CN111054865A - Forging process selection method for guiding elbow forge piece of deep sea oil extraction equipment based on steel ingot internal defect classification - Google Patents
Forging process selection method for guiding elbow forge piece of deep sea oil extraction equipment based on steel ingot internal defect classification Download PDFInfo
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Abstract
The invention relates to a forging process selection method for guiding a deep-sea oil extraction equipment elbow forge piece based on steel ingot internal defect classification, which comprises the following steps of: detecting internal defects of the steel ingot, and grading detection results: dividing flaw detection into 5 grades according to flaw detection waveforms; selecting a forging process according to flaw detection classification: with the increase of the flaw detection grade, the forging temperature is increased, the forging ratio is increased, the forging speed is increased, and the forging times are increased. The method can obtain an accurate steel ingot blank manufacturing process, correctly guide production, and avoid material waste and property loss caused by the scrapping of forgings due to the defects of raw materials (steel ingot blanks) or the problems of a forging process.
Description
Technical Field
The invention relates to a method for selecting a steel ingot forging process based on steel ingot internal defect classification, and belongs to the technical field of steel ingot nondestructive testing and hot forging process selection.
Background
Steel products used in the modern time are all rolled or forged from steel ingots, so that the pursuit of steel ingot quality is always the object pursued by large-scale steel enterprises today when the steel industry is rapidly developing. In the production process of steel ingots, the quality detection of the steel ingots is the most important link. Only if the enterprise can timely and accurately detect the quality of the product, the production strategy can be correctly adjusted according to the specific production condition. The effective quality detection of the steel ingot can ensure the production efficiency and the product quality, and is a powerful guarantee for enterprises to obtain economic benefits.
The elbow forging of the deep-sea oil extraction equipment is applied to the deep-sea environment, needs to bear high pressure caused by water depth and impact of underwater undercurrent, and needs to have very strong bearing capacity and very high impact energy. The quality guarantee of the elbow forging of the deep sea oil extraction equipment needs to be made from the source, once the product quality problem exists midway, the elbow forging must be scrapped, very high economic loss can be caused, and according to the application amount of an applicant unit, if the forging treatment amount is waste, the daily loss reaches 50 thousands. Therefore, the method has very high work guidance significance for the material selection of the forged piece, namely the judgment of the steel ingot blank.
Disclosure of Invention
In order to solve the technical problems, the invention provides a forging process selection method for guiding a deep sea oil extraction equipment elbow forge piece based on steel ingot internal defects in a grading manner, which has the following specific technical scheme:
the method for selecting the forging process of the elbow forge piece of the deep sea oil extraction equipment based on the steel ingot internal defect classification guidance comprises the following steps of:
step 1: detecting internal defects of the steel ingot: selecting a steel ingot, wherein the ratio of the length of the steel ingot to the equivalent diameter is less than 2.5-3, standing the steel ingot, and detecting the other end of the steel ingot from one end in the length direction by using an ultrasonic detector to obtain the waveform of ultrasonic flaw detection;
step 2: grading the detection result: flaw detection is divided into 5 grades according to flaw detection waveforms, and the steps are as follows:
when the flaw detection waveform is in a reduced grass shape, the steel ingot has no obvious defects, the crystal grains are in a coarse shape, the named flaw detection grade is 0 grade,
when flaw detection waveform is center porosity, dispersed tiny holes are formed in the center of the steel ingot, the named flaw detection grade is grade 1,
when the flaw detection waveform is center porosity and shrinkage, the center of the steel ingot is provided with dispersed tiny holes and small concentrated holes, the named flaw detection grade is grade 2,
when the flaw detection waveform is central shrinkage and loosening, the steel ingot has concentrated holes and a small amount of dispersed fine holes, the named flaw detection grade is 3 grade,
when the flaw detection waveform is a central shrinkage cavity, a large centralized hole is formed in the center of the steel ingot, and the named flaw detection grade is 4 grade;
and step 3: selecting a forging process according to flaw detection classification: with the increase of the flaw detection grade, the forging temperature is increased, the forging ratio is increased, the forging speed is increased, and the forging times are increased.
Further, in step 1, the blank needs to be pretreated before ultrasonic flaw detection, and the pretreatment specifically includes:
and when the roughness of the detected surface of the blank is more than 30 micrometers, polishing the detected surface until the roughness is 10-30 micrometers, and when the visible brightness of the detected surface of the blank is less than 50%, polishing the detected surface until the visible brightness is more than 50%.
Further, the method for grinding the surface of the blank comprises the following steps: polishing in a 0 degree, 45 degree, 90 degree or 0 degree, 120 degree and 240 degree interval mode, wherein the polishing width is not less than 100mm, polishing along the length direction of the blank steel ingot, and polishing from one end to the other end of the length direction to form longitudinal poker, wherein at least 3 poker are formed, and the number of the poker is sequentially marked.
Further, areas of 100mmX100mm are sequentially taken along the longitudinal through bars to be subjected to flaw detection measurement, flaw detection grades of all sections are obtained, a table is made according to flaw detection measurement results and positions where the flaw detection measurement results are located, the sizes and the grades of flaw detection defects of the blank steel ingot in the length direction and the positions are obtained, a distribution diagram of the sizes of the flaw detection defects in the steel ingot blank length direction and a distribution diagram of the grades of the flaw detection defects in the blank steel ingot length direction are drawn according to table making data, and the overall flaw detection grade of the steel ingot is obtained according to the distribution diagram of the sizes of the flaw detection defects in the steel ingot blank length direction and the distribution diagram of the grades of the flaw detection.
Further, when the number of defect levels reaching level 4 exceeds 30%, judging that the defect level is level 4;
when the number of the defect grades reaching 4 grades is not more than 30 percent, and the number of the defect grades exceeding 3 grades is more than 30 percent, judging the defect grade to be 3 grade;
when the number of the defect grades exceeding 3 grades does not exceed 30 percent, calculating the defect grade of the steel ingot according to a calculation formula, wherein the calculation formula is as follows: and (3) the integral flaw detection grade of the steel ingot is the sum of flaw detection defect grades/steel ingot length/100, wherein the unit of the steel ingot length is mm.
Further, when the ratio of the length to the diameter of the steel ingot forging is 2.2-3.5, the step 3 specifically comprises the following steps:
when the flaw detection grade is 0 grade, the following forging process is adopted:
step (01): adding the steel ingot blank into a heating furnace, heating to 1200 ℃, transferring the steel ingot blank to a free forging hammer, and forging, wherein the upsetting ratio is 1.5 +/-0.1;
step (02): putting the upset ingot blank into the heating furnace again, heating to 1200 ℃, and drawing to a length which is 1.7 +/-0.2 times of the equivalent diameter of the section;
step (03): entering a heat treatment process;
when the flaw detection grade is 1 grade, the following forging process is adopted:
step (11): adding the steel ingot blank into a heating furnace, heating to 1250-1280 ℃, transferring to a free forging hammer, and forging, wherein the upsetting ratio is 1.7-1.9;
step (12): putting the upset steel ingot blank into a heating furnace again, heating to 1250-1280 ℃, and drawing to a length which is 1.9-2.1 times of the equivalent diameter of the section;
step (13): entering a heat treatment process;
when the flaw detection grade is 2 grade, the following forging process is adopted:
step (21): adding the steel ingot blank into a heating furnace, heating to 1280-1320 ℃, transferring to a free forging hammer, and forging, wherein the upsetting ratio is 1.9-2.0;
step (22): putting the upset steel ingot blank into a heating furnace again, heating to 1280-1320 ℃, and drawing to a length which is 2.0-2.2 times of the equivalent diameter of the section;
step (23): repeating steps (21) and (22) once;
step (24): entering a heat treatment process;
when the flaw detection grade is 3 grades, the following forging process is adopted:
step (31): adding the steel ingot blank into a heating furnace, heating to 1320-1350 ℃, transferring to a free forging hammer, and forging, wherein the upsetting ratio is 1.9-2.0;
step (32): putting the upset steel ingot blank into a heating furnace again, heating to 1280-1350 ℃, and drawing to a length which is 2.0-2.2 times of the equivalent diameter of the section;
step (33): repeating steps (31) and (32) once;
step (34): entering a heat treatment process;
and when the flaw detection grade is 4 grade, judging that the steel ingot is a defective product and cannot be used for forging the elbow forging of the deep-sea oil extraction equipment.
Further, when the ratio of the length to the diameter of the steel ingot forging is less than 2.2, the step 3 specifically comprises the following steps:
when the flaw detection grade is 0 grade, the following forging process is adopted:
step (01): adding the steel ingot blank into a heating furnace, heating to 1200 ℃, and drawing to a length which is 1.7 +/-0.2 times of the equivalent diameter of the section;
step (02): putting the steel ingot blank after upsetting into the heating furnace again, heating to 1200 ℃, transferring to a free forging hammer for forging, wherein the upsetting ratio is 1.5 +/-0.1;
step (03): entering a heat treatment process;
when the flaw detection grade is 1 grade, the following forging process is adopted:
step (11): adding the steel ingot blank into a heating furnace, heating to 1250-1280 ℃, and drawing to a length which is 1.9-2.1 times of the equivalent diameter of the section;
step (12): putting the upset steel ingot blank into a heating furnace again, heating to 1250-1280 ℃, transferring to a free forging hammer for forging with the upsetting ratio of 1.7-1.9;
step (13): entering a heat treatment process;
when the flaw detection grade is 2 grade, the following forging process is adopted:
step (21): adding the steel ingot blank into a heating furnace, heating to 1280-1320 ℃, and drawing to a length which is 2.0-2.2 times of the equivalent diameter of the section;
step (22): putting the upset ingot blank into a heating furnace again, heating to 1280-1320 ℃, transferring to a free forging hammer for forging with the upsetting ratio of 1.9-2.0;
step (23): repeating steps (21) and (22) once;
step (24): entering a heat treatment process;
when the flaw detection grade is 3 grades, the following forging process is adopted:
step (31): adding the steel ingot blank into a heating furnace, heating to 1320-1350 ℃, and drawing to a length 2.0-2.2 times of the equivalent diameter of the section;
step (32): putting the upset steel ingot blank into a heating furnace again, heating to 1280-1350 ℃, transferring to a free forging hammer for forging with the upsetting ratio of 1.9-2.0;
step (33): repeating steps (31) and (32) once;
step (34): entering a heat treatment process;
and when the flaw detection grade is 4 grade, judging that the steel ingot is a defective product and cannot be used for forging the elbow forging of the deep-sea oil extraction equipment.
The invention has the beneficial effects that:
the method comprises the steps of firstly carrying out nondestructive ultrasonic detection on a steel ingot blank, judging the defect grade inside the steel ingot, drawing a corresponding defect map, then calculating the integral defect grade of the steel ingot, and selecting a corresponding process according to the grade and the ratio of the length to the diameter equivalent of the steel ingot after the grade is confirmed, so that the energy consumption of forging is reduced to the maximum extent, and the quality of a forging is ensured.
Drawings
FIG. 1 is a distribution diagram showing the size of a flaw detected in the longitudinal direction of an embodiment 1 of the present invention,
FIG. 2 is a distribution diagram of flaw detection defect levels in the longitudinal direction of inventive example 1.
Detailed Description
The technical solution and the achievement of the present invention will now be further described with reference to the specific embodiments.
Example 1:
a specific application of the invention will be described below by taking a round steel ingot with a continuous casting billet material AISI4130, a diameter of 600mm and a length of 6000mm as an example. When ultrasonic nondestructive inspection is used, inspection is performed once every 10cm from the head to the stomach. The flaw detection sensitivity adopts a test block DAC method, the bottom wave is adjusted to a proper height, 18dB is increased to be used as the flaw detection sensitivity, and the flaw detection equivalent result and the flaw detection grade are divided as shown in Table 1.
Table 1: flaw detection size and classification
| Distance (cm) | ≤10 | 20 | 30 | 40 | 50 | 60 | 70 | 80 | 90 | 100 | 110 | 120 | 130 | 140 | 150 |
| Equivalent (dB) | -18 | -12 | -10 | -18 | -17 | -9.5 | -15 | -11 | -10 | -15 | -14 | -14 | -14 | -21 | -17 |
| Grade | 0 | 4 | 4 | 0 | 0 | 2 | 0 | 2 | 4 | 2 | 0 | 0 | 1 | 0 | 0 |
| Distance (cm) | 160 | 170 | 180 | 190 | 200 | 210 | 220 | 230 | 240 | 250 | 260 | 270 | 280 | 290 | 300 |
| Equivalent (dB) | -11 | -19 | -19 | -13 | -16 | -18 | -12 | -13 | -11 | -18 | -12 | -13 | -12 | -15 | -12 |
| Grade | 2 | 0 | 2 | 2 | 2 | 0 | 1 | 2 | 1 | 0 | 2 | 1 | 2 | 0 | 1 |
| Distance (cm) | 310 | 320 | 330 | 340 | 350 | 360 | 370 | 380 | 390 | 400 | 410 | 420 | 430 | 440 | 450 |
| Equivalent (dB) | -10 | -15 | -16 | -15 | -20 | -26 | -17 | -12 | -17 | -14 | -16 | -20 | -15 | -21 | -20 |
| Grade | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 2 | 0 | 2 | 2 | 0 |
| Distance (cm) | 460 | 470 | 480 | 490 | 500 | 510 | 520 | 530 | 540 | 550 | 560 | 570 | 580 | 590 | 600 |
| Equivalent (dB) | -20 | -21 | -17 | -22 | -12 | -25 | -15 | -20 | -12 | -11 | -20 | -17 | -21 | -23 | -17 |
| Grade | 0 | 2 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2 | 1 | 0 | 0 | 0 | 0 |
The data in table 1 are combined with the size and classification of nondestructive inspection to make figures 1 and 2, and as can be seen from the attached figures, for a continuous casting billet, the equivalent size of the flaw detection defect is changed from the head to the tail, the flaw detection grade is also changed, so that the integral flaw grade of the continuous casting billet needs to be calculated, the integral billet flaw grade of the billet needs to be calculated, and then the corresponding forging process is selected according to the flaw grade.
Firstly, when the number of defect grades reaching 4 grades exceeds 30%, judging that the defect grade is 4 grades;
when the number of the defect grades reaching 4 grades is not more than 30 percent, and the number of the defect grades exceeding 3 grades is more than 30 percent, judging the defect grade to be 3 grade;
when the number of the defect grades exceeding 3 grades does not exceed 30 percent, calculating the defect grade of the steel ingot according to a calculation formula, wherein the calculation formula is as follows: and (3) the integral flaw detection grade of the steel ingot is the sum of flaw detection defect grades/steel ingot length/100, wherein the unit of the steel ingot length is mm.
After the defect grade of the continuous casting billet is confirmed, selecting a forging process according to the shape of the continuous casting billet:
when the ratio of the length to the diameter of the steel ingot forging is 2.2-3.5, the step 3 specifically comprises the following steps:
when the flaw detection grade is 0 grade, the following forging process is adopted:
step (01): adding the steel ingot blank into a heating furnace, heating to 1200 ℃, transferring the steel ingot blank to a free forging hammer, and forging, wherein the upsetting ratio is 1.5 +/-0.1;
step (02): putting the upset ingot blank into the heating furnace again, heating to 1200 ℃, and drawing to a length which is 1.7 +/-0.2 times of the equivalent diameter of the section;
step (03): entering a heat treatment process;
when the flaw detection grade is 1 grade, the following forging process is adopted:
step (11): adding the steel ingot blank into a heating furnace, heating to 1250-1280 ℃, transferring to a free forging hammer, and forging, wherein the upsetting ratio is 1.7-1.9;
step (12): putting the upset steel ingot blank into a heating furnace again, heating to 1250-1280 ℃, and drawing to a length which is 1.9-2.1 times of the equivalent diameter of the section;
step (13): entering a heat treatment process;
when the flaw detection grade is 2 grade, the following forging process is adopted:
step (21): adding the steel ingot blank into a heating furnace, heating to 1280-1320 ℃, transferring to a free forging hammer, and forging, wherein the upsetting ratio is 1.9-2.0;
step (22): putting the upset steel ingot blank into a heating furnace again, heating to 1280-1320 ℃, and drawing to a length which is 2.0-2.2 times of the equivalent diameter of the section;
step (23): repeating steps (21) and (22) once;
step (24): entering a heat treatment process;
when the flaw detection grade is 3 grades, the following forging process is adopted:
step (31): adding the steel ingot blank into a heating furnace, heating to 1320-1350 ℃, transferring to a free forging hammer, and forging, wherein the upsetting ratio is 1.9-2.0;
step (32): putting the upset steel ingot blank into a heating furnace again, heating to 1280-1350 ℃, and drawing to a length which is 2.0-2.2 times of the equivalent diameter of the section;
step (33): repeating steps (31) and (32) once;
step (34): entering a heat treatment process;
and when the flaw detection grade is 4 grade, judging that the steel ingot is a defective product and cannot be used for forging the elbow forging of the deep-sea oil extraction equipment.
Further, when the ratio of the length to the diameter of the steel ingot forging is less than 2.2, the step 3 specifically comprises the following steps:
when the flaw detection grade is 0 grade, the following forging process is adopted:
step (01): adding the steel ingot blank into a heating furnace, heating to 1200 ℃, and drawing to a length which is 1.7 +/-0.2 times of the equivalent diameter of the section;
step (02): putting the steel ingot blank after upsetting into the heating furnace again, heating to 1200 ℃, transferring to a free forging hammer for forging, wherein the upsetting ratio is 1.5 +/-0.1;
step (03): entering a heat treatment process;
when the flaw detection grade is 1 grade, the following forging process is adopted:
step (11): adding the steel ingot blank into a heating furnace, heating to 1250-1280 ℃, and drawing to a length which is 1.9-2.1 times of the equivalent diameter of the section;
step (12): putting the upset steel ingot blank into a heating furnace again, heating to 1250-1280 ℃, transferring to a free forging hammer for forging with the upsetting ratio of 1.7-1.9;
step (13): entering a heat treatment process;
when the flaw detection grade is 2 grade, the following forging process is adopted:
step (21): adding the steel ingot blank into a heating furnace, heating to 1280-1320 ℃, and drawing to a length which is 2.0-2.2 times of the equivalent diameter of the section;
step (22): putting the upset ingot blank into a heating furnace again, heating to 1280-1320 ℃, transferring to a free forging hammer for forging with the upsetting ratio of 1.9-2.0;
step (23): repeating steps (21) and (22) once;
step (24): entering a heat treatment process;
when the flaw detection grade is 3 grades, the following forging process is adopted:
step (31): adding the steel ingot blank into a heating furnace, heating to 1320-1350 ℃, and drawing to a length 2.0-2.2 times of the equivalent diameter of the section;
step (32): putting the upset steel ingot blank into a heating furnace again, heating to 1280-1350 ℃, transferring to a free forging hammer for forging with the upsetting ratio of 1.9-2.0;
step (33): repeating steps (31) and (32) once;
step (34): entering a heat treatment process;
and when the flaw detection grade is 4 grade, judging that the steel ingot is a defective product and cannot be used for forging the elbow forging of the deep-sea oil extraction equipment.
The method can obtain an accurate steel ingot blank manufacturing process, correctly guide production, and avoid material waste and property loss caused by the scrapping of forgings due to the defects of raw materials (steel ingot blanks) or the problems of a forging process.
In light of the foregoing description of the preferred embodiment of the present invention, many modifications and variations will be apparent to those skilled in the art without departing from the spirit and scope of the invention. The technical scope of the present invention is not limited to the content of the specification, and must be determined according to the scope of the claims.
Claims (7)
1. A forging process selection method for guiding a deep-sea oil extraction equipment elbow forge piece based on steel ingot internal defects in a grading manner is characterized by comprising the following steps of: the method comprises the following steps:
step 1: detecting internal defects of the steel ingot: selecting a steel ingot, wherein the ratio of the length of the steel ingot to the equivalent diameter is less than 2.5-3, standing the steel ingot, and detecting the other end of the steel ingot from one end in the length direction by using an ultrasonic detector to obtain the waveform of ultrasonic flaw detection;
step 2: grading the detection result: flaw detection is divided into 5 grades according to flaw detection waveforms, and the steps are as follows:
when the flaw detection waveform is in a reduced grass shape, the steel ingot has no obvious defects, the crystal grains are in a coarse shape, the named flaw detection grade is 0 grade,
when flaw detection waveform is center porosity, dispersed tiny holes are formed in the center of the steel ingot, the named flaw detection grade is grade 1,
when the flaw detection waveform is center porosity and shrinkage, the center of the steel ingot is provided with dispersed tiny holes and small concentrated holes, the named flaw detection grade is grade 2,
when the flaw detection waveform is central shrinkage and loosening, the steel ingot has concentrated holes and a small amount of dispersed fine holes, the named flaw detection grade is 3 grade,
when the flaw detection waveform is a central shrinkage cavity, a large centralized hole is formed in the center of the steel ingot, and the named flaw detection grade is 4 grade;
and step 3: selecting a forging process according to flaw detection classification: with the increase of the flaw detection grade, the forging temperature is increased, the forging ratio is increased, the forging speed is increased, and the forging times are increased.
2. The method for selecting the forging process of the elbow forging of the deep-sea oil extraction equipment based on the grading guidance of the internal defects of the steel ingot according to claim 1, which is characterized by comprising the following steps of: the step 1 is to perform pretreatment on the blank before ultrasonic flaw detection, and the pretreatment specifically comprises the following steps:
and when the roughness of the detected surface of the blank is more than 30 micrometers, polishing the detected surface until the roughness is 10-30 micrometers, and when the visible brightness of the detected surface of the blank is less than 50%, polishing the detected surface until the visible brightness is more than 50%.
3. The method for selecting the forging process of the elbow forging of the deep-sea oil extraction equipment based on the grading guidance of the internal defects of the steel ingot according to claim 2, is characterized in that: the method for polishing the surface of the blank comprises the following steps: polishing in a 0 degree, 45 degree, 90 degree or 0 degree, 120 degree and 240 degree interval mode, wherein the polishing width is not less than 100mm, polishing along the length direction of the blank steel ingot, and polishing from one end to the other end of the length direction to form longitudinal poker, wherein at least 3 poker are formed, and the number of the poker is sequentially marked.
4. The method for selecting the forging process of the elbow forging of the deep-sea oil extraction equipment based on the grading guidance of the internal defects of the steel ingot according to claim 3, wherein the method comprises the following steps: and (3) sequentially taking 100mmX100mm areas along the longitudinal steel bars to perform flaw detection measurement respectively to obtain flaw detection grades of each section, tabulating according to flaw detection measurement results and positions of the flaw detection measurement results to obtain the size and grade of flaw detection defects of the blank steel ingot at each position in the length direction of the blank steel ingot, drawing a distribution diagram of the size of the flaw detection defects in the length direction of the steel ingot blank and a distribution diagram of the grade of the flaw detection defects in the length direction of the blank steel ingot according to tabulated data, and calculating the integral flaw detection grade of the steel ingot according to the distribution diagram of the size of the flaw detection defects in the length direction of the steel ingot blank and the distribution diagram of the.
5. The method for selecting the forging process of the elbow forging of the deep-sea oil extraction equipment based on the grading guidance of the internal defects of the steel ingot according to claim 1, which is characterized by comprising the following steps of: judging the defect grade to be 4 grade when the number of the defect grades reaching 4 grade exceeds 30 percent;
when the number of the defect grades reaching 4 grades is not more than 30 percent, and the number of the defect grades exceeding 3 grades is more than 30 percent, judging the defect grade to be 3 grade;
when the number of the defect grades exceeding 3 grades does not exceed 30 percent, calculating the defect grade of the steel ingot according to a calculation formula, wherein the calculation formula is as follows: and (3) the integral flaw detection grade of the steel ingot is the sum of flaw detection defect grades/steel ingot length/100, wherein the unit of the steel ingot length is mm.
6. The method for selecting the forging process of the elbow forging of the deep-sea oil extraction equipment based on the grading guidance of the internal defects of the steel ingot according to claim 1, which is characterized by comprising the following steps of: when the ratio of the length to the diameter of the steel ingot forging is 2.2-3.5, the step 3 specifically comprises the following steps:
when the flaw detection grade is 0 grade, the following forging process is adopted:
step (01): adding the steel ingot blank into a heating furnace, heating to 1200 ℃, transferring the steel ingot blank to a free forging hammer, and forging, wherein the upsetting ratio is 1.5 +/-0.1;
step (02): putting the upset ingot blank into the heating furnace again, heating to 1200 ℃, and drawing to a length which is 1.7 +/-0.2 times of the equivalent diameter of the section;
step (03): entering a heat treatment process;
when the flaw detection grade is 1 grade, the following forging process is adopted:
step (11): adding the steel ingot blank into a heating furnace, heating to 1250-1280 ℃, transferring to a free forging hammer, and forging, wherein the upsetting ratio is 1.7-1.9;
step (12): putting the upset steel ingot blank into a heating furnace again, heating to 1250-1280 ℃, and drawing to a length which is 1.9-2.1 times of the equivalent diameter of the section;
step (13): entering a heat treatment process;
when the flaw detection grade is 2 grade, the following forging process is adopted:
step (21): adding the steel ingot blank into a heating furnace, heating to 1280-1320 ℃, transferring to a free forging hammer, and forging, wherein the upsetting ratio is 1.9-2.0;
step (22): putting the upset steel ingot blank into a heating furnace again, heating to 1280-1320 ℃, and drawing to a length which is 2.0-2.2 times of the equivalent diameter of the section;
step (23): repeating steps (21) and (22) once;
step (24): entering a heat treatment process;
when the flaw detection grade is 3 grades, the following forging process is adopted:
step (31): adding the steel ingot blank into a heating furnace, heating to 1320-1350 ℃, transferring to a free forging hammer, and forging, wherein the upsetting ratio is 1.9-2.0;
step (32): putting the upset steel ingot blank into a heating furnace again, heating to 1280-1350 ℃, and drawing to a length which is 2.0-2.2 times of the equivalent diameter of the section;
step (33): repeating steps (31) and (32) once;
step (34): entering a heat treatment process;
and when the flaw detection grade is 4 grade, judging that the steel ingot is a defective product and cannot be used for forging the elbow forging of the deep-sea oil extraction equipment.
7. The method for selecting the forging process of the elbow forging of the deep-sea oil extraction equipment based on the grading guidance of the internal defects of the steel ingot according to claim 1, which is characterized by comprising the following steps of: when the ratio of the length to the diameter of the steel ingot forging is less than 2.2, the step 3 specifically comprises the following steps:
when the flaw detection grade is 0 grade, the following forging process is adopted:
step (01): adding the steel ingot blank into a heating furnace, heating to 1200 ℃, and drawing to a length which is 1.7 +/-0.2 times of the equivalent diameter of the section;
step (02): putting the steel ingot blank after upsetting into the heating furnace again, heating to 1200 ℃, transferring to a free forging hammer for forging, wherein the upsetting ratio is 1.5 +/-0.1;
step (03): entering a heat treatment process;
when the flaw detection grade is 1 grade, the following forging process is adopted:
step (11): adding the steel ingot blank into a heating furnace, heating to 1250-1280 ℃, and drawing to a length which is 1.9-2.1 times of the equivalent diameter of the section;
step (12): putting the upset steel ingot blank into a heating furnace again, heating to 1250-1280 ℃, transferring to a free forging hammer for forging with the upsetting ratio of 1.7-1.9;
step (13): entering a heat treatment process;
when the flaw detection grade is 2 grade, the following forging process is adopted:
step (21): adding the steel ingot blank into a heating furnace, heating to 1280-1320 ℃, and drawing to a length which is 2.0-2.2 times of the equivalent diameter of the section;
step (22): putting the upset ingot blank into a heating furnace again, heating to 1280-1320 ℃, transferring to a free forging hammer for forging with the upsetting ratio of 1.9-2.0;
step (23): repeating steps (21) and (22) once;
step (24): entering a heat treatment process;
when the flaw detection grade is 3 grades, the following forging process is adopted:
step (31): adding the steel ingot blank into a heating furnace, heating to 1320-1350 ℃, and drawing to a length 2.0-2.2 times of the equivalent diameter of the section;
step (32): putting the upset steel ingot blank into a heating furnace again, heating to 1280-1350 ℃, transferring to a free forging hammer for forging with the upsetting ratio of 1.9-2.0;
step (33): repeating steps (31) and (32) once;
step (34): entering a heat treatment process;
and when the flaw detection grade is 4 grade, judging that the steel ingot is a defective product and cannot be used for forging the elbow forging of the deep-sea oil extraction equipment.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115319014A (en) * | 2022-08-10 | 2022-11-11 | 成都成德重型锻造有限公司 | Forging quality control method of ratchet disc for nuclear island |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101920304A (en) * | 2010-06-30 | 2010-12-22 | 华南理工大学 | Method for forging large steel shaft forging |
| CN102319845A (en) * | 2011-06-16 | 2012-01-18 | 南京迪威尔重型锻造股份有限公司 | Manufacturing process of forging stock of steel forging piece for oil extraction equipment in deep sea |
| CN104251881A (en) * | 2014-08-29 | 2014-12-31 | 内蒙古北方重工业集团有限公司 | Classification and assessment method of ultrasonic detection defects of extrusion formed thick-walled seamless steel pipe |
| CN104624900A (en) * | 2015-02-11 | 2015-05-20 | 中国科学院金属研究所 | Forging method for efficiently recovering internal defects of thin plate forged pieces |
| CN104807884A (en) * | 2015-04-30 | 2015-07-29 | 南京迪威尔高端制造股份有限公司 | Ultrasonic flaw detection grading method for internal defects of steel ingot |
| US9798884B1 (en) * | 2016-10-11 | 2017-10-24 | Veracode, Inc. | Systems and methods for identifying insider threats in code |
-
2019
- 2019-12-31 CN CN201911406417.7A patent/CN111054865A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101920304A (en) * | 2010-06-30 | 2010-12-22 | 华南理工大学 | Method for forging large steel shaft forging |
| CN102319845A (en) * | 2011-06-16 | 2012-01-18 | 南京迪威尔重型锻造股份有限公司 | Manufacturing process of forging stock of steel forging piece for oil extraction equipment in deep sea |
| CN104251881A (en) * | 2014-08-29 | 2014-12-31 | 内蒙古北方重工业集团有限公司 | Classification and assessment method of ultrasonic detection defects of extrusion formed thick-walled seamless steel pipe |
| CN104624900A (en) * | 2015-02-11 | 2015-05-20 | 中国科学院金属研究所 | Forging method for efficiently recovering internal defects of thin plate forged pieces |
| CN104807884A (en) * | 2015-04-30 | 2015-07-29 | 南京迪威尔高端制造股份有限公司 | Ultrasonic flaw detection grading method for internal defects of steel ingot |
| US9798884B1 (en) * | 2016-10-11 | 2017-10-24 | Veracode, Inc. | Systems and methods for identifying insider threats in code |
Non-Patent Citations (1)
| Title |
|---|
| 陈昌华等: "钢锭超声波探伤质量分级与探讨", 《物理测试》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115319014A (en) * | 2022-08-10 | 2022-11-11 | 成都成德重型锻造有限公司 | Forging quality control method of ratchet disc for nuclear island |
| CN115319014B (en) * | 2022-08-10 | 2024-04-02 | 成都成德重型锻造有限公司 | Forging quality control method of ratchet disc for nuclear island |
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