Method and system for grading artificially grown diamond rough

Abstract

The present invention discloses a method for grading artificially grown diamond roughs, comprising the following steps: S1: weighing the rough diamond m and calculating a weight assignment coefficient α; S2: performing a 3D scan to obtain a 3D image of the rough diamond, calculating the yield y, and calculating a yield coefficient γ based on the yield; S3: performing a color analysis to obtain a transparency value T and calculate a color assignment coefficient τ; S4: measuring the rough diamond clarity C and calculating a clarity coefficient β; and S5: calculating a rough diamond assignment value M, where M = m·α·γ·τ·β·100. The present invention grades the rough diamond based on multiple dimensions, such as weight, clarity, transparency, and yield, and their impact on the market value of the diamond. These dimensions are then unified to assign a score to the rough diamond. This score reflects the market value of the rough diamond, thus resolving the problem of large errors in manual grading with the naked eye.

Description

Technical Field

[0001] The present invention relates to the technical field of artificially grown diamond synthesis, and in particular to a method and system for grading artificially grown diamond roughs. Background Art

[0002] After years of development, lab-grown diamonds have achieved large-scale production in recent years, posing a significant market potential and a shortage of supply. While polished diamonds (loose diamonds) have a mature international grading system, with numerous professional testing agencies conducting inspections and issuing certifications, the testing of rough diamonds (rough or unpolished diamonds) has traditionally relied on empirical judgment, resulting in the majority of profits going to middlemen. This is also true for lab-grown diamonds. Currently, each lab-grown diamond manufacturer has its own testing methods, but most rely on empirical grading, leading to significant discrepancies in assessment results between manufacturers. Some smaller companies even fail to conduct inspections and sell their products as mixed materials. These factors have led to a chaotic market for lab-grown diamonds, with significant price and grade variations between manufacturers. Many companies are unclear about the market pricing of their rough diamonds. Grading lab-grown diamonds and mitigating the influence of subjective factors on grading results have become a pressing challenge for the entire industry.

[0003] Chinese patent CN109991230A discloses a diamond color grading method and system. This method captures optical images of multiple locations, such as the crown and pavilion, and then grades the diamond's color according to the GIA color grading system based on the image's hue, saturation, and brightness, eliminating errors caused by visual grading. However, this document primarily addresses the color grading of finished diamonds. For irregularly shaped rough diamonds with uncut surfaces, their optical images differ significantly from those of cut finished diamonds, making this method unsuitable for grading rough diamonds.

[0004] Chinese patent CN111007068A discloses a deep learning-based yellow cultured diamond grade classification method. The method collects raw sample images, then processes them through grayscale conversion, filtering, denoising, and binarization. Finally, the processed images are input into a model library for grading. This method can roughly categorize cultured diamonds into three categories: Grade 1, Grade 2, and Grade 3. However, for gem-quality cultured diamonds, this grading standard is too broad and inadequate to meet market demands. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for grading artificially grown diamond roughs.

[0006] The technical solution adopted in the present invention is as follows:

[0007] A method for grading artificially grown diamond roughs comprises the following steps:

[0008] S1: Weigh the weight m of the diamond rough and calculate the weight assignment coefficient α;

[0009] S2: Perform 3D scanning to obtain a 3D image of the diamond rough, calculate the drilling rate y, and calculate the drilling rate coefficient γ based on the drilling rate;

[0010] S3: Perform color analysis to obtain the transparency value T and calculate the color assignment coefficient τ;

[0011] S4: Measure the clarity C of the rough diamond and calculate the clarity coefficient β;

[0012] S5: Calculate the value M of the diamond rough, M = m·α·γ·τ·β·100.

[0013] Preferred:

[0014] m and α conform to the following mapping relationship f1:

[0015] m∈[0,0.5),α=0.02;

[0016] m∈[0.5,1),α=0.05;

[0017] m∈[1,2),α=0.06;

[0018] m∈[2,3),α=0.08;

[0019] m∈[3,4),α=0.12;

[0020] m∈[4,5),α=0.15;

[0021] m∈[5,6),α=0.20;

[0022] m∈[6,7),α=0.28;

[0023] m∈[7,8),α=0.32;

[0024] m∈[8,9),α=0.45;

[0025] m∈[9,10],α=0.65;

[0026] y and γ conform to the following mapping relationship f2:

[0027] y∈[0%,30%), γ=0.05;

[0028] y∈[30%,40%), γ=0.1;

[0029] y∈[40%,50%), γ=0.2;

[0030] y∈[50%,60%), γ=0.4;

[0031] y∈[60%,70%), γ=0.6;

[0032] y∈[70%,80%), γ=0.8;

[0033] y∈[80%,90%), γ=0.9;

[0034] y∈[90%, 100%], γ=1.0;

[0035] T and τ conform to the following mapping relationship f3:

[0036] T∈[0%,40%), τ=0.05;

[0037] T∈[40%,50%), τ=0.10;

[0038] T∈[50%,60%), τ=0.20;

[0039] T∈[60%,70%), τ=0.40;

[0040] T∈[70%,80%), τ=0.60;

[0041] T∈[80%,90%), τ=0.90;

[0042] T∈[90%, 100%], τ=1.00;

[0043] C and β conform to the following mapping relationship f4:

[0044] C∈[0%, 40%), β=0.05;

[0045] C∈[40%, 50%), β=0.1;

[0046] C∈[50%, 60%), β=0.2;

[0047] C∈[60%, 70%), β=0.4;

[0048] C∈[70%, 80%), β=0.6;

[0049] C∈[80%, 90%), β=0.9;

[0050] C∈[90%, 99%], β=1.0;

[0051] In mapping f1, the unit of m is carat.

[0052] Preferably, in step S3, the transparency value T is measured as follows:

[0053] Randomly select n points (n≥3) of the diamond rough under a microscope and measure the RGB color value and transparency value of each point.

[0054] Preferably, in step S4, the clarity C is measured as follows:

[0055] Measure the short axis radius D0 of the diamond rough and the long axis diameter D of the impurity particles in the diamond rough under a microscope A and the distance D between the impurity particle and the center of mass of the diamond rough B , and press D A 、D B The size of the impurity particles is weighted by percentage to obtain the purity value C of each impurity particle. i , clarity

[0056] Preferably, three points of the diamond rough are randomly selected under a microscope, and the RGB color value and transparency value of each point are measured respectively.

[0057] Preferably, C i =C iA +C iB ,in:

[0058] D A with C iA The following mapping relationship f5 is met:

[0059] D A ∈[1,∞), C iA =20%;

[0060] D A ∈[0.8, 1), C iA =25%;

[0061] D A ∈[0.6,0.8), C iA =30%;

[0062] D A ∈[0.4,0.6), C iA =35%;

[0063] D A ∈[0.3,0.4), C iA =40%;

[0064] D A ∈[0.2,0.3), C iA =45%;

[0065] D A ∈[0.1,0.2), C iA =50%;

[0066] D B with C iB The following mapping relationship f6 is met:

[0067]

[0068]

[0069]

[0070] In the mapping f5, D A The unit is millimeters.

[0071] The present invention further provides a system for grading artificially grown diamond rough, for performing steps S2 to S5 in claim 1, comprising:

[0072] An optical image acquisition device comprising a stage, a 3D scanning lens, a light source capture lens, a ring light source, and a point light source, and configured to obtain at least a first optical image, a second optical image, and a third optical image of a rough diamond under a preset lighting environment, wherein the first optical image is a 3D scanned image of the rough diamond, the second optical image is obtained in a direction perpendicular to the stage under illumination from a ring light source coaxial with the light source capture lens, and the third optical image is obtained under illumination from the point light source directly below the stage;

[0073] A processor is configured to perform a diamond cutting simulation on the first optical image to obtain a drill yield, the processor is further configured to analyze the size and quantity of impurity particles in the second optical image, and the processor is further configured to obtain RGB color data of at least three random points in the third optical image.

[0074] Preferably, the loading platform can move in at least a first direction or a second direction in a horizontal plane, and the angle between the first direction and the second direction is 90°.

[0075] Preferably, a light-transmitting plate is provided in the central area of the loading platform.

[0076] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0077] (1) Based on the weight, clarity, transparency, and diamond yield of rough diamonds, the rough diamonds are graded according to their impact on the market value. These dimensions are then unified and the rough diamonds are assigned a score. This score can reflect the market value of the rough diamonds and can be priced based on the assigned value M. There is no need for manual inspection for grading and pricing, so that the pricing of rough diamonds is more in line with their true market value, reducing conflicts and disputes in transactions. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 This is a simulation chart of the diamond drilling rate.

[0079] Figure 2 This is an image of diamond clarity.

[0080] Figure 3 This is a diamond transparency image.

[0081] Figure 4 This is a structural diagram of Example 4.

[0082] Figure 5 A top view of the stage.

[0083] Figure 6 This is a system block diagram of Example 4.

[0084] Markings in the figure: 100, stage; 200, 3D scanning lens; 300, light source capture lens; 400, ring light source; 500, point light source; 600, computer; 101, light-transmitting plate. DETAILED DESCRIPTION

[0085] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0086] Example 1

[0087] This embodiment provides a method for grading artificially grown diamond rough, comprising the following steps:

[0088] S1: Weigh the weight m of the diamond rough and calculate the weight assignment coefficient α;

[0089] S2: Perform 3D scanning to obtain a 3D image of the diamond rough, calculate the drilling rate y, and calculate the drilling rate coefficient γ based on the drilling rate;

[0090] S3: Perform color analysis to obtain the transparency value T and calculate the color assignment coefficient τ;

[0091] S4: Measure the clarity C of the rough diamond and calculate the clarity coefficient β;

[0092] S5: Calculate the value M of the diamond rough, M = m·α·γ·τ·β·100.

[0093] Among them, m and α conform to the following mapping relationship f1:

[0094] Table 1. Mapping relationship between m and α f1

[0095] m / carat α [0,0.5) 0.02 [0.5,1) 0.05 [1,0.5) 0.06 [2,0.5) 0.08 [3,0.5) 0.12 [4,0.5) 0.15 [5,0.5) 0.20 [6,0.5) 0.28 [7,0.5) 0.32 [8,0.5) 0.45 [9,10] 0.65

[0096] y and γ conform to the following mapping relationship f2:

[0097] Table 2 y, γ mapping relationship f2

[0098] y / ％ γ [0,30) 0.05 [30,40) 0.10 [40,50) 0.20 [50,60) 0.40 [60,70) 0.60 [70,80) 0.80 [80,90) 0.90 [90,100) 1.00

[0099] T and τ conform to the following mapping relationship f3:

[0100] Table 3 T, τ mapping relationship f3

[0101]

[0102]

[0103] C and β conform to the following mapping relationship f4:

[0104] Table 4 C, β mapping relationship f4

[0105] C / ％ β [0,40) 0.05 [40,50) 0.10 [50,60) 0.20 [60,70) 0.40 [70,80) 0.60 [80,90) 0.90 [90,99) 1.00

[0106] Example:

[0107] Take any purified rough diamond and first weigh it on an electronic scale, obtaining a weight m of 3.25 carats. According to mapping table 1, the corresponding weight assignment coefficient α is 0.12. Then, perform 3D composition analysis on an electron microscope and obtain a maximum diamond yield y of 49.5%. According to mapping table 2, the diamond yield coefficient γ is 0.2. Then, perform color analysis on an electron microscope and obtain a transparency value T of 73%. According to mapping table 3, the color assignment coefficient τ is 0.6. Then, measure the clarity C on an electron microscope and obtain a clarity value of 86%. According to mapping table 3, the clarity coefficient β is 0.9. Therefore, the rough diamond assignment M = 3.25 × 0.12 × 0.2 × 0.6 × 0.9 × 100 = 4.212.

[0108] Because manual grading relies on subjective judgment based on visual observation and experience, grading results from different graders often vary significantly, making consensus difficult. Visual fatigue and observation angle can also lead to discrepancies in the results of multiple evaluations of the same rough diamond by the same grader. Each parameter of the assigned value M can be measured by equipment, eliminating human interference. The differences between multiple measurements of the same rough diamond are within an acceptable range, resulting in a grading result that is acceptable to both parties to the transaction and objectively reflects the market value of the rough diamond.

[0109] When making a sales quotation, a benchmark value can be selected from the latest quotes published by Papaport (Rapaport Diamond Report), and the product of the benchmark value and the assigned value M is used as the sales quotation for the rough diamond. For example, in this embodiment, the latest price of a 1-1.49 ct diamond with VS1 clarity and G color is used as the benchmark value. The latest published price of a 1-1.49 ct diamond with VS1 clarity and G color is 93 (hundreds of US dollars) obtained from Papaport (Rapaport Diamond Report). Then, M×93 is used to obtain the sales quotation for the rough diamond, that is, 4.212×93=391.716 US dollars.

[0110] When you need to sell multiple rough diamonds at one time, you only need to add up all the assigned numbers of the purchased diamonds, and then multiply it by the value of the diamond price anchor reflected in the most recent papaport to get the total selling price of this batch of diamonds.

[0111] For example, on April 18, a total of 1,000 carats (325 diamonds) of rough diamonds were sold. The total value of this batch of rough diamonds was $1,267.5. The Papaport diamond price anchor value is 93, so the total value of this batch of rough diamonds is $1,267.5 * 93 = $117,877.5. The average price per carat for this batch is $117.87, which is in line with the market pricing range.

[0112] The benchmark value here does not use the quotation of finished diamonds of corresponding weight, color and clarity as the benchmark value based on the weight, color and clarity of the rough diamond. This is because the rough diamond has not been cut, and the weight, color and clarity of the finished diamond cut from it are quite different from the rough diamond. Therefore, the most common diamond indicators of 1-1.49ct, VS1 clarity and G color are selected as the benchmark value. Appropriate adjustments can be made in actual applications.

[0113] Example 2

[0114] This embodiment provides a method for measuring the transparency value T in step S3 of embodiment 1. Specifically, three points of the diamond rough are randomly selected under a microscope, and the RGB color value of each point is measured respectively. Here, RGB refers to red, green, and blue respectively. Then, the average value of the R, G, and B values of each point is calculated. and As shown in Table 5 below:

[0115] Table 5 RGB values of the three selected points

[0116]

[0117]

[0118] As shown in Table 5, we can calculate

[0119] Transparency value

[0120] Substituting T=87.7% into the mapping relationship f3, we obtain the color assignment coefficient τ=0.90.

[0121] In other embodiments, the number of measurement points is not limited to 3. Any number of points can be selected as needed and the RGB value of each point can be measured. In this case, the transparency value T is calculated according to the following formula:

[0122]

[0123] Where n is the number of selected measurement points.

[0124] Example 3

[0125] This embodiment provides a method for measuring clarity C. Specifically, the short axis radius D0 of the diamond rough, the long axis diameter D of the impurity particles in the diamond rough, and the diameter of the diamond rough are measured under a microscope. A and the distance D between the impurity particle and the center of mass of the diamond rough B , and press D A 、D B The size of the impurity particles is weighted by percentage to obtain the purity value C of each impurity particle. i , then the clarity in:

[0126] C i =C iA +C iB ,

[0127] D A with C iA The following mapping relationship f5 is met:

[0128] Table 6 D A 、C iAMapping relationship f5

[0129] <![CDATA[D A / mm]]> <![CDATA[C iA / %]]> [1,∞) 20 [0.8,1) 25 [0.6,0.8) 30 [0.4,0.6) 35 [0.3,0.4) 40 [0.2,0.3) 45 [0.1,0.2) 50

[0130] D0, D B with C iB The following mapping relationship f6 is met:

[0131] Table 7 D0, D B with C iB Mapping relationship f6

[0132]

[0133] For example, the D0 of a diamond blank is 3.2 mm and 3 D A Impurity particles with a value greater than 0.1 mm are shown in Table 8 below:

[0134] Table 8 Three impurity particles

[0135] Impurity particles <![CDATA[D A / mm]]> <![CDATA[C iA / %]]> <![CDATA[D B / mm]]> <![CDATA[C iB / %]]> 1 0.32 40 2.63 50 2 0.15 50 1.76 30 3 0.36 40 2.85 50

[0136] Then C1=C 1A +C 1B =90%,

[0137] C2=C 2A +C 2B =80%,

[0138] C3=C 3A +C 3B =90%;

[0139] The clarity of the rough diamond According to the C, β mapping relationship f4, the corresponding clarity coefficient β is 0.90.

[0140] Example 4

[0141] This embodiment provides a system for grading artificially grown diamond rough, for executing steps S2 to S5 in claim 1, comprising an optical image acquisition device and a processor 600, such as Figure 6 shown.

[0142] like Figure 5As shown, the optical image acquisition device includes a stage 100, a 3D scanning lens 200, a light source capture lens 300, a ring light source 400, and a point light source 500, and is used to obtain at least a first optical image, a second optical image, and a third optical image of a rough diamond under a preset lighting environment. The first optical image is a 3D scan image of the rough diamond, the second optical image is obtained in a direction perpendicular to the stage 100 under the illumination of the ring light source 400 coaxial with the light source capture lens 300, and the third optical image is obtained under the illumination of the point light source 500 directly below the stage 100.

[0143] The above preset lighting environment refers to:

[0144] The light intensity emitted by the light source is a preset value;

[0145] The center of mass of the diamond rough and the center of the light source are kept on the same straight line, and the straight line is perpendicular to the horizontal plane;

[0146] The center of mass of the diamond rough, the center of the light source, and the light source capturing lens 300 are kept on the same straight line, and the straight line is perpendicular to the horizontal plane.

[0147] The processor 600 is used to perform a diamond cutting simulation on the first optical image to obtain a drill yield, the processor 600 is also used to analyze the size and quantity of impurity particles in the second optical image, and the processor 600 is also used to obtain RGB color data of at least three random points in the third optical image.

[0148] The stage 100 is movable in at least a first direction or a second direction within a horizontal plane, with the first and second directions forming a 90° angle. This allows the position of the diamond blank relative to the 3D scanning lens 200 or the light capture lens 300 to be adjusted so as to maintain the diamond blank at the center of the field of view. A light-transmitting plate 101 is provided in the central region of the stage 100 to allow light from the point light source 500 to pass through the stage 100.

[0149] When grading artificially grown diamond rough, the rough diamond is placed in a transparent glass dish and then placed on the light-transmitting plate 101. The ring light source 400 and the point light source 500 are turned on. A first optical image of the rough diamond is obtained through the 3D scanning lens 200 and the diamond rate y is calculated. The second and third optical images are obtained through the light source capture lens 300, and the transparency value T and clarity C are calculated. Then, the assignment value M is finally calculated according to the methods in Examples 1 to 3.

[0150] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A system for grading rough cultured diamonds, characterized in that: include: An optical image acquisition device comprises an object stage (100), a 3D scanning lens (200), a light source capturing lens (300), an annular light source (400), and a point light source (500), and is used to obtain at least a first optical image, a second optical image, and a third optical image of a rough diamond under a preset lighting environment, wherein the first optical image is a 3D scanning image of the rough diamond, the second optical image is obtained in a direction perpendicular to the object stage (100) under the illumination of an annular light source (400) coaxial with the light source capturing lens (300), and the third optical image is obtained under the illumination of the point light source (500) directly below the object stage (100); A processor (600) is used to perform a diamond cutting simulation on the first optical image to obtain a drill yield, the processor (600) is further used to analyze the size and quantity of impurity particles in the second optical image, and the processor (600) is further used to obtain RGB color data of at least three random points in the third optical image.

2. The system for grading rough cultured diamonds according to claim 1, wherein: The object carrier (100) can move in at least a first direction or a second direction in a horizontal plane, and the angle between the first direction and the second direction is 90°.

3. The system for grading rough cultured diamonds according to claim 1, wherein: A light-transmitting plate (101) is provided in the central area of the object carrier (100).

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