CN111783686A - Asphalt pavement health state monitoring system and method - Google Patents
Asphalt pavement health state monitoring system and method Download PDFInfo
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Abstract
The invention discloses a system and a method for monitoring the health state of an asphalt pavement, wherein the method comprises the following steps: collecting satellite-borne high-resolution remote sensing image data of asphalt roads in a monitoring area and existing pavement state investigation information; preprocessing the collected satellite-borne high-resolution remote sensing data, and extracting a road area image by using an object-oriented technology and a decision tree threshold method; extracting spectral characteristics, textural characteristics and morphological characteristics of the asphalt pavement in different aging stages and different diseased pavements in the high-resolution remote sensing image, and constructing sensitive characteristics or characteristic combinations of the aged and diseased pavements through characteristic analysis; and constructing an asphalt pavement health state evaluation model based on the sensitive characteristics or the characteristic combination and a BP neural network method. According to the invention, the satellite-borne high-resolution remote sensing image data is utilized, the remote sensing image processing and image recognition technology is combined, the health state of the asphalt pavement is researched, the health state information of the asphalt pavement in a large range can be rapidly provided for a highway maintenance department, the problems that the traditional pavement monitoring method is long in detection period and high in cost, and the condition information of the pavement in the large range cannot be rapidly acquired are solved, and meanwhile, a basis is provided for the highway maintenance department to make a maintenance plan.
Description
Technical Field
The invention relates to the technical field of highway pavement maintenance management, in particular to a system and a method for monitoring the health state of an asphalt pavement.
Background
The highway is used as a link for transportation, plays a considerable role in national development and economic construction, and is displayed according to reports, so that the road traffic mileage is rapidly increased. The high-grade roads (expressways and first-grade roads) in China are mostly constructed by adopting asphalt concrete, the traffic volume and the load of asphalt road surfaces are continuously increased, and due to the influence of natural environment, the road surface structure is always damaged and is increasingly serious along with the time lapse, so that the service capacity and the operation benefit of the roads are directly influenced, and huge economic loss and accident risk are caused.
The traditional road surface monitoring method needs a large-scale vehicle-mounted platform, influences traffic, has long detection period and high cost, can only carry out sampling investigation on a road section with a longer route, and cannot quickly acquire large-scale road surface condition information. The remote sensing image enables large-scale pavement monitoring to be possible due to the improvement of space and spectral resolution, and the remote sensing technology can quickly and quantitatively acquire the pavement information of a large-area highway, realize the real-time monitoring of the pavement condition and is suitable for monitoring and evaluating the condition of the pavement of the highway.
Therefore, in order to facilitate the highway maintenance department to timely master the information of the road surface condition in a large range, corresponding maintenance measures are taken, and the development of the road surface condition monitoring and evaluation research based on the remote sensing technology has important scientific significance.
Disclosure of Invention
In order to solve the problems in the related art, the embodiment of the invention provides a system and a method for monitoring the health state of an asphalt pavement, which solve the problems that the traditional vehicle-mounted monitoring period of the asphalt pavement is long, the cost is high, and the condition information of the pavement in a large range cannot be quickly acquired.
The embodiment of the invention provides a method for monitoring the health state of an asphalt pavement, which comprises the following steps:
collecting satellite-borne high-resolution remote sensing image data of asphalt roads in a monitoring area and existing pavement state investigation information;
preprocessing the collected satellite-borne high-resolution remote sensing data, and extracting a road area image by using an object-oriented technology and a decision tree threshold method;
constructing sensitive characteristic wave bands or characteristic combinations of the aged and damaged pavements, and determining characteristics related to pavement aging and damage through characteristic analysis;
establishing a road surface health state evaluation model based on high-resolution remote sensing data by combining the selected sensitive characteristics or characteristic combinations with a W neural network algorithm;
and evaluating the asphalt road surface through a road surface health state evaluation model based on high-grade remote sensing data to generate a road surface health state diagram.
Further, the satellite-borne high-resolution remote sensing image data comprises a Worldview-3 high-resolution data set of the road surface area.
Further, the road surface condition survey information includes high-precision vehicle-mounted road surface condition index (PCl) data and manually-surveyed PCl data.
Further, the preprocessing of the satellite-borne high-resolution remote sensing data comprises the steps of remote sensing image orthorectification, radiometric calibration, atmospheric correction, image fusion, image splicing and cutting processing.
Further, the extracting the road area image comprises performing image segmentation on the preprocessed high-resolution image based on spectrum, texture and morphological characteristics by using an object-oriented segmentation method.
Further, the method for constructing the sensitive characteristic wave bands or characteristic combinations of the road surface aging and the diseases comprises the following steps,
spectral characteristics: original spectrum, ratio, difference and other characteristics;
texture characteristics: gray level co-occurrence matrix GLCM textures and local binary pattern LBP textures of different windows;
morphological characteristics: expansion, corrosion, opening operation and closing operation.
A suitable feature or combination of features is then selected by correlation analysis between the features and the sample PCl.
An asphalt pavement health state monitoring system comprises a collection module, a transmission module, a data preprocessing module, a pavement area extraction module, a pavement characteristic extraction module and a pavement state evaluation model module, wherein the collection module is connected with the data preprocessing module, the data preprocessing module is connected with the pavement area extraction module, the pavement area extraction module is connected with the pavement characteristic extraction module, the pavement area extraction module is connected with the pavement state evaluation model module through the transmission module, the asphalt pavement health state monitoring system comprises a data acquisition module, a transmission module, a data preprocessing module, a pavement area extraction module, a pavement characteristic extraction module and a pavement state evaluation model,
the data preprocessing module is used for performing radiation correction, orthorectification, atmospheric correction, image fusion and image splicing and cutting operations on the collected high-resolution remote sensing images of the highway domains;
the road surface area extraction module is used for extracting the image of the road area from the preprocessed high-resolution fusion image by an object-oriented segmentation method and a decision tree threshold method;
the road surface feature extraction module is used for extracting typical spectrum, texture and morphological features of the fused image road surface area;
and the road surface state evaluation model module is used for constructing a road surface state evaluation model through the W neural network according to the acquired road surface area characteristics.
Further, the road surface state evaluation model module also comprises a road surface state evaluation unit and a maintenance decision support unit;
the road surface state evaluation unit is used for carrying out state evaluation on a road area so as to obtain the road surface state condition and provide information support for road surface maintenance according to the road surface state grade of the road area;
and the maintenance decision support unit is used for providing support for the road maintenance decision according to the road surface state evaluation result and the maintenance condition.
The technical scheme provided by the embodiment of the invention has the following beneficial effects: the satellite-borne high-resolution remote sensing image data is combined with remote sensing image processing and image recognition technologies to research the health state of the asphalt pavement, so that the method can quickly provide large-range asphalt pavement health state information for a highway maintenance department, solve the problems that the traditional pavement monitoring method is long in detection period and high in cost, and cannot quickly acquire large-range pavement condition information, and provide a basis for the highway maintenance department to make a maintenance plan.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
FIG. 1 is a flow chart of a method for monitoring the state of health of an asphalt pavement according to an embodiment of the present invention.
Fig. 2 is a road surface condition evaluation grade chart of the asphalt road surface health condition monitoring method in the embodiment of the invention.
Fig. 3 is a schematic structural diagram of a system for monitoring the state of health of an asphalt pavement according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus, and associated applications, methods consistent with certain aspects of the invention, as detailed in the following claims.
Fig. 1 is a flowchart of a method for monitoring a state of health of an asphalt pavement according to an embodiment of the present invention, and fig. 2 is a road surface condition evaluation level chart of the method for monitoring a state of health of an asphalt pavement according to an embodiment of the present invention, as shown in fig. 1 and 2, the method for monitoring a state of health of an asphalt pavement includes the steps of:
The satellite-borne high-resolution remote sensing image data comprises a Worldview-3 high-resolution data set of a road surface area.
The road surface condition survey information includes high-precision vehicle-mounted PCl data and manually surveyed PCl data.
And 102, preprocessing the collected satellite-borne high-resolution remote sensing data, and extracting a road area image by using an object-oriented technology and a decision tree threshold method.
The method comprises the steps of performing orthorectification, radiometric calibration and atmospheric correction on a multiband image, fusing the multispectral band with a panchromatic image to generate a high-resolution fused image, and splicing and cutting to obtain a fused image taking a road as a center.
Preprocessing the satellite-borne high-resolution remote sensing data comprises the steps of ortho-correction, radiometric calibration, atmospheric correction, image fusion, image splicing and cutting of remote sensing images.
The method for extracting the road area image comprises the steps of utilizing an object-oriented segmentation method, carrying out image segmentation on a preprocessed high-resolution image based on spectrum, texture and morphological characteristics, determining the optimal segmentation scale through continuous tests, and then adopting a decision tree threshold method to extract the road area of the image.
103, constructing sensitive characteristic wave bands or characteristic combinations of the aged and damaged pavements, and determining characteristics related to pavement aging and damage through characteristic analysis.
Constructing sensitive characteristic wave bands or characteristic combinations of the pavement aging and the diseases comprises,
spectral characteristics: original spectrum, ratio, difference and other characteristics;
texture characteristics: gray level co-occurrence matrix GLCM textures and local binary pattern LBP textures of different windows;
morphological characteristics: expansion, corrosion, opening operation and closing operation.
A suitable feature or combination of features is then selected by correlation analysis between the features and the sample PCl.
And step 104, establishing a road surface health state evaluation model based on high-grade remote sensing data by combining the selected sensitive characteristics or characteristic combinations with a BP neural network algorithm.
And 105, evaluating the asphalt road surface through a road surface health state evaluation model based on high-score remote sensing data to generate a road surface health state diagram.
The road surface health state evaluation model of the high-resolution remote sensing data is a 4-layer network structure and comprises an input layer, a hidden layer, an output layer and a Softmax layer: the method comprises the steps that sensitive features are input into an input layer, weights are randomly generated, 1 hidden layer is set, a Sigmoid function is used as an activation function, 5 road surface state levels are established in an output layer (as shown in figure 2), finally, an output result of the output layer is transmitted into a Softmax layer, output vectors are normalized, the probability of the class to which a sample belongs is increased, the probability of the class to which the sample belongs is restrained, road surface state training sample data is used as an output true value, the weights are updated through a back propagation algorithm and a gradient descent algorithm, the update weights of a whole network model are obtained, and finally a road surface state evaluation model is formed.
The road surface state condition of the monitored area is obtained based on the road surface state evaluation model, information can be timely provided for a road management department, the road management department is helped to master the state of the road surface in a large range, targeted investigation and maintenance are facilitated, and a large amount of manpower and material resources can be saved.
Fig. 3 is a schematic structural diagram of an asphalt pavement health status monitoring system in an embodiment of the present invention, and as shown in fig. 3, the asphalt pavement health status monitoring system includes a collection module 1, a transmission module 2, a data preprocessing module 3, a pavement area extraction module 4, a pavement feature extraction module 5, and a pavement status evaluation model 6, the collection module is connected to the data preprocessing module, the data preprocessing module is connected to the pavement area extraction module, the pavement area extraction module is connected to the pavement feature extraction module, the pavement area extraction module is connected to the pavement status evaluation model module through the transmission module, wherein,
the data preprocessing module is used for carrying out radiation correction, orthorectification, atmospheric correction, image fusion and image splicing and cutting operations on the collected high-resolution remote sensing images of the highway domains.
The road surface area extraction module is used for extracting the image of the road area from the preprocessed high-resolution fusion image by an object-oriented segmentation method and a decision tree threshold method.
The road surface feature extraction module is used for extracting typical spectrum, texture and morphological features of the fused image road surface area.
And the road surface state evaluation model module is used for constructing a road surface state evaluation model through the W neural network according to the acquired road surface area characteristics.
The road surface state evaluation model module further comprises a road surface state evaluation unit and a maintenance decision support unit.
The road surface state evaluation unit is used for carrying out state evaluation on the road area so as to obtain the road surface state condition, and information support is provided for road surface maintenance according to the road surface state grade of the road area.
And the maintenance decision support unit is used for providing support for the road maintenance decision according to the road surface state evaluation result and the maintenance condition.
By adopting the embodiment of the invention, the satellite-borne high-resolution remote sensing image data is utilized, the remote sensing image processing and the image recognition technology are combined, the health state of the asphalt pavement is researched, the health state information of the asphalt pavement in a large range can be quickly provided for a highway maintenance department, the problems that the traditional pavement monitoring method is long in detection period and high in cost, and the condition information of the pavement in the large range cannot be quickly acquired are solved, and meanwhile, a basis is provided for the highway maintenance department to make a maintenance plan.
Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains.
It will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
Claims (8)
1. The method for monitoring the health state of the asphalt pavement is characterized by comprising the following steps of:
collecting satellite-borne high-resolution remote sensing image data of asphalt roads in a monitoring area and existing pavement state investigation information;
preprocessing the collected satellite-borne high-resolution remote sensing data, and extracting a road area image by using an object-oriented technology and a decision tree threshold method;
constructing sensitive characteristic wave bands or characteristic combinations of the aged and damaged pavements, and determining characteristics related to pavement aging and damage through characteristic analysis;
establishing a road surface health state evaluation model based on high-resolution remote sensing data by combining the selected sensitive characteristics or characteristic combinations with a W neural network algorithm;
and evaluating the asphalt road surface through a road surface health state evaluation model based on high-grade remote sensing data to generate a road surface health state diagram.
2. The method for monitoring the state of health of the asphalt pavement according to claim 1, wherein the satellite-borne high-resolution remote sensing image data comprises a Worldview-3 high-resolution data set of a pavement area.
3. The asphalt pavement health monitoring method according to claim 1, wherein the pavement condition survey information includes high-precision vehicle pavement condition index (W /) data and manually surveyed W/data.
4. The system and the method for monitoring the health state of the asphalt pavement according to claim 1, wherein the preprocessing of the satellite-borne high-resolution remote sensing data comprises ortho-correction, radiometric calibration, atmospheric correction, image fusion, image splicing and cutting processing of remote sensing images.
5. The asphalt pavement health monitoring method according to claim 1, wherein the extracting the road region image comprises image segmentation of the preprocessed high-resolution image based on spectral, texture, and morphological features using an object-oriented segmentation method.
6. The method for monitoring the state of health of an asphalt pavement according to claim 1, wherein the constructing of the characteristic band or characteristic combination sensitive to the aging and the disease of the pavement comprises,
spectral characteristics: original spectrum, ratio, difference and other characteristics;
texture characteristics: different window gray level co-occurrence matrix' > D texture and local binary pattern > W texture
C, processing; morphological characteristics: expansion, corrosion, opening operation and closing operation;
an appropriate feature or combination of features is then selected by correlation analysis between the features and the sample W/.
7. An asphalt pavement health state monitoring system is characterized by comprising a collection module, a transmission module, a data preprocessing module, a pavement area extraction module, a pavement characteristic extraction module and a pavement state evaluation model module, wherein the collection module is connected with the data preprocessing module, the data preprocessing module is connected with the pavement area extraction module, the pavement area extraction module is connected with the pavement characteristic extraction module, the pavement area extraction module is connected with the pavement state evaluation model module through the transmission module, the transmission module is used for transmitting the data to the data preprocessing module,
the data preprocessing module is used for performing radiation correction, orthorectification, atmospheric correction, image fusion and image splicing and cutting operations on the collected high-resolution remote sensing images of the highway domains;
the road surface area extraction module is used for extracting the image of the road area from the preprocessed high-resolution fusion image by an object-oriented segmentation method and a decision tree threshold method;
the road surface feature extraction module is used for extracting typical spectrum, texture and morphological features of the fused image road surface area;
and the road surface state evaluation model module is used for constructing a road surface state evaluation model through the W neural network according to the acquired road surface area characteristics.
8. The asphalt pavement health status monitoring system according to claim 7, wherein the pavement status evaluation model module further comprises a pavement status evaluation unit and a maintenance decision support unit;
the road surface state evaluation unit is used for carrying out state evaluation on a road area so as to obtain the road surface state condition and provide information support for road surface maintenance according to the road surface state grade of the road area;
and the maintenance decision support unit is used for providing support for the road maintenance decision according to the road surface state evaluation result and the maintenance condition.
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| CN114821333A (en) * | 2022-05-16 | 2022-07-29 | 中国人民解放军61540部队 | High-resolution remote sensing image road material identification method and device |
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| CN114775382A (en) * | 2022-06-21 | 2022-07-22 | 源利腾达(西安)科技有限公司 | Ultrasonic-based road surface quality detection method for highway traffic engineering |
| CN117370897A (en) * | 2023-12-04 | 2024-01-09 | 四川正路建设工程检测咨询有限公司 | Road health state detection method, electronic device and computer readable medium |
| CN117370897B (en) * | 2023-12-04 | 2024-02-09 | 四川正路建设工程检测咨询有限公司 | Road health state detection method, electronic device and computer readable medium |
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