CN111340799B

CN111340799B - Method and system for determining contact stress between tire and rough road surface

Info

Publication number: CN111340799B
Application number: CN202010190938.XA
Authority: CN
Inventors: 陈搏; 王湛; 李伟雄; 张肖宁; 王端宜; 黄志勇; 聂文; 熊春龙; 罗传熙
Original assignee: Guangzhou Xiaoning Institute Of Roadway Engineering Co ltd; South China University of Technology SCUT
Current assignee: Guangzhou Xiaoning Institute Of Roadway Engineering Co ltd; South China University of Technology SCUT
Priority date: 2020-03-18
Filing date: 2020-03-18
Publication date: 2023-03-10
Anticipated expiration: 2040-03-18
Also published as: CN111340799A

Abstract

The invention relates to a method and a system for determining contact stress between a tire and a rough road surface. Acquiring a plurality of film mark images of the contact between the tire and a rough road surface; carrying out numerical processing on each film impression image to obtain a plurality of film impression stress cloud images; extracting contour features and barycentric coordinates of each film impression stress cloud image; carrying out spatial transformation processing and interpolation processing on each film impression stress cloud image to obtain a processed film impression stress cloud image; according to the contour features, the gravity center coordinates and the processed film impression stress cloud images, registering each film impression stress cloud image by adopting a dynamic reference image method to obtain registered film impression stress coordinates; and fusing the film impression images according to the registered film impression stress coordinates to obtain a tire and rough road surface contact stress image. The invention can carry out registration and fusion processing on the multi-specification film impression images, thereby reducing the overall distribution state of the contact stress between the tire and the road surface.

Description

Method and system for determining contact stress between tire and rough road surface

Technical Field

The invention relates to the field of contact stress testing, in particular to a method and a system for determining contact stress between a tire and a rough road surface.

Background

Road traffic safety has always been a social concern and a technical problem in road engineering, and about 70% of wet and slippery accidents in rainy days can be avoided by improving the skid resistance of the road surface. Previous research has focused on tire manufacture, pavement mix design and construction, etc.: the control performance of the automobile is improved by designing tire structures suitable for different environments, and the adhesive force of the tire is increased by changing the characteristics of the tread rubber synthetic material; in the aspect of asphalt pavement structure, grading indexes such as construction depth, friction coefficient and the like are formed mainly by test means of different pavement forms, special linear road sections, meteorological conditions and service time. In the prior art, a sand paving method, a pendulum instrument method, a transverse force coefficient vehicle, a laser construction method and a digital image method show the skid resistance of a road surface only indirectly or singly in a strict sense, and neglect the contact problem in a friction phenomenon. The anti-skid performance of the asphalt pavement is completely the horizontal braking force generated by the joint action of the automobile tire and the pavement structure, mainly comprises retarding force and adhesion force, the adhesion force is generated by the shearing action of a contact surface and is mainly related to the rubber property of the tire, the pavement structure material, the cleanliness degree and the driving speed; the retarding forces are mainly generated by the energy dissipation caused by the contact deformation of the tire on the rough road surface. Therefore, road skid resistance is essentially a contact mechanics problem, and excellent vehicle braking performance depends on the contact characteristics of the tire with the road surface. Road users are increasingly aware that the anti-skid properties of roads are not only of new build-up, but also of their durability during long-term use, and therefore the friction and wear behaviour under contact is of great importance.

Recently, a high-precision flexible film (Fujifilm-Prescale) technology is developed quickly, the thickness is extremely thin, the precision of a microscopic scale can be identified, the defect that the rough structure characteristic of a pavement is difficult to reflect by a traditional pressure sensor method and the like is overcome, the price is low, and the high-precision flexible film has good research and application potentials. The basic principle is that the contact stress value is converted through chemical color reaction, the double-sheet type is mainly characterized in that microcapsules wrapping chemical substances are uniformly coated on the film A, powdery color substances are coated on the film C, and when the capsules are broken, the released reagent can generate color reaction with the color substances. The sensitivity of the microcapsules coated on films with different specifications to contact pressure is different and depends on the size of the microcapsules, the thickness of cell walls, the strength of cell wall materials and the like. At present, the types of films mainly comprise 4LW (effective range 0.05-0.2 MPa), 3LW (effective range 0.2-0.6 MPa), 2LW (effective range 0.5-2.5 MPa) and LW (effective range 2.5-10 MPa). Due to the influence of the material property of chemical substances carried by the pressure film and the limitation of the single-specification range of the pressure film, the application of the pressure film testing technology in contact stress measurement is greatly restricted. At present, in most fields, only a single specification pressure film can be selected to obtain a contact stress value in a specific range, and in the research process of the contact characteristics of an automobile tire and a rough road surface, a plurality of specification films are required to obtain complete contact stress information between the tire and the road surface. However, the truncated stress distribution information is difficult to restore the overall distribution state of the contact stress between the tire and the road surface, and it is necessary to perform fusion processing on the multi-specification film stress results.

Disclosure of Invention

The invention aims to provide a method and a system for determining the contact stress between a tire and a rough road surface, which can perform registration and fusion processing on multi-specification film impression images so as to restore the overall distribution state of the contact stress between the tire and the road surface.

In order to achieve the purpose, the invention provides the following scheme:

a method for determining the contact stress of a tyre with a rough road surface, comprising:

acquiring a plurality of film mark images of a tire in contact with a rough road surface, wherein the film mark images comprise more than three film mark images with different specifications;

carrying out numerical processing on each film impression image to obtain a plurality of film impression stress cloud images;

extracting contour features of the film impression stress cloud images;

extracting the barycentric coordinates of the film impression stress cloud images;

carrying out spatial transformation processing and interpolation processing on each film impression stress cloud image to obtain a processed film impression stress cloud image;

according to the contour features, the gravity center coordinates and the processed film impression stress cloud images, registering the film impression stress cloud images by adopting a dynamic reference image method to obtain registered film impression stress coordinates;

fusing the film impression images according to the registered film impression stress coordinates to obtain a tire and rough road surface contact stress image;

and determining the contact stress of the tire and the rough road surface according to the contact stress image of the tire and the rough road surface.

Optionally, the extracting the contour feature of each film impression stress cloud image specifically includes:

performing binarization processing on the stress data of each film impression stress cloud image to obtain a binarization stress matrix;

and carrying out cyclic contour extraction on the binarization stress matrix to obtain contour characteristics.

Optionally, the extracting the barycentric coordinates of each film impression stress cloud image specifically includes:

carrying out numerical processing according to the film impression stress cloud images to obtain a plurality of stress image matrix data;

adopting a formula according to each stress image matrix data

And

determining barycentric coordinates of the impression area;

wherein,

is the abscissa value of the center of gravity, N is the number of columns of the stress image matrix data in the X-axis direction, X _i Is the sum of each column of data;

is the longitudinal coordinate value of the center of gravity, M is the number of rows of stress image matrix data in the Y-axis direction, Y _j Is the sum of each row of data.

Optionally, the performing spatial transformation processing and interpolation processing on each film impression stress cloud image to obtain a processed film impression stress cloud image specifically includes:

adopting a formula for each film impression stress cloud image

Carrying out spatial transformation processing to obtain a film impression stress cloud image after spatial transformation;

wherein (x) ₀ ,y ₀ ) Initial coordinates of the feature points; (x) ₁ ,y ₁ ) Is the transformed coordinates;

is the rotation angle;

is a translation vector;

adopting a formula for the film impression stress cloud image after the space transformation

And

carrying out interpolation processing to obtain a processed film impression stress cloud image;

wherein, I (A) ₁₁ )、I(A ₂₁ )、I(A ₁₂ )、I(A ₂₂ ) Film print stress cloud image before spatial transformation at A ₁₁ ，A ₁₂ ，A ₂₁ ，A ₂₂ Values at four points; i (B) ₁ ) For the 1 st linear interpolation of the point P to be found in the x direction, I (B) ₂ ) The 2 nd linear interpolation of the point P to be solved in the x direction; and I (P) is linear interpolation in the y direction, namely the value of a point P to be solved of the transformed image.

Optionally, the registering, according to the contour feature, the barycentric coordinate, and the processed film impression stress cloud image, each film impression stress cloud image by using a dynamic reference image method to obtain a registered film impression stress coordinate specifically includes:

the film print images are assumed to contain four film print images of different specifications, which specifically include: 4LW film print image, 3LW film print image, 2LW film print image and LW film print image;

taking the 4LW film impression stress cloud image as a reference image, taking the 3LW film impression stress cloud image as a floating image, translating the gravity center of the 3LW film impression to the position of the 4LW film impression stress cloud image, and obtaining a first gravity center initial registration point and a first impression contour;

selecting the impression contour with the maximum mutual information value according to the first gravity center initial registration point and the surrounding characteristics of the first impression contour to obtain a registration transformation image 3LW-R;

determining the registration transformation coordinates of the 3LW film print image and the 4LW film print image according to the registration transformation image 3LW-R;

taking the registration transformation image 3LW-R as a new reference image, taking the 2LW film impression stress cloud image as a floating image, and translating the gravity center of the 2LW film impression to the position of the 3LW film impression stress cloud image to obtain a second gravity center initial registration point and a second impression contour;

selecting the impression contour with the maximum mutual information value according to the second gravity center initial registration point and the surrounding characteristics of the second impression contour to obtain a registration transformation image 2LW-R;

determining the registration transformation coordinates of the 2LW film print image and the 3LW film print image according to the registration transformation image 2LW-R;

taking the registration transformation image 2LW-R as a new reference image, taking the LW film impression stress cloud image as a floating image, translating the gravity center of the LW film impression to the position of the 2LW film impression stress cloud image, and obtaining a third gravity center initial registration point and a third impression outline;

selecting the impression contour with the maximum mutual information value according to the third centroid initial registration point and the surrounding characteristics of the third impression contour to obtain a registration transformation image LW-R;

determining the registration transformation coordinates of the LW film print image and the 2LW film print image according to the registration transformation image LW-R.

A system for determining the contact stress of a tyre with a rough road surface, comprising:

the film impression image acquisition module is used for acquiring a plurality of film impression images of tires in contact with a rough road surface, and the film impression images comprise more than three film impression images with different specifications;

the first processing module is used for carrying out numerical processing on each film impression image to obtain a plurality of film impression stress cloud images;

the contour feature extraction module is used for extracting contour features of the film impression stress cloud images;

the gravity center coordinate extraction module is used for extracting the gravity center coordinates of each film impression stress cloud image;

the second processing module is used for carrying out spatial transformation processing and interpolation processing on each film impression stress cloud image to obtain a processed film impression stress cloud image;

the registration module is used for registering the film impression stress cloud images by adopting a dynamic reference image method according to the contour features, the gravity center coordinates and the processed film impression stress cloud images to obtain registered film impression stress coordinates;

the fusion module is used for fusing the film impression images according to the registered film impression stress coordinates to obtain a contact stress image of the tire and the rough road surface;

and the contact stress determining module is used for determining the contact stress of the tire and the rough road surface according to the contact stress image of the tire and the rough road surface.

Optionally, the contour feature extraction module specifically includes:

the binaryzation processing unit is used for carrying out binaryzation processing on the stress data of the film impression stress cloud images to obtain a binaryzation stress matrix;

and the contour feature extraction unit is used for performing cyclic contour extraction on the binarization stress matrix to obtain contour features.

Optionally, the barycentric coordinate extraction module specifically includes:

the stress image matrix data determining unit is used for carrying out numerical processing according to each film impression stress cloud image to obtain a plurality of stress image matrix data;

a barycentric coordinate determination unit for employing a formula based on each of the stress image matrix data

And

determining barycentric coordinates of the impression area;

wherein,

is the ordinate value of the center of gravity, M is the number of rows of stress image matrix data in the Y-axis direction, Y _j Is the sum of each row of data.

Optionally, the second processing module specifically includes:

spatial transform processing sheetAn element for applying a formula to each of said film print stress cloud images

wherein (x) ₀ ,y ₀ ) Initial coordinates of the feature points; (x) ₁ ,y ₁ ) The transformed coordinates;

is the rotation angle;

is a translation vector;

an interpolation processing unit for applying a formula to the film impression stress cloud image after the spatial transformation

And

Optionally, the registration module specifically includes:

the image setting unit is used for setting that the film impression image comprises four film impression images with different specifications, and specifically comprises: 4LW film print image, 3LW film print image, 2LW film print image and LW film print image;

a first center-of-gravity initial registration point/first footprint contour determination unit, configured to take the 4LW film footprint stress cloud image as a reference image, the 3LW film footprint stress cloud image as a floating image, and translate the center of gravity of the 3LW film footprint to the position of the 4LW film footprint stress cloud image, resulting in a first center-of-gravity initial registration point and a first footprint contour;

a first registration transformation image determining unit, configured to select a footprint contour with a maximum mutual information value according to the first barycentric initial registration point and the enclosing feature of the first footprint contour, so as to obtain a registration transformation image 3LW-R;

a first registration transformation coordinate determination unit for determining registration transformation coordinates of the 3LW film print image and the 4LW film print image according to the registration transformation image 3LW-R;

a second center-of-gravity initial registration point/second footprint contour determination unit for translating the center of gravity of said 2LW film footprint to the position of said 3LW film footprint stress cloud image, with said registration transformed image 3LW-R as a new reference image and said 2LW film footprint stress cloud image as a floating image, resulting in a second center-of-gravity initial registration point and a second footprint contour;

a second registration transformation image determining unit, configured to select the impression contour with the largest mutual information value according to the second center-of-gravity initial registration point and the enclosing feature of the second impression contour, so as to obtain a registration transformation image 2LW-R;

a second registration transformation coordinate determination unit for determining the registration transformation coordinates of the 2LW film print image and the 3LW film print image according to the registration transformation image 2LW-R;

a third centroid initial registration point/second footprint contour determination unit for translating the centroid of the LW film footprint to the position of the 2LW film footprint stress cloud image with the registration transformation image 2LW-R as a new reference image and the LW film footprint stress cloud image as a floating image, resulting in a third centroid initial registration point and a third footprint contour;

a third registration transformation image determining unit, configured to select the impression contour with the maximum mutual information value according to the third centroid initial registration point and the enclosing feature of the third impression contour, so as to obtain a registration transformation image LW-R;

a third registration transformation coordinate determination unit for determining the registration transformation coordinates of the LW film print image and the 2LW film print image according to the registration transformation image LW-R.

According to the specific embodiment provided by the invention, the invention discloses the following technical effects:

the invention provides a method and a system for determining contact stress between a tire and a rough road surface. Acquiring a plurality of film mark images of the contact between the tire and a rough road surface; carrying out numerical processing on each film impression image to obtain a plurality of film impression stress cloud images; extracting contour features and barycentric coordinates of each film impression stress cloud image; in the registration process, spatial transformation processing and interpolation processing are required to be carried out on each film impression stress cloud image to obtain a processed film impression stress cloud image; according to the contour features, the gravity center coordinates and the processed film impression stress cloud images, registering each film impression stress cloud image by adopting a dynamic reference image method to obtain registered film impression stress coordinates; and fusing the film impression images according to the registered film impression stress coordinates to obtain a contact stress image of the tire and the rough road surface.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.

FIG. 1 is a flow chart of a method for determining the contact stress between a tire and a rough road surface according to the present invention;

FIG. 2 is a schematic representation of a film print image of the present invention;

FIG. 3 is a schematic view of an impression stress cloud image of films of various specifications according to the present invention;

FIG. 4 is a schematic diagram of the fusion process of the present invention;

FIG. 5 is a fused tire to rough road contact stress image of the present invention;

FIG. 6 is a view showing a configuration of a system for determining the contact stress between a tire and a rough road surface according to the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.

In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.

FIG. 1 is a flow chart of the method for determining the contact stress between a tire and a rough road surface according to the present invention. As shown in fig. 1, a method for determining the contact stress between a tire and a rough road surface includes:

step 101: a plurality of film print images of tires in contact with rough road surfaces are acquired, wherein the film print images comprise more than three film print images with different specifications.

As a preferred embodiment, the acquisition of a plurality of film print images of a tire in contact with a rough road surface comprises the steps of:

(1) Adopt more representative passenger train to move towards decorative pattern all steel silk radial tire, specific parameter is: the tire specification is 7.00R16, the rim specification is 5.5F, the level is 12, the rated load is 12.15kN, and the standard tire pressure is 670kPa. According to the information of the size of the tested tire, the tire pressure, the load applied to a single wheel and the like, the outline size of the effective contact area of the tire is determined to be about 270mm and 220mm.

(2) Four types of pressure films are selected, and the main types are as follows: 4LW (0.05-0.2 MPa), 3LW (0.2-0.6 MPa), 2LW (0.5-2.5 MPa) and LW (2.5-10 MPa). The film is cut correctly to the specified size (usually the color development A film is in black bag and is transparent; the color development C film is in blue bag and is milky).

(3) The rough surfaces of each film are mutually opposite to avoid mutual friction and water contact as much as possible so as to prevent the loss of the film microcapsules, and the films are placed between the tire and the road surface.

(4) Tire loads were applied and either held at static pressure for 2 minutes or instantaneous pressure for 5 seconds. Film print image fig. 2 is a schematic representation of a film print image of the present invention, fig. 2. The specification of the film print image in fig. 2 is 4LW, 3LW, 2LW, and LW in this order from left to right.

Step 102: and carrying out numerical processing on each film impression image to obtain a plurality of film impression stress cloud images.

Taking out the color development C film, standing for 60min, and adopting Perfection after the color density is gradually stabilized ^TM A scanner dedicated to a V300Photo CCD (Epson corporation, japan) and a color correction plate read a characteristic pattern of a contact stress distribution with an image resolution of 0.125 (200 dpi), and then numerically analyzed by a supporting FPD-8010E pressure image digital measurement analysis system V2.0. The conversion process can be defined as the following function:

f(x,y)＝ξ·ρ(x,y)

in the formula: f (x, y) represents a single point stress value at the planar position (x, y), which may also be referred to as a pressure value, MPa; ρ (x, y) represents the color density at the planar position (x, y); ξ represents a scaling function between the pressure value and the color density.

Regarding the xi conversion function, the FUJI product mainly defines the temperature and the humidity, and simultaneously provides a calibration curve of the contact stress and the color concentration under the action of dynamic load and static load, and can be selected according to the test temperature and the test humidity.

The converted stress information is processed, quantized and stored in a two-dimensional matrix, which is further expressed as a mathematical expression of a compact matrix type discrete function as shown in the following formula:

in the formula: f (X, Y) is the total contact pressure value, N; f (M, N) is the mean value of the contact stress of the single-point contact area, MPa.

Four film footprint stress cloud images of 4LW, 3LW, 2LW, LW were output using the MATLAB matrix test, as shown in fig. 3. Fig. 3 is a schematic diagram of film footprint stress cloud images of various specifications of the present invention, wherein a is a 4LW film footprint stress cloud image, b is a 3LW film footprint stress cloud image, c is a 2LW film footprint stress cloud image, and d is an LW film footprint stress cloud image.

Step 103: extracting the contour features of the film impression stress cloud images, which specifically comprises the following steps:

and carrying out binarization processing on the stress data of each film impression stress cloud image to obtain a binarization stress matrix.

The tire/road contact patch can clearly show the patch shape of the tire pattern. The amount of information contained in different size films varies due to differences in sensitivity of the microcapsules. The sensitivity of the micro-range 4LW film is the highest, and the displayed impression outline characteristics are the most complete. With decreasing sensitivity of microcapsules, contact mark contour information is gradually reduced for 3LW, 2LW, LW specification films, on the one hand, the area enclosed by the contour becomes smaller, and on the other hand, the integrity of the contour becomes worse, but the low sensitivity mark contour is inside the high sensitivity film mark contour at all, so the film mark contour feature can be used as a constraint target feature, i.e. the high sensitivity mark contour should enclose the low sensitivity mark.

Firstly, the stress data is subjected to binarization processing, namely, nonzero stress values are uniformly converted into 1, and zero value areas are uniformly expressed by 0. And then carrying out cyclic contour extraction on the stress binarization matrix, starting scanning from the first row, when encountering non-zero values, respectively reserving the first 1 and the last 1, and carrying out zero-returning processing on the middle 1 value, thereby extracting contour features in such a way as shown in the following formula:

step 104: extracting barycentric coordinates of each film impression stress cloud image, and specifically comprising the following steps:

and carrying out numerical processing according to each film impression stress cloud image to obtain a plurality of stress image matrix data.

Adopting a formula according to each stress image matrix data

And

barycentric coordinates of the impression area are determined.

Wherein,

is the abscissa value of the center of gravity, and N is the number of columns of stress image matrix data in the X-axis direction, X _i Is the sum of each column of data;

In the process of manually scanning the film, the deviation of the spatial position of the scanned impression image is easy to be overlarge, and the single contour feature registration calculation amount is overlarge due to the translation and rotation in a larger space. The initial feature matching is carried out by combining the numerical features of the stress image matrix data, so that the registration calculation amount can be reduced, and the operation speed can be increased. The gravity center coordinates of the impression area are calculated according to the stress image matrix data and are used as initial registration point positions.

Step 105: and carrying out spatial transformation processing and interpolation processing on each film impression stress cloud image to obtain a processed film impression stress cloud image. The steps are performed in the film impression stress cloud image registration process of each step, and specifically comprise the following steps:

step 1051: adopting a formula for each film impression stress cloud image

And carrying out spatial transformation processing of a corresponding transformation coordinate system to obtain a film impression stress cloud image after spatial transformation.

is the rotation angle;

is a translation vector.

In order to truly restore the test result, the size consistency and the numerical result uniformity of each film impression stress cloud image are kept in the spatial transformation process. The method mainly adopts a rigid body transformation function to carry out space transformation, and is mainly characterized in that the characteristic size of an image is kept unchanged before and after transformation.

Step 1052: adopting a formula for the film impression stress cloud image after the space transformation

And

and carrying out interpolation processing to obtain a processed film impression stress cloud image.

Wherein, I (A) ₁₁ )、I(A ₂₁ )、I(A ₁₂ )、I(A ₂₂ ) Respectively for pre-spatial-transform film printsStress cloud image at A ₁₁ ，A ₁₂ ，A ₂₁ ，A ₂₂ Values at four points; i (B1) is the 1 st linear interpolation of the point P to be found in the x direction, I (B) ₂ ) The 2 nd linear interpolation of the point P to be solved in the x direction; and I (P) is linear interpolation in the y direction, namely the value of a point P to be solved of the transformed image.

In the process of registering two film images, when the mutual information measurement value of the two images is the maximum, the registration effect is the best, so that in the process of continuous and cyclic attempts, the registration is finished by setting the maximum mutual information value of a limited number of registration steps.

After the film impression stress cloud image is subjected to spatial rotation, the position of a new pixel point is changed, the coordinate of the pixel point is not necessarily an integer, and interpolation conversion needs to be carried out on the new pixel point at the moment in order to ensure undistorted image. The bilinear interpolation method is the most widely used interpolation method, and the basic principle is as follows: four adjacent points (A) according to the point P to be solved along the x and y directions ₁₁ ，A ₁₂ ，A ₂₁ ，A ₂₂ ) The pixel value of (2) is linearly interpolated, the calculation effect is equivalent to that of a cubic convolution interpolation method, and the calculation efficiency is high. The present invention employs the above interpolation method.

Step 106: according to the contour feature, the barycentric coordinate and the processed film impression stress cloud image, registering each film impression stress cloud image by adopting a dynamic reference image method to obtain a registered film impression stress coordinate, which specifically comprises the following steps:

step 1060: the film impression image is designed to contain four film impression images with different specifications, and the method specifically comprises the following steps: 4LW film print image, 3LW film print image, 2LW film print image and LW film print image.

Step 1061: and taking the 4LW film impression stress cloud image as a reference image, taking the 3LW film impression stress cloud image as a floating image, translating the gravity center of the 3LW film impression to the position of the 4LW film impression stress cloud image, and obtaining a first gravity center initial registration point and a first impression contour.

Step 1062: and selecting the impression contour with the maximum mutual information value according to the first gravity center initial registration point and the surrounding characteristic of the first impression contour to obtain a registration transformation image 3LW-R.

Step 1063: determining the registration transformation coordinates of the 3LW film print image and the 4LW film print image from the registration transformation image 3LW-R.

Step 1064: and taking the registration transformation image 3LW-R as a new reference image, taking the 2LW film impression stress cloud image as a floating image, and translating the gravity center of the 2LW film impression to the position of the 3LW film impression stress cloud image to obtain a second gravity initial registration point and a second impression outline.

Step 1065: and selecting the impression contour with the maximum mutual information value according to the second gravity center initial registration point and the surrounding characteristics of the second impression contour to obtain a registration transformation image 2LW-R.

Step 1066: determining the registration transformation coordinates of the 2LW film print image and the 3LW film print image from the registration transformation image 2LW-R.

Step 1067: and taking the registration transformation image 2LW-R as a new reference image, taking the LW film impression stress cloud image as a floating image, and translating the gravity center of the LW film impression to the position of the 2LW film impression stress cloud image to obtain a third gravity center initial registration point and a third impression outline.

Step 1068: and selecting the impression contour with the maximum mutual information value according to the third centroid initial registration point and the surrounding characteristics of the third impression contour to obtain a registration transformation image LW-R.

Step 1069: determining the registration transformation coordinates of the LW film print image and the 2LW film print image according to the registration transformation image LW-R.

For the registration processing of multi-specification film impression images, a fixed reference image method is adopted in the traditional method, namely before image registration, an image is required to be selected as a reference image, other images are used as floating images to be respectively registered with the characteristics of the floating images, when the image sequence is small or the image information difference is not large, a fixed reference image is usually selected, and the other images are registered with the reference image one by one. The registration steps are as follows:

(1) And converting the original four-specification film imprint numerical value into a stress cloud chart, and rejecting numerical value information outside a small range.

(2) And selecting a reference image, and aligning the initial point according to the gravity center position of the impression image, wherein the contour feature is used as a registration constraint.

(3) The multi-modal functionality of the evolutionary algorithm optimizer is used and a rigid transformation function is selected.

(4) The increase factor of the search radius is set to be 1.01, and the minimum value of the search radius is set to be 1.5 multiplied by 10 ^-6 The initial value of the search radius is 6.25X 10 ^-3 And the number of iterations of the optimizer is 200.

(5) And (4) converting the stress value in the image conversion process by adopting a bilinear interpolation method.

(6) And selecting a mutual information function as a measurement criterion of the image similarity, respectively registering the floating image to the reference image pairwise, calculating a mutual information result after registration, and taking an optimal value as the basis of the next iterative calculation.

(7) And changing initial registration parameters of the optimizer, and improving the image registration precision.

(8) And determining the optimal registration precision according to the calculated similarity measurement criterion, and finishing registration.

However, for film print images containing different sizes (here, more than three different sizes), the print characteristic information carried by the film print images gradually decreases as the sensitivity of the film microcapsules decreases, due to the greater amount of information carried per image. In the four-specification film, the difference of the characteristics of the first specification film image and the fourth specification film image is the largest, and the first specification film image and the fourth specification film image are directly registered to easily generate larger errors; and the sensitivity of the microcapsules of the adjacent specification films is closer, and the information difference between images is smaller. Therefore, in order to solve the problem of large skip-level error in the multi-specification film Registration process, a conventional Registration algorithm needs to be further optimized, different reference images are adopted, that is, an optimization algorithm that a dynamic reference image replaces a single reference image is adopted, and for convenience of analysis, the optimization algorithm is defined as Dynamic Reference Image Registration (DRIR).

The main operational steps of the DRIR optimization algorithm are as follows:

firstly, loading 4 specifications of pressure film matrix data, specifically comprising: 4LW film print image, 3LW film print image, 2LW film print image and LW film print image.

And taking the 4LW film impression stress cloud image as a reference image, taking the 3LW film impression stress cloud image as a floating image, taking the coordinates of the centers of gravity of the two images as an initial registration point, namely translating the center of gravity of the 3LW film impression to the position of the center of gravity of the 4LW film impression stress cloud image, and then taking the impression outlines of the two films as matching characteristics, wherein when the 3LW impression outline is completely surrounded by the impression outline of the 4LW film, the mutual information measurement value of the two images is the maximum at the moment, the effect of fine registration is achieved, and the registration transformation image 3LW-R is obtained.

And taking the registration transformation image 3LW-R as a new reference image, taking the 2LW film impression stress cloud image as a floating image, and selecting the fine registration processing of the 2LW film impression stress cloud image when the mutual information value is maximum according to the initial registration point of the gravity centers of the two films and the surrounding characteristics of the impression contour to obtain the registration transformation image 2LW-R.

And taking the registration transformation image 2LW-R as a new reference image, taking the LW film impression stress cloud image as a floating image, and selecting the fine registration processing of the LW film impression stress cloud image when the mutual information value is maximum according to the initial registration point of the gravity centers of the two films and the surrounding characteristics of the impression outline to obtain the registration transformation image LW-R.

According to the pairwise registration steps, the registration transformation coordinates of the 3LW film and the 4LW film can be obtained

is the rotation angle;

is a translation vector. Similarly, registration transformation coordinates of 2LW and 3LW-R can be obtained; likewise, the registration transformation coordinates of LW and 2LW-R can be obtained.

For different types of images, even if the images are the same registration algorithm, the registration effect is different; in image processing in different fields, the evaluation methods vary depending on the portion of interest to the user. Registration effectiveness evaluation is performed from mainly two angles, based on the data characteristics of film prints: 1. judging whether the registration is successful or not by adopting the mutual information measure between the two images from the angle of the image characteristics; 2. and evaluating the registration and fusion effects of the film from the view point of the contact stress distribution result.

Mutual information

Mutual information is a concept in information theory, and is generally used to describe statistical correlation between two systems, or how much information is contained in one system in another system. Mutual information measure judges whether the registration is successful by comparing the mutual information between the two images, which can be defined as:

S _MI (X,Y)＝H(X)+H(Y)-H(X,Y)

h (X), H (Y) are the entropy of images X, Y, respectively, and H (X, Y) are their joint entropy. In general, the entropy of a K-dimensional continuous random variable Z, Z = (Z1, Z2, \8230;, zn) is defined as:

H(Z)＝-∫p(z)logp(z)dz＝-∫…∫p(z ₁ ,…,z _n )logp(z ₁ ,…,z _n )dz ₁ ,…,z _n

in image registration based on mutual information, pixel values are regarded as samples of a certain continuous random variable, the discrete sampling values are used for estimating the probability densities p (Xi) and p (Yi) of a single image X and Y and the joint probability density p (Xi, yi) of two images, and then the mutual information of the images is obtained, so that the calculation formula of the mutual information can be rewritten as follows:

in the formula, N represents the number of pixels of the images X and Y, and it is assumed here that the number of pixels of both images is N by default. Xi, yi represent the gray scale values of the ith pixel of the images X, Y, respectively. It can be seen that the better the registration of the two images, the greater the correlation between them, the greater the mutual information value; conversely, the more mismatched the images, the smaller the mutual information value.

Where p (Xi), p (Yi), is also called the edge probability density, can be determined from the joint probability density of X and Y:

for the estimation of the joint probability density p (Xi, yi), a histogram method is used for calculation. Let h (Xi, yi) represent the two-dimensional joint histogram of the two images, the estimate of its joint probability density p (Xi, yi) is:

mutual information is used as similarity measurement of image registration, no assumption needs to be made on the correlation of image gray space, no limitation needs to be made on image content, and preprocessing such as image segmentation is not needed. When the two images reach the best registration, the mutual information of the two images takes the maximum value, so the method is widely applied to multi-modal medical image registration. Mutual information can be used for registration of images of any different modalities, and a good effect can be achieved even if a part of data information is lost.

(II) evaluation of contact mechanics

The final aim of the registration of different specification film images is to perform stress combination so as to break through the limitation of the single specification film range. Therefore, it is necessary to evaluate the fusion effect after film registration. And respectively adopting the effective contact area ratio and the pressure ratio index after the film fusion to evaluate and analyze errors. It is basically defined as follows:

effective contact area ratio:

pressure ratio:

in the formula, A ₀ Is the actual contact area (mm) of tyre/road ² ) 4LW film imprints with high sensitivity are generally selected for calculation; a. The ₁ Effective contact area (mm) for multi-specification film after registration and fusion ² )；F ₀ Respectively intercepting the effective range pressure interval of each specification film for the actual contact pressure value (N) of the tire/road to perform integral calculation; f ₁ Registering and fusing the pressure value (N) for the multi-specification films. f (x, y) is the single-point stress value (MPa) of the effective contact area of the original films with various specifications; f' (x, y) is the single-point stress value (MPa) of the effective contact area after registration and fusion of the multi-specification films.

And comparing the mutual information measurement values of the two images before and after the registration algorithm is optimized, and calculating the mutual information total value of the multi-specification film in the registration process. The time spent in different algorithms is recorded at the same time, and the calculation results are shown in the following table.

TABLE 1 mutual image information evaluation for different algorithms

Different reference image algorithm	Mutual information value	Time spent(s)
			4LW	0.8094	49.271
3LW	1.0609	45.496
			2LW	0.9396	46.035
LW	0.6013	45.107
			DRIR	1.2104	48.215

The similarity measure index and algorithm time spending calculation result analysis based on the image field can be obtained as follows:

(1) The registration mutual information values under the optimization algorithm of the dynamic reference images are all larger than the registration mutual information value under the single reference image, and the image registration effect of the optimization algorithm is better.

(2) The time cost of the optimization algorithm is not greatly different from that of a single reference image, so that the change of the reference image does not increase the calculation time of a program, and the optimization registration scheme is really feasible.

The film fused effective contact area ratio and pressure ratio indices were further calculated and the statistical results are shown in table 2.

TABLE 2 stress index evaluation of different registration algorithms

The analysis of the film stress distribution results after image registration and fusion can be used as follows:

(1) The effective contact area ratio of the DRIR optimization algorithm is 100%, and effective contact area information after multi-specification film image registration and fusion is not lost.

(2) The overall contact pressure ratio for the DRIR optimization algorithm was 97.29%, which is substantially equivalent to the registration pressure ratio result for the 2LW film as the reference image, and higher than the other registration schemes. Considering that interpolation processing of the image in the rotation and translation transformation processes can also cause the loss of partial numerical information, under the effective guarantee rate of 95%, the loss amount of stress value information of the DRIR algorithm is considered to be less, and the registration and fusion results are stable and reliable. The mutual information value and the stress distribution index of the image similarity measure are integrated, the registration and fusion of the multi-specification film images can be realized by adopting the DRIR optimization algorithm of the dynamic registration image, and the method has good operation speed and registration precision and optimal performance.

Step 107: and fusing the film impression images according to the registered film impression stress coordinates to obtain a tire and rough road surface contact stress image.

The final purpose of registering film impression images of different specifications is to combine film data of different ranges into a complete stress distribution, thereby breaking through the limitation of the original single specification film range. The fusion of different range film data is not a simple matrix superposition relationship. According to the effective range of the four-specification film, the numerical results of the effective range are respectively intercepted, and the parts exceeding the range are all displayed as uniform results on the film image, and the method specifically comprises the following steps: the effective range of the 4LW film is 0.05-0.2MPa, and the maximum value displayed by the film is 0.25MPa; the effective range of the 3LW film is 0.2-0.6MPa, and the maximum value displayed by the film is 0.637MPa; the effective range of the 2LW film is 0.5-2.5MPa, and the maximum value displayed by the film is 3.06MPa; the effective range of the LW film is 2.5-10MPa, and the maximum value displayed by the film is 12.75MPa. And intercepting effective range data of each film, wherein the range of adjacent films has an overlapping part, and the small-range film with high sensitivity is taken as a main part. The specific interception is as follows: the [0.05,0.2] MPa interval of the 4LW film, the (0.2, 0.6] MPa interval of the 3LW film, the (0.6, 2.5] MPa interval of the 2LW film and the (2.5, 12.75) MPa interval of the LW film, as shown in the figure 4, the figure 4 is a fusion schematic diagram of the invention.

The fusion algorithm is performed after the registration stage is completed, and the main steps are as follows:

step1: finding out the data position of 4LW specification film greater than 0.2MPa by line-by-line search, and recording as (x) ₁ ，y ₁ )。

Step2: line-by-line search for 3LW film correspondence (x) ₁ Y 1) the numerical result of the location and replacing the 4LW gauge film value at that location, the first graph, denoted I, to achieve registration merging ₁ 。

Step3: searching line by line to find I ₁ Is greater than 0.6MPa, is noted as (x) ₂ ，y ₂ )。

Step4: searching line by line to find the correspondence (x) of 2LW film ₂ ，y ₂ ) Numerical result of position and substitution of I in that position ₁ Numerical value, second graph for realizing registration and combination, marked as I ₂ 。

Step5: searching line by line to find I ₂ Is greater than 2.5MPa, is noted as (x) ₃ ，y ₃ )。

Step6: line-by-line search for LW-specification film correspondence (x) ₃ ，y ₃ ) Numerical result of a position and substitution of I in that position ₂ Numerical values, the final matrix for achieving registration merging, denoted as I ₃ 。

Step7: after the algorithm is finished, matrix data and images are output, as shown in fig. 5, fig. 5 is an image of the contact stress between the tire and the rough road surface after the fusion of the invention.

Step 108: and determining the contact stress of the tire and the rough road according to the contact stress image of the tire and the rough road.

The method for determining the contact stress between the tire and the rough road surface adopts a film impression image registration and fusion optimization algorithm, and provides a new method with high measurement precision, simple operation and strong adaptability for testing the contact stress between the tire and the actual road surface. Compared with other sensors, the pressure film is low in price, high in testing precision and stable in performance, stress distribution under real meshing contact of a tire and a road surface can be accurately collected by matching with the algorithm, the interaction state of the tire/road can be objectively reflected, a new thought is provided for evaluation and prediction of the anti-skid performance of the road surface, and necessary basic data support is provided for wear-resistant tire development, road surface wearing layer design and vehicle-road coupling simulation.

The invention also provides a system for determining the contact stress of the tire and the rough road. As shown in fig. 6, a system for determining the contact stress of a tire with a rough road surface. The method comprises the following steps:

a film impression image collecting module 201, configured to collect a plurality of film impression images of tires in contact with a rough road surface, where the film impression images include more than three film impression images with different specifications;

a first processing module 202, configured to perform a numerical processing on each film impression image to obtain a plurality of film impression stress cloud images;

a contour feature extraction module 203, configured to extract contour features of each film impression stress cloud image;

a barycentric coordinate extraction module 204, configured to extract barycentric coordinates of each of the film impression stress cloud images;

the second processing module 205 is configured to perform spatial transformation processing and interpolation processing on each film impression stress cloud image to obtain a processed film impression stress cloud image;

a registration module 206, configured to register each film impression stress cloud image by using a dynamic reference image method according to the contour feature, the barycentric coordinate, and the processed film impression stress cloud image, so as to obtain a registered film impression stress coordinate;

a fusion module 207 for fusing each film impression image according to the registered film impression stress coordinate to obtain a tire and rough road surface contact stress image;

and a contact stress determining module 208 for determining the contact stress of the tire and the rough road surface according to the contact stress image of the tire and the rough road surface.

The contour feature extraction module 203 specifically includes:

and the binarization processing unit is used for carrying out binarization processing on the stress data of each film impression stress cloud image to obtain a binarization stress matrix.

The barycentric coordinate extraction module 204 specifically includes:

and the stress image matrix data determining unit is used for carrying out numerical processing according to each film impression stress cloud image to obtain a plurality of stress image matrix data.

A barycentric coordinate determination unit for employing a formula according to each of the stress image matrix data

And

the barycentric coordinates of the footprint area are determined.

Wherein,

The second processing module 205 specifically includes:

a spatial transform processing unit for applying a formula to each film impression stress cloud image

And carrying out spatial transformation processing to obtain a film impression stress cloud image after spatial transformation.

is the rotation angle;

is a translation vector.

An interpolation processing unit for applying a formula to the film footprint stress cloud image after the spatial transformation

And

The registration module 206 specifically includes:

a first center-of-gravity initial registration point/first impression contour determination unit, configured to take the 4LW film impression stress cloud image as a reference image, take the 3LW film impression stress cloud image as a floating image, and translate the center of gravity of the 3LW film impression to the position of the 4LW film impression stress cloud image, so as to obtain a first center-of-gravity initial registration point and a first impression contour;

a first registration transformation image determining unit, configured to select the impression contour with the maximum mutual information value according to the first gravity center initial registration point and the enclosing feature of the first impression contour, so as to obtain a registration transformation image 3LW-R;

a second registration transformation image determining unit, configured to select the impression contour with the maximum mutual information value according to the second center-of-gravity initial registration point and the enclosing feature of the second impression contour, so as to obtain a registration transformation image 2LW-R;

In the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.

The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the foregoing, the description is not to be taken in a limiting sense.

Claims

1. A method for determining the contact stress between a tyre and a rough road, comprising:

extracting the contour characteristics of the film impression stress cloud images;

extracting barycentric coordinates of each film impression stress cloud image, and specifically comprising the following steps:

performing numerical processing according to the film impression stress cloud images to obtain a plurality of stress image matrix data;

adopting a formula according to each stress image matrix data

And

determining barycentric coordinates of the impression area;

wherein,

is the longitudinal coordinate value of the center of gravity, M is the number of rows of stress image matrix data in the Y-axis direction, Y _j Is the sum of each row of data;

according to the contour features, the barycentric coordinates and the processed film impression stress cloud images, registering the film impression stress cloud images by adopting a dynamic reference image method to obtain registered film impression stress coordinates, which specifically comprises the following steps:

the film impression image is designed to contain four film impression images with different specifications, and the method specifically comprises the following steps: 4LW film print image, 3LW film print image, 2LW film print image and LW film print image;

taking the 4LW film impression image as a reference image and the 3LW film impression image as a floating image, and translating the gravity center of the 3LW film impression image to the position of the 4LW film impression image to obtain a first gravity center initial registration point and a first impression outline;

according to the first gravity center initial registration point and the surrounding characteristics of the first impression contour, selecting the impression contour with the maximum mutual information value to obtain a registration transformation image 3LW-R;

translating the center of gravity of the 2LW film print image to the position of the 3LW film print image with the registration transformation image 3LW-R as a new reference image and the 2LW film print image as a floating image, resulting in a second center of gravity initial registration point and a second print contour;

taking the registration transformation image 2LW-R as a new reference image, taking the LW film impression image as a floating image, and translating the gravity center of the LW film impression image to the position of the 2LW film impression image to obtain a third centroid initial registration point and a third impression outline;

determining registration transformation coordinates of the LW film print image and the 2LW film print image according to the registration transformation image LW-R;

and determining the contact stress of the tire and the rough road according to the contact stress image of the tire and the rough road.

2. The method for determining the contact stress between the tire and the rough road surface according to claim 1, wherein the extracting the contour features of each film footprint stress cloud image specifically comprises:

and carrying out cyclic contour extraction on the binary stress matrix to obtain contour features.

3. The method for determining the contact stress between the tire and the rough road surface according to claim 1, wherein the performing spatial transformation processing and interpolation processing on each film footprint stress cloud image to obtain a processed film footprint stress cloud image specifically comprises:

applying a formula to each film impression stress cloud image

wherein (x) ₀ ,y ₀ ) Initial coordinates of the characteristic points are obtained; (x) ₁ ,y ₁ ) Is the transformed coordinates;

is the rotation angle;

is a translation vector;

And

wherein, I (A) ₁₁ )、I(A ₂₁ )、I(A ₁₂ )、I(A ₂₂ ) Film print stress cloud image before spatial transformation at A ₁₁ ，A ₁₂ ，A ₂₁ ，A ₂₂ Values at four points; i (B) ₁ ) For the 1 st linear interpolation of the point P to be found in the x direction, I (B) ₂ ) For the point P to be solved in the x direction2 nd linear interpolation; and I (P) is linear interpolation in the y direction, namely the value of a point P to be solved of the transformed image.

4. A system for determining the contact stress of a tyre with a rough road surface, comprising:

the film impression image acquisition module is used for acquiring a plurality of film impression images of the tires in contact with the rough road surface, and the film impression images comprise more than three film impression images with different specifications;

the barycentric coordinate extraction module is used for extracting barycentric coordinates of each film impression stress cloud image, and specifically comprises the following steps:

And

determining barycentric coordinates of the impression area;

wherein,

as ordinate values of the center of gravity, M is the stress image moment in the Y-axis directionNumber of lines of matrix data, y _j Is the sum of each row of data;

a registration module, configured to register each film impression stress cloud image by using a dynamic reference image method according to the contour feature, the barycentric coordinate, and the processed film impression stress cloud image, so as to obtain a registered film impression stress coordinate, which specifically includes:

an image setting unit, configured to set that the film print images include four film print images with different specifications, specifically including: 4LW film print image, 3LW film print image, 2LW film print image and LW film print image;

a first center-of-gravity initial registration point/first impression contour determination unit for translating the center of gravity of the 3LW film impression image to the position of the 4LW film impression image with the 4LW film impression image as a reference image and the 3LW film impression image as a floating image, resulting in a first center-of-gravity initial registration point and a first impression contour;

a second centroid initial registration point/second footprint contour determination unit for translating the centroid of said 2LW film footprint image to the position of said 3LW film footprint image with said registration transformed image 3LW-R as a new reference image, said 2LW film footprint image as a floating image, resulting in a second centroid initial registration point and a second footprint contour;

a third centroid initial registration point/second footprint contour determination unit for translating the centroid of said LW film footprint image to the position of said 2LW film footprint image with said registration transformation image 2LW-R as a new reference image, said LW film footprint image as a floating image, resulting in a third centroid initial registration point and a third footprint contour;

a third registration transformation coordinate determination unit for determining the registration transformation coordinate of the LW film mark image and the 2LW film mark image according to the registration transformation image LW-R;

5. The system for determining contact stress between a tire and a rough road according to claim 4, wherein the contour feature extraction module specifically comprises:

a binarization processing unit, configured to perform binarization processing on the stress data of each film impression stress cloud image to obtain a binarization stress matrix;

6. The system for determining contact stress between a tire and a rough road according to claim 4, wherein the second processing module comprises:

is the rotation angle;

is a translation vector;

And

wherein, I (A) ₁₁ )、I(A ₂₁ )、I(A ₁₂ )、I(A ₂₂ ) Film print stress cloud image before spatial transformation at A ₁₁ ，A ₁₂ ，A ₂₁ ，A ₂₂ Values at four points; i (B) ₁ ) For the 1 st linear interpolation of the point P to be found in the x direction, I (B) ₂ ) For the 2 nd line of the point P to be solved in the x directionPerforming linear interpolation; and I (P) is linear interpolation in the y direction, namely the value of a point P to be solved of the transformed image.