CN117387500A - Method and system for detecting thickness of each layer of asphalt concrete pavement core drilling sample - Google Patents
Method and system for detecting thickness of each layer of asphalt concrete pavement core drilling sample Download PDFInfo
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- 238000005553 drilling Methods 0.000 title claims abstract description 140
- 239000011384 asphalt concrete Substances 0.000 title claims abstract description 55
- 238000000034 method Methods 0.000 title claims abstract description 34
- 238000001514 detection method Methods 0.000 claims abstract description 35
- 238000003708 edge detection Methods 0.000 claims abstract description 31
- 238000012545 processing Methods 0.000 claims abstract description 28
- 238000006243 chemical reaction Methods 0.000 claims abstract description 15
- 238000009683 ultrasonic thickness measurement Methods 0.000 claims abstract description 8
- 239000000523 sample Substances 0.000 claims description 178
- 238000001914 filtration Methods 0.000 claims description 12
- 238000000605 extraction Methods 0.000 claims description 9
- 238000004458 analytical method Methods 0.000 claims description 8
- 238000004422 calculation algorithm Methods 0.000 claims description 8
- 230000003993 interaction Effects 0.000 claims description 8
- 238000007654 immersion Methods 0.000 claims description 7
- 239000000463 material Substances 0.000 claims description 4
- 238000012935 Averaging Methods 0.000 claims description 3
- 230000005540 biological transmission Effects 0.000 claims description 3
- 239000004575 stone Substances 0.000 claims description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims 1
- 239000010426 asphalt Substances 0.000 abstract description 3
- 239000010410 layer Substances 0.000 description 84
- 238000004364 calculation method Methods 0.000 description 4
- 201000010099 disease Diseases 0.000 description 4
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 4
- 238000012423 maintenance Methods 0.000 description 4
- 238000013461 design Methods 0.000 description 3
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- 238000004590 computer program Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000002791 soaking Methods 0.000 description 2
- 239000002344 surface layer Substances 0.000 description 2
- 230000002238 attenuated effect Effects 0.000 description 1
- 239000002131 composite material Substances 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 239000011229 interlayer Substances 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000003801 milling Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
- G01B11/06—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B17/00—Measuring arrangements characterised by the use of infrasonic, sonic or ultrasonic vibrations
- G01B17/02—Measuring arrangements characterised by the use of infrasonic, sonic or ultrasonic vibrations for measuring thickness
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
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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
- G06T2207/30108—Industrial image inspection
- G06T2207/30132—Masonry; Concrete
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A30/00—Adapting or protecting infrastructure or their operation
- Y02A30/60—Planning or developing urban green infrastructure
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- Computer Vision & Pattern Recognition (AREA)
- Theoretical Computer Science (AREA)
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- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention discloses a method and a system for detecting the thickness of each layer of a core drilling sample of an asphalt concrete pavement, wherein the method comprises the following steps: acquiring a surface image of a core drilling sample of an asphalt concrete pavement to be tested; performing gray level conversion on the surface image of the core drilling sample to obtain gray level distribution information of the surface of the core drilling sample; performing edge detection based on the gray level distribution information of the surface of the core drilling sample to obtain an edge boundary line between each structural layer in the core drilling sample; processing the distribution information of each structural layer based on the boundary line between the structural layers to obtain the proportion of the thickness of each structural layer to the total thickness; performing ultrasonic thickness measurement on the core drilling sample to obtain the actual overall thickness of the core drilling sample; and determining the actual thickness of each structural layer according to the actual overall thickness of the drill core sample and the proportion of the thickness of each structural layer to the total thickness. The invention can realize the detection of different structure layer thicknesses of the core sample of the asphalt pavement, improve the detection accuracy and reduce the human error.
Description
Technical Field
The invention relates to the technical field of detection of asphalt concrete pavement drill core samples, in particular to a method and a system for detecting the thickness of each layer of an asphalt concrete pavement drill core sample.
Background
The asphalt concrete pavement drill core belongs to a part of special road detection in pavement maintenance design, and is obtained by drilling an asphalt concrete pavement by using a special pavement coring machine.
With the continuous increase of the road operation time, the service performance of the asphalt concrete pavement is continuously attenuated under the composite influence of traffic and environmental factors, and the evaluation of the apparent diseases of the pavement is insufficient to define the service performance of the asphalt concrete pavement under the long-term service effect. The cause and development trend of pavement diseases need to be investigated during pavement maintenance design, and deep diseases hidden below the surface layer of the pavement need to be analyzed through a certain detection means, and the integrity of each structural layer of the pavement and the form of disease development can be analyzed through coring of the asphalt concrete pavement, so that accurate information is provided for maintenance designers to make maintenance decisions.
The traditional method for judging the layer thickness of each layer of the asphalt concrete core drilling sample by naked eyes is low in efficiency, is greatly influenced by subjective assumption of observers, is quite easy to generate errors, is quite inconvenient for the observers to record on site, and is not easy to store paper-based recording materials. Meanwhile, the detection process of the layer thicknesses of the core sample layers of the traditional asphalt concrete pavement has the following problems to influence judgment: (1) the interlayer which is not completely paved due to the previous milling and planing is not easy to judge; (2) the boundary between layers of the drill core sample of the damaged road sections such as ruts is not obvious, and the boundary line of the edge is difficult to judge; (3) without knowledge of the curing history, the number of surface layer structures cannot be determined.
Disclosure of Invention
The invention aims to provide a method and a system for detecting the thickness of each layer of an asphalt concrete pavement drill core sample, so as to realize detection of the thicknesses of different structural layers of the asphalt concrete pavement drill core sample and improve detection accuracy.
In order to achieve the above object, the present invention provides the following solutions:
the method for detecting the thickness of each layer of the asphalt concrete pavement drill core sample comprises the following steps:
s1, acquiring a surface image of a core drilling sample of an asphalt concrete pavement to be tested, wherein the surface image of the core drilling sample is a complete image of the core drilling sample of the asphalt concrete pavement to be tested, which is taken out by a pavement core drilling machine;
s2, carrying out gray level conversion on the surface image of the core drilling sample to obtain gray level distribution information of the surface of the core drilling sample;
s3, carrying out edge detection based on the gray level distribution information of the surface of the core drilling sample to obtain an edge boundary line between each structural layer in the core drilling sample;
s4, processing the distribution information of each structural layer based on the boundary line between the structural layers to obtain the proportion of the thickness of each structural layer to the total thickness;
s5, performing ultrasonic thickness measurement on the core drilling sample to obtain the actual overall thickness of the core drilling sample;
s6, determining the actual thickness of each structural layer according to the actual overall thickness of the drill core sample and the proportion of the thickness of each structural layer to the total thickness.
Further, in the step S1, a surface image of a core drilling sample of the asphalt concrete pavement to be measured is obtained, which specifically includes:
taking out a core drilling sample of the asphalt concrete pavement to be tested through a pavement core drilling machine;
transversely placing a core drilling sample on a horizontal road surface, and acquiring a two-dimensional digital image of the core drilling sample by adopting a mobile image acquisition terminal device; the acquisition parameters of the mobile image acquisition terminal equipment are as follows: the lens shooting angle is parallel to the road surface, the acquisition mode is 1 times focusing mode, the surface image should contain the complete core drilling sample, and the core drilling sample is placed in the center of the image.
Further, in the step S2, gray level conversion is performed on the surface image of the drill core sample to obtain gray level distribution information of the surface of the drill core sample, which specifically includes:
the surface image of the drill core sample adopts an RGB color mode to form a corresponding color image;
and (3) averaging the three-component brightness in the color image by adopting an average value method to obtain the gray value of the image pixel, and obtaining the gray distribution information of the surface of the drilling core sample.
Further, in the step S3, edge detection is performed based on the gray scale distribution information of the surface of the core drilling sample, so as to obtain an edge boundary between each structural layer in the core drilling sample, which specifically includes:
based on the gray level distribution information of the surface of the core drilling sample, gaussian filtering is adopted to filter the surface image of the core drilling sample, so that the signal-to-noise ratio of the image is improved;
and (3) carrying out edge detection on the filtered image by adopting an improved sobel operator, extracting an image contour, filtering out finely divided edges generated by the detected broken stone contour, and obtaining edge boundaries generated by different structural layers.
Further, in the step S4, based on the boundary between the structural layers, the distribution information of each structural layer is processed to obtain the ratio of the thickness of each structural layer to the total thickness, which specifically includes:
obtaining the relative thickness of each structural layer in the surface image of the core drilling sample according to the boundary line between each structural layer;
and calculating the ratio of the thickness of each structural layer in the surface image of the core drilling sample to the total thickness based on the relative thickness of each structural layer, wherein the total thickness is the on-graph thickness of the core drilling sample in the surface image of the core drilling sample.
The invention also provides a system for detecting the thickness of each layer of the asphalt concrete pavement core drilling sample, which is applied to the method for detecting the thickness of each layer of the asphalt concrete pavement core drilling sample, and comprises the following steps:
the mobile image acquisition terminal equipment comprises a camera and an image transmission module, and is used for acquiring a surface image of a core drilling sample of the asphalt concrete pavement to be detected, wherein the surface image of the core drilling sample is a complete image of the core drilling sample of the asphalt concrete pavement to be detected, which is taken out by a pavement core drilling machine;
the gray processing module is used for carrying out gray conversion on the surface image of the core drilling sample to obtain gray distribution information of the surface of the core drilling sample;
the edge detection module is used for carrying out edge detection based on the gray level distribution information of the surface of the core drilling sample to obtain an edge boundary line between each structural layer in the core drilling sample;
the data processing module is used for processing the distribution information of each structural layer based on the boundary line between the structural layers to obtain the proportion of the thickness of each structural layer to the total thickness;
the ultrasonic detection module is used for carrying out ultrasonic thickness measurement on the core drilling sample to obtain the actual overall thickness of the core drilling sample;
the data processing module is also used for determining the actual thickness of each structural layer according to the actual overall thickness of the drill core sample and the proportion of the thickness of each structural layer to the total thickness.
Further, the edge detection module comprises a boundary analysis sub-module, an edge extraction sub-module, a layer demarcation sub-module, a soaking filling fitting sub-module and a contour detection sub-module, wherein:
the boundary analysis submodule is used for judging the boundary contour of the surface image of the core drilling sample and filtering out the image boundary;
the edge extraction submodule is used for carrying out edge detection by utilizing an edge extraction four-edge detection algorithm and judging whether four straight lines of the edge are detected or not;
the layer demarcation submodule is used for judging demarcations detected by layers of different structural layers in the image due to material grading;
the immersion filling fitting sub-module is used for carrying out four-side straight line forced fitting by utilizing an immersion filling four-side detection algorithm and determining four intersection points of the four-side straight lines;
the contour detection submodule is used for carrying out contour detection on the surface image of the drill core sample and extracting Gaussian noise image edges.
Further, the ultrasonic detection module comprises a probe, a transmitting module, a receiving module, a main control module, a signal amplifying module, an analog-to-digital conversion module, a waveform generation module, a gate generation module, a man-machine interaction module and a signal processing module, wherein:
the transmitting module and the receiving module are used for transmitting ultrasonic waves to the drill core sample and receiving reflected ultrasonic information;
the signal amplifying module is used for filtering the received ultrasonic information and amplifying the obtained electric signal;
the main control module is used for controlling the emission and the reception of ultrasonic waves;
the analog-to-digital conversion module is used for converting the amplified electric signals into ultrasonic waveforms;
the waveform generation module is used for generating an electric signal received by the reflected wave receiver;
the signal processing module is used for comparing ultrasonic waveforms with different intensities and identifying the time difference of ultrasonic waves reflected from different edges.
Further, the system also comprises a man-machine interaction module for storing the actual thickness of each structural layer of the drill core sample and the needed core sample information.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects: according to the method and the system for detecting the thickness of each layer of the asphalt concrete pavement core drilling sample, the thickness condition of each structural layer of the core drilling sample can be obtained through simple data calculation according to the actual overall thickness of the core drilling sample and the proportion of the thickness of each structural layer to the total thickness. Therefore, the invention can realize the automatic detection of the thicknesses of different structural layers of the core sample of the asphalt pavement, improves the detection accuracy and reduces the human error.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for detecting the thickness of each layer of a core drilling sample of an asphalt concrete pavement;
FIG. 2 is a schematic flow chart of an edge detection process according to the present invention;
FIG. 3 is a block diagram of the system for detecting the thickness of each layer of the core drilling sample of the asphalt concrete pavement.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide a method and a system for detecting the thickness of each layer of an asphalt concrete pavement core drilling sample, which can realize the detection of the thicknesses of different structural layers of the asphalt pavement core drilling sample, improve the detection accuracy and reduce human errors.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
As shown in fig. 1 and 2, the method for detecting the thickness of each layer of the asphalt concrete pavement drill core sample provided by the invention comprises the following steps:
s1, acquiring a surface image of a core drilling sample of an asphalt concrete pavement to be tested, wherein the surface image of the core drilling sample is a complete image of the core drilling sample of the asphalt concrete pavement to be tested, which is taken out by a pavement core drilling machine, and specifically comprises the following steps:
taking out a core drilling sample of the asphalt concrete pavement to be tested through a pavement core drilling machine;
transversely placing a core drilling sample on a horizontal road surface, and acquiring a two-dimensional digital image of the core drilling sample by adopting a mobile image acquisition terminal device; the acquisition parameters of the mobile image acquisition terminal equipment are as follows: the lens shooting angle is parallel to the road surface, the acquisition mode is 1 times focusing mode, the surface image should contain the complete core drilling sample, and the core drilling sample is placed in the center of the image.
S2, carrying out gray level conversion on the surface image of the drill core sample to obtain the gray level distribution information of the surface of the drill core sample, wherein the method specifically comprises the following steps:
the surface image of the drill core sample adopts an RGB color mode to form a corresponding color image;
and (3) averaging the three-component brightness in the color image by adopting an average value method to obtain the gray value of the image pixel, and obtaining the gray distribution information of the surface of the drilling core sample.
S3, carrying out edge detection based on the gray level distribution information of the surface of the core drilling sample to obtain an edge boundary line between each structural layer in the core drilling sample, wherein the method specifically comprises the following steps:
based on the gray level distribution information of the surface of the core drilling sample, gaussian filtering is adopted to filter the surface image of the core drilling sample, so that the signal-to-noise ratio of the image is improved;
and (3) carrying out edge detection on the filtered image by adopting an improved sobel operator, extracting an image contour, filtering out finely divided edges generated by the detected broken stone contour, and obtaining edge boundaries generated by different structural layers.
S4, processing the distribution information of each structural layer based on the boundary line between each structural layer to obtain the proportion of the thickness of each structural layer to the total thickness, wherein the method specifically comprises the following steps:
obtaining the relative thickness of each structural layer in the surface image of the core drilling sample according to the boundary line between each structural layer; the relative thickness is the on-map thickness in the image;
and calculating the ratio of the thickness of each structural layer in the surface image of the core drilling sample to the total thickness based on the relative thickness of each structural layer, wherein the total thickness is the on-graph thickness of the core drilling sample in the surface image of the core drilling sample.
S5, performing ultrasonic thickness measurement on the core drilling sample to obtain the actual overall thickness of the core drilling sample;
s6, determining the actual thickness of each structural layer according to the actual overall thickness of the drill core sample and the proportion of the thickness of each structural layer to the total thickness.
And S4, according to the edge boundary lines of the layers of the different structural layers of the core sample obtained through detection, converting to obtain a cut rectangular picture, identifying and detecting the widths of the rectangular pictures corresponding to the different structural layers, further obtaining the relative thickness of each structural layer in the surface image, and calculating the proportion of the thickness of each structural layer to the total thickness of the core sample through a data processing module.
In the step S5, the thickness of the core drilling sample to be measured is measured by ultrasonic waves, the core drilling sample of the asphalt concrete pavement is detected by ultrasonic waves emitted by a mobile image acquisition terminal device with an ultrasonic processing device, and the thickness of the core drilling sample is calculated reversely by the ultrasonic intensity reflected by the upper edge and the lower edge of the core drilling sample, so as to obtain the actual overall thickness of the core drilling sample.
Specifically, in the step S3, an improved Sobel operator is adopted to perform edge detection on the surface image of the core drilling sample, as shown in fig. 2, and meanwhile, a field programmable gate array FPGA is utilized to perform parallel pipeline processing, and a Verilog HDL language is adopted to simulate the improved Sobel operator, and implementation and test are performed on the FPGA platform.
The improved Sobel operator is that the templates in the horizontal and vertical directions are increased to 8 directions (0 degrees, 45 degrees, 90 degrees, 135 degrees, 180 degrees, 225 degrees, 270 degrees and 315 degrees) on the basis that the traditional Sobel operator only detects the vertical and horizontal directions;
the traditional Sobel operator belongs to a discrete difference operator, and can obtain the gray approximation value of an image to detect the boundary position of the image.
Improved Sobel operator pass-through gradientDirections representing the edge intensities of the surface image of the core sample at the (x, y) position for gradients +.>The calculation mode of (2) is as follows:
wherein f means the original image, g x Meaning the gray value, g, of each pixel of the image in the x-direction y Meaning the gray value of each pixel of the image in the y-direction.
The modified Sobel operator calculates the gradient vector of the surface image of the core sample at (x, y) as shown below, and the direction of the vector is represented by θ (x, y):
the improved Sobel operator uses a 3X 3 operator template in the vertical direction and the horizontal direction to detect the edge of the surface image of the core drilling sample, and firstly calculates convolution integral of the image in the x axis and the y axis in the two directions from top to bottom and from left to right respectively;
the convolution coefficient table is expanded, the number of direction templates is increased from 2 to 8 (45 degrees, 135 degrees, 180 degrees, 225 degrees, 270 degrees and 315 degrees), and operator templates are as follows:
the center of the template and a certain pixel of the surface image of the drill core sample are positioned at the same position, and points around the pixel and coefficients on the template are multiplied and added; taking the maximum value obtained by the convolution function as a new gray value of the pixel to replace the pixel value of the central position of the template in the image;
graying the surface image of the drill core sample, and converting the RGB digital image into Gray values through the formula Gray=0.299R+0.857G+0.114B.
And analyzing the calculation result, setting a threshold value, comparing the obtained gray value with the threshold value, thereby obtaining edge points calculated by a Sobel operator, and using a weighted average algorithm to inhibit random noise of the image.
The FPGA system design comprises a camera acquisition and driving module, a storage module and an edge detection module, wherein a data image read in real time is stored in an SDRAM memory, and an edge detection algorithm is realized in parallel in the FPGA chip. By utilizing the advantages of parallel processing and pipeline operation of the FPGA, each module can run simultaneously, and multistage pipeline operation is carried out under one clock, so that the processing speed of images is greatly improved.
The FPGA system receives continuous data flow through the camera, stores the acquired data in the SDRAM memory, converts the data in the image from serial output to parallel output, and outputs 3 lines of data, and the 3 pixels can be clocked with a 3X 3 image pixel matrix.
The FPGA system is realized by calling the shift-RAM in the IP core, the output module can support the displacement of one or more clock period data by setting the number of the shift registers, and the specific bit width can be determined according to the number of one line of pixels of the image provided by the camera. Since Shift RAM can only generate one line of data at a time, two IP cores and one line of data being input are employed to generate a 3×3 matrix.
The Shift-RAM functions as Shift storage, when one of the Shift-RAM cores is filled with data, the Shift-RAM jumps to the next IP core to continue Shift storage, when all three RAMs are filled, a 3×3 matrix is output, and only the 3 rd RAM is filled with data. At the same time, 9 registers (P1-P9) need to be defined to receive the data output by the 3×3 template. Also during the calculation, the clock should be left empty at this time in order to keep the input signal synchronized with the output data. In order to ensure the synchronization of the data clock and the row field clock, the row field signal and the read signal need to be correspondingly adjusted, and the two clocks are moved.
As shown in fig. 3, the invention further provides a system for detecting the thickness of each layer of the asphalt concrete pavement drill core sample, which is applied to the method for detecting the thickness of each layer of the asphalt concrete pavement drill core sample, and comprises the following steps:
the mobile image acquisition terminal equipment comprises a camera and an image transmission module, and is used for acquiring a surface image of a core drilling sample of the asphalt concrete pavement to be detected, wherein the surface image of the core drilling sample is a complete image of the core drilling sample of the asphalt concrete pavement to be detected, which is taken out by a pavement core drilling machine;
the gray processing module is used for carrying out gray conversion on the surface image of the core drilling sample to obtain gray distribution information of the surface of the core drilling sample;
the edge detection module is used for carrying out edge detection based on the gray level distribution information of the surface of the core drilling sample to obtain an edge boundary line between each structural layer in the core drilling sample;
the data processing module is used for processing the distribution information of each structural layer based on the boundary line between the structural layers to obtain the proportion of the thickness of each structural layer to the total thickness;
the ultrasonic detection module is used for carrying out ultrasonic thickness measurement on the core drilling sample to obtain the actual overall thickness of the core drilling sample;
the data processing module is also used for determining the actual thickness of each structural layer according to the actual overall thickness of the drill core sample and the proportion of the thickness of each structural layer to the total thickness.
Specifically, the edge detection module comprises a boundary analysis sub-module, an edge extraction sub-module, a layer demarcation sub-module, a soaking filling fitting sub-module and a contour detection sub-module, wherein:
the boundary analysis submodule is used for judging the boundary contour of the surface image of the core drilling sample and filtering out the image boundary;
the edge extraction submodule is used for carrying out edge detection by utilizing an edge extraction four-edge detection algorithm and judging whether four straight lines of the edge are detected or not;
the layer demarcation submodule is used for judging demarcations detected by layers of different structural layers in the image due to material grading;
the immersion filling fitting sub-module is used for carrying out four-side straight line forced fitting by utilizing an immersion filling four-side detection algorithm and determining four intersection points of the four-side straight lines;
the contour detection submodule is used for carrying out contour detection on the surface image of the drill core sample and extracting Gaussian noise image edges.
Specifically, the ultrasonic detection module comprises a probe, a transmitting module, a receiving module, a main control module, a signal amplifying module, an analog-to-digital conversion module, a waveform generation module, a gate generation module, a man-machine interaction module and a signal processing module, wherein:
the transmitting module and the receiving module are used for transmitting ultrasonic waves to the drill core sample and receiving reflected ultrasonic information;
the signal amplifying module is used for filtering the received ultrasonic information and amplifying the obtained electric signal;
the main control module is used for controlling the emission and the reception of ultrasonic waves;
the analog-to-digital conversion module is used for converting the amplified electric signals into ultrasonic waveforms;
the waveform generation module is used for generating an electric signal received by the reflected wave receiver;
the signal processing module is used for comparing ultrasonic waveforms with different intensities and identifying the time difference of ultrasonic waves reflected from different edges.
In addition, the system also comprises a man-machine interaction module which is used for storing the actual thickness of each structural layer of the drill core sample and the needed core sample information.
Summarizing the core sample edge information obtained by the edge detection module to obtain the proportion of the layers of different structural layers, and interacting the core sample overall thickness information obtained by the ultrasonic analysis module with the information obtained by the edge detection module through the man-machine interaction module to obtain the layer thicknesses of the different structural layers of the core sample of the asphalt concrete pavement to be tested through the information processing module.
According to the invention, the core sample to be tested after on-site coring is subjected to photographing identification, edge detection positioning and ultrasonic thickness measurement to obtain the boundary line of each layer of edge in the picture and the overall thickness of the core sample, then the data processing module processes analysis data to obtain the real thickness information of each layer of the core sample, and the on-site obtained core sample is subjected to label remarking through man-machine interaction, so that the detection accuracy is improved, the working efficiency is increased, and the trouble of manual recording of a phase field is avoided.
The invention also provides a non-transitory computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the method for detecting the layer thickness of the asphalt concrete pavement core drilling sample according to any one of the above.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (9)
1. The method for detecting the thickness of each layer of the asphalt concrete pavement drill core sample is characterized by comprising the following steps of:
s1, acquiring a surface image of a core drilling sample of an asphalt concrete pavement to be tested, wherein the surface image of the core drilling sample is a complete image of the core drilling sample of the asphalt concrete pavement to be tested, which is taken out by a pavement core drilling machine;
s2, carrying out gray level conversion on the surface image of the core drilling sample to obtain gray level distribution information of the surface of the core drilling sample;
s3, carrying out edge detection based on the gray level distribution information of the surface of the core drilling sample to obtain an edge boundary line between each structural layer in the core drilling sample;
s4, processing the distribution information of each structural layer based on the boundary line between the structural layers to obtain the proportion of the thickness of each structural layer to the total thickness;
s5, performing ultrasonic thickness measurement on the core drilling sample to obtain the actual overall thickness of the core drilling sample;
s6, determining the actual thickness of each structural layer according to the actual overall thickness of the drill core sample and the proportion of the thickness of each structural layer to the total thickness.
2. The method for detecting the thickness of each layer of the asphalt concrete pavement core drilling sample according to claim 1, wherein in the step S1, the surface image of the core drilling sample of the asphalt concrete pavement to be detected is obtained, specifically comprising:
taking out a core drilling sample of the asphalt concrete pavement to be tested through a pavement core drilling machine;
transversely placing a core drilling sample on a horizontal road surface, and acquiring a two-dimensional digital image of the core drilling sample by adopting a mobile image acquisition terminal device; the acquisition parameters of the mobile image acquisition terminal equipment are as follows: the lens shooting angle is parallel to the road surface, the acquisition mode is 1 times focusing mode, the surface image should contain the complete core drilling sample, and the core drilling sample is placed in the center of the image.
3. The method for detecting the thickness of each layer of the core drilling sample of the asphalt concrete pavement according to claim 1, wherein in the step S2, gray scale conversion is performed on the surface image of the core drilling sample to obtain gray scale distribution information of the surface of the core drilling sample, specifically comprising:
the surface image of the drill core sample adopts an RGB color mode to form a corresponding color image;
and (3) averaging the three-component brightness in the color image by adopting an average value method to obtain the gray value of the image pixel, and obtaining the gray distribution information of the surface of the drilling core sample.
4. The method for detecting the thickness of each layer of the core drilling sample for the asphalt concrete pavement according to claim 3, wherein in the step S3, edge detection is performed based on the gray scale distribution information of the surface of the core drilling sample, so as to obtain an edge boundary between each structural layer in the core drilling sample, and the method specifically comprises the following steps:
based on the gray level distribution information of the surface of the core drilling sample, gaussian filtering is adopted to filter the surface image of the core drilling sample, so that the signal-to-noise ratio of the image is improved;
and (3) carrying out edge detection on the filtered image by adopting an improved sobel operator, extracting an image contour, filtering out finely divided edges generated by the detected broken stone contour, and obtaining edge boundaries generated by different structural layers.
5. The method for detecting the thickness of each layer of the asphalt concrete pavement drill core sample according to claim 1, wherein in the step S4, the distribution information of each structural layer is processed based on the boundary line between each structural layer to obtain the proportion of the thickness of each structural layer to the total thickness, and the method specifically comprises:
obtaining the relative thickness of each structural layer in the surface image of the core drilling sample according to the boundary line between each structural layer;
and calculating the ratio of the thickness of each structural layer in the surface image of the core drilling sample to the total thickness based on the relative thickness of each structural layer, wherein the total thickness is the on-graph thickness of the core drilling sample in the surface image of the core drilling sample.
6. An asphalt concrete pavement drill core sample layer thickness detection system, which is characterized in that the method applied to the asphalt concrete pavement drill core sample layer thickness detection system in any one of claims 1-5 comprises the following steps:
the mobile image acquisition terminal equipment comprises a camera and an image transmission module, and is used for acquiring a surface image of a core drilling sample of the asphalt concrete pavement to be detected, wherein the surface image of the core drilling sample is a complete image of the core drilling sample of the asphalt concrete pavement to be detected, which is taken out by a pavement core drilling machine;
the gray processing module is used for carrying out gray conversion on the surface image of the core drilling sample to obtain gray distribution information of the surface of the core drilling sample;
the edge detection module is used for carrying out edge detection based on the gray level distribution information of the surface of the core drilling sample to obtain an edge boundary line between each structural layer in the core drilling sample;
the data processing module is used for processing the distribution information of each structural layer based on the boundary line between the structural layers to obtain the proportion of the thickness of each structural layer to the total thickness;
the ultrasonic detection module is used for carrying out ultrasonic thickness measurement on the core drilling sample to obtain the actual overall thickness of the core drilling sample;
the data processing module is also used for determining the actual thickness of each structural layer according to the actual overall thickness of the drill core sample and the proportion of the thickness of each structural layer to the total thickness.
7. The system for layer thickness detection of asphalt concrete pavement drill core samples according to claim 6, wherein the edge detection module comprises a boundary analysis sub-module, an edge extraction sub-module, a horizon demarcation sub-module, a water immersion filling fitting sub-module, and a contour detection sub-module, wherein:
the boundary analysis submodule is used for judging the boundary contour of the surface image of the core drilling sample and filtering out the image boundary;
the edge extraction submodule is used for carrying out edge detection by utilizing an edge extraction four-edge detection algorithm and judging whether four straight lines of the edge are detected or not;
the layer demarcation submodule is used for judging demarcations detected by layers of different structural layers in the image due to material grading;
the immersion filling fitting sub-module is used for carrying out four-side straight line forced fitting by utilizing an immersion filling four-side detection algorithm and determining four intersection points of the four-side straight lines;
the contour detection submodule is used for carrying out contour detection on the surface image of the drill core sample and extracting Gaussian noise image edges.
8. The system for detecting the thickness of each layer of the asphalt concrete pavement drill core sample according to claim 6, wherein the ultrasonic detection module comprises a probe, a transmitting module, a receiving module, a main control module, a signal amplifying module, an analog-to-digital conversion module, a waveform generation module, a gate generation module, a man-machine interaction module and a signal processing module, wherein:
the transmitting module and the receiving module are used for transmitting ultrasonic waves to the drill core sample and receiving reflected ultrasonic information;
the signal amplifying module is used for filtering the received ultrasonic information and amplifying the obtained electric signal;
the main control module is used for controlling the emission and the reception of ultrasonic waves;
the analog-to-digital conversion module is used for converting the amplified electric signals into ultrasonic waveforms;
the waveform generation module is used for generating an electric signal received by the reflected wave receiver;
the signal processing module is used for comparing ultrasonic waveforms with different intensities and identifying the time difference of ultrasonic waves reflected from different edges.
9. The system for detecting the thickness of each layer of the asphalt concrete pavement drill core sample according to claim 6, wherein the system further comprises a man-machine interaction module for storing the actual thickness of each structural layer of the drill core sample and the required core sample information.
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