Electric arc additive process optimization method and system based on deposition rate

Abstract

The invention relates to the technical field of welding parameter control, in particular to an electric arc additive process optimization method and system based on the deposition rate, and the method comprises the steps that melting deposition is conducted according to an original welding parameter set to obtain an intermediate metal component, welding influence factor evaluation is conducted on the melting deposition step to obtain a welding correction coefficient, and the original deposition rate is calculated; a shooting unit is used for shooting the surface of the middle metal component, a component surface image is obtained, a component defect score is obtained based on the component surface image, an adjusting deposition rate is obtained based on the component defect score and a standard defect score, and an adjusting welding parameter set is obtained according to the adjusting deposition rate; and the adjusted welding parameter set serves as an original welding parameter set, and melting deposition is repeatedly conducted till the middle metal component is constructed. According to the method, the component quality and the component production efficiency in the electric arc additive manufacturing process can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of welding parameter control, and in particular to an arc additive process optimization method and system based on deposition rate. Background Art

[0002] Arc additive manufacturing is an advanced manufacturing technology that uses arc to melt metal wire to build components layer by layer. It has the advantages of high material utilization, fast prototype manufacturing, and high production efficiency. Therefore, it is widely used in various fields, especially in high value-added fields such as aerospace, automobiles, and medical treatment. It is an important development direction of the future manufacturing industry and is of great significance to promoting industrial upgrading and sustainable development.

[0003] At present, arc additive manufacturing mainly relies on manual experience for parameter setting. However, the parameters formulated based on experience often lead to uncontrolled welding process, thus reducing the quality of components. In addition, this method relies more on post-testing for quality control and lacks real-time feedback and optimization mechanism, which makes it difficult to detect and correct component defects in time, thus affecting the forming quality of components and reducing production efficiency. Summary of the invention

[0004] The present invention provides an arc additive process optimization method and system based on deposition rate, the main purpose of which is to improve component quality and component production efficiency in the arc additive process.

[0005] To achieve the above object, the present invention provides an arc additive process optimization method based on deposition rate, comprising: Receiving an arc additive instruction, and determining an original welding parameter group based on the arc additive instruction, wherein the original welding parameter group includes: an original voltage, an original current, and an original wire feeding speed; Under the control of the original welding parameter group, a pre-constructed arc additive device is used to melt and deposit the pre-acquired metal welding wire to obtain an intermediate metal component, wherein the duration of the melting and deposition is a preset welding cycle, and the arc additive device includes: a sensor monitoring unit and a shooting unit; The welding influencing factors of the melting deposition step are evaluated to obtain a welding correction coefficient, and an original deposition rate is calculated according to the welding correction coefficient and an original welding parameter group; Using a photographing unit to photograph the surface of the intermediate metal component to obtain a component surface image, and based on the component surface image, performing a component surface quality analysis on the intermediate metal component to obtain a component defect score; Based on the component defect score and the preset standard defect score, the original deposition rate is adjusted to obtain an adjusted deposition rate; According to the adjusted deposition rate, the original welding parameter group is adjusted to obtain an adjusted welding parameter group; The adjusted welding parameter group is used as the original welding parameter group, and the step of melting and depositing the pre-acquired metal welding wire using the pre-built arc additive equipment under the control of the original welding parameter group is returned until the intermediate metal component is completed.

[0006] Optionally, the evaluating welding influencing factors of the melting deposition step to obtain a welding correction coefficient includes: Obtaining a welding influencing factor group, wherein the welding influencing factor group includes: welding wire diameter, welding wire extension length, welding angle and shielding gas flow rate; The sensor monitoring unit is used to detect the environmental influencing factor group, wherein the sensor monitoring unit includes: a temperature sensor, a humidity sensor and a wind speed sensor, and the environmental influencing factor group includes: ambient temperature, ambient humidity and ambient wind speed; According to the welding influencing factor group and the environmental influencing factor group, the welding correction coefficient is calculated, wherein the welding correction coefficient is expressed as: , in, Indicates the welding correction factor, represents the preset empirical fitting coefficient, Indicates the ambient temperature, Indicates the wire diameter, Indicates the protective gas flow rate, Indicates the wire extension length. Indicates the ambient humidity. Indicates the ambient wind speed, represents the sine function, Indicates the welding angle.

[0007] Optionally, calculating the original deposition rate according to the welding correction coefficient and the original welding parameter group includes: The original deposition rate is calculated using a preset deposition rate calculation formula, wherein the deposition rate calculation formula is expressed as: , in, represents the original deposition rate, represents the original voltage, represents the original current, Indicates the preset arc efficiency, Indicates the preset metal wire density, Indicates the original wire feed speed.

[0008] Optionally, the component surface quality analysis of the intermediate metal component based on the component surface image to obtain the component defect score includes: Performing image detection on the component surface image to obtain a quality assessment parameter group, wherein the quality assessment parameter group includes: crack growth rate and surface roughness; Based on the quality assessment parameter group, the component defect score is calculated using the following formula: , in, represents the component defect score, Indicates the surface roughness, Indicates the preset standard roughness, represents the crack growth rate.

[0009] Optionally, the performing image detection on the component surface image to obtain the quality assessment parameter group includes: Graying the surface image of the component to obtain a gray surface image, and performing roughness detection on the gray surface image to obtain surface roughness; Using a preset edge detection algorithm to perform crack contour detection on the grayscale surface image to obtain a crack surface image, and determining whether the crack surface image contains a crack; If the crack surface image does not contain cracks, the crack growth rate is recorded as 0; If the crack surface image includes cracks, a surface crack group in the crack surface image is identified, wherein the surface crack group includes one or more surface cracks; Identifying a surface crack length group of the surface crack group, wherein the surface crack lengths in the surface crack length group correspond one-to-one to the surface cracks in the surface crack group, and the surface crack lengths are the lengths of the corresponding surface cracks; The crack growth rate is calculated according to the surface crack length group, and the crack growth rate and surface roughness are confirmed as a quality evaluation parameter group.

[0010] Optionally, calculating the crack growth rate according to the surface crack length group includes: constructing a surface crack vector based on the surface crack length group, wherein the dimension of the surface crack vector is the same as the number of surface crack lengths in the surface crack length group; Constructing a historical crack vector according to the surface crack group, wherein the dimension of the historical crack vector is the same as the dimension of the surface crack vector; The crack growth rate is calculated based on the surface crack vector and the historical crack vector, where the crack growth rate is expressed as: , in, represents the dimension of the surface crack vector or the dimension of the historical crack vector, represents the surface crack vector, represents the historical crack vector, Indicates the modulus length.

[0011] Optionally, constructing a historical crack vector according to the surface crack group includes: Determining the start time of the melt deposition step, and querying the previous cycle crack group based on the start time; Respectively obtain the number of previous cycle cracks of the previous cycle crack group and the number of surface cracks of the surface crack group, and determine whether the number of previous cycle cracks is equal to the number of surface cracks; If the number of previous cycle cracks is equal to the number of surface cracks, a previous cycle crack length group of the previous cycle crack group is obtained, and a historical crack vector is constructed according to the previous cycle crack length group, wherein the dimension of the historical crack vector is the same as the number of previous cycle crack lengths in the previous cycle crack length group; If the number of cracks in the previous cycle is not equal to the number of surface cracks, then the newly added crack group and the homologous crack group are identified in the surface crack group; Respectively obtain the newly added sequence number group and the homologous sequence number group of the newly added crack group and the homologous crack group in the surface crack group, wherein the newly added crack group corresponds to the newly added sequence number group one by one, and the homologous crack group corresponds to the homologous sequence number group one by one; Based on the newly added crack group and the newly added sequence number group, the previous cycle crack group is expanded to obtain a historical crack group, wherein the historical crack group includes all previous cycle cracks and multiple empty cracks in the previous cycle crack group, and the arrangement sequence number of the previous cycle crack in the historical crack group is the same as the homologous sequence number of the corresponding homologous crack, the empty crack refers to a crack with a length of 0, and the arrangement sequence number of the empty crack in the historical crack group is the same as the newly added sequence number of the corresponding newly added crack; A historical crack length group of the historical crack group is obtained, and a historical crack vector is constructed based on the historical crack length group.

[0012] Optionally, performing roughness detection on the grayscale surface image to obtain the surface roughness includes: Extracting grayscale directions in a preset grayscale direction group in sequence, and calculating a grayscale co-occurrence matrix of the grayscale surface image in the grayscale direction; Calculating the contrast of the gray level co-occurrence matrix; The contrasts are summarized to obtain a contrast group, and the average contrast of the contrast group is calculated, and the average contrast is recorded as the roughness.

[0013] Optionally, adjusting the original deposition rate based on the component defect score and the preset standard defect score to obtain the adjusted deposition rate includes: Calculate the score data difference between the component defect score and the standard defect score, and determine whether the score data difference is greater than a preset controllable data difference; If the score data difference is not greater than the controllable data difference, the original deposition rate is recorded as the adjusted deposition rate; If the scoring data difference is greater than the controllable data difference, the adjusted deposition rate is calculated using the following formula: , in, represents the adjustment of the deposition rate, Indicates the standard defect score.

[0014] To achieve the above object, the present invention further provides an arc additive process optimization system based on deposition rate, comprising: A metal component deposition module, used to receive an arc additive instruction, determine an original welding parameter group based on the arc additive instruction, wherein the original welding parameter group includes: an original voltage, an original current and an original wire feeding speed, and under the control of the original welding parameter group, use a pre-built arc additive device to melt and deposit the pre-acquired metal welding wire to obtain an intermediate metal component, wherein the duration of the melting and deposition is a preset welding cycle, and the arc additive device includes: a sensor monitoring unit and a shooting unit; a component defect assessment module, for assessing welding influencing factors of the melting deposition step, obtaining a welding correction coefficient, and calculating an original deposition rate according to the welding correction coefficient and an original welding parameter group, photographing the surface of the intermediate metal component by using a photographing unit to obtain a component surface image, and performing a component surface quality analysis on the intermediate metal component based on the component surface image to obtain a component defect score; A welding parameter adjustment module, used to adjust the original deposition rate based on the component defect score and the preset standard defect score to obtain an adjusted deposition rate, and to adjust the original welding parameter group according to the adjusted deposition rate to obtain an adjusted welding parameter group; The melting deposition cycle module is used to use the adjusted welding parameter group as the original welding parameter group and return to the step of melting and depositing the pre-acquired metal welding wire using the pre-built arc additive equipment under the control of the original welding parameter group until the intermediate metal component is completed.

[0015] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising: A memory storing at least one instruction; A processor executes the instructions stored in the memory to implement the above-mentioned arc additive process optimization method based on deposition rate.

[0016] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one instruction is stored. The at least one instruction is executed by a processor in an electronic device to implement the above-mentioned arc additive process optimization method based on deposition rate.

[0017] In order to solve the problem described in the background technology, the present invention first determines the original welding parameter group based on the arc additive instruction, which provides initial conditions for the subsequent additive manufacturing process, and then performs melting deposition under the control of the original welding parameter group to obtain an intermediate metal component, and then evaluates the welding influencing factors of the melting deposition step to obtain a welding correction coefficient. The welding correction coefficient combines the factors that may affect the deposition rate in the welding process, so that the original deposition rate calculated subsequently is more accurate. Furthermore, the component surface image is obtained by a shooting unit, and the component defect score displayed by the component surface image is calculated. The component defect score can intuitively reflect the defect conditions on the component surface, such as cracks, pores, roughness, etc. Therefore, surface defects can be discovered in time through the component defect score to avoid further expansion of defects in the subsequent manufacturing process, thereby improving the overall quality of the component. According to the defect score, the original deposition rate is adjusted to obtain the adjusted deposition rate. In this step, the deposition rate can be dynamically adjusted by comparing the component defect score with the standard defect score, thereby realizing real-time optimization of the additive manufacturing process. Moreover, by adjusting the deposition rate, the production efficiency can be improved under the premise of ensuring the quality of the component. In addition, the present invention also adjusts the original welding parameter group according to the adjusted deposition rate to obtain the adjusted welding parameter group. This step shows the process of accurately controlling the melt deposition, further improving the quality of the component, and according to different manufacturing stages and component states, the welding parameters can be dynamically adjusted, so that the present invention can adapt to complex manufacturing environments and requirements. Finally, the melt deposition process is cyclically executed by using the adjusted welding parameter group as the new original welding parameter group. This step reduces the influence of random factors on the manufacturing process through multiple cycle optimization and improves the stability of component manufacturing. Therefore, the present invention can improve the component quality and component production efficiency in the arc additive process. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A schematic flow chart of a method for optimizing an arc additive process based on deposition rate provided in one embodiment of the present invention; Figure 2 A functional module diagram of an arc additive process optimization system based on deposition rate provided by an embodiment of the present invention; Figure 3 A schematic diagram of the structure of an electronic device for implementing the arc additive process optimization method based on deposition rate provided in one embodiment of the present invention.

[0019] Description of reference numerals: 1. Electronic device; 10. Processor; 11. Memory; 12. Bus.

[0020] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0021] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0022] The embodiment of the present application provides an arc additive process optimization method based on deposition rate. The execution subject of the arc additive process optimization method based on deposition rate includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided in the embodiment of the present application. In other words, the arc additive process optimization method based on deposition rate can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0023] Reference Figure 1 FIG. 1 is a flow chart of an arc additive process optimization method based on deposition rate provided by an embodiment of the present invention. In this embodiment, the arc additive process optimization method based on deposition rate includes: S1. Receive an arc additive instruction, and determine an original welding parameter group based on the arc additive instruction, wherein the original welding parameter group includes: an original voltage, an original current, and an original wire feeding speed.

[0024] It can be understood that the arc additive instruction refers to a signal instruction initiated manually for arc additive, which includes parameters that need to be set during the arc additive process, namely, the original welding parameter group. The original welding parameter group includes: original voltage, original current and original wire feeding speed, wherein the original voltage refers to the welding power supply output voltage preset in the arc additive process, the original current refers to the welding power supply output current preset in the arc additive process, and the original wire feeding speed refers to the welding wire feeding speed preset in the arc additive process.

[0025] S2. Under the control of the original welding parameter group, the pre-constructed arc additive equipment is used to melt and deposit the pre-acquired metal welding wire to obtain an intermediate metal component, wherein the duration of the melting and deposition is a preset welding cycle, and the arc additive equipment includes: a sensor monitoring unit and a shooting unit.

[0026] It should be explained that the arc additive equipment refers to equipment for melting and depositing metal welding wire, wherein the sensor monitoring unit refers to a collection of temperature sensors, wind speed sensors and humidity sensors, which are respectively used to detect the temperature, wind speed and humidity during the melting and deposition process. The shooting unit refers to a high-definition camera used to shoot the components after melting and deposition. In addition to the above-mentioned sensor monitoring unit and shooting unit, the arc additive equipment also includes: a power supply, a wire feeding system, a welding robot, a welding gun, a shielding gas system, a cooling system and a fixture workbench, wherein the power supply is used to provide stable arc energy and to control the current and voltage during the welding process. The wire feeding system refers to a conveying device that transports the metal welding wire from the wire outlet to the arc molten pool, and the speed at which the wire feeding system runs the metal welding wire is the subsequent original wire feeding speed. The welding robot is used to control the movement trajectory of the welding gun during the arc welding process, so that the welding process can be carried out according to a pre-set path. The shielding gas system refers to a device that provides inert gas, which is used to protect the arc molten pool from oxidation contamination. The cooling system refers to the equipment used to cool the welding gun. By cooling the welding gun, the problem of overheating of the welding gun can be avoided. The fixture workbench refers to the flat table used to fix the workpiece to be processed to ensure stability during the processing.

[0027] It is understandable that the welding cycle refers to the duration of melting deposition between every two adjustments to the original parameter group. It should be noted that the welding cycle here does not refer to the duration to complete the entire melting deposition, but rather that the original parameter group in the current melting deposition process is adjusted every other welding cycle.

[0028] S3. Evaluate the welding influencing factors of the melting deposition step to obtain the welding correction coefficient, and calculate the original deposition rate according to the welding correction coefficient and the original welding parameter group.

[0029] It can be understood that the welding influencing factor assessment refers to the process of comprehensively analyzing the influence of various factors (including process parameters, environmental conditions, etc.) on the melting deposition effect during the welding process to obtain the welding correction factor. The welding correction factor refers to the quantitative value of the influence of welding influencing factors and environmental influencing factors on the deposition rate during the melting deposition process. The greater the influence of welding influencing factors and environmental influencing factors on the deposition rate, the greater the welding correction factor. The original deposition rate refers to the volume of metal wire deposited per unit time in the melting deposition step.

[0030] In detail, the step of evaluating the welding influencing factors of the melting deposition step to obtain the welding correction coefficient includes: Obtaining a welding influencing factor group, wherein the welding influencing factor group includes: welding wire diameter, welding wire extension length, welding angle and shielding gas flow rate; The sensor monitoring unit is used to detect the environmental influencing factor group, wherein the sensor monitoring unit includes: a temperature sensor, a humidity sensor and a wind speed sensor, and the environmental influencing factor group includes: ambient temperature, ambient humidity and ambient wind speed; According to the welding influencing factor group and the environmental influencing factor group, the welding correction coefficient is calculated, wherein the welding correction coefficient is expressed as: , in, Indicates the welding correction factor, represents the preset empirical fitting coefficient, Indicates the ambient temperature, Indicates the wire diameter, Indicates the protective gas flow rate, Indicates the wire extension length. Indicates the ambient humidity. Indicates the ambient wind speed, represents the sine function, Indicates the welding angle.

[0031] It can be understood that the welding wire diameter refers to the diameter of the metal welding wire used for welding, and the welding wire extension length refers to the distance of the metal welding wire from the welding gun nozzle to the end of the arc. The welding angle refers to the angle between the welding gun and the surface of the component to be welded. The temperature sensor, humidity sensor and wind speed sensor refer to sensors for detecting temperature, humidity and wind speed respectively, and the ambient temperature, ambient humidity and ambient wind speed refer to the temperature, humidity and wind speed of the environment in the melting and deposition process respectively. The shielding gas flow rate refers to the volume of shielding gas delivered to the molten pool through the welding gun nozzle per unit time. The main function of the shielding gas is to isolate the molten pool from the outside air and prevent the metal in the molten pool from chemically reacting with oxygen, nitrogen, etc. at high temperature, thereby avoiding the generation of defects such as oxidation and nitridation. The shielding gas flow rate can be measured by a gas flow meter. The empirical fitting coefficient refers to a constant set artificially based on historical experience. It can be fitted through multiple pre-experiments. Optionally, the empirical fitting coefficient is set to 0.9.

[0032] In detail, the calculation of the original deposition rate according to the welding correction coefficient and the original welding parameter group includes: The original deposition rate is calculated using a preset deposition rate calculation formula, wherein the deposition rate calculation formula is expressed as: , in, represents the original deposition rate, represents the original voltage, represents the original current, Indicates the preset arc efficiency, Indicates the preset metal wire density, Indicates the original wire feed speed.

[0033] It is understandable that the arc efficiency refers to the energy required to melt a unit mass of metal welding wire, and the metal welding wire density refers to the density of the metal welding wire. Both the arc efficiency and the metal welding wire density are related to the metal welding wire, and can be obtained by looking up the specifications of the metal welding wire.

[0034] S4. Using a photographing unit to photograph the surface of the intermediate metal component to obtain a component surface image, and based on the component surface image, performing a component surface quality analysis on the intermediate metal component to obtain a component defect score.

[0035] It is clear that the surface shooting refers to shooting the surface of the intermediate metal component by a shooting unit, wherein the position of the shooting unit is fixed, and this solution does not limit the specific position, but it should be noted that the fixed position of the shooting unit should not interfere with the normal operation of the welding gun, and the shooting unit should be able to shoot the surface of the intermediate metal component to the greatest extent. For example: in the pre-planned three-dimensional component diagram, the left side of the intermediate metal component to be welded is a smooth and complete plane. In order to shoot the surface of the intermediate metal component to the greatest extent, the shooting unit can be fixed on the left side of the intermediate metal component. The component surface image refers to the surface image of the intermediate metal component. The component surface quality analysis refers to the process of obtaining a component defect score by performing image analysis on the component surface image. The component defect score refers to the quantitative value of the degree of surface defects of the intermediate metal component. The higher the degree of surface defects of the intermediate metal component, the greater the defect score of the construction.

[0036] In detail, the component surface quality analysis of the intermediate metal component based on the component surface image to obtain the component defect score includes: Performing image detection on the component surface image to obtain a quality assessment parameter group, wherein the quality assessment parameter group includes: crack growth rate and surface roughness; Based on the quality assessment parameter group, the component defect score is calculated using the following formula: , in, represents the component defect score, Indicates the surface roughness, Indicates the preset standard roughness, represents the crack growth rate.

[0037] It should be explained that the crack growth rate refers to the quantitative value of the growth degree of the crack on the surface of the intermediate metal component compared with the previous melting and deposition cycle. The higher the growth degree of the crack on the surface of the intermediate metal component compared with the previous melting and deposition cycle, the greater the crack growth rate. The surface roughness refers to the quantitative value of the surface roughness of the intermediate metal component. The rougher the surface of the intermediate metal component, the greater the surface roughness. The standard roughness rate refers to an artificially set constant of roughness.

[0038] Furthermore, the crack growth rate reflects the expansion of the surface cracks of the intermediate metal components between adjacent melting and deposition cycles. By detecting the crack growth rate, potential problems can be found in the early stage of crack expansion. At the same time, the crack growth rate is closely related to the welding process parameters (such as current, voltage, wire feeding speed, etc.). By detecting the crack growth rate, it also helps the staff to judge whether the current process parameters are reasonable. The surface roughness reflects the microscopic unevenness of the component surface. A higher surface roughness may lead to stress concentration, accelerated corrosion and other problems. Therefore, by detecting the surface roughness, the quality of the component surface can be intuitively evaluated.

[0039] In detail, the image detection of the component surface image is performed to obtain a quality assessment parameter group, including: Graying the surface image of the component to obtain a gray surface image, and performing roughness detection on the gray surface image to obtain surface roughness; Using a preset edge detection algorithm to perform crack contour detection on the grayscale surface image to obtain a crack surface image, and determining whether the crack surface image contains a crack; If the crack surface image does not contain cracks, the crack growth rate is recorded as 0; If the crack surface image includes cracks, a surface crack group in the crack surface image is identified, wherein the surface crack group includes one or more surface cracks; Identifying a surface crack length group of the surface crack group, wherein the surface crack lengths in the surface crack length group correspond one-to-one to the surface cracks in the surface crack group, and the surface crack lengths are the lengths of the corresponding surface cracks; The crack growth rate is calculated according to the surface crack length group, and the crack growth rate and surface roughness are confirmed as a quality evaluation parameter group.

[0040] It can be understood that the grayscale surface image refers to the component surface image after grayscale conversion, and the edge detection algorithm refers to an image processing technology that can identify the area where the grayscale value changes significantly in the grayscale image, wherein the significantly changed area can be regarded as a crack on the component surface in the grayscale surface image. Some existing edge detection algorithms can achieve this purpose, such as: Canny edge detection, Sobel edge detection, etc. The crack surface image refers to the grayscale surface image that highlights the crack outline after edge detection processing. The surface crack group refers to the set of cracks appearing in the crack surface image, and the surface crack length group refers to the set of lengths of all surface cracks in the surface crack group.

[0041] In detail, the calculating the crack growth rate according to the surface crack length group includes: constructing a surface crack vector based on the surface crack length group, wherein the dimension of the surface crack vector is the same as the number of surface crack lengths in the surface crack length group; Constructing a historical crack vector according to the surface crack group, wherein the dimension of the historical crack vector is the same as the dimension of the surface crack vector; The crack growth rate is calculated based on the surface crack vector and the historical crack vector, where the crack growth rate is expressed as: , in, represents the dimension of the surface crack vector or the dimension of the historical crack vector, represents the surface crack vector, represents the historical crack vector, Indicates the modulus length.

[0042] It should be explained that the surface crack vector refers to a vector representing the surface crack length information in the surface crack length group, and the surface crack vector is composed of the surface crack lengths in the surface crack length group.

[0043] For example, a surface crack group is: ( , , ),in, , , Represent three different cracks, the lengths of these three cracks are: 2.5mm, 1.2mm, 0.9mm, then the surface crack length group corresponding to the surface crack group is (2.5mm, 1.2mm, 0.9mm), and the corresponding surface crack vector is: It should be noted that the order of surface crack lengths in the surface crack vector should be consistent with the order of surface cracks in the surface crack group.

[0044] It is clear that the historical crack vector refers to the surface crack vector in the previous cycle (i.e., the previous welding cycle of the current welding cycle). It should be noted that since new cracks may be generated in the current welding cycle, in this case, the number of vector elements in the historical crack vector will be different from the number of vector elements in the surface crack vector. Therefore, when constructing the historical crack vector, it is necessary to insert 0 elements according to the actual situation. The detailed steps will be given later.

[0045] In detail, constructing the historical crack vector according to the surface crack group includes: Determining the start time of the melt deposition step, and querying the previous cycle crack group based on the start time; Respectively obtain the number of previous cycle cracks of the previous cycle crack group and the number of surface cracks of the surface crack group, and determine whether the number of previous cycle cracks is equal to the number of surface cracks; If the number of previous cycle cracks is equal to the number of surface cracks, a previous cycle crack length group of the previous cycle crack group is obtained, and a historical crack vector is constructed according to the previous cycle crack length group, wherein the dimension of the historical crack vector is the same as the number of previous cycle crack lengths in the previous cycle crack length group; If the number of cracks in the previous cycle is not equal to the number of surface cracks, then the newly added crack group and the homologous crack group are identified in the surface crack group; Respectively obtain the newly added sequence number group and the homologous sequence number group of the newly added crack group and the homologous crack group in the surface crack group, wherein the newly added crack group corresponds to the newly added sequence number group one by one, and the homologous crack group corresponds to the homologous sequence number group one by one; Based on the newly added crack group and the newly added sequence number group, the previous cycle crack group is expanded to obtain a historical crack group, wherein the historical crack group includes all previous cycle cracks and multiple empty cracks in the previous cycle crack group, and the arrangement sequence number of the previous cycle crack in the historical crack group is the same as the homologous sequence number of the corresponding homologous crack, the empty crack refers to a crack with a length of 0, and the arrangement sequence number of the empty crack in the historical crack group is the same as the newly added sequence number of the corresponding newly added crack; A historical crack length group of the historical crack group is obtained, and a historical crack vector is constructed based on the historical crack length group.

[0046] It can be understood that the start time refers to the start time of the melt deposition in the current welding cycle, and the previous cycle crack group refers to the surface crack group in the surface component image taken in the previous welding cycle at the start time. It should be noted that when this welding cycle is the first welding cycle, the previous cycle crack group will be an empty set. The number of previous cycle cracks refers to the number of previous cycle cracks in the previous cycle crack group, and the number of surface cracks refers to the number of surface cracks in the surface crack group. The previous cycle crack length group refers to the length combination of all previous cycle cracks in the previous cycle crack group.

[0047] It should be explained that the number of surface cracks should be greater than or equal to the number of cracks in the previous cycle, because in the process of melting and deposition, the cracks will gradually increase or remain unchanged over time, but will not decrease. At the same time, the increase in cracks not only refers to the increase in the number of cracks, the added cracks at this time are the newly added cracks, but also means: for the same crack, its length becomes longer than that of the previous cycle, and the same crack here refers to the homologous cracks. It can be understood that the newly added sequence number refers to the sorting sequence number of the newly added cracks in the newly added crack group in the surface crack group, and the homologous sequence number refers to the sorting sequence number of the homologous cracks in the homologous crack group in the surface crack group. The expansion of the previous cycle crack group refers to using a value of 0 to supplement the previous cycle crack group with a crack number less than the surface crack group until the crack number is consistent with the surface crack group.

[0048] For example, a surface crack group is: ( , , ), its corresponding surface crack length group is (2.5mm, 1.2mm, 0.9mm), and the previous cycle crack group in the previous welding cycle is: ( , ), the corresponding pre-cycle crack length group is (2.2mm, 1.0mm). The number of cracks in the pre-cycle crack group here is not equal to the number of cracks in the surface crack group. At this time, the cracks with the same source in the surface crack group and the pre-cycle crack group are and , and the newly added crack is , then the newly added crack groups and the homologous crack groups are ( )and( , ), their corresponding newly added serial number groups and homologous serial number groups are (3) and (1, 2) respectively. It should be noted here that although in the newly added crack group The arrangement number of is 1 (i.e., it is arranged in the first place), but its arrangement number in the surface crack group is 3, so its new number is recorded as 3 instead of 1. Since the new cracks in the new crack group do not appear in the previous cycle crack group, it is necessary to increase the position corresponding to the new number group in the previous cycle crack group, and the previous cycle crack group after the increase is ( , , ),at this time It is a crack with a length of 0. Since the previous cycle crack number in the previous cycle crack group is consistent with the homologous number group, no adjustment is required. At this time, the historical crack length group corresponding to the added previous cycle crack group is (2.2mm, 1.0mm, 0mm).

[0049] In detail, the roughness detection of the grayscale surface image to obtain the surface roughness includes: Extracting grayscale directions in a preset grayscale direction group in sequence, and calculating a grayscale co-occurrence matrix of the grayscale surface image in the grayscale direction; Calculating the contrast of the gray level co-occurrence matrix; The contrasts are summarized to obtain a contrast group, and the average contrast of the contrast group is calculated, and the average contrast is recorded as the roughness.

[0050] It can be understood that the grayscale direction group refers to a combination of directions set artificially. In the calculation of the grayscale co-occurrence matrix, 0 degrees, 45 degrees, 90 degrees and 135 degrees can be selected as this grayscale direction group. The grayscale co-occurrence matrix refers to a two-dimensional matrix that describes the distribution of pixel grayscale values ​​in a grayscale surface image. Calculating the grayscale co-occurrence matrix of a grayscale surface image in the grayscale direction is an existing technology and will not be described in detail here. The contrast refers to a value that measures the amplitude of change in the grayscale value of a pixel in a surface grayscale image, and the average contrast refers to the average value of all contrasts in the contrast group. Calculating the contrast of the grayscale co-occurrence matrix can be achieved by existing technology. For example, the contrast can be calculated by a contrast calculation formula. The contrast calculation formula is expressed as: , in, Indicates contrast, and Respectively represent the grayscale values ​​of two pixels in the grayscale surface image, and their value ranges are from 1 to , Represents the grayscale level of the surface grayscale image, Indicates the gray value is The frequency at which the pixel with gray value j appears simultaneously in the gray direction.

[0051] S5. Based on the component defect score and the preset standard defect score, the original deposition rate is adjusted to obtain an adjusted deposition rate.

[0052] It is understandable that the standard defect score refers to an artificially set constant, which is used to indicate the maximum acceptable value of the component defect score. The adjusted deposition rate refers to the original deposition rate after adjustment.

[0053] In detail, the original deposition rate is adjusted based on the component defect score and the preset standard defect score to obtain the adjusted deposition rate, including: Calculate the score data difference between the component defect score and the standard defect score, and determine whether the score data difference is greater than a preset controllable data difference; If the score data difference is not greater than the controllable data difference, the original deposition rate is recorded as the adjusted deposition rate; If the scoring data difference is greater than the controllable data difference, the adjusted deposition rate is calculated using the following formula: , in, represents the adjustment of the deposition rate, Indicates the standard defect score.

[0054] It should be explained that the scoring data difference refers to the difference between the component defect score and the standard defect score, and the controllable data difference refers to an artificially set constant. When the scoring data difference is not greater than the controllable data difference, it means that the component defect score is within a controllable range and does not need to be adjusted. When the scoring data difference is greater than the controllable data difference, it means that the component defect score deviates greatly from the standard defect score.

[0055] It should be noted that when the score data difference is greater than the controllable data difference, when the component defect score is higher than the standard defect score, it means that the number or severity of defects of the current component exceeds the preset acceptable range. In this case, in order to reduce the defects that may occur in the subsequent melting and deposition process, the deposition rate should be appropriately reduced, so that the melting process can be more accurately controlled and the generation of defects can be reduced. On the contrary, when the component defect score is lower than or equal to the standard defect score, it means that the number or severity of defects of the current component is within the acceptable range, or even better than expected. At this time, in order to improve production efficiency, the deposition rate can be appropriately increased to speed up the melting and deposition process, thereby improving manufacturing efficiency while ensuring component quality.

[0056] S6. According to the adjusted deposition rate, the original welding parameter group is adjusted to obtain an adjusted welding parameter group.

[0057] It can be understood that the welding parameter group adjustment includes: adjusting voltage, adjusting current and adjusting wire feeding speed, and the adjusting voltage, adjusting current and adjusting wire feeding speed refer to the original voltage, original current and original wire feeding speed after adjustment respectively. The detailed steps of adjusting the original welding parameter group are: determining the adjustment ratio, and the adjustment ratio is: ,in, Indicates the adjustment ratio. As the voltage and current increase, the deposition rate also increases, and as the wire feeding speed increases, the deposition rate decreases. The original welding parameter group can be adjusted according to the following formula: , , ,in, , and They are respectively expressed as adjusting voltage, adjusting current and adjusting wire feeding speed.

[0058] S7. Use the adjusted welding parameter group as the original welding parameter group, and return to the step of melting and depositing the pre-acquired metal welding wire using the pre-built arc additive equipment under the control of the original welding parameter group until the intermediate metal component is completed.

[0059] It should be explained that the standard for completing the construction of the intermediate metal components is that the size, shape and overall structure of the intermediate metal components are consistent with the design model.

[0060] In order to solve the problem described in the background technology, the present invention first determines the original welding parameter group based on the arc additive instruction, which provides initial conditions for the subsequent additive manufacturing process, and then performs melting deposition under the control of the original welding parameter group to obtain an intermediate metal component, and then evaluates the welding influencing factors of the melting deposition step to obtain a welding correction coefficient. The welding correction coefficient combines the factors that may affect the deposition rate in the welding process, so that the original deposition rate calculated subsequently is more accurate. Furthermore, the component surface image is obtained by a shooting unit, and the component defect score displayed by the component surface image is calculated. The component defect score can intuitively reflect the defect conditions on the component surface, such as cracks, pores, roughness, etc. Therefore, surface defects can be discovered in time through the component defect score, so as to avoid further expansion of defects in the subsequent manufacturing process, thereby improving the overall quality of the component. According to the defect score, the original deposition rate is adjusted to obtain the adjusted deposition rate. In this step, the deposition rate can be dynamically adjusted by comparing the component defect score with the standard defect score, thereby realizing real-time optimization of the additive manufacturing process. Moreover, by adjusting the deposition rate, the production efficiency can be improved under the premise of ensuring the quality of the component. In addition, the present invention also adjusts the original welding parameter group according to the adjusted deposition rate to obtain the adjusted welding parameter group. This step shows the process of accurately controlling the melt deposition, further improving the quality of the component, and according to different manufacturing stages and component states, the welding parameters can be dynamically adjusted, so that the present invention can adapt to complex manufacturing environments and requirements. Finally, the melt deposition process is cyclically executed by using the adjusted welding parameter group as the new original welding parameter group. This step reduces the influence of random factors on the manufacturing process through multiple cycle optimization and improves the stability of component manufacturing. Therefore, the present invention can improve the component quality and component production efficiency in the arc additive process.

[0061] like Figure 2 , which is a functional module diagram of a deposition rate-based arc additive process optimization system provided by one embodiment of the present invention.

[0062] The arc additive process optimization system 100 based on deposition rate of the present invention can be installed in an electronic device. According to the functions to be implemented, the arc additive process optimization system 100 based on deposition rate can include a metal component deposition module 101, a component defect assessment module 102, a welding parameter adjustment module 103 and a melting deposition cycle module 104. The module of the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0063] The metal component deposition module 101 is used to receive an arc additive instruction, and determine an original welding parameter group based on the arc additive instruction, wherein the original welding parameter group includes: an original voltage, an original current, and an original wire feeding speed. Under the control of the original welding parameter group, a pre-constructed arc additive device is used to melt and deposit a pre-acquired metal welding wire to obtain an intermediate metal component, wherein the duration of the melting and deposition is a preset welding cycle, and the arc additive device includes: a sensor monitoring unit and a shooting unit; The component defect assessment module 102 is used to assess the welding influencing factors of the melting deposition step, obtain the welding correction coefficient, and calculate the original deposition rate according to the welding correction coefficient and the original welding parameter group, and use the shooting unit to shoot the surface of the intermediate metal component to obtain the component surface image, and based on the component surface image, perform component surface quality analysis on the intermediate metal component to obtain a component defect score; The welding parameter adjustment module 103 is used to adjust the original deposition rate based on the component defect score and the preset standard defect score to obtain an adjusted deposition rate, and adjust the original welding parameter group according to the adjusted deposition rate to obtain an adjusted welding parameter group; The melting deposition cycle module 104 is used to use the adjusted welding parameter group as the original welding parameter group, and return to the step of melting and depositing the pre-acquired metal welding wire using the pre-built arc additive equipment under the control of the original welding parameter group until the intermediate metal component is completed.

[0064] In detail, the modules in the arc additive process optimization system 100 based on deposition rate in the embodiment of the present invention are used in the same manner as described above. Figure 1 The arc additive process optimization method based on deposition rate is the same technical means as described in the previous section and can produce the same technical effects, so it will not be repeated here.

[0065] like Figure 3 , is a schematic diagram of the structure of an electronic device for implementing an arc additive process optimization method based on deposition rate provided by an embodiment of the present invention.

[0066] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as an arc additive process optimization method program based on deposition rate.

[0067] Among them, the memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example: SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a mobile hard disk of the electronic device 1. In other embodiments, the memory 11 can also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device 1. Further, the memory 11 also includes an internal storage unit of the electronic device 1 and an external storage device. The memory 11 can not only be used to store application software and various types of data installed in the electronic device 1, such as the code of the arc additive process optimization method program based on the deposition rate, but also can be used to temporarily store data that has been output or is to be output.

[0068] In some embodiments, the processor 10 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips, etc. The processor 10 is the control core (Control Unit) of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device, and executes or executes programs or modules (such as a deposition rate-based arc additive process optimization method program, etc.) stored in the memory 11, and calls data stored in the memory 11 to execute various functions of the electronic device 1 and process data.

[0069] The bus 12 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 may be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0070] Figure 3 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 3 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0071] For example, although not shown, the electronic device 1 may also include a power source (such as a battery) for supplying power to various components. Preferably, the power source may be logically connected to the at least one processor 10 through a power management system, so that the power management system can realize functions such as charging management, discharging management, and power consumption management. The power source may also include any components such as one or more DC or AC power sources, recharging systems, power failure detection circuits, power converters or inverters, and power status indicators. The electronic device 1 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0072] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device 1 and other electronic devices.

[0073] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch device. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device 1 and to display a visual user interface.

[0074] The arc additive process optimization method program based on deposition rate stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can achieve: Receiving an arc additive instruction, and determining an original welding parameter group based on the arc additive instruction, wherein the original welding parameter group includes: an original voltage, an original current, and an original wire feeding speed; Under the control of the original welding parameter group, a pre-constructed arc additive device is used to melt and deposit the pre-acquired metal welding wire to obtain an intermediate metal component, wherein the duration of the melting and deposition is a preset welding cycle, and the arc additive device includes: a sensor monitoring unit and a shooting unit; The welding influencing factors of the melting deposition step are evaluated to obtain a welding correction coefficient, and an original deposition rate is calculated according to the welding correction coefficient and an original welding parameter group; Using a photographing unit to photograph the surface of the intermediate metal component to obtain a component surface image, and based on the component surface image, performing a component surface quality analysis on the intermediate metal component to obtain a component defect score; Based on the component defect score and the preset standard defect score, the original deposition rate is adjusted to obtain an adjusted deposition rate; According to the adjusted deposition rate, the original welding parameter group is adjusted to obtain an adjusted welding parameter group; The adjusted welding parameter group is used as the original welding parameter group, and the step of melting and depositing the pre-acquired metal welding wire using the pre-built arc additive equipment under the control of the original welding parameter group is returned until the intermediate metal component is completed.

[0075] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figures 1 to 3 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0076] Furthermore, if the module / unit integrated in the electronic device 1 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or system that can carry the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0077] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program can implement: Receiving an arc additive instruction, and determining an original welding parameter group based on the arc additive instruction, wherein the original welding parameter group includes: an original voltage, an original current, and an original wire feeding speed; Under the control of the original welding parameter group, a pre-constructed arc additive device is used to melt and deposit the pre-acquired metal welding wire to obtain an intermediate metal component, wherein the duration of the melting and deposition is a preset welding cycle, and the arc additive device includes: a sensor monitoring unit and a shooting unit; The welding influencing factors of the melting deposition step are evaluated to obtain a welding correction coefficient, and an original deposition rate is calculated according to the welding correction coefficient and an original welding parameter group; Using a photographing unit to photograph the surface of the intermediate metal component to obtain a component surface image, and based on the component surface image, performing a component surface quality analysis on the intermediate metal component to obtain a component defect score; Based on the component defect score and the preset standard defect score, the original deposition rate is adjusted to obtain an adjusted deposition rate; According to the adjusted deposition rate, the original welding parameter group is adjusted to obtain an adjusted welding parameter group; The adjusted welding parameter group is used as the original welding parameter group, and the step of melting and depositing the pre-acquired metal welding wire using the pre-built arc additive equipment under the control of the original welding parameter group is returned until the intermediate metal component is completed.

[0078] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, systems and methods can be implemented in other ways. For example, the system embodiments described above are only illustrative, and actual implementation may have other division methods.

[0079] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0080] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0081] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for optimizing arc additive process based on deposition rate, characterized in that: The method comprises: Receiving an arc additive instruction, and determining an original welding parameter group based on the arc additive instruction, wherein the original welding parameter group includes: an original voltage, an original current, and an original wire feeding speed; Under the control of the original welding parameter group, a pre-constructed arc additive device is used to melt and deposit the pre-acquired metal welding wire to obtain an intermediate metal component, wherein the duration of the melting and deposition is a preset welding cycle, and the arc additive device includes: a sensor monitoring unit and a shooting unit; The welding influencing factors of the melting deposition step are evaluated to obtain a welding correction coefficient, and an original deposition rate is calculated according to the welding correction coefficient and an original welding parameter group; Using a photographing unit to photograph the surface of the intermediate metal component to obtain a component surface image, and based on the component surface image, performing a component surface quality analysis on the intermediate metal component to obtain a component defect score; Based on the component defect score and the preset standard defect score, the original deposition rate is adjusted to obtain an adjusted deposition rate; According to the adjusted deposition rate, the original welding parameter group is adjusted to obtain an adjusted welding parameter group; The adjusted welding parameter group is used as the original welding parameter group, and the step of melting and depositing the pre-acquired metal welding wire using the pre-built arc additive equipment under the control of the original welding parameter group is returned until the intermediate metal component is completed.

2. The arc additive process optimization method based on deposition rate according to claim 1, characterized in that: The step of evaluating the welding influencing factors on the melting deposition step to obtain the welding correction coefficient includes: Obtaining a welding influencing factor group, wherein the welding influencing factor group includes: welding wire diameter, welding wire extension length, welding angle and shielding gas flow rate; The sensor monitoring unit is used to detect the environmental influencing factor group, wherein the sensor monitoring unit includes: a temperature sensor, a humidity sensor and a wind speed sensor, and the environmental influencing factor group includes: ambient temperature, ambient humidity and ambient wind speed; According to the welding influencing factor group and the environmental influencing factor group, the welding correction coefficient is calculated, wherein the welding correction coefficient is expressed as: ， in, Indicates the welding correction factor, represents the preset empirical fitting coefficient, Indicates the ambient temperature, Indicates the wire diameter, Indicates the protective gas flow rate, Indicates the wire extension length. Indicates the ambient humidity. Indicates the ambient wind speed, represents the sine function, Indicates the welding angle.

3. The arc additive process optimization method based on deposition rate according to claim 2, characterized in that: The calculating of the original deposition rate according to the welding correction coefficient and the original welding parameter group includes: The original deposition rate is calculated using a preset deposition rate calculation formula, wherein the deposition rate calculation formula is expressed as: ， in, represents the original deposition rate, represents the original voltage, represents the original current, Indicates the preset arc efficiency, Indicates the preset metal wire density, Indicates the original wire feed speed.

4. The arc additive process optimization method based on deposition rate according to claim 3, characterized in that: The component surface quality analysis of the intermediate metal component is performed based on the component surface image to obtain the component defect score, including: Performing image detection on the component surface image to obtain a quality assessment parameter group, wherein the quality assessment parameter group includes: crack growth rate and surface roughness; Based on the quality assessment parameter group, the component defect score is calculated using the following formula: ， in, represents the component defect score, Indicates the surface roughness, Indicates the preset standard roughness, represents the crack growth rate.

5. The arc additive process optimization method based on deposition rate according to claim 4, characterized in that: The step of performing image detection on the component surface image to obtain a quality assessment parameter group includes: Graying the surface image of the component to obtain a gray surface image, and performing roughness detection on the gray surface image to obtain surface roughness; Using a preset edge detection algorithm to perform crack contour detection on the grayscale surface image to obtain a crack surface image, and determining whether the crack surface image contains a crack; If the crack surface image does not contain cracks, the crack growth rate is recorded as 0; If the crack surface image includes cracks, a surface crack group in the crack surface image is identified, wherein the surface crack group includes one or more surface cracks; Identifying a surface crack length group of the surface crack group, wherein the surface crack lengths in the surface crack length group correspond one-to-one to the surface cracks in the surface crack group, and the surface crack lengths are the lengths of the corresponding surface cracks; The crack growth rate is calculated according to the surface crack length group, and the crack growth rate and surface roughness are confirmed as a quality evaluation parameter group.

6. The arc additive process optimization method based on deposition rate according to claim 5, characterized in that: Calculating the crack growth rate according to the surface crack length group includes: constructing a surface crack vector based on the surface crack length group, wherein the dimension of the surface crack vector is the same as the number of surface crack lengths in the surface crack length group; Constructing a historical crack vector according to the surface crack group, wherein the dimension of the historical crack vector is the same as the dimension of the surface crack vector; The crack growth rate is calculated based on the surface crack vector and the historical crack vector, where the crack growth rate is expressed as: ， in, represents the dimension of the surface crack vector or the dimension of the historical crack vector, represents the surface crack vector, represents the historical crack vector, Indicates the modulus length.

7. The arc additive process optimization method based on deposition rate according to claim 6, characterized in that: The constructing of the historical crack vector according to the surface crack group includes: Determining the start time of the melt deposition step, and querying the previous cycle crack group based on the start time; Respectively obtain the number of previous cycle cracks of the previous cycle crack group and the number of surface cracks of the surface crack group, and determine whether the number of previous cycle cracks is equal to the number of surface cracks; If the number of previous cycle cracks is equal to the number of surface cracks, a previous cycle crack length group of the previous cycle crack group is obtained, and a historical crack vector is constructed according to the previous cycle crack length group, wherein the dimension of the historical crack vector is the same as the number of previous cycle crack lengths in the previous cycle crack length group; If the number of cracks in the previous cycle is not equal to the number of surface cracks, then the newly added crack group and the homologous crack group are identified in the surface crack group; Respectively obtain the newly added sequence number group and the homologous sequence number group of the newly added crack group and the homologous crack group in the surface crack group, wherein the newly added crack group corresponds to the newly added sequence number group one by one, and the homologous crack group corresponds to the homologous sequence number group one by one; Based on the newly added crack group and the newly added sequence number group, the previous cycle crack group is expanded to obtain a historical crack group, wherein the historical crack group includes all previous cycle cracks and multiple empty cracks in the previous cycle crack group, and the arrangement sequence number of the previous cycle crack in the historical crack group is the same as the homologous sequence number of the corresponding homologous crack, the empty crack refers to a crack with a length of 0, and the arrangement sequence number of the empty crack in the historical crack group is the same as the newly added sequence number of the corresponding newly added crack; A historical crack length group of the historical crack group is obtained, and a historical crack vector is constructed based on the historical crack length group.

8. The arc additive process optimization method based on deposition rate according to claim 7, characterized in that: The step of performing roughness detection on the grayscale surface image to obtain the surface roughness comprises: Extracting grayscale directions in a preset grayscale direction group in sequence, and calculating a grayscale co-occurrence matrix of the grayscale surface image in the grayscale direction; Calculating the contrast of the gray level co-occurrence matrix; The contrasts are summarized to obtain a contrast group, and the average contrast of the contrast group is calculated, and the average contrast is recorded as the roughness.

9. The arc additive process optimization method based on deposition rate according to claim 8, characterized in that: The adjusting the original deposition rate based on the component defect score and the preset standard defect score to obtain the adjusted deposition rate includes: Calculate the score data difference between the component defect score and the standard defect score, and determine whether the score data difference is greater than a preset controllable data difference; If the score data difference is not greater than the controllable data difference, the original deposition rate is recorded as the adjusted deposition rate; If the scoring data difference is greater than the controllable data difference, the adjusted deposition rate is calculated using the following formula: ， in, represents the adjustment of the deposition rate, Indicates the standard defect score.

10. An arc additive process optimization system based on deposition rate, characterized in that: The system comprises: A metal component deposition module, used to receive an arc additive instruction, determine an original welding parameter group based on the arc additive instruction, wherein the original welding parameter group includes: an original voltage, an original current and an original wire feeding speed, and under the control of the original welding parameter group, use a pre-built arc additive device to melt and deposit the pre-acquired metal welding wire to obtain an intermediate metal component, wherein the duration of the melting and deposition is a preset welding cycle, and the arc additive device includes: a sensor monitoring unit and a shooting unit; a component defect assessment module, for assessing welding influencing factors of the melting deposition step, obtaining a welding correction coefficient, and calculating an original deposition rate according to the welding correction coefficient and an original welding parameter group, photographing the surface of the intermediate metal component by using a photographing unit to obtain a component surface image, and performing a component surface quality analysis on the intermediate metal component based on the component surface image to obtain a component defect score; A welding parameter adjustment module, used to adjust the original deposition rate based on the component defect score and the preset standard defect score to obtain an adjusted deposition rate, and to adjust the original welding parameter group according to the adjusted deposition rate to obtain an adjusted welding parameter group; The melting deposition cycle module is used to use the adjusted welding parameter group as the original welding parameter group and return to the step of melting and depositing the pre-acquired metal welding wire using the pre-built arc additive equipment under the control of the original welding parameter group until the intermediate metal component is completed.

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