High-end automobile sheet product casting blank quality judgment method

Abstract

The invention relates to a high-end automobile sheet product casting blank quality judgment method, and belongs to the technical field of ferrous metallurgy continuous casting production methods. According to the technical scheme, liquid level fluctuation judgment, heat flow ratio judgment, constant pulling speed judgment and secondary cooling water judgment are carried out, and grade subdivision is carried out; and based on the weight difference of different quality indexes of the high-strength automobile sheet, setting the weight of each dimension, calculating a comprehensive score, and mapping the comprehensive score into a final quality grade. The method has the beneficial effects that through a three-layer framework of'single-dimensional accurate judgment-multi-dimensional weight collaboration-comprehensive grade mapping ', accurate control over the quality of the high-strength automobile sheet casting blank is achieved, and four core dimensions of liquid level fluctuation, a heat flow ratio and secondary cooling water are covered; a refined grading standard is established to adapt to the quality requirements of different parts of the high-strength automobile sheet; and multi-dimensional collaborative judgment logic is constructed, so that misjudgment of a single index is avoided, and the judgment accuracy is improved.

Description

Technical Field

[0001] This invention relates to a method for judging the quality of high-end automotive steel sheet castings, belonging to the technical field of continuous casting production methods in iron and steel metallurgy. Background Technology

[0002] High-strength automotive steel sheets (such as Q&P980, DP1180, and TRIP steel) are widely used in automotive body safety components (A-pillars, B-pillars, anti-collision beams) and structural components (door inner panels, chassis crossbeams). They have stringent requirements for mechanical properties (tensile strength ≥980MPa, elongation after fracture ≥15%), surface quality (no inclusions, no cracks), and compositional uniformity (elemental segregation ≤0.05%). The quality of the cast billet, as the "raw material" for high-strength automotive steel sheets, directly determines the pass rate of subsequent rolled products. If the cast billet has issues such as slag entrapment due to liquid level fluctuations, internal cracks due to uneven heat flow ratios, compositional segregation due to casting speed fluctuations, or uneven cooling due to secondary cooling water deviations, the rolled automotive steel sheets will experience cracking and substandard performance, increasing the rework rate by more than 30% and severely impacting production efficiency.

[0003] Existing billet quality assessment technologies have three major flaws:

[0004] 1. Limitations of single-dimensional judgment: It only focuses on single indicators such as surface cracks and composition, ignoring key hidden factors such as liquid level fluctuation and heat flow ratio (e.g., liquid level fluctuation > ±5mm is prone to slag entrapment and is not included in the grading judgment).

[0005] 2. Coarse grading standards: Mostly adopting a binary judgment of "qualified / unqualified", which cannot match the differentiated requirements of different components of high-strength automotive steel sheets (e.g., safety components require higher surface quality, and structural components require higher internal uniformity).

[0006] 3. Lack of coordinated judgment logic: Each indicator is judged separately (e.g., liquid level fluctuation is grade A, heat flow ratio is grade C), lacking comprehensive weight allocation, which easily leads to misjudgment of "single indicator is qualified but overall quality is not up to standard", resulting in subsequent rolling risks.

[0007] Therefore, there is an urgent need for a billet quality assessment technology that covers all dimensions of "surface-internal-composition-cooling", is graded and refined, and has collaborative judgment, in order to meet the stringent quality requirements of high-strength automotive steel sheets. Summary of the Invention

[0008] The purpose of this invention is to provide a method for judging the quality of high-strength automotive steel sheet castings. Through a three-layer architecture of "single-dimensional precise judgment - multi-dimensional weighted coordination - comprehensive grade mapping," it achieves precise control over the quality of high-strength automotive steel sheet castings, covering four core dimensions: liquid level fluctuation, heat flow ratio, and secondary cooling water. It establishes refined grading standards to adapt to the quality requirements of different components of high-strength automotive steel sheets; and it constructs a multi-dimensional collaborative judgment logic to avoid misjudgment based on a single indicator, improving judgment accuracy and effectively solving the aforementioned problems existing in the background technology.

[0009] The technical solution of this invention is: a method for judging the quality of high-end automotive steel sheet castings, comprising the following steps:

[0010] (1) Single-dimensional judgment, liquid surface fluctuation judgment, heat flow ratio judgment, constant pulling speed judgment and secondary cooling water judgment, and further subdivided into levels;

[0011] (2) Multi-dimensional collaborative judgment: Based on the weight differences of different quality indicators of high-strength automotive steel sheets, the weights of each dimension are set, the comprehensive score is calculated, and the final quality level is mapped.

[0012] The specific steps in step (1) are as follows:

[0013] (11) Liquid surface fluctuation determination: The liquid surface fluctuation value of the crystallizer is scanned in real time by computer and classified according to the fluctuation amplitude and cumulative number of times to meet the surface quality requirements of high-strength automotive steel.

[0014] (12) Heat flow ratio determination: Define the heat flow ratio as follows: Narrow left heat flow ratio = 2 × heat flow on the left side of the narrow face / (heat flow inside the wide face + heat flow outside the wide face), Narrow right heat flow ratio = 2 × heat flow on the right side of the narrow face / (heat flow inside the wide face + heat flow outside the wide face); Sampling and grading: Collect measuring points at equal intervals along the length of the billet, calculate the proportion of measuring points in a certain heat flow ratio range, and take the most severe level of narrow left heat flow ratio and narrow right heat flow ratio as the final result;

[0015] (13) Constant casting speed determination and data processing: Extract the actual casting speed series of the whole billet. If there is a value <0.9m / min in the series, it is directly determined that the casting speed is too low and will easily lead to serious segregation; calculate the fluctuation coefficient: calculate the absolute value of the difference between adjacent elements in the series to form a new series; multiply each element in the new series by 2 to amplify the influence of small fluctuations on solidification, sum and divide by the length of the series to obtain the fluctuation coefficient; constant casting speed = (1-fluctuation coefficient)×100, and classify according to the fluctuation coefficient;

[0016] (14) Secondary cooling water determination: Calculate the absolute value of the actual cooling zone water volume and the set water volume to form a series; determine the corresponding level based on the proportion of measuring points within a certain deviation range.

[0017] The specific steps in step (2) are as follows:

[0018] (21) Weighting: Liquid surface fluctuation accounts for 40%, surface quality is directly related to appearance and corrosion resistance; heat flow ratio accounts for 30%, internal quality is related to fatigue performance; constant pulling speed accounts for 20%, composition uniformity is related to mechanical properties; secondary cooling water accounts for 10%, cooling uniformity is related to rolling stability.

[0019] (22) Score mapping, with each dimension level corresponding to a base score: AAA=100, AA=95, A=90, B=80, C=70, D=60 and E=50;

[0020] (23) Calculation of comprehensive score: Comprehensive score = liquid surface fluctuation score × 40% + heat flow ratio score × 30% + constant pulling speed score × 20% + secondary cooling water score × 10%;

[0021] The final mapping level is obtained.

[0022] The beneficial effects of this invention are: through a three-layer architecture of "single-dimensional precise judgment - multi-dimensional weighted coordination - comprehensive grade mapping", it achieves precise control of the quality of high-strength automotive steel billet, covering four core dimensions: liquid level fluctuation, heat flow ratio, and secondary cooling water; it establishes a refined grading standard to adapt to the quality requirements of different components of high-strength automotive steel; and it constructs a multi-dimensional collaborative judgment logic to avoid misjudgment by a single indicator and improve the accuracy of judgment. Detailed Implementation

[0023] To make the purpose, technical solutions, and advantages of the embodiments of the invention clearer, the technical solutions in the embodiments of the invention are described clearly and completely below. Obviously, the embodiments described are only a small part of the embodiments of the invention, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without creative effort are within the protection scope of the invention.

[0024] A method for judging the quality of high-end automotive steel sheet castings includes the following steps:

[0025] (1) Single-dimensional judgment, liquid surface fluctuation judgment, heat flow ratio judgment, constant pulling speed judgment and secondary cooling water judgment, and further subdivided into levels;

[0026] (2) Multi-dimensional collaborative judgment: Based on the weight differences of different quality indicators of high-strength automotive steel sheets, the weights of each dimension are set, the comprehensive score is calculated, and the final quality level is mapped.

[0027] The specific steps in step (1) are as follows:

[0028] (11) Liquid surface fluctuation determination: The liquid surface fluctuation value of the crystallizer is scanned in real time by computer and classified according to the fluctuation amplitude and cumulative number of times to meet the surface quality requirements of high-strength automotive steel.

[0029] (12) Heat flow ratio determination: Define the heat flow ratio as follows: Narrow left heat flow ratio = 2 × heat flow on the left side of the narrow face / (heat flow inside the wide face + heat flow outside the wide face), Narrow right heat flow ratio = 2 × heat flow on the right side of the narrow face / (heat flow inside the wide face + heat flow outside the wide face); Sampling and grading: Collect measuring points at equal intervals along the length of the billet, calculate the proportion of measuring points in a certain heat flow ratio range, and take the most severe level of narrow left heat flow ratio and narrow right heat flow ratio as the final result;

[0030] (13) Constant casting speed determination and data processing: Extract the actual casting speed series of the whole billet. If there is a value <0.9m / min in the series, it is directly determined that the casting speed is too low and will easily lead to serious segregation; calculate the fluctuation coefficient: calculate the absolute value of the difference between adjacent elements in the series to form a new series; multiply each element in the new series by 2 to amplify the influence of small fluctuations on solidification, sum and divide by the length of the series to obtain the fluctuation coefficient; constant casting speed = (1-fluctuation coefficient)×100, and classify according to the fluctuation coefficient;

[0031] (14) Secondary cooling water determination: Calculate the absolute value of the actual cooling zone water volume and the set water volume to form a series; determine the corresponding level based on the proportion of measuring points within a certain deviation range.

[0032] The specific steps in step (2) are as follows:

[0033] (21) Weighting: Liquid surface fluctuation accounts for 40%, surface quality is directly related to appearance and corrosion resistance; heat flow ratio accounts for 30%, internal quality is related to fatigue performance; constant pulling speed accounts for 20%, composition uniformity is related to mechanical properties; secondary cooling water accounts for 10%, cooling uniformity is related to rolling stability.

[0034] (22) Score mapping, with each dimension level corresponding to a base score: AAA=100, AA=95, A=90, B=80, C=70, D=60 and E=50;

[0035] (23) Calculation of comprehensive score: Comprehensive score = liquid surface fluctuation score × 40% + heat flow ratio score × 30% + constant pulling speed score × 20% + secondary cooling water score × 10%;

[0036] The final mapping level is obtained.

[0037] In practical applications, this invention achieves precise quality control of high-strength automotive steel sheet castings through a three-layer architecture of "single-dimensional precise judgment - multi-dimensional weighted coordination - comprehensive level mapping," as detailed below:

[0038] 1. Single-dimensional judgment module (refined grading based on core quality indicators)

[0039] (1) Liquid level fluctuation judgment (controlling the risk of surface slag / inclusion)

[0040] The system employs real-time cyclic scanning of the crystallizer liquid level fluctuation values ​​(sampling frequency 0.5s / time to ensure data continuity), and classifies the fluctuation amplitude and cumulative number of times to meet the surface quality requirements of high-strength automotive steel sheets.

[0041] (11) Decision logic:

[0042] Peak determination: When the absolute value of the actual liquid level reaches +5mm, +10mm, +15mm, or +20mm, the determination is initiated until the actual value falls below the corresponding threshold value, and one corresponding level peak is accumulated.

[0043] Valley determination: When the absolute value of the actual liquid level reaches -5mm, -10mm, -15mm, or -20mm, the determination is initiated until the actual value is higher than the corresponding threshold value, and one valley of the corresponding level is accumulated.

[0044] (12) Grading criteria:

[0045]

[0046]

[0047] (2) Heat flow ratio determination (controlling internal solidification uniformity / crack risk)

[0048] The heat flow ratio reflects the cooling uniformity of the narrow and wide faces of the cast billet, directly affecting the internal stress distribution (uneven heat flow ratio easily leads to internal cracks). The determination steps are as follows:

[0049] (21) Definition of heat flow ratio:

[0050] Narrow left heat flux ratio = 2 × Narrow left side heat flux / (Wide inner heat flux + Wide outer heat flux);

[0051] Narrow right heat flux ratio = 2 × Narrow right side heat flux / (Wide inner heat flux + Wide outer heat flux);

[0052] (22) Sampling and grading: Collect 60 measuring points at equal intervals along the length of the billet (ensuring full coverage of the crystallizer length), calculate the percentage of measuring points within a certain heat flow ratio range (a percentage > 10% is considered the corresponding grade), and take the most severe grade of narrow left and narrow right heat flow ratios as the final result:

[0053]

[0054]

[0055] (3) Constant pulling speed determination (controlling the risk of component segregation)

[0056] Fluctuations in casting speed can cause changes in the solidification rate of the billet, leading to elemental segregation (such as C and Mn segregation), which affects the mechanical properties of automotive steel sheets. The determination steps are as follows:

[0057] (31) Data processing: Extract the actual casting speed series of the whole billet (sampling frequency 1s / time). If there is a value <0.9m / min in the series, it is directly judged as Grade E (too low casting speed can easily lead to serious segregation).

[0058] (32) Calculation of volatility coefficient:

[0059] ① Calculate the absolute value of the difference between adjacent elements in a sequence to form a new sequence;

[0060] ② Multiply each element of the new sequence by 2 (to amplify the effect of small fluctuations on solidification), sum them, and divide by the length of the sequence to obtain the fluctuation coefficient;

[0061] ③ Constant pulling rate = (1 - fluctuation coefficient) × 100;

[0062] (33) Grading criteria:

[0063]

[0064]

[0065] (4) Secondary cooling water assessment (controlling cooling uniformity / surface hardness risk)

[0066] Secondary cooling water deviation can lead to uneven cooling of the billet surface, causing fluctuations in surface hardness (deviation > 20 easily leads to rolling thickness deviation). The judgment logic is as follows:

[0067] (41) Data processing: Calculate the absolute value of the actual cooling zone water volume and the set water volume to form a series;

[0068] (42) Grading criteria: Based on the percentage of measuring points within a certain deviation range (a percentage > 10% is considered the corresponding grade):

[0069] grade <![CDATA[Water volume deviation range (m 3 / h)]]> Surface cooling effect Grade A The percentage of projects with no deviation > 10 or with deviation > 10% is ≤ 10%. Uniform cooling and consistent surface hardness Grade B The percentage of deviations [10, 20) is greater than 10%. Slight uneven cooling can be used for non-load-bearing components. Class C The percentage of deviations [20, 30) is greater than 10%. Uneven cooling at moderate temperatures requires adjustment of rolling temperature. Class D The percentage of deviations [30, 40) is greater than 10%. Severe uneven cooling requires rework Class E The percentage of deviations >40 is >10%. Extremely uneven cooling, substandard

[0070] 2. Multi-dimensional collaborative judgment logic

[0071] Based on the weight differences of different quality indicators of high-strength automotive steel sheets (surface quality has the greatest impact, while cooling uniformity has the least impact), weights are set for each dimension, a comprehensive score is calculated, and mapped to the final quality grade:

[0072] (1) Weight allocation:

[0073] Liquid surface fluctuation (40%, surface quality directly affects appearance and corrosion resistance) > heat flow ratio (30%, internal quality affects fatigue performance) > constant pulling speed (20%, composition uniformity affects mechanical properties) > secondary cooling water (10%, cooling uniformity affects rolling stability);

[0074] (2) Score mapping: Base score corresponding to each dimension level (AAA=100, AA=95, A=90, B=80, C=70, D=60, E=50);

[0075] (3) Calculation of overall score:

[0076] Overall score = Liquid surface fluctuation score × 40% + Heat flow ratio score × 30% + Constant pulling speed score × 20% + Secondary cooling water score × 10%;

[0077] (4) Final grade mapping (Table 5, adapted to high-strength automotive steel sheet application scenarios):

[0078]

[0079] Example:

[0080] High-strength Q&P980 billets for automotive steel sheets are produced on-site in the continuous casting process of a steel plant (specifications...).

[0081] Taking a 220mm × 1500mm sample as an example, the application process of this invention is explained:

[0082] 1. Data Collection

[0083] (1) Liquid surface fluctuation: The computer scans once every 0.5 seconds, collecting a total of 1000 data points, and accumulating...

[0084] Three instances of ±5mm peaks / troughs were recorded, classifying it as Grade A (score 90).

[0085] (2) Heat flow ratio: 60 measuring points were collected along the length of the billet. 7 measuring points (11.7%) with a heat flow ratio in the range of [105, 115) on the narrow left side were judged as Grade A (score 90); 8 measuring points (13.3%) with a heat flow ratio in the range of [100, 105) on the narrow right side were judged as Grade B (score 80). The most severe grade, Grade B (score 80), was selected.

[0086] (3) Constant pulling speed: 500 pulling speed data were collected, and there were no values ​​<0.9m / min; the sum of the absolute values ​​of adjacent differences ×2 equals 25, the fluctuation coefficient = 25 / 500 = 0.05, the constant pulling speed = (1-0.05)×100 = 95, which is judged as Grade A (score 90);

[0087] (4) Secondary cooling water: 80 water volume data were collected. 5 measurement points had a deviation of [10, 20) (accounting for 6.25%). There was no higher deviation, so it was judged as Grade A (score 90).

[0088] 2. Comprehensive judgment

[0089] Overall score = 90×40% + 80×30% + 90×20% + 90×10% = 36 + 24 + 18 + 9 = 87 points, corresponding to Level II, suitable for high-strength structural components (inner door panel).

[0090] 3. Subsequent verification

[0091] After the billet enters the rolling process, 10% of the samples are randomly inspected: the surface is free of inclusions, the interior is free of cracks (100% pass rate for flaw detection), the compositional segregation is ≤0.04%, and the mechanical properties meet the standards (tensile strength 1020MPa, elongation after fracture 18%), fully meeting the technical requirements of Q&P980 door inner panel.

[0092] The beneficial effects of this invention are as follows:

[0093] 1. Comprehensive coverage with no quality blind spots: For the first time, four core indicators, namely liquid surface fluctuation, heat flow ratio, constant pulling speed, and secondary cooling water, are integrated to cover the entire quality dimension of "surface-internal-composition-cooling", thus solving the limitations of traditional single-dimensional judgment.

[0094] 2. Refined grading to meet differentiated needs: Liquid level fluctuations are subdivided into AAA grades, and heat flow ratio, constant pulling speed, and other grades correspond to specific risks. This can accurately match the different quality requirements of high-strength automotive steel sheets from safety components to non-load-bearing components, avoiding "excessive quality" or "insufficient quality".

[0095] 3. Collaborative judgment to improve accuracy: By weighting and comprehensive scoring, misjudgment based on a single indicator is avoided (e.g., a billet with a liquid level fluctuation of grade A but a heat flow ratio of grade C is judged as grade III and requires full inspection before rolling), thus improving the judgment accuracy rate to over 98%.

[0096] 4. High degree of automation, cost reduction and efficiency improvement: Based on real-time computer data collection and calculation, no manual intervention is required, the judgment efficiency is improved by 50%, and the rework rate of subsequent rolling is reduced (from 10% to less than 1%), saving more than 10 million yuan in production costs annually.

Claims

1. A method for judging the quality of high-end automotive steel sheet castings, characterized in that... Includes the following steps: (1) Single-dimensional judgment, liquid surface fluctuation judgment, heat flow ratio judgment, constant pulling speed judgment and secondary cooling water judgment, and further subdivided into levels; (2) Multi-dimensional collaborative judgment: Based on the weight differences of different quality indicators of high-strength automotive steel sheets, the weights of each dimension are set, the comprehensive score is calculated, and the final quality level is mapped.

2. The method for judging the quality of high-end automotive steel sheet castings according to claim 1, characterized in that: The specific steps in step (1) are as follows: (11) Liquid surface fluctuation determination: The liquid surface fluctuation value of the crystallizer is scanned in real time by computer and classified according to the fluctuation amplitude and cumulative number of times to meet the surface quality requirements of high-strength automotive steel sheet. (12) Heat flow ratio determination: Define the heat flow ratio as follows: Narrow left heat flow ratio = 2 × Narrow left side heat flow / (Wide inner heat flow + Wide outer heat flow), Narrow right heat flow ratio = 2 × Narrow right side heat flow / (Wide inner heat flow + Wide outer heat flow); Sampling and grading: Collect measuring points at equal intervals along the length of the billet, calculate the proportion of measuring points in a certain heat flow ratio range, and take the most severe level of narrow left heat flow ratio and narrow right heat flow ratio as the final result; (13) Constant casting speed determination and data processing: Extract the actual casting speed series of the whole billet. If there is a value <0.9m / min in the series, it is directly determined that the casting speed is too low and will easily lead to serious segregation. Perform fluctuation coefficient calculation: calculate the absolute value of the difference between adjacent elements of the sequence to form a new sequence; Each element of the new sequence is multiplied by 2 to amplify the effect of small fluctuations on solidification. The summation is divided by the sequence length to obtain the fluctuation coefficient. The constant pulling rate is calculated as (1 - fluctuation coefficient) × 100, and the sequence is graded according to the fluctuation coefficient. (14) Secondary cooling water determination: Calculate the absolute value of the actual cooling zone water volume and the set water volume to form a series; determine the corresponding level based on the proportion of measuring points within a certain deviation range.

3. The method for judging the quality of high-end automotive steel sheet castings according to claim 1, characterized in that: The specific steps in step (2) are as follows: Weighting is as follows: liquid surface fluctuation accounts for 40%, surface quality is directly related to appearance and corrosion resistance; heat flux ratio accounts for 30%, internal quality is related to fatigue performance; constant stretching speed accounts for 20%, composition uniformity is related to mechanical properties; secondary cooling water accounts for 10%, cooling uniformity is related to rolling stability. The scoring mapping is as follows: each dimension level corresponds to a base score, AAA=100, AA=95, A=90, B=80, C=70, D=60, and E=50. The overall score is calculated as follows: Overall Score = Liquid Surface Fluid Fluid Score × 40% + Heat Flow Ratio Score × 30% + Constant Pulling Speed ​​Score × 20% + Secondary Cooling Water Score × 10%; The final mapping level is obtained.

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