Reaction force cone profile measurement method, device, computer equipment and system

Abstract

The present application relates to a reaction force cone morphology measurement method, device, computer equipment and system. The method comprises: obtaining the three-dimensional point data corresponding to each cross section of the reaction force cone, and generating a coordinate matrix corresponding to the cross section; for each of the coordinate matrices, obtaining a first weight coefficient, a first product between the coordinate matrix and the ellipse fitting parameters, and a second weight coefficient, a second product between the coordinate matrix and the ellipse fitting parameters, and obtaining target ellipse fitting parameters according to the L1 norm of the first product and the L2 norm of the second product, and determining the cross-sectional radius of the cross section corresponding to the coordinate matrix based on the target ellipse fitting parameters; obtaining the radius of the reaction force cone according to the cross-sectional radius of each cross section, and outputting the three-dimensional morphology of the reaction force cone based on the radius of the reaction force cone. The present application can improve the accuracy and precision of the measurement results and broaden the scope of application.

Description

Technical Field

[0001] The present application relates to the field of measurement technology, and in particular to a reaction force cone profile measurement method, device, computer equipment and system. Background Art

[0002] In concealed cable projects, quality problems with the reaction cone of high-voltage cables have led to losses and harm. There are many factors involved in the defect failure of the reaction cone of high-voltage cables. A large amount of fault analysis experience shows that cable failures caused by abnormal surface dimensions of cable joints are relatively common. In existing electrical engineering, there is no electronic record of the surface state of the reaction cone of high-voltage cables. It is necessary to use manual touch experience to determine the three-dimensional morphological information such as the smoothness and size of the surface of the cable reaction cone. Therefore, it is difficult to form a consistent evaluation standard for the quality of the cable reaction cone, which is not conducive to the overall project quality control and equipment maintenance. Therefore, collecting the three-dimensional point cloud of the cable reaction cone surface, analyzing the three-dimensional size information of the key cross-section and focusing on monitoring during the construction process are of great significance to the process control and long-term operation, fault analysis and improvement of cable construction.

[0003] At present, traditional technology can calculate the axis direction and position of the measured cylinder based on any set of discrete measurement data points on the cylinder, and estimate the cross-sectional radius of the cylinder using the least squares fitting method. However, this method uses three-coordinate point sampling to collect coordinates, and the measurement process is time-consuming. In addition, the least squares fitting method is sensitive to non-Gaussian noise, which can easily cause large estimation errors when there are abnormal noise points in the cross-sectional data.

[0004] In addition, traditional technology can also be based on the principle of laser triangulation to design a monocular object shape measurement system using a rotating platform, and used to measure the three-dimensional shape of cylindrical and conical surfaces. For objects with sizes ranging from 4mm (millimeter) to 30mm, the system measurement error is less than 3.5%, achieving a high overall accuracy. However, since this method uses a rotating platform, the stability of the system is affected by the rotating platform. When the equipment has been working for a long time, performance degradation is prone to occur. For example, when there are slight changes in the width and brightness of the laser line and the relative position of the laser line and the camera, the system accuracy loss is large. At the same time, the single-target positioning method is more complicated. If the equipment needs to restore the factory accuracy, it needs to be returned to the factory for recalibration, and the maintenance cost is high.

[0005] In other words, the current reaction force cone topography measurement method has the problem of low measurement accuracy. Summary of the invention

[0006] Based on this, it is necessary to provide a reaction force cone profile measurement method, device, computer equipment and system that can improve the measurement accuracy in order to address the problem of low measurement accuracy in traditional technologies.

[0007] A reaction force cone profile measurement method, the method comprising:

[0008] Obtain the three-dimensional point data corresponding to each cross section of the reaction force cone and generate a coordinate matrix corresponding to the cross section;

[0009] For each coordinate matrix, a first product between a first weight coefficient, a coordinate matrix and an ellipse fitting parameter, and a second product between a second weight coefficient, a coordinate matrix and an ellipse fitting parameter are obtained, and target ellipse fitting parameters are obtained according to an L1 norm of the first product and an L2 norm of the second product, and a cross-sectional radius of a cross section corresponding to the coordinate matrix is ​​determined based on the target ellipse fitting parameters;

[0010] The radius of the reaction force cone is obtained according to the cross-sectional radius of each cross section, and the three-dimensional morphology of the reaction force cone is output based on the radius of the reaction force cone.

[0011] In one embodiment, the step of obtaining the three-dimensional point data corresponding to each cross section of the reaction force cone includes:

[0012] Obtaining three-dimensional point cloud data of the reaction force cone and the axis direction of the shape corresponding to the three-dimensional point cloud data;

[0013] The three-dimensional point cloud data is divided according to the axis direction to obtain the three-dimensional point data corresponding to each section.

[0014] In one embodiment, the step of obtaining the radius of the reaction force cone according to the cross-sectional radius of each cross section includes:

[0015] The average value of the radii of each section is determined as the radius of the reaction force cone.

[0016] In one embodiment, the step of obtaining the target ellipse fitting parameters according to the L1 norm of the first product and the L2 norm of the second product includes:

[0017] Solve the following hybrid energy functional to obtain the target ellipse parameters:

[0018]

[0019] Among them, θ is the ellipse fitting parameter; w is the first weight coefficient; o represents the multiplication of corresponding elements; P is the coordinate matrix; ‖‖1 is the L1 norm; 1-w is the second weight coefficient; ‖ ‖2 is the L2 norm; λ is the Lagrangian parameter; θ T is the transpose of the ellipse fitting parameters; C is the matrix expression of the ellipse discrimination condition; arg min θ {} is the θ corresponding to when the function takes the minimum value.

[0020] In one embodiment, the step of solving the hybrid energy functional to obtain the target ellipse parameters includes:

[0021] Auxiliary variables are introduced to deform the hybrid energy functional. The deformed hybrid energy functional is:

[0022]

[0023] Among them, s is an auxiliary variable; st is a constraint condition;

[0024] By introducing the Bregman iteration variable, the unrestricted hybrid energy functional is obtained. The unrestricted hybrid energy functional is:

[0025]

[0026] Among them, μ is a constant; t is the Bregman iteration variable;

[0027] Solve the unrestricted hybrid energy functional and obtain the target ellipse fitting parameters.

[0028] In one embodiment, the step of solving the unrestricted hybrid energy functional to obtain the target ellipse fitting parameters further includes:

[0029] The standard Shrink operator is used to solve and obtain auxiliary variables;

[0030] According to the auxiliary variables and Bregman iteration variables, the target ellipse fitting parameters are obtained.

[0031] A reaction force cone profile measuring device, the device comprising:

[0032] A coordinate matrix acquisition module is used to obtain the three-dimensional point data corresponding to each cross section of the reaction force cone and generate a coordinate matrix corresponding to the cross section;

[0033] A cross-sectional radius acquisition module, for acquiring, for each coordinate matrix, a first product between a first weight coefficient, a coordinate matrix and an ellipse fitting parameter, and a second product between a second weight coefficient, a coordinate matrix and an ellipse fitting parameter, and obtaining target ellipse fitting parameters according to an L1 norm of the first product and an L2 norm of the second product, and determining a cross-sectional radius of a cross section corresponding to the coordinate matrix based on the target ellipse fitting parameters;

[0034] The three-dimensional shape output module is used to obtain the radius of the reaction force cone according to the cross-sectional radius of each cross section, and output the three-dimensional shape of the reaction force cone based on the radius of the reaction force cone.

[0035] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0036] A reaction force cone profile measurement system, comprising a handheld line laser device and a computer device as described above;

[0037] The handheld line laser device is used to scan the reaction force cone, obtain the three-dimensional point cloud data of the reaction force cone, and transmit the three-dimensional point cloud data to the computer device.

[0038] A computer-readable storage medium stores a computer program, which implements the steps of the above method when executed by a processor.

[0039] The above reaction force cone morphology measurement method, device, computer equipment and system obtain the three-dimensional point data corresponding to each cross section of the reaction force cone and generate a coordinate matrix corresponding to the cross section; for each coordinate matrix, obtain the first product between the first weight coefficient, the coordinate matrix and the ellipse fitting parameter, and the second product between the second weight coefficient, the coordinate matrix and the ellipse fitting parameter, and obtain the target ellipse fitting parameter according to the L1 norm of the first product and the L2 norm of the second product, and determine the cross-sectional radius of the cross section corresponding to the coordinate matrix based on the target ellipse fitting parameter; according to the cross-sectional radius of each cross section, obtain the radius of the reaction force cone. The present application introduces the L1-L2 mixed norm into the ellipse fitting framework, and obtains the ellipse fitting parameters based on the algebraic distance minimization cost function of the L1-L2 norm, thereby improving the anti-interference ability to Gaussian noise and non-Gaussian noise. By combining different weight coefficients, the advantages of the L1 norm and the L2 norm are integrated. Only the first weight coefficient and the second weight coefficient need to be adjusted to adjust the anti-interference ability to Gaussian noise and non-Gaussian noise, thereby improving the accuracy and precision of the measurement results and broadening the scope of use. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A schematic diagram of a process for measuring a reaction force cone profile in one embodiment;

[0041] Figure 2a is the elliptical data of Gaussian noise with mean 0 and variance 6;

[0042] Figure 2b Based on Figure 2a Measurement data of

[0043] Figure 3a is the elliptical data of Laplace noise with a mean of 0 and a variance of 121;

[0044] Figure 3b Based on Figure 3a Measurement data of

[0045] Figure 4 The 3D point cloud data of the reaction force cone of the high-voltage cable is obtained by handheld laser scanning;

[0046] Figure 5a for Figure 4 An image of a point cloud cross section;

[0047] Figure 5b Based on Figure 5a Measurement data of

[0048] Figure 6 is a structural block diagram of a reaction force cone device in one embodiment;

[0049] Figure 7 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0051] As described in the background technology, the traditional contact measurement method has relatively high measurement accuracy, but it is time-consuming and has high equipment costs. Although the non-contact optical measurement method has a good suppression effect on the ideal Gaussian noise or Laplace noise in the measurement data, various types of noise may exist in the actual working environment, which will seriously affect the measurement accuracy and reduce the accuracy of the measurement results.

[0052] The present application introduces the L1-L2 mixed norm into the ellipse fitting framework and obtains the ellipse fitting parameters based on the algebraic distance minimization cost function of the L1-L2 norm, thereby improving the accuracy and precision of the measurement results and broadening the scope of application.

[0053] In one embodiment, Figure 1 As shown, a reaction force cone profile measurement method is provided, the method comprising:

[0054] Step 110, obtaining the three-dimensional point data corresponding to each cross section of the reaction force cone, and generating a coordinate matrix corresponding to the cross section.

[0055] The reaction force cone may be a reaction force cone arranged on a cable. In one example, the reaction force cone may be arranged on a high voltage cable. The shape of the reaction force cone may be determined according to actual conditions, for example, it may be cylindrical. The three-dimensional point data may be obtained by scanning with a laser device and include corresponding three-dimensional coordinates.

[0056] Specifically, the reaction force cone may be divided into different cross sections. For example, the reaction force cone may be divided according to the axial direction or radial direction of the reaction force cone, and the three-dimensional point data corresponding to each cross section may be obtained respectively.

[0057] The same section may correspond to multiple 3D point data, and each 3D point data may be located on the same plane or on the same plane within a certain error. For example, when a certain coordinate value of each 3D point data corresponding to the same section is the same (such as the same x coordinate), it can be confirmed that each 3D point data may be located on the same plane; when a certain coordinate value of all 3D point data corresponding to the same section remains within a certain error range, it can be confirmed that each 3D point data is located on the same plane within a certain error.

[0058] After obtaining the three-dimensional point data corresponding to each cross section, a coordinate matrix corresponding to the cross section may be generated according to the coordinate values ​​of the three-dimensional point data corresponding to the same cross section.

[0059] Step 120, for each coordinate matrix, obtain the first product of the first weight coefficient, the coordinate matrix and the ellipse fitting parameters, and the second product of the second weight coefficient, the coordinate matrix and the ellipse fitting parameters, and obtain the target ellipse fitting parameters based on the L1 norm of the first product and the L2 norm of the second product, and determine the cross-sectional radius of the cross-section corresponding to the coordinate matrix based on the target ellipse fitting parameters.

[0060] The first weight coefficient and the second weight coefficient may be two independent coefficients, that is, there may be no necessary connection between the two; or they may satisfy a certain preset relationship, for example, the sum of the first weight coefficient and the second weight coefficient may be a preset value, or the ratio of the first weight coefficient to the second weight coefficient may be a preset value, etc. The ellipse fitting parameter is an unknown quantity, that is, a value to be solved; the ellipse fitting parameter may be a matrix, and includes multiple ellipse parameters to be solved.

[0061] Specifically, for each coordinate matrix, a first product between a first weight coefficient, a coordinate matrix and an ellipse fitting parameter, and a second product between a second weight coefficient, a coordinate matrix and an ellipse fitting parameter are obtained. The hybrid energy functional includes an L1 norm of the first product and an L2 norm of the second product. It should be noted that the hybrid energy functional includes but is not limited to the above two function terms, and may also include more function terms.

[0062] By solving the hybrid energy functional, the target ellipse fitting parameters can be obtained. By calculating the target ellipse fitting parameters, the cross-sectional radius can be obtained. The cross-sectional radius is the radius of the cross-section corresponding to the coordinate matrix involved in the calculation. Therefore, the hybrid energy functional can be used to estimate the radii of different cross-sections.

[0063] For each coordinate matrix, the first product and the second product are determined respectively, and the corresponding hybrid energy functional is obtained. By solving the corresponding hybrid energy functional, the cross-sectional radius corresponding to each coordinate matrix can be obtained, that is, the cross-sectional radius corresponding to each cross section. In this way, the cross-sectional radius of each cross section of the reaction force cone can be obtained.

[0064] Step 130, obtaining the radius of the reaction force cone according to the cross-sectional radius of each cross section, and outputting the three-dimensional morphology of the reaction force cone based on the radius of the reaction force cone.

[0065] Specifically, the radius of the reaction force cone can be determined based on the estimated cross-sectional radius of each cross section. The present application can adopt various methods listed in the prior art to obtain the radius of the reaction force cone, and the present application does not make specific limitations on this. After obtaining the radius of the reaction force cone, the three-dimensional morphology of the reaction force cone can be obtained based on the radius of the reaction force cone, thereby completing the measurement of the reaction force cone.

[0066] The reaction force cone morphology measurement method in each embodiment of the present application overcomes the problem that the traditional L2 norm is sensitive to non-Gaussian noise and the L1 norm is sensitive to Gaussian noise. It can obtain high-precision parameter estimation accuracy for noise-free data, Gaussian noise interference data, and non-Gaussian noise interference data, and reduce the interference of noise on the estimated reaction force cone size accuracy.

[0067] In the above-mentioned reaction force cone morphology measurement method, the L1-L2 mixed norm is introduced into the ellipse fitting framework, and the ellipse fitting parameters are obtained based on the algebraic distance minimization cost function of the L1-L2 norm, so as to improve the anti-interference ability to Gaussian noise and non-Gaussian noise. By combining different weight coefficients, the advantages of the L1 norm and the L2 norm are integrated. Only the first weight coefficient and the second weight coefficient need to be adjusted to adjust the anti-interference ability to Gaussian noise and non-Gaussian noise, thereby improving the accuracy and precision of the measurement results and broadening the scope of application.

[0068] In one embodiment, the step of obtaining the radius of the reaction force cone according to the cross-sectional radius of each cross section includes:

[0069] The average value of the radii of each section is determined as the radius of the reaction force cone.

[0070] Specifically, after the cross-sectional radius of each cross-section of the reaction force cone is calculated, the cross-sectional radiuses may be averaged, and the obtained average value may be used as the radius of the reaction force cone.

[0071] In one embodiment, the step of obtaining the three-dimensional point data corresponding to each cross section of the reaction force cone includes:

[0072] Obtaining three-dimensional point cloud data of the reaction force cone and the axis direction of the shape corresponding to the three-dimensional point cloud data;

[0073] The three-dimensional point cloud data is divided according to the axis direction to obtain the three-dimensional point data corresponding to each section.

[0074] The three-dimensional point cloud data includes a plurality of three-dimensional point data.

[0075] Specifically, the reaction force cone can be scanned by a laser device, such as a handheld line laser device, to obtain three-dimensional point cloud data of the reaction force cone surface, calculate the axial direction of the reaction force cone surface point cloud, and divide the three-dimensional point cloud data into different cross-sectional data according to the axial line, thereby obtaining multiple cross-sections in the axial direction, the axial direction is perpendicular to each cross-section, and each cross-section corresponds to multiple three-dimensional point data.

[0076] In one embodiment, the step of obtaining the target ellipse fitting parameters according to the L1 norm of the first product and the L2 norm of the second product includes:

[0077] Solve the following hybrid energy functional to obtain the target ellipse parameters:

[0078]

[0079] Among them, θ is the ellipse fitting parameter; w is the first weight coefficient; o represents the multiplication of corresponding elements; P is the coordinate matrix; ‖‖1 is the L1 norm; 1-w is the second weight coefficient; ‖ ‖2 is the L2 norm; λ is the Lagrangian parameter; θ T is the transpose of the ellipse fitting parameters; C is the matrix expression of the ellipse discrimination condition; arg min θ {} is the θ corresponding to when the function takes the minimum value.

[0080] Specifically, the reaction force cone can be cylindrical, and the cross-section can be circular. Considering the influence of noise, the cylinder radius estimation problem can be converted into an ellipse fitting problem on a two-dimensional plane. For a general quadratic curve, J(P, θ) = P·θ = ax 2 +bxy+cy 2 +dx+ey+f=0, where J() is the energy functional, x is the x-coordinate in the two-dimensional coordinate system; y is the y-coordinate in the two-dimensional coordinate system; a is the first ellipse fitting parameter; b is the second ellipse fitting parameter; c is the third ellipse fitting parameter; d is the fourth ellipse fitting parameter; e is the fifth ellipse fitting parameter; f is the sixth ellipse fitting parameter; P=(x 2 ,xy,y 2 , x, y, 1), that is, the coordinate matrix; θ = (a, b, c, d, e, f) T .

[0081] When the discriminant satisfies condition b 2 When +4ac<0, before the quadratic curve degenerates into an ellipse, take b 2 When +4ac=-1, -1<0 satisfies the ellipse condition, and its equivalent form is 4ac-b 2 =1, the matrix expression of this equivalent form is:

[0082]

[0083] When b 2 When +4ac=-1, the matrix form is θ T Cθ = 1. The ellipse fitting parameters are solved by minimizing the L2 norm of the algebraic distance. The parameters of the ellipse equation can be estimated by solving the following L2 energy functional constrained problem:

[0084]

[0085] Among them, arg min θ {} is the θ corresponding to the minimum value of ‖Pθ‖2; P is the coordinate matrix; θ is the ellipse fitting parameter; ‖‖2 is the L2 norm; st is the constraint condition; a is the first ellipse fitting parameter; b is the second ellipse fitting parameter; c is the third ellipse fitting parameter.

[0086] By using the Lagrange multiplier method, the above problem can be transformed into the following unrestricted problem:

[0087]

[0088] Wherein, λ is the Lagrangian parameter and can be a constant greater than 0.

[0089] In the present application, the target ellipse fitting parameters can be obtained based on the L1-L2 mixed energy functional, and the L1-L2 mixed energy functional can be shown as follows:

[0090]

[0091] Among them, θ is the ellipse fitting parameter; w is the first weight coefficient; o represents the multiplication of corresponding elements; P is the coordinate matrix; ‖‖1 is the L1 norm; 1-w is the second weight coefficient; ‖ ‖2 is the L2 norm; λ is the Lagrangian parameter; θ T is the transpose of the ellipse fitting parameters; C is the matrix expression of the ellipse discrimination condition; arg min θ {} is the θ corresponding to when the function takes the minimum value.

[0092] In one embodiment, the step of solving the hybrid energy functional to obtain the target ellipse parameters includes:

[0093] Auxiliary variables are introduced to deform the hybrid energy functional. The deformed hybrid energy functional is:

[0094]

[0095] Among them, s is an auxiliary variable; st is a constraint condition;

[0096] By introducing the Bregman iteration variable, the unrestricted hybrid energy functional is obtained. The unrestricted hybrid energy functional is:

[0097]

[0098] Among them, μ is a constant; t is the Bregman iteration variable;

[0099] Solve the unrestricted hybrid energy functional and obtain the target ellipse fitting parameters.

[0100] Specifically, for the minimization problem that includes both L1 and L2 terms in the hybrid energy functional, the Bregman iterative solution method can be used to obtain the ellipse. First, an auxiliary variable s = Pθ can be introduced to transform the hybrid energy functional into:

[0101]

[0102] Among them, s is the auxiliary variable; st is the constraint condition; θ is the ellipse fitting parameter; w is the first weight coefficient; o represents the multiplication of corresponding elements; ‖ ‖1 is the L1 norm; 1-w is the second weight coefficient; ‖ ‖2 is the L2 norm; λ is the Lagrangian parameter; θ T is the transpose of the ellipse fitting parameters; C is the matrix expression of the ellipse discrimination condition; arg min θ {} is the θ corresponding to when the function takes the minimum value.

[0103] Then, the Bregman iteration variable t is introduced to transform the above equation into the following unrestricted problem, and the unrestricted hybrid energy functional is obtained:

[0104]

[0105] Here, μ is a constant greater than 0 and can be 1.

[0106] By solving the unrestricted hybrid energy functional, the target ellipse fitting parameters corresponding to the coordinate matrix can be obtained, that is, the target ellipse fitting parameters corresponding to the cross section.

[0107] In the above reaction force cone profile measurement method, the hybrid energy functional includes both the L1 norm and the L2 norm. In signal analysis, the Gaussian noise can be suppressed by the L2 norm, and the Laplace noise can be suppressed by the L1 norm. By selecting the corresponding weight coefficient, the hybrid energy functional can effectively suppress the interference of Gaussian noise and Laplace noise at the same time, further improving the accuracy and precision of the measurement.

[0108] In one embodiment, the step of solving the unrestricted hybrid energy functional to obtain the target ellipse fitting parameters further includes:

[0109] The standard Shrink operator is used to solve and obtain auxiliary variables;

[0110] According to the auxiliary variables and Bregman iteration variables, the target ellipse fitting parameters are obtained.

[0111] Specifically, for the subproblem of the auxiliary variable s, the hybrid energy functional can be transformed into:

[0112]

[0113] Among them, arg min s {} is the s corresponding to when the function takes the minimum value.

[0114] The above formula takes partial derivative of the auxiliary variable s and satisfies the necessary conditions at the extreme value of the function Among them, |s| is the absolute value of s. There are two cases for discussion:

[0115] (1) Let s>0, then w+2(1-w)s+μ(s-Pθ-t)=0;

[0116] (2) Let s<0, then -w+2(1-w)s+μ(s-Pθ-t)=0.

[0117] μ is a constant greater than 0, w and (1-w) are coefficient matrices, each element of which is in the interval [0,1]. The standard shrink operator can be used to solve it, and we get:

[0118]

[0119] Where k is the number of iterations; Where x is the first parameter, which can be equal to μ(Pθ k+1 +t k ); r is the second parameter, which can be equal to w. s k+1 is the k+1th iteration result of variable s; θ k+1 is the ellipse fitting parameter obtained by the k+1th iteration of variable θ; t k is the Bregman iteration variable obtained by the k-th iteration of variable t.

[0120] For the subproblem of Bregman iteration variable t, t is updated as follows:

[0121] t k+1 =t k +Pθ k+1 -s k+1

[0122] Among them, t k+1 is the Bregman iteration variable obtained at the k+1th iteration.

[0123] For the subproblem of θ, the hybrid energy functional can be transformed into:

[0124]

[0125] It can be obtained by using the least - square algorithm, and the following closed - form solution is obtained:

[0126]

[0127] where s k is the k - th iteration result of the variable s.

[0128] Furthermore, the present application can be understood in combination with the following example. Let w = 1, λ = 1, μ = 1, k = 0, s 0 = 0, t 0 = 0, and the maximum number of iterations N = 20.

[0129] When k < N and ||Pθ k+1 ||1 > ||Pθ k ||1, it can be updated based on , updated based on , and the Bregman iteration variable t is updated based on t k+1 = t k + Pθ k+1 - s k+1 .

[0130] Increment k by 1 as the step unit. For each value of k, the above - mentioned step is executed until k is greater than or equal to N, and the obtained θ k is returned.

[0131] After iteration, the elliptical fitting parameters θ = (a, b, c, d, e, f) T can be obtained. The elliptical fitting parameters θ are normalized by dividing each element in the matrix by f, and The center of the ellipse (X C , Y C ), the major semi - axis R x of the ellipse, the minor semi - axis R y of the ellipse, and the rotation angle δ of the ellipse can be obtained through the following formula:

[0132]

[0133] The cross - sectional radius R of the cross - section can be:

[0134] To facilitate the description of the solution of the present application, the following is illustrated by a specific example. The reaction - force cone profile measurement method provided by the present application can be used to measure the three - dimensional profile of the reaction - force cone of a cylindrical high - voltage cable. As Figure 2a shown, Figure 2a shows the elliptical data of Gaussian noise with a mean of 0 and a variance of 6. The center of the ellipse (XC , Y C )=(128,256), major semi-axis R x =40, the minor axis of the ellipse R y =30 and the ellipse rotation angle δ = 0.785398 radians. Figure 2b for Figure 2a Using L1-L2 hybrid energy functional, set the first weight coefficient w = 0.5, μ = 1, iterate 12 times, and the ellipse fitting result is (X C , Y C )=(128.10,256.07), major semi-axis R x =39.66, short semi-axis R y =30.17, rotation angle δ = 0.767142 radians.

[0135] like Figure 3a As shown, Figure 3a The ellipse data of Laplace noise with a mean of 0 and a variance of 121 is shown. The center of the ellipse (X C , Y C )=(128,256), major semi-axis R x =40, the minor axis of the ellipse R y =30 and the ellipse rotation angle δ = 0.785398 radians. Figure 3b for Figure 3a Using L1-L2 hybrid energy functional, set the first weight coefficient w = 0.5, μ = 1, iterate 5 times, and the ellipse fitting result is (X C , Y C )=(127.42,255.91), major semi-axis R x =40.26, short semi-axis R y =30.02, rotation angle γ = 0.684863 radians.

[0136] Figure 4 Point cloud showing the handheld laser scan of the high voltage cable reaction force cone. Figure 5a A point cloud cross-section image of the high-voltage cable reaction force cone. Figure 5b for Figure 5a Using L1-L2 hybrid energy functional, set the first weight coefficient w = 0.5, μ = 1, iterate 30 times, and the ellipse fitting result is (X C , Y C )=(44.80,-240.56), major semi-axis R x =38.16, short semi-axis R y =37.57, rotation angle δ = 1.566432 radians. Then the estimated cross-sectional radius is mm, a deviation of 0.14 mm from the design value of 38.00 mm.

[0137] It should be understood that although Figure 1 The steps in the flowchart of -5 are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 -At least part of the steps in 5 may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the steps or stages in other steps.

[0138] In one embodiment, Figure 6 As shown, a reaction force cone profile measuring device is provided, comprising:

[0139] A coordinate matrix acquisition module is used to obtain the three-dimensional point data corresponding to each cross section of the reaction force cone and generate a coordinate matrix corresponding to the cross section;

[0140] A cross-sectional radius acquisition module, for acquiring, for each coordinate matrix, a first product between a first weight coefficient, a coordinate matrix and an ellipse fitting parameter, and a second product between a second weight coefficient, a coordinate matrix and an ellipse fitting parameter, and obtaining target ellipse fitting parameters according to an L1 norm of the first product and an L2 norm of the second product, and determining a cross-sectional radius of a cross section corresponding to the coordinate matrix based on the target ellipse fitting parameters;

[0141] The three-dimensional shape output module is used to obtain the radius of the reaction force cone according to the section radius of each section, and output the three-dimensional shape of the reaction force cone based on the radius of the reaction force cone.

[0142] In one embodiment, the coordinate matrix acquisition module is also used to obtain the three-dimensional point cloud data of the reaction force cone and the axial direction of the shape corresponding to the three-dimensional point cloud data; the three-dimensional point cloud data is divided according to the axial direction to obtain the three-dimensional point data corresponding to each section.

[0143] In one embodiment, the reaction force cone radius acquisition module is further used to confirm the average value of the radii of each cross section as the radius of the reaction force cone.

[0144] In one embodiment, the cross-sectional radius acquisition module includes:

[0145] The hybrid energy functional solving unit is used to solve the following hybrid energy functional to obtain the target ellipse parameters:

[0146]

[0147] Among them, θ is the ellipse fitting parameter; w is the first weight coefficient; o represents the multiplication of corresponding elements; P is the coordinate matrix; ‖‖1 is the L1 norm; 1-w is the second weight coefficient; ‖ ‖2 is the L2 norm; λ is the Lagrangian parameter; θ T is the transpose of the ellipse fitting parameters; C is the matrix expression of the ellipse discrimination condition; arg min θ {} is the θ corresponding to when the function takes the minimum value.

[0148] In one embodiment, the hybrid energy functional solving unit is further used to introduce auxiliary variables to deform the hybrid energy functional. The deformed hybrid energy functional is:

[0149]

[0150] Among them, s is an auxiliary variable; st is a constraint condition;

[0151] By introducing the Bregman iteration variable, the unrestricted hybrid energy functional is obtained. The unrestricted hybrid energy functional is:

[0152]

[0153] Among them, μ is a constant; t is the Bregman iteration variable;

[0154] Solve the unrestricted hybrid energy functional and obtain the target ellipse fitting parameters.

[0155] In one embodiment, the hybrid energy functional solution unit is also used to adopt a standard Shrink operator to solve and obtain auxiliary variables; and obtain target ellipse fitting parameters according to the auxiliary variables and Bregman iteration variables.

[0156] For the specific definition of the reaction force cone profile measurement device, please refer to the definition of the reaction force cone profile measurement method mentioned above, which will not be repeated here. Each module in the above reaction force cone profile measurement device can be implemented in whole or in part by software, hardware and their combination. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0157] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 7As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store three-dimensional point cloud data, a coordinate matrix, a first weight coefficient, a second weight coefficient, a Lagrangian parameter, a matrix expression of a discrimination condition, etc. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a reaction force cone morphology measurement method is implemented.

[0158] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0159] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0160] Obtain the three-dimensional point data corresponding to each cross section of the reaction force cone and generate a coordinate matrix corresponding to the cross section;

[0161] For each coordinate matrix, a first product between a first weight coefficient, a coordinate matrix and an ellipse fitting parameter, and a second product between a second weight coefficient, a coordinate matrix and an ellipse fitting parameter are obtained, and target ellipse fitting parameters are obtained according to an L1 norm of the first product and an L2 norm of the second product, and a cross-sectional radius of a cross section corresponding to the coordinate matrix is ​​determined based on the target ellipse fitting parameters;

[0162] The radius of the reaction force cone is obtained according to the cross-sectional radius of each cross section, and the three-dimensional morphology of the reaction force cone is output based on the radius of the reaction force cone.

[0163] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining the three-dimensional point cloud data of the reaction force cone and the axial direction of the shape corresponding to the three-dimensional point cloud data; dividing the three-dimensional point cloud data according to the axial direction to obtain the three-dimensional point data corresponding to each section.

[0164] In one embodiment, when the processor executes the computer program, the following steps are further implemented: an average value of the radii of each cross section is determined as the radius of the reaction force cone.

[0165] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0166] Solve the following hybrid energy functional to obtain the target ellipse parameters:

[0167]

[0168] Among them, θ is the ellipse fitting parameter; w is the first weight coefficient; o represents the multiplication of corresponding elements; P is the coordinate matrix; ‖‖1 is the L1 norm; 1-w is the second weight coefficient; ‖ ‖2 is the L2 norm; λ is the Lagrangian parameter; θ T is the transpose of the ellipse fitting parameters; C is the matrix expression of the ellipse discrimination condition; arg min θ {} is the θ corresponding to when the function takes the minimum value.

[0169] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0170] Auxiliary variables are introduced to deform the hybrid energy functional. The deformed hybrid energy functional is:

[0171]

[0172] Among them, s is an auxiliary variable; st is a constraint condition;

[0173] By introducing the Bregman iteration variable, the unrestricted hybrid energy functional is obtained. The unrestricted hybrid energy functional is:

[0174]

[0175] Among them, μ is a constant; t is the Bregman iteration variable;

[0176] Solve the unrestricted hybrid energy functional and obtain the target ellipse fitting parameters.

[0177] In one embodiment, when the processor executes the computer program, the following steps are further implemented: using a standard Shrink operator to solve and obtain auxiliary variables; and obtaining target ellipse fitting parameters according to the auxiliary variables and Bregman iteration variables.

[0178] In one embodiment, a reaction force cone topography measurement system is provided, comprising a handheld line laser device and a computer device in any of the above embodiments;

[0179] The handheld line laser device is used to scan the reaction force cone, obtain the three-dimensional point cloud data of the reaction force cone, and transmit the three-dimensional point cloud data to the computer device.

[0180] Specifically, a handheld laser device can be used to scan the reaction force cone of the cable, so as to obtain the three-dimensional point cloud data of the surface of the cable reaction force cone, and transmit the three-dimensional point cloud data to the computer device. The computer device obtains the point cloud section data of the cable reaction force cone surface, and estimates the major and minor axes of the elliptical section respectively based on the L1-L2 mixed energy functional, and outputs the cross-sectional radius of the cable reaction force cone according to the major and minor axes. Specifically, the computer device can execute the reaction force cone morphology measurement method in any of the above embodiments.

[0181] The above reaction force cone topography measurement system uses a handheld line laser device for scanning and estimates the radius of the reaction force cone through a computer device. It does not require cooperation with other displacement auxiliary platforms, thereby improving measurement accuracy and measurement precision while reducing maintenance costs and improving ease of use.

[0182] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0183] Obtain the three-dimensional point data corresponding to each cross section of the reaction force cone and generate a coordinate matrix corresponding to the cross section;

[0184] For each coordinate matrix, a first product between a first weight coefficient, a coordinate matrix and an ellipse fitting parameter, and a second product between a second weight coefficient, a coordinate matrix and an ellipse fitting parameter are obtained, and target ellipse fitting parameters are obtained according to an L1 norm of the first product and an L2 norm of the second product, and a cross-sectional radius of a cross section corresponding to the coordinate matrix is ​​determined based on the target ellipse fitting parameters;

[0185] The radius of the reaction force cone is obtained according to the cross-sectional radius of each cross section, and the three-dimensional morphology of the reaction force cone is output based on the radius of the reaction force cone.

[0186] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining the three-dimensional point cloud data of the reaction force cone and the axial direction of the shape corresponding to the three-dimensional point cloud data; dividing the three-dimensional point cloud data according to the axial direction to obtain the three-dimensional point data corresponding to each section.

[0187] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: an average value of the radii of each cross section is determined as the radius of the reaction force cone.

[0188] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0189] Solve the following hybrid energy functional to obtain the target ellipse parameters:

[0190]

[0191] Among them, θ is the ellipse fitting parameter; w is the first weight coefficient; o represents the multiplication of corresponding elements; P is the coordinate matrix; ‖‖1 is the L1 norm; 1-w is the second weight coefficient; ‖ ‖2 is the L2 norm; λ is the Lagrangian parameter; θ T is the transpose of the ellipse fitting parameters; C is the matrix expression of the ellipse discrimination condition; arg min θ {} is the θ corresponding to when the function takes the minimum value.

[0192] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0193] Auxiliary variables are introduced to deform the hybrid energy functional. The deformed hybrid energy functional is:

[0194]

[0195] Among them, s is an auxiliary variable; st is a constraint condition;

[0196] By introducing the Bregman iteration variable, the unrestricted hybrid energy functional is obtained. The unrestricted hybrid energy functional is:

[0197]

[0198] Among them, μ is a constant; t is the Bregman iteration variable;

[0199] Solve the unrestricted hybrid energy functional and obtain the target ellipse fitting parameters.

[0200] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: using the standard Shrink operator to solve and obtain auxiliary variables; and obtaining the target ellipse fitting parameters according to the auxiliary variables and the Bregman iteration variables.

[0201] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0202] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0203] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for measuring reaction force cone morphology, characterized in that: The method comprises: Obtaining the three-dimensional point data corresponding to each cross section of the reaction force cone, and generating a coordinate matrix corresponding to the cross section; For each of the coordinate matrices, a first weight coefficient, a first product of the coordinate matrix and the ellipse fitting parameters, and a second weight coefficient, a second product of the coordinate matrix and the ellipse fitting parameters are obtained, and target ellipse fitting parameters are obtained according to an L1 norm of the first product and an L2 norm of the second product, and a cross-sectional radius of the cross section corresponding to the coordinate matrix is ​​determined based on the target ellipse fitting parameters; Obtaining the radius of the reaction force cone according to the cross-sectional radius of each cross section, and outputting the three-dimensional morphology of the reaction force cone based on the radius of the reaction force cone; The step of obtaining the target ellipse fitting parameters according to the L1 norm of the first product and the L2 norm of the second product includes: Solve the following mixed energy functional to obtain the target ellipse fitting parameters: Wherein, θ is the ellipse fitting parameter; w is the first weight coefficient; o represents the multiplication of corresponding elements; P is the coordinate matrix; ||||1 is the L1 norm; 1-w is the second weight coefficient; ||||2 is the L2 norm; λ is the Lagrangian parameter; θ T is the transpose of the ellipse fitting parameters; C is the matrix expression of the ellipse discrimination condition; To obtain the θ corresponding to the minimum value of the function.

2. The reaction force cone profile measurement method according to claim 1, characterized in that: The steps of obtaining the three-dimensional point data corresponding to each cross section of the reaction force cone include: Acquire three-dimensional point cloud data of the reaction force cone and the axis direction of the shape corresponding to the three-dimensional point cloud data; The three-dimensional point cloud data is divided according to the axis direction to obtain the three-dimensional point data corresponding to each cross section.

3. The reaction force cone profile measurement method according to claim 1, characterized in that: The step of obtaining the radius of the reaction force cone according to the cross-sectional radius of each cross-section comprises: The average value of the cross-sectional radii is determined as the radius of the reaction force cone.

4. The reaction force cone profile measurement method according to claim 1, characterized in that: The step of solving the following mixed energy functional to obtain the target ellipse fitting parameters includes: Auxiliary variables are introduced to deform the hybrid energy functional. The hybrid energy functional after deformation is: Among them, s is an auxiliary variable; st is a constraint condition; The Bregman iteration variable is introduced to obtain the unrestricted hybrid energy functional, which is: Among them, μ is a constant; t is the Bregman iteration variable; The unrestricted hybrid energy functional is solved to obtain the target ellipse fitting parameters.

5. The reaction force cone profile measurement method according to claim 4, characterized in that: The step of measuring the reaction force cone profile to solve the unrestricted hybrid energy functional and obtain the target ellipse fitting parameters also includes: A standard Shrink operator is used to solve the problem and obtain the auxiliary variable; The target ellipse fitting parameters are obtained according to the auxiliary variables and the Bregman iteration variables.

6. A reaction force cone profile measurement device, characterized in that: The device comprises: A coordinate matrix acquisition module is used to acquire the three-dimensional point data corresponding to each cross section of the reaction force cone and generate a coordinate matrix corresponding to the cross section; a cross-sectional radius acquisition module, configured to respectively acquire, for each of the coordinate matrices, a first weight coefficient, a first product between the coordinate matrix and the ellipse fitting parameters, and a second weight coefficient, a second product between the coordinate matrix and the ellipse fitting parameters, and obtain target ellipse fitting parameters according to an L1 norm of the first product and an L2 norm of the second product, and determine a cross-sectional radius of the cross section corresponding to the coordinate matrix based on the target ellipse fitting parameters; A three-dimensional shape output module, used for obtaining the radius of the reaction force cone according to the cross-sectional radius of each cross section, and outputting the three-dimensional shape of the reaction force cone based on the radius of the reaction force cone; The device is used to solve the following mixed energy functional to obtain the target ellipse fitting parameters: Wherein, θ is the ellipse fitting parameter; w is the first weight coefficient; o represents the multiplication of corresponding elements; P is the coordinate matrix; ||||1 is the L1 norm; 1-w is the second weight coefficient; ||||2 is the L2 norm; λ is the Lagrangian parameter; θ T is the transpose of the ellipse fitting parameters; C is the matrix expression of the ellipse discrimination condition; To obtain the θ corresponding to the minimum value of the function.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A reaction force cone profile measurement system, characterized in that: comprising a handheld line laser device and a computer device as claimed in claim 7; The handheld line laser device is used to scan the reaction force cone, obtain the three-dimensional point cloud data of the reaction force cone, and transmit the three-dimensional point cloud data to the computer device.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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