CN105547185A - Method for obtaining lateral jet boundary of liquid - Google Patents
Method for obtaining lateral jet boundary of liquid Download PDFInfo
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- CN105547185A CN105547185A CN201610028138.1A CN201610028138A CN105547185A CN 105547185 A CN105547185 A CN 105547185A CN 201610028138 A CN201610028138 A CN 201610028138A CN 105547185 A CN105547185 A CN 105547185A
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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
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
Abstract
The invention provides a method for obtaining the lateral jet boundary of liquid. Through comparing relative errors among a plurality of linear fitting curves, the method obtains a clear lateral jet boundary of liquid.
Description
Technical field
The present invention relates to the technical field that hydrofluidic border obtains, be specifically related to a kind of acquisition methods of liquid transverse jet border.
Background technology
In liquid fuel within engine, the jet of liquid fuel and atomization are very important processes.Wherein, the boundary information of jet receives much concern as the index weighing atomizing effect, and it affects the fogging degree of transverse jet, the blending degree of jet and air, also affects the exhibition of jet to expansion simultaneously.The way of current research jet boundary mainly contains two kinds: a kind of is the grand design being obtained transverse jet by optical imagery, then is obtained the information of jet boundary by image procossing.Another kind is the size droplet diameter information by optical measuring technique single-point, obtains jet boundary by the size droplet diameter information of each point, then matching jet curve penetration depth.Conventional measuring method comprises schlieren method, shadowing method, High Speed Photography, sheet light method and PDA (ParticleDynamicAnalyzer).
Be not quite similar for penetration depth definition and acquisition methods in domestic and international research, adopt PDA spot measurement, its efficiency is lower, is difficult to the overall boundary information once obtaining complete flow field; High Speed Photography, shadowing method and schlieren method can obtain the general profile of jet main flow, but based on the jet boundary information that high speed photography obtains through image procossing, physical significance is indefinite.
Summary of the invention
The object of the present invention is to provide a kind of acquisition methods of liquid transverse jet border, this invention solves prior art border acquisition methods cannot fast, quantitatively, obtain to explicit physical meaning the technical matters on liquid transverse jet border in supersonic flow.
The invention provides a kind of acquisition methods of liquid transverse jet border, comprise the following steps:
Step S100: obtain the scale map picture in jet plane by pulse background formation method, then the liquid transverse jet in supersonic flow field is taken continuously, obtain the transient images of liquid transverse jet, obtain initial jet boundary point by given gray threshold;
Step S200: once fitting is carried out to the hydrofluidic frontier point in image, obtain the first matched curve, first matched curve follows the example of line successively along jet direction, and be that zone boundary is searched jet boundary and to be fallen apart a little the most concentrated region with circle in got normal direction, and in this region, extract multiple fisrt feature points of jet boundary successively;
Step S300: quadratic fit is carried out to fisrt feature point, obtain the second matched curve, second matched curve follows the example of line successively along jet direction, and be that zone boundary is searched jet boundary and to be fallen apart a little the most concentrated region with circle in got normal direction, and in this region, extract multiple second feature points of jet boundary successively;
Step S400: cubic fit is carried out to second feature point, obtain the 3rd matched curve, calculate the relative error of the second matched curve and the 3rd matched curve, when relative error magnitudes is less than 0.1%, using second feature point as liquid transverse jet border, otherwise, repeat step S300 ~ step S400, until relative error magnitudes is less than 0.1%;
Step S500: the pixel in image is converted into actual physics distance according to scale, obtains the physical boundary on liquid transverse jet border.
Further, the frontier point Image Acquisition of original liquid transverse jet is obtained by the method for given gray threshold, and gray threshold is 10% of maximum gray scale.
Further, carry out matching according to least square method principle to obtain;
First time matched curve is
Second matched curve is
3rd matched curve is
Wherein x is the horizontal ordinate of pixel, and y is the ordinate of pixel, a
nand b
nfor fitting coefficient.
Further, step S200 comprises the following steps:
Step S210: get first time matched curve
upper any point (x
i, y
i), the normal crossing the first matched curve of this point is
And it is crossing with the border of image;
Step S220: with the initial point of first time matched curve for starting point, x-axis is positive dirction, with 10 pixel distances for step-length, make the normal of the point in the first matched curve, with this normal and image border away from the intersection point of jet area for starting point, with any point on this normal for the center of circle, R is radius, is that the pixel number of 255 is designated as S by the gray-scale value dropped in this circle
1, then move 10 pixel distances along this normal, obtain the next one and search the round heart;
Step S230: search the round heart for the center of circle with this next one, radius is R, and the pixel number being 255 by the gray-scale value dropped in this circle is S
2, by that analogy, obtain S
3, S
4s
i, the round heart of searching getting maximum S value corresponding is unique point in this normal direction;
To the more lower (x in the second matched curve
i+1, y
i+1) repeat step S110 ~ 130 acquisition unique point, after having moved along the first matched curve, obtain the set of all unique points as fisrt feature point.
Further, step S300 comprises the following steps:
Step S310: got any point (x in the second matched curve
i, y
i) normal, this normal is
and it is crossing with image boundary;
Step S320: with the initial point of first time matched curve for starting point, x-axis is positive dirction, with 10 pixel distances for step-length, make the normal of the point in the second matched curve, with this normal and image boundary away from the intersection point of jet area for starting point, along this normal direction, with on this normal a bit for the center of circle, R is radius, is that the pixel number of 255 is designated as S by the gray-scale value dropped in this circle
1, then move 10 pixel distances along this normal, obtain the next one and search the round heart;
Step S330: search the round heart for the center of circle with this next one, radius is R, and the pixel number being 255 by the gray-scale value dropped in this circle is T
2, by that analogy, obtain T
3, T
4t
i, the round heart of searching getting maximum S value corresponding is unique point in this normal direction;
To the more lower (x in the second matched curve
i+1, y
i+1) repeat step S310 ~ 330 acquisition unique point, after having moved along the second matched curve, the set obtaining all unique points is second feature point.
Further, the relative error of the second matched curve and the 3rd matched curve is
wherein
for the relative error number percent that arbitrary location of pixels is corresponding, η is average error number percent, and n is pixel number.
Further, formation method is pulse laser background imaging method.
Technique effect of the present invention:
The acquisition methods on liquid transverse jet border provided by the invention, feature point extraction and linear fit is carried out repeatedly by the jet boundary point obtained grey relevant dynamic matrix, obtain the border of liquid transverse jet, gained measurement result is objective, quantitative, physical significance is clear accurately.
Specifically please refer to the following description of the various embodiments proposed according to the acquisition methods on liquid transverse jet border of the present invention, above and other aspect of the present invention will be made apparent.
Accompanying drawing explanation
Fig. 1 is the process flow diagram schematic diagram of the preferred embodiment of the acquisition methods that the invention provides liquid transverse jet border;
Fig. 2 the invention provides the pulse background imaging test apparatus structure schematic diagram used in the acquisition methods on liquid transverse jet border;
The jet boundary point schematic diagram obtained when Fig. 3 is set threshold value as maximum gradation value in the acquisition methods preferred embodiment that the invention provides liquid transverse jet border 10%;
Fig. 4 is the first matched curve and initial jets frontier point distribution schematic diagram in the acquisition methods preferred embodiment that the invention provides liquid transverse jet border;
Fig. 5 is the second matched curve and second feature point distribution schematic diagram in the acquisition methods preferred embodiment that the invention provides liquid transverse jet border;
Fig. 6 is the 3rd matched curve and third feature point distribution schematic diagram in the acquisition methods preferred embodiment that the invention provides liquid transverse jet border;
Fig. 7 is that in the acquisition methods preferred embodiment that the invention provides liquid transverse jet border, the second matched curve and the 3rd curve compare schematic diagram.
Embodiment
The accompanying drawing forming a application's part is used to provide a further understanding of the present invention, and schematic description and description of the present invention, for explaining the present invention, does not form inappropriate limitation of the present invention.
See Fig. 1, the acquisition methods on liquid transverse jet border provided by the invention comprises the following steps:
Step S100: obtain the scale map picture in jet plane by pulse background formation method, then the liquid transverse jet in supersonic flow field is taken continuously, obtain the transient images of liquid transverse jet, initial jet boundary point is obtained, see Fig. 3 by given gray threshold (10% of maximum gray scale);
Step S200: once fitting is carried out to the hydrofluidic frontier point in image, obtain the first matched curve, first matched curve follows the example of line successively along jet direction, and be that zone boundary is searched jet boundary and to be fallen apart a little the most concentrated region with circle in got normal direction, and in this region, extract multiple fisrt feature points of jet boundary successively;
Step S300: quadratic fit is carried out to fisrt feature point, obtain the second matched curve, second matched curve follows the example of line successively along jet direction, and be that zone boundary is searched jet boundary and to be fallen apart a little the most concentrated region with circle in got normal direction, and in this region, extract multiple second feature points of jet boundary successively;
Step S400: cubic fit is carried out to second feature point, obtain the 3rd matched curve, calculate the relative error of the second matched curve and the 3rd matched curve, when relative error magnitudes is less than 0.1%, using second feature point as liquid transverse jet border, otherwise, repeat step S300 ~ step S400, until relative error magnitudes is less than 0.1%;
Step S500: the pixel in image is converted into actual physics distance according to scale, obtains the physical boundary on liquid transverse jet border.
Method provided by the invention is by after carrying out repeatedly matching to the transient images of liquid transverse jet, and the image that pulse background formation method can be obtained, change the jet boundary of explicit physical meaning into.
See Fig. 2, the pulse background formation method that preferred the present invention adopts obtains liquid transverse jet image by this device.This device comprises: be arranged in the laser generator 8 of test section 6 side, be relatively arranged on CCD camera 2 and the optical screen 4 of test section 6 side with laser generator 8.Test section 6 is inner hollow, can be test section structure conventional in this formation method.Optical screen 4 is arranged between laser generator 8 and test section 6.Laser generator 8 can launch laser beam 7 to optical screen 4.The outer wall in test section 6 region that laser generator 8 is just right is quartz glass, and the outer wall adopting this material to make test section 6 is conducive to CCD camera 2 and obtains associated picture.Laser generator 8 and CCD camera 2 all with computing machine 1 data cube computation, the storage to obtained image and transmission can be realized.Jet-core region 5 is in test section 6.During use, by the optical center position adjustments of light source center, jet-core region 5 and CCD camera 2 to same vertical height, then focus, the bias light plane of micro-lens focal plane, optical screen 4 is adjusted to parallel with jet-core region 5.Regulate laser irradiating angle, make bias light imagewise uniform.Regulate laser intensity and camera exposure time, ensure to obtain image clearly.Then in camera focal plane, place scale and take, preserving scale information, thus obtain the scale map picture in jet plane.Keep the parameter constant of CCD camera 2 and laser generator 8, supersonic flow 3 is passed in test section 6, and start injected liquid, open laser generator 8 by computing machine 1 and CCD camera 2 starts continuous recording liquid fluidics diagram picture, obtain digitized transient images.
See Fig. 3, for gained jet transient images is after grey relevant dynamic matrix process, the jet boundary scatter diagram obtained.Given gray threshold (10% of the maximum gray scale of image), obtains the image of jet boundary point; Can find out, the jet upstream boundary that this kind of method obtains is comparatively clear, and jet downstream causes frontier point to disperse due to ground unrest and jet current secondary atomization, does not have clear and definite jet boundary, therefore needs the given jet boundary that a kind of method is clear and definite.Wherein grey relevant dynamic matrix operation steps is: after carrying out denoising to image, background gray levels is 255, region, jet-core region gray-scale value is 0, therefore a given gray threshold, 10% of such as maximum gradation value, then each pixel of image is judged one by one, extract the pixel that gray-scale value equals threshold value, Image Reconstruction shown in Fig. 3 is become initial jet boundary image.
Disclosed in existing many sections of documents, the known penetration depth experimental formula of content is in form
wherein, h is jet penetration, and d is nozzle diameter, and q is hydraulic pneumatic amount ratio:
Wherein, u
∞for lateral gas flow velocity, u
jfor lip jet speed, a
1, a
2, a
3be constant, under same operating, because speed of incoming flow and lip jet speed are definite values, namely think that q is definite value in same operating.Therefore matching provided by the invention adopts least square method principle, selects shape as y=ax
bcurve fit type matching is carried out to borderline region; See Fig. 3, set up coordinate system, with the intersection point of the dull and stereotyped coboundary of jet expansion jet cylinder windward side and spray for coordinate origin o, x-axis overlaps with the dull and stereotyped coboundary of spray, and be just along airflow direction, y-axis is just along liquid injection direction, perpendicular to spray flat board; Wherein x is pixel horizontal ordinate, and y is pixel ordinate, and a, b are undetermined coefficient, obtains the first matched curve
as shown in Figure 4.
Preferably, step S200 comprises the following steps:
Step S210: get first time matched curve
upper any point (x
i, y
i), the normal crossing the first matched curve of this point is
And it is crossing with transient images border;
Step S220: with the initial point of first time matched curve for starting point, x-axis is positive dirction, with 10 pixel distances for step-length, make the normal of the point in the first matched curve, with this normal and image border away from the intersection point of jet area for starting point, with any on normal for the center of circle, R is radius, is that the pixel number of 255 is designated as S by the gray-scale value dropped in this circle
1, then move 10 pixel distances along this normal, obtain the next one and search the round heart;
Step S230: search the round heart for the center of circle with this next one, radius is R, and the pixel number being 255 by the gray-scale value dropped in this circle is S
2, by that analogy, obtain S
3, S
4s
i, the round heart of searching getting maximum S value corresponding is unique point in this normal direction;
To the more lower (x in the second matched curve
i+1, y
i+1) repeat step S110 ~ 130 acquisition unique point, after having moved along the first matched curve, obtain the set of all unique points as fisrt feature point.
Be specially the first matched curve
on point taking method line; With above-mentioned coordinate origin for starting point, x-axis positive dirction, with 10 pixel distances for step-length, and as horizontal ordinate, gets curve
on a bit (x
i, y
i), crossing this normal is
And it is crossing with image boundary.
This normal direction is searched the region that frontier point distribution is the most concentrated, determines a bit as the unique point in this region; With normal and image edge away from the intersection point of jet area for starting point, along normal direction, with the point on normal for the center of circle, R is radius, adds up, be designated as S to the pixel that the gray-scale value dropped in circle is 255
1, then move 10 pixel distances along normal, adding up under new position gray-scale value in circle is the pixel number of 255, is designated as S
2, be designated as S successively in this approach
3, S
4s
i, the S value that comparative statistics obtains, get maximal value corresponding search the round center of circle as the unique point in this normal direction, then move normal along the first matched curve, use the same method obtain all unique points; By the unique point that the method is chosen, the physical significance on transverse jet border of more fitting on the one hand, on the other hand, unique point distribution is more even, makes jet downstream boundary more clear.
Matching is carried out to fisrt feature point and obtains the second matched curve.The second matched curve preferably obtained is
matching jet boundary curve as shown in Figure 5.Due to the second matching to as if the first matched curve normal near extract the fisrt feature point obtained, the matched curve therefore obtained more is fitted real jet boundary.This matching is same to be carried out according to least square method principle.
Preferably, step S300 comprises the following steps:
Step S310: cross any point (x in the second matched curve
i, y
i) normal be
and it is crossing with image boundary;
Step S320: with the initial point of first time matched curve for starting point, x-axis is positive dirction, with 10 pixel distances for step-length, make the normal of the point in the second matched curve, with this normal and image border away from the intersection point of jet area for starting point, along normal direction, with on normal a bit for the center of circle, R is radius, is that the pixel number of 255 is designated as S by the gray-scale value dropped in this circle
1, then move 10 pixel distances along this normal, obtain the next one and search the round heart;
Step S330: search the round heart for the center of circle with this next one, radius is R, is that the pixel number of 255 is designated as T by the gray-scale value dropped in this circle
2, by that analogy, obtain T
3, T
4t
i, the round heart of searching getting maximum T value corresponding is unique point in this normal direction;
To the more lower (x in the second matched curve
i+1, y
i+1) repeat step S310 ~ 330 acquisition unique point, after having moved along the second matched curve, the set obtaining all unique points is second feature point.
Effect is identical with front.
Carry out matching with gained second feature point for object, obtain the 3rd matched curve.Preferably, the 3rd matched curve is
see Fig. 6, can extract the unique point near the 3rd matched curve normal with reference to abovementioned steps equally.In full, in all matched curves, x is the horizontal ordinate of pixel, and y is the ordinate of pixel, a
nand b
nfor fitting coefficient.Because in step S200, the extracting method of second feature point is identical with third feature point extracting method in step S300, the number of second feature point and the number of third feature point adopt same letter to state.
Preferably, calculating formula is adopted
wherein
for the relative error number percent that single location of pixels is corresponding, η is average error number percent, and n is pixel number; When the value of η is less than 0.1%, think that this series of features point can as transverse jet border, otherwise, repeat above-mentioned steps six to eight, until η meets the demands; Calculate the relative error between the second matched curve and the 3rd matched curve, twice fitting curve is shown in Fig. 7.When relative error between the second matched curve obtained after adopting the method matching and the 3rd matched curve meets this condition, gained boundary curve as shown in Figure 7.By comparison diagram 3 and Fig. 7 known, the two is more identical.
The scale that step S500 obtains according to pulse background formation method, the pixel distance of scale label in measurement image, can calculate image resolution ratio according to scale label, is multiplied by the pixel distance of image with image resolution ratio, obtain actual physics distance, namely obtain the jet boundary of physics.
Clear scope of the present invention is not restricted to example discussed above by those skilled in the art, likely carries out some changes and amendment to it, and does not depart from the scope of the present invention of appended claims restriction.Although oneself is through illustrating in detail in the accompanying drawings and the description and describing the present invention, such explanation and description are only explanations or schematic, and nonrestrictive.The present invention is not limited to the disclosed embodiments.
By to accompanying drawing, the research of instructions and claims, it will be appreciated by those skilled in the art that when implementing of the present invention and realize the distortion of the disclosed embodiments.In detail in the claims, term " comprises " does not get rid of other steps or element, and indefinite article " " or " one " are not got rid of multiple.The fact of some measure of quoting in mutually different dependent claims does not mean that the combination of these measures can not be advantageously used.Any reference marker in claims does not form the restriction to scope of the present invention.
Claims (7)
1. the acquisition methods on liquid transverse jet border, is characterized in that, comprises the following steps:
Step S100: obtain the scale map picture in jet plane by pulse background formation method, then the liquid transverse jet in supersonic flow field is taken continuously, obtain the transient images of liquid transverse jet, obtain initial jet boundary point by given gray threshold;
Step S200: once fitting is carried out to the hydrofluidic frontier point in image, obtain the first matched curve, first matched curve follows the example of line successively along jet direction, and be that zone boundary is searched jet boundary and to be fallen apart a little the most concentrated region with circle in got normal direction, and in this region, extract multiple fisrt feature points of jet boundary successively;
Step S300: quadratic fit is carried out to fisrt feature point, obtain the second matched curve, second matched curve follows the example of line successively along jet direction, and be that zone boundary is searched jet boundary and to be fallen apart a little the most concentrated region with circle in got normal direction, and in this region, extract multiple second feature points of jet boundary successively;
Step S400: cubic fit is carried out to described second feature point, obtain the 3rd matched curve, calculate the relative error of described second matched curve and the 3rd matched curve, when described relative error magnitudes is less than 0.1%, using described second feature point as described liquid transverse jet border, otherwise, repeat step S300 ~ step S400, until described relative error magnitudes is less than 0.1%;
Step S500: the pixel in described image is converted into actual physics distance according to described scale, obtains the physical boundary on described liquid transverse jet border.
2. the acquisition methods on liquid transverse jet border according to claim 1, is characterized in that, the frontier point Image Acquisition of described original liquid transverse jet is obtained by the method for given gray threshold, and described gray threshold is 10% of maximum gray scale.
3. the acquisition methods on liquid transverse jet border according to claim 2, is characterized in that, carries out matching obtain according to least square method principle;
Described first time matched curve is
Described second matched curve is
Described 3rd matched curve is
Wherein x is the horizontal ordinate of pixel, and y is the ordinate of pixel, a
nand b
nfor fitting coefficient.
4. the acquisition methods on liquid transverse jet border according to claim 3, it is characterized in that, described step S200 comprises the following steps:
Step S210: get described first time matched curve
upper any point (x
i, y
i), the normal crossing described first matched curve of this point is
And it is crossing with the border of described image;
Step S220: with the initial point of described first time matched curve for starting point, x-axis is positive dirction, with 10 pixel distances for step-length, make the normal of the point in described first matched curve, with this normal and described image border away from the intersection point of jet area for starting point, with any point on this normal for the center of circle, R is radius, is that the pixel number of 255 is designated as S by the gray-scale value dropped in this circle
1, then move 10 pixel distances along this normal, obtain the next one and search the round heart;
Step S230: search the round heart for the center of circle with this next one, radius is R, and the pixel number being 255 by the gray-scale value dropped in this circle is S
2, by that analogy, obtain S
3, S
4s
i, the round heart of searching getting maximum S value corresponding is unique point in this normal direction;
To the more lower (x in described second matched curve
i+1, y
i+1) repeating said steps S110 ~ 130 acquisition unique point, after having moved along described first matched curve, obtain the set of all described unique points as described fisrt feature point.
5. the acquisition methods on liquid transverse jet border according to claim 4, it is characterized in that, described step S300 comprises the following steps:
Step S310: got any point (x in described second matched curve
i, y
i) normal, this normal is
and it is crossing with described image boundary;
Step S320: with the initial point of described first time matched curve for starting point, x-axis is positive dirction, with 10 pixel distances for step-length, make the normal of the point in described second matched curve, with this normal and image boundary away from the intersection point of jet area for starting point, along this normal direction, with on this normal a bit for the center of circle, R is radius, is that the pixel number of 255 is designated as T by the gray-scale value dropped in this circle
1, then move 10 pixel distances along this normal, obtain the next one and search the round heart;
Step S330: search the round heart for the center of circle with this next one, radius is R, is that the pixel number of 255 is designated as T by the gray-scale value dropped in this circle
2, by that analogy, obtain T
3, T
4t
i, the round heart of searching getting maximum T value corresponding is unique point in this normal direction;
To the more lower (x in described second matched curve
i+1, y
i+1) repeat step S310 ~ 330 acquisition unique point, after having moved along described second matched curve, the set obtaining all described unique points is described second feature point.
6. the acquisition methods on liquid transverse jet border according to claim 5, is characterized in that, the relative error of described second matched curve and described 3rd matched curve is
wherein
for the relative error number percent that arbitrary location of pixels is corresponding, η is average error number percent, and n is pixel number.
7. the acquisition methods on the liquid transverse jet border according to any one of claim 1 ~ 6, is characterized in that, described formation method is pulse laser background imaging method.
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