Optimization method and system based on multi-target laser cleaning parameters

Abstract

The invention provides an optimization method and system based on multi-target laser cleaning parameters, and the method comprises the steps: carrying out the initialization setting of a plurality of laser cleaning parameter sets, and enabling each set to correspond to a different cleaning target; evaluating the influence effect of the laser cleaning parameter set on the cleaning target through analogue simulation, and constructing an effect evaluation matrix; a multi-target optimization algorithm is adopted to solve conflicts among the cleaning targets, the laser cleaning parameter set is adjusted according to the effect evaluation matrix, and a target laser cleaning parameter set is obtained; when a key cleaning target is achieved in the target laser cleaning parameter set, the laser cleaning parameter with the optimal comprehensive performance is selected as a final optimization result; according to the technical scheme, a more scientific and comprehensive optimization means is provided, the cleaning quality and the parameter optimization efficiency are improved, and the efficient and intelligent laser cleaning parameter optimization process is achieved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of laser cleaning technology, and in particular to an optimization method and system based on multi-objective laser cleaning parameters. Background Art

[0002] In modern manufacturing, especially for the surface treatment of precision parts, laser cleaning technology has been widely used due to its advantages of high efficiency, precision and environmental protection. However, with the continuous improvement of industrial standards, the requirements for laser cleaning process are becoming increasingly stringent.

[0003] At present, many industrial production lines use manual adjustment methods based on experience to set laser cleaning parameters. This method relies on the operator's experience to adjust parameters such as laser power, scanning speed, pulse frequency, etc. to achieve a better cleaning effect. Manual parameter adjustment is time-consuming and easily affected by the operator's personal experience and skill level. It is difficult to ensure that the best cleaning effect can be achieved every time. With the changes in industrial needs and the advancement of technology, simple rules of thumb are increasingly difficult to adapt to diverse production environments and complex work requirements. Summary of the invention

[0004] The embodiment of the present invention provides an optimization method and system based on multi-objective laser cleaning parameters, which are used to solve the problems of low efficiency, poor cleaning effect and inability to adapt to diverse production environments and complex work requirements in the prior art.

[0005] In a first aspect, an embodiment of the present invention provides an optimization method based on multi-objective laser cleaning parameters, comprising: Initializing and setting a plurality of laser cleaning parameter sets, each set corresponding to a different cleaning target, wherein the cleaning target includes: improving cleaning efficiency, reducing material damage, and reducing energy consumption; Evaluate the effect of the laser cleaning parameter set on the cleaning target through simulation, and construct an effect evaluation matrix; A multi-objective optimization algorithm is used to resolve conflicts between the cleaning objectives, and the laser cleaning parameter set is adjusted according to the effect evaluation matrix to obtain a target laser cleaning parameter set; When the key cleaning goals are achieved in the target laser cleaning parameter set, the laser cleaning parameters with the best comprehensive performance are selected as the final optimization results. The key cleaning goals include: surface cleanliness reaches a predetermined standard, substrate is not damaged, and cleaning efficiency reaches an expected level.

[0006] Optionally, the initialization sets a plurality of laser cleaning parameter sets, each set corresponding to a different cleaning target, wherein the cleaning targets include: improving cleaning efficiency, reducing material damage, and reducing energy consumption. Defining multiple laser cleaning parameter sets, each set targeting different cleaning objectives, wherein the cleaning objectives include improving cleaning efficiency, reducing material damage, and reducing energy consumption; Setting an initial laser parameter range for each cleaning target to form a parameter combination, wherein the parameter combination includes laser power, pulse frequency, and scanning speed; Based on the cleaning target, designing an evaluation criterion for the laser cleaning parameter set; According to the evaluation criteria, multiple laser cleaning parameter sets are initialized and generated.

[0007] Optionally, evaluating the effect of the laser cleaning parameter set on the cleaning target through simulation to construct an effect evaluation matrix includes: Inputting the laser cleaning parameter set into a preset simulation model, and collecting key performance indicator data of the laser cleaning program of the preset simulation model in real time during operation, wherein the key performance indicator data includes cleaning rate, material surface quality, and energy consumption level; According to the key performance indicator data, quantitatively analyze the effect of the laser cleaning parameter set on the cleaning target, and construct a data matrix containing the key performance indicator data; Processing the data matrix using a statistical analysis method to obtain statistical analysis results; Based on the statistical analysis results, the effect evaluation matrix is ​​constructed.

[0008] Optionally, the multi-objective optimization algorithm is used to resolve the conflict between the cleaning objectives, and the laser cleaning parameter set is adjusted according to the effect evaluation matrix to obtain the target laser cleaning parameter set, which includes: Determining a multi-objective optimization objective function, wherein the optimization objectives of the objective function include: improving cleaning efficiency, reducing material damage, and reducing energy consumption; The objective function of the multi-objective optimization is as follows: ; in, represents the objective function of multi-objective optimization; Indicates cleaning efficiency; It means reducing material damage; It means reducing energy consumption; The calculation formula of cleaning efficiency is as follows: ; in, Indicates cleaning efficiency; Indicates the area cleaned per unit time; is the maximum acceptable cleaning efficiency; Indicates the efficiency reduction coefficient due to environmental factors; Among them, the calculation formula for reducing material damage is as follows: ; in, It means reducing material damage; Indicates the amount of change in the surface quality of the material; Indicates the change in surface roughness; Indicates quality loss due to processing defects; , , is the weight of the corresponding indicator; The calculation formula for reducing energy consumption is as follows: ; in, It means reducing energy consumption; represents the total energy consumption, Indicates the laser power used; Indicates the additional energy consumption due to thermal effect, , The coefficient that represents the relationship between power and energy consumption, Indicates the maximum acceptable energy consumption; Based on the objective function of the multi-objective optimization, a multi-objective optimization algorithm is introduced to determine the performance of different sets of laser cleaning parameters; Applying the multi-objective optimization algorithm to process the effect evaluation matrix, identifying a non-inferior solution frontier, wherein the non-inferior solution frontier is used to characterize a parameter set that does not have an inferiority between different cleaning objectives; According to the non-inferior solution frontier, a laser cleaning parameter set with the best comprehensive performance is selected as the target laser cleaning parameter set.

[0009] Optionally, the method further comprises: Define the initial efficiency reduction factor; Introducing an interaction term into the initial efficiency reduction coefficient to obtain a target efficiency reduction coefficient, wherein the interaction term includes: temperature and humidity; Introducing a polynomial term into the target efficiency reduction coefficient to obtain the efficiency reduction coefficient; The calculation formula of the efficiency reduction coefficient is as follows: ; ; ; Wherein, A is the first influencing parameter of the efficiency reduction coefficient; B is the second influencing parameter of the efficiency reduction coefficient; Indicates the efficiency reduction coefficient caused by the environment; Indicates temperature; Indicates humidity; Indicates air pressure; Indicates wind speed; Indicates light intensity; Indicates the optimal temperature; Indicates optimal humidity; Indicates the optimal air pressure; Indicates the optimal wind speed; Indicates the optimal light intensity; represents the standard deviation of temperature, The standard deviation of humidity, The standard deviation of air pressure, The standard deviation of wind speed, Indicates the standard deviation of light intensity; is the coefficient of the interaction between temperature and humidity, is the cubic coefficient of temperature; is the cubic coefficient of temperature.

[0010] Optionally, when a key cleaning target is achieved in the target laser cleaning parameter set, the laser cleaning parameter with the best comprehensive performance is selected as the final optimization result, and the key cleaning target includes: the surface cleanliness reaches a predetermined standard, the substrate is not damaged, and the cleaning efficiency reaches an expected level, including: Setting key cleaning effect evaluation indicators in the target laser cleaning parameter set to monitor the achievement of predetermined key cleaning targets during the cleaning process, wherein the key cleaning effect evaluation indicators include surface cleanliness and residual material content; When the key cleaning effect evaluation index caused by any combination in the target laser cleaning parameter set shows that the key cleaning target has been achieved, a predetermined comprehensive performance evaluation model is used to perform a comprehensive performance evaluation on all parameter combinations that achieve the key cleaning target to obtain a comprehensive performance evaluation result; According to the comprehensive performance evaluation result, a laser cleaning parameter combination with the best comprehensive performance is screened out, and the laser cleaning parameters with the best comprehensive performance are determined as the final optimization result.

[0011] Optionally, key cleaning effect evaluation indicators are set in the target laser cleaning parameter set to monitor the achievement of predetermined key cleaning targets during the cleaning process, and the key cleaning effect evaluation indicators include surface cleanliness and residual material content, including: The surface state during the cleaning process is monitored in real time by a sensor, and the surface state is analyzed by image processing technology to obtain surface cleanliness information; Use chemical analysis instruments to detect the residual substance content in the cleaning area to obtain residual substance information; Based on the surface cleanliness information and the residual material content information, an evaluation model is established, and the key cleaning effect evaluation index is generated by combining the surface quality and the residue distribution characteristics, where the surface quality includes: surface roughness, glossiness and defects, and the residue distribution characteristics include: density, type and morphology of the residue; The key cleaning effect evaluation index is processed using preset evaluation criteria to evaluate whether the key cleaning target is achieved, so as to monitor the achievement of the key cleaning target during the cleaning process. The evaluation criteria need to determine whether the surface cleanliness and the residual material content meet the key cleaning target.

[0012] In a second aspect, an embodiment of the present application provides an optimization system based on multi-objective laser cleaning parameters, comprising: A setting module, used to initialize and set multiple laser cleaning parameter sets, each set corresponding to a different cleaning target, wherein the cleaning targets include: improving cleaning efficiency, reducing material damage, and reducing energy consumption; A construction module is used to evaluate the effect of the laser cleaning parameter set on the cleaning target through simulation and construct an effect evaluation matrix; An adjustment module, used for adopting a multi-objective optimization algorithm to resolve conflicts between the cleaning objectives, adjusting the laser cleaning parameter set according to the effect evaluation matrix, and obtaining a target laser cleaning parameter set; A selection module is used to select the laser cleaning parameters with the best comprehensive performance as the final optimization result when the key cleaning goals are achieved in the target laser cleaning parameter set. The key cleaning goals include: the surface cleanliness reaches a predetermined standard, the substrate is not damaged, and the cleaning efficiency reaches an expected level.

[0013] In a third aspect, an embodiment of the present invention provides a computing device, comprising a processor and a memory, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute any optimization method based on multi-objective laser cleaning parameters as described in the first aspect.

[0014] In a fourth aspect, an embodiment of the present invention provides a computer storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement the optimization method based on multi-objective laser cleaning parameters as described in any one of the first aspects.

[0015] In an embodiment of the present invention, multiple laser cleaning parameter sets are initialized, each set corresponds to a different cleaning target, and the cleaning targets include: improving cleaning efficiency, reducing material damage, and reducing energy consumption; evaluating the effect of the laser cleaning parameter set on the cleaning target through simulation, and constructing an effect evaluation matrix; using a multi-objective optimization algorithm to resolve conflicts between the cleaning targets, adjusting the laser cleaning parameter set according to the effect evaluation matrix, and obtaining a target laser cleaning parameter set; when the key cleaning target is achieved in the target laser cleaning parameter set, the laser cleaning parameter with the best comprehensive performance is selected as the final optimization result, and the key cleaning targets include: surface cleanliness reaches a predetermined standard, substrate is not damaged, and cleaning efficiency reaches an expected level. The technical solution provided by the present invention provides a more scientific and comprehensive optimization method, which improves the efficiency of parameter optimization while ensuring the cleaning quality, and realizes an efficient and intelligent laser cleaning parameter optimization process.

[0016] These and other aspects of the present invention will become more apparent from the following description of the embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 A flowchart of a method for optimizing multi-objective laser cleaning parameters provided by an embodiment of the present invention; Figure 2 A schematic diagram of the structure of an optimization system based on multi-objective laser cleaning parameters provided by an embodiment of the present invention; Figure 3 A schematic diagram of the structure of a computing device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0020] In some of the processes described in the specification and claims of the present invention and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to be different types.

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0022] In modern industrial manufacturing, laser cleaning technology is widely used due to its high efficiency, precision and environmental protection. However, how to achieve multiple cleaning goals at the same time has become an important technical challenge. Based on this, the present invention provides an optimization method based on multi-objective laser cleaning parameters, such as Figure 1 ,include: Step 101: Initialize and set multiple laser cleaning parameter sets, each set corresponding to a different cleaning target, wherein the cleaning target includes: improving cleaning efficiency, reducing material damage, and reducing energy consumption; In this step, the cleaning target refers to the specific effect that is desired to be achieved during the laser cleaning process. In this embodiment, the cleaning targets include improving cleaning efficiency, reducing material damage, and reducing energy consumption.

[0023] In this step, multiple laser cleaning parameter sets are defined according to actual needs; each set contains a set of parameters, such as laser power , Scanning speed , pulse frequency Each set corresponds to different cleaning goals, including improving cleaning efficiency, reducing material damage, and reducing energy consumption. These goals are achieved through different combinations of parameter sets. For example, set set 1 to , , .

[0024] Step 102: Evaluate the effect of the laser cleaning parameter set on the cleaning target through simulation, and construct an effect evaluation matrix; In this step, the effect evaluation matrix refers to a data table with a matrix structure, which is used to record the effect of each laser cleaning parameter set on each cleaning target.

[0025] This step uses professional laser cleaning simulation software, inputs various parameter sets defined in step 101, and simulates the laser cleaning process; the simulation results include cleaning efficiency, such as cleaning area / time; material damage degree, such as surface roughness change, material removal amount; energy consumption, such as total energy consumption, etc. The simulation results are organized into a matrix form, with each row being a parameter set and each column being an effect score of a cleaning target. For example, the first row and the first column are the effect scores of set 1 on improving cleaning efficiency, the second row and the second column are the effect scores of set 2 on reducing material damage, and so on.

[0026] Step 103: using a multi-objective optimization algorithm to resolve conflicts between the cleaning objectives, adjusting the laser cleaning parameter set according to the effect evaluation matrix, and obtaining a target laser cleaning parameter set; In this step, the multi-objective optimization algorithm refers to a class of algorithms used to solve problems with multiple optimization objectives, which can optimize multiple objectives simultaneously and find non-inferior solutions or Pareto optimal solutions.

[0027] In this step, an algorithm suitable for multi-objective optimization problems is selected, such as NSGA-II. The effect evaluation matrix is ​​input as the input data of the algorithm to find the non-inferior solution frontier that has no disadvantages among the three goals of improving cleaning efficiency, reducing material damage, and reducing energy consumption; according to the non-inferior solution frontier output by the algorithm, the laser cleaning parameter set initialized is adjusted to obtain the target laser cleaning parameter set.

[0028] Step 104: When the key cleaning targets are achieved in the target laser cleaning parameter set, the laser cleaning parameters with the best comprehensive performance are selected as the final optimization result. The key cleaning targets include: the surface cleanliness reaches a predetermined standard, the substrate is not damaged, and the cleaning efficiency reaches an expected level; In this step, for each target laser cleaning parameter set, it is evaluated whether the key cleaning goals are achieved, that is, the surface cleanliness reaches the predetermined standard, the substrate is not damaged, and the cleaning efficiency reaches the expected level; in the target laser cleaning parameter set that meets the key cleaning goals, the laser cleaning parameters with the best comprehensive performance are selected as the final optimization result, and the evaluation of the comprehensive performance can be weighted averaged according to the importance of each goal.

[0029] The embodiments of the present invention can achieve the following beneficial effects through the above steps: By initializing and setting multiple laser cleaning parameter sets, evaluating their effects through simulation, and building an effect evaluation matrix, the laser cleaning parameters can be systematically optimized to ensure that the best balance point is found between multiple goals. A multi-objective optimization algorithm is used to adjust the laser cleaning parameter set according to the effect evaluation matrix, which improves the efficiency of parameter optimization and reduces the time and resources required by traditional trial and error methods; The key cleaning objectives were achieved, ensuring the quality and efficiency of the laser cleaning process; As a result, the laser cleaning parameters with the best overall performance were selected, achieving key cleaning goals and improving overall production efficiency and economic benefits.

[0030] In modern industrial manufacturing, laser cleaning technology is highly favored due to its advantages of high efficiency, precision and environmental protection. However, to achieve an ideal cleaning effect, it is necessary to find the best balance between multiple goals. Based on this, the present invention provides a specific embodiment, wherein step 101 initializes and sets multiple laser cleaning parameter sets, each set corresponding to a different cleaning target, and the cleaning target includes: improving cleaning efficiency, reducing material damage and reducing energy consumption, and specifically includes the following steps: Step 110: defining a plurality of laser cleaning parameter sets, each set targeting a different cleaning target, wherein the cleaning target includes improving cleaning efficiency, reducing material damage, and reducing energy consumption; This step clarifies the goals of laser cleaning, including improving cleaning efficiency, reducing material damage, and reducing energy consumption; multiple laser cleaning parameter sets are defined according to different cleaning goals. For example, set 1 focuses on improving cleaning efficiency, set 2 focuses on reducing material damage, and set 3 focuses on reducing energy consumption.

[0031] Step 111: setting an initial laser parameter range for each cleaning target to form a parameter combination, wherein the parameter combination includes laser power, pulse frequency, and scanning speed; In this step, the initial laser parameter range refers to the value range of the laser cleaning parameters, including the maximum and minimum values ​​of parameters such as laser power, pulse frequency and scanning speed.

[0032] This step determines the initial laser parameter range corresponding to each cleaning target. For example, the laser power range is 400 W to 800 W, the pulse frequency range is 5 kHz to 20 kHz, and the scanning speed range is 5 mm / s to 20 mm / s.

[0033] Step 112: designing an evaluation criterion for the laser cleaning parameter set based on the cleaning target; In this step, the evaluation criteria refers to a set of standards or indicators used to evaluate the degree of influence of the laser cleaning parameter set on the cleaning target. In this embodiment, the evaluation criteria include cleaning efficiency, material damage degree and energy consumption.

[0034] In this step, corresponding evaluation criteria are designed for different cleaning objectives. For example, the evaluation criteria for improving cleaning efficiency is the area cleaned per unit time; the evaluation criteria for reducing material damage is the change in surface roughness or the amount of material removed; the evaluation criteria for reducing energy consumption is the energy consumed per unit area; the evaluation criteria are quantified to facilitate subsequent comparison and optimization. For example, the cleaning efficiency is quantified as a percentage, the material damage is quantified as an absolute value, and the energy consumption is quantified as the energy consumed per unit area.

[0035] Step 113: Initializing and generating multiple laser cleaning parameter sets according to the evaluation criteria; In this step, initialization generation refers to generating multiple laser cleaning parameter sets within a given parameter range by random or other means for subsequent simulation and optimization.

[0036] In this step, multiple laser cleaning parameter sets are generated within the initial laser parameter range according to the evaluation criteria set in step 112; the generated multiple laser cleaning parameter sets are recorded and numbered for subsequent simulation and optimization processing. For example, multiple parameter combinations are generated using a random method, or multiple points are uniformly selected in the parameter space using a grid search method.

[0037] The embodiments of the present invention can achieve the following beneficial effects through the above steps: By defining multiple laser cleaning parameter sets and setting the initial laser parameter range for each cleaning target to form a parameter combination, the laser cleaning parameters can be set systematically to ensure that the best parameter combination is found between different cleaning targets; Design detailed evaluation criteria to quantitatively evaluate the effect of each laser cleaning parameter set on the cleaning target, which is convenient for subsequent simulation and optimization processing; By initializing and generating multiple laser cleaning parameter sets, a large number of parameter combinations for testing can be quickly generated, improving the efficiency of parameter optimization and reducing the time and resources required for traditional trial and error methods; Ensure that the final selected laser cleaning parameter set achieves the best comprehensive performance in terms of improving cleaning efficiency, reducing material damage and reducing energy consumption, thereby improving the overall effect and reliability of the laser cleaning process.

[0038] In order to achieve multiple cleaning targets, it is necessary to finely control the laser cleaning parameters. Based on this, the present invention provides a specific embodiment, wherein step 102 evaluates the effect of the laser cleaning parameter set on the cleaning target through simulation and constructs an effect evaluation matrix, which specifically includes the following steps: Step 201: inputting the laser cleaning parameter set into a preset simulation model, and collecting key performance indicator data of the laser cleaning program of the preset simulation model in real time during operation, wherein the key performance indicator data includes cleaning rate, material surface quality, and energy consumption level; In this step, the preset simulation model refers to a model established using computer software to simulate the laser cleaning process, which is used to evaluate the effects of different sets of laser cleaning parameters; the key performance indicator data refers to important data collected in the simulation model that reflects the laser cleaning effect, including cleaning rate, material surface quality, and energy consumption level.

[0039] In this step, the multiple laser cleaning parameter sets generated in step 113 are input into a preset simulation model, each parameter set including specific parameter values ​​such as laser power, pulse frequency and scanning speed; the laser cleaning program is run in the simulation model to simulate the actual laser cleaning process; during the operation of the simulation model, key performance indicator data are collected in real time, and the key performance indicator data include cleaning rate, area cleaned per unit time; material surface quality, surface roughness, material removal amount, etc.; energy consumption level, energy consumed per unit area.

[0040] Step 202: quantitatively analyzing the effect of the laser cleaning parameter set on the cleaning target according to the key performance indicator data, and constructing a data matrix containing the key performance indicator data; In this step, quantitative analysis refers to mathematical processing of key performance indicator data to convert them into specific numerical values ​​for easy comparison and evaluation.

[0041] This step quantitatively analyzes the collected key performance indicator data and converts it into specific values; the key performance indicator data after quantitative analysis is organized into a data matrix, each row represents a laser cleaning parameter set, and each column represents a key performance indicator. For example, the cleaning rate is expressed in square meters per minute, the material surface quality is expressed in microns, and the energy consumption level is expressed in joules per square meter; the first row and first column of the data matrix is ​​the cleaning rate of set 1, the second row and second column is the material surface quality of set 2, and the third row and third column is the energy consumption level of set 3.

[0042] Step 203: Processing the data matrix using a statistical analysis method to obtain statistical analysis results; In this step, the data matrix refers to a data set in a two-dimensional table structure, which is used to store the key performance indicator data of each laser cleaning parameter set.

[0043] This step uses statistical tools and techniques to process the data matrix and obtain statistical analysis results. Statistical analysis can identify the differences and correlations between different parameter sets; the results of statistical analysis are recorded for subsequent evaluation and optimization. For example, the mean, variance, correlation coefficient and other statistics of each parameter set are calculated.

[0044] Step 204: constructing the effect evaluation matrix based on the statistical analysis results; In this step, the effect evaluation matrix refers to a data matrix containing the effect of each laser cleaning parameter set on the cleaning target, which is used to evaluate and select the optimal parameter set.

[0045] In this step, an effect evaluation matrix is ​​constructed based on the statistical analysis results. The effect evaluation matrix contains the effect of each laser cleaning parameter set on the cleaning target. Each row represents a laser cleaning parameter set, and each column represents the evaluation result of a cleaning target. The effect evaluation matrix is ​​used to evaluate the comprehensive performance of each laser cleaning parameter set. For example, the cleaning efficiency, material damage degree, and energy consumption level of each set are comprehensively evaluated by weighted average or other methods.

[0046] The embodiments of the present invention can achieve the following beneficial effects through the above steps: By collecting key performance indicator data in the preset simulation model in real time and conducting quantitative analysis on it, the effect of each laser cleaning parameter set can be accurately evaluated, providing a reliable basis for subsequent optimization. Constructing a data matrix containing key performance indicator data can systematically manage and display the effects of different parameter sets, facilitating subsequent statistical analysis and optimization processing; The statistical analysis method is used to process the data matrix and obtain statistical analysis results, which can scientifically identify the differences and correlations between different parameter sets and provide data support for optimization selection; Based on the statistical analysis results, an effect evaluation matrix is ​​constructed, which can comprehensively evaluate the performance of each laser cleaning parameter set and select the parameter set with the best comprehensive performance as the final optimization result.

[0047] In order to further optimize the laser cleaning parameters and achieve multiple cleaning targets, the present invention provides a specific embodiment, in which the step 103 adopts a multi-objective optimization algorithm to resolve the conflicts between the cleaning targets, adjusts the laser cleaning parameter set according to the effect evaluation matrix, and obtains the target laser cleaning parameter set, which specifically includes the following steps: Step 301: determining an objective function of multi-objective optimization, wherein the optimization objectives of the objective function include: improving cleaning efficiency, reducing material damage, and reducing energy consumption; The objective function of the multi-objective optimization is as follows: ; in, represents the objective function of multi-objective optimization; Indicates cleaning efficiency; It means reducing material damage; It means reducing energy consumption; The calculation formula of cleaning efficiency is as follows: ; in, Indicates cleaning efficiency; Indicates the area cleaned per unit time; is the maximum acceptable cleaning efficiency; Indicates the efficiency reduction coefficient due to environmental factors; Among them, the calculation formula for reducing material damage is as follows: ; in, It means reducing material damage; Indicates the amount of change in the surface quality of the material; Indicates the change in surface roughness; Indicates quality loss due to processing defects; , , is the weight of the corresponding indicator; The calculation formula for reducing energy consumption is as follows: ; in, It means reducing energy consumption; represents the total energy consumption, Indicates the laser power used; Indicates the additional energy consumption due to thermal effect, , The coefficient that represents the relationship between power and energy consumption, Indicates the maximum acceptable energy consumption; In this step, the objective function of multi-objective optimization refers to a mathematical expression used to define the multi-objective optimization problem, which contains multiple sub-objectives, each of which corresponds to an optimization objective.

[0048] The objective function defined in this step can consider multiple optimization objectives at the same time and express them in the form of vectors, making the optimization process more systematic and scientific.

[0049] Step 302: Based on the objective function of the multi-objective optimization, a multi-objective optimization algorithm is introduced to determine the performance of different laser cleaning parameter sets; For example, select the NSGA-II algorithm, input the objective function and the laser cleaning parameter set, and run the algorithm to find the non-inferior solution frontier.

[0050] Step 303: applying the multi-objective optimization algorithm to process the effect evaluation matrix, identifying a non-inferior solution frontier, where the non-inferior solution frontier is used to characterize a parameter set that does not have an inferiority between different cleaning objectives; In this step, the non-inferior solution frontier (Pareto frontier) refers to a set of solutions that are not inferior to another set of solutions in all objectives in a multi-objective optimization problem. The set of these solutions is called the non-inferior solution frontier.

[0051] This step uses a multi-objective optimization algorithm to process the effect evaluation matrix and identify a set of parameters that do not have disadvantages between different cleaning objectives, namely, the non-inferior solution frontier.

[0052] Step 304: selecting a laser cleaning parameter set with the best comprehensive performance as a target laser cleaning parameter set according to the non-inferior solution frontier; This step performs a comprehensive performance evaluation on each parameter set on the non-inferior solution frontier, and selects the laser cleaning parameter set with the best comprehensive performance as the target laser cleaning parameter set in the non-inferior solution frontier. For example, the cleaning efficiency, material damage reduction, and energy consumption reduction effects of each set are comprehensively evaluated by weighted average or other methods.

[0053] The embodiments of the present invention can achieve the following beneficial effects through the above steps: By defining the objective function of multi-objective optimization and using the multi-objective optimization algorithm, the laser cleaning parameter set can be systematically optimized to achieve multiple cleaning goals; Quantitatively evaluate the effects of different parameter sets through specific calculation formulas, provide scientific data support, and ensure the accuracy of optimization results; By identifying the frontier of non-inferior solutions and selecting the parameter set with the best comprehensive performance, the efficiency of parameter optimization is improved, and the time and resources required for traditional trial and error methods are reduced; Key cleaning objectives were achieved, ensuring the quality and efficiency of the laser cleaning process.

[0054] In the pursuit of efficient, environmentally friendly and sustainable production processes, it is crucial to determine a reasonable multi-objective optimization strategy. Based on this, the present invention provides a specific embodiment, wherein step 301 determines the objective function of multi-objective optimization, and the optimization objectives of the objective function include: improving cleaning efficiency, reducing material damage and reducing energy consumption, and specifically also includes the following steps: Step 311: defining an initial efficiency reduction coefficient; In this step, the initial efficiency reduction coefficient refers to the reduction coefficient of laser cleaning efficiency when the interaction of environmental factors and the influence of high-order terms are not considered.

[0055] This step facilitates the gradual introduction of more complex factors in subsequent steps by defining the initial efficiency drop coefficient, and can serve as an important reference in subsequent steps. By comparing the initial efficiency drop coefficient with the improved efficiency drop coefficient, the effectiveness of the newly introduced items can be evaluated.

[0056] Step 312: introducing an interaction term into the initial efficiency reduction coefficient to obtain a target efficiency reduction coefficient, wherein the interaction term includes: temperature and humidity; In this step, the interaction term refers to adding the interaction term between environmental factors to the efficiency reduction coefficient, such as the interaction between temperature and humidity.

[0057] This step introduces the interaction between temperature and humidity so that the efficiency drop coefficient can more precisely describe the impact of environmental changes on the laser cleaning process, thereby making the control more precise and avoiding deviations caused by single parameter adjustment.

[0058] Step 313: introducing a polynomial term into the target efficiency reduction coefficient to obtain the efficiency reduction coefficient; The calculation formula of the efficiency reduction coefficient is as follows: ; ; ; Wherein, A is the first influencing parameter of the efficiency reduction coefficient; B is the second influencing parameter of the efficiency reduction coefficient; Indicates the efficiency reduction coefficient caused by the environment; Indicates temperature; Indicates humidity; Indicates air pressure; Indicates wind speed; Indicates light intensity; Indicates the optimal temperature; Indicates optimal humidity; Indicates the optimal air pressure; Indicates the optimal wind speed; Indicates the optimal light intensity; represents the standard deviation of temperature, The standard deviation of humidity, The standard deviation of air pressure, The standard deviation of wind speed, Indicates the standard deviation of light intensity; is the coefficient of the interaction between temperature and humidity, is the cubic coefficient of temperature; is the cubic coefficient of temperature.

[0059] In this step, the polynomial term refers to the introduction of a high-order polynomial term into the efficiency reduction coefficient to more accurately describe the influence of environmental factors on the laser cleaning efficiency; In this step, based on the target efficiency reduction coefficient, high-order polynomial terms of the influencing parameters are introduced to more accurately describe the impact of environmental factors on laser cleaning efficiency.

[0060] More specifically, this embodiment further provides an expression for the coefficient of interaction between temperature and humidity, wherein the calculation formula for the coefficient of interaction between temperature and humidity is as follows: ; ; ; in, is the coefficient of interaction between temperature and humidity; is the basic coefficient of interaction; is the modulation coefficient of the interaction by temperature fluctuation; is the nonlinear interaction coefficient; Indicates temperature; Indicates humidity; Indicates the optimal temperature; Indicates optimal humidity; represents the standard deviation of temperature; represents the standard deviation of humidity; Indicates the range of temperature fluctuation; Indicates the fluctuation range of humidity; represents the nonlinear response time constant of temperature; represents the nonlinear response time constant of humidity; The first influencing parameter representing the coefficient of interaction between temperature and humidity; A second influencing parameter representing the coefficient of interaction between temperature and humidity; is pi; This step introduces the sine function and cosine function , to simulate the effect of temperature and humidity fluctuations on the interaction. This can capture the periodic changes in the interaction when the temperature and humidity change periodically, especially in certain temperature and humidity ranges, the interaction may be enhanced or weakened due to temperature and humidity fluctuations; introduce the hyperbolic tangent function and To simulate the nonlinear interaction between temperature and humidity when they deviate from the optimal value. The hyperbolic tangent function can better capture the nonlinear variation of temperature and humidity when they are close to the optimal value.

[0061] The embodiments of the present invention can achieve the following beneficial effects through the above steps: By introducing interaction terms and polynomial terms, the influence of environmental factors on laser cleaning efficiency can be described more accurately, achieving refined regulation. By optimizing the efficiency drop coefficient, it can ensure that the laser cleaning efficiency reaches the best under various environmental conditions, thereby improving the cleaning efficiency; Reduce material damage caused by environmental factors and improve material surface quality; Reduce unnecessary energy consumption and improve energy efficiency; By introducing interaction terms and high-order polynomial terms between environmental factors, the adaptability of the laser cleaning process to different environmental conditions is enhanced, enabling it to operate stably in various environments.

[0062] In order to ensure that the laser cleaning process can achieve the predetermined goals efficiently and show excellent comprehensive performance, it is necessary to screen and optimize the target laser cleaning parameter set. Based on this, the present invention provides a specific embodiment, in step 104, when the key cleaning goals are achieved in the target laser cleaning parameter set, the laser cleaning parameters with the best comprehensive performance are selected as the final optimization result. The key cleaning goals include: the surface cleanliness reaches the predetermined standard, the substrate is not damaged, and the cleaning efficiency reaches the expected level, which specifically includes the following steps: Step 401: setting key cleaning effect evaluation indicators in the target laser cleaning parameter set to monitor the achievement of predetermined key cleaning targets during the cleaning process, wherein the key cleaning effect evaluation indicators include surface cleanliness and residual material content; In this step, the key cleaning effect evaluation index refers to an index used to monitor the achievement of predetermined key cleaning goals during the cleaning process. In this embodiment, the key cleaning effect evaluation index includes surface cleanliness and residual material content; surface cleanliness refers to the cleanliness of the material surface after cleaning, which is usually quantitatively evaluated by detecting surface reflectivity, surface roughness or microscopic observation; residual material content refers to the quantity or mass of pollutants remaining on the surface of the material after cleaning, which can be quantitatively evaluated by chemical analysis, weight measurement and other methods.

[0063] In this step, key cleaning effect evaluation indicators are set according to actual needs, including surface cleanliness and residual material content; the key cleaning effect evaluation indicators are used to monitor the cleaning effect under each combination of laser cleaning parameters to determine whether the predetermined key cleaning goals have been achieved. For example, if the surface cleanliness reaches 95% and the residual material content is less than 0.1%, it is considered that the key cleaning goal has been achieved.

[0064] Step 402: When the key cleaning effect evaluation index caused by any combination in the target laser cleaning parameter set shows that the key cleaning target has been achieved, a predetermined comprehensive performance evaluation model is used to perform a comprehensive performance evaluation on all parameter combinations that achieve the key cleaning target to obtain a comprehensive performance evaluation result; In this step, the comprehensive performance evaluation result refers to the result output by the comprehensive performance evaluation model, which reflects the performance of different parameter combinations in terms of comprehensive performance.

[0065] In this step, when the key cleaning effect evaluation index of a certain parameter combination shows that the key cleaning target has been achieved, a predetermined comprehensive performance evaluation model is used to further evaluate these parameter combinations. The comprehensive performance evaluation model includes multiple evaluation dimensions, such as cleaning efficiency, material damage degree, and energy consumption level. According to the comprehensive performance evaluation model, a comprehensive performance evaluation is performed on all parameter combinations that have achieved the key cleaning target to obtain a comprehensive performance evaluation result. For example, a multi-criteria decision-making method, such as AHP, is used to comprehensively evaluate various performance indicators.

[0066] Step 403: Screening out a laser cleaning parameter combination with the best comprehensive performance according to the comprehensive performance evaluation result, and determining the laser cleaning parameter with the best comprehensive performance as the final optimization result; In this step, the optimal comprehensive performance refers to the parameter combination that performs best in the comprehensive performance evaluation results, that is, the parameter combination that achieves the best balance among various evaluation indicators.

[0067] In this step, the laser cleaning parameter combination with the best comprehensive performance is screened out based on the comprehensive performance evaluation results; the screened laser cleaning parameter combination with the best comprehensive performance is determined as the final optimization result and applied to the actual laser cleaning process.

[0068] The embodiments of the present invention can achieve the following beneficial effects through the above steps: By setting key cleaning effect evaluation indicators and monitoring their achievement, we can ensure that the predetermined key cleaning goals are achieved during the cleaning process; Use a comprehensive performance evaluation model to conduct a comprehensive performance evaluation of all parameter combinations that achieve key cleaning goals to ensure that the best balance is found between multiple performance indicators; Through the comprehensive performance evaluation results, the laser cleaning parameter combination with the best comprehensive performance is screened out and determined as the final optimization result, which improves the reliability and practicality of the optimization result; Ensures that while improving cleaning efficiency, material damage is reduced and energy consumption is lowered, thereby improving cleaning quality and efficiency; By optimizing laser cleaning parameters, the process's adaptability to different environmental conditions is enhanced, allowing it to operate stably in a variety of environments.

[0069] In order to accurately control the laser cleaning process and ensure that it achieves the expected effect, based on this, the present invention provides a specific embodiment, in which step 401 sets key cleaning effect evaluation indicators in the target laser cleaning parameter set to monitor the achievement of predetermined key cleaning targets during the cleaning process, and the key cleaning effect evaluation indicators include surface cleanliness and residual material content, and specifically include the following steps: Step 411: monitor the surface state during the cleaning process in real time through a sensor, and analyze the surface state using image processing technology to obtain surface cleanliness information; In this step, the image processing technology refers to processing the collected images through computer vision technology to extract useful information. In this embodiment, it is used to analyze the surface state and obtain surface cleanliness information.

[0070] For example, a laser displacement sensor is used to monitor the state of the material surface during the cleaning process in real time. The sensor is installed near the laser cleaning equipment to capture real-time images of the cleaning area. The collected images are analyzed through image processing technologies such as edge detection, feature extraction, and image segmentation to obtain image processing results. For example, the surface is divided into clean areas and contaminated areas using image segmentation technology, and then the surface roughness, glossiness and other information are obtained through feature extraction technology. Surface cleanliness information is extracted from the image processing results, including whether there is residue on the surface, the smoothness of the surface, and other information.

[0071] Step 412: using a chemical analysis instrument to detect the residual substance content in the cleaning area to obtain residual substance information; In this step, chemical analysis instruments, such as spectrometers and mass spectrometers, are used to detect the content of residual substances in the cleaning area, obtain chemical analysis results, and extract residual substance information from the chemical analysis results. For example, a spectrometer is used to detect the chemical composition and concentration of the residues on the surface of the material.

[0072] Step 413: Based on the surface cleanliness information and the residual material content information, an evaluation model is established, and the key cleaning effect evaluation index is generated by combining the surface quality and the residue distribution characteristics. The surface quality includes: surface roughness, glossiness and defects, and the residue distribution characteristics include: density, type and morphology of the residue. In this step, the evaluation model refers to a mathematical model or algorithm used to comprehensively evaluate the surface state and residual material information to generate key cleaning effect evaluation indicators; surface quality refers to the quantitative indicators of the surface state, which in this embodiment include surface roughness, glossiness and defects; residue distribution characteristics refer to the state characteristics of the residual material, which in this embodiment include the density, type and shape of the residue.

[0073] This step combines the surface cleanliness information and the residual material content information to establish an evaluation model for generating key cleaning effect evaluation indicators. The evaluation model can be a mathematical formula or algorithm, with the input being the surface cleanliness information and the residual material content information, and the output being the key cleaning effect evaluation indicators. The key cleaning effect evaluation indicators are generated through the evaluation model, including surface quality and residue distribution characteristics.

[0074] Step 414: Processing the key cleaning effect evaluation index using a preset evaluation standard to evaluate whether the key cleaning target is achieved, so as to monitor the achievement of the key cleaning target during the cleaning process. The evaluation standard needs to determine whether the surface cleanliness and the residual material content meet the key cleaning target; This step uses preset evaluation criteria to process the generated key cleaning effect evaluation indicators. The evaluation criteria need to determine whether the surface cleanliness and residual material content meet the key cleaning goals; based on the evaluation criteria, determine whether the key cleaning effect evaluation indicators have reached the predetermined key cleaning goals; by continuously monitoring the key cleaning effect evaluation indicators, understand in real time the achievement of the key cleaning goals during the cleaning process; if the evaluation results show that the key cleaning goals have not been achieved, adjust the laser cleaning parameters and re-evaluate.

[0075] The embodiments of the present invention can achieve the following beneficial effects through the above steps: Using chemical analysis instruments to detect the residual substance content in the cleaning area can accurately obtain residual substance information and ensure the accuracy of the evaluation results; Establish an evaluation model, combine surface cleanliness information and residual material content information, generate key cleaning effect evaluation indicators, and comprehensively evaluate the cleaning effect to ensure cleaning quality; Using preset evaluation criteria to process key cleaning effect evaluation indicators can objectively evaluate whether key cleaning goals have been achieved and ensure that the cleaning process meets the predetermined standards; Through real-time monitoring and precise detection, timely adjustment of laser cleaning parameters can improve cleaning efficiency and reduce unnecessary repeated cleaning.

[0076] Figure 2 A schematic diagram of a multi-objective laser cleaning parameter optimization system is provided for an embodiment of the present application. Figure 2 As shown, the system includes: A setting module 21, used to initialize and set a plurality of laser cleaning parameter sets, each set corresponding to a different cleaning target, wherein the cleaning target includes: improving cleaning efficiency, reducing material damage, and reducing energy consumption; A construction module 22 is used to evaluate the effect of the laser cleaning parameter set on the cleaning target through simulation and construct an effect evaluation matrix; An adjustment module 23, configured to use a multi-objective optimization algorithm to resolve conflicts between the cleaning objectives, and to adjust the laser cleaning parameter set according to the effect evaluation matrix to obtain a target laser cleaning parameter set; The selection module 24 is used to select the laser cleaning parameters with the best comprehensive performance as the final optimization result when the key cleaning goals are achieved in the target laser cleaning parameter set. The key cleaning goals include: the surface cleanliness reaches the predetermined standard, the substrate is not damaged, and the cleaning efficiency reaches the expected level.

[0077] Figure 2 The optimization system based on multi-objective laser cleaning parameters can be performed Figure 1 The implementation principle and technical effect of the optimization method based on multi-objective laser cleaning parameters described in the embodiment shown will not be repeated. The specific way in which each module and unit performs operations in the optimization system based on multi-objective laser cleaning parameters in the above embodiment has been described in detail in the embodiment of the method, and will not be elaborated here.

[0078] Figure 2 An optimization system based on multi-objective laser cleaning parameters of the embodiment shown can be implemented as a computing device, such as Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32; The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32 .

[0079] The processing component 32 is used to: initialize and set multiple laser cleaning parameter sets, each set corresponds to a different cleaning target, and the cleaning targets include: improving cleaning efficiency, reducing material damage and reducing energy consumption; evaluating the effects of the laser cleaning parameter set on the cleaning targets through simulation, and constructing an effect evaluation matrix; using a multi-objective optimization algorithm to resolve conflicts between the cleaning targets, adjusting the laser cleaning parameter set according to the effect evaluation matrix, and obtaining a target laser cleaning parameter set; when key cleaning targets are achieved in the target laser cleaning parameter set, selecting the laser cleaning parameters with the best comprehensive performance as the final optimization result, and the key cleaning targets include: surface cleanliness reaches a predetermined standard, substrate is not damaged, and cleaning efficiency reaches an expected level.

[0080] The processing component 32 includes one or more processors to execute computer instructions to complete all or part of the steps in the above method. Of course, the processing component can also be implemented by one or more application-specific integrated circuits (AICs), digital signal processors (DPs), digital signal processing devices (DPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to perform the above method.

[0081] The storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (RAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0082] Computing devices also include other components, such as input / output interfaces, display components, and communication components.

[0083] The input / output interface provides an interface between the processing component and the peripheral interface module, and the above-mentioned peripheral interface module can be an output device or an input device.

[0084] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0085] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0086] The embodiment of the present invention further provides a computer storage medium storing a computer program, which can achieve the above-mentioned Figure 1 The embodiment shown is an optimization method for laser cleaning parameters based on multiple objectives.

[0087] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0088] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0089] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0090] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing laser cleaning parameters based on multiple objectives, characterized in that: include: Initializing and setting a plurality of laser cleaning parameter sets, each set corresponding to a different cleaning target, wherein the cleaning target includes: improving cleaning efficiency, reducing material damage, and reducing energy consumption; Evaluate the effect of the laser cleaning parameter set on the cleaning target through simulation, and construct an effect evaluation matrix; A multi-objective optimization algorithm is used to resolve conflicts between the cleaning objectives, and the laser cleaning parameter set is adjusted according to the effect evaluation matrix to obtain a target laser cleaning parameter set; When the key cleaning goals are achieved in the target laser cleaning parameter set, the laser cleaning parameters with the best comprehensive performance are selected as the final optimization results. The key cleaning goals include: surface cleanliness reaches a predetermined standard, substrate is not damaged, and cleaning efficiency reaches an expected level.

2. The method according to claim 1, characterized in that The initialization sets a plurality of laser cleaning parameter sets, each set corresponding to a different cleaning target, wherein the cleaning targets include: improving cleaning efficiency, reducing material damage, and reducing energy consumption. Defining multiple laser cleaning parameter sets, each set targeting different cleaning objectives, wherein the cleaning objectives include improving cleaning efficiency, reducing material damage, and reducing energy consumption; Setting an initial laser parameter range for each cleaning target to form a parameter combination, wherein the parameter combination includes laser power, pulse frequency, and scanning speed; Based on the cleaning target, designing an evaluation criterion for the laser cleaning parameter set; According to the evaluation criteria, multiple laser cleaning parameter sets are initialized and generated.

3. The method according to claim 1, characterized in that The evaluation of the effect of the laser cleaning parameter set on the cleaning target by simulation and construction of the effect evaluation matrix includes: Inputting the laser cleaning parameter set into a preset simulation model, and collecting key performance indicator data of the laser cleaning program of the preset simulation model in real time during operation, wherein the key performance indicator data includes cleaning rate, material surface quality, and energy consumption level; According to the key performance indicator data, quantitatively analyze the effect of the laser cleaning parameter set on the cleaning target, and construct a data matrix containing the key performance indicator data; Processing the data matrix using a statistical analysis method to obtain statistical analysis results; Based on the statistical analysis results, the effect evaluation matrix is ​​constructed.

4. The method according to claim 1, characterized in that: The multi-objective optimization algorithm is used to resolve the conflicts between the cleaning objectives, and the laser cleaning parameter set is adjusted according to the effect evaluation matrix to obtain the target laser cleaning parameter set, which includes: Determining a multi-objective optimization objective function, wherein the optimization objectives of the objective function include: improving cleaning efficiency, reducing material damage, and reducing energy consumption; The objective function of the multi-objective optimization is as follows: ； in, represents the objective function of multi-objective optimization; Indicates cleaning efficiency; It means reducing material damage; It means reducing energy consumption; The calculation formula of cleaning efficiency is as follows: ； in, Indicates cleaning efficiency; Indicates the area cleaned per unit time; is the maximum acceptable cleaning efficiency; Indicates the efficiency reduction coefficient due to environmental factors; Among them, the calculation formula for reducing material damage is as follows: ； in, It means reducing material damage; Indicates the amount of change in the surface quality of the material; Indicates the change in surface roughness; Indicates quality loss due to processing defects; , , is the weight of the corresponding indicator; The calculation formula for reducing energy consumption is as follows: ； in, It means reducing energy consumption; represents the total energy consumption, Indicates the laser power used; Indicates the additional energy consumption due to thermal effect, , The coefficient that represents the relationship between power and energy consumption, Indicates the maximum acceptable energy consumption; Based on the objective function of the multi-objective optimization, a multi-objective optimization algorithm is introduced to determine the performance of different sets of laser cleaning parameters; Applying the multi-objective optimization algorithm to process the effect evaluation matrix, identifying a non-inferior solution frontier, wherein the non-inferior solution frontier is used to characterize a parameter set that does not have an inferiority between different cleaning objectives; According to the non-inferior solution frontier, a laser cleaning parameter set with the best comprehensive performance is selected as the target laser cleaning parameter set.

5. The method according to claim 4, characterized in that The method further comprises: Define the initial efficiency reduction factor; Introducing an interaction term into the initial efficiency reduction coefficient to obtain a target efficiency reduction coefficient, wherein the interaction term includes: temperature and humidity; Introducing a polynomial term into the target efficiency reduction coefficient to obtain the efficiency reduction coefficient; The calculation formula of the efficiency reduction coefficient is as follows: ； ； ； Wherein, A is the first influencing parameter of the efficiency reduction coefficient; B is the second influencing parameter of the efficiency reduction coefficient; Indicates the efficiency reduction coefficient caused by the environment; Indicates temperature; Indicates humidity; Indicates air pressure; Indicates wind speed; Indicates light intensity; Indicates the optimal temperature; Indicates optimal humidity; Indicates the optimal air pressure; Indicates the optimal wind speed; Indicates the optimal light intensity; represents the standard deviation of temperature, The standard deviation of humidity, The standard deviation of air pressure, The standard deviation of wind speed, Indicates the standard deviation of light intensity; is the coefficient of the interaction between temperature and humidity, is the cubic coefficient of temperature; is the cubic coefficient of temperature.

6. The method according to claim 1, characterized in that When the key cleaning target is achieved in the target laser cleaning parameter set, the laser cleaning parameter with the best comprehensive performance is selected as the final optimization result. The key cleaning targets include: surface cleanliness reaches a predetermined standard, substrate is not damaged, and cleaning efficiency reaches an expected level. Setting key cleaning effect evaluation indicators in the target laser cleaning parameter set to monitor the achievement of predetermined key cleaning targets during the cleaning process, wherein the key cleaning effect evaluation indicators include surface cleanliness and residual material content; When the key cleaning effect evaluation index caused by any combination in the target laser cleaning parameter set shows that the key cleaning target has been achieved, a predetermined comprehensive performance evaluation model is used to perform a comprehensive performance evaluation on all parameter combinations that achieve the key cleaning target to obtain a comprehensive performance evaluation result; According to the comprehensive performance evaluation result, a laser cleaning parameter combination with the best comprehensive performance is screened out, and the laser cleaning parameters with the best comprehensive performance are determined as the final optimization result.

7. The method according to claim 6, characterized in that The key cleaning effect evaluation index is set in the target laser cleaning parameter set to monitor the achievement of the predetermined key cleaning target during the cleaning process. The key cleaning effect evaluation index includes surface cleanliness and residual material content, including: The surface state during the cleaning process is monitored in real time by a sensor, and the surface state is analyzed by image processing technology to obtain surface cleanliness information; Use chemical analysis instruments to detect the residual substance content in the cleaning area to obtain residual substance information; Based on the surface cleanliness information and the residual material content information, an evaluation model is established, and the key cleaning effect evaluation index is generated by combining the surface quality and the residue distribution characteristics, where the surface quality includes: surface roughness, glossiness and defects, and the residue distribution characteristics include: density, type and morphology of the residue; The key cleaning effect evaluation index is processed using preset evaluation criteria to evaluate whether the key cleaning target is achieved, so as to monitor the achievement of the key cleaning target during the cleaning process. The evaluation criteria need to determine whether the surface cleanliness and the residual material content meet the key cleaning target.

8. An optimization system based on multi-objective laser cleaning parameters, characterized in that: include: A setting module, used to initialize and set multiple laser cleaning parameter sets, each set corresponding to a different cleaning target, wherein the cleaning targets include: improving cleaning efficiency, reducing material damage, and reducing energy consumption; A construction module is used to evaluate the effect of the laser cleaning parameter set on the cleaning target through simulation and construct an effect evaluation matrix; An adjustment module, used for adopting a multi-objective optimization algorithm to resolve conflicts between the cleaning objectives, adjusting the laser cleaning parameter set according to the effect evaluation matrix, and obtaining a target laser cleaning parameter set; A selection module is used to select the laser cleaning parameters with the best comprehensive performance as the final optimization result when the key cleaning goals are achieved in the target laser cleaning parameter set. The key cleaning goals include: the surface cleanliness reaches a predetermined standard, the substrate is not damaged, and the cleaning efficiency reaches an expected level.

9. A computing device, characterized in that It comprises a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement an optimization method based on multi-objective laser cleaning parameters as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that: A computer program is stored, and when the computer program is executed by a computer, an optimization method based on multi-objective laser cleaning parameters as described in any one of claims 1 to 7 is implemented.

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