Method for evaluating welding flux uniformity in real time in production of smelting welding flux

Abstract

The invention discloses a welding flux uniformity real-time evaluation method in smelting welding flux production, and relates to the technical field of data processing, and the method comprises the following steps: constructing particle internal melt solidification impedance layer distribution in a thermal radiation image; identifying the composition segregation boundary in the flux particles according to the distribution of the melt solidification impedance layer; generating a segregation position mark based on the component segregation boundary and the thermal radiation image; the segregation position marks and the microstructure evolution process of the welding flux particles are subjected to time sequence corresponding verification, and a causal chain is established; when the causal chain is broken, the distribution of a melt solidification impedance layer is adjusted according to the recapture of heat conduction shunting in the thermal radiation image; based on the adjusted distribution of the melt solidification impedance layer, the component uniformity of welding flux particles is determined; according to the method, the thermal radiation characteristics of the welding flux particles are monitored, and the dynamic evolution of the melt solidification impedance layer and the component segregation is accurately analyzed, so that the high-precision evaluation of the component uniformity of the welding flux particles is realized.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, specifically a method for real-time evaluation of flux uniformity in the production of smelting flux. Background Technology

[0002] As a key material in welding processes, the uniformity of the composition of fused flux directly affects weld quality, welding stability, and the performance of the final product. This is especially true for fused flux used in submerged arc welding, where differences in the melting and solidification rates of different components during smelting easily lead to localized component segregation within the particles. Currently, flux particle composition uniformity is primarily assessed offline through sampling analysis or post-weld metallographic examination, which cannot achieve real-time detection. This offline assessment method has significant lag and randomness, failing to promptly identify and control factors leading to component segregation in the flux smelting process, thus affecting the consistency and quality stability of fused flux production.

[0003] Furthermore, most existing methods for evaluating flux uniformity are based on post-weld macroscopic properties or laboratory metallographic observations, failing to consider the kinetic evolution of flux particle microstructure formation during the initial solidification stage. They also lack sophisticated real-time monitoring and analysis methods to correlate thermophysical phenomena during the melting process with microstructure composition. This deficiency makes it difficult for traditional methods to accurately capture key transient information during flux particle solidification (such as changes in heat conduction paths during the initial solidification stage and the formation mechanism of the internal solidification resistance layer), resulting in insufficient reliability and accuracy of the evaluation results.

[0004] Therefore, there is an urgent need for an evaluation method that can monitor and accurately analyze the solidification process of the melt inside flux particles in real time and can quickly locate the component segregation region based on microscopic solidification characteristics. This would enable high-precision real-time evaluation of the uniformity of flux particle composition, guide and optimize flux production processes, and significantly improve the stability, consistency and reliability of flux quality. Summary of the Invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes a method for real-time evaluation of flux uniformity in the production of smelting flux.

[0006] To achieve the above objectives, the present invention provides a method for real-time evaluation of flux uniformity in the production of smelting flux, comprising: Acquire thermal radiation images of flux particles at the moment of exiting the furnace; construct the distribution of the melt solidification resistance layer inside the particles by the heat conduction shunting phenomenon on the particle surface in the thermal radiation images. The compositional segregation boundaries inside flux particles are identified based on the spatial fragmentation pattern of the melt solidification impedance layer distribution; segregation location markers are generated based on the spatial overlap between the compositional segregation boundaries and the temperature change trajectory in the thermal radiation image. The segregation location markers and the microstructure evolution process of flux particles were time-sequentially verified to establish a causal chain between compositional segregation and microstructure changes. When the causal chain breaks, the distribution of the melt solidification resistance layer is adjusted according to the recapture of heat conduction shunting in the thermal radiation image. The compositional uniformity level of flux particles is determined based on the adjusted melt solidification impedance layer distribution, and the uniformity test results are output.

[0007] Furthermore, the construction of the melt solidification resistance layer distribution inside the particle through the heat conduction shunting phenomenon on the particle surface in the thermal radiation image includes: Identify the main heat transfer channels on the surface of flux particles in thermal radiation images, and mark the areas with the largest temperature gradient in the temperature field on the particle surface as the main heat transfer channels; Track the heat conduction diversion phenomenon that occurs during the propagation of the main heat transfer channel. When the main channel disperses into multiple conduction branches at a certain location, mark that location as the heat conduction diversion point. The location of the impedance layer during the solidification process of the melt inside the particle can be inferred by the spatial distribution law of the heat conduction diversion point. Each heat conduction diversion point corresponds to the boundary position of a solidification impedance layer. The boundary positions of adjacent solidification impedance layers are connected to form the spatial outline of the impedance layer, thus constructing the distribution of the melt solidification impedance layer.

[0008] Furthermore, the identification of the heat conduction diversion phenomenon is based on the geometric shape change of the main heat transfer channel. When the width of the main channel increases and disperses into multiple narrow channels during the propagation process, the location of the shape change is determined as the heat conduction diversion point.

[0009] Further, the generation of segregation location markers includes: Analyze the spatial continuity of the impedance layer in the solidification impedance layer distribution of the melt to identify the location of spatial breaks in the impedance layer. The location of the fracture in the impedance layer space is taken as the location where component separation occurs during the solidification process of the melt, and the fracture location corresponds to the boundary line of different component regions inside the particle. Connecting adjacent fracture locations forms a complete boundary line network, which is then used to define the component segregation boundaries within the flux particles. Extract the temperature change trajectory of the region corresponding to the component segregation boundary in the thermal radiation image, and combine the spatial coordinates of the segregation boundary with the temperature change trajectory to generate segregation location markers.

[0010] Furthermore, the identification of the spatial break in the impedance layer is based on the geometric discontinuity of the impedance layer profile. When the impedance layer profile is geometrically discontinuous or missing during spatial extension, the discontinuity location is determined as the location of the spatial break in the impedance layer.

[0011] Furthermore, the extraction of the temperature change trajectory is based on the temporal evolution pattern of the temperature field in the thermal radiation image. When the temperature of a certain region shows a continuous decrease or fluctuation in the time series, the temperature evolution path of that region is taken as the temperature change trajectory.

[0012] Furthermore, the step of verifying the temporal correspondence between segregation location markers and the microstructure evolution process of flux particles to establish a causal chain between component segregation and microstructure changes includes: To obtain information on the microstructure of flux particles at different times during solidification and to identify the evolution stages of the microstructure; Establish the temporal correspondence between the formation time of component segregation boundaries and the microstructure evolution stages, and analyze the temporal synchronization between segregation occurrence and tissue changes; The strength of the causal relationship between component segregation and microorganism evolution is assessed based on the degree of consistency in temporal synchronization. A causal chain between component segregation and organizational change was established based on the assessment results of the strength of causal association.

[0013] Furthermore, the microstructure evolution stages include primary phase precipitation, eutectic reaction, and solid-state phase transformation. Microstructure information is obtained through metallographic analysis of flux particles, and the identification of evolution stages is based on the formation and transformation characteristics of different phase structures.

[0014] Furthermore, the adjustment of the melt solidification resistance layer distribution based on the recapture of heat conduction shunting in the thermal radiation image includes: Identify the time points at which the causal chain of component segregation and tissue changes breaks down; By reanalyzing the occurrence pattern of heat conduction shunting in thermal radiation images at the time point of chain breakage, the spatial evolution trajectory of the shunting phenomenon is traced. The location distribution of heat conduction shunting points was corrected based on the reanalysis results of the spatial evolution trajectory of the shunting phenomenon. Based on the corrected location of the heat conduction diversion point, the spatial profile of the solidification resistance layer is reconstructed, and the distribution of the melt solidification resistance layer is adjusted.

[0015] Furthermore, the identification of chain breakage is based on the degree of mismatch between the formation time of component segregation and the evolution time of microstructure. When the difference between the formation time of the segregation boundary and the occurrence time of the corresponding microstructure evolution stage exceeds the time cycle of the flux particle solidification process, it is determined to be a causal chain breakage.

[0016] Compared with the prior art, the beneficial effects of the present invention are: This invention acquires thermal radiation images at the moment flux particles exit the furnace and constructs the melt solidification impedance layer distribution by utilizing the shunting phenomenon of heat conduction on the particle surface. This allows for real-time and accurate reflection of the microstructure evolution process of the melt in the early stage of solidification within the flux particles. It effectively overcomes the problem that traditional offline detection methods cannot capture the initial dynamic characteristics of the solidification process in real time, and realizes real-time monitoring of the flux production process.

[0017] This invention analyzes the geometric continuity interruption characteristics in the spatial distribution of the solidification impedance layer to accurately identify the spatial boundaries of melt component segregation inside flux particles, and combines this with spatial matching based on temperature change trajectories. This effectively improves the accuracy and real-time performance of identifying component segregation regions inside flux particles, overcoming the shortcomings of traditional methods that rely solely on post-conductivity metallographic testing, which leads to detection lag and position misjudgment.

[0018] This invention establishes a temporal causal chain between segregation location markers and microstructure evolution, and dynamically adjusts the spatial distribution of the solidification impedance layer based on the chain breakage. This ensures the consistency and reliability between component segregation boundaries and microstructure changes, thereby significantly improving the accuracy and robustness of real-time evaluation of flux particle composition uniformity. It provides precise data support for optimizing flux smelting production processes and ensuring flux quality stability. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the method of the present invention. Detailed Implementation

[0021] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Please see Figure 1 This embodiment provides a method for real-time evaluation of flux uniformity in flux production, including: S101: Acquire thermal radiation images of flux particles at the moment of exiting the furnace; construct the distribution of the melt solidification resistance layer inside the particles by the thermal conduction diversion phenomenon on the particle surface in the thermal radiation images. It should be noted that in this embodiment, the flux particles exhibit significant thermal radiation on their surface the instant they are discharged from the melting furnace. This embodiment uses an infrared thermal imager to capture thermal radiation images of the flux particles at the moment they exit the furnace, for subsequent analysis of the solidification process of the melt inside the particles.

[0023] In practice, the infrared thermal imager should be installed directly above the flux particles exiting the furnace, ensuring that images are acquired immediately after the flux particles enter the instrument's field of view to accurately capture the real-time thermal radiation distribution on the particle surface. The infrared thermal radiation image of the flux particles at the moment of exiting the furnace is recorded in grayscale value form and converted into true temperature field data according to the equipment calibration parameters. The specific conversion formula is as follows:

[0024] In the formula: Indicates the coordinate position of the flux particle surface The actual temperature value at that location; Indicates the position in the infrared thermal radiation image The grayscale value at that location; These are the calibration coefficients provided by the infrared thermal imager at the factory, and the specific values ​​are determined according to the factory calibration manual of the thermal imager.

[0025] In practice, the above steps are used to obtain high-precision temperature field data of flux particles at the moment they exit the furnace, which is then used to analyze the heat conduction and diversion phenomenon on the particle surface.

[0026] In the specific implementation process, the construction of the melt solidification resistance layer distribution inside the particle through the heat conduction shunting phenomenon on the particle surface in the thermal radiation image includes: Identify the main heat transfer channels on the surface of flux particles in thermal radiation images, and mark the areas with the largest temperature gradient in the temperature field on the particle surface as the main heat transfer channels; It is understandable that heat transfer on the surface of flux particles exhibits a clear spatial directionality. This embodiment first calculates the spatial gradient of the aforementioned temperature field data to identify the main heat transfer channels on the particle surface. Specifically, it uses the two-dimensional temperature field spatial gradient calculation formula:

[0027] In the formula: This represents the spatial gradient value of the temperature field at the location coordinates; These represent the temperature field in the horizontal direction ( Direction) and vertical direction ( The partial derivative of the direction is calculated using the central difference method, and the formula is as follows:

[0028] In the formula: , This represents the actual physical resolution of the image space, i.e., the spatial distance between pixels in the image.

[0029] For example, after obtaining the above-mentioned spatial gradient distribution of the temperature field, this embodiment uses a local maximum search algorithm, such as a non-maximum suppression algorithm, to automatically identify and mark the region with the largest and continuous temperature gradient, and determine it as the main heat transfer channel on the surface of the flux particles.

[0030] Track the heat conduction diversion phenomenon that occurs during the propagation of the main heat transfer channel. When the main channel disperses into multiple conduction branches at a certain location, mark that location as the heat conduction diversion point. It should be understood that during the cooling process of flux particles, due to the non-uniformity of the internal composition and temperature field of the particles, the main heat transfer channel on the surface may exhibit dispersion during spatial propagation. This embodiment utilizes image refinement technology to perform skeletonization analysis on the main channel and calculates the local width changes of the main channel to identify heat conduction diversion phenomena. The specific implementation method is as follows: First, the identified main channel regions are thinned to obtain skeleton curves with a single pixel width. Then, skeleton analysis is used to calculate the local width of the main channel, with the specific formula defined as follows: In the formula: Indicates the local width of the main channel; L represents the area of ​​the main channel within the corresponding region; L represents the length of the skeleton line of the corresponding region.

[0031] Specifically, the identification of the heat conduction diversion phenomenon is based on the geometric shape change of the main heat transfer channel. When the width of the main channel increases and disperses into multiple narrow channels during the propagation process, the location of the shape change is determined as the heat conduction diversion point. It should be noted that this embodiment identifies heat conduction shunting points by monitoring changes in the local width of the main channel. When the width of the main channel ( When the heat conduction branch point increases and splits into two or more clearly identifiable narrow branches at a certain location along the spatial propagation direction, that location is determined as the heat conduction branch point. For example, the specific determination condition can be set as follows: when the local width value increases by 20% compared to the initial channel width along the propagation path. When the main channel skeleton line after this position splits from a continuous channel into at least two independent channel branches in the propagation direction, the spatial position is marked as the heat conduction split point and its spatial coordinate position is recorded. Specifically, the criterion for determining channel splitting is: consecutive pixels of the main channel skeleton line no longer form a single path after this position, but instead show at least two path branches, and the included angle between any two path branches is... satisfy (The included angle threshold can be determined based on actual experiments). At the same time, when the independent extension length of each path branch in space is greater than twice the initial average width of the main channel, it is determined to be a channel split.

[0032] The location of the impedance layer during the solidification process of the melt inside the particle can be inferred by the spatial distribution law of the heat conduction diversion point. Each heat conduction diversion point corresponds to the boundary position of a solidification impedance layer. It should be noted that during the solidification process of the melt inside the flux particles, differences in composition or temperature in different regions can lead to significant heat conduction diversion phenomena in the heat transfer path. Based on the spatial distribution of the heat conduction diversion points identified above, this embodiment infers the location of the impedance layer during the solidification process inside the particles.

[0033] In the specific implementation process, the set of spatial coordinates of each heat conduction split point obtained in the aforementioned steps is first denoted as:

[0034] In the formula: This represents the set of spatial coordinates of all identified heat conduction split points; The coordinates of the i-th heat conduction shunt point represent the spatial location coordinates; n represents the total number of heat conduction shunt points.

[0035] It should be understood that each heat conduction diversion point corresponds to the specific location of the impedance layer boundary during the solidification process of the flux particles, that is, the melt solidification interface caused by the difference in thermal conductivity or solidification rate in local areas during the solidification process.

[0036] Furthermore, to accurately represent the spatial structure of the melt solidification resistance layer inside the particles, this embodiment analyzes the three-dimensional coordinate distribution of the splitting point; specifically, to obtain the three-dimensional spatial coordinates required for subsequent analysis... This embodiment requires reconstructing a three-dimensional model of flux particles based on multi-view infrared thermal radiation images. It should be noted that the specific steps for multi-view infrared image reconstruction described here are as follows: First, at the moment the flux particles exit the furnace, multiple infrared thermal imagers are arranged at different spatial orientations of the particle exit port to simultaneously acquire multiple two-dimensional thermal radiation images from different perspectives. Then, based on the multi-view two-dimensional thermal radiation images, a three-dimensional surface model of the flux particles is obtained through three-dimensional reconstruction algorithms (such as spatial geometric projection transformation, three-dimensional spatial coordinate mapping, and image fusion algorithms). The temperature data from the corresponding two-dimensional thermal radiation images are then mapped onto the constructed three-dimensional surface model, thereby clarifying the three-dimensional temperature field distribution on the flux particle surface. Specifically, the three-dimensional temperature field distribution function is expressed as:

[0037] In the formula: Represents the spatial coordinates of the flux particle surface Temperature value at; This represents the mapping function from a two-dimensional thermal radiation image to a three-dimensional surface temperature field, which can be achieved using a spatial mapping and interpolation fusion algorithm. This represents two-dimensional thermal radiation image data collected from different perspectives.

[0038] Connecting the boundary positions of adjacent solidification impedance layers forms the spatial outline of the impedance layer, thus constructing the distribution of the melt solidification impedance layer. For example, in this embodiment, the three-dimensional spatial coordinates of the heat conduction diversion point obtained above are used to connect the boundary positions of each impedance layer by interpolation method to form the spatial outline of the impedance layer, thereby constructing a complete spatial distribution of the melt solidification impedance layer.

[0039] Specifically, this embodiment uses the Radial Basis Function (RBF) interpolation algorithm to construct the spatial profile between heat conduction split points. The RBF interpolation formula is as follows:

[0040] In the formula: This is the spatial profile surface function of the melt solidification impedance layer constructed by interpolation; The undetermined weighting coefficients in the interpolation calculation are obtained using the method of undetermined coefficients. This is the shape parameter in the radial basis function, and its specific value is determined according to the actual requirements of the interpolation fitting accuracy. Position to be interpolated Euclidean distance to the i-th heat conduction shunt point.

[0041] It is understandable that the spatial contour function constructed through the above interpolation... It can clearly describe the spatial distribution of the solidification resistance layer inside the flux particles, and use this as an important basis for judging the uniformity of the internal composition of the particles.

[0042] S102: Identify the compositional segregation boundaries inside flux particles based on the spatial fragmentation pattern of the melt solidification impedance layer distribution; generate segregation location markers based on the spatial overlap between the compositional segregation boundaries and the temperature change trajectory in the thermal radiation image. It should be noted that the spatial distribution of the resistive layer of the melt solidification inside the flux particles reflects the differences in local composition during the solidification process of the flux particles. When there is a significant break in the spatial continuity of the resistive layer, the break point represents the interface between different melt components inside the particle, and is called the compositional segregation boundary.

[0043] In the specific implementation process, this embodiment identifies the spatial dislocation position in the melt solidification impedance layer distribution based on the spatial distribution characteristics of the melt solidification impedance layer constructed in step S101 above, so as to determine the spatial position of the component segregation boundary, and performs spatial overlap analysis by combining the temperature change trajectory information of the corresponding area in the thermal radiation image, and finally determines the component segregation position marker.

[0044] In the specific implementation process, the generation of segregation location markers includes: Analyze the spatial continuity of the impedance layer in the solidification impedance layer distribution of the melt to identify the location of spatial breaks in the impedance layer. Specifically, the identification of the spatial break in the impedance layer is based on the geometric discontinuity of the impedance layer profile. When the impedance layer profile is geometrically discontinuous or missing during spatial extension, the discontinuity location is determined as the location of the spatial break in the impedance layer.

[0045] It should be noted that, in this embodiment, the spatial profile function of the melt solidification resistance layer obtained in step S101 above is used. Spatial continuity analysis is performed. Specifically, this is done by calculating the impedance layer profile function. The spatial gradient field is used to detect the continuity of the impedance layer profile in three-dimensional space. The formula for calculating the spatial gradient is:

[0046] In the formula: These are the impedance layer spatial profile functions in three-dimensional space. The spatial partial derivatives in the direction are obtained by calculating the central difference method.

[0047] Furthermore, to ensure consistency in determining the location of spatial breaks in the impedance layer, this embodiment requires that the following two conditions be met simultaneously when identifying the location of geometrical interruption in the impedance layer profile: Condition 1: Impedance layer profile function at the above spatial location The absolute value of the spatial gradient exceeds the set continuity threshold. :

[0048] Condition 2: At the location satisfying Condition 1, there is a significant geometric connection interruption or missing point along the main propagation direction of the impedance layer profile; in specific implementation, this is determined by the Euclidean distance between two adjacent points along the propagation direction of the impedance layer profile. Exceeding the set distance threshold Judgment, that is:

[0049] In the formula: This is the current spatial location; This represents the next adjacent spatial position along the main propagation direction of the impedance layer profile. The distance threshold for determining geometrical discontinuity in spatial continuity is determined through actual statistical analysis.

[0050] The location of the fracture in the impedance layer space is taken as the location where component separation occurs during the solidification process of the melt, and the fracture location corresponds to the boundary line of different component regions inside the particle. It should be noted that the locations of the impedance layer spatial fractures identified above represent the interfaces of different component melt regions within the flux particles. In this embodiment, these locations are directly used as the locations where component separation occurs during the solidification process of the melt, so as to clearly define the boundaries of different component regions within the particles.

[0051] Specifically, the set of spatial coordinates of the location of the spatial fracture in the impedance layer is represented as:

[0052] In the formula: This is the set of coordinates for the location of the spatial fracture in the impedance layer; Indicates the first Three-dimensional coordinates of the location of the spatial fracture in the impedance layer; The total number of spatial fracture locations identified.

[0053] It should be understood that the set of spatial fracture locations of the impedance layer determined above provides basic data for the spatial positioning of the melt composition boundary line inside the flux particles, and directly reflects the composition segregation interface that occurs during the solidification process of the melt.

[0054] Connecting adjacent fracture locations forms a complete boundary line network, which is then used to define the component segregation boundaries within the flux particles. For example, this embodiment refers to the set of spatial fracture locations of the impedance layer identified above. A three-dimensional interpolation method is used to connect the particles, forming a continuous spatial boundary network structure, which clearly defines the specific spatial location of the segregation boundary of the particles.

[0055] Specifically, this embodiment uses a three-dimensional spline interpolation algorithm to connect adjacent spatial break points. The interpolation function is expressed as follows:

[0056] In the formula: The function representing the spatial boundary network formed is specifically the interpolation curve network; It is a three-dimensional spline interpolation function; It should be noted that the spatial boundary network constructed by the above interpolation is the component segregation boundary inside the flux particles, providing accurate spatial structure information and providing a spatial positioning basis for further real-time evaluation of the component uniformity of flux particles.

[0057] Extract the temperature change trajectory of the region corresponding to the component segregation boundary in the thermal radiation image, and combine the spatial coordinates of the segregation boundary with the temperature change trajectory to generate segregation location markers. Specifically, the extraction of the temperature change trajectory is based on the temporal evolution pattern of the temperature field in the thermal radiation image. When the temperature of a certain region shows a continuous decrease or fluctuation in the time series, the temperature evolution path of that region is taken as the temperature change trajectory.

[0058] For example, when the temperature in a certain area consistently shows a monotonically decreasing trend over at least three consecutive sampling times (the temperature decrease in each measurement is not less than...), (The specific threshold is determined based on actual experiments), or the temperature data shows periodic or non-monotonic fluctuations (fluctuation amplitude greater than) within three or more consecutive sampling times. When the fluctuation period is no less than 2 sampling periods (the specific threshold is determined through experiments), the temperature change sequence of the region is determined as the temperature change trajectory.

[0059] It should be understood that this embodiment first extracts temperature change data of the region corresponding to the component segregation boundary from the time-series data of the thermal radiation image, specifically through the following method: Define the temperature change trajectory as:

[0060] In the formula: Indicates spatial location The temperature trajectory of the location as a function of time; Indicates different points in time; When the temperature change trajectory continuously decreases or fluctuates significantly within the time series, it indicates that there are significant differences in the melt composition inside the particles.

[0061] Furthermore, the temperature change trajectory is compared with the aforementioned spatial boundary network. Spatial location matching is performed to mark and confirm the locations where component segregation occurs within flux particles, thereby generating precise segregation location markers.

[0062] S103: The segregation location markers are time-sequentially correlated with the microstructure evolution of flux particles to establish a causal chain between compositional segregation and microstructure changes; when the causal chain breaks, the distribution of the melt solidification resistance layer is adjusted according to the recapture of heat conduction shunting in the thermal radiation image. It should be noted that, in order to verify the accuracy of the determined component segregation location, this embodiment conducts a rigorous time-series correspondence analysis between the segregation location markers generated in step S102 and the evolution of the microstructure of flux particles during solidification, so as to clarify the causal relationship between component segregation and microstructure changes.

[0063] In the specific implementation process, the step of verifying the temporal correspondence between the segregation location markers and the microstructure evolution process of flux particles to establish a causal chain between component segregation and microstructure changes includes: To obtain information on the microstructure of flux particles at different times during solidification and to identify the evolution stages of the microstructure; Specifically, the microstructure evolution stages include primary phase precipitation, eutectic reaction and solid-state phase transformation. Microstructure information is obtained through metallographic analysis of flux particles, and the identification of evolution stages is based on the formation and transformation characteristics of different phase structures.

[0064] Understandably, this embodiment involves periodically sampling flux particles and using standard metallographic microscopy to collect microstructure images of the particles at different solidification stages. Specifically, by identifying microstructure morphology characteristics (such as grain size, crystal phase morphology, and distribution density), different microstructure evolution stages during particle solidification are clearly defined, including: primary phase precipitation stage, eutectic reaction stage, and phase transition stage.

[0065] For example, the solidification process of flux particles can be divided into multiple specific time periods (e.g., sampling once per second), and the corresponding microstructure evolution image data can be recorded and the time labels of the microstructure image data can be stored for subsequent analysis.

[0066] Establish the temporal correspondence between the formation time of component segregation boundaries and the microstructure evolution stages, and analyze the temporal synchronization between segregation occurrence and tissue changes; It should be noted that, based on the microstructure evolution images and their corresponding time data obtained above, this embodiment further determines the temporal correspondence between the formation time of the component segregation boundary and the stage of microstructure feature change.

[0067] Specifically, the temporal synchronization between the segregation locations marked on the thermal radiation image was analyzed by matching the temporal information of different clearly identified stages in the microstructure image. This synchronization was then expressed as a time difference. Quantification is expressed as:

[0068] In the formula: This indicates the formation time at which the location of component segregation is determined in the thermal radiation image; This indicates the moment when the microstructure of flux particles is clearly identified as the beginning or transition point in a specific evolutionary stage.

[0069] The strength of the causal relationship between component segregation and microorganism evolution is assessed based on the degree of consistency in temporal synchronization. It is understood that this embodiment is based on the time difference value obtained from the above analysis. This study aims to quantitatively assess the strength of the causal relationship between component segregation and microstructure evolution. Specifically, it defines an evaluation index for the strength of the causal relationship. for:

[0070] In the formula: This indicates the strength of the causal relationship, with a value ranging from 0 to 1. The closer the value is to 1, the stronger the causal relationship. This is an empirical coefficient; the specific value is determined based on statistical analysis of experimental data.

[0071] It should be noted that when the causal relationship strength C is less than the preset threshold... This indicates a mismatch between the causal relationship between the location of component segregation and the stage of microstructure evolution, i.e., a break in the causal chain.

[0072] Establish a causal chain between component segregation and tissue changes based on the assessment results of the strength of causal association; It should be understood that this embodiment is based on the above-mentioned causal relationship strength evaluation index. The evaluation results establish a causal chain between component segregation locations and microstructural changes. When evaluation indicators... Greater than or equal to the set threshold At that time, it was assumed that a stable causal relationship existed, forming a clear causal chain, and this was recorded in the database.

[0073] In the specific implementation process, adjusting the melt solidification impedance layer distribution based on the recapture of heat conduction shunting in the thermal radiation image includes: It should be noted that in this embodiment, when the causal chain evaluation results between component segregation and tissue changes are broken, the previously unidentified or inaccurately identified heat conduction shunting points will be captured by re-analyzing the heat conduction shunting phenomenon in the thermal radiation image, and the spatial distribution structure of the melt solidification impedance layer will be readjusted.

[0074] Identify the time points at which the causal chain of component segregation and tissue changes breaks down; Specifically, the identification of chain breakage is based on the degree of mismatch between the formation time of component segregation and the evolution time of microstructure. When the difference between the formation time of the segregation boundary and the occurrence time of the corresponding microstructure evolution stage exceeds the time cycle of the flux particle solidification process, it is determined to be a causal chain breakage.

[0075] For example, when the absolute time difference between the two exceeds 20% of the average time of the flux particle solidification process (the average time of the solidification process is determined by actual testing, for example, the average time from the particle leaving the furnace to complete solidification is taken as the average time of the solidification process), it is determined that the causal chain has broken.

[0076] It should be understood that the method for determining the time point of chain breakage is as follows: First, record the formation time of the segregation location markers. and the timing of the corresponding micro-organization evolution stage The time difference between the two ; When this time difference This exceeds the reasonable time range of microstructure changes during flux particle solidification (exemplarily, this range can be defined as the typical cycle of the particle solidification process). When it is a certain proportion, such as 20%, that is:

[0077] In this embodiment, it is determined that the causal chain breaks at this time point and recorded as the specific time point of the chain break.

[0078] By reanalyzing the occurrence pattern of heat conduction shunting in thermal radiation images at the time point of chain breakage, the spatial evolution trajectory of the shunting phenomenon is traced. Understandably, in order to repair the aforementioned chain breakage problem, this embodiment re-analyzes the heat conduction shunting phenomenon on the surface of flux particles in the thermal radiation image at the determined chain breakage time point. The specific implementation process is as follows: In the thermal radiation image sequence near the chain breakage time point, the aforementioned main channel identification and heat conduction shunting point detection steps are re-executed. Specifically, if the change in the width of the main heat conduction channel, which was ignored in the initial analysis, is less than the set threshold (e.g., the initial channel width increase is less than 20%, but reaches a slight change of more than 10%), or if the splitting angle did not reach the original threshold in the initial identification but is found to reach a new corrected threshold in the re-analysis (e.g., ... When the threshold is determined by actual testing, these locations are re-identified as heat conduction shunt points, and their spatial coordinates are recorded to correct the distribution of heat conduction shunt points.

[0079] Furthermore, the spatial evolution trajectory of heat conduction shunting phenomena is traced, that is, the trajectories of the heat conduction shunting points re-identified in the continuous image sequence are reconstructed according to their chronological order to obtain the corrected spatial trajectory information of heat conduction shunting, specifically represented as follows:

[0080] In the formula: This represents the location and time node of the j-th re-identified heat conduction shunt point in three-dimensional space; k represents the total number of heat conduction shunt points on the trajectory.

[0081] The location distribution of heat conduction shunting points was corrected based on the reanalysis results of the spatial evolution trajectory of the shunting phenomenon. It should be noted that the spatial evolution trajectory of the heat conduction diversion phenomenon, which was re-tracked based on the above steps, is... In this embodiment, the spatial distribution of heat conduction shunt points is redefined, and the following modifications are made specifically: First, using spatial trajectory analysis methods (such as trajectory fitting or filtering methods), the positional errors or omissions of the branching points in spatial coordinates are corrected to obtain the corrected set of branching point coordinates:

[0082] In the formula: each location point All of these are the precise coordinates of the divergence points after trajectory correction.

[0083] It should be understood that the above-mentioned corrected distribution of the diversion point location more accurately represents the true spatial distribution of the melt solidification resistance layer inside the particle compared to the initially determined diversion point.

[0084] Based on the corrected location of the heat conduction diversion point, the spatial profile of the solidification resistance layer is reconstructed, and the distribution of the melt solidification resistance layer is adjusted. It is understandable that this is based on the above-corrected set of heat conduction split point locations. In this embodiment, the spatial profile of the flux particle melt solidification impedance layer is reconstructed, thereby precisely adjusting the spatial distribution of the impedance layer.

[0085] Specifically, the aforementioned three-dimensional radial basis function interpolation method is used to spatially reconstruct the corrected set of shunt point locations, thereby constructing the adjusted spatial profile function of the solidification impedance layer:

[0086] In the formula: This represents the spatial profile function of the solidification impedance layer after adjustment and reconstruction. The weighting coefficients obtained by re-interpolation calculation; For shape parameters during the re-interpolation process; Represents any interpolation space point and the th The spatial distance between each corrected diversion point.

[0087] It should be noted that the solidification impedance layer spatial profile function after the above reconstruction It can accurately reflect the actual spatial structure of the melt solidification process inside the particles, thereby effectively repairing the problem of the broken causal chain between component segregation and microstructure changes, and providing reliable data for subsequent uniformity level assessment.

[0088] S104: Determine the compositional uniformity level of flux particles based on the adjusted melt solidification resistance layer distribution, and output the uniformity test results; It should be noted that this embodiment utilizes the reconstructed spatial distribution function of the melt solidification impedance layer described above. This further clarifies the spatial structure of the melt inside the flux particles, thereby accurately evaluating the compositional uniformity level of the flux particles.

[0089] In the specific implementation process, the following steps are used to evaluate and determine the uniformity level of flux particle composition: First, based on the reconstructed spatial profile of the impedance layer distribution. The spatial uniformity characteristic parameters of the melt impedance layer inside the flux particles are calculated. Specifically, this embodiment uses the spatial impedance layer density parameter. To characterize uniformity, the following formula is defined:

[0090] In the formula; The effective quantity of the melt solidification resistance layer inside the flux particles, i.e., the spatial profile function. The number of solidification resistance layers that can be clearly distinguished in the middle; This represents the total volume of the particles, which can be calculated based on a three-dimensional model of the particles (obtained through three-dimensional reconstruction of the image).

[0091] Furthermore, this embodiment will increase the impedance layer density. The value range is divided into multiple levels, forming an evaluation standard for the uniformity of flux particle composition. For example: when At that time, it was judged as Grade I (excellent, highly uniform composition); when At that time, it was judged as Grade II (good, relatively uniform composition); when At that time, it was judged as Level III (general, with slight bias). when At that time, it was judged to be Grade IV (poor, with obvious segregation); in: The threshold parameter for uniformity evaluation level is obtained from statistical analysis of a large amount of experimental data.

[0092] It should be understood that the above-mentioned classification criteria and the selection of impedance layer density parameters are determined based on actual data statistics from experimental testing, metallographic observation, and flux performance analysis, which can effectively and objectively evaluate the compositional uniformity of flux particles.

[0093] Finally, this embodiment uses a pre-designed data processing software system to automatically generate a test report from the determined component uniformity level and output it in a visual manner (such as a color diagram or level number).

[0094] For example, the output uniformity detection result includes: the identification number of the flux particles; Component uniformity grade (Grade I to Grade IV); Impedance layer density parameter value ; Visualized image of the spatial distribution of the particle impedance layer.

[0095] Through the above specific embodiments, the present invention can evaluate the compositional uniformity of particles in the flux production process in real time, accurately and reliably, and has important industrial application value.

[0096] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A method for real-time evaluation of flux uniformity in the production of smelting flux, characterized in that, include: Acquire thermal radiation images of flux particles the instant they exit the furnace; The distribution of the melt solidification resistance layer inside the particle was constructed by observing the heat conduction shunting phenomenon on the particle surface in thermal radiation images. The compositional segregation boundaries inside flux particles are identified based on the spatial fragmentation pattern of the melt solidification impedance layer distribution; segregation location markers are generated based on the spatial overlap between the compositional segregation boundaries and the temperature change trajectory in the thermal radiation image. The segregation location markers and the microstructure evolution process of flux particles were time-sequentially verified to establish a causal chain between compositional segregation and microstructure changes. When the causal chain breaks, the distribution of the melt solidification resistance layer is adjusted according to the recapture of heat conduction shunting in the thermal radiation image. The compositional uniformity level of flux particles is determined based on the adjusted melt solidification impedance layer distribution, and the uniformity test results are output.

2. The method for real-time evaluation of flux uniformity in the production of smelting flux according to claim 1, characterized in that, The method of constructing the distribution of the melt solidification resistance layer inside the particle by means of the heat conduction shunting phenomenon on the particle surface in thermal radiation images includes: Identify the main heat transfer channels on the surface of flux particles in thermal radiation images, and mark the areas with the largest temperature gradient in the temperature field on the particle surface as the main heat transfer channels; Track the heat conduction diversion phenomenon that occurs during the propagation of the main heat transfer channel. When the main channel disperses into multiple conduction branches at a certain location, mark that location as the heat conduction diversion point. The location of the impedance layer during the solidification process of the melt inside the particle can be inferred by the spatial distribution law of the heat conduction diversion point. Each heat conduction diversion point corresponds to the boundary position of a solidification impedance layer. The boundary positions of adjacent solidification impedance layers are connected to form the spatial outline of the impedance layer, thus constructing the distribution of the melt solidification impedance layer.

3. The method for real-time evaluation of flux uniformity in flux production according to claim 2, characterized in that, The identification of the heat conduction diversion phenomenon is based on the geometric shape change of the main heat transfer channel. When the width of the main channel increases and disperses into multiple narrow channels during the propagation process, the location of the shape change is determined as the heat conduction diversion point.

4. The method for real-time evaluation of flux uniformity in the production of smelting flux according to claim 3, characterized in that, The generation of segregation location markers includes: Analyze the spatial continuity of the impedance layer in the solidification impedance layer distribution of the melt to identify the location of spatial breaks in the impedance layer. The location of the fracture in the impedance layer space is taken as the location where component separation occurs during the solidification process of the melt, and the fracture location corresponds to the boundary line of different component regions inside the particle. Connecting adjacent fracture locations forms a complete boundary line network, which is then used to define the component segregation boundaries within the flux particles. Extract the temperature change trajectory of the region corresponding to the component segregation boundary in the thermal radiation image, and combine the spatial coordinates of the segregation boundary with the temperature change trajectory to generate segregation location markers.

5. The method for real-time evaluation of flux uniformity in the production of smelting flux according to claim 4, characterized in that, The identification of the spatial break in the impedance layer is based on the geometric discontinuity of the impedance layer profile. When the impedance layer profile is geometrically discontinuous or missing during spatial extension, the discontinuity location is determined as the location of the spatial break in the impedance layer.

6. The method for real-time evaluation of flux uniformity in the production of smelting flux according to claim 5, characterized in that, The extraction of the temperature change trajectory is based on the temporal evolution pattern of the temperature field in the thermal radiation image. When the temperature of a certain region shows a continuous decrease or fluctuation in the time series, the temperature evolution path of that region is taken as the temperature change trajectory.

7. The method for real-time evaluation of flux uniformity in the production of smelting flux according to claim 6, characterized in that, The step of verifying the temporal correspondence between segregation location markers and the microstructure evolution of flux particles to establish a causal chain between component segregation and microstructure changes includes: To obtain information on the microstructure of flux particles at different times during solidification and to identify the evolution stages of the microstructure; Establish the temporal correspondence between the formation time of component segregation boundaries and the microstructure evolution stages, and analyze the temporal synchronization between segregation occurrence and tissue changes; The strength of the causal relationship between component segregation and microorganism evolution is assessed based on the degree of consistency in temporal synchronization. A causal chain between component segregation and organizational change was established based on the assessment results of the strength of causal association.

8. The method for real-time evaluation of flux uniformity in the production of smelting flux according to claim 7, characterized in that, The microstructure evolution stages include primary phase precipitation, eutectic reaction, and solid-state phase transformation. Microstructure information is obtained through metallographic analysis of flux particles, and the identification of evolution stages is based on the formation and transformation characteristics of different phase structures.

9. The method for real-time evaluation of flux uniformity in the production of smelting flux according to claim 8, characterized in that, The adjustment of the melt solidification impedance layer distribution based on the recapture of heat conduction shunting in the thermal radiation image includes: Identify the time points at which the causal chain of component segregation and tissue changes breaks down; By reanalyzing the occurrence pattern of heat conduction shunting in thermal radiation images at the time point of chain breakage, the spatial evolution trajectory of the shunting phenomenon is traced. The location distribution of heat conduction shunting points was corrected based on the reanalysis results of the spatial evolution trajectory of the shunting phenomenon. Based on the corrected locations of the heat conduction split points, a three-dimensional radial basis function interpolation method is used to spatially reconstruct the set of corrected split point locations, thereby reconstructing the spatial profile of the solidification resistance layer and adjusting the distribution of the melt solidification resistance layer. Among them, the adjusted and reconstructed spatial profile of the solidification impedance layer is expressed as a function. It is expressed as follows: In the formula: This represents the spatial profile function of the solidification impedance layer after adjustment and reconstruction. The weighting coefficients obtained by re-interpolation calculation; For shape parameters during the re-interpolation process; Represents any interpolation space point and the first The spatial distance between each corrected diversion point.

10. The method for real-time evaluation of flux uniformity in the production of smelting flux according to claim 9, characterized in that, The identification of chain breakage is based on the degree of mismatch between the formation time of component segregation and the evolution time of microstructure. When the difference between the formation time of the segregation boundary and the occurrence time of the corresponding microstructure evolution stage exceeds the time period of the flux particle solidification process, it is determined to be a causal chain breakage.

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