CN114373013B - Quick filling and rolling speed statistics method based on image processing - Google Patents
Quick filling and rolling speed statistics method based on image processing Download PDFInfo
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- 238000005096 rolling process Methods 0.000 title claims abstract description 126
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Abstract
The invention discloses a rapid statistical method for the running speed of a filling rolling vehicle based on image processing. The method is characterized in that: the method comprises the steps of realizing rapid calculation and statistics of average rolling speed at each position in rolling construction in an image processing mode, converting actual engineering plane coordinates into image coordinates, and then calculating by a design algorithm on an image to finally obtain the average rolling speed of each pixel point. The invention can rapidly and accurately obtain the high-precision average rolling speed map of the rolling construction whole bin surface, realizes the statistics of the average rolling speed in the filling rolling construction process of real-time, accurate and corresponding space positions, truly and intuitively reflects the real-time quality information in the filling rolling construction process of the earth and stone party, allows a supervisor party, an industry main party and a constructor to know in time, controls the construction quality in real time, ensures engineering safety and has important market value.
Description
Technical Field
The invention belongs to the technical field of control and management of the rolling construction quality process of earth and stone filling engineering, and particularly relates to a rapid statistical method of the running speed of a filling rolling vehicle based on image processing.
Background
In earth and stone filling engineering, the compaction quality of the filling material is critical to the stability and durability of the structure. Therefore, quality control in the construction process of filling and rolling of the earth and stone is a key link for ensuring the construction quality and safety of the structure. At present, quality management in filling and rolling construction mainly adopts 'double control' control of rolling parameters in the construction process and pit sampling detection after construction is finished, namely, means of manually controlling the rolling process parameters (mainly comprising the running speed of rolling machinery, the number of rolling passes, bin surface flatness and the like) of construction and manually performing pit digging sampling detection on site and the like are mainly adopted. However, the rolling parameters are roughly managed by means of supervision and manual control of constructors, and are greatly interfered by human factors in the implementation process, so that accurate control of the rolling construction process parameters is difficult to realize, and finally the rolling construction quality cannot be ensured to meet the design requirements. Moreover, along with the increase of construction scale and construction strength, higher requirements are put forward on the quality control of earth and stone filling construction, and the conventional manual quality management mechanism cannot meet the requirements of current large-scale mechanical construction and construction progress.
The real-time, continuous and high-precision automatic monitoring of the rolling machine in construction can be realized by utilizing the positioning technologies of modern advanced GNSS, measuring robots and the like, the three-dimensional coordinate data of the rolling machine in construction operation can be obtained, and the calculation of important rolling construction parameters can be realized by the data, so that the purpose of monitoring the rolling construction quality is achieved. Wherein the rolling speed is the distance between two spatial positions through which the rolling machine runs in unit time. The rolling speed has obvious influence on the compactness of the filling material layer, and the rolling speed is too high, so that the flatness of the pressed layer is easily deteriorated. The rolling speed affects the compaction time of the material per unit area of the vibrating wheel pair. When the rolling speed is low, the number of vibrations per unit area is larger than when the rolling speed is high, and thus the energy applied to the material to be pressed is larger than the former. In fact, the energy transferred into the layer of material being compacted is inversely proportional to the rolling speed. Assuming that the compaction energy required to achieve a given degree of compaction of the layer of millboard material is unchanged, the number of passes is approximately doubled when the milling speed is doubled. Therefore, how to quickly and accurately obtain the average rolling speed of the current area is one of the focus points of the rolling quality monitoring system. Currently, the monitoring of the rolling speed in the rolling monitoring system in application is mainly statistical and control in the time dimension, namely, the rolling speed in a certain time period or a certain moment. The construction rolling is to construct a planar area, so that the rolling speed can be counted and controlled in the space domain more accurately and effectively. Therefore, how to quickly and accurately obtain the average rolling speed at each position of the construction area is one of the key problems to be solved by the rolling construction quality real-time monitoring system for further improving the actual demands.
Disclosure of Invention
Aiming at the defects of the existing statistical method, the invention provides a rapid statistical method for the running speed of a filling rolling vehicle based on image processing by converting the statistics and control of the rolling speed from a one-dimensional time domain to a two-dimensional space domain.
The technical scheme adopted by the invention is a rapid statistical method for the running speed of a filling rolling vehicle based on image processing, which specifically comprises the following steps:
step 1, designing a functional relation c= (R, G, B) =f (v) of the color value and the velocity value;
step 2, determining the size of an image used for calculation according to the size and shape of a construction bin surface, and establishing a conversion relation between an engineering coordinate system and an image coordinate system;
step 3, initializing background color of the image by using color values (0, 0), namely initializing the average rolling speed at any position of a construction bin surface to be 0;
step 4, acquiring the time t of the rolling vehicle in the filling construction process through a space positioning technology i Three-dimensional space coordinate data (x i ,y i ,h i ) Where i is the number in the sequence of consecutively sampled spatial position data, x i 、y i Is the plane coordinate of the rolling vehicle in the engineering coordinate system, h i Is rolling vehicle elevation data; the left end point L of the rolling roller wheel at the moment is obtained through calculation of geometric position relation i And right end point R i And finally determining t i-1 From time to t i Time-of-day rolling strip L i-1 L i R i R i-1 And average speed
Step 5, drawing a quadrangle L in the image through the coordinate transfer relation in the step 2 i-1 L i R i R i-1 And calculating to determine which pixels are included in the quadrangle, and adding color values to the color values of the pixelsThereby obtaining an accumulated rolling speed map with a color value corresponding to the accumulated value of the speed values of all rolling machines at the position when passing through;
step 6, synchronously obtaining a full bin surface rolling pass number chart with the same size by using a rolling pass number calculation method based on image processing;
step 7, scanning the accumulated rolling speed diagram and the rolling pass diagram to obtain the speed color value C of each pixel point i,j And the number of rolling passes N i,j Calculating to obtain the average rolling speed at each pixel pointThus obtaining the average rolling speed value at any position of the construction bin surface at the moment;
and 8, continuously repeating the processes of the steps 4-7 in the construction process to obtain real-time average rolling speed information of the whole bin surface in rolling construction, and obtaining a qualified condition distribution map of the average rolling speed of the whole bin surface by comparing the construction quality control requirements.
Further, in step 1, the functional relationship c= (R, G, B) =f (v) between the color value and the velocity value, where R, G, B is the numerical value of three channels in the RGB color model, specifically as follows:
when v < = 2.55,
when 2.55 < v < = 5.10,
when v is greater than 5.10, the catalyst,
further, in the step 2, the size of the image is determined according to the size of the actual rolling bin surface, the larger the image is, the higher the spatial resolution corresponding to each pixel is, the more accurate and finer the obtained average rolling speed distribution is, but the larger the calculated amount is, the higher the requirement on computer hardware is, so that the image is reasonably determined after the actual requirement is comprehensively considered.
Further, in the step 2, a plane coordinate mutual conversion relation between an engineering coordinate system and an image coordinate system of the construction bin surface is established, conversion parameters are obtained through calculation, and a calculation formula is as follows;
wherein X, Y is the plane coordinate of any point in the image coordinate system, X and y are the plane coordinate of any point in the engineering coordinate system, and X 0 、Y 0 The offset of the origin of the image coordinate system relative to the origin of the engineering coordinate system is represented by θ, the rotation angle of the engineering coordinate system converted to the image coordinate system is represented by m, and the scale factor of the engineering coordinate system converted to the image coordinate system is represented by m; the engineering coordinate system is customized according to the actual requirements of the field in engineering, and the image coordinate system is defined in computer graphics.
Further, in step 4, the average speed in the rolled strip is calculated by the following formula
Wherein, (x) i-1 ,y i-1 ,h i-1 ) Is that the rolling vehicle is at t i-1 Three-dimensional space coordinate data of time.
Further, step 7 further includes defining a function of gray value and average speedAnd generating an average rolling speed gray scale map, and obtaining an average rolling speed value at any position of the construction bin surface at the moment in the gray scale map.
The invention provides a rapid statistical method for the running speed of a filling rolling vehicle based on image processing, which can rapidly and accurately obtain a high-precision average rolling speed diagram of the whole rolling construction warehouse surface, realizes the statistics of the average rolling speed in the filling rolling construction process of real-time, accurate and corresponding space positions, truly and intuitively reflects the real-time quality information in the filling rolling construction process of the earth and stone side, ensures that a supervisor, an industry master and a constructor can know in time the construction quality in real time, ensures engineering safety and has important market value.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a schematic view of a laminating belt according to an embodiment of the present invention.
FIG. 3 is a graph of total bin surface cumulative rolling speed in accordance with an embodiment of the present invention.
Fig. 4 is a gray scale plot of the average rolling speed across the full bin surface of an embodiment of the invention.
FIG. 5 is a graph of the full face average rolling speed qualification profile of an embodiment of the present invention.
Detailed Description
The method provided by the invention can realize the flow by using a computer software technology, and is shown in fig. 1. In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail below with reference to the accompanying drawings and examples, in which:
step 1, in this embodiment, a functional relationship c= (R, G, B) =f (v) corresponding to the color value and the velocity value is defined, where R, G, B is a numerical value of three channels in the RGB color model, specifically as follows:
when v < = 2.55,
when 2.55 < v < = 5.10,
when v is greater than 5.10, the catalyst,
step 2, in this embodiment, the size of the construction warehouse surface is about 20m×100m, the size of the image used for calculation is 1100×400px determined in consideration of the actual situation, and then the conversion relation between the engineering plane coordinate system and the image coordinate system is established, and the calculation formula is as follows
Wherein X, Y is the plane coordinate of any point in the image coordinate system, X and y are the plane coordinate of any point in the engineering coordinate system, and X 0 、Y 0 The offset of the origin of the image coordinate system relative to the origin of the engineering coordinate system is represented by θ, the rotation angle of the engineering coordinate system converted to the image coordinate system is represented by m, and the scale factor of the engineering coordinate system converted to the image coordinate system is represented by m; the engineering coordinate system is generally customized according to the actual requirements of the field in engineering, and the image coordinate system is defined in computer graphics.
Step 3, initializing background color of the image by using color values (0, 0), namely f (0) defined in step 1, and initializing average rolling speed at any position of a construction bin surface to be 0;
step 4, acquiring the time t of the rolling vehicle in the filling construction process through a space positioning technology i Three-dimensional space coordinate data (x i ,y i ,h i ) Where i is the number in the sequence of consecutively sampled spatial position data, x i 、y i Is the plane coordinate of the rolling vehicle in the engineering coordinate system, h i Is rolling vehicle elevation data; the left end point L of the rolling roller wheel at the moment is obtained through calculation of geometric position relation i And right end point R i Plane coordinates of (c) to finally obtain t i-1 From time to t i Time-of-day rolling strip L i-1 L i R i R i-1 An example of a rolled strip is shown in FIG. 2, and the average velocity within the rolled strip is calculated using the following formula
Wherein, (x) i-1 ,y i-1 ,h i-1 ) Is that the rolling vehicle is at t i-1 Three-dimensional space coordinate data of moment;
step 5, drawing a quadrangle L in the image i-1 L i R i R i-1 And calculating to determine which pixels are included in the quadrangle, and adding color values to the color values of the pixelsThereby obtaining an accumulated rolling speed map with a color value corresponding to the accumulated value of the speed values of all rolling machines passing through at the position, as shown in fig. 3;
step 6, synchronously obtaining a full bin surface rolling pass number chart with the same size by using a rolling pass number calculation method based on image processing;
step 7, scanning the accumulated rolling speed diagram and the rolling pass diagram to obtain the speed color value C of each pixel point i,j And the number of rolling passes N i,j Calculating to obtain the average rolling speed at each pixel pointDefining gray value as a function of average speed +.>Generating an average rolling speed gray scale map, as shown in fig. 4, and obtaining an average rolling speed value at any position of the construction bin surface at the moment from the map;
and 8, continuously repeating the processes of the steps 4-7 in the construction process to obtain real-time average rolling speed information of the whole bin surface in rolling construction, and obtaining a qualified condition distribution diagram of the average rolling speed of the whole bin surface by comparing the construction quality control requirements, as shown in fig. 5.
The foregoing description of the preferred embodiments of the invention is provided for the purpose of illustration only and is not intended to limit the scope of the invention, so that any modifications, equivalents, improvements or the like which fall within the spirit and principles of the invention should be construed as being included in the scope of the invention.
Claims (6)
1. The rapid statistical method for the running speed of the filling rolling vehicle based on the image processing is characterized by comprising the following steps of:
step 1, designing a functional relation c= (R, G, B) =f (v) of the color value and the velocity value;
step 2, determining the size of an image used for calculation according to the size and shape of a construction bin surface, and establishing a conversion relation between an engineering coordinate system and an image coordinate system;
step 3, initializing background color of the image by using color values (0, 0), namely initializing the average rolling speed at any position of a construction bin surface to be 0;
step 4, acquiring the time t of the rolling vehicle in the filling construction process through a space positioning technology i Three-dimensional space coordinate data (x i ,y i ,h i ) Where i is the number in the sequence of consecutively sampled spatial position data, x i 、y i Is the plane coordinate of the rolling vehicle in the engineering coordinate system, h i Is rolling vehicle elevation data; the left end point L of the rolling roller wheel at the moment is obtained through calculation of geometric position relation i And right end point R i And finally determining t i-1 From time to t i Time-of-day rolling strip L i-1 L i R i R i-1 And average speed
Step 5, drawing a quadrangle L in the image through the coordinate transfer relation in the step 2 i-1 L i R i R i-1 And calculating to determine which pixels are included in the quadrangle, and adding color values to the color values of the pixelsThereby obtaining an accumulated rolling speed map with a color value corresponding to the accumulated value of the speed values of all rolling machines at the position when passing through;
step 6, synchronously obtaining a full bin surface rolling pass number chart with the same size by using a rolling pass number calculation method based on image processing;
step 7, scanning the accumulated rolling speed diagram and the rolling pass diagram to obtain the speed color value C of each pixel point i,j And the number of rolling passes N i,j Calculating to obtain the average rolling speed at each pixel point
And 8, continuously repeating the processes of the steps 4-7 in the construction process to obtain real-time average rolling speed information of the whole bin surface in rolling construction, and obtaining a qualified condition distribution map of the average rolling speed of the whole bin surface by comparing the construction quality control requirements.
2. The rapid statistical method for the running speed of the filling rolling vehicle based on the image processing according to claim 1, wherein: in step 1, the functional relation c= (R, G, B) =f (v) between the color value and the velocity value, where R, G, B is the numerical value of three channels in the RGB color model, specifically as follows:
when v < = 2.55,
when 2.55 < v < = 5.10,
when v is greater than 5.10, the catalyst,
3. the rapid statistical method for the running speed of the filling rolling vehicle based on the image processing according to claim 1, wherein:
in the step 2, the image size is determined according to the actual rolling bin surface size, the larger the image is, the higher the spatial resolution corresponding to each pixel is, the more accurate and finer the obtained average rolling speed distribution is, but the larger the calculated amount is, the higher the requirement on computer hardware is, so that the image is reasonably determined after the actual requirement is comprehensively considered.
4. The rapid statistical method for the running speed of the filling rolling vehicle based on the image processing according to claim 1, wherein: in the step 2, establishing a plane coordinate mutual conversion relation between an engineering coordinate system and an image coordinate system of a construction bin surface, and calculating to obtain conversion parameters, wherein a calculation formula is as follows;
wherein X, Y is the plane coordinate of any point in the image coordinate system, X and y are the plane coordinate of any point in the engineering coordinate system, and X 0 、Y 0 The offset of the origin of the image coordinate system relative to the origin of the engineering coordinate system is represented by θ, the rotation angle of the engineering coordinate system converted to the image coordinate system is represented by m, and the scale factor of the engineering coordinate system converted to the image coordinate system is represented by m; the engineering coordinate system is customized according to the actual requirements of the field in engineering, and the image coordinate system is defined in computer graphics.
5. The rapid statistical method for the running speed of the filling rolling vehicle based on the image processing according to claim 1, wherein: in step 4, the average speed in the rolled strip is calculated by the following formula
Wherein, (x) i-1 ,y i-1 ,h i-1 ) Is that the rolling vehicle is at t i-1 Three-dimensional space coordinate data of time.
6. The rapid statistical method for the running speed of the filling rolling vehicle based on the image processing according to claim 1, wherein: step 7 also includes defining gray scale value as a function of average speedAnd generating an average rolling speed gray scale map, and obtaining an average rolling speed value at any position of the construction bin surface at the moment in the gray scale map.
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