acquisition precision can reach the level of 0.1mm, and the working position of the road roller can be accurately determined; the method of combining video data and laser point cloud is adopted for real-time positioning of the road roller, and conventional GPS equipment is not needed, so that the road roller is convenient to use in signal difference or no-signal areas for carrying out the full-compaction number analysis of asphalt pavement; and the laser point cloud model is utilized to obtain three-dimensional data of the rolling condition in the whole construction process, and the later display is also convenient.
Those of ordinary skill in the art will appreciate that implementing all or part of the steps in the above-described method embodiments may be accomplished by programming instructions in a computer readable storage medium, referred to herein as a storage medium, such as: ROM/RAM, magnetic disks, optical disks, etc.
While the embodiments of the present application have been described in detail, the detailed description of the application is provided herein, and the description of the embodiments is merely an example of some, but not all, of the methods and apparatus of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application, and the present description should not be construed as limiting the present application. It is therefore contemplated that any modifications, equivalents, improvements or modifications falling within the spirit and principles of the application will fall within the scope of the application.
Claims (6)
1. The utility model provides a bituminous paving compaction number dynamic monitoring method which is characterized in that the method includes:
the method comprises the steps that video images and three-dimensional laser point cloud data in a rolling working area are respectively collected in real time by using camera equipment and laser point cloud equipment which are arranged on a paver;
establishing a three-dimensional laser point cloud coordinate system with a dynamically changed coordinate origin, and recording the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system to obtain three-dimensional laser point cloud models at different moments;
performing machine vision identification and tracking on the video image, and determining the action range of each road roller at different moments;
respectively fusing and superposing the video image and the laser point cloud model image at the same moment to obtain data point coordinates in the action range of each road roller at different moments;
counting the times of occurrence of each coordinate point in the three-dimensional laser point cloud model in the working range of the road roller according to the data point coordinates in the working range of the road roller to obtain the compaction pass number of each coordinate point;
the establishing a three-dimensional laser point cloud coordinate system with a dynamically changed coordinate origin, and recording the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system, and obtaining three-dimensional laser point cloud models at different moments comprises:
establishing a three-dimensional laser point cloud coordinate system by taking the position of the laser point cloud equipment as a coordinate origin, and updating the coordinate origin according to the positions of the laser point cloud equipment at different moments;
determining coordinates of the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system according to displacement of the paver at different moments;
recording the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system according to the coordinates of the three-dimensional laser point cloud data to obtain three-dimensional laser point cloud models at different moments;
the method further comprises the steps of: pre-establishing an identification model;
the machine vision identification and tracking are carried out on the video image, and the determination of the action range of each road roller at different moments comprises the following steps:
identifying the video image by using the identification model, and tracking an identification object to obtain Mask information of each road roller at different moments;
and determining the action range of the road roller according to Mask information of the road roller at different moments.
2. The method according to claim 1, wherein the method further comprises:
and acquiring the motion parameters of the paver in real time, and determining the displacement of the paver at different moments and the positions of the laser point cloud equipment at different moments according to the motion parameters.
3. The method according to claim 1 or 2, wherein the image pickup apparatus is a pan-tilt camera with an anti-shake function.
4. An asphalt pavement compaction pass dynamic monitoring system, characterized in that the system comprises: the system comprises an image pickup device and a laser point cloud device which are arranged on a paver, and a data processing device which is respectively connected with the image pickup device and the laser point cloud device; the data processing apparatus includes: the system comprises a point cloud model building module, an image analysis module, a fusion processing module and a statistics module;
the camera equipment is used for acquiring video images in the rolling working area in real time and transmitting the acquired video images to the data processing equipment;
the laser point cloud device is used for collecting three-dimensional laser point cloud data in a rolling working area in real time and transmitting the collected three-dimensional laser point cloud data to the data processing device;
the point cloud model building module is used for building a three-dimensional laser point cloud coordinate system with a coordinate origin dynamically changed, and recording the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system to obtain three-dimensional laser point cloud models at different moments;
the image analysis module is used for carrying out machine vision identification and tracking on the video image to determine the action range of each road roller at different moments;
the fusion processing module is used for respectively carrying out fusion superposition on the video image and the laser point cloud model image at the same moment to obtain data point coordinates in the action range of each road roller at different moments;
the statistics module is used for counting the times of occurrence of each coordinate point in the three-dimensional laser point cloud model in the working range of the road roller according to the data point coordinates in the working range of the road roller to obtain the compaction pass number of each coordinate point;
the point cloud model building module comprises:
the coordinate system establishing unit is used for establishing a three-dimensional laser point cloud coordinate system by taking the position of the laser point cloud equipment as a coordinate origin, and updating the coordinate origin according to the positions of the laser point cloud equipment at different moments;
the point cloud data coordinate determining unit is used for determining coordinates of the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system according to displacement of the paver at different moments;
the model generation unit is used for recording the three-dimensional laser point cloud data in the three-dimensional laser point cloud coordinate system according to the coordinates of the three-dimensional laser point cloud data to obtain three-dimensional laser point cloud models at different moments;
the data processing apparatus further includes: the recognition model construction module is used for pre-building a recognition model;
the image analysis module comprises:
the image recognition unit is used for recognizing the video image by using the recognition model and tracking a recognition object to obtain Mask information of each road roller at different moments;
and the action range determining unit is used for determining the action range of the road roller according to Mask information of the road roller at different moments.
5. The system of claim 4, wherein the system further comprises: the vehicle-mounted equipment is arranged on the paver; the data processing apparatus further includes: a position determining module;
the vehicle-mounted equipment is used for acquiring the motion parameters of the paver in real time;
the position determining module is used for determining the displacement of the paver at different moments and the positions of the laser point cloud equipment at different moments according to the motion parameters.
6. The system according to claim 4 or 5, wherein the image capturing apparatus is a pan-tilt camera with an anti-shake function.
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