A molding material detection method and system based on three-dimensional printing

Abstract

The present invention relates to the field of molding material detection technology, and specifically discloses a molding material detection method and system based on three-dimensional printing, the method comprising: S1, taking all-round photos of a printed part by a high-resolution camera, and acquiring surface image data of the printed part; S2, detecting and analyzing the inside of the printed part by an ultrasonic flaw detector, and acquiring internal flaw detection data of the printed part; S3, performing comprehensive analysis on the surface image data and internal flaw detection data of the printed part by an analysis control module, and then judging whether the printed part is qualified; the present invention analyzes the detection results of all printed parts of non-destructive detection, and in the process of detecting molding materials based on three-dimensional printing, intelligently adjusts the sampling frequency in the process of mechanical property sampling detection, which can effectively reduce material waste and reduce detection costs, and at the same time, ensure the purpose of accurate and sufficient detection of molding materials for three-dimensional printing.

Description

Technical Field

[0001] The present invention relates to the technical field of molding material detection, and in particular to a molding material detection method and system based on three-dimensional printing. Background Art

[0002] A three-dimensional printer, also known as a 3D printer, is a device that uses digital model files to create three-dimensional objects by adding materials layer by layer. It works by converting three-dimensional computer-aided design (CAD) models into physical objects. It is usually used in prototyping, product design, medical, aerospace, automobile manufacturing, architecture, and artistic creation. For example, when producing parts with complex shapes in the fields of aerospace or automobile manufacturing, three-dimensional printers are often needed to mass-produce these parts with complex shapes, especially when manufacturing lightweight and high-performance parts.

[0003] In the process of batch production of parts with complex shapes, existing 3D printers mostly use a variety of detection methods such as visual detection, ultrasonic detection and mechanical property testing to conduct comprehensive analysis in order to fully detect the molding materials for 3D printing. Since most of the detection items of mechanical property testing are destructive detection, the mechanical property testing of molding materials is a sampling test. However, in the sampling test of mechanical properties of molding materials based on 3D printing in the prior art, the sampling frequency is manually preset and relatively fixed, and cannot be intelligently adjusted according to the detection results of the molding materials. This may cause material waste and cost increase due to malfunctions in the production process of the 3D printer. Summary of the invention

[0004] The purpose of the present invention is to provide a molding material detection method and system based on 3D printing to solve the following technical problems:

[0005] The problem of how to intelligently adjust the sampling frequency during the mechanical property sampling test of molding materials.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A molding material detection method based on three-dimensional printing, the method comprising:

[0008] S1. Using a high-resolution camera to take omnidirectional photos of the printed part, and collect surface image data of the printed part;

[0009] S2. Detect and analyze the interior of the printed part by using an ultrasonic flaw detector to obtain internal flaw detection data of the printed part;

[0010] S3, comprehensively analyzing the surface image data and internal flaw detection data of the printed part through the analysis control module to obtain non-destructive detection parameters of the printed part, and then judging whether the printed part is qualified;

[0011] S4, within a preset time period, analyzing the test results of all prints from steps S1 to S3, and then intelligently adjusting the sampling frequency of the mechanical properties testing module;

[0012] S5. Perform sampling inspection on the batch-produced printed parts at the adjusted sampling frequency through the mechanical property inspection module to form an inspection batch and determine whether the batch of printed parts is qualified.

[0013] Furthermore, the process of obtaining the non-destructive detection parameters of the print comprises:

[0014]

[0015] The non-destructive testing parameters of the printed part are obtained by analyzing and calculating formula (1): ;

[0016] in, is the surface abnormality parameter of the print, is the internal defect parameter of the print, and is the first weight coefficient.

[0017] Furthermore, the process of obtaining the surface abnormality parameters of the printed part includes:

[0018]

[0019] The surface abnormality parameters of the printed part are obtained by analysis and calculation using formula (2): ;

[0020] in, is the number of defects on the surface of the print. , is the evaluation value of the ith defect. When the ith defect is within the allowable range, , when the i-th defect is a defect not within the allowable range, , is the shape deviation characteristic value of the print, and is the second weight coefficient.

[0021] Furthermore, the process of obtaining the internal defect parameters of the printed part includes:

[0022]

[0023] The internal defect parameters of the printed part are obtained by analysis and calculation using formula (3): ;

[0024] in, is the number of cracks inside the print. , is the evaluation value of the jth crack. When the jth crack is within the allowable range, , when the jth crack is a crack not within the allowable range, , B is the number of holes inside the print, , is the evaluation value of the kth hole. When the kth hole is within the allowable range, , when the kth hole is a hole outside the operating range, , and is the third weight coefficient.

[0025] Furthermore, the process of determining whether the printout is qualified includes:

[0026] The non-destructive testing parameters of the print and preset non-destructive testing parameter critical values Make a comparison;

[0027] like , then an early warning signal of the unqualified printout is generated, and the statistical record of the number of unqualified printouts is stored;

[0028] like , then the non-destructive testing parameters of the print are recorded and stored;

[0029] in, , , .

[0030] In one embodiment, the process of intelligently adjusting the sampling frequency of mechanical property testing includes:

[0031]

[0032]

[0033] The mechanical properties inspection frequency after intelligent adjustment is obtained by analyzing and calculating formulas (4)-(5) ;

[0034] in, The number of unqualified prints detected by the non-destructive detection module within a preset time period. is the average value of non-destructive inspection parameters of all normal prints obtained by the non-destructive inspection module within a preset time period. and is the fourth weight coefficient, It is the comprehensive quality characteristic parameters of all prints obtained by the non-destructive inspection module within a preset time period. To preset standard quality characteristic parameters, is the preset standard sampling frequency, [] is the rounding symbol.

[0035] In one embodiment, the process of determining whether the batch of prints is qualified includes:

[0036]

[0037] The quality abnormality characteristic value of this batch of prints is obtained by analysis and calculation through formula (6): ;

[0038] in, The comprehensive quality characteristic parameters of all prints obtained by the non-destructive inspection module for this batch of prints. The number of unqualified prints obtained by the mechanical properties test module for this batch of prints. The number of prints in this batch that have been tested by the mechanical properties test module. and is the fifth weight coefficient;

[0039] The quality abnormality characteristic value of this batch of prints Characteristic values ​​of abnormal quality compared to the standard quality of the preset type of print Make a comparison;

[0040] like , then an early warning signal indicating that the batch of prints is unqualified is generated;

[0041] Otherwise, a warning signal indicating that the batch of prints is qualified is generated.

[0042] A molding material detection system based on three-dimensional printing, the system is used in a molding material detection method based on three-dimensional printing, the system comprising:

[0043] A high-resolution camera is used to take all-round photos of the printed part and collect surface image data of the printed part;

[0044] Ultrasonic flaw detector, used to detect flaws inside printed parts and collect internal flaw detection data of printed parts;

[0045] Mechanical properties testing module, used to perform tensile, compression, fatigue and other mechanical properties tests on printed parts to evaluate whether their material properties and performance meet the design requirements;

[0046] The analysis and control module is used to comprehensively analyze the information collected by the high-resolution camera and the ultrasonic flaw detector to determine whether the printed parts are qualified, and to adjust the sampling frequency of the mechanical properties detection module, and then comprehensively analyze the sampling results of the mechanical properties detection module to determine whether the batch of printed parts is qualified;

[0047] The early warning module is used to execute the early warning signal during the molding material detection process.

[0048] Beneficial effects of the present invention:

[0049] (1) The present invention analyzes the test results of all printed parts by non-destructive testing within a preset time period, and intelligently adjusts the sampling frequency during the mechanical property sampling test of the molding materials based on three-dimensional printing, which can effectively reduce material waste and reduce testing costs, while ensuring the purpose of accurate and sufficient testing of the molding materials based on three-dimensional printing.

[0050] (2) The present invention determines whether a batch of printed parts is qualified by analyzing the comprehensive quality characteristic parameters of the batch of printed parts and the results of mechanical property sampling tests on the batch of printed parts. In this way, quality control can be performed on each batch in the printing process instead of each individual part. This can reduce the sampling frequency, but can still effectively control the overall quality, thereby achieving the purpose of overall quality control of the molding material. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The present invention will be further described below in conjunction with the accompanying drawings.

[0052] Figure 1 It is a flow chart of the steps of a molding material detection method based on three-dimensional printing proposed by the present invention;

[0053] Figure 2 This is a schematic block diagram of a molding material detection system based on three-dimensional printing proposed by the present invention. DETAILED DESCRIPTION

[0054] 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.

[0055] See also Figure 1As shown, in one embodiment, a molding material detection method based on three-dimensional printing is provided, the method comprising:

[0056] S1. Using a high-resolution camera to take omnidirectional photos of the printed part, and collect surface image data of the printed part;

[0057] S2. Detect and analyze the interior of the printed part by using an ultrasonic flaw detector to obtain internal flaw detection data of the printed part;

[0058] S3, comprehensively analyzing the surface image data and internal flaw detection data of the printed part by the analysis control module to obtain non-destructive detection parameters of the printed part, and then judging whether the printed part is qualified, wherein both step S1 and step S2 are non-destructive detection and will not affect the quality of the printed part;

[0059] S4, within a preset time period, analyzing the test results of all prints from steps S1 to S3, and then intelligently adjusting the sampling frequency of the mechanical properties testing module;

[0060] S5. Perform sampling inspection on the batch-produced prints at an adjusted sampling frequency through a mechanical property inspection module to form an inspection batch, and then determine whether the batch of prints is qualified. The mechanical property sampling inspection module includes but is not limited to a tensile test module, a compression test module, a bending test module, a hardness test module, a fatigue test module, etc.

[0061] Through the above technical scheme, this embodiment provides a molding material detection method based on three-dimensional printing, firstly, the printed part is photographed in all directions by a high-resolution camera, then the inside of the printed part is detected and analyzed by an ultrasonic flaw detector, and then the surface image data and internal flaw detection data of the printed part are comprehensively analyzed by the analysis control module to obtain the non-destructive detection parameters of the printed part, and the non-destructive detection parameters of the printed part are compared with the preset non-destructive detection parameter critical values ​​to determine whether the printed part is qualified, and at the same time, within a preset time period, the detection results of all printed parts subjected to non-destructive detection are analyzed, and then the sampling frequency of the mechanical property detection module is intelligently adjusted, and finally, the batch-produced printed parts are sampled and tested by the mechanical property detection module at the adjusted sampling frequency, and all the test result data are comprehensively analyzed to determine whether the batch of printed parts is qualified.

[0062] In one embodiment, the process of obtaining the non-destructive detection parameters of the printed part includes:

[0063]

[0064] The non-destructive testing parameters of the printed part are obtained by analyzing and calculating formula (1): ;

[0065] in, is the surface abnormality parameter of the print, is the internal defect parameter of the print, and is the first weight coefficient, which can be obtained based on experience.

[0066] The process of obtaining the surface abnormality parameters of the printed part includes:

[0067]

[0068] The surface abnormality parameters of the printed part are obtained by analysis and calculation using formula (2): ;

[0069] in, is the number of defects on the surface of the printed part, which can be obtained by analyzing the surface image data of the printed part according to the analysis control module. The surface defects include but are not limited to cracks, corrosion, color difference, etc. , is the evaluation value of the ith defect. When the ith defect is within the allowable range of the product, , when the i-th defect is a defect that is not within the allowable range of the product, , is a constant preset based on experience, is the shape deviation characteristic value of the printed part, which can be obtained by analyzing the surface image data of the printed part according to the analysis control module, including the volume proportion of the missing part and the volume proportion of the excess part of the printed part compared with the standard model, and is the second weight coefficient, which can be obtained based on experience.

[0070] The process of obtaining the internal defect parameters of the printed part includes:

[0071]

[0072] The internal defect parameters of the printed part are obtained by analysis and calculation using formula (3): ;

[0073] in, is the number of cracks inside the printed part, which can be obtained by analyzing the internal flaw detection data of the printed part according to the analysis control module. , is the evaluation value of the jth crack. When the jth crack is within the allowable range, , when the jth crack is a crack not within the allowable range, , B is the number of cavities inside the printed part, which can be obtained by analyzing the internal flaw detection data of the printed part according to the analysis control module. , is the evaluation value of the kth hole. When the kth hole is within the allowable range, , when the kth hole is a hole outside the operating range, , and are constants preset based on experience. and is the third weight coefficient, which can be obtained based on experience.

[0074] The process of judging whether the printout is qualified includes:

[0075] The non-destructive testing parameters of the print and preset non-destructive testing parameter critical values Compare, wherein the preset non-destructive detection parameter critical value It can be obtained by conducting non-destructive testing qualification tests based on the printouts;

[0076] like , then an early warning signal of the unqualified printout is generated, and the number of all unqualified printouts is statistically recorded and stored;

[0077] like , it means that the printout is a normal printout, and the non-destructive testing parameters of all normal printouts are recorded and stored. It should be noted that a normal printout is not necessarily a qualified printout;

[0078] in, , , .

[0079] The process of intelligently adjusting the sampling frequency of mechanical property testing includes:

[0080]

[0081]

[0082] The mechanical properties inspection frequency after intelligent adjustment is obtained by analyzing and calculating formulas (4)-(5) ;

[0083] in, The number of unqualified printouts detected by the non-destructive detection module within a preset time period can be obtained by counting the number of unqualified printouts detected in step S3 within the preset time period. The non-destructive detection module includes a high-resolution camera and an ultrasonic flaw detector. The preset time period can be obtained based on experience. is the average value of the non-destructive detection parameters of all normal printouts detected by the non-destructive detection module within a preset time period, which can be obtained by averaging the non-destructive detection parameters of all normal printouts detected in step S3 within the preset time period. and is the fourth weight coefficient, which can be obtained based on experience. The comprehensive quality characteristic parameters of all prints obtained by non-destructive testing modules within a preset time period. To preset standard quality characteristic parameters, it can be obtained by conducting non-destructive testing and sampling frequency adjustment experiments on prints within a preset time period. is the preset standard sampling frequency, which can be obtained based on experience. The preset standard sampling frequency is the minimum sampling frequency, and the unit is a certain number of printouts, one sampling interval, [] is the rounding symbol, () is the IF function.

[0084] Through the above technical solution, this embodiment provides a method for intelligently adjusting the sampling frequency of mechanical property testing. First, non-destructive testing is performed on each print in turn, and the test results are recorded and stored. Then, within a preset time period, the test results of all the prints tested are analyzed. When the comprehensive quality characteristic parameters of all the prints within the preset time period are less than the preset standard quality characteristic parameters, the frequency of mechanical property testing sampling is adjusted to the lowest frequency. For example, one out of 100 printed parts is selected for mechanical property testing. When the comprehensive quality characteristic parameters of all printed parts are greater than or equal to the preset standard quality characteristic parameters within the preset time period, the frequency of mechanical property testing is adjusted to As the comprehensive quality characteristic parameters of all printed parts increase, the frequency of mechanical property testing increases. The value decreases, that is, the frequency of random inspection increases. For example, one piece is selected from 80 printed parts for mechanical property testing. In this way, the sampling frequency of mechanical property sampling testing can be intelligently adjusted during the testing of molding materials based on 3D printing, which can effectively reduce material waste and reduce testing costs. When an abnormality occurs in the process of 3D printing molding materials, when the comprehensive quality characteristic parameters of all prints within a preset time period are greater than or equal to the preset standard quality characteristic parameters, the frequency of random inspection will be intelligently increased to ensure the purpose of accurate and sufficient testing of 3D printing molding materials.

[0085] In one embodiment, the process of determining whether the batch of prints is qualified includes:

[0086]

[0087] The quality abnormality characteristic value of this batch of prints is obtained by analysis and calculation through formula (6): ;

[0088] in, is the comprehensive quality characteristic parameter of all prints obtained by the non-destructive inspection module for this batch of prints, which can be calculated according to formula (4), and the preset time period is set as the entire inspection time of this batch of prints. The number of unqualified prints obtained by the mechanical properties testing module for the batch of prints can be obtained by statistically analyzing the number of unqualified prints detected by mechanical properties sampling for the batch of prints. The standard for unqualified prints detected by the mechanical properties testing module can be obtained based on the standard qualified mechanical properties of this type of prints, which is specifically obtained based on experience. The number of printed parts of the batch tested by the mechanical properties testing module can be obtained based on the number of mechanical properties sampling tests performed on the batch of printed parts. and is the fifth weight coefficient, which can be obtained based on experience;

[0089] The quality abnormality characteristic value of this batch of prints Characteristic values ​​of abnormal quality compared to the standard quality of the preset type of print Compare the standard quality abnormal characteristic value of the preset type of print It can be obtained based on the qualified test of the batch of printed parts of this type;

[0090] like , then an early warning signal indicating that the batch of prints is unqualified is generated;

[0091] Otherwise, a warning signal indicating that the batch of prints is qualified is generated.

[0092] Through the above technical scheme, this embodiment provides a method for judging whether the batch of printed parts is qualified. By analyzing the comprehensive quality characteristic parameters of the batch of printed parts and the results of mechanical property sampling inspection of the batch of printed parts, the quality abnormality characteristic value of the batch of printed parts is obtained, and the value is compared with the standard quality abnormality characteristic value preset for this type of printed parts to judge whether the batch of printed parts is qualified. In this way, quality control can be performed on each batch in the printing process instead of each individual part. This can reduce the sampling frequency, but can still effectively control the overall quality, thereby achieving the purpose of overall quality control of molding materials. It should be noted that each batch of printed parts can be obtained by artificial preset based on experience, and is not a fixed number or fixed production date of printed parts.

[0093] See also Figure 2 As shown, in one embodiment, a molding material detection system based on three-dimensional printing is provided, and the system is used for a molding material detection method based on three-dimensional printing, and the system includes:

[0094] A high-resolution camera is used to take all-round photos of the printed part and collect surface image data of the printed part;

[0095] Ultrasonic flaw detector, used to detect flaws inside printed parts and collect internal flaw detection data of printed parts;

[0096] Mechanical properties testing module, used to perform tensile, compression, fatigue and other mechanical properties tests on printed parts to evaluate whether their material properties and performance meet the design requirements;

[0097] The analysis control module is used to comprehensively analyze the information collected by the high-resolution camera and the ultrasonic flaw detector, obtain the non-destructive detection parameters of the printed parts, and judge whether the printed parts are qualified; according to the analysis of the results of the printed parts detected within the preset time period, the sampling frequency of the mechanical property detection module is adjusted; according to the non-destructive detection parameter data of all printed parts and the results of the printed parts, combined with the results of the mechanical property detection module sampling, a comprehensive analysis is performed to judge whether the batch of printed parts is qualified;

[0098] The early warning module is used to execute the early warning signal during the molding material detection process.

[0099] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A molding material detection method based on three-dimensional printing, characterized in that: The method comprises: S1. Using a high-resolution camera to take omnidirectional photos of the printed part, and collect surface image data of the printed part; S2. Detect and analyze the interior of the printed part by using an ultrasonic flaw detector to obtain internal flaw detection data of the printed part; S3, comprehensively analyzing the surface image data and internal flaw detection data of the printed part through the analysis control module to obtain non-destructive detection parameters of the printed part, and then judging whether the printed part is qualified; S4, within a preset time period, analyzing the test results of all prints from step S1 to S3, and then intelligently adjusting the sampling frequency of the mechanical properties testing module; S5. Perform sampling inspection on the batch-produced printed parts at the adjusted sampling inspection frequency through the mechanical property inspection module to form an inspection batch and determine whether the batch of printed parts is qualified; The process of intelligently adjusting the sampling frequency of mechanical property testing includes: The mechanical properties inspection frequency after intelligent adjustment is obtained by analyzing and calculating formulas (4)-(5) ; in, The number of unqualified prints detected by the non-destructive inspection module within a preset time period. is the average value of non-destructive inspection parameters of all normal prints obtained by the non-destructive inspection module within a preset time period. and is the fourth weight coefficient, It is the comprehensive quality characteristic parameters of all prints obtained by the non-destructive inspection module within a preset time period. To preset standard quality characteristic parameters, is the preset standard sampling frequency, [] is the rounding symbol.

2. A molding material detection method based on three-dimensional printing according to claim 1, characterized in that: The process of obtaining the non-destructive detection parameters of the printed part includes: The non-destructive testing parameters of the printed part are obtained by analyzing and calculating formula (1): ; in, is the surface abnormality parameter of the print, is the internal defect parameter of the print, and is the first weight coefficient.

3. A molding material detection method based on three-dimensional printing according to claim 2, characterized in that: The process of obtaining the surface abnormality parameters of the printed part includes: The surface abnormality parameters of the printed part are obtained by analysis and calculation using formula (2): ; in, is the number of defects on the surface of the print. , is the evaluation value of the ith defect. When the ith defect is within the allowable range, , when the i-th defect is a defect not within the allowable range, , is the shape deviation characteristic value of the print, and is the second weight coefficient.

4. A molding material detection method based on three-dimensional printing according to claim 3, characterized in that: The process of obtaining the internal defect parameters of the printed part includes: The internal defect parameters of the printed part are obtained by analysis and calculation using formula (3): ; in, is the number of cracks inside the print. , is the evaluation value of the jth crack. When the jth crack is within the allowable range, , when the jth crack is a crack not within the allowable range, , B is the number of holes inside the print, , is the evaluation value of the kth hole. When the kth hole is within the allowable range, , when the kth hole is a hole outside the operating range, , and is the third weight coefficient.

5. A molding material detection method based on three-dimensional printing according to claim 4, characterized in that: The process of judging whether the printout is qualified includes: The non-destructive testing parameters of the print and preset non-destructive testing parameter critical values Make a comparison; like , then an early warning signal of the unqualified printout is generated, and the statistical record of the number of unqualified printouts is stored; like , then the non-destructive testing parameters of the print are recorded and stored; in, , , .

6. A molding material detection method based on three-dimensional printing according to claim 5, characterized in that: The process of judging whether the batch of prints is qualified includes: The quality abnormality characteristic value of this batch of prints is obtained by analysis and calculation through formula (6): ; in, The comprehensive quality characteristic parameters of all prints obtained by the non-destructive inspection module for this batch of prints. The number of unqualified prints obtained by the mechanical properties test module for this batch of prints. The number of prints in this batch that have been tested by the mechanical properties test module. and is the fifth weight coefficient; The quality abnormality characteristic value of this batch of prints Characteristic values ​​of abnormal quality compared to the standard quality of the preset type of print Make a comparison; like , then an early warning signal indicating that the batch of prints is unqualified is generated; Otherwise, a warning signal indicating that the batch of prints is qualified is generated.

7. A molding material detection system based on three-dimensional printing, characterized in that: The system is used for a molding material detection method based on three-dimensional printing according to any one of claims 1 to 6, and the system comprises: A high-resolution camera is used to take all-round photos of the printed part and collect surface image data of the printed part; Ultrasonic flaw detector, used to detect flaws inside printed parts and collect internal flaw detection data of printed parts; Mechanical properties testing module, used to perform tensile, compression, fatigue and other mechanical properties tests on printed parts to evaluate whether their material properties and performance meet the design requirements; The analysis and control module is used to comprehensively analyze the information collected by the high-resolution camera and the ultrasonic flaw detector to determine whether the printed parts are qualified, and to adjust the sampling frequency of the mechanical properties detection module, and then comprehensively analyze the results of the sampling of the mechanical properties detection module to determine whether the batch of printed parts is qualified; The early warning module is used to execute the early warning signal during the molding material detection process.

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