CN114908726A - Real-time global intelligent detection method and system for construction quality of highway broad-width roadbed - Google Patents
Real-time global intelligent detection method and system for construction quality of highway broad-width roadbed Download PDFInfo
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Abstract
The invention discloses a real-time global intelligent detection method and a system for construction quality of a highway broad subgrade, which comprises the steps of obtaining vibration wheel data, and calculating the vibration wheel data in real time through a compaction measurement model to obtain compaction data, wherein the vibration wheel data comprises acceleration data and vibration VCV data; acquiring the positioning information of the vibrating wheel, carrying out region judgment on the positioning information, counting and calculating compaction data according to the positioning information based on a judgment result to obtain compaction quality data and compaction uniformity data of different regions, and judging the compaction quality data and the compaction uniformity data to obtain construction quality. By the technical scheme, the method can effectively carry out real-time global intelligent detection on the construction quality of the highway broad subgrade.
Description
Technical Field
The invention relates to the technical field of roadbed construction quality detection, in particular to a real-time global intelligent detection method and system for the construction quality of a wide roadbed of an expressway.
Background
In the prior art, detection of roadbed compaction mostly depends on a detection method after construction, fixed-point test methods such as a sand pouring method and a cutting ring method are generally adopted, but detection needs to be carried out after construction is completed in the above technology, effective data in the construction process cannot be fully utilized, meanwhile, a detection method of fixed-point operation needs to be carried out at a certain position of construction environments in different areas and positions, the detection result is not representative, global detection cannot be effectively reflected, time is consumed in the detection process, and the real-time requirement cannot be met.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides the real-time global intelligent detection method and the system for the construction quality of the highway broad roadbed, which can effectively carry out real-time global intelligent detection on the construction quality of the highway broad roadbed.
On one hand, in order to realize the technical purpose, the invention provides a real-time global intelligent detection method for the construction quality of a wide roadbed of an expressway, which comprises the following steps:
acquiring measurement data, and calculating the measurement data in real time through a compaction measurement model to obtain compaction data, wherein the measurement data comprises acceleration data and vibration VCV data of a vibration wheel;
acquiring the positioning information of the vibrating wheel, carrying out region judgment on the positioning information, counting and calculating compaction data according to the positioning information based on a judgment result to obtain compaction quality data and compaction uniformity data of different regions, and judging the compaction quality data and the compaction uniformity data to obtain construction quality.
Optionally, the process of obtaining the compaction measurement model includes:
and constructing a deep learning model, inputting the measurement data as the variable of the deep learning model, outputting the compaction data as the variable of the deep learning model, and training the deep learning model to obtain the compaction measurement model.
Optionally, the process of determining the area of the positioning information includes:
acquiring a wide roadbed construction area image of the highway, performing grid division on the construction area image, mapping the positioning information and pixels in the construction area image, judging whether the vibration wheel detects the construction area or not based on the mapping result, and detecting the incomplete grid again if the detection is not completed.
Optionally, the process of performing statistical calculation on the compaction data includes:
and carrying out region division on the positioning information, corresponding the compaction data with the divided positioning information, counting the compaction data of the positioning information in different regions as compaction quality data, and calculating compaction uniformity data according to the compaction quality data.
Optionally, the process of determining the compaction quality data and the compaction uniformity data includes:
the quality grade and the uniformity grade are obtained by respectively carrying out grade judgment on the compaction quality data and the compaction uniformity data, and the construction quality is obtained by calculating the quality grade and the uniformity grade.
On the other hand, in order to achieve the technical purpose, the invention provides a real-time global intelligent detection system for construction quality of a highway broad-width roadbed, which comprises the following components:
the compaction data calculation module is used for acquiring measurement data, and calculating the measurement data in real time through the compaction measurement model to obtain compaction data, wherein the measurement data comprises acceleration data and vibration VCV data of the vibration wheel;
the construction quality detection module is used for acquiring positioning information of the vibrating wheel, performing region judgment on the positioning information, counting and calculating compaction data according to the positioning information based on a judgment result to obtain compaction quality data and compaction uniformity data of different regions, and judging the compaction quality data and the compaction uniformity data to obtain construction quality.
Optionally, the compaction data calculation module comprises a first calculation module;
the first calculation module is used for constructing a deep learning model, inputting the measurement data as variables of the deep learning model, outputting the compaction data as the variables of the deep learning model, and training the deep learning model to obtain the compaction measurement model.
Optionally, the construction quality detection module includes a first processing module;
the first processing module is used for obtaining an image of a wide roadbed construction area of the highway, performing grid division on the image of the construction area, mapping the positioning information and pixels in the image of the construction area, judging whether the vibration wheel detects the construction area or not based on the mapping result, and detecting the incomplete grid again if the detection is not completed.
Optionally, the construction quality detection module includes a second processing module;
the second processing module is used for carrying out region division on the positioning information, corresponding the compaction data with the divided positioning information, counting the compaction data of the positioning information of different regions as compaction quality data, and calculating compaction uniformity data according to the compaction quality data.
The construction quality detection module comprises a third processing module;
the third processing module is used for respectively carrying out grade judgment on the compaction quality data and the compaction uniformity data to obtain a quality grade and a uniformity grade, and calculating the quality grade and the uniformity grade to obtain the construction quality.
The invention has the following technical effects:
according to the technical scheme, effective real-time global detection can be carried out on construction quality by effectively using data in the construction process, partial areas can be effectively detected in the detection process, the detection is not needed according to the whole data after the detection is finished, areas with irrelevant construction quality can be quickly selected, the construction speed is accelerated, and the real-time performance and the intelligence of construction quality detection are improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a schematic flow chart of a method provided by an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a system according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
As shown in fig. 1, the invention provides a real-time global intelligent detection method for construction quality of a highway broad subgrade, which specifically comprises the following steps:
the vibration wheel of the vibratory roller is provided with the related sensor, so that the acceleration data and the vibration VCV data of the vibration wheel are automatically acquired in real time, and the related equipment information of the vibratory roller, such as the length, the width, the weight and the like of the vibration wheel, is recorded.
Constructing a compaction measurement model, calculating compaction degree through the compaction measurement model, adopting a deep learning model structure for the compaction measurement model, using vibration wheel data as fixed input of the deep learning model in the model, using the measurement data as variable input of the deep learning model, using the compaction data as variable output of the deep learning model, learning and simulating a correlation relation between input data and output data through the deep learning model structure, and calculating the compaction degree by using the correlation relation, specifically, selecting a convolutional neural network structure, adopting three convolutional-pooling layers which are connected in sequence and two full-connection layers in the convolutional neural network structure, learning the inherent correlation relation by performing convolutional pooling operation on the data for multiple times, training and learning the convolutional neural network before use, and collecting the measurement data in the construction process by training sample data, the compactness of the vibration wheel is directly measured according to a circular cutting method or a sand filling method, the model is trained through the data to generate a compaction measurement model, meanwhile, the compaction measurement model can also set relevant data of the vibration wheel as model input to learn the relevance of the vibration wheel besides inputting the measurement data, so that the error of the vibration wheel is reduced, the vibration wheel data used in the learning process when the vibration wheel data are used is the same as the vibration wheel data used in the measurement process, and the generated error is reduced.
Whether all areas are traversed is judged according to the positioning information, the vibration wheel is specifically positioned through a GPS or other positioning modes, the working state of the vibration wheel is considered, the positioning device cannot be directly installed on the vibration wheel, the positioning device needs to be installed on a cab, and the real positioning information of the vibration wheel is obtained through calculation according to the position relation between the positioning device and the center of the vibration wheel. Then obtaining a geographical image of a wide roadbed construction area in the highway, carrying out area division on the geographical image, mapping positioning information into the geographical image, specifically, corresponding the positioning information to pixels in the geographical image, expressing the positioning information by the pixels in the geographical image, extracting corresponding pixels after the positioning information corresponds to the pixels in the construction area image, wherein the corresponding pixels only can represent simple point positions and cannot represent area areas driven by the width of the vibration wheel, so that adjacent pixels of the corresponding pixels are required in the extraction, extracting the two pixels, judging the two pixels after the extraction, if the number of the extracted pixels is less than 95% of the total number of the pixels in the area image, considering that some area contents are detected, extracting the pixels, and converting a real proportion according to the pixel positions corresponding to the positioning information, and according to the position relation between the unselected pixel points and the selected pixel points, real position information is obtained through conversion, and the missing region is subjected to recompaction detection through the position information, so that the detection of the universe can be ensured.
After global detection, calculating compaction indexes including compaction quality data and compaction uniformity data, specifically, corresponding positioning information to the compaction data, integrating data at the same time, calculating an average value of the compaction data as corresponding compaction data under the same positioning information, then performing region division according to the positioning information, dividing the region division according to the geographical diagram, counting the compaction data under different regions, dividing the compaction data under different regions into different sets or constructing a positioning information-compaction data curve graph, performing statistics on the whole compaction data into the compaction quality data of different regions according to the divided positioning information, and calculating the compaction uniformity data of the compaction quality data according to the area of the regions, the compaction uniformity data is a variance value of the compaction quality data in the region, thereby representing the compaction uniformity in the region.
Judging the compaction index, wherein the judgment levels of the compaction quality data and the compaction uniformity data in the compaction index can be set through related standards, if the judgment levels exceed the related standard values, the construction quality is considered to be met, the recorded value is 3, if the judgment levels exceed the related standard values by 95%, the construction quality is considered to be qualified, the recorded value is 2, if the judgment levels are lower than the related standard values by 95%, the construction quality is considered to be unqualified, the recorded value is 1, after the judgment of the levels is completed, the values of the levels of the compaction quality data and the compaction uniformity data are obtained, the weights of the compaction quality data and the compaction uniformity data are respectively set to be 0.7 and 0.3, the construction quality values are obtained through calculation, when the construction quality values are more than 2, the construction is considered to be good, when the construction quality values are more than 1.5, the construction is considered to be qualified, and when the construction quality values are less than 1.5, the construction plan needs to be reset.
Example two
As shown in fig. 2, the invention provides a real-time global intelligent detection system for construction quality of a highway broad subgrade, which comprises:
the compaction data calculation module is used for acquiring measurement data, and calculating the measurement data in real time through the compaction measurement model to obtain compaction data, wherein the measurement data comprises acceleration data and vibration VCV data of the vibration wheel;
the construction quality detection module is used for obtaining the positioning information of the vibrating wheel, carrying out region judgment on the positioning information, carrying out statistics and calculation on compaction data according to the positioning information based on a judgment result to obtain compaction quality data and compaction uniformity data of different regions, and judging the compaction quality data and the compaction uniformity data to obtain construction quality, and the system corresponds to the content of the method and is not repeated.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (10)
1. The real-time global intelligent detection method for the construction quality of the highway broad subgrade is characterized by comprising the following steps:
acquiring measurement data, and calculating the measurement data in real time through a compaction measurement model to obtain compaction data, wherein the measurement data comprises acceleration data and vibration VCV data of a vibration wheel;
acquiring the positioning information of the vibrating wheel, carrying out region judgment on the positioning information, counting and calculating compaction data according to the positioning information based on a judgment result to obtain compaction quality data and compaction uniformity data of different regions, and judging the compaction quality data and the compaction uniformity data to obtain construction quality.
2. The method of claim 1, further comprising:
the process of obtaining a compaction measurement model includes:
and constructing a deep learning model, inputting the measurement data as variables of the deep learning model, outputting the compaction data as the variables of the deep learning model, and training the deep learning model to obtain the compaction measurement model.
3. The method of claim 1, wherein:
the process of judging the area of the positioning information comprises the following steps:
acquiring a wide roadbed construction area image of the highway, performing grid division on the construction area image, mapping the positioning information and pixels in the construction area image, judging whether the vibration wheel detects the construction area or not based on the mapping result, and detecting the incomplete grid again if the detection is not completed.
4. The method of claim 1, further comprising:
the process of statistically calculating compaction data includes:
and carrying out region division on the positioning information, corresponding the compaction data with the divided positioning information, counting the compaction data of the positioning information in different regions as compaction quality data, and calculating compaction uniformity data according to the compaction quality data.
5. The method of claim 1, further comprising:
the process of judging the compaction quality data and the compaction uniformity data comprises the following steps:
the quality grade and the uniformity grade are obtained by respectively carrying out grade judgment on the compaction quality data and the compaction uniformity data, and the construction quality is obtained by calculating the quality grade and the uniformity grade.
6. The detection system of the real-time global intelligent detection method for the construction quality of the highway broad subgrade according to any one of claims 1 to 5 is characterized by comprising the following steps:
the compaction data calculation module is used for acquiring measurement data, and calculating the measurement data in real time through the compaction measurement model to obtain compaction data, wherein the measurement data comprises acceleration data and vibration VCV data of the vibration wheel;
the construction quality detection module is used for acquiring positioning information of the vibrating wheel, performing region judgment on the positioning information, counting and calculating compaction data according to the positioning information based on a judgment result to obtain compaction quality data and compaction uniformity data of different regions, and judging the compaction quality data and the compaction uniformity data to obtain construction quality.
7. The system of claim 6, wherein:
the compaction data calculation module comprises a first calculation module;
the first calculation module is used for constructing a deep learning model, inputting the measurement data as variables of the deep learning model, outputting the compaction data as the variables of the deep learning model, and training the deep learning model to obtain the compaction measurement model.
8. The system of claim 6, wherein:
the construction quality detection module comprises a first processing module;
the first processing module is used for acquiring an image of a wide roadbed construction area of the highway, performing grid division on the image of the construction area, mapping the positioning information and pixels in the image of the construction area, judging whether the vibration wheel detects the construction area or not based on the mapping result, and detecting the incomplete grid again if the detection is not completed.
9. The system of claim 6, wherein:
the construction quality detection module comprises a second processing module;
the second processing module is used for carrying out region division on the positioning information, corresponding the compaction data with the divided positioning information, counting the compaction data of the positioning information of different regions as compaction quality data, and calculating compaction uniformity data according to the compaction quality data.
10. The system of claim 6, wherein:
the construction quality detection module comprises a third processing module;
the third processing module is used for respectively carrying out grade judgment on the compaction quality data and the compaction uniformity data to obtain a quality grade and a uniformity grade, and calculating the quality grade and the uniformity grade to obtain the construction quality.
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