Spraying control method and system

Abstract

The invention provides a spraying control method and system, and relates to the technical field of spraying control. The method comprises the steps that spraying process data are collected, spraying material characteristic analysis is conducted on a spraying object, and spraying material object use characteristic data are formed; obtaining target spraying object model data, and performing material analysis in combination with the spraying material object use characteristic data to form spraying material parameter data; and according to the spraying material parameter data, spraying planning control analysis is carried out in combination with the target spraying object model data, and spraying planning result data is formed. According to the method, reasonable selection of spraying parameters is realized through reasonable data analysis and processing, so that the stability and continuity of quality control of the spraying process are ensured.

Description

Technical Field

[0001] The present invention relates to the field of spraying control technology, and in particular to a spraying control method and system. Background Art

[0002] Spraying is a coating method that uses pressure or centrifugal force to disperse a uniform, fine mist of liquid onto the surface of an object using a spray gun or disc atomizer. It is a crucial production process in the manufacturing industry. With advancements in technology, spraying has become increasingly automated, significantly improving its efficiency.

[0003] However, the current control parameters for spraying, such as the number of times, pressure, paint ratio, etc., are still mainly set based on experience. This makes it impossible to ensure the continuous stability of the spraying quality, which is not conducive to the control of process quality.

[0004] Therefore, designing a spraying control method and system to achieve reasonable selection of spraying parameters through reasonable data analysis and processing to ensure the stability and continuity of spraying process quality control is an urgent problem to be solved. Summary of the Invention

[0005] The purpose of the present invention is to provide a spray control method, which establishes mapping data of the sprayed material, especially the surface material and roughness data, and the concentration, temperature and humidity parameters corresponding to different types of spray materials by collecting historical spray process data, so as to form a feature database for direct reference and selection of spray basic data. On the basis of utilizing the feature data and combining it with the actual spray object structure data, spray control parameter data for the sprayed object can be established. Since the control parameters of the spraying are closely related and there is a certain range of optional specific parameter values ​​of the control parameters, a reasonable spray benefit analysis is performed on the parameter selection of the control parameters. After all, the process ultimately needs to consider the benefit. Taking the optimal value of the benefit as the basis for determining the specific parameter value selection of the control parameter can ensure the rationality of the control parameter selection, ensure the stability of the quality of the spray process, and ensure that the cost control of the spray process is more effective, which greatly improves the cost benefit, process quality and control efficiency of the spray process control.

[0006] The present invention also aims to provide a spray control system that uses a data acquisition unit to acquire basic big data and target spray data for process control parameter selection and analysis. A feature extraction unit extracts features from the big data to establish reasonable feature correspondence data for selecting spray objects and basic material data. A material analysis unit forms a personalized parameter control relationship model for the target spray object, and a spray planning unit makes accurate and reasonable control parameter selection based on the cost-effectiveness of the process. The interconnected data between different functional units forms an organic system that achieves reasonable and accurate spray control parameter control, which is an important material basis for achieving spray process parameter control.

[0007] In a first aspect, the present invention provides a spray control method, comprising: collecting spray process data, performing spray material characteristic analysis on the spray object, and forming spray material object usage characteristic data; obtaining target spray object model data, and performing material analysis in combination with the spray material object usage characteristic data to form spray material parameter data; performing spray planning control analysis based on the spray material parameter data and in combination with the target spray object model data to form spray planning result data.

[0008] In the present invention, the method establishes mapping data on the sprayed materials, especially the surface materials and roughness data, and the corresponding selected concentrations, temperature and humidity parameters of different types of spray coatings by collecting historical spraying process data, so that a feature database for direct reference and selection of spraying basic data can be formed. On the basis of utilizing the feature data and combining it with the actual spraying object structure data, spraying control parameter data for the sprayed object can be established. Since the spraying control parameters are closely related and there is a certain range of optional specific parameter values ​​of the control parameters, a reasonable spraying benefit analysis is performed on the parameter selection of the control parameters. After all, the process ultimately needs to consider the benefit. Taking the optimal value of the benefit as the basis for determining the selection of the specific parameter value of the control parameter can ensure the rationality of the control parameter selection, ensure the stability of the quality of the spraying process, and ensure that the cost control of the spraying process is more effective, which greatly improves the cost-effectiveness, process quality and control efficiency of the spraying process control.

[0009] As a possible implementation method, spraying process data is collected, and spraying material characteristics analysis is performed on the spraying object to form spraying material object usage characteristic data, including: extracting single spraying process information that meets the spraying requirements based on the spraying process data; clustering different single spraying process information for different spraying object surface materials to form different object material single spraying process information sets; clustering different material parameters based on surface roughness for different object material single spraying process information sets to form object material roughness material selection parameter data; and gathering object material roughness material selection parameter data in different object material single spraying process information sets to form spraying material object usage characteristic data.

[0010] In the present invention, the extraction of feature data from the collected historical spraying process data is mainly to establish a corresponding relationship between the sprayed object and the spraying material selection. It is understandable that for different spraying objects, since the spraying process mainly covers the surface of the sprayed object with material, the material of the sprayed surface is an important parameter that determines the adhesion of the material. For some sprayed objects, the surface material may be inconsistent with the internal material, such as a thin aluminum coating on the surface, so the surface material is mainly used as the reference. Since the surface material has a significant impact on the spraying process, clustering the surface materials of the sprayed objects first can ensure the rationality and accuracy of the data for the subsequent object relationship establishment. After clustering the surface materials of the sprayed objects, it is necessary to consider the different types of spraying materials. It should be noted that when considering different spraying materials, even for the same surface material, the surface roughness of the material itself can cause different basic parameter selections for the same spraying material. Therefore, the extraction of the feature relationship mapping of parameter selection for the same surface material for different spraying materials also needs to take the surface material roughness as a reference. The roughness actually fully considers the original surface condition of the material, or the surface condition after surface treatment processes such as sandblasting and machining. It is an important basis for reflecting the actual smoothness of the material surface and has an important impact on the adhesion of the spray material.

[0011] As a possible implementation method, cluster analysis of different material parameters based on surface roughness is performed on different object material single spraying process information sets to form object material roughness material selection parameter data, including: clustering different single spraying process information in the object material single spraying process information set according to the type of spraying material to form different single material spraying process information sets; extracting the object surface roughness, material concentration, and stable control temperature range and stable control humidity range corresponding to the different single material spraying process information sets; merging the same object surface roughness in the single material spraying process information set in the following manner: for multiple objects with the same surface roughness, the average concentration determined according to the corresponding material concentration is used as the effective material concentration corresponding to the object surface roughness, and the intersection of the corresponding stable control temperature range is used as the object The effective stable control temperature range corresponding to the surface roughness will be used as the effective stable control humidity range corresponding to the object surface roughness according to the intersection of the corresponding stable control humidity ranges; for the unique single material spraying process information that does not have the same object surface roughness, the corresponding material concentration will be determined as the effective material concentration corresponding to the object surface roughness, the corresponding stable control temperature range will be determined as the effective stable control temperature range corresponding to the object surface roughness, and the corresponding stable control humidity range will be determined as the effective stable control humidity range corresponding to the object surface roughness; all the different object surface roughnesses and the corresponding effective material concentrations, effective stable control temperature ranges and effective stable control humidity ranges in the single material spraying process information set are collected to form the corresponding surface roughness material selection parameter data; the surface roughness material selection parameter data corresponding to different single material spraying process information sets are collected to form the object material roughness material selection parameter data.

[0012] In the present invention, when extracting mapping feature data of different spraying materials based on surface roughness for the same surface material, first clustering of spraying material selection is performed based on different roughness, and then clustering is performed for different spraying materials on the clustering results, so that the most appropriate material concentration ratio corresponding to different surface roughness when selecting different spraying materials can be determined. It should be noted that the clustering of data is performed based on the process data of each spraying as the data unit, because the process control parameters of each spraying will change due to actual conditions. Of course, there will be cases where the same control parameters are selected. It is possible that the concentration of the spraying material corresponding to the same surface roughness value of the same surface material is different. Then, multiple optional items can be provided in the form of establishing a data set, or the average value can be used as the corresponding value. It should be noted that for different spraying material concentrations, in order to ensure that the spraying process does not affect the adhesion due to concentration changes, there will be a strict range of ambient temperature and ambient humidity control that affects the concentration change. Therefore, it is necessary to also use the control range of ambient temperature and ambient humidity as the accompanying parameter data for different spraying material concentration selection in the feature data. For the case where the same surface material and the same surface roughness value correspond to different concentrations of the spray material, if you choose to establish a data set to provide multiple options, then different concentrations will need to correspond to different ambient temperature and ambient humidity control range parameters. If you choose to use the average as a reference, then the intersection of the ambient temperature range and the ambient humidity range will be used as a reference. On the other hand, for the spraying process, under a certain surface material, surface roughness, and type of spray material, the concentration of the spray material is the basis for subsequent spraying control. Therefore, it is reasonable to use it as the material parameter data corresponding to the surface material characteristics. At the same time, after the concentration of the spray material is determined, the control of the ambient temperature and ambient humidity is also determined. Correspondingly, these data can be used as the basis for setting the spraying process parameters.

[0013] As a possible implementation method, the target spray object model data is obtained, and the material analysis is performed in combination with the spray material object usage characteristic data to form spray material parameter data, including: extracting the target surface material, target surface roughness and target material of the target spray object model data; determining the target material concentration, target temperature control range and target humidity control range corresponding to the target spray object based on the target surface material, target surface roughness and target material, and in combination with the spray material object usage characteristic data; extracting the target size information of the target spray object model data, and performing spray parameter control analysis based on the target material concentration and equipment control parameter data to establish a spray parameter control model.

[0014] In the present invention, after obtaining the big data correspondence between surface material characteristics and the concentration of the spray material, as well as the corresponding temperature and humidity control ranges, these characteristic correspondence data can be used to select the basic spray material data for the actual spraying operation. First, it is necessary to obtain surface material characteristic information and spray material usage information about the target object being sprayed, namely, the surface material type and the corresponding surface roughness, as well as the type of spray material. Then, based on the determined surface material type, the corresponding surface roughness, and the type of spray material, the corresponding spray material concentration and the corresponding temperature and humidity control ranges corresponding to the data with the same surface material characteristic information and spray material type are obtained from the correspondence data obtained based on the big data. Thus, the determined spray material concentration and the corresponding temperature and humidity control ranges are used as input data for spray process control to establish control parameter relationship data that matches these input data to ensure spray adhesion stability and uniformity. Of course, the control parameter relationship data needs to be coordinated with the control parameter data of the spraying equipment. After all, different equipment will have certain deviations in the limit ranges of different control parameters and the mutual influence relationship between parameters, so it is necessary to fully consider the control parameter data of the spraying equipment.

[0015] As a possible implementation method, based on the target surface material, target surface roughness and target material, and combined with the usage characteristic data of the spraying material object, the target material concentration, target temperature control range and target humidity control range corresponding to the target spraying object are determined, including: based on the target surface material, determining the object material roughness material selection parameter data that is the same as the target surface material; based on the target material, determining the surface roughness material selection parameter data that is the same as the target material in the object material roughness material selection parameter data; based on the target surface roughness, determining the effective material concentration, effective stable control temperature range and effective stable control humidity range corresponding to the roughness that is the same as the target surface roughness in the surface roughness material selection parameter data, and calibrating them as the target material concentration, target temperature control range and target humidity control range respectively.

[0016] In the present invention, the basic data of the materials are obtained according to the corresponding characteristic data in combination with the surface material, roughness data and spray material selection of the target object to be sprayed, mainly for matching the surface material, roughness and spray material type. The matching of surface material and spray material type is unique and easy to match. For roughness, generally speaking, there are no special requirements for surface roughness. They are all selected from several main common roughness values. Range selection can also be made. For example, a given roughness range uses a certain concentration parameter of a specific material type. This makes it easier to cover the data, but it is necessary to conduct in-depth analysis based on big data or material adhesion to ensure the accuracy of the data. Most of the time, a one-to-one selection based on a determined value of roughness can basically meet the requirements of actual production.

[0017] As a possible implementation method, the target size information of the target spraying object model data is extracted, and the spraying parameter control analysis is performed according to the target material concentration and the equipment control parameter data, and a spraying parameter control model is established, including: determining the target spraying thickness range A = (a min , a max ), where a min Indicates the minimum target thickness in the target thickness range, a max Indicates the maximum target thickness in the target thickness range; set the spraying times K, according to the target thickness range A, determine the target single thickness range B = (b min , b max ), where b min Indicates the minimum single target thickness in the target single thickness range. b max Indicates the maximum single target thickness in the target single thickness range. Based on the target single thickness range B, target material concentration, target temperature control range and target humidity control range, and combined with the equipment control parameter data, the spraying control parameters and the spraying parameter control model for the target single thickness range B are determined: Where C represents the adjustment coefficient; is the jet velocity of the nozzle, and Indicates the minimum permissible jet velocity, Indicates the maximum allowable jet flow rate, is the injection pressure of the nozzle, and Indicates the minimum allowable injection pressure, Indicates the maximum allowable injection pressure, is the spraying distance of the nozzle relative to the spraying surface, and Indicates the minimum allowable spraying distance, Indicates the maximum allowable spraying distance, represents the movement speed of the nozzle, and Indicates the minimum allowed movement speed. Indicates the maximum allowed movement speed. represents the spray angle of the nozzle relative to the horizontal plane, and Indicates the minimum allowable injection angle, represents the maximum allowable spray angle, D represents the spray control thickness, and D∈B.

[0018] In the present invention, the establishment of a spraying parameter control model not only uses the determined spray material concentration, ambient temperature control range, and ambient humidity control range as control targets, but also considers two other constraints on process parameter selection. First, there are the size requirements of the sprayed object. For spraying processes, a reasonable spray thickness range is generally specified, which is both a guarantee of product quality and a requirement for process quality. Therefore, it is necessary to obtain spray thickness data for the sprayed object during the spraying process and define an accurate spray thickness range as a constraint for parameter selection and control. Second, there are the constraints between the different control parameters set in the spraying equipment for parameter selection and control, as well as the range limitations that the equipment itself can implement for a single parameter. Regarding the constraints between different control parameters, this application establishes relationships between different control parameters and spray thickness to reflect these constraints and simultaneously form relationships that influence spray thickness. It can be understood that, given the determined concentration, ambient temperature, and ambient humidity, reasonable adhesion performance can be essentially guaranteed from the raw material perspective. By utilizing the constraints between different control parameters to select control parameters, it is possible to effectively control the influence of adhesion on the spraying process. The final spray forming thickness, that is, the thickness of a single spray, is also a reflection of the material adhesion to a certain extent. For the nozzle's spraying speed and spraying pressure, the greater the speed and the greater the pressure, the more material is sprayed per unit area, so it is directly proportional to the spraying thickness. For the nozzle's moving speed, the distance relative to the spraying object, and the spraying angle, it is inversely proportional to the spraying thickness. Thus, the relationship between these control parameters is established to form a control model for the influence on the spraying thickness. In addition, for different parameters, on the one hand, they are interconnected and influential. That is, if the value of a certain control parameter is determined to ensure the target spraying thickness, then the value selection of other control parameters is limited and constrained to a smaller allowable range within the limit range that can be achieved by the relative equipment. On the other hand, different control parameters are also limited by the parameter value selection range due to the equipment situation. Based on the target spraying thickness, each control parameter forms its own allowable control range. In addition, it should be noted that the number of spraying times can be set according to actual conditions, or a permanent value can be provided for calibration. However, different numbers of spraying times will correspond to different single spraying thickness requirements, and the different adjustment coefficients in the relationship shown will of course also affect the allowable range of the parameter values ​​of the control parameters.

[0019] As a possible implementation method, spray planning control analysis is performed based on the spraying material parameter data and combined with the target spraying object model data to form spray planning result data, including: based on the spraying parameter control model, spraying effect parameter analysis based on single-factor variable control is performed to form spraying effect parameter change data; based on the spraying effect parameter change data, control planning analysis based on spraying benefits is performed to form spray planning result data.

[0020] In the present invention, after obtaining the spraying parameter control model, what needs to be considered is how to select the specific control parameter values ​​for actual spraying. The spraying parameter control model can provide different control parameter combinations for selection, and how to reasonably select requires focusing on the benefits of the spraying process. After all, the spraying process ultimately needs to be measured in combination with the market value of the product. Based on this, the parameter data corresponding to the spraying process that affects the benefits should be obtained first, and then the parameter data that affects the benefits should be planned and then the final spraying process parameter control scheme should be determined based on the parameter data that affects the benefits to ensure that the spraying process control has reasonable and optimal benefits.

[0021] As a possible implementation method, according to the spraying parameter control model, the spraying effect parameter analysis based on single factor variable control is performed to form the spraying effect parameter change data, including: for the spraying parameter control model, determining any control parameter as the control change parameter β, where β can be selected Taking the allowable variation range of any control parameter as a reference and the target single thickness range B as the target, the total spraying time T is established. all , the parameter change mapping relationship F(β~(T all , W, Q, E)).

[0022] In the present invention, for obtaining the parameter data that affects the benefits of the spraying process, the main consideration is the economic cost. This application takes into account the time cost, environmental cost, energy consumption cost and material cost. For a given control parameter value, the definite data of these benefit parameters can be obtained, so the data of these benefit parameters corresponding to the selection range allowed by the control parameter can be established, that is, the parameter change mapping relationship. Of course, since there are many types of control parameters, the range determined by any one of the control parameters basically defines all the parameter value selection combinations that can be achieved under the spraying parameter control model. Therefore, the parameter change mapping relationship - the range of any one of the control parameters can be used as a reference.

[0023] As a possible implementation method, according to the spraying effect parameter change data, a control planning analysis based on the spraying benefit is performed to form the spraying planning result data, including: according to the parameter change mapping relationship F(β~(T all , W, Q, E)), plan the spraying cost M and determine the minimum spraying benefit M0, where M=T all *[W*m w +Q*q w +E*e w ],m w represents the unit cost of VOC emissions, q w Indicates the unit cost of materials, e w Represents the unit cost of electric energy; all control parameter values ​​corresponding to the minimum spraying benefit M0 are collected to form the spraying planning result data.

[0024] In the present invention, the planning analysis using the parameter change mapping relationship is mainly to determine the combination of control parameter values ​​with the lowest cost-effectiveness. For different types of economic costs, the corresponding unit cost is measured in time. For unit cost, it can be determined based on historical big data analysis. Thus, the combination of control parameter values ​​with the lowest cost-effectiveness is selected as the specific control parameter selection scheme for the spraying process. On the one hand, the control parameters of the spraying process are selected based on the quantitative analysis of economic benefits to ensure the accuracy and rationality of the selection. On the other hand, it can also well control the cost of the spraying process and improve the production and processing efficiency of the product and even the enterprise.

[0025] In the second aspect, the present invention provides a spray control system, including: a data acquisition unit for collecting spraying process data, target spraying object model data and equipment control parameter data; a feature extraction unit for performing feature analysis on the spraying process data collected by the data acquisition unit to form spraying material object usage feature data; a material analysis unit for performing material analysis on the target spraying object model data and equipment control parameter data collected by the data acquisition unit in combination with the spraying material object usage feature data formed by the feature extraction unit to form spraying material parameter data; a spray planning unit for performing spray planning control analysis based on the target spraying object model data collected by the data acquisition unit and the spraying material parameter data formed by the material analysis unit to form spray planning result data.

[0026] In this invention, the system uses a data acquisition unit to acquire basic big data and target spray data for process control parameter selection and analysis. A feature extraction unit then extracts features from this big data to establish reasonable feature correspondences between spray targets and basic material data. The material analysis unit then forms a personalized parameter control relationship model for the target spray target. Furthermore, the spray planning unit then makes accurate and reasonable control parameter selection based on the cost-effectiveness of the process. The interconnected data between different functional units forms an organic system for achieving reasonable and accurate spray control parameters, which is an important material foundation for achieving spray process parameter control.

[0027] The beneficial effects of a spray control method and system provided by the present invention are:

[0028] The method collects historical spraying process data to establish mapping data on the sprayed materials, especially surface materials and roughness data, and the corresponding concentrations, temperature and humidity parameters of different types of spray coatings, so as to form a feature database for direct reference and selection of spraying basic data. Based on the use of feature data and the actual spraying object structure data, spraying control parameter data for the sprayed object can be established. Since the spraying control parameters are closely related and there is a certain range of optional specific parameter values ​​of the control parameters, a reasonable spraying benefit analysis is performed on the parameter selection of the control parameters. After all, the process ultimately needs to consider the benefit. Taking the optimal value of the benefit as the basis for determining the specific parameter value selection of the control parameter can ensure the rationality of the control parameter selection, ensure the stability of the quality of the spraying process, and ensure that the cost control of the spraying process is more effective, which greatly improves the cost-effectiveness, process quality and control efficiency of the spraying process control.

[0029] The system uses a data acquisition unit to acquire basic big data and target spray data for process control parameter selection and analysis. The feature extraction unit extracts features from this big data to establish reasonable feature correspondence data for selecting spray objects and basic material data. The material analysis unit then forms a personalized parameter control relationship model for the target spray object. The spray planning unit then makes accurate and reasonable control parameter selection based on the process's cost-effectiveness. The interconnected data between different functional units forms an organic system for achieving reasonable and accurate spray control parameters, which is an important material foundation for achieving spray process parameter control. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments of the present invention. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0031] Figure 1 A step diagram of a spray control method provided by an embodiment of the present invention;

[0032] Figure 2 A schematic structural diagram of a spray control system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The technical solutions in the embodiments of the present invention will be described below with reference to the accompanying drawings in the embodiments of the present invention.

[0034] Spraying is a coating method that uses pressure or centrifugal force to disperse a uniform, fine mist of liquid onto the surface of an object using a spray gun or disc atomizer. It is a crucial production process in the manufacturing industry. With advancements in technology, spraying has become increasingly automated, significantly improving its efficiency.

[0035] However, the current control parameters for spraying, such as the number of times, pressure, paint ratio, etc., are still mainly set based on experience. This makes it impossible to ensure the continuous stability of the spraying quality, which is not conducive to the control of process quality.

[0036] refer to Figure 1-Figure 2 The embodiment of the present invention provides a spray control method, which collects historical spray process data to establish mapping data on the sprayed materials, especially surface materials and roughness data, and the corresponding concentrations, temperature and humidity parameters of different types of spray materials. In this way, a feature database for direct reference and selection of spray basic data can be formed. On the basis of utilizing the feature data and combining it with the actual spray object structure data, spray control parameter data for the sprayed object can be established. Since the spray control parameters are closely related and there is a certain range of optional specific parameter values ​​of the control parameters, a reasonable spray benefit analysis is performed on the parameter selection of the control parameters. After all, the process ultimately needs to consider the benefits. Taking the optimal value of the benefits as the basis for determining the selection of the specific parameter values ​​of the control parameters can ensure the rationality of the control parameter selection, ensure the stability of the quality of the spray process, and ensure that the cost control of the spray process is more effective, which greatly improves the cost-effectiveness, process quality and control efficiency of the spray process control.

[0037] A spraying control method specifically includes the following steps:

[0038] S1: Collect spraying process data, perform spraying material feature analysis on the spraying object, and form spraying material object usage feature data.

[0039] Collect spraying process data, conduct spraying material feature analysis on the spraying object, and form spraying material object usage feature data, including: extracting single spraying process information that meets the spraying requirements based on the spraying process data; clustering different single spraying process information for different spraying object surface materials to form different object material single spraying process information sets; clustering different material parameters based on surface roughness on different object material single spraying process information sets to form object material roughness material selection parameter data; and gathering object material roughness material selection parameter data in different object material single spraying process information sets to form spraying material object usage feature data.

[0040] Extracting feature data from historical spraying process data primarily establishes a correspondence between the sprayed object and the selected spraying material. It's understandable that for different spraying objects, since the spraying process primarily involves coating the surface with material, the surface material is a key parameter determining material adhesion. For some sprayed objects, the surface material may differ from the internal material, such as for thin aluminum coatings. Therefore, the surface material is the primary factor determining adhesion. Because surface material has a significant impact on the spraying process, clustering the surface materials of the sprayed objects within the big data ensures the rationality and accuracy of the subsequent object relationship data. After clustering the surface materials of the sprayed objects, it's necessary to consider the different types of spraying materials. It's important to note that even for the same surface material, the surface roughness of the material itself can lead to differences in the basic parameter selection for the same spraying material. Therefore, extracting the feature relationship mapping between parameter selection for different spraying materials for the same surface material requires considering the surface material roughness. The roughness actually fully considers the original surface condition of the material, or the surface condition after surface treatment processes such as sandblasting and machining. It is an important basis for reflecting the actual smoothness of the material surface and has an important impact on the adhesion of the spray material.

[0041] Cluster analysis of different material parameters based on surface roughness is performed on single spraying process information sets of different object materials to form material selection parameter data of object material roughness, including: clustering different single spraying process information in the single spraying process information set of object materials according to the type of spraying materials to form different single material spraying process information sets; extracting the object surface roughness, material concentration and stable control temperature range and stable control humidity range corresponding to the different single material spraying process information sets; merging the same object surface roughness in the single material spraying process information set in the following manner: for single material spraying process information of multiple objects with the same surface roughness, the average concentration determined according to the corresponding material concentration is used as the effective material concentration corresponding to the object surface roughness, and the intersection of the corresponding stable control temperature range is used as the object surface roughness. The corresponding effective stable control temperature range will be determined as the effective stable control humidity range corresponding to the object surface roughness according to the intersection of the corresponding stable control humidity ranges; for the unique single material spraying process information that does not have the same object surface roughness, the corresponding material concentration will be determined as the effective material concentration corresponding to the object surface roughness, the corresponding stable control temperature range will be determined as the effective stable control temperature range corresponding to the object surface roughness, and the corresponding stable control humidity range will be determined as the effective stable control humidity range corresponding to the object surface roughness; all different object surface roughnesses and the corresponding effective material concentrations, effective stable control temperature ranges and effective stable control humidity ranges in the single material spraying process information set are collected to form the corresponding surface roughness material selection parameter data; the surface roughness material selection parameter data corresponding to different single material spraying process information sets are collected to form the object material roughness material selection parameter data.

[0042] When extracting mapping feature data of different spray materials based on surface roughness for the same surface material, the spray material selection is first clustered based on different roughness, and then clustered for different spray materials based on the clustering results. In this way, the most appropriate material concentration ratio corresponding to different surface roughness can be determined when selecting different spray materials. It should be noted that the data clustering is performed based on the process data of each spraying as the data unit, because the process control parameters of each spraying will change due to actual conditions. Of course, there will also be cases where the same control parameters are selected. It is possible that the same surface material and the same surface roughness value may have different spray material concentrations. In this case, multiple options can be provided in the form of a data set, or the average value can be used as the corresponding value. It should be noted that for different spray material concentrations, in order to ensure that the spraying process does not affect the adhesion due to concentration changes, there will be strict control ranges of ambient temperature and ambient humidity that affect concentration changes. Therefore, it is necessary to also include the control ranges of ambient temperature and ambient humidity as accompanying parameter data for different spray material concentration selections in the feature data. For the case where the same surface material and the same surface roughness value correspond to different concentrations of the spray material, if you choose to establish a data set to provide multiple options, then different concentrations will need to correspond to different ambient temperature and ambient humidity control range parameters. If you choose to use the average as a reference, then the intersection of the ambient temperature range and the ambient humidity range will be used as a reference. On the other hand, for the spraying process, under a certain surface material, surface roughness, and type of spray material, the concentration of the spray material is the basis for subsequent spraying control. Therefore, it is reasonable to use it as the material parameter data corresponding to the surface material characteristics. At the same time, after the concentration of the spray material is determined, the control of the ambient temperature and ambient humidity is also determined. Correspondingly, these data can be used as the basis for setting the spraying process parameters.

[0043] S2: Obtain target spraying object model data, and perform material analysis in combination with spraying material object usage feature data to form spraying material parameter data.

[0044] Obtain target spray object model data, and perform material analysis in combination with spray material object usage characteristic data to form spray material parameter data, including: extracting target surface material, target surface roughness and target material of target spray object model data; determining target material concentration, target temperature control range and target humidity control range corresponding to the target spray object based on target surface material, target surface roughness and target material, and in combination with spray material object usage characteristic data; extracting target size information of target spray object model data, and performing spray parameter control analysis based on target material concentration and equipment control parameter data to establish a spray parameter control model.

[0045] After obtaining the big data correspondence between surface material characteristics, spray material concentration, and the corresponding temperature and humidity control ranges, this characteristic correspondence data can be used to select the basic spray material data for the actual spraying operation. First, it is necessary to obtain surface material characteristic information and spray material usage information about the target object being sprayed, namely the surface material type, corresponding surface roughness, and type of spray material. Then, based on the determined surface material type, corresponding surface roughness, and type of spray material, the corresponding spray material concentration and corresponding temperature and humidity control ranges for the data with the same surface material characteristic information and spray material type are obtained from the correspondence data obtained based on the big data. Thus, the determined spray material concentration and corresponding temperature and humidity control ranges are used as input data for spray process control to establish control parameter relationship data that matches these input data to ensure spray adhesion stability and uniformity. Of course, the control parameter relationship data needs to be coordinated with the control parameter data of the spraying equipment. After all, different equipment will have certain deviations in the control parameter limit ranges and the mutual influence between parameters, so the control parameter data of the spraying equipment needs to be fully considered.

[0046] According to the target surface material, target surface roughness and target material, and in combination with the usage characteristic data of the spraying material object, the target material concentration, target temperature control range and target humidity control range corresponding to the target spraying object are determined, including: according to the target surface material, determining the object material roughness material selection parameter data that is the same as the target surface material; according to the target material, determining the surface roughness material selection parameter data that is the same as the target material in the object material roughness material selection parameter data; according to the target surface roughness, determining the effective material concentration, effective stable control temperature range and effective stable control humidity range corresponding to the roughness that is the same as the target surface roughness in the surface roughness material selection parameter data, and calibrating them as the target material concentration, target temperature control range and target humidity control range respectively.

[0047] The basic data of the materials is obtained according to the corresponding characteristic data in combination with the surface material, roughness data and spray material selection of the target object to be sprayed. The main purpose is to match the surface material, roughness and spray material type. The matching of surface material and spray material type is unique and easy to match. For roughness, generally speaking, there are no special requirements for surface roughness. The selection is based on several main common roughness values. A range can also be selected. For example, a given roughness range uses a certain concentration parameter of a specific material type. This makes it easier to cover the data, but an in-depth analysis based on big data or material adhesion is required to ensure the accuracy of the data. Most of the time, a one-to-one selection based on the determined value of roughness can basically meet the requirements of actual production.

[0048] Extract the target size information of the target spray object model data, and conduct spray parameter control analysis based on the target material concentration and equipment control parameter data to establish a spray parameter control model, including: determining the target spray thickness range A = (a min , a max ), where a min Indicates the minimum target thickness in the target thickness range, a max Indicates the maximum target thickness in the target thickness range; set the spraying times K, according to the target thickness range A, determine the target single thickness range B = (b min , b max ), where b min Indicates the minimum single target thickness in the target single thickness range. b max Indicates the maximum single target thickness in the target single thickness range. Based on the target single thickness range B, target material concentration, target temperature control range and Allowable jet flow rate, is the injection pressure of the nozzle, and Indicates the minimum allowable injection pressure, Indicates the maximum allowable injection pressure, is the spraying distance of the nozzle relative to the spraying surface, and Indicates the minimum allowable spraying distance, Indicates the maximum allowable spraying distance, represents the movement speed of the nozzle, and Indicates the minimum allowed movement speed. Indicates the maximum allowed movement speed. represents the spray angle of the nozzle relative to the horizontal plane, and Indicates the minimum allowable injection angle, represents the maximum allowable spray angle, D represents the spray control thickness, and D∈B.

[0049] In establishing a spray parameter control model, in addition to using the determined spray material concentration, ambient temperature control range, and ambient humidity control range as control targets, two other aspects of process parameter selection must be considered. First, there are the size requirements for the sprayed object. For spray processes, a reasonable spray thickness range is generally given, which is both a guarantee of product quality and a requirement for process quality. Therefore, it is necessary to obtain spray thickness data for the sprayed object during the spray process and define an accurate spray thickness range requirement as a limiting aspect of parameter selection and control. Second, there are the constraints between the different control parameters set in the spray equipment for parameter selection and control, and the range limitations that the equipment itself can implement for a single parameter. Regarding the constraints between different control parameters, this application demonstrates this constraint relationship by establishing the relationship between different control parameters and spray thickness, while also forming a relationship that influences spray thickness. It can be understood that for a given concentration, ambient temperature, and ambient humidity, reasonable adhesion performance can basically be guaranteed from the raw material perspective. By utilizing the constraints between different control parameters to select control parameters, it is possible to effectively control the influence of adhesion on the spray process. The final spray forming thickness, that is, the thickness of a single spray, is also a reflection of the material adhesion to a certain extent. For the nozzle's spraying speed and spraying pressure, the greater the speed and the greater the pressure, the more material is sprayed per unit area, so it is directly proportional to the spraying thickness. For the nozzle's moving speed, the distance relative to the spraying object, and the spraying angle, it is inversely proportional to the spraying thickness. Thus, the relationship between these control parameters is established to form a control model for the influence on the spraying thickness. In addition, for different parameters, on the one hand, they are interconnected and influential. That is, if the value of a certain control parameter is determined to ensure the target spraying thickness, then the value selection of other control parameters is limited and constrained to a smaller allowable range within the limit range that can be achieved by the relative equipment. On the other hand, different control parameters are also limited by the parameter value selection range due to the equipment situation. Based on the target spraying thickness, each control parameter forms its own allowable control range. In addition, it should be noted that the number of spraying times can be set according to actual conditions, or a permanent value can be provided for calibration. However, different numbers of spraying times will correspond to different single spraying thickness requirements, and the different adjustment coefficients in the relationship shown will of course also affect the allowable range of the parameter values ​​of the control parameters.

[0050] S3: Perform spray planning control analysis based on the spray material parameter data and in combination with the target spray object model data to form spray planning result data.

[0051] Based on the spraying material parameter data and combined with the target spraying object model data, spraying planning control analysis is performed to form spraying planning result data, including: based on the spraying parameter control model, spraying effect parameter analysis based on single factor variable control is performed to form spraying effect parameter change data; based on the spraying effect parameter change data, control planning analysis based on spraying benefits is performed to form spraying planning result data.

[0052] After obtaining the spraying parameter control model, what needs to be considered is how to select specific control parameter values ​​for actual spraying. The spraying parameter control model can provide different control parameter combinations for selection, and how to make a reasonable choice requires focusing on the benefits of the spraying process. After all, the spraying process ultimately needs to be measured in combination with the market value of the product. Based on this, the parameter data that affects the benefits of the spraying process should be obtained first, and then the parameter data that affects the benefits should be combined to plan and determine the final spraying process parameter control plan to ensure that the spraying process control has reasonable and optimal benefits.

[0053] According to the spraying parameter control model, the spraying effect parameter analysis based on single factor variable control is carried out to form the spraying effect parameter change data, including: for the spraying parameter control model, any control parameter is determined as the control change parameter β, where β can be selected Taking the allowable variation range of any control parameter as a reference and the target single thickness range B as the target, the total spraying time T is established. all , the parameter change mapping relationship F(β~(T all , W, Q, E)).

[0054] When it comes to obtaining parameter data that affect the benefits of the spraying process, the main consideration is economic cost. This application takes into account time cost, environmental cost, energy consumption cost, and material cost. For given control parameter values, the definite data of these benefit parameters can be obtained, so the data of these benefit parameters corresponding to the selection range allowed by the control parameters can be established, that is, the parameter change mapping relationship. Of course, since there are many types of control parameters, the range determined by any one of the control parameters basically defines all the parameter value selection combinations that can be achieved under the spraying parameter control model. Therefore, the parameter change mapping relationship can be referred to by the range of any one of the control parameters.

[0055] According to the spraying effect parameter change data, the control planning analysis based on the spraying benefit is carried out to form the spraying planning result data, including: according to the parameter change mapping relationship F(β~(T all, W, Q, E)), plan the spraying cost M and determine the minimum spraying benefit M0, where M=T all *[W*m w +Q*q w +E*e w ],m w represents the unit cost of VOC emissions, q w Indicates the unit cost of materials, e w Represents the unit cost of electric energy; all control parameter values ​​corresponding to the minimum spraying benefit M0 are collected to form the spraying planning result data.

[0056] The purpose of planning and analysis using parameter change mapping relationships is to determine the combination of control parameter values ​​with the lowest cost-effectiveness. For different types of economic costs, the corresponding unit cost is measured in time. For unit cost, it can be determined based on historical big data analysis. In this way, the combination of control parameter values ​​with the lowest cost-effectiveness is selected as the specific control parameter selection scheme for the spraying process. On the one hand, selecting the control parameters of the spraying process based on a quantitative analysis of economic benefits can ensure the accuracy and rationality of the selection. On the other hand, it can also effectively control the cost of the spraying process and improve the production and processing efficiency of the product and even the enterprise.

[0057] The present invention also provides a spraying control system, which includes: a data acquisition unit for collecting spraying process data, target spraying object model data and equipment control parameter data; a feature extraction unit for performing feature analysis on the spraying process data collected by the data acquisition unit to form spraying material object usage feature data; a material analysis unit for performing material analysis on the target spraying object model data and equipment control parameter data collected by the data acquisition unit in combination with the spraying material object usage feature data formed by the feature extraction unit to form spraying material parameter data; a spray planning unit for performing spraying planning control analysis based on the target spraying object model data collected by the data acquisition unit and the spraying material parameter data formed by the material analysis unit to form spraying planning result data.

[0058] The system uses a data acquisition unit to acquire basic big data and target spray data for process control parameter selection and analysis. The feature extraction unit extracts features from this big data to establish reasonable feature correspondence data for selecting spray objects and basic material data. The material analysis unit then forms a personalized parameter control relationship model for the target spray object. The spray planning unit then makes accurate and reasonable control parameter selection based on the process's cost-effectiveness. The interconnected data between different functional units forms an organic system for achieving reasonable and accurate spray control parameters, which is an important material foundation for achieving spray process parameter control.

[0059] In summary, the spraying control method and system provided by the embodiments of the present invention have the following beneficial effects:

[0060] The method collects historical spraying process data to establish mapping data on the sprayed materials, especially surface materials and roughness data, and the corresponding concentrations, temperature and humidity parameters of different types of spray coatings, so as to form a feature database for direct reference and selection of spraying basic data. Based on the use of feature data and the actual spraying object structure data, spraying control parameter data for the sprayed object can be established. Since the spraying control parameters are closely related and there is a certain range of optional specific parameter values ​​of the control parameters, a reasonable spraying benefit analysis is performed on the parameter selection of the control parameters. After all, the process ultimately needs to consider the benefit. Taking the optimal value of the benefit as the basis for determining the specific parameter value selection of the control parameter can ensure the rationality of the control parameter selection, ensure the stability of the quality of the spraying process, and ensure that the cost control of the spraying process is more effective, which greatly improves the cost-effectiveness, process quality and control efficiency of the spraying process control.

[0061] The system uses a data acquisition unit to acquire basic big data and target spray data for process control parameter selection and analysis. The feature extraction unit extracts features from this big data to establish reasonable feature correspondence data for selecting spray objects and basic material data. The material analysis unit then forms a personalized parameter control relationship model for the target spray object. The spray planning unit then makes accurate and reasonable control parameter selection based on the process's cost-effectiveness. The interconnected data between different functional units forms an organic system for achieving reasonable and accurate spray control parameters, which is an important material foundation for achieving spray process parameter control.

[0062] In the embodiment of the present application, "indication" may include direct indication and indirect indication, and may also include explicit indication and implicit indication. The information indicated by a certain information is called information to be indicated. In the specific implementation process, there are many ways to indicate the information to be indicated, such as but not limited to, the information to be indicated can be directly indicated, such as the information to be indicated itself or the index of the information to be indicated. The information to be indicated can also be indirectly indicated by indicating other information, wherein there is an association relationship between the other information and the information to be indicated. It is also possible to indicate only a part of the information to be indicated, while the other parts of the information to be indicated are known or agreed in advance. For example, the indication of specific information can also be achieved by means of the arrangement order of each piece of information agreed in advance (such as specified in the protocol), thereby reducing the indication overhead to a certain extent. At the same time, the common parts of each piece of information can also be identified and indicated uniformly to reduce the indication overhead caused by indicating the same information separately.

[0063] In addition, the specific indication method can also be various existing indication methods, such as but not limited to the above-mentioned indication methods and various combinations thereof. The specific details of the various indication methods can be referred to the prior art and will not be repeated herein. As can be seen from the above, for example, when it is necessary to indicate multiple information of the same type, there may be a situation where the indication methods for different information are different. In the specific implementation process, the required indication method can be selected according to specific needs. The embodiment of the present application does not limit the selected indication method. In this way, the indication method involved in the embodiment of the present application should be understood to cover various methods that can enable the party to be indicated to obtain the information to be indicated.

[0064] It should be understood that the information to be indicated can be sent as a whole or divided into multiple sub-information and sent separately, and the sending period and / or sending time of these sub-information can be the same or different. The specific sending method is not limited in the embodiments of this application. The sending period and / or sending time of these sub-information can be predefined, for example, predefined according to a protocol, or can be configured by the transmitting device by sending configuration information to the receiving device.

[0065] "Pre-definition" or "pre-configuration" can be implemented by pre-saving corresponding codes, tables or other methods that can be used to indicate relevant information in the device, and the embodiments of the present application do not limit the specific implementation method. Among them, "saving" can mean saving in one or more memories. The one or more memories can be set separately or integrated in an encoder or decoder, a processor, or a communication device. The one or more memories can also be partially set separately and partially integrated in a decoder, a processor, or a communication device. The type of memory can be any form of storage medium, and the embodiments of the present application do not limit this.

[0066] The "protocol" involved in the embodiments of the present application may refer to a protocol family in the communication field, a standard protocol with a similar protocol family frame structure, or a related protocol used in future communication systems. The embodiments of the present application do not make specific limitations on this.

[0067] In the embodiments of the present application, descriptions such as "when...", "in the case of...", "if" and "if" all mean that the device will perform corresponding processing under certain objective circumstances. It does not limit the time, nor does it require the device to perform judgment actions when implemented, nor does it mean that there are other limitations.

[0068] In the description of the embodiments of the present application, unless otherwise specified, " / " indicates that the objects associated with each other are in an "or" relationship. For example, A / B can represent A or B. "And / or" in the embodiments of the present application is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, in the description of the embodiments of the present application, unless otherwise specified, "multiple" refers to two or more than two. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple. In addition, in order to facilitate the clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, words such as "first" and "second" are used to distinguish between identical or similar items with basically the same functions and effects. Those skilled in the art will understand that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit differences. At the same time, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or design. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way for easy understanding.

[0069] It should be understood that the processor in the embodiments of the present application may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0070] It should also be understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DRRAM).

[0071] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired (such as infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0072] It should be understood that the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, the character " / " as used herein generally indicates an "or" relationship between the associated objects, but it may also indicate an "and / or" relationship. For specific understanding, please refer to the context.

[0073] In this application, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or plural.

[0074] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0075] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0076] Those skilled in the art will 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.

[0077] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0078] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0079] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0080] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0081] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A spraying control method, characterized in that: include: Collect spraying process data, analyze the characteristics of spraying materials for the spraying objects, and form the usage characteristic data of spraying materials objects; Acquire target spraying object model data, and perform material analysis in combination with the spraying material object usage characteristic data to form spraying material parameter data; According to the spraying material parameter data, spraying planning control analysis is performed in combination with the target spraying object model data to form spraying planning result data.

2. The spraying control method according to claim 1, characterized in that: The collection of spraying process data, analysis of spraying material characteristics for the spraying object, and formation of spraying material object usage characteristic data include: Extracting single spraying process information that meets spraying requirements based on the spraying process data; Clustering the different single spraying process information according to different surface materials of the spraying objects to form single spraying process information sets for different object materials; Performing cluster analysis of different material parameters based on surface roughness on different single-time spraying process information sets of the target materials to form target material roughness material selection parameter data; The roughness material selection parameter data of the target material in the single spraying process information set of different target materials are collected to form the spraying material object usage feature data.

3. The spraying control method according to claim 2, characterized in that: The cluster analysis of different material parameters based on surface roughness is performed on the single spraying process information sets of different target materials to form the target material roughness material selection parameter data, including: Clustering different single spraying process information in the single spraying process information set of the object material according to the type of spraying materials to form different single material spraying process information sets; For different sets of single material spraying process information, extracting the object surface roughness, material concentration, and the stable control temperature range and stable control humidity range corresponding to the different single material spraying process information; The same surface roughness of the objects in the single material spraying process information set is merged in the following manner: For the single material spraying process information of multiple objects with the same surface roughness, the average concentration determined according to the corresponding material concentrations is used as the effective material concentration corresponding to the surface roughness of the object, the intersection of the corresponding stable control temperature ranges is used as the effective stable control temperature range corresponding to the surface roughness of the object, and the intersection of the corresponding stable control humidity ranges is used as the effective stable control humidity range corresponding to the surface roughness of the object; For the single material spraying process information that does not have the same surface roughness of the object, the corresponding material concentration is determined as the effective material concentration corresponding to the surface roughness of the object, the corresponding stable control temperature range is determined as the effective stable control temperature range corresponding to the surface roughness of the object, and the corresponding stable control humidity range is determined as the effective stable control humidity range corresponding to the surface roughness of the object; Gathering all the different surface roughnesses of the objects and the corresponding effective material concentrations, the effective stable control temperature ranges, and the effective stable control humidity ranges in the single material spraying process information set to form corresponding surface roughness material selection parameter data; The surface roughness material selection parameter data corresponding to different single material spraying process information sets are collected to form the object material roughness material selection parameter data.

4. The spraying control method according to claim 3, characterized in that: The acquisition of target spraying object model data and the combination of the spraying material object usage characteristic data to perform material analysis to form spraying material parameter data include: Extracting target surface material, target surface roughness and target material of the target spraying object model data; Determining a target material concentration, a target temperature control range, and a target humidity control range corresponding to a target spraying object based on the target surface material, the target surface roughness, and the target material, and in combination with the spraying material object usage characteristic data; The target size information of the target spray object model data is extracted, and spray parameter control analysis is performed according to the target material concentration and equipment control parameter data to establish a spray parameter control model.

5. The spraying control method according to claim 4, characterized in that: The target material concentration, target temperature control range, and target humidity control range corresponding to the target spraying object are determined based on the target surface material, the target surface roughness, and the target material, in combination with the spraying material object usage characteristic data, including: Determining, based on the target surface material, material selection parameter data for the roughness of the object material that is the same as the target surface material; According to the target material, determining the surface roughness material selection parameter data that is the same as the target material in the object material roughness material selection parameter data; According to the target surface roughness, the effective material concentration, the effective stable control temperature range and the effective stable control humidity range corresponding to the roughness same as the target surface roughness in the surface roughness material selection parameter data are determined, and are calibrated as the target material concentration, the target temperature control range and the target humidity control range respectively.

6. The spraying control method according to claim 5, characterized in that: The method of extracting target size information of the target spray object model data, performing spray parameter control analysis based on the target material concentration and equipment control parameter data, and establishing a spray parameter control model includes: According to the target size information, the target thickness range of spraying is determined as A=(a min , a max ), where a min represents the minimum target thickness in the target thickness range, a max represents the maximum target thickness in the target thickness range; Set the spraying times K, and determine the target single thickness range B according to the target thickness range A = (b min , b max ), where b min Indicates the minimum single target thickness in the target single thickness range, b max Indicates the maximum single target thickness in the target single thickness range, Based on the target single thickness range B, the target material concentration, the target temperature control range, and the target humidity control range, and in combination with the equipment control parameter data, the spraying control parameters and the spraying parameter control model for the target single thickness range B are determined: Where C represents the adjustment coefficient; is the jet velocity of the nozzle, and Indicates the minimum permissible jet velocity, Indicates the maximum allowable jet flow rate, is the injection pressure of the nozzle, and Indicates the minimum allowable injection pressure, Indicates the maximum allowable injection pressure, is the spraying distance of the nozzle relative to the spraying surface, and Indicates the minimum allowable spraying distance, Indicates the maximum allowable spraying distance, represents the movement speed of the nozzle, and Indicates the minimum allowed movement speed. Indicates the maximum allowed movement speed. represents the spray angle of the nozzle relative to the horizontal plane, and Indicates the minimum allowable injection angle, represents the maximum allowable spray angle, D represents the spray control thickness, and D∈B.

7. The spraying control method according to claim 6, characterized in that: The spraying planning control analysis is performed based on the spraying material parameter data and in combination with the target spraying object model data to form spraying planning result data, including: According to the spraying parameter control model, spraying effect parameter analysis based on single factor variable control is performed to form spraying effect parameter change data; According to the spraying effect parameter change data, a control planning analysis based on spraying benefits is performed to form the spraying planning result data.

8. The spraying control method according to claim 7, characterized in that: The spraying effect parameter analysis based on single factor variable control is performed according to the spraying parameter control model to form spraying effect parameter change data, including: For the spraying parameter control model, any control parameter is determined as the control variation parameter β, where β can be selected Taking the allowable variation range of any control parameter as a reference and the target single thickness range B as the target, the total spraying time T is established. all , the parameter change mapping relationship F(β~(T all , W, Q, E)).

9. The spraying control method according to claim 8, characterized in that: The control planning analysis based on the spraying benefit is performed according to the spraying effect parameter change data to form the spraying planning result data, including: According to the parameter change mapping relationship F(β~(T all , W, Q, E)), plan the spraying cost M and determine the minimum spraying benefit M0, where M=T all *[W*m w +Q*q w +E*e w ],m w represents the unit cost of VOC emissions, q w Indicates the unit cost of materials, e w represents the unit cost of electric energy; All control parameter values ​​corresponding to the minimum spraying benefit M0 are collected to form the spraying planning result data.

10. A spray control system, adopting the spray control method according to any one of claims 1 to 9, characterized in that: include: A data acquisition unit is used to collect spraying process data, target spraying object model data and equipment control parameter data; A feature extraction unit is used to perform feature analysis on the spraying process data collected by the data collection unit to form usage feature data of the spraying material object; A material analysis unit is used to combine the target spraying object model data and the equipment control parameter data collected by the data acquisition unit with the spraying material object usage feature data formed by the feature extraction unit to perform material analysis to form spraying material parameter data; The spray planning unit is used to perform spray planning control analysis based on the target spray object model data collected by the data collection unit and the spray material parameter data formed by the material analysis unit to form spray planning result data.

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