3D printing product defect repair method, system, equipment and storage medium

Abstract

The present invention discloses a method, system, device and storage medium for repairing defects of 3D printed products, wherein the method comprises: obtaining layer-by-layer printing data and theoretical printing data in the printing process to determine the printing defect area, and generating a point cloud data set corresponding to the printing defect area; comparing the point cloud data set with the theoretical printing data to determine the defect type of the printing defect area; generating a repair strategy containing repair data according to the point cloud data set and the defect type; generating a process table for performing specific repair actions based on the repair strategy; estimating the repair cost of executing the process table according to the preset process cost data, and judging whether the repair cost exceeds the preset cost threshold; if so, judging to abandon the repair; if not, reading the process table for performing specific repair actions. The present invention can effectively repair 3D printed products and achieve the purpose of reducing processing costs.

Description

Technical Field

[0001] The present invention relates to the field of 3D printing technology, and in particular to a 3D printing product defect repair method, system, device and storage medium. Background Art

[0002] 3D printing (3DP) is a type of rapid prototyping technology. It is a technology that uses materials to gradually accumulate to create entities. It is also called additive manufacturing. It is a technology that uses powdered metal or plastic and other bondable materials to construct objects by printing layer by layer based on digital model files. Currently, 3D printing technology has been widely used in many fields such as automobiles, aerospace, dentistry and medical equipment, and has become one of the important technical means of product manufacturing.

[0003] Although 3D printing technology has a great advantage in product molding speed, it also has high requirements for the precision of hardware equipment. During the processing, errors often occur in the product process due to assembly errors or print head travel errors. The most direct manifestation is poor surface quality of the product, such as surface roughness and flaws. At the same time, factors such as printing material defects, slag inclusions, and internal stress accumulation during the printing process will also affect the accuracy of the product. Some 3D printed products have a high overall processing cost due to expensive processing materials. When the accuracy exceeds the error range, if the product is directly judged as scrapped, it will cause great losses. Therefore, it is necessary to repair these products to improve the yield rate and reduce processing costs. Summary of the invention

[0004] In order to overcome the deficiencies of the prior art, the purpose of the present invention is to provide a 3D printing product defect repair method, system, device and storage medium, which have the advantages of improving the yield rate and reducing processing costs.

[0005] The purpose of the present invention is achieved by the following technical solutions:

[0006] According to a first aspect of an embodiment of the present disclosure, a method for repairing defects of a 3D printed product is provided, comprising:

[0007] Acquire layer-by-layer printing data and theoretical printing data during the printing process to determine the printing defect area, and generate a point cloud data set corresponding to the printing defect area;

[0008] Comparing the point cloud data set with the theoretical printing data to determine the defect type of the printing defect area, the defect type including: a first type of defect smaller than a preset error range and a second type of defect larger than a preset error range;

[0009] generating a repair strategy including repair data according to the point cloud data set and the defect type, the repair strategy including an additive repair procedure corresponding to the first type of defect and a subtractive repair procedure corresponding to the second type of defect;

[0010] Generate a process schedule for executing specific repair actions based on the repair strategy;

[0011] estimating the repair cost of executing the process schedule according to the preset process cost data, and determining whether the repair cost exceeds a preset cost threshold;

[0012] If so, it is determined that the repair is abandoned and a repair diagnosis report is generated;

[0013] If not, the process recipe is read to perform specific repair actions.

[0014] To implement the above technical solution, layer-by-layer printing data will be recorded during the 3D printing process, and theoretical printing data will be generated when designing 3D printed products. By comparing the layer-by-layer printing data with the theoretical printing data, the defective points in the layer-by-layer printing data can be determined. Multiple adjacent defective points can form a printing defect area, and each point in the printing defect area can constitute a point cloud data set. By comparing the point cloud data set with the corresponding theoretical printing data, the deviation of each point can be obtained. The deviation can reflect the defect situation of the point, and the corresponding defect type can be determined, namely the first type of defect and the second type of defect. Different defect types need to be repaired by different processes. For example, in the first type of defect state, the corresponding point is concave, and additive processing is required to repair the concave part, while in the second type of defect state, the corresponding point is concave. The corresponding points are convex, and subtractive processing is required to remove the convexities. A corresponding repair strategy is generated according to the point cloud data set and the defect type. The repair strategy provides a basis for the formulation of the process. Based on the generated additive repair program or subtractive repair program, combined with the process parameters of the required repair equipment, a process schedule is formed. The process schedule is used to control the execution of the repair action. Since the processes included in the process schedule are fixed, the repair cost can be calculated in combination with the corresponding preset process cost data. The purpose of the repair is to reduce the cost, so a preset cost threshold is set. When the repair cost is too high and exceeds the preset cost threshold, the purpose of reducing the cost cannot be achieved, so the repair is abandoned. Otherwise, specific repair actions can be performed according to the process schedule to repair the product and achieve the purpose of reducing the processing cost.

[0015] In some exemplary embodiments, the step of acquiring layer-by-layer printing data and theoretical printing data during the printing process to determine a printing defect area and generating a point cloud data set corresponding to the printing defect area specifically includes:

[0016] After acquiring the layer-by-layer printing data and theoretical printing data during the printing process, multiple printing comparison points are selected at the contour lines in each of the layer-by-layer printing data;

[0017] Determining the deviation between the printing comparison point and the theoretical printing data, and if the deviation exceeds a preset error range, determining the printing comparison point as a defective point;

[0018] If it is determined that there are at least three adjacent defective points in the adjacent layer-by-layer printing data, an area surrounded by the defective points is used as a printing defective area;

[0019] The coordinate values ​​of all printing points in the defect area are obtained to form the point cloud data set.

[0020] To implement the above technical solution, the outermost printing points of the layer-by-layer printing data constitute the contour line, and the deviation of the printing points at the contour line can directly reflect whether the product has defects. The deviation between the selected printing comparison point and the theoretical printing data is compared with a preset error range, and the preset error range is the product design tolerance range. When the deviation exceeds the preset error range, it can be determined as a defective point. When only individual printing points have defects, it does not affect the actual quality of the product. When there are at least three adjacent defective points in the adjacent layer-by-layer printing data, usually there are defects in a certain area. At this time, it is necessary to repair it. The area enclosed by the determined adjacent defective points is used as the printing defect area. All printing points in this printing area may have defects. Therefore, the coordinate values ​​of these printing points are formed into a point cloud data set as the basis for subsequent calculation and judgment.

[0021] In some exemplary embodiments, comparing the point cloud data set with the theoretical printing data to determine the defect type of the printing defect area specifically includes:

[0022] Comparing the coordinate value of each printing point in the point cloud data set with the theoretical printing data to obtain the deviation of each printing point;

[0023] Determining the defect type of the printing defect area according to the comparison between the deviation amount and a preset error range;

[0024] If it is determined that there are only defect points whose deviation is less than the preset error range in the printing defect area, the defect type is determined to be a first type defect;

[0025] If it is determined that there are only defect points with a deviation greater than a preset error range in the printing defect area, the defect type is determined to be a second type defect;

[0026] If it is determined that the printing defect area includes defect points whose deviation is less than the preset error range and defect points whose deviation is greater than the preset error range, the defect type is determined to be a mixed defect including the first type of defect and the second type of defect.

[0027] The above technical solution is implemented to realize the determination of defect types.

[0028] In some exemplary embodiments, generating a repair strategy including repair data according to the point cloud data set and the defect type specifically includes:

[0029] Obtain the coordinate value of each printing point in the point cloud data set, calculated as (Xn, Yn, Zn);

[0030] According to the deviation between the theoretical printing data and each printing point, a repair value corresponding to each printing point is obtained, which is calculated as (△Xn, △Yn, △Zn);

[0031] Classifying and marking each repair value to form a first repair set corresponding to a first type of defect and a second repair set corresponding to a second type of defect, wherein the first repair set and the second repair set form the repair data;

[0032] A repair strategy is formed according to the repair data and the defect type; wherein,

[0033] If the defect type is a first type defect, the repair strategy is an additive repair procedure including a repair value;

[0034] If the defect type is a second type defect, the repair strategy is a subtractive repair procedure including a repair value;

[0035] If the defect type is a mixed defect, the repair strategy is to first execute a first strategy of an additive repair program including a repair value and to execute a second strategy including a repair value and a compensation value, wherein the compensation value is determined by a deviation relative to theoretical printing data formed after the additive repair program.

[0036] To implement the above technical solution, usually the deviation between the printing point and the theoretical printing data can be used as the repair value. The first repair set needs to be repaired by additive processing, and the second repair set needs to be removed by subtractive processing. Therefore, different repair strategies are formed to provide a basis for subsequent process development.

[0037] In some exemplary embodiments, generating a process schedule for performing a specific repair action based on the repair strategy specifically includes:

[0038] If the repair strategy is an additive repair procedure including a repair value, then based on the processing parameter characteristics of the additive repair procedure, the first repair set is sliced ​​at a predetermined interval to obtain a plurality of processing slice layers, and a first process schedule is generated according to the slice data included in each of the processing slice layers, wherein the slice data includes a coordinate value corresponding to a defect point in the processing slice layer;

[0039] If the repair strategy is a subtractive repair procedure including a repair value, a machining reference plane is established according to the theoretical printing data, and a maximum value in the second repair set is obtained, and a second process schedule is generated with the maximum value as the repair starting point and the machining reference plane as the repair end point;

[0040] If the repair strategy is to first execute a first strategy of an additive repair program including a repair value and to execute a second strategy of executing a repair value and a compensation value, a first process schedule is first generated for the first repair set, and then a second repair set including a compensation value is retrieved, and a second process schedule is generated for the retrieved second repair set.

[0041] To implement the above technical solution, when it is necessary to perform repair processing through an additive repair program, since additive processing usually requires layer-by-layer processing, it is necessary to slice the first repair set, and then generate a first process schedule based on the slice data so that repairs can be performed on defect points located in different layers; and when it is necessary to perform repair processing through a subtractive repair program, since subtractive processing requires determining a specific amount of subtraction, after determining the processing reference surface and the maximum value in the second repair set, the repair starting point and repair end point of the subtractive processing can be determined, and then a second process schedule can be generated, so that repair processing can be performed on the second repair set; and when the defect type is a mixed defect, in order to simplify the repair processing process, all printing points in the defect area are usually first repaired by additive processing. After the additive processing repair, the deviation at the printing point corresponding to the second repair set will be further increased, and the increase is the amount generated by the additive processing. At this time, the repair starting point and repair end point can be re-determined using the increase as a compensation value, and then the second process is generated.

[0042] In some exemplary embodiments, estimating the repair cost of executing the process recipe according to the preset process cost data specifically includes:

[0043] A first cost parameter corresponding to the execution process is obtained according to the first process schedule and the preset process cost data, and a second cost parameter corresponding to the required consumable raw materials is obtained according to the preset process cost data and the first repair set, and the first cost parameter and the second cost parameter form a first repair cost; and / or,

[0044] A third cost parameter corresponding to the execution process is obtained as a second repair cost according to the second process schedule, the second repair set and the preset process cost data.

[0045] To implement the above technical solution, since the processing costs of additive processing and subtractive processing are different, for the first process schedule corresponding to additive processing, it is necessary to consider the cost of raw materials consumed during repair and the process cost when performing the repair action. For the second process schedule corresponding to subtractive processing, the cost mainly lies in the process cost when performing the repair action, thereby obtaining different repair costs.

[0046] In some exemplary embodiments, when determining whether the repair cost exceeds a preset cost threshold, a corresponding repair cost is selected according to the defect type and compared with the preset cost threshold;

[0047] If the defect type is a first type defect, selecting a first repair cost to compare with a preset cost threshold;

[0048] If the defect type is a second type defect, selecting a second repair cost to compare with a preset cost threshold;

[0049] If the defect type is a mixed defect, the first repair cost and the second repair cost are summed and compared with a preset cost threshold.

[0050] By implementing the above technical solution, after determining the total repair cost according to different defect types, and then comparing it with the preset cost threshold, it can be judged whether the repair process can achieve the purpose of cost saving.

[0051] According to a second aspect of an embodiment of the present disclosure, a 3D printing product defect repair system is provided, based on the 3D printing product defect repair method according to the first aspect, comprising:

[0052] A first judgment unit is used to obtain layer-by-layer printing data and theoretical printing data during the printing process to judge the printing defect area, and generate a point cloud data set corresponding to the printing defect area;

[0053] A second judgment unit, used for comparing the point cloud data set with the theoretical printing data to judge the defect type of the printing defect area, the defect type including: a first type of defect smaller than a preset error range and a second type of defect larger than a preset error range;

[0054] A first generating unit, configured to generate a repair strategy including repair data according to the point cloud data set and the defect type, wherein the repair strategy includes an additive repair program corresponding to the first type of defects and a subtractive repair program corresponding to the second type of defects;

[0055] A second generating unit, configured to generate a process recipe for executing a specific repair action based on the repair strategy;

[0056] The cost comparison unit is used to estimate the repair cost of executing the process schedule based on the preset process cost data, and determine whether the repair cost exceeds the preset cost threshold; if so, determine to abandon the repair and generate a repair diagnosis report; if not, read the process schedule for executing specific repair actions.

[0057] According to a third aspect of an embodiment of the present disclosure, a computer device is provided, including a memory and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the processor executes the steps of the 3D printing product defect repair method as described in the first aspect.

[0058] According to a fourth aspect of an embodiment of the present disclosure, a storage medium storing computer-readable instructions is provided. When the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the 3D printing product defect repair method as described in the first aspect.

[0059] In summary, compared with the prior art, the present invention has the following beneficial effects:

[0060] The embodiments of the present invention provide a 3D printed product defect repair method, system, device and storage medium. During the 3D printing process, layer-by-layer printing data will be recorded, and theoretical printing data will be generated when the 3D printed product is designed. By comparing the layer-by-layer printing data with the theoretical printing data, the defective points in the layer-by-layer printing data can be determined. Multiple adjacent defective points can form a printing defect area. Each point in the printing defect area can constitute a point cloud data set. By comparing the point cloud data set with the corresponding theoretical printing data, the deviation of each point can be obtained. The deviation can reflect the defect situation of the point, and the corresponding defect type, i.e., the first type of defect and the second type of defect, can be determined. Different defect types need to be repaired by different processes. For example, the corresponding point in the first type of defect state is concave, and additive processing is required to repair the concave part. In the first defect state, the corresponding point is in a convex shape. At this time, subtractive processing is required to remove the convex part. The corresponding repair strategy is generated according to the point cloud data set and the defect type. The repair strategy provides a basis for the formulation of the process. On the basis of the generated additive repair program or subtractive repair program, combined with the process parameters of the required repair equipment, a process schedule is formed. The process schedule is used to control the execution of the repair action. Since the process steps included in the process schedule are fixed, the repair cost can be calculated in combination with the corresponding preset process cost data. The purpose of the repair is to reduce the cost. Therefore, a preset cost threshold is set. When the repair cost is too high and exceeds the preset cost threshold, the purpose of reducing the cost cannot be achieved. Therefore, the repair is abandoned. Otherwise, specific repair actions can be performed according to the process schedule to repair the product and achieve the purpose of reducing the processing cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 The figure is a process flow chart of a 3D printing product defect repair method in an embodiment of the present invention.

[0062] Figure 2 Schematic diagram of the structure of a 3D printing product defect repair system in an embodiment of the present invention.

[0063] Figure 3 4 is a basic structural block diagram of a computer device in an embodiment of the present invention.

[0064] The numbers and letters in the figure represent the corresponding component names:

[0065] 10. A first judgment unit; 20. A second judgment unit; 30. A first generation unit; 40. A second generation unit; 50. A cost comparison unit. DETAILED DESCRIPTION

[0066] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0067] like Figure 1 As shown, the first aspect of the present invention provides a 3D printing product defect repair method, which is more suitable for large-scale 3D printing products. The method specifically includes:

[0068] S100, acquiring layer-by-layer printing data and theoretical printing data during the printing process to determine a printing defect area, and generating a point cloud data set corresponding to the printing defect area.

[0069] It should be noted that the layer-by-layer printing data can usually be the slice data of each layer of the 3D printed product, which is determined by the data actually generated during the 3D printing process, while the theoretical printing data is the theoretical data when designing 3D printed products. Due to the inherent precision errors of 3D printing equipment, the layer-by-layer printing data may have errors compared with the theoretical printing data, and a certain tolerance range will be set for product design. When the layer-by-layer printing data is within the tolerance range, it is qualified, and when it exceeds the tolerance range, there is a defect.

[0070] Among them, S100 specifically includes:

[0071] S101, after acquiring the layer-by-layer printing data and theoretical printing data in the printing process, select a plurality of printing comparison points at the contour lines in each layer-by-layer printing data.

[0072] Among them, the contour line is formed by the printing points located at the edge. Since it is only necessary to judge whether the contour line of each layer is within the tolerance range to determine whether the layer has defects, when selecting the printing comparison points, in order to ensure sufficient judgment accuracy while selecting as few points as possible to improve the judgment efficiency, a fixed spacing is usually set for uniform sampling. The fixed spacing can be determined according to the particle size of the powder raw material of the 3D printing product. For example, the particle size of the powder raw material is f, and the fixed spacing is d. Preferably, d=(3~5)*f, and the printing comparison points selected between adjacent layers are staggered and offset.

[0073] S102, determining the deviation between the printing comparison point and the theoretical printing data, and if the deviation exceeds a preset error range, determining that the printing comparison point is a defective point.

[0074] In the 3D printing process, the height direction is usually corrected, so the probability of defects in the height direction is relatively small, while defects are more likely to occur in the horizontal direction due to the limitation of the movement accuracy of the print head. Therefore, the deviation between the printing comparison point and the theoretical printing data is mainly manifested as the deviation of the X-axis coordinate and the Y-axis coordinate, and the preset error range is consistent with the tolerance range. The coordinate value of the printing comparison point is compared with the coordinate value of the corresponding point in the theoretical printing data, and the deviation of the X-axis coordinate and the Y-axis coordinate is mainly compared. When the deviation exceeds the preset error range, it can be determined as a defective point.

[0075] S103: If it is determined that there are at least three adjacent defective points in the adjacent layer-by-layer printing data, an area surrounded by the defective points is used as a printing defective area.

[0076] Among them, when there are at least three adjacent defective points in two adjacent layer-by-layer printing data, since the printing comparison points are selected at intervals, the area enclosed by these defective points contains multiple printing points. Since 3D printing is a continuous process, the printing points in this area usually have the same defects, that is, this area can be used as a printing defective area. When there are adjacent defective points in multiple continuous layer-by-layer printing data, the area enclosed by these defective points can also be used as a printing defective area.

[0077] S104, obtaining coordinate values ​​of all printing points in the defective area to form a point cloud data set. It can be understood that all printing points include defective points, and each time a defective area is determined, a point cloud data set is formed, and each point cloud data set can be marked and distinguished.

[0078] The outermost printing points of the layer-by-layer printing data constitute the contour line, and the deviation of the printing points at the contour line can directly reflect whether the product has defects. The deviation between the selected printing comparison point and the theoretical printing data is compared with the preset error range. The preset error range is the product design tolerance range. When the deviation exceeds the preset error range, it can be determined as a defective point. When only individual printing points have defects, it does not affect the actual quality of the product. When there are at least three adjacent defective points in the adjacent layer-by-layer printing data, there are usually defects in a certain area. At this time, it is necessary to repair it. The area enclosed by the determined adjacent defective points is used as the printing defect area. All printing points in this printing area may have defects. Therefore, the coordinate values ​​of these printing points are formed into a point cloud data set as the basis for subsequent calculation and judgment.

[0079] S200, comparing the point cloud data set with the theoretical printing data to determine the defect type of the printing defect area, the defect type including: a first type of defect smaller than a preset error range and a second type of defect larger than a preset error range.

[0080] Specifically, comparing the point cloud data set with the theoretical printing data to determine the defect type of the printing defect area specifically includes:

[0081] S201, comparing the coordinate value of each printing point in the point cloud data set with the theoretical printing data to obtain the deviation of each printing point. As mentioned above, in this embodiment, the deviation of the X-axis coordinate and the Y-axis coordinate is mainly determined.

[0082] S202: Determine the defect type of the print defect area according to the comparison between the deviation amount and the preset error range. The specific determination rules include:

[0083] S2021. If it is determined that there are only defect points whose deviation is less than the preset error range in the print defect area, the defect type is determined to be a first-class defect, which is usually caused by insufficient printing volume and is specifically manifested as a "concave" state compared with theoretical printing data;

[0084] S2022, if it is determined that there are only defect points whose deviation is greater than the preset error range in the print defect area, the defect type is determined to be a second type defect, which is usually caused by overprinting, excessive temperature, etc., and is specifically manifested as a "convex" state compared with the theoretical print data;

[0085] S2023. If it is determined that the printing defect area includes defect points whose deviations are less than the preset error range and defect points whose deviations are greater than the preset error range, the defect type is determined to be a mixed defect including first-type defects and second-type defects. The printing defect area is usually manifested in areas where the product surface shape changes, such as near corner edges, areas with large curvature changes, etc.

[0086] S300, generating a repair strategy including repair data according to the point cloud data set and the defect type, wherein the repair strategy includes an additive repair program corresponding to the first type of defects and a subtractive repair program corresponding to the second type of defects.

[0087] Specifically, the repair strategy containing repair data generated according to the point cloud data set and defect type includes:

[0088] S301, obtaining the coordinate value of each printing point in the point cloud data set, calculated as (Xn, Yn, Zn), the coordinate value is obtained by setting the printing point and the theoretical printing data in the same coordinate system.

[0089] S302, obtaining a repair value corresponding to each printing point according to the deviation between the theoretical printing data and each printing point, calculated as (△Xn, △Yn, △Zn), and usually the deviation is consistent with the repair value.

[0090] S303. Classify and mark each repair value to form a first repair set corresponding to the first type of defects and a second repair set corresponding to the second type of defects. The first repair set and the second repair set form repair data. It can be understood that the repair value in the first repair set can be set to a positive value, and the repair value in the second repair set can be set to a negative value. When only the first type of defects exist, the repair data only includes the first repair set. When only the second type of defects exist, the repair data only includes the second repair set. When it is a mixed type of defect, the repair data includes both the first repair set and the second repair set.

[0091] S304, forming a repair strategy based on the repair data and defect type; wherein,

[0092] If the defect type is a first-class defect, the repair strategy is an additive repair procedure including a repair value. The additive repair procedure is related to the additive repair equipment to be used. The additive repair method may be, for example, 3D printing, fused deposition modeling, selective laser sintering, etc.;

[0093] If the defect type is a second type defect, the repair strategy is a subtractive repair procedure including a repair value. The subtractive repair procedure is related to the subtractive repair equipment to be used. For example, the subtractive repair method may be grinding, milling, polishing, etc.;

[0094] If the defect type is a mixed defect, the repair strategy is to first execute the first strategy of the additive repair program including the repair value and to execute the second strategy including the repair value and the compensation value. The compensation value is determined by the deviation relative to the theoretical printing data formed after the additive repair program. Since the additive repair program is executed first, the deviation of the normal point or the printing point with the second type of defect will be enlarged during the repair process, and the enlarged deviation is the compensation value.

[0095] Usually, the deviation between the printed point and the theoretical printed data can be used as the repair value. The first repair set needs to be repaired by additive processing, and the second repair set needs to be removed by subtractive processing. Therefore, different repair strategies are formed to provide a basis for subsequent process development.

[0096] S400: Generate a process schedule for executing specific repair actions based on the repair strategy.

[0097] Specifically, S400 includes:

[0098] S401. If the repair strategy is an additive repair program including a repair value, based on the processing parameter characteristics of the additive repair program, the first repair set is sliced ​​at a predetermined interval to obtain a plurality of processed slice layers, and a first process schedule is generated according to the slice data contained in each processed slice layer, wherein the slice data includes coordinate values ​​corresponding to defect points in the processed slice layer.

[0099] Among them, the predetermined spacing is determined according to the particle size of the printing powder. Since the defect points may be located in different planes, for example, the defect points are located on an inclined surface or a curved surface, slicing processing is required to cover the defect points located in different layers. The first process schedule is formulated based on the additive repair program. It can be understood that the first process schedule is a set of programs that can be imported into the additive repair equipment to realize its repair action control.

[0100] S402. If the repair strategy is a subtractive repair program including a repair value, a machining reference plane is established based on the theoretical printing data, and the maximum value in the second repair set is obtained. A second process schedule is generated with the maximum value as the repair starting point and the machining reference plane as the repair end point. It can be understood that the machining reference plane is a reference plane consistent with the contour surface defined by the theoretical printing data, and the second process schedule is a program set that can be imported into the subtractive repair equipment to realize its repair action control.

[0101] S403. If the repair strategy is to first execute a first strategy of an additive repair program including a repair value and then execute a second strategy of executing a repair value and a compensation value, then first generate a first process schedule for the first repair set, then reacquire a second repair set including the compensation value, and generate a second process schedule for the reacquired second repair set.

[0102] When repair processing is required through an additive repair program, since additive processing usually requires layer-by-layer processing, it is necessary to slice the first repair set and generate a first process schedule based on the slice data so that repairs can be performed on defect points located in different layers; and when repair processing is required through a subtractive repair program, since subtractive processing requires determining a specific amount of subtraction, the repair starting point and repair end point of the subtractive processing can be determined after determining the processing reference surface and the maximum value in the second repair set, and then a second process schedule is generated, so that repair processing can be performed on the second repair set; and when the defect type is a mixed defect, in order to simplify the repair processing process, all printing points in the defect area are usually first repaired by additive processing. After the additive processing repair, the deviation at the printing point corresponding to the second repair set will be further increased, and the increase is the amount generated by the additive processing. At this time, the repair starting point and repair end point can be re-determined using the increase as a compensation value, and then the second process is generated.

[0103] S500: Estimate the repair cost of executing the process schedule according to the preset process cost data, and determine whether the repair cost exceeds the preset cost threshold. The specific determination process includes:

[0104] S601, if yes, then decide to abandon the repair and generate a repair diagnosis report, which may include the generated repair data, repair strategy, process schedule, repair cost and other data for relevant personnel to review and further evaluate;

[0105] S602: If not, read the process recipe to perform specific repair actions.

[0106] Among them, the repair cost of executing the process schedule is estimated based on the preset process cost data and specifically includes:

[0107] S501, obtaining a first cost parameter corresponding to the executed process according to the first process schedule and the preset process cost data, and obtaining a second cost parameter corresponding to the required consumable raw materials according to the preset process cost data and the first repair set, the first cost parameter and the second cost parameter forming a first repair cost; and / or,

[0108] S502, obtaining a third cost parameter corresponding to the execution process as a second repair cost according to the second process schedule, the second repair set and the preset process cost data.

[0109] It can be understood that if only the first type of defects exist in the printing defect area, only the first repair cost needs to be calculated; if only the second type of defects exist in the printing defect area, only the second repair cost needs to be calculated; and if the printing defect area is a mixed type of defect, both the first repair cost and the second repair cost need to be calculated at the same time; since the processing costs of additive processing and subtractive processing are different, for the first process schedule corresponding to additive processing, it is necessary to consider the cost of raw materials consumed during repair and the process cost when performing the repair action; for the second process schedule corresponding to subtractive processing, the cost mainly lies in the process cost when performing the repair action, thereby obtaining different repair costs.

[0110] It can be understood that the process cost of each additive machining action and the cost of raw materials consumed are certain, and the first process schedule includes the sequence of steps for performing the additive repair action, so the first repair cost required to perform the additive repair action can be estimated; and the process cost of subtractive machining is also relatively certain, and the second process schedule also includes the sequence of steps for the subtractive repair action, so the second repair cost required to perform the subtractive repair action can also be estimated.

[0111] Furthermore, when determining whether the repair cost exceeds a preset cost threshold, the corresponding repair cost is selected according to the defect type and compared with the preset cost threshold, which specifically includes:

[0112] S5031. If the defect type is a first type defect, select a first repair cost and compare it with a preset cost threshold;

[0113] S5032. If the defect type is a second type defect, select a second repair cost and compare it with a preset cost threshold;

[0114] S5033. If the defect type is a mixed defect, the first repair cost and the second repair cost are summed and compared with the preset cost threshold. At this time, since additive repair processing is performed first and then subtractive repair processing is performed, the first repair cost and the second repair cost will be generated respectively.

[0115] After determining the total repair cost based on different defect types and comparing it with the preset cost threshold, it can be determined whether the repair process can achieve the purpose of cost saving.

[0116] During the 3D printing process, layer-by-layer printing data will be recorded, and theoretical printing data will be generated when designing 3D printed products. By comparing the layer-by-layer printing data with the theoretical printing data, the defective points in the layer-by-layer printing data can be determined. Multiple adjacent defective points can form a printing defect area, and each point in the printing defect area can constitute a point cloud data set. By comparing the point cloud data set with the corresponding theoretical printing data, the deviation of each point can be obtained. The deviation can reflect the defect situation of the point, and the corresponding defect type can be determined, that is, the first type of defect and the second type of defect. Different defect types need to be repaired by different processes. For example, in the first type of defect state, the corresponding point is concave, and additive processing is required to repair the concave part, while in the second type of defect state, the corresponding point is If the defect is convex, subtractive processing is required to remove the protrusion. A corresponding repair strategy is generated according to the point cloud data set and the defect type. The repair strategy provides a basis for the formulation of the process. Based on the generated additive repair program or subtractive repair program, combined with the process parameters of the required repair equipment, a process schedule is formed. The process schedule is used to control the execution of the repair action. Since the processes included in the process schedule are fixed, the repair cost can be calculated in combination with the corresponding preset process cost data. The purpose of the repair is to reduce the cost, so a preset cost threshold is set. When the repair cost is too high and exceeds the preset cost threshold, the purpose of reducing the cost cannot be achieved, so the repair is abandoned. Otherwise, specific repair actions can be performed according to the process schedule to repair the product and achieve the purpose of reducing the processing cost.

[0117] like Figure 2 As shown, according to a second aspect of an embodiment of the present disclosure, a 3D printing product defect repair system is provided, based on the 3D printing product defect repair method as described in the first aspect, comprising:

[0118] The first judgment unit 10 is used to obtain the layer-by-layer printing data and theoretical printing data in the printing process to judge the printing defect area, and generate a point cloud data set corresponding to the printing defect area;

[0119] The second judgment unit 20 is used to compare the point cloud data set with the theoretical printing data to judge the defect type of the printing defect area, and the defect type includes: a first type of defect smaller than a preset error range and a second type of defect larger than a preset error range;

[0120] A first generating unit 30, configured to generate a repair strategy including repair data according to the point cloud data set and the defect type, wherein the repair strategy includes an additive repair program corresponding to the first type of defect and a subtractive repair program corresponding to the second type of defect;

[0121] A second generating unit 40 is used to generate a process recipe for performing a specific repair action based on the repair strategy;

[0122] The cost comparison unit 50 is used to estimate the repair cost of executing the process schedule based on the preset process cost data, and determine whether the repair cost exceeds the preset cost threshold; if so, determine to abandon the repair and generate a repair diagnosis report; if not, read the process schedule for executing specific repair actions.

[0123] When repairing, the first judgment unit 10 compares the layer-by-layer printing data with the theoretical printing data to determine the defective points in the layer-by-layer printing data. Multiple adjacent defective points can form a printing defect area, and each point in the printing defect area can constitute a point cloud data set. The second judgment unit 20 compares the point cloud data set with the corresponding theoretical printing data to obtain the deviation of each point, and the deviation can reflect the defect situation of the point, so as to determine the corresponding defect type, i.e., the first type of defect and the second type of defect. Different defect types need to be repaired by different processes. For example, in the first type of defect state, the corresponding point is concave, and additive processing is required to repair the concave part, while in the second type of defect state, the corresponding point is convex, and subtractive processing is required to repair the convex part. Elimination, the first generation unit 30 generates a corresponding repair strategy according to the point cloud data set and the defect type, and the repair strategy provides a basis for the formulation of the process. The second generation unit 40 forms a process schedule based on the generated additive repair program or subtractive repair program and the process parameters of the required repair equipment. The process schedule is used to control the execution of the repair action. Since the processes included in the process schedule are fixed, the cost comparison unit 50 can calculate the repair cost in combination with the corresponding preset process cost data. The purpose of the repair is to reduce the cost, so a preset cost threshold is set. When the repair cost is too high and exceeds the preset cost threshold, the purpose of reducing the cost cannot be achieved, so the repair is abandoned. Otherwise, specific repair actions can be performed according to the process schedule to repair the product and achieve the purpose of reducing the processing cost.

[0124] A third aspect of the present invention also provides a computer device, such as Figure 3 As shown, a schematic diagram of the internal structure of a computer device. The computer device includes a processor, a non-volatile storage medium, a memory, and a network interface connected via a system bus. Among them, the non-volatile storage medium of the computer device stores an operating system, a database, and computer-readable instructions. The database may store a control information sequence. When the computer-readable instructions are executed by the processor, the processor can implement a 3D printing product defect repair method. The processor of the computer device is used to provide computing and control capabilities to support the operation of the entire computer device. The memory of the computer device may store computer-readable instructions. When the computer-readable instructions are executed by the processor, the processor can execute a 3D printing product defect repair method. The network interface of the computer device is used to connect and communicate with a terminal. Those skilled in the art will understand that Figure 3The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0125] In this embodiment, the processor is used to execute Figure 3 The specific functions of the first judgment unit 10, the second judgment unit 20, the first generation unit 30, the second generation unit 40 and the cost comparison unit 50 are described in detail. The memory stores the program code and various data required to execute the above modules. The network interface is used to transmit data between the user terminal or the server. In this embodiment, the server can call the program code and data of the server to execute the functions of all sub-modules.

[0126] A fourth aspect of an embodiment of the present invention further provides a storage medium storing computer-readable instructions. When the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the 3D printing product defect repair method in any of the above embodiments.

[0127] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the aforementioned storage medium can be a non-volatile storage medium such as a disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0128] The above embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the present invention, which are equivalent modifications and improvements made to the above embodiments based on the essential technology of the present invention, and all of them belong to the protection scope of the present invention.

Claims

1. A method for repairing defects in 3D printed products, characterized in that: include: Acquire layer-by-layer printing data and theoretical printing data during the printing process to determine the printing defect area, and generate a point cloud data set corresponding to the printing defect area; Comparing the point cloud data set with the theoretical printing data to determine the defect type of the printing defect area, the defect type including: a first type of defect smaller than a preset error range and a second type of defect larger than a preset error range; generating a repair strategy including repair data according to the point cloud data set and the defect type, the repair strategy including an additive repair procedure corresponding to the first type of defect and a subtractive repair procedure corresponding to the second type of defect; Generate a process schedule for executing specific repair actions based on the repair strategy; estimating the repair cost of executing the process schedule according to the preset process cost data, and determining whether the repair cost exceeds a preset cost threshold; If so, it is determined that the repair is abandoned and a repair diagnosis report is generated; If not, then read the process recipe to perform specific repair actions; The step of obtaining the layer-by-layer printing data and theoretical printing data during the printing process to determine the printing defect area and generating a point cloud data set corresponding to the printing defect area specifically includes: After acquiring the layer-by-layer printing data and theoretical printing data during the printing process, multiple printing comparison points are selected at the contour lines in each of the layer-by-layer printing data; Determining the deviation between the printing comparison point and the theoretical printing data, and if the deviation exceeds a preset error range, determining the printing comparison point as a defective point; If it is determined that there are at least three adjacent defective points in the adjacent layer-by-layer printing data, an area surrounded by the defective points is used as a printing defective area; The coordinate values ​​of all printing points in the defect area are obtained to form the point cloud data set.

2. The 3D printing product defect repair method according to claim 1, characterized in that: The step of comparing the point cloud data set with the theoretical printing data to determine the defect type of the printing defect area specifically includes: Comparing the coordinate value of each printing point in the point cloud data set with the theoretical printing data to obtain the deviation of each printing point; Determining the defect type of the printing defect area according to the comparison between the deviation amount and a preset error range; If it is determined that there are only defect points whose deviation is less than the preset error range in the printing defect area, the defect type is determined to be a first type defect; If it is determined that there are only defect points whose deviation is greater than the preset error range in the printing defect area, the defect type is determined to be a second type defect; If it is determined that the printing defect area includes defect points whose deviation is less than the preset error range and defect points whose deviation is greater than the preset error range, the defect type is determined to be a mixed defect including the first type of defect and the second type of defect.

3. The 3D printing product defect repair method according to claim 2, characterized in that: The generating of the repair strategy including the repair data according to the point cloud data set and the defect type specifically includes: Obtain the coordinate value of each printing point in the point cloud data set, calculated as (Xn, Yn, Zn); According to the deviation between the theoretical printing data and each printing point, the repair value corresponding to each printing point is obtained, which is calculated as (△Xn, △Yn, △Zn); Classifying and marking each repair value to form a first repair set corresponding to a first type of defect and a second repair set corresponding to a second type of defect, wherein the first repair set and the second repair set form the repair data; A repair strategy is formed according to the repair data and the defect type; wherein, If the defect type is a first type defect, the repair strategy is an additive repair procedure including a repair value; If the defect type is a second type defect, the repair strategy is a subtractive repair procedure including a repair value; If the defect type is a mixed defect, the repair strategy is to first execute a first strategy of an additive repair program including a repair value and to execute a second strategy including a repair value and a compensation value, wherein the compensation value is determined by a deviation relative to theoretical printing data formed after the additive repair program.

4. The 3D printing product defect repair method according to claim 3, characterized in that: The process schedule for performing a specific repair action based on the repair strategy specifically includes: If the repair strategy is an additive repair procedure including a repair value, then based on the processing parameter characteristics of the additive repair procedure, the first repair set is sliced ​​at a predetermined interval to obtain a plurality of processing slice layers, and a first process schedule is generated according to the slice data included in each of the processing slice layers, wherein the slice data includes a coordinate value corresponding to a defect point in the processing slice layer; If the repair strategy is a subtractive repair procedure including a repair value, a machining reference plane is established according to the theoretical printing data, and a maximum value in the second repair set is obtained, and a second process schedule is generated with the maximum value as the repair starting point and the machining reference plane as the repair end point; If the repair strategy is to first execute a first strategy of an additive repair program including a repair value and to execute a second strategy of executing a repair value and a compensation value, a first process schedule is first generated for the first repair set, and then a second repair set including a compensation value is retrieved, and a second process schedule is generated for the retrieved second repair set.

5. The 3D printing product defect repair method according to claim 4, characterized in that: The estimated repair cost of executing the process schedule according to the preset process cost data specifically includes: A first cost parameter corresponding to the execution process is obtained according to the first process schedule and the preset process cost data, and a second cost parameter corresponding to the required consumable raw materials is obtained according to the preset process cost data and the first repair set, and the first cost parameter and the second cost parameter form a first repair cost; and / or, A third cost parameter corresponding to the execution process is obtained as a second repair cost according to the second process schedule, the second repair set and the preset process cost data.

6. The 3D printing product defect repair method according to claim 5, characterized in that: When determining whether the repair cost exceeds a preset cost threshold, selecting a corresponding repair cost according to the defect type and comparing it with the preset cost threshold; If the defect type is a first type defect, selecting a first repair cost to compare with a preset cost threshold; If the defect type is a second type defect, selecting a second repair cost to compare with a preset cost threshold; If the defect type is a mixed defect, the first repair cost and the second repair cost are summed and compared with a preset cost threshold.

7. A 3D printing product defect repair system, characterized in that: The 3D printing product defect repair method according to any one of claims 1 to 6 comprises: A first judgment unit is used to obtain layer-by-layer printing data and theoretical printing data during the printing process to judge the printing defect area, and generate a point cloud data set corresponding to the printing defect area; A second judgment unit, used for comparing the point cloud data set with the theoretical printing data to judge the defect type of the printing defect area, the defect type including: a first type of defect smaller than a preset error range and a second type of defect larger than a preset error range; A first generating unit, configured to generate a repair strategy including repair data according to the point cloud data set and the defect type, wherein the repair strategy includes an additive repair program corresponding to the first type of defects and a subtractive repair program corresponding to the second type of defects; A second generating unit, configured to generate a process recipe for executing a specific repair action based on the repair strategy; The cost comparison unit is used to estimate the repair cost of executing the process schedule based on the preset process cost data, and determine whether the repair cost exceeds the preset cost threshold; if so, determine to abandon the repair and generate a repair diagnosis report; if not, read the process schedule for executing specific repair actions.

8. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the processor executes the steps of the 3D printing product defect repairing method according to any one of claims 1 to 6.

9. A storage medium storing computer-readable instructions, wherein when the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the 3D printing product defect repairing method according to any one of claims 1 to 6.

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