Laser cladding method based on feedback adjustment under thermal expansion and melting point difference constraint

Abstract

The invention discloses a laser cladding method based on feedback adjustment under the constraint of thermal expansion and melting point difference, and the method achieves the prediction of a real crack shape feature value of a scene generated by the laser cladding prediction of the cladding combination through laser cladding experiment parameters through the comprehensive influence quantity obtained through the calculation of the cladding combination in the step S1. In the step S3, a corresponding first laser parameter adjustment set and / or a second laser parameter adjustment set is matched according to the type and size of a scene real crack shape feature prediction value predicted by the cladding combination, and then the cladding combination is obtained through the matching of each laser parameter value in the first laser parameter adjustment set or the second laser parameter adjustment set. Or the parameter values of the laser cladding experiment parameters of the same type are updated according to the smaller change value of the common laser parameter in the first laser parameter adjustment set and the second laser parameter adjustment set, so that the rapid and accurate adjustment of the laser cladding experiment parameter values capable of resisting the generation of the predicted scene real crack shape feature prediction values is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of laser cladding, and particularly to a laser cladding method based on feedback adjustment under the constraint of thermal expansion and melting point differences. Background Art

[0002] Cladding is a surface treatment technology that improves the performance of a substrate by melting materials and covering them on the surface of the substrate. Common cladding processes include laser cladding, plasma cladding, arc cladding, etc. During the cladding process, cracks may appear on the cladding layer and the surface of the substrate. These cracks will affect the firmness of the bond between the cladding layer and the substrate, thereby affecting the performance of the substrate. The formation reasons and types of cracks are diverse, and different reasons usually produce different types of cracks. Crack types include longitudinal cracks, transverse cracks, intergranular cracks, periodically expanding cracks, radial cracks, boundary cracks, internal cracks, etc. These different crack shape characteristics are generated under corresponding scenario factors. For example, when laser cladding a YSZ@Ni coating, due to the cooling shrinkage of the molten pool material, the stress at both ends of the cladding layer is relatively large, and the bonding layer between the substrate and the YSZ coating has the maximum tensile stress in the X direction, making it easy to generate transverse cracks perpendicular to the scanning direction. However, no matter which type of crack, if the physical properties such as the thermal expansion coefficient and melting point of the cladding material and the substrate are quite different, the type characteristics of the cracks under the corresponding scenario factors (ignoring the differences in thermal expansion coefficient and melting point) may be significantly changed, making it difficult to use the type characteristics of the cracks under this scenario factor as a feedback basis to adjust the relevant control parameters during the laser cladding process.

[0003] And inevitably, there are different differences in the thermal expansion coefficient and melting point of the cladding material and the substrate at different life stages. Even if the differences are within the constraint conditions (the differences are within the preset difference threshold range), these different differences may further cause obvious changes in the crack shape characteristics formed under the corresponding scenario factors. How to quantify the ability of different differences in thermal expansion coefficient and melting point at different life stages to change the crack shape characteristics formed under the corresponding scenario factors (ignoring the differences in thermal expansion coefficient and melting point) is the first technical problem to be solved in this application.

[0004] Most importantly, after the cracks formed under the corresponding scenario factors are changed due to the dynamically changing (changing due to the different life stages of the cladding material and the substrate) differences in thermal expansion coefficient and melting point, how to use the changed crack shape characteristics as a feedback basis to adjust the relevant control parameters during the laser cladding process, thereby improving the cladding quality is the second technical problem to be solved in this application. Summary of the Invention

[0005] The present invention aims to reduce the probability of generating cladding cracks and improve the cladding quality when the thermal expansion coefficients and melting points of the cladding material and the substrate are different at their respective life stages but meet the constraint conditions, and provides a laser cladding method based on feedback adjustment under the constraint of thermal expansion and melting point differences.

[0006] To achieve this purpose, the present invention adopts the following technical solutions:

[0007] Provided is a laser cladding method based on feedback adjustment under the constraint of thermal expansion and melting point differences, including the steps of:

[0008] S1. Obtain the thermal expansion coefficient difference and melting point difference between the cladding material and the substrate constituting the cladding combination at the current life stage, and calculate the comprehensive influence amount of the comprehensive difference in thermal expansion coefficient and melting point on changing the initial eigenvalue of the scene experimental crack shape formed in the experimental environment of the scene factors currently possessed by the cladding combination through the difference point matching method;

[0009] S2. Predict the predicted value of the real crack shape feature of the scene expected to be generated by laser cladding of the cladding combination with the laser cladding experimental parameters according to the comprehensive influence amount calculated in step S1;

[0010] S3. After adjusting the laser cladding experimental parameters by corresponding strategies according to the type and size of the predicted value of the real crack shape feature of the scene predicted in step S2, start laser cladding of the cladding combination.

[0011] Preferably, in step S1, the method for calculating the comprehensive influence amount of the comprehensive difference in thermal expansion coefficient and melting point on changing the initial eigenvalue of the scene experimental crack shape formed in the experimental environment of the scene factors currently possessed by the cladding combination includes the steps of:

[0012] S11. Substitute the obtained thermal expansion coefficient difference and melting point difference between the cladding material and the substrate at the current life stage into the first fitting function and the second fitting function respectively, and solve for the y values of the first fitting function and the second fitting function;

[0013] S12. Calculate the absolute value of the difference between the y value of the first fitting function and the initial eigenvalue of the scene experimental crack shape as the first influence amount of the thermal expansion coefficient difference at the current life stage on changing the initial eigenvalue of the scene experimental crack shape; calculate the absolute value of the difference between the y value of the second fitting function and the initial eigenvalue of the scene experimental crack shape as the second influence amount of the melting point difference at the current life stage on changing the initial eigenvalue of the scene experimental crack shape;

[0014] S13. Obtain the piecewise compensation function corresponding to the cladding combination with the first influencing quantity and the second influencing quantity, and use the y value obtained by solving the obtained piecewise compensation function as the comprehensive influencing quantity of the comprehensive difference on changing the initial characteristic value of the crack shape in the scenario experiment.

[0015] Preferably, the first fitting function and / or the second fitting function is a unary high-degree function. The method for constructing the unary high-degree function includes the steps:

[0016] A1. Under the experimental environment where the cladding combination currently has the scenario factors, perform laser cladding on the cladding experimental material and the experimental substrate at the initial stage of life with the laser cladding experimental parameters to obtain the initial characteristic value of the crack shape in the scenario experiment.

[0017] A2. In the same real environment with the scenario factors, perform laser cladding on each sample combination with different life stages with the same laser cladding experimental parameters to obtain the characteristic value of the change in the crack shape in the scenario experiment associated with each sample combination; at least one of the cladding sample materials and the sample substrates in each sample combination has a different life stage.

[0018] A3. Compare the similarity between each characteristic value of the change in the crack shape in the scenario experiment and the initial characteristic value of the crack shape in the scenario experiment to filter out the characteristic values of the change in the crack shape in the scenario experiment with a similarity less than the similarity threshold.

[0019] A4. Classify each sample combination remaining after being filtered in step A3 to obtain fitting sample combinations respectively used for fitting the first curve and the second curve.

[0020] A5. Fit the first curve or the second curve with the corresponding fitting sample combinations to solve the term coefficients of the first fitting function associated with the first curve and the term coefficients of the second fitting function associated with the second curve.

[0021] The types of the cladding experimental material, the cladding sample material and the cladding material are the same; the types of the experimental substrate, the sample substrate and the substrate are the same.

[0022] Preferably, in step A4, the method for classifying each sample combination remaining after being filtered in step A3 is as follows:

[0023] Classify each sample combination with an absolute value of the difference in the coefficient of thermal expansion less than the first difference threshold as the first fitting sample combination, and the first fitting sample combination is used to construct the second fitting function; classify each sample combination with an absolute value of the difference in melting point less than the second difference threshold as the second fitting sample combination, and the second fitting sample combination is used to construct the first fitting function.

[0024] Preferably, the absolute value of the difference in melting point between any two of the first fitting sample combinations is greater than the second difference threshold; the absolute value of the difference in coefficient of thermal expansion between any two of the second fitting sample combinations is greater than the first difference threshold.

[0025] Preferably, in step A5, the method for solving the term coefficients of the second fitting function is as follows:

[0026] Taking the eigenvalue of the change in the crack shape of the scenario experiment associated with each of the first fitting sample combinations as the dependent variable of the second fitting function, and taking the difference in melting point between the clad sample material and the sample substrate in the corresponding first fitting sample combination that forms the eigenvalue of the change in the crack shape of the scenario experiment as the independent variable, and inversely solving for the term coefficients of the second fitting function;

[0027] The method for solving the term coefficients of the first fitting function is as follows:

[0028] Taking the eigenvalue of the change in the crack shape of the scenario experiment associated with each of the second fitting sample combinations as the dependent variable of the first fitting function, and taking the difference in coefficient of thermal expansion between the clad sample material and the sample substrate in the corresponding second fitting sample combination that forms the eigenvalue of the change in the crack shape of the scenario experiment as the independent variable, and inversely solving for the term coefficients of the first fitting function.

[0029] Preferably, the piecewise compensation function in step S13 is a quadratic function of one variable, and the method for constructing the piecewise compensation function includes the steps of:

[0030] B1. Obtaining the first influence quantity and the second influence quantity respectively possessed by each of the sample combinations, obtaining a first influence quantity numerical interval with the maximum value in each of the first influence quantities as the interval upper limit and the minimum value as the interval lower limit, and obtaining a second influence quantity numerical interval with the maximum value in each of the second influence quantities as the interval upper limit and the minimum value as the interval lower limit;

[0031] B2. Dividing the first influence quantity numerical interval and the second influence quantity numerical interval into a number of interval segments at corresponding numerical intervals;

[0032] B3. Classifying the remaining sample combinations filtered by step A3 to obtain a first piecewise compensation sample group set and a second piecewise compensation sample group set;

[0033] B4. Group each of the sample combinations in the first segmented compensation sample group set into a first segmented compensation sample group subset bound to a first interval segment into which the first influencing quantity of the sample combination falls, and group each of the sample combinations in the second segmented compensation sample group set into a second segmented compensation sample group subset bound to a second interval segment into which the second influencing quantity of the sample combination falls;

[0034] B5. Using the second unit influencing quantity and the first crack shape eigenvalue deviation of each of the sample combinations in the first segmented compensation sample group subset as the dependent variable and independent variable of a first segmented compensation function bound to the first segmented compensation sample group subset respectively, and using the first unit influencing quantity and the second crack shape eigenvalue deviation of each of the sample combinations in the second segmented compensation sample group subset as the dependent variable and independent variable of a second segmented compensation function bound to the second segmented compensation sample group subset respectively, solve for the term coefficients of the first segmented compensation function and / or the second segmented compensation function through curve fitting.

[0035] Preferably, in step B3, the method for classifying each of the sample combinations remaining after being filtered in step A3 is as follows:

[0036] Add the sample combinations for which the y value of the first fitting function is greater than the y value of the second fitting function to the first segmented compensation sample group set; add the sample combinations for which the y value of the first fitting function is less than or equal to the y value of the second fitting function to the second segmented compensation sample group set;

[0037] The second unit influencing quantity in step B5 is: the ratio of the absolute value of the difference between the y value of each of the sample combinations in the first segmented compensation sample group subset in the second fitting function and the true crack shape eigenvalue of the scene of the sample combination to the melting point difference of the sample combination;

[0038] The first crack shape eigenvalue deviation in step B5 is: the absolute value of the difference between the true crack shape eigenvalue of the scene of the sample combination with the second unit influencing quantity in the first segmented compensation sample group subset and the y value in the first fitting function;

[0039] The first unit influencing quantity in step B5 is: the ratio of the absolute value of the difference between the y value of each of the sample combinations in the second segmented compensation sample group subset in the first fitting function and the true crack shape eigenvalue of the scene of the sample combination to the coefficient of thermal expansion difference of the sample combination;

[0040] The deviation of the second crack shape feature value in step B5 is: the absolute value of the difference between the actual crack shape feature value of the sample combination with the first unit influence amount in the subset of the second segmented compensation sample group and the y value in the second fitting function.

[0041] Preferably, in step S13, the method for obtaining the corresponding segmented compensation function for the cladding combination is:

[0042] Judge whether the y value of the cladding combination in the first segmented compensation function associated with the first influence amount is greater than the y value of the cladding combination in the second segmented compensation function associated with the second influence amount.

[0043] If so, use the first segmented compensation function as the obtained segmented compensation function.

[0044] If not, use the second segmented compensation function as the obtained segmented compensation function.

[0045] Preferably, in step S13, the method for calculating the comprehensive influence amount associated with the cladding combination is:

[0046] Solve the first average value of the actual crack shape feature values of the sample combinations in the subset of the first segmented compensation sample group bound by the first interval segment into which the first influence amount of the cladding combination falls, and use the thermal expansion coefficient difference of the cladding combination as the independent variable of the constructed first fitting function to solve the y value of the first fitting function. Then, use the absolute value of the difference between the first average value and the y value of the solved first fitting function as the independent variable of the first segmented compensation function to solve the y value of the first segmented compensation function as the first comprehensive influence amount associated with the cladding combination.

[0047] Solve the second average value of the actual crack shape feature values of the sample combinations in the subset of the second segmented compensation sample group bound by the second interval segment into which the second influence amount of the cladding combination falls, and use the melting point difference of the cladding combination as the independent variable of the constructed second fitting function to solve the y value of the second fitting function. Then, use the absolute value of the difference between the second average value and the y value of the solved second fitting function as the independent variable of the second segmented compensation function to solve the y value of the second segmented compensation function as the second comprehensive influence amount associated with the cladding combination.

[0048] The predicted value of the real crack shape feature in step S2 is: the first comprehensive influence quantity, the sum of the y value of the cladding combination in the first fitting function and the initial feature value of the crack shape in the scenario experiment, and / or the second comprehensive influence quantity, the sum of the y value of the cladding combination in the second fitting function and the initial feature value of the crack shape in the scenario experiment;

[0049] The first type associated with the first sum value is bound with a first set of laser parameter adjustments capable of resisting the change of the initial feature value of the crack shape in the scenario experiment to the first sum value; the second type associated with the second sum value is bound with a second set of laser parameter adjustments capable of resisting the change of the initial feature value of the crack shape in the scenario experiment to the second sum value;

[0050] In step S3, according to the type and magnitude of the first sum value and / or the second sum value, the corresponding first set of laser parameter adjustments and / or the second set of laser parameter adjustments are matched. Then, using the laser parameter values in the first set of laser parameter adjustments or the second set of laser parameter adjustments, or the parameter values of the common laser parameters in the first set of laser parameter adjustments and the second set of laser parameter adjustments, the parameter values of the common laser parameters with the smallest change amount compared to the parameter values of the same type of laser cladding experiment parameters are used to update the parameter values of the same type of the laser cladding experiment parameters.

[0051] The present invention has the following beneficial effects:

[0052] 1. By establishing a mapping relationship at different life stages of the thermal expansion coefficient, melting point, cladding material, and substrate, after identifying the current life stage, the thermal expansion coefficient and melting point of the cladding material and substrate can be directly read, realizing non-destructive detection of the thermal expansion coefficient and melting point of the cladding material and substrate at different life stages.

[0053] 2. The fluctuations of the first curve fitted by the first fitting function and the second curve fitted by the second fitting function reflect the change characteristics of the samples in the same type but at different life stages under the same scenario factors for the characteristic that "the greater the difference in thermal expansion coefficient and melting point, the easier it is to generate cracks". This makes the first curve and the second curve better able to characterize the influence characteristics of each sample combination with different life stages, the same type of cladding material and substrate material, and having differences in thermal expansion coefficient and / or melting point on changing the initial characteristics of the scenario experimental crack shape formed in the experimental environment with the same scenario factors. That is, it considers the mutual influence relationship between the scenario factors and the characteristic that "the greater the difference in thermal expansion coefficient and melting point, the easier it is to generate cracks" on changing the initial characteristics of the scenario experimental crack shape formed in the experimental environment without considering the differences in thermal expansion coefficient and melting point at different life stages. Furthermore, it makes the comprehensive influence amount calculated in step S13 more accurate, which is conducive to improving the accuracy of subsequent adjustment of laser cladding parameters, and thus greatly improving the quality of laser cladding.

[0054] 3. Through step A3, the filtering of the invalid shape samples that further change the initial characteristic values of the scenario experimental crack shape formed in the experimental environment with the same scenario factors caused by the sample combinations at different life stages is realized. This makes the constructed univariate high-order function better able to accurately characterize the influence degree of each sample combination at different life stages on changing the characteristic values of the scenario experimental crack shape, and specifically quantifies this influence degree. Furthermore, it makes it possible to control and adjust the process parameters of laser cladding based on these quantified data as the basis for feedback adjustment in the subsequent process.

[0055] 4. The comprehensive influence amount calculated for the cladding combination through step S1 realizes the prediction of the characteristic values of the scenario real crack shape that is expected to be generated by the laser cladding with the laser cladding experimental parameters for this cladding combination. In step S3, according to the type and size of the predicted characteristic values of the scenario real crack shape for this cladding combination, the corresponding first laser parameter adjustment set and / or the second laser parameter adjustment set are matched. Then, the parameter values of the same type of laser cladding experimental parameters are updated with the laser parameter values in the first laser parameter adjustment set or the second laser parameter adjustment set, or the smaller change values of the common laser parameters in the first laser parameter adjustment set and the second laser parameter adjustment set, realizing the rapid and accurate adjustment of the laser cladding experimental parameter values that can resist generating the predicted characteristic values of the scenario real crack shape.

[0056] 5. After calculating the first influence quantity and the second influence quantity of the cladding combination, by obtaining the piecewise compensation function corresponding to the cladding combination and using the y value obtained by solving the piecewise compensation function as the comprehensive influence quantity required for predicting the predicted value of the true crack shape characteristics of the laser cladding expected to be performed on the cladding combination with the laser cladding experimental parameters in step S2. When calculating this comprehensive influence quantity, it is only necessary to calculate the absolute value of the difference between the first average value of the cladding combination and the y value in the first fitting function or the absolute value of the difference between the second average value of the cladding combination and the y value in the second fitting function and substitute it into the obtained piecewise compensation function, thus realizing the rapid calculation of the comprehensive influence quantity required in step S2. Moreover, the piecewise compensation function is associated with the corresponding influence quantity numerical interval segments, and the piecewise compensation function characterizes the different change characteristics of different comprehensive influence quantities on changing the initial characteristic value of the experimental crack shape of the scene in a fine-grained manner, making the calculated comprehensive influence quantity more accurate. Furthermore, it is beneficial to improve the response speed and accuracy of updating and adjusting the laser cladding experimental parameters subsequently, thereby improving the quality of laser cladding. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0058] Figure 1 It is a flowchart of the implementation steps of the laser cladding method based on feedback adjustment under the constraint of thermal expansion and melting point difference provided by the embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0059] The technical solutions of the present invention will be further described below with reference to the drawings and through specific embodiments.

[0060] Among them, the drawings are only for illustrative purposes, showing only schematic diagrams, not physical diagrams, and should not be construed as a limitation of this patent; in order to better illustrate the embodiments of the present invention, some components in the drawings will be omitted, enlarged or reduced, and do not represent the dimensions of the actual product; for those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0061] In the drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components; in the description of the present invention, it should be understood that if terms such as "upper", "lower", "left", "right", "inner", "outer", etc. are used to indicate the orientation or positional relationship, it is based on the orientation or positional relationship shown in the drawings. This is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, the terms used to describe the positional relationship in the drawings are only for illustrative purposes and cannot be construed as a limitation of this patent. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific circumstances.

[0062] In the description of the present invention, unless otherwise clearly defined and limited, if terms such as "connection" are used to indicate the connection relationship between components, this term should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral one; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two components or the interaction relationship between two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0063] A laser cladding method based on feedback adjustment under the constraint of thermal expansion and melting point difference provided by the embodiments of the present invention, as Figure 1 shown, includes the steps:

[0064] S1. Obtain the thermal expansion coefficient difference and melting point difference between the cladding material and the substrate that make up the cladding combination at the current life stage, and calculate the comprehensive influence amount of the comprehensive difference in thermal expansion coefficient and melting point on the initial characteristic value of the shape of the scenario experimental crack formed in the experimental environment that changes the scenario factors (ignoring the thermal expansion coefficient difference and melting point difference) currently possessed by the cladding combination through the difference point matching method;

[0065] The cladding combination is composed of a cladding material and a substrate. For example, the cladding material uses yttria-stabilized zirconia (YSZ), and the substrate is Ni. Which life stage the cladding material and the substrate are currently in is identified by existing methods, and since the method for identifying the current life stage of the cladding material and the substrate is not the scope of the claims of this application, no specific description is given.

[0066] After identifying the current life stages of the cladding material and the substrate, by constructing the mapping relationship between the life stage, the coefficient of thermal expansion, and the melting point, directly look up the coefficient of thermal expansion and the melting point of the cladding material and the substrate at the current life stage in the table. Then calculate the differences in the coefficient of thermal expansion and the melting point between the two. The difference in the coefficient of thermal expansion is the absolute value of the difference between the coefficient of thermal expansion of the cladding material and the coefficient of thermal expansion of the substrate, and the difference in the melting point is the absolute value of the difference between the melting point of the cladding material and the melting point of the substrate.

[0067] Currently, the calculation methods for the coefficient of thermal expansion and the melting point of the cladding material and the substrate are relatively complex and have low accuracy. For example, the existing calculation methods for the coefficient of thermal expansion include the dilatometry method, X-ray diffraction method, laser interferometry method, two-wire method, etc. These methods either have high accuracy but high detection costs, or low detection costs but poor accuracy, and cannot achieve non-destructive detection of the coefficient of thermal expansion and the melting point of the cladding material and the substrate. Therefore, in this application, by establishing a mapping relationship between the coefficient of thermal expansion, the melting point, and the life stage of the cladding material and the substrate, after identifying the current life stage, the coefficient of thermal expansion and the melting point of the cladding material and the substrate can be directly read, realizing non-destructive detection of the coefficient of thermal expansion and the melting point of the cladding material and the substrate at different life stages.

[0068] After obtaining the differences in the coefficient of thermal expansion and the melting point of the cladding material and the substrate at the current life stage, in step S1, the comprehensive influence amount of the comprehensive difference in the coefficient of thermal expansion and the melting point on the initial characteristic value of the scene experimental crack shape formed under the experimental environment that changes the scene factors currently possessed by this cladding combination is also calculated through the difference point matching method.

[0069] It should be noted here that the scene factors currently possessed by the cladding material do not ignore the influence of the differences in the coefficient of thermal expansion and the melting point on the formation of the scene crack shape characteristic value, but when forming the initial characteristic value of the scene experimental crack shape under the experimental environment of the scene factors currently possessed by this cladding combination, the differences in the coefficient of thermal expansion and the melting point in the scene factors are ignored. The ignoring method is as follows:

[0070] For example, yttria-stabilized zirconia as the cladding material and Ni as the substrate are considered to be in the initial life stage when they are just out of the factory or within one month after leaving the factory. For the cladding material and the substrate that are both in the initial life stage, it is generally recognized that the differences in their coefficients of thermal expansion and melting points can be ignored because before laser cladding, cladding combinations are usually formed by selecting cladding materials and substrates with relatively small differences in the coefficient of thermal expansion and melting point. The scene factors that ignore the differences in the coefficient of thermal expansion and the melting point usually include the size characteristics of the cladding material and / or the substrate, the molten pool cooling characteristics, etc. For example, as described in the background technology, the cooling and shrinkage characteristics of the molten pool material, the stress characteristics at both ends of the cladding layer, etc.

[0071] However, during different life stages of the cladding material and the substrate, the differences in thermal expansion coefficients and melting points between the two may change significantly. Even if the change range is within the controllable range (under constrained conditions), these changes may also cause significant changes in the initial characteristic values of the crack shape in the scenario experiment. Therefore, when the selected types of the cladding material and the substrate remain unchanged, the influence of the differences in thermal expansion coefficients and melting points of the cladding material and the substrate at different life stages on crack generation cannot be ignored. Therefore, it is necessary to quantify the influence of the comprehensive differences in thermal expansion coefficients and melting points on changing the initial characteristic values of the crack shape in the scenario experiment, so as to achieve precise parameter adjustment based on the quantified influence data during the subsequent adjustment of the cladding parameters and improve the cladding quality.

[0072] In this embodiment, the method for calculating the comprehensive influence amount of the comprehensive differences in thermal expansion coefficients and melting points of the cladding material and the substrate at the current life stage on changing the initial characteristic values of the crack shape in the scenario experiment formed in the experimental environment of this scenario factor currently possessed by this cladding combination (ignoring the influence of the differences in thermal expansion coefficients and melting points) specifically includes the following steps:

[0073] S11, substitute the obtained differences in thermal expansion coefficients and melting points of the cladding material and the substrate at the current life stage into the first fitting function and the second fitting function respectively as independent variables, and solve for the y values of the first fitting function and the second fitting function;

[0074] In this embodiment, the first fitting function and the second fitting function are preferably univariate higher-order equations. The method for constructing this univariate higher-order equation specifically includes the following steps:

[0075] A1, in the experimental environment of this scenario factor currently possessed by this cladding combination, perform laser cladding on the cladding experimental material and the experimental substrate at the initial life stage with the laser cladding experimental parameters to obtain the initial characteristic values of the crack shape in the scenario experiment; the laser cladding parameters include laser power, scanning speed, preheating temperature, powder feeding amount, powder feeding speed, etc. The experimental values of the laser cladding parameters (laser cladding experimental parameters) can be set, for example, with a specified laser power, a specified scanning speed, a specified preheating temperature, a specified powder feeding amount, and a specified powder feeding speed. The specified values of the laser cladding parameters are empirical values, which are the empirical values with the lowest probability of crack generation.

[0076] A2, in the real environment with this scenario factor (the differences in thermal expansion coefficients and melting points cannot be ignored), perform laser cladding on each sample combination with different life stages with the same laser cladding experimental parameters to obtain the crack shape change characteristic values associated with each sample combination;

[0077] It should be noted here that the fact that each sample combination has different life stages means that at least one of the cladding sample material and the sample substrate in each sample combination is in a different life stage. For example, the same type of cladding sample material in two sample combinations is in the same life stage, but the same type of sample substrate is in different life stages; or the same type of cladding sample material in two sample combinations is in different life stages, but the same type of sample substrate is in the same life stage; or both the cladding sample material and the sample substrate in two sample combinations are in different life stages. In addition, the types of the cladding experimental material, the cladding sample material, and the cladding material constituting the cladding combination are the same, such as yttria-stabilized zirconia, and the types of the experimental substrate, the sample substrate, and the substrate constituting the cladding combination are also the same, such as Ni.

[0078] A3. Compare the eigenvalues of the changed crack shapes in each scenario experiment obtained in step A2 with the initial eigenvalues of the crack shapes in the scenario experiment obtained in step A1 to filter out the eigenvalues of the changed crack shapes in the scenario experiment whose similarity is less than the similarity threshold.

[0079] It should be noted here that the differences in the thermal expansion coefficients and melting points at different life stages have relatively minor effects on the initial eigenvalues of the crack shapes in the scenario experiment formed by the same type of cladding material and substrate in an experimental environment with the same scenario factors under the same laser cladding experimental parameters. The eigenvalues of the changed crack shapes in the scenario experiment and the initial eigenvalues of the crack shapes in the scenario experiment theoretically do not differ much. Therefore, step A3 realizes the filtering of invalid shape samples, making the constructed univariate high-degree function more accurately represent the influence degree of each sample combination in different life stages on the eigenvalues of the changed crack shapes in the scenario experiment.

[0080] It should also be noted here that the initial eigenvalues of the crack shapes in the scenario experiment are the numerical representations of the initially formed crack shapes; the eigenvalues of the changed crack shapes in the scenario experiment are the numerical representations of the changed crack shapes. For example, the shape of a crack can be represented by parameters such as the length, width, and bending angle of the crack. For the convenience of calculation, in this embodiment, the crack shape characteristics expressed in the form of an image are converted into the eigenvalues representing the shape in numerical form. There are currently many such conversion methods, and the core lies in establishing a conversion relationship between the numerical value and the shape. Since the conversion process is not within the scope of the rights claimed in this application, no specific description is given.

[0081] Similarly, in step A3, there are many methods for comparing the similarity between the changed eigenvalue of the crack shape in the scenario experiment and the initial eigenvalue of the crack shape in the scenario experiment. For example, the absolute value of the difference between the two eigenvalues can be calculated. If the absolute value of the difference is greater than the preset absolute value threshold of the difference, it is determined that the two do not have similarity, and then the changed eigenvalue of the crack shape in this scenario experiment is filtered out.

[0082] After the filtering in step A3 is completed, the method for constructing the univariate high-degree function proceeds to the steps:

[0083] A4. Classify each remaining sample combination after being filtered in step A3 to obtain the fitting sample combinations respectively used for fitting the first curve and the second curve. The classification method is specifically as follows:

[0084] Classify each sample combination with the absolute value of the difference in thermal expansion coefficient less than the first difference threshold as the first fitting sample combination, and the first fitting sample combination is used to construct the second fitting function; classify each sample combination with the absolute value of the difference in melting point less than the second difference threshold as the second fitting sample combination, and the second fitting sample combination is used to construct the first fitting function.

[0085] For example, assume that the remaining sample combinations after filtering include combinations c1, c2, c3, and c4. Among them, assume that the differences in thermal expansion coefficient and melting point between the cladding sample material and the sample substrate in combination c1 are t1 and m1 respectively, and the differences in thermal expansion coefficient and melting point between the cladding sample material and the sample substrate in combination c2 are t2 and m2 respectively, and the absolute value of the difference between t1 and t2 is less than the first difference threshold. Then classify combinations c1 and c2 as the first fitting sample combinations for constructing the second fitting function and add them to the first fitting sample combination set. Assume that the differences in melting point between the cladding sample material and the sample substrate in combinations c3 and c4 are m3 and m4 respectively, and the absolute value of the difference between m3 and m4 is less than the second difference threshold. Then classify combinations c3 and c4 as the second fitting sample combinations for constructing the first fitting function and add them to the second fitting sample combination set. To improve the feature distinctiveness among the first fitting samples in the first fitting sample combination set, preferably, the absolute value of the difference in melting point between any two first fitting sample combinations is greater than the second difference threshold. Similarly, to improve the feature distinctiveness among the second fitting samples in the second fitting sample combination set, preferably, the absolute value of the difference in thermal expansion coefficient between any two second fitting sample combinations is greater than the first difference threshold.

[0086] A5. Fit the first curve or the second curve with the corresponding fitting sample combination to solve the coefficient of the term of the first fitting function associated with the first curve and the coefficient of the term of the second fitting function associated with the second curve;

[0087] Specifically, the method for solving the coefficient of the term of the second fitting function is:

[0088] Taking the characteristic value of the change in the crack shape of the scenario experiment associated with each first fitting sample combination as the dependent variable of the second fitting function, and taking the melting point difference between the clad sample material and the sample substrate in the corresponding first fitting sample combination of the characteristic value of the change in the crack shape of the scenario experiment as the independent variable, the term coefficients of the second fitting function are inversely deduced and solved, so as to complete the construction of the second fitting function;

[0089] The method for solving the term coefficients of the first fitting function is as follows:

[0090] Taking the characteristic value of the change in the crack shape of the scenario experiment associated with each second fitting sample combination as the dependent variable of the first fitting function, and taking the coefficient of thermal expansion difference between the clad material and the sample substrate in the corresponding second fitting sample combination of the characteristic value of the change in the crack shape of the scenario experiment as the independent variable, the term coefficients of the first fitting function are inversely deduced and solved, so as to complete the construction of the first fitting function.

[0091] It should be noted here that the fluctuations of the first curve fitted by the first fitting function and the second curve fitted by the second fitting function reflect the change characteristics of the samples in the same type but at different life stages under the same scenario factor for the characteristic that "the greater the coefficient of thermal expansion difference and melting point difference, the easier it is to generate cracks", that is, when the scenario factor and / or the type of the sample combination change, the change characteristics of the fluctuations of the first curve and the second curve for the characteristic that "the greater the coefficient of thermal expansion difference and melting point difference, the easier it is to generate cracks" change accordingly, so that the first curve and the second curve can better characterize the influence characteristics of each sample combination with a coefficient of thermal expansion difference and / or melting point difference for the clad material and the substrate of the same type but at different life stages on changing the initial characteristics of the scenario experiment crack shape formed in the experimental environment with the same scenario factor, that is, considering the mutual influence relationship between the scenario factor and the characteristic that "the greater the coefficient of thermal expansion and melting point difference, the easier it is to generate cracks" on changing the initial characteristics of the scenario experiment crack shape formed in the experimental environment with this scenario factor without considering the coefficient of thermal expansion difference and melting point difference at different life stages, thereby making the comprehensive influence amount calculated in step S13 below more accurate, which is beneficial to improving the accuracy of the subsequent adjustment of the laser cladding parameters, and further greatly improving the laser cladding quality.

[0092] Through step S11, for the coefficient of thermal expansion difference and melting point difference of the clad material and the substrate at the current life stage, the y values of the first fitting function and the second fitting function are solved, that is, after obtaining the change characteristic values of the current coefficient of thermal expansion difference and the current melting point difference on the initial characteristic value of the scenario experiment crack shape respectively, in step S1, the method for calculating the comprehensive influence amount of the comprehensive difference between the coefficient of thermal expansion and the melting point on changing the initial characteristic value of the scenario experiment crack shape formed in the experimental environment with this scenario factor that the clad material currently has is transferred to the step:

[0093] S12. Calculate the absolute value of the difference between the y - value of the first fitting function and the initial eigenvalue of the crack shape in the scenario experiment, as the first influence quantity of the coefficient of thermal expansion difference in the current life stage on changing the initial eigenvalue of the crack shape in this scenario experiment; calculate the absolute value of the difference between the y - value of the second fitting function and the initial eigenvalue of the crack shape in this scenario experiment, as the second influence quantity of the melting point difference in the current life stage on changing the initial eigenvalue of the crack shape in this scenario experiment.

[0094] S13. Obtain the piece - wise compensation function corresponding to the cladding combination with the first influence quantity and the second influence quantity, and use the y - value obtained by solving the obtained piece - wise compensation function as the comprehensive influence quantity of the comprehensive difference between the coefficient of thermal expansion and the melting point on changing the initial eigenvalue of the crack shape in the scenario experiment.

[0095] In this embodiment, the piece - wise compensation function is preferably a quadratic function of one variable. The method for constructing the piece - wise compensation function includes the steps:

[0096] B1. Obtain the first influence quantity and the second influence quantity respectively possessed by each sample combination, and obtain the first influence quantity numerical interval with the maximum value among the first influence quantities as the interval upper limit and the minimum value as the interval lower limit, and obtain the second influence quantity numerical interval with the maximum value among the second influence quantities as the interval upper limit and the minimum value as the interval lower limit.

[0097] For example, assume that among n sample combinations, the minimum value of the first influence quantity is minc2 and the maximum value is maxc8, then the first influence quantity numerical interval is [minc2, maxc8]. Similarly, assume that among n sample combinations, the minimum value of the second influence quantity is minc5 and the maximum value is maxc29, then the second influence quantity numerical interval is [minc5, maxc29].

[0098] B2. Divide the first influence quantity numerical interval and the second influence quantity numerical interval into several interval segments with their respective corresponding numerical intervals.

[0099] For example, assume that the first influence quantity numerical interval is divided into 10 interval segments, then the corresponding numerical interval is Assume that the second influence quantity numerical interval is divided into 8 interval segments, then the corresponding numerical interval is

[0100]

[0101] B3. Classify the remaining sample combinations after being filtered by step A3 to obtain the first piece - wise compensation sample group set and the second piece - wise compensation sample group set.

[0102] In step B3, the method for classifying the remaining sample combinations after being filtered by step A3 is:

[0103] The sample combinations where the y-value of the first fitting function is greater than the y-value of the second fitting function are added to the first segmented compensation sample group set; the sample combinations where the y-value of the first fitting function is less than or equal to the y-value of the second fitting function are added to the second segmented compensation sample group set;

[0104] For example, for the sample combination c1, assuming that the difference in the coefficient of thermal expansion between the clad sample material and the sample substrate in c1 is substituted into the first fitting function, and the obtained y-value is greater than the y-value obtained by substituting the difference in the melting point between the clad sample material and the sample substrate in c1 into the second fitting function, then the sample combination c1 is added to the first segmented compensation sample group set; otherwise, it is added to the second segmented compensation sample group set;

[0105] B4. Each sample combination in the first segmented compensation sample group set is grouped into the first segmented compensation sample group subset bound to the first interval segment into which the first influencing quantity of the sample combination falls, and each sample combination in the second segmented compensation sample group set is grouped into the second segmented compensation sample group subset bound to the second interval segment into which the second influencing quantity of the sample combination falls;

[0106] Taking the grouping of the first segmented compensation sample group subset as an example, the grouping method is described:

[0107] For example, for the sample combination c1 in the first segmented compensation sample group set, assuming that the first influencing quantity associated with c1 falls into the first interval segment represented as and this first interval segment is bound to the first segmented compensation sample group subset numbered "001", then the sample combination c1 is added to the first segmented compensation sample group subset numbered "001".

[0108] B5. Taking the second unit influencing quantity and the first crack shape characteristic value deviation of each sample combination in the first segmented compensation sample group subset as the dependent variable and independent variable of the first segmented compensation function bound to the first segmented compensation sample group subset respectively, and taking the first unit influencing quantity and the second crack shape characteristic value deviation of each sample combination in the second segmented compensation sample group subset as the dependent variable and independent variable of the second segmented compensation function bound to the second segmented compensation sample group subset respectively, the term coefficients of the first segmented compensation function and / or the second segmented compensation function are obtained by curve fitting.

[0109] The second unit influencing quantity is: the ratio of the absolute value of the difference between the y-value of each sample combination in the first segmented compensation sample group subset in the second fitting function and the actual crack shape characteristic value of the sample combination scenario to the melting point difference of the sample combination;

[0110] For example, assume that in the subset of the first segmented compensation sample group, there are sample combinations c1, c2, c3, ……, cn, where n is the number of sample combinations in the subset of the first segmented compensation sample group. Among them, the y value of the melting point difference c1dm of the sample combination c1 in the second fitting function is c1b2, and the y value of the coefficient of thermal expansion difference c1dt in the first fitting function is c1b1. Assume that the crack shape eigenvalue (defined as the true crack shape eigenvalue of the scenario) formed by the sample combination c1 in the real environment with the above scenario factors is v1. Then, the second unit influence amount of the sample combination c1 is as follows:

[0111] The first crack shape eigenvalue deviation is: the absolute value of the difference between the true crack shape eigenvalue of the scenario of the sample combination with the second unit influence amount in the subset of the first segmented compensation sample group and the y value in the first fitting function. For example, the second unit influence amount of the sample combination c1 in the above example of the subset of the first segmented compensation sample group is And the true crack shape eigenvalue of the scenario of this sample combination c1 is v1, and the y value of the coefficient of thermal expansion difference of this sample combination c1 in the first fitting function is c1b1. Then, the first crack shape eigenvalue deviation is |c1b1 - v1|.

[0112] Taking the second unit influence amount of the sample combination c1 in the above example as the dependent variable of the first segmented compensation function, and the first crack shape eigenvalue deviation |c1b1 - v1| as the independent variable of the first segmented compensation function. At the same time, fit the data points formed by all the sample combinations in the subset of the first segmented compensation sample group including the sample combination c1 into the first segmented compensation curve, and then inversely deduce and solve the term coefficients of the first segmented compensation function according to this first segmented compensation curve, so as to complete the construction of the first segmented compensation function in step B5.

[0113] The method for constructing the second segmented compensation function corresponding to the subset of the second segmented compensation sample group is the same as the construction method of the first segmented compensation function, so it will not be elaborated here.

[0114] It can be seen from steps B1 - B5 that in step S13, there are two segmented compensation functions obtained according to the first influence amount and the second influence amount of the cladding combination, namely the first segmented compensation function associated with the first interval segment where the first influence amount of the cladding combination falls and the second segmented compensation function associated with the second interval segment where the second influence amount falls. Therefore, in step S13, there are two comprehensive influence amounts of the y value of the segmented compensation function on changing the initial eigenvalue of the experimental crack shape of the thermal expansion coefficient difference and the melting point difference of the cladding combination.

[0115] The following specifically elaborates on the method for calculating the comprehensive influence amount associated with the cladding combination in step S13:

[0116] Solve for the first average value of the scene true crack shape characteristic values of each sample combination in the first segmented compensation sample group subset bound by the first interval segment in which the first influence quantity of the cladding combination falls, and use the difference in the thermal expansion coefficients of the cladding combination as the independent variable of the constructed first fitting function to solve for the y value of the first fitting function. Then, use the absolute value of the difference between the first average value and the y value of the first fitting function solved as the independent variable of the first segmented compensation function to solve for the y value of the first segmented compensation function as the first comprehensive influence quantity associated with the cladding combination;

[0117] For example, the first segmented compensation sample group subset bound by the first interval segment in which the first influence quantity of the cladding combination falls includes sample combinations c1, c2, and c3. Assume that the scene true crack shape characteristic values of sample combinations c1, c2, and c3 are denoted as v1, v2, and v3 respectively. Then the first average value is Assume that the difference in the thermal expansion coefficients of the cladding combination is denoted as t1. Then substitute t1 as the independent variable into the constructed first fitting function to solve for the y value of the first fitting function. Then, use The absolute value of the difference from the y value of the first fitting function as the independent variable of the first segmented compensation function associated with the first segmented compensation sample group subset to solve for the y value of the first segmented compensation function as the first comprehensive influence quantity of the cladding combination.

[0118] The method for solving the second comprehensive influence quantity of the cladding combination is as follows:

[0119] Solve for the second average value of the scene true crack shape characteristic values of each sample combination in the second segmented compensation sample group subset bound by the second interval segment in which the second influence quantity of the cladding combination falls, and use the difference in the melting points of the cladding combination as the independent variable of the constructed second fitting function to solve for the y value of the second fitting function. Then, use the absolute value of the difference between the second average value and the y value of the second fitting function solved as the independent variable of the second segmented compensation function associated with the second segmented compensation sample group subset to solve for the y value of the second segmented compensation function as the second comprehensive influence quantity associated with the cladding combination.

[0120] Preferably, in this embodiment, the y-value of the piecewise compensation function with a larger y-value is used as the comprehensive influence amount for predicting the predicted value of the actual crack shape characteristics of the cladding combination in step S2 below. The larger y-value in the two piecewise compensation functions represents the maximum crack shape characteristic change value of the y-value of the first fitting function or the second fitting function for laser cladding of the cladding combination at the current life stage with the laser cladding experimental parameters under the above scenario factors. This means that in step S3 below, it is more necessary to adjust the laser cladding experimental parameters to resist this larger y-value of the piecewise compensation function, in order to reduce the probability of the deviation of the first crack shape characteristic value or the second crack shape characteristic value represented by this larger y-value. Therefore, in this embodiment, preferably, the y-value of the piecewise compensation function with a larger y-value is used as the comprehensive influence amount.

[0121] However, in fact, assuming that the y-value of the first piecewise compensation function is greater than the y-value of the second piecewise compensation function, but for the same cladding combination, when laser cladding is performed on this cladding combination with the laser cladding experimental parameters, there is a certain probability of the deviation of the first crack shape characteristic value or the deviation of the second crack shape characteristic value. Since the y-values of the first piecewise compensation function and the second piecewise compensation function are both predicted values, therefore, theoretically, it is possible to choose to adjust the laser cladding parameters (such as laser power, laser cladding speed, etc.) that can resist the deviation of the first crack shape characteristic value represented by the y-value of the first piecewise compensation function, or it is possible to choose to adjust the laser cladding parameters (such as powder feeding amount, powder feeding speed, etc.) that can resist the deviation of the second crack shape characteristic value represented by the y-value of the second piecewise compensation function, or it is also possible to choose to simultaneously adjust the laser cladding parameters (such as laser power, laser cladding parameters, powder feeding amount, powder feeding speed, etc.) that can resist the deviation of the first crack shape characteristic value and the deviation of the second crack shape characteristic value respectively represented by the y-values of the first piecewise compensation function and the second piecewise compensation function. Therefore, after calculating the comprehensive influence amount of the comprehensive difference in the thermal expansion coefficient and melting point of the cladding combination on the initial characteristic value of the scenario experimental crack shape through the above step S1, any one of the following 3 strategies is used to adjust the laser cladding experimental parameters, and then laser cladding is started on the cladding combination.

[0122] The 3 adjustment strategies are specifically as follows:

[0123] After calculating the comprehensive influence amount of the cladding combination on the initial characteristic value of the scenario experimental crack shape through step S1, first transfer to the steps as Figure 1 shown:

[0124] S2. According to the comprehensive influence amount calculated in step S1, predict the predicted value of the actual crack shape characteristics of the scenario expected to be generated by laser cladding the cladding combination with the laser cladding experimental parameters;

[0125] S3. According to the type and magnitude of the predicted values of the true crack shape features of the scenario obtained in step S2, after adjusting the laser cladding experimental parameters using the corresponding strategy, laser cladding is started on the cladding combination.

[0126] The prediction method in step S2 is specifically as follows:

[0127] Calculate the sum value of the first comprehensive influence quantity, the y value of the cladding combination in the first fitting function, and the initial characteristic value of the crack shape in the scenario experiment (defined as the first sum value), and / or the sum value of the second comprehensive influence quantity, the y value of the cladding combination in the second fitting function, and the initial characteristic value of the crack shape in the scenario experiment (defined as the second sum value) as the predicted value of the true crack shape features of the scenario predicted for this cladding combination.

[0128] The above-mentioned first sum value is associated with the first type, and the second sum value is associated with the second type. Among them, the first type is bound with a first set of laser parameter adjustments having the ability to resist changing the initial characteristic value of the crack shape in the scenario experiment to the first sum value; the second type is bound with a second set of laser parameter adjustments having the ability to resist changing the initial characteristic value of the crack shape in the scenario experiment to the second sum value.

[0129] For example, for a cladding combination with "yttria-stabilized zirconia" as the cladding material and "Ni" as the substrate, under the scenario factors of "the molten pool material cools and shrinks, the stress at both ends of the cladding layer is relatively large, and the tensile stress in the X direction is the largest at the bonding layer between the substrate and the YSZ coating", laser cladding is to be carried out with the laser cladding experimental parameters determined by the empirical values summarized from repeated experiments. Assume that the laser cladding experimental parameters include laser power, scanning speed, preheating temperature, powder feeding amount, and powder feeding speed, and these experimental parameters each have corresponding initial empirical parameter values.

[0130] When the predicted value of the true crack shape features of the scenario expected to be generated by laser cladding the cladding combination with these laser cladding experimental parameters is obtained in step S2, if the predicted value of the true crack shape features of the scenario corresponds to the first sum value, then the first set of laser parameter adjustments associated with the first sum value is matched. If the predicted value of the true crack shape features of the scenario corresponds to the second sum value, then the second set of laser parameter adjustments associated with the second sum value is matched.

[0131] For example, if the first sum value is assumed to be v11 and the initial characteristic value of the crack shape in the scenario experiment is assumed to be v0, then the resistance to changing v0 to v11 is v11 - v0. Therefore, the change amount of each laser cladding parameter value in the first laser parameter adjustment set relative to the empirical initial parameter value of the same type of experimental parameter in the laser cladding experimental parameters can resist the resistance amount of v11 - v0. For example, the laser cladding experimental parameters include laser power p1, scanning speed p2, preheating temperature p3, powder feeding amount p4, and powder feeding speed p5. The parameter values of the experimental parameters p1, p2, p3, p4, and p5 are respectively expressed as vp1, vp2, vp3, vp4, and vp5. Assume that the laser power is adjusted from vp1 to vp11 and the scanning speed is adjusted from vp2 to vp22, which is sufficient to resist the resistance amount of v11 - v0. Then the respective laser cladding parameter values in the first laser parameter adjustment set are: the parameter value of the laser power is vp11, the parameter value of the scanning speed is vp22, the parameter value of the preheating temperature remains vp3, the parameter value of the powder feeding amount remains vp4, and the parameter value of the powder feeding speed remains vp5.

[0132] It should be noted here that the change amount that each parameter value in the first laser parameter adjustment set can resist the change of v11 - v0 compared with the empirical initial parameter value of the same type of experimental parameter is obtained by summarizing repeated experiments. For example, it can also be obtained by fitting prediction through a corresponding curve fitting function. For example, for each cladding sample combination with a predicted change amount of v11 - v0 in the corresponding life stage using the laser cladding experimental parameters, one of the laser cladding experimental parameters is selected as the parameter to be adjusted, and the parameter values of the other parameters remain unchanged. Taking the adjusted parameter value of each adjustment of the extracted parameter as the independent variable and the characteristic value of the real crack shape of the cladding sample combination within the specified time length under the adjusted parameter value as the dependent variable, a quadratic function of one variable is fitted, and the parameter value of the adjusted parameter corresponding to the valley value in the fitting curve represented by the quadratic function of one variable is used as the parameter value that can resist the change amount of v11 - v0. In the same way, the corresponding parameter values of each parameter in the laser cladding experimental parameters that can resist the change amount of v11 - v0 are obtained. Since the calculation method of the change amount that each parameter value in the first laser parameter adjustment set can resist the change of v11 - v0 compared with the empirical initial parameter value of the same type of experimental parameter is not within the scope of the claims of this application, no specific description is given.

[0133] The specific setting method of each parameter value in the second laser parameter adjustment set is the same as that of the first laser parameter adjustment set, and will not be elaborated here.

[0134] In addition, it should be noted that when step S2 predicts using the first comprehensive influence quantity and the second comprehensive influence quantity respectively, and obtains the predicted values of the real crack shape characteristics of two scenarios for the same cladding combination, compare the parameter values of the common laser parameters in the first laser parameter adjustment set and the second laser parameter adjustment set, and update the parameter values of the same type of laser cladding experimental parameters with the parameter values of the common laser parameters having the smallest change amount.

[0135] For example, the first laser cladding parameter adjustment set includes laser power, scanning speed, and powder feeding amount; the second laser cladding parameter adjustment set includes scanning speed, powder feeding amount, and powder feeding speed. Assume that the absolute value of the difference between the scanning speed in the first laser cladding parameter adjustment set and the scanning speed in the laser cladding experimental parameters is smaller than the absolute value of the difference between the scanning speed in the second laser cladding parameter adjustment set and the scanning speed in the laser cladding experimental parameters. Then, update the parameter value of the scanning speed in the laser cladding experimental parameters with the scanning speed in the first laser cladding parameter adjustment set. Assume that the absolute value of the difference between the powder feeding amount in the first laser cladding parameter adjustment set and the powder feeding amount in the laser cladding experimental parameters is larger than the absolute value of the difference between the powder feeding amount in the second laser cladding parameter adjustment set and the powder feeding amount in the laser cladding experimental parameters. Then, update the parameter value of the powder feeding amount in the laser cladding experimental parameters with the powder feeding amount in the second laser cladding parameter adjustment set. Update the parameter values of the same type of laser cladding experimental parameters with the parameter values of the common laser parameters having the smallest change amount, making the laser cladding process smoother and conducive to reducing the probability of crack generation.

[0136] In summary, through the comprehensive influence quantity calculated for the cladding combination in step S1 of the present application, the prediction of the predicted value of the real crack shape characteristics of the scenario expected to be generated by the laser cladding to be performed on the cladding combination using the laser cladding experimental parameters is realized. In step S3, match the corresponding first laser parameter adjustment set and / or second laser parameter adjustment set according to the type and size of the predicted value of the real crack shape characteristics of the scenario predicted for the cladding combination, and then update the parameter values of the same type of laser cladding experimental parameters with the respective laser parameter values in the first laser parameter adjustment set or the second laser parameter adjustment set, or the smaller change value of the common laser parameters in the first laser parameter adjustment set and the second laser parameter adjustment set, realizing the rapid and accurate adjustment of the laser cladding experimental parameter values that can resist the generation of the predicted value of the real crack shape characteristics of the scenario.

[0137] It should be noted that the above specific embodiments are only the preferred embodiments of the present invention and the technical principles applied. Those skilled in the art should understand that various modifications, equivalent replacements, changes, etc. can also be made to the present invention. However, as long as these transformations do not depart from the spirit of the present invention, they should be within the protection scope of the present invention. In addition, some terms used in the description and claims of this application are not restrictive, but are only for the convenience of description.

Claims

1. A laser cladding method based on feedback adjustment under the constraint of thermal expansion and melting point difference, characterized in that Including the steps: S1. Obtain the differences in thermal expansion coefficients and melting points between the cladding material and the substrate that make up the cladding combination at the current life stage, and calculate the comprehensive influence amount of the comprehensive differences in thermal expansion coefficients and melting points on changing the initial characteristic values of the scenario experimental crack shape formed under the experimental environment of the scenario factors currently possessed by the cladding combination through the difference point matching method; S2. Predict the predicted values of the characteristics of the scenario real crack shape that is expected to be generated by laser cladding on the cladding combination with the laser cladding experimental parameters according to the comprehensive influence amount calculated in step S1; S3. After adjusting the laser cladding experimental parameters by corresponding strategies according to the type and size of the predicted values of the characteristics of the scenario real crack shape predicted in step S2, start laser cladding on the cladding combination.

2. The laser cladding method based on feedback adjustment under the constraints of thermal expansion and melting point difference according to claim 1, wherein In step S1, the method for calculating the comprehensive influence amount of the comprehensive differences in thermal expansion coefficients and melting points on changing the initial characteristic values of the scenario experimental crack shape formed under the experimental environment of the scenario factors currently possessed by the cladding combination includes the steps: S11. Substitute the obtained differences in thermal expansion coefficients and melting points between the cladding material and the substrate at the current life stage into the first fitting function and the second fitting function respectively as independent variables, and solve for the y values of the first fitting function and the second fitting function; S12. Calculate the absolute value of the difference between the y value of the first fitting function and the initial characteristic value of the scenario experimental crack shape as the first influence amount of the difference in thermal expansion coefficients at the current life stage on changing the initial characteristic value of the scenario experimental crack shape; calculate the absolute value of the difference between the y value of the second fitting function and the initial characteristic value of the scenario experimental crack shape as the second influence amount of the difference in melting points at the current life stage on changing the initial characteristic value of the scenario experimental crack shape; S13. Obtain the piecewise compensation function corresponding to the cladding combination with the first influence amount and the second influence amount, and take the y value obtained by solving the obtained piecewise compensation function as the comprehensive influence amount of the comprehensive difference on changing the initial characteristic value of the scenario experimental crack shape.

3. The laser cladding method based on feedback adjustment under the constraints of thermal expansion and melting point difference according to claim 2, wherein, The first fitting function and / or the second fitting function is a univariate high-order function, and the method for constructing the univariate high-order function includes the steps: A1. Under the experimental environment where the cladding combination currently has the scenario factors, perform laser cladding on the cladding experimental material and the experimental substrate at the initial stage of life with the laser cladding experimental parameters to obtain the initial characteristic values of the scenario experimental crack shape; A2. In the same real environment with the scenario factors, perform laser cladding on each sample combination with different life stages with the same laser cladding experimental parameters to obtain the changed characteristic values of the scenario experimental crack shape associated with each sample combination; At least one of the life stages of the cladding sample materials and sample substrates in each of the sample combinations is different; A3. Compare the similarity between the crack shape change characteristic values of each of the scenario experiments and the initial crack shape characteristic values of the scenario experiments to filter out the crack shape change characteristic values of the scenario experiments with a similarity less than the similarity threshold; A4. Classify each of the remaining sample combinations after being filtered in step A3 to obtain fitting sample combinations for fitting the first curve and the second curve respectively; A5. Fit the first curve or the second curve with the corresponding fitting sample combinations to solve for the term coefficients of the first fitting function associated with the first curve and the term coefficients of the second fitting function associated with the second curve; The types of the clad experimental materials, the clad sample materials, and the clad materials are the same; the types of the experimental substrates, the sample substrates, and the substrates are the same.

4. The laser cladding method based on feedback adjustment under the constraints of thermal expansion and melting point difference according to claim 3, characterized in that In step A4, the method for classifying each of the remaining sample combinations after being filtered in step A3 is as follows: Classify the sample combinations with the absolute value of the difference in thermal expansion coefficients less than the first difference threshold as the first fitting sample combinations, and the first fitting sample combinations are used to construct the second fitting function; classify the sample combinations with the absolute value of the difference in melting points less than the second difference threshold as the second fitting sample combinations, and the second fitting sample combinations are used to construct the first fitting function; The absolute value of the difference in melting points between any two of the first fitting sample combinations is greater than the second difference threshold; the absolute value of the difference in thermal expansion coefficients between any two of the second fitting sample combinations is greater than the first difference threshold.

5. The laser cladding method based on feedback adjustment under the constraint of thermal expansion and melting point difference according to claim 4, characterized in that In step A5, the method for solving the term coefficients of the second fitting function is as follows: Use the crack shape change characteristic values of the scenario experiments respectively associated with the first fitting sample combinations as the dependent variables of the second fitting function, and use the difference in melting points of the clad sample materials and the sample substrates in the corresponding first fitting sample combinations of the crack shape change characteristic values of the scenario experiments as the independent variables, and inversely solve for the term coefficients of the second fitting function; The method for solving the term coefficients of the first fitting function is as follows: Use the crack shape change characteristic values of the scenario experiments respectively associated with the second fitting sample combinations as the dependent variables of the first fitting function, and use the difference in thermal expansion coefficients of the clad sample materials and the sample substrates in the corresponding second fitting sample combinations of the crack shape change characteristic values of the scenario experiments as the independent variables, and inversely solve for the term coefficients of the first fitting function.

6. The laser cladding method based on feedback adjustment under the constraints of thermal expansion and melting point difference according to claim 3, wherein, The piecewise compensation function in step S13 is a quadratic function of one variable, and the method for constructing the piecewise compensation function includes the following steps: B1. Obtain the first influence quantity and the second influence quantity respectively possessed by each of the sample combinations, use the maximum value in each of the first influence quantities as the upper limit of the interval and the minimum value as the lower limit of the interval to obtain the first influence quantity numerical interval, and use the maximum value in each of the second influence quantities as the upper limit of the interval and the minimum value as the lower limit of the interval to obtain the second influence quantity numerical interval; B2. Divide the first influence quantity numerical interval and the second influence quantity numerical interval into several interval segments at corresponding numerical intervals; B3. Classify each of the remaining sample combinations after filtering in step A3 to obtain a first set of segmented compensation sample groups and a second set of segmented compensation sample groups; B4. Group each of the sample combinations in the first set of segmented compensation sample groups into a first subset of segmented compensation sample groups bound to the first interval segment into which the first influencing quantity of the sample combination falls, and group each of the sample combinations in the second set of segmented compensation sample groups into a second subset of segmented compensation sample groups bound to the second interval segment into which the second influencing quantity of the sample combination falls; B5. Use the second unit influencing quantity and the first crack shape eigenvalue deviation of each of the sample combinations in the first subset of segmented compensation sample groups as the dependent variable and independent variable, respectively, of the first segmented compensation function bound to the first subset of segmented compensation sample groups, and use the first unit influencing quantity and the second crack shape eigenvalue deviation of each of the sample combinations in the second subset of segmented compensation sample groups as the dependent variable and independent variable, respectively, of the second segmented compensation function bound to the second subset of segmented compensation sample groups, and solve for the term coefficients of the first segmented compensation function and / or the second segmented compensation function through curve fitting.

7. The laser cladding method based on feedback adjustment under the constraints of thermal expansion and melting point difference according to claim 6, characterized in that In step B3, the method for classifying each of the remaining sample combinations after filtering in step A3 is as follows: Add the sample combinations for which the y value of the first fitting function is greater than the y value of the second fitting function to the first set of segmented compensation sample groups; add the sample combinations for which the y value of the first fitting function is less than or equal to the y value of the second fitting function to the second set of segmented compensation sample groups; The second unit influencing quantity in step B5 is: the ratio of the absolute value of the difference between the y value of each of the sample combinations in the first subset of segmented compensation sample groups in the second fitting function and the actual crack shape eigenvalue of the sample combination to the melting point difference of the sample combination; The first crack shape eigenvalue deviation in step B5 is: the absolute value of the difference between the actual crack shape eigenvalue of the sample combination having the second unit influencing quantity in the first subset of segmented compensation sample groups and the y value in the first fitting function; The first unit influencing quantity in step B5 is: the ratio of the absolute value of the difference between the y value of each of the sample combinations in the second subset of segmented compensation sample groups in the first fitting function and the actual crack shape eigenvalue of the sample combination to the coefficient of thermal expansion difference of the sample combination; The second crack shape eigenvalue deviation in step B5 is: the absolute value of the difference between the actual crack shape eigenvalue of the sample combination having the first unit influencing quantity in the second subset of segmented compensation sample groups and the y value in the second fitting function.

8. The laser cladding method based on feedback adjustment under the constraints of thermal expansion and melting point difference according to claim 6, characterized in that In step S13, the method for obtaining the corresponding segmented compensation function for the cladding combination is as follows: Judge whether the y value of the cladding combination in the first segmented compensation function associated with the first influencing quantity is greater than the y value of the cladding combination in the second segmented compensation function associated with the second influencing quantity. If so, use the first piecewise compensation function as the obtained piecewise compensation function; If not, use the second piecewise compensation function as the obtained piecewise compensation function.

9. The laser cladding method based on feedback adjustment under the constraints of thermal expansion and melting point difference according to claim 6, wherein In step S13, the method for calculating the comprehensive influence amount associated with the cladding combination is as follows: Solve the first average value of the scene true crack shape feature values of each sample combination in the first piecewise compensation sample group subset bound to the first interval segment into which the first influence amount of the cladding combination falls, and use the thermal expansion coefficient difference of the cladding combination as the independent variable of the constructed first fitting function to solve the y value of the first fitting function. Then, use the absolute value of the difference between the first average value and the y value of the first fitting function solved as the independent variable of the first piecewise compensation function to solve the y value of the first piecewise compensation function as the first comprehensive influence amount associated with the cladding combination; Solve the second average value of the scene true crack shape feature values of each sample combination in the second piecewise compensation sample group subset bound to the second interval segment into which the second influence amount of the cladding combination falls, and use the melting point difference of the cladding combination as the independent variable of the constructed second fitting function to solve the y value of the second fitting function. Then, use the absolute value of the difference between the second average value and the y value of the second fitting function solved as the independent variable of the second piecewise compensation function to solve the y value of the second piecewise compensation function as the second comprehensive influence amount associated with the cladding combination.

10. The laser cladding method based on feedback adjustment under the constraints of thermal expansion and melting point difference according to claim 6, characterized in that, The predicted value of the scene true crack shape feature in step S2 is: the first sum of the first comprehensive influence amount, the y value of the cladding combination in the first fitting function, and the initial feature value of the scene experimental crack shape, and / or the second sum of the second comprehensive influence amount, the y value of the cladding combination in the second fitting function, and the initial feature value of the scene experimental crack shape; The first type associated with the first sum is bound with a first set of laser parameter adjustments capable of resisting changing the initial feature value of the scene experimental crack shape to the first sum; the second type associated with the second sum is bound with a second set of laser parameter adjustments capable of resisting changing the initial feature value of the scene experimental crack shape to the second sum; In step S3, match the corresponding first set of laser parameter adjustments and / or the second set of laser parameter adjustments according to the type and size of the first sum and / or the second sum, and then use each laser parameter value in the first set of laser parameter adjustments or the second set of laser parameter adjustments, or the parameter value of the common laser parameter in the first set of laser parameter adjustments and the second set of laser parameter adjustments with the smallest change amount compared to the parameter value of the same type of laser cladding experimental parameter to update the parameter value of the same type of laser cladding experimental parameter.

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