A non-axisymmetric plasma arc temperature field calculation and processing system and method

Abstract

The invention discloses a non-axisymmetric plasma arc temperature field calculation processing system and method, the method comprising: reading arc characteristic spectral line images, segmenting plasma arcs, and obtaining integrated data; performing discrete processing on the arc cross section; calculating projection value vectors and projection coefficient matrices according to the integrated data, and obtaining emission coefficient distribution by synchronous iteration; evaluating the iteration result by root mean square error, and obtaining the emission coefficient distribution with the minimum error; determining the interface between the high temperature area and the low temperature area in the axial direction of the arc; creating a fitting model based on the emission coefficient distribution, performing fitting, and determining the maximum point position and the corresponding maximum value according to the fitting result, and determining the high temperature area and the low temperature area of ​​the arc cross section; and calculating the temperature values ​​of the high temperature area and the low temperature area of ​​the arc cross section by a standard temperature method according to the relationship curve between the emission coefficient and the temperature. The effect is that the invention can obtain a reliable plasma arc temperature field distribution.

Description

Technical Field

[0001] The invention relates to the technical field of metal welding, and in particular to a non-axisymmetric plasma arc temperature field calculation processing system and method. Background Art

[0002] Arc spectra contain rich information, and through spectral diagnosis, characteristic signals reflecting welding quality can be obtained. Arc temperature field is an important part of arc spectrum diagnosis. Calculating it helps to further understand the heat generation mechanism of the arc and provide a theoretical basis for improving welding technology and weld quality. Plasma-MIG hybrid welding can give full play to the advantages of strong penetration of plasma welding arc and high deposition efficiency of MIG welding, and has very good application prospects in the welding of thick plate high-strength aluminum alloys in aerospace and military industries.

[0003] However, since the arc in plasma-MIG hybrid welding no longer presents an axisymmetric shape, the emission coefficient obtained by traditional Abel inverse transformation deviates from the actual value, resulting in large errors in the arc temperature field diagnosis, which seriously restricts the in-depth study of the coupling mechanism of plasma-MIG hybrid welding. Summary of the invention

[0004] In view of the technical defects mentioned in the background technology, an object of the embodiments of the present invention is to provide a system and method for calculating and processing a non-axisymmetric plasma arc temperature field.

[0005] To achieve the above objectives, in a first aspect, an embodiment of the present invention provides a non-axisymmetric plasma arc temperature field calculation and processing system, the system comprising a processing device, the processing device comprising:

[0006] An acquisition module is used to read the arc characteristic spectral line image and segment the plasma arc from the arc characteristic spectral line image to obtain integrated data;

[0007] Transformation recovery module for:

[0008] Discretizing the cross section of the plasma arc;

[0009] and calculating a two-dimensional spectral line tomography projection value vector and a projection coefficient matrix according to the integrated data;

[0010] The two-dimensional spectrum line tomography projection value vector and projection coefficient matrix obtained by the calculation are restored by using a synchronous iterative cimmino algorithm to obtain the emission coefficient distribution of the entire plasma arc;

[0011] The first processing module is used for:

[0012] The root mean square error is used to evaluate the iteration results to obtain the emission coefficient distribution with the minimum error;

[0013] Determine the interface between the high temperature region and the low temperature region in the arc axis according to the state characteristics of the emission coefficient distribution with the minimum error, and normalize the emission coefficients corresponding to the high / low temperature regions respectively;

[0014] The second processing module is used for:

[0015] Creating a double Gaussian fitting model based on the emission coefficient distribution, performing nonlinear least squares fitting, and determining the position of the maximum point and its corresponding maximum value according to the fitting result, determining the high temperature area and the low temperature area of ​​the arc cross section, and obtaining the emission coefficient distribution of the high temperature area of ​​the arc cross section and the emission coefficient distribution of the low temperature area of ​​the arc cross section;

[0016] Compute module for:

[0017] Based on the physical property parameters corresponding to the arc characteristic spectrum line and according to the relationship curve between the emission coefficient and the temperature, the temperature values ​​of the high temperature area and the low temperature area of ​​the arc cross section are calculated by using the standard temperature method.

[0018] In a second aspect, an embodiment of the present invention further provides a method for calculating and processing a non-axisymmetric plasma arc temperature field, which is applied to a processing device, and the method includes:

[0019] Reading the arc characteristic spectral line image, and segmenting the plasma arc from the arc characteristic spectral line image to obtain integrated data;

[0020] Discretizing the cross section of the plasma arc;

[0021] and calculating a two-dimensional spectral line tomography projection value vector and a projection coefficient matrix according to the integrated data;

[0022] The two-dimensional spectrum line tomography projection value vector and projection coefficient matrix obtained by the calculation are restored by using a synchronous iterative cimmino algorithm to obtain the emission coefficient distribution of the entire plasma arc;

[0023] The root mean square error is used to evaluate the iteration results to obtain the emission coefficient distribution with the minimum error;

[0024] Determine the interface between the high temperature region and the low temperature region in the arc axis according to the state characteristics of the emission coefficient distribution with the minimum error, and normalize the emission coefficients corresponding to the high / low temperature regions respectively;

[0025] Creating a double Gaussian fitting model based on the emission coefficient distribution, performing nonlinear least squares fitting, and determining the position of the maximum point and its corresponding maximum value according to the fitting result, determining the high temperature area and the low temperature area of ​​the arc cross section, and obtaining the emission coefficient distribution of the high temperature area of ​​the arc cross section and the emission coefficient distribution of the low temperature area of ​​the arc cross section;

[0026] Based on the physical property parameters corresponding to the arc characteristic spectrum line and according to the relationship curve between the emission coefficient and the temperature, the temperature values ​​of the high temperature area and the low temperature area of ​​the arc cross section are calculated by using the standard temperature method.

[0027] By implementing the embodiments of the present invention, it is possible to obtain the distribution of non-axisymmetric arc emission coefficients based on the characteristics of the plasma-MIG hybrid welding arc and utilize a small amount of projection characteristic spectral line intensity information to obtain a reliable plasma arc temperature field distribution, thereby effectively improving the accuracy and automation level of spectral diagnosis and laying a reliable foundation for subsequent arc spectral diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the specific implementation of the present invention or the technical solution in the prior art, the drawings required for use in the specific implementation or the description of the prior art are briefly introduced below.

[0029] Figure 1 A schematic diagram of the structure of a non-axisymmetric plasma arc temperature field calculation and processing system provided by an embodiment of the present invention;

[0030] Figure 2 A characteristic spectrum diagram of a composite arc provided by an embodiment of the present invention;

[0031] Figure 3 A plasma arc and MIG arc segmentation diagram provided in an embodiment of the present invention;

[0032] Figure 4 Iterative error evolution diagram provided by an embodiment of the present invention;

[0033] Figure 5 A stripe artifact image of the outer side of a plasma arc cross section provided by an embodiment of the present invention;

[0034] Figure 6 A cross-sectional view of a plasma arc after eliminating stripe artifacts provided by an embodiment of the present invention;

[0035] Figure 7 A pseudo-color image of the emission coefficient of a certain cross section of a plasma arc provided by an embodiment of the present invention;

[0036] Figure 8 A normalized distribution diagram of the emission coefficient of a certain cross section in the axial high temperature area of ​​the arc provided in an embodiment of the present invention;

[0037] Fig. 9 The double Gaussian fitting result of a certain row of a certain cross section of an arc provided by an embodiment of the present invention;

[0038] Fig.10 A distribution diagram of the emission coefficient of a certain row of a certain cross section of an arc provided by an embodiment of the present invention;

[0039] Fig.11 A distribution diagram of the emission coefficient of a high-temperature area of ​​a certain cross section of an arc provided by an embodiment of the present invention;

[0040] Fig.12 A distribution diagram of the emission coefficient of a low-temperature region of a certain cross section of an arc provided by an embodiment of the present invention;

[0041] Fig.13 A temperature field distribution diagram of a certain cross section of a plasma arc provided by an embodiment of the present invention;

[0042] Fig.14 A flowchart of a method for calculating and processing a non-axisymmetric plasma arc temperature field provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] It should be noted that, unless otherwise specified, the technical terms or scientific terms used in this application should have the common meanings understood by those skilled in the art to which the present invention belongs.

[0045] Embodiment 1:

[0046] Please refer to Figure 1 , an embodiment of the present invention provides a non-axisymmetric plasma arc temperature field calculation and processing system, the system includes a processing device, the processing device can be understood as an electronic device, the processing device includes:

[0047] An acquisition module is used to read the arc characteristic spectral line image and segment the plasma arc from the arc characteristic spectral line image to obtain integrated data;

[0048] Transformation recovery module for:

[0049] Discretizing the cross section of the plasma arc;

[0050] and calculating a two-dimensional spectral line tomography projection value vector and a projection coefficient matrix according to the integrated data;

[0051] The two-dimensional spectrum line tomography projection value vector and projection coefficient matrix obtained by the calculation are restored by using a synchronous iterative cimmino algorithm to obtain the emission coefficient distribution of the entire plasma arc;

[0052] The first processing module is used for:

[0053] The root mean square error is used to evaluate the iteration results to obtain the emission coefficient distribution with the minimum error;

[0054] Determine the interface between the high temperature region and the low temperature region in the arc axis according to the state characteristics of the emission coefficient distribution with the minimum error, and normalize the emission coefficients corresponding to the high / low temperature regions respectively;

[0055] The second processing module is used for:

[0056] Creating a double Gaussian fitting model based on the emission coefficient distribution, performing nonlinear least squares fitting, and determining the position of the maximum point and its corresponding maximum value according to the fitting result, determining the high temperature area and the low temperature area of ​​the arc cross section, and obtaining the emission coefficient distribution of the high temperature area of ​​the arc cross section and the emission coefficient distribution of the low temperature area of ​​the arc cross section;

[0057] Compute module for:

[0058] Based on the physical property parameters corresponding to the arc characteristic spectrum line and according to the relationship curve between the emission coefficient and the temperature, the temperature values ​​of the high temperature area and the low temperature area of ​​the arc cross section are calculated by using the standard temperature method.

[0059] During implementation, a pre-processing module is also included. After the acquisition module processes, the pre-processing module is used to dynamically translate the plasma arc position to ensure that the axes of the plasma arcs acquired at different angles coincide with each other. The specific steps are as follows:

[0060] Dynamically translate the plasma arc position so that the center of the characteristic spectrum line image coincides with the plasma arc axis;

[0061] The above preprocessing is performed on all welding arc characteristic spectral line images collected at intervals of 10° within a range of 180°, so that the plasma arc axes collected at different angles coincide with each other;

[0062] The plasma arc characteristic spectrum line data after the dynamic translation are integrated, and the image height data of the same characteristic spectrum line are sorted into a cell array according to the acquisition sequence, and the cell array is used as the integrated data.

[0063] Specifically, the steps are as follows:

[0064] Call the imread function to read the arc characteristic spectrum line image according to the specified path;

[0065] The spline cubic interpolation is used to obtain the boundary coordinates and realize the effective segmentation of plasma arc and MIG arc;

[0066] Call the ginput function to eliminate the adverse effects of noise such as dark current of the CMOS high-speed camera, nozzle and workpiece reflection on the spectral data;

[0067] Dynamically translate the plasma arc position so that the center of the characteristic spectrum line image coincides with the plasma arc axis;

[0068] Repeat the above steps to process all welding arc characteristic spectrum line images collected at intervals of 10° within a range of 180°;

[0069] The plasma arc characteristic spectral line data after the above dynamic translation are integrated, and the image height data of the same characteristic spectral line are sorted into a cell array according to the acquisition order. The cell array is the integrated data.

[0070] It should be noted that in this embodiment, a high-speed camera equipped with an Ar I 794.8nm narrow-band filter collects composite arc characteristic spectral line images and stores them in a specified path, and calls the imread function to read welding arc characteristic spectral line images collected at intervals of 10° within a range of 180° in the specified path. Since the arc characteristic spectral line images derived by the high-speed camera are in index mode, it is necessary to call the ind2gray function to convert the index mode image to grayscale mode, and force the data to be converted to double type for subsequent spectral data processing.

[0071] For the composite arc characteristic line image, which is composed of plasma arc and MIG arc, such as Figure 2 As shown. Before analyzing the data, the above two arcs need to be separated to achieve high-quality spectral diagnosis. Determine the position of the plasma arc in the composite arc characteristic spectrum line image. When the plasma arc is on the left side of the composite welding arc, it is recorded as 1, and when it is on the right side, it is recorded as -1. Call the size function to calculate the width of the characteristic spectrum line image. Call the ginput function to select 9 feature points from top to bottom at the intersection of the plasma arc and the MIG arc boundary. Use spline cubic spline interpolation according to the coordinates of the feature points to obtain the coordinates of the intersection of the two arcs to achieve effective segmentation of the arc. The results are shown in Figure 3 As shown, the right side is the plasma arc and the left side is the MIG arc. The black dots in the figure represent the selected feature points, and the white solid line represents the boundary between the plasma arc and the MIG arc obtained by cubic spline interpolation.

[0072] A 3*3 cross binary mask is constructed as a structural element to perform morphological opening and erosion operations on the above dynamically shifted images. For each pixel of the characteristic spectral line image, the medfilt2 function is called to perform a 3*3 neighborhood two-dimensional median filter to suppress the salt and pepper noise signal generated by the dark current of the CMOS photosensitive element of the high-speed camera. The maximum inter-class variance method is used to obtain the segmentation threshold of the arc and the background, and the im2bw function is called to convert the grayscale image into a binary image. The canny operator is used for edge detection to extract the coordinates of the plasma arc boundary away from the MIG arc, and to shield the noise signal generated by welding spatter and environmental interference outside the arc edge.

[0073] When the high-speed camera takes the arc characteristic spectrum image, the high-speed camera is facing the center of the plasma arc and the MIG arc. The welding arc characteristic spectrum image collected at intervals of 10° within the range of 180° causes the position of the plasma arc in the characteristic spectrum image to change with the shooting angle, which is not conducive to the subsequent multi-angle spectral data fusion. To this end, it is necessary to dynamically translate the plasma arc position so that the axes of the plasma arc collected at different angles coincide. According to the characteristic spectrum image width data obtained by the size function, the ceil function is called to calculate the center coordinate position of the characteristic spectrum image. Combined with the upper and left boundary points of the plasma arc selected by the ginput function, the difference between the center of the characteristic spectrum image and the axis of the plasma arc is calculated. When the difference between the center of the characteristic spectrum image and the axis of the plasma arc is greater than zero, a nested loop statement is used to translate the plasma arc data to the right as a whole so that the center of the characteristic spectrum image and the axis of the plasma arc coincide. When the difference between the center of the characteristic spectral line image and the axis of the plasma arc is less than zero, a nested loop statement is used to shift the plasma arc data to the left as a whole so that the center of the characteristic spectral line image and the axis of the plasma arc coincide with each other.

[0074] Repeat the above steps to process all welding arc characteristic spectral line images collected at intervals of 10° within a range of 180°, so that the plasma arc axes collected at different angles coincide with each other.

[0075] In order to facilitate the recovery of the emission coefficient later, it is necessary to integrate the characteristic spectral line data of the plasma arc after the above dynamic translation, and organize the image height data of the same characteristic spectral line into a cell array according to the acquisition order.

[0076] Further, the conversion recovery module performs discrete processing on the cross section of the plasma arc;

[0077] and calculating a two-dimensional spectral line tomography projection value vector and a projection coefficient matrix according to the integrated data;

[0078] The two-dimensional spectrum line tomography projection value vector and projection coefficient matrix obtained by calculation are restored by using a synchronous iterative cimmino algorithm to obtain the emission coefficient distribution of the entire plasma arc, specifically including sequentially performing the following steps on each height section of the plasma arc:

[0079] Discretize the plasma arc cross section and determine the number of rays;

[0080] Calculate the two-dimensional spectrum line tomography projection value vector according to the above integrated data, project the emission coefficient distribution mathematical model, and obtain the tomography projection coefficient matrix;

[0081] The relaxation factor, the maximum number of iterations and the iteration boundary constraints are set, and the synchronous iterative cimmino algorithm is used to restore the emission coefficient distribution.

[0082] Specifically, in order to ensure the accuracy of the recovery of the emission coefficient, the plasma arc cross section is discretized into 62*62 squares. Based on the above integrated data, the number of rays is determined by the number of pixels in the width direction of the arc characteristic spectrum line image taken by a high-speed camera.

[0083] The reshape function is called to convert the transposed integrated data into a column vector to obtain a two-dimensional spectral line tomography projection value vector, where the number of columns is the product of the number of pixels in the width direction of the arc characteristic line image and the number of high-speed camera shooting angles. Based on the number of discrete cross-section grids, the number of rays, and the number of high-speed camera shooting angles, the paralleltomo function is called to project the emission coefficient distribution mathematical model and calculate the tomography projection coefficient matrix.

[0084] The synchronous iterative cimmino algorithm is used to restore the emission coefficient distribution in two steps. In the first step, the number of iterations is set to 1. According to the two-dimensional spectral line tomography projection value vector and projection coefficient matrix obtained by the above calculation, the relaxation factor is obtained through preliminary trial calculation. In the second step, the maximum number of iterations is set, and the plasma arc cross-section emission coefficient is restored according to the relaxation factor obtained above. During the calculation process, in order to ensure the convergence of the iteration, the maximum number of iterations is set to 1000. In addition, since the emission coefficient will not have negative values, during the iteration process, the lower boundary of the iteration is limited to 0.

[0085] Repeat the above steps to process arc cross sections at different plasma heights to obtain the distribution of the entire plasma arc emission coefficient.

[0086] Furthermore, the first processing module uses a root mean square error to evaluate the iteration result to obtain a transmission coefficient distribution with a minimum error;

[0087] According to the state characteristics of the emission coefficient distribution with the minimum error, the interface between the high temperature area and the low temperature area in the arc axis is determined, and the emission coefficients corresponding to the high / low temperature areas are normalized respectively; specifically, the following steps are performed on each height section of the plasma arc in sequence:

[0088] Calculate the root mean square error of adjacent iteration results to obtain the emission coefficient distribution with the minimum error;

[0089] Eliminate stripe artifacts and improve the accuracy of emission coefficient recovery;

[0090] Draw a pseudo-color map of the emission coefficient distribution of each height section of the plasma arc to determine the interface between the high-temperature area and the low-temperature area of ​​the arc axis;

[0091] Normalization is performed according to the distribution characteristics of the emissivity coefficients in the high temperature area and the low temperature area of ​​the arc axis.

[0092] Specifically, the root mean square error is used to evaluate the results of each iteration, and the iterative error evolution results are as follows: Figure 4 As shown. As the iteration proceeds, the root mean square error of the adjacent iteration results is greatly reduced, and the calculated emission coefficient distribution is closer to the true value. The more iterations, the better. Too many iterations will significantly increase the iterative calculation time. Call the min function to calculate the minimum value of the root mean square error of adjacent iterations. Select the value with a root mean square error less than 10 -5 The iterative result at t is taken as the emission coefficient distribution of the plasma arc cross section of this layer.

[0093] For spectral line tomography, stripe artifacts are inevitably generated outside the plasma arc cross section, such as Figure 5 In order to further improve the accuracy of emission coefficient recovery, the artifact threshold is set to eliminate the influence of strip artifacts on the iterative results. The results are shown in Figure 6 shown.

[0094] Call imagesc to draw a pseudo-color distribution map of the emission coefficient of each height section of the plasma arc. According to the characteristics of the plasma arc temperature distribution, the arc temperature near the plasma compression nozzle is relatively high, which has exceeded the standard temperature corresponding to the Ar I794.8nm characteristic spectrum line. Therefore, near the arc section near the plasma compression nozzle, the arc center emission coefficient is relatively low, and as it gradually moves away from the arc center, the emission coefficient shows a trend of first increasing and then decreasing, such as Figure 7As shown. If the pseudo-color map of the emission coefficient distribution shows the above distribution characteristics, the height section is determined to be the arc axial high temperature area. As the distance from the plasma compression nozzle increases, the arc temperature gradually decreases. When the pseudo-color map of the emission coefficient distribution of a certain height section shows the highest arc center emission coefficient for the first time, and the emission coefficient shows a decreasing trend as the distance from the arc center increases, the height is determined to be the interface between the arc axial high temperature area and the arc low temperature area.

[0095] For the high temperature area of ​​the arc axial direction, normalization is performed based on the maximum value of the cross-sectional emission coefficient at that height, such as Figure 8 As shown in Figure 2, for the arc axial low temperature area, the normalization is performed based on the maximum value of the emission coefficient of all height sections in the entire arc axial low temperature area.

[0096] Further, the second processing module creates a double Gaussian fitting model based on the emission coefficient distribution, performs nonlinear least squares fitting, and determines the position of the maximum point and its corresponding maximum value according to the fitting result, determines the high temperature area and the low temperature area of ​​the arc cross section, and obtains the emission coefficient distribution of the high temperature area of ​​the arc cross section and the emission coefficient distribution of the low temperature area of ​​the arc cross section; specifically, the following steps are performed on each height section of the plasma arc in sequence:

[0097] Create a double Gaussian fitting model for the emission coefficient distribution, set the lower limit of the fitting parameters, and perform nonlinear least squares fitting;

[0098] Determine the position of the maximum point of each row of data in the height section and its corresponding maximum value according to the fitting results;

[0099] According to the above maximum value characteristics, the maximum value position information outside the high temperature area of ​​the arc cross section is cleared, and the alternative high temperature area of ​​the arc cross section is delineated;

[0100] According to the interface between the high temperature area and the low temperature area in the arc axis, the unreasonable area in the above-mentioned candidate high temperature area is eliminated to determine the high temperature area in the arc cross section;

[0101] According to the high temperature area of ​​the arc cross section, a low temperature area of ​​the arc cross section is determined;

[0102] According to the above division results of the high temperature area and the low temperature area of ​​the arc cross section, the emission coefficient distribution of the high temperature area of ​​the arc cross section and the emission coefficient distribution of the low temperature area of ​​the arc cross section are obtained.

[0103] Specifically, the fittype function is called to create a double Gaussian fitting model of the emission coefficient distribution. The model expression is:

[0104]

[0105] Where ε is the emission coefficient, A 1 , A 2is the amplitude of the emission coefficient distribution curve, b 1 、b 2 is the center of the curve, c 1 、c 2 is the standard deviation, and x is the horizontal axis. There are 6 fitting parameters in the formula A 1 , A 2 、b 1 、b 2 、c 1 、c 2 It is necessary to determine that the lower limits of the fitting parameters are set to -Inf, -Inf, 0, -Inf, -Inf and 0 respectively. Call the fit function to perform nonlinear least squares fitting. After the fitting is completed, call the feval function to calculate the fitting result, such as Fig. 9 shown.

[0106] The find, diff, and sign functions are nested to determine the location of the maximum point of each row of data and its corresponding maximum value. The calculation results have three situations: (1) The data of each point in the row are equal, there is no maximum value, and the calculation result returns an empty vector; (2) There is a maximum value in the row of data, and the calculation result returns a maximum value coordinate and its maximum value, such as Fig.10 (3) There are two maximum values ​​in this row of data, and the calculation result returns the coordinates of the two maximum values ​​and their maximum values. Repeat the above operation until all the row data of this height section are calculated.

[0107] If the maximum value position coordinates meet the following conditions, the maximum value position information is cleared: (1) the maximum value coordinates of the row are empty vectors; (2) there is only one maximum value coordinate in the row; (3) there are two maximum value coordinates in the row, but the maximum values ​​corresponding to the two maximum value coordinates are not both greater than 0.7. After the above calculations, the area whose maximum value position information is not cleared is defined as the alternative high temperature area of ​​the arc cross section, and each point in the alternative high temperature area is represented by 1.

[0108] According to the interface between the arc axial high temperature region and the low temperature region determined in the previous step, the high temperature region data of the height section above the interface between the arc axial high temperature region and the low temperature region are retained, and the high temperature region data of the height section below the interface are set to 0, and the unreasonable regions in the above-mentioned candidate high temperature regions are further eliminated to obtain the arc cross-section high temperature region, such as Fig.11 shown.

[0109] According to the arc cross section high temperature area, other points outside the high temperature area of ​​the height cross section are determined as arc cross section low temperature areas, such as Fig.12 shown.

[0110] According to the above-mentioned arc cross section high temperature area and low temperature area division results, the emission coefficient after normalization in the previous step is allocated to the corresponding partition to obtain the arc cross section high temperature area emission coefficient distribution and the arc cross section low temperature area emission coefficient distribution.

[0111] When this embodiment is used, the arc is processed into a high temperature area and a low temperature area in the arc axis, and a high temperature area and a low temperature area in the arc cross section, so that subsequent calculations are more accurate.

[0112] Further, the calculation module calculates the temperature values ​​of the high temperature area and the low temperature area of ​​the arc cross section by using the standard temperature method based on the physical property parameters corresponding to the characteristic spectrum of the arc and the relationship curve between the emission coefficient and the temperature; specifically, the following steps are performed on each height section of the plasma arc in sequence:

[0113] Set the physical property parameters of the characteristic spectrum line of Ar I 794.8nm;

[0114] Divide the curve of the relationship between the emissivity and temperature into a high temperature part and a low temperature part;

[0115] The interpolation function is called and the temperature values ​​of the high temperature area and the low temperature area of ​​the arc cross section are calculated using the standard temperature method.

[0116] Specifically, this embodiment uses the physical property parameters of the characteristic spectrum of Ar I 794.8nm, including: the transition probability is 1.86×10 7 s -1 , the statistical weight is 3, the high-level excitation energy is 13.28 eV, and the Planck constant is 6.63×10 -34 J·s, and the Boltzmann constant is 1.38×10 -23 J / K. The functional relationship between the emissivity, physical parameters and temperature is:

[0117]

[0118] Where ε is the emission coefficient, h is Planck's constant, v is the speed of light, A is the transition probability, g is the statistical weight, E is the high-level excitation energy, k is the Boltzmann constant, T is the temperature, n is the total particle density in the arc, and Z is the particle partition function when the plasma temperature is T. The values ​​of the particle density and the partition function are functions of temperature.

[0119] According to the functional relationship between the emissivity coefficient and the temperature, the curve of the relationship between the emissivity coefficient and the temperature is divided into a high temperature part and a low temperature part, with the temperature corresponding to the maximum value of the emissivity coefficient as the boundary.

[0120] Call the interp1 interpolation function, and bring the emissivity coefficient of the high temperature area of ​​the arc section in the previous step into the high temperature part of the curve of the relationship between the emissivity coefficient and temperature, and interpolate to obtain the temperature value of the high temperature area of ​​the arc section. Similarly, bring the emissivity coefficient of the low temperature area of ​​the arc section into the low temperature part of the curve of the relationship between the emissivity coefficient and temperature, and interpolate to obtain the temperature value of the low temperature area of ​​the arc section. The temperature field distribution of a certain height section of the arc is calculated as follows: Fig.13 shown.

[0121] Embodiment 2:

[0122] Based on the same inventive concept, the embodiment of the present invention also provides a method for calculating and processing a non-axisymmetric plasma arc temperature field, which is applied to a processing device such as Fig.14 As shown, the method includes:

[0123] S1, reading an arc characteristic spectral line image, and segmenting a plasma arc from the arc characteristic spectral line image to obtain integrated data;

[0124] S2, performing discretization processing on the cross section of the plasma arc;

[0125] S3, and calculating a two-dimensional spectral line tomography projection value vector and a projection coefficient matrix according to the integrated data;

[0126] S4, using a synchronous iterative cimmino algorithm to recover the two-dimensional spectral line tomography projection value vector and projection coefficient matrix obtained by the calculation to obtain the emission coefficient distribution of the entire plasma arc;

[0127] S5, using the root mean square error to evaluate the iteration results to obtain the transmission coefficient distribution with the minimum error;

[0128] S6, determining the boundary between the high temperature region and the low temperature region in the arc axis according to the state characteristics of the emission coefficient distribution with the minimum error, and normalizing the emission coefficients corresponding to the high / low temperature regions respectively;

[0129] S7, creating a double Gaussian fitting model based on the emission coefficient distribution, performing nonlinear least squares fitting, and determining the position of the maximum point and its corresponding maximum value according to the fitting result, determining the high temperature area and the low temperature area of ​​the arc cross section, and obtaining the emission coefficient distribution of the high temperature area of ​​the arc cross section and the emission coefficient distribution of the low temperature area of ​​the arc cross section;

[0130] S8, based on the physical parameters corresponding to the arc characteristic spectrum and according to the relationship curve between the emission coefficient and the temperature, the temperature values ​​of the high temperature area and the low temperature area of ​​the arc cross section are calculated by using the standard temperature method.

[0131] Furthermore, the method further comprises: dynamically translating the plasma arc position to ensure that the axes of the plasma arcs collected at different angles coincide with each other, the specific steps being:

[0132] Dynamically translate the plasma arc position so that the center of the characteristic spectrum line image coincides with the plasma arc axis;

[0133] The above preprocessing is performed on all welding arc characteristic spectral line images collected at intervals of 10° within a range of 180°, so that the plasma arc axes collected at different angles coincide with each other;

[0134] The plasma arc characteristic spectral line data after the above dynamic translation are integrated, and the image height data of the same characteristic spectral line are sorted into a cell array according to the acquisition sequence.

[0135] Furthermore, the cross section of the plasma arc is discretized; and a two-dimensional spectrum line tomography projection value vector and a projection coefficient matrix are calculated based on the integrated data;

[0136] The two-dimensional spectrum line tomography projection value vector and projection coefficient matrix obtained by calculation are restored by using a synchronous iterative cimmino algorithm to obtain the emission coefficient distribution of the entire plasma arc; specifically, the following steps are performed on each height section of the plasma arc in sequence:

[0137] Discretize the plasma arc cross section and determine the number of rays;

[0138] Calculate the two-dimensional spectrum line tomography projection value vector according to the above integrated data, project the emission coefficient distribution mathematical model, and obtain the tomography projection coefficient matrix;

[0139] The relaxation factor, the maximum number of iterations and the iteration boundary constraints are set, and the synchronous iterative cimmino algorithm is used to restore the emission coefficient distribution.

[0140] Furthermore, the root mean square error is used to evaluate the iteration results to obtain the emission coefficient distribution with the minimum error;

[0141] According to the state characteristics of the emission coefficient distribution with the minimum error, the interface between the high temperature area and the low temperature area in the arc axis is determined, and the emission coefficients corresponding to the high / low temperature areas are normalized respectively; specifically, the following steps are performed on each height section of the plasma arc in sequence:

[0142] Calculate the root mean square error of adjacent iteration results to obtain the emission coefficient distribution with the minimum error;

[0143] Eliminate stripe artifacts and improve the accuracy of emission coefficient recovery;

[0144] Draw a pseudo-color map of the emission coefficient distribution of each height section of the plasma arc, and determine the interface between the high-temperature area and the low-temperature area of ​​the arc axial direction according to the temperature distribution characteristics of the plasma arc;

[0145] Normalization is performed according to the distribution characteristics of the emissivity coefficients in the high temperature area and the low temperature area of ​​the arc axis.

[0146] Further, a double Gaussian fitting model based on the emission coefficient distribution is created, a nonlinear least squares fitting is performed, and the position of the maximum point and its corresponding maximum value are determined according to the fitting result, the high temperature area and the low temperature area of ​​the arc cross section are determined, and the emission coefficient distribution of the high temperature area of ​​the arc cross section and the emission coefficient distribution of the low temperature area of ​​the arc cross section are obtained; specifically, the following steps are performed on each height section of the plasma arc in sequence:

[0147] Create a double Gaussian fitting model for the emission coefficient distribution, set the lower limit of the fitting parameters, and perform nonlinear least squares fitting;

[0148] Determine the position of the maximum point of each row of data in the height section and its corresponding maximum value according to the fitting results;

[0149] According to the above maximum value characteristics, the maximum value position information outside the high temperature area of ​​the arc cross section is cleared, and the alternative high temperature area of ​​the arc cross section is delineated;

[0150] According to the interface between the high temperature area and the low temperature area in the arc axis, the unreasonable area in the above-mentioned candidate high temperature area is eliminated to determine the high temperature area in the arc cross section;

[0151] According to the high temperature area of ​​the arc cross section, a low temperature area of ​​the arc cross section is determined;

[0152] According to the above division results of the high temperature area and the low temperature area of ​​the arc cross section, the emission coefficient distribution of the high temperature area of ​​the arc cross section and the emission coefficient distribution of the low temperature area of ​​the arc cross section are obtained.

[0153] Furthermore, based on the physical parameters corresponding to the characteristic spectrum of the arc and according to the relationship curve between the emission coefficient and the temperature, the temperature values ​​of the high temperature area and the low temperature area of ​​the arc cross section are calculated by the standard temperature method, which specifically includes sequentially performing the following steps on each height cross section of the plasma arc:

[0154] In this embodiment, the physical property parameters of the characteristic spectrum line of Ar I 794.8nm are used;

[0155] Divide the curve of the relationship between the emissivity and temperature into a high temperature part and a low temperature part;

[0156] The interpolation function is called and the temperature values ​​of the high temperature area and the low temperature area of ​​the arc cross section are calculated using the standard temperature method.

[0157] Specifically, this embodiment uses the physical property parameters of the characteristic spectrum of Ar I 794.8nm, including: the transition probability is 1.86×10 7 s -1 , the statistical weight is 3, the high-level excitation energy is 13.28 eV, and the Planck constant is 6.63×10 -34 J·s, and the Boltzmann constant is 1.38×10 -23 J / K. The functional relationship between the emissivity, physical parameters and temperature is:

[0158]

[0159] Where ε is the emission coefficient, h is Planck's constant, v is the speed of light, A is the transition probability, g is the statistical weight, E is the high-level excitation energy, k is the Boltzmann constant, T is the temperature, n is the total particle density in the arc, and Z is the particle partition function when the plasma temperature is T. The values ​​of the particle density and the partition function are functions of temperature.

[0160] According to the functional relationship between the emissivity coefficient and the temperature, the curve of the relationship between the emissivity coefficient and the temperature is divided into a high temperature part and a low temperature part, with the temperature corresponding to the maximum value of the emissivity coefficient as the boundary.

[0161] Call the interp1 interpolation function, bring the emissivity coefficient of the high temperature area of ​​the arc section in the previous step into the high temperature part of the curve of the relationship between the emissivity coefficient and temperature, and interpolate to obtain the temperature value of the high temperature area of ​​the arc section. Similarly, bring the emissivity coefficient of the low temperature area of ​​the arc section into the low temperature part of the curve of the relationship between the emissivity coefficient and temperature, and interpolate to obtain the temperature value of the low temperature area of ​​the arc section.

[0162] According to the characteristics of the plasma-MIG hybrid welding arc and based on the principle of tomography, the present invention can obtain the distribution of non-axisymmetric arc emission coefficients and obtain reliable plasma arc temperature field distribution using a small amount of projection characteristic spectral line intensity information, thereby effectively improving the accuracy and automation level of spectral diagnosis and laying a reliable foundation for subsequent arc spectral diagnosis.

[0163] It should be noted that for more specific workflows of the method embodiments, please refer to the aforementioned method embodiment part, which will not be repeated here.

[0164] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or substitutions within the technical scope disclosed by the present invention, and these modifications or substitutions should be included in the protection scope of the present invention.

Claims

1. A non-axisymmetric plasma arc temperature field calculation and processing system, characterized in that: The system includes a processing device, the processing device including: An acquisition module is used to read the arc characteristic spectral line image and segment the plasma arc from the arc characteristic spectral line image to obtain integrated data; Transformation recovery module for: Discretizing the cross section of the plasma arc; and calculating a two-dimensional spectral line tomography projection value vector and a projection coefficient matrix according to the integrated data; The two-dimensional spectrum line tomography projection value vector and projection coefficient matrix obtained by the calculation are restored by using a synchronous iterative cimmino algorithm to obtain the emission coefficient distribution of the entire plasma arc; The first processing module is used for: The root mean square error is used to evaluate the iteration results to obtain the emission coefficient distribution with the minimum error; Determine the interface between the high temperature region and the low temperature region in the arc axis according to the state characteristics of the emission coefficient distribution with the minimum error, and normalize the emission coefficients corresponding to the high / low temperature regions respectively; The second processing module is used for: Creating a double Gaussian fitting model based on the emission coefficient distribution, performing nonlinear least squares fitting, and determining the position of the maximum point and its corresponding maximum value according to the fitting result, determining the high temperature area and the low temperature area of ​​the arc cross section, and obtaining the emission coefficient distribution of the high temperature area of ​​the arc cross section and the emission coefficient distribution of the low temperature area of ​​the arc cross section; Compute module for: Based on the physical property parameters corresponding to the arc characteristic spectrum line and according to the relationship curve between the emission coefficient and the temperature, the temperature values ​​of the high temperature area and the low temperature area of ​​the arc cross section are calculated by using the standard temperature method.

2. A non-axisymmetric plasma arc temperature field calculation and processing system according to claim 1, characterized in that: It also includes a pre-processing module, which is used to dynamically translate the position of the plasma arc to ensure that the axes of the plasma arcs collected at different angles coincide with each other. The specific steps are as follows: Dynamically translate the plasma arc position so that the center of the characteristic spectrum line image coincides with the plasma arc axis; The above dynamic translation processing is performed on all welding arc characteristic spectrum line images collected at intervals of 10° within a range of 180°, so that the plasma arc axes collected at different angles coincide with each other; The plasma arc characteristic spectrum line data after the dynamic translation are integrated, and the image height data of the same characteristic spectrum line are sorted into a cell array according to the acquisition sequence, and the cell array is used as the integrated data.

3. A non-axisymmetric plasma arc temperature field calculation and processing system according to claim 2, characterized in that: The conversion recovery module specifically includes sequentially performing the following steps on each height section of the plasma arc: Discretize the plasma arc cross section and determine the number of rays; Calculating a two-dimensional spectral line tomography projection value vector according to the integrated data, projecting the emission coefficient distribution mathematical model, and obtaining a tomography projection coefficient matrix; The relaxation factor, the maximum number of iterations and the iteration boundary constraints are set, and the synchronous iterative cimmino algorithm is used to restore the emission coefficient distribution.

4. The non-axisymmetric plasma arc temperature field calculation and processing system according to claim 1, characterized in that: The first processing module specifically includes sequentially performing the following steps on each height section of the plasma arc: Calculate the root mean square error of adjacent iteration results to obtain the emission coefficient distribution with the minimum error; Eliminate stripe artifacts and improve the accuracy of emission coefficient recovery; Draw a pseudo-color map of the emission coefficient distribution of each height section of the plasma arc, and determine the interface between the high-temperature area and the low-temperature area of ​​the arc axial direction according to the temperature distribution characteristics of the plasma arc; Normalization is performed according to the distribution characteristics of the emissivity coefficients in the high temperature area and the low temperature area of ​​the arc axis.

5. The non-axisymmetric plasma arc temperature field calculation and processing system according to claim 1, characterized in that: The second processing module specifically includes sequentially performing the following steps on each height section of the plasma arc: Create a double Gaussian fitting model for the emission coefficient distribution, set the lower limit of the fitting parameters, and perform nonlinear least squares fitting; Determine the maximum point position of each row of data in the height section and its corresponding maximum value according to the fitting results; According to the above maximum value characteristics, the maximum value position information outside the high temperature area of ​​the arc cross section is cleared, and the alternative high temperature area of ​​the arc cross section is delineated; According to the interface between the high temperature area and the low temperature area in the arc axis, the unreasonable area in the above-mentioned candidate high temperature area is eliminated to determine the high temperature area in the arc cross section; According to the high temperature area of ​​the arc cross section, a low temperature area of ​​the arc cross section is determined; According to the above division results of the high temperature area and the low temperature area of ​​the arc cross section, the emission coefficient distribution of the high temperature area of ​​the arc cross section and the emission coefficient distribution of the low temperature area of ​​the arc cross section are obtained.

6. A method for calculating and processing the temperature field of a non-axisymmetric plasma arc, characterized in that: Applied to a processing device, the method comprises: Reading the arc characteristic spectral line image, and segmenting the plasma arc from the arc characteristic spectral line image to obtain integrated data; Discretizing the cross section of the plasma arc; and calculating a two-dimensional spectral line tomography projection value vector and a projection coefficient matrix according to the integrated data; The two-dimensional spectrum line tomography projection value vector and projection coefficient matrix obtained by the calculation are restored by using a synchronous iterative cimmino algorithm to obtain the emission coefficient distribution of the entire plasma arc; The root mean square error is used to evaluate the iteration results to obtain the emission coefficient distribution with the minimum error; Determine the interface between the high temperature region and the low temperature region in the arc axis according to the state characteristics of the emission coefficient distribution with the minimum error, and normalize the emission coefficients corresponding to the high / low temperature regions respectively; Creating a double Gaussian fitting model based on the emission coefficient distribution, performing nonlinear least squares fitting, and determining the position of the maximum point and its corresponding maximum value according to the fitting result, determining the high temperature area and the low temperature area of ​​the arc cross section, and obtaining the emission coefficient distribution of the high temperature area of ​​the arc cross section and the emission coefficient distribution of the low temperature area of ​​the arc cross section; Based on the physical property parameters corresponding to the arc characteristic spectrum line and according to the relationship curve between the emission coefficient and the temperature, the temperature values ​​of the high temperature area and the low temperature area of ​​the arc cross section are calculated by using the standard temperature method.

7. A method for calculating and processing a non-axisymmetric plasma arc temperature field according to claim 6, characterized in that: The method further comprises: Dynamically translate the plasma arc position to ensure that the plasma arc axes collected at different angles coincide. The specific steps are as follows: Dynamically translate the plasma arc position so that the center of the characteristic spectrum line image coincides with the plasma arc axis; The above dynamic translation processing is performed on all welding arc characteristic spectrum line images collected at intervals of 10° within a range of 180°, so that the plasma arc axes collected at different angles coincide with each other; The plasma arc characteristic spectrum line data after the dynamic translation are integrated, and the image height data of the same characteristic spectrum line are sorted into a cell array according to the acquisition sequence, and the cell array is used as the integrated data.

8. The method for calculating and processing the temperature field of a non-axisymmetric plasma arc according to claim 7, characterized in that: Discretizing the cross section of the plasma arc; and calculating a two-dimensional spectrum line tomography projection value vector and a projection coefficient matrix according to the integrated data; The two-dimensional spectrum line tomography projection value vector and projection coefficient matrix obtained by calculation are restored by using a synchronous iterative cimmino algorithm to obtain the emission coefficient distribution of the entire plasma arc; specifically, the following steps are performed on each height section of the plasma arc in sequence: Discretize the plasma arc cross section and determine the number of rays; Calculating a two-dimensional spectral line tomography projection value vector according to the integrated data, projecting the emission coefficient distribution mathematical model, and obtaining a tomography projection coefficient matrix; The relaxation factor, the maximum number of iterations and the iteration boundary constraints are set, and the synchronous iterative cimmino algorithm is used to restore the emission coefficient distribution.

9. The method for calculating and processing the temperature field of a non-axisymmetric plasma arc according to claim 6, characterized in that: The root mean square error is used to evaluate the iteration results to obtain the emission coefficient distribution with the minimum error; According to the state characteristics of the emission coefficient distribution with the minimum error, the interface between the high temperature area and the low temperature area in the arc axis is determined, and the emission coefficients corresponding to the high / low temperature areas are normalized respectively; specifically, the following steps are performed on each height section of the plasma arc in sequence: Calculate the root mean square error of adjacent iteration results to obtain the emission coefficient distribution with the minimum error; Eliminate stripe artifacts and improve the accuracy of emission coefficient recovery; Draw a pseudo-color map of the emission coefficient distribution of each height section of the plasma arc, and determine the interface between the high-temperature area and the low-temperature area of ​​the arc axial direction according to the temperature distribution characteristics of the plasma arc; Normalization is performed according to the distribution characteristics of the emissivity coefficients in the high temperature area and the low temperature area of ​​the arc axis.

10. The method for calculating and processing the temperature field of a non-axisymmetric plasma arc according to claim 6, characterized in that: A double Gaussian fitting model based on the emission coefficient distribution is created, a nonlinear least squares fitting is performed, and the position of the maximum point and its corresponding maximum value are determined according to the fitting result, the high temperature area and the low temperature area of ​​the arc cross section are determined, and the emission coefficient distribution of the high temperature area of ​​the arc cross section and the emission coefficient distribution of the low temperature area of ​​the arc cross section are obtained; specifically, the following steps are performed on each height section of the plasma arc in sequence: Create a double Gaussian fitting model for the emission coefficient distribution, set the lower limit of the fitting parameters, and perform nonlinear least squares fitting; Determine the maximum point position of each row of data in the height section and its corresponding maximum value according to the fitting results; According to the above maximum value characteristics, the maximum value position information outside the high temperature area of ​​the arc cross section is cleared, and the alternative high temperature area of ​​the arc cross section is delineated; According to the interface between the high temperature area and the low temperature area in the arc axis, the unreasonable area in the above-mentioned candidate high temperature area is eliminated to determine the high temperature area in the arc cross section; According to the high temperature area of ​​the arc cross section, a low temperature area of ​​the arc cross section is determined; According to the above division results of the high temperature area and the low temperature area of ​​the arc cross section, the emission coefficient distribution of the high temperature area of ​​the arc cross section and the emission coefficient distribution of the low temperature area of ​​the arc cross section are obtained.

Images