Optimization system of laser tailor-welded blank technology based on property prediction and method
A technology for performance prediction and process optimization, applied in laser welding equipment, welding equipment, manufacturing tools, etc., to achieve the effect of friendly interface, easy debugging and process improvement
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Embodiment 1
[0043] Taking 1.5mm St12 sheet / galvanized sheet tailor-welded blank as an example, the welding process adopts single-sided welding and double-sided forming. The welding process parameters are: power P=1525~1850W, welding speed 1.6~2.0m / min, spot diameter Φ0. 3mm to 1mm, the absorption rate is 0.7, and the focal length of the welding lens is 127mm.
[0044] Using MATLAB software to map the existing welding process parameters and mechanical properties j=0, 1,...k, i=1, 2) to perform PLS calculation, the algorithm steps are as follows.
[0045] Step 1: Relevant process data of weldment samples (≥9), as shown in Table 1.
[0046] Table 1 Relevant process data of weldment samples
[0047]
[0048] Step 2: Investigate the issue of multiple correlations between input variables. It can be seen from Table 2 that the multiple correlations between input variables are obvious.
[0049] Table 2 Correlation coefficient matrix between input variables and output variables in weld are...
Embodiment 2
[0081] Taking 0.8mm St12 plate / 1.5mm galvanized sheet tailor-welded blank as an example, the welding process is the same as that of Example 1, and the modeling and optimization process and steps are the same as Example 1
[0082] Step 1: Relevant process data of weldment samples (≥9), as shown in Table 7.
[0083] Table 7 Relevant process data of weldment samples
[0084]
[0085] After steps 2 to 4 described in Example 2, a PLS prediction model group of mechanical properties is obtained, as shown below.
[0086] Yield strength y 1 for:
[0087] the y 1 =-0.0471x 1 +39.1667x 2 -21.4414x 3 +202.0455
[0088] Tensile strength y 2 for:
[0089] the y 2 =-0.0472x 1 +38.3333x 2 -23.8288x 3 +359.7018
[0090] Elongation y 3 for:
[0091] the y 3 =0.0103x 1 -6.6667x 2 +4.2793x 3+16.6625
[0092] Step 5: Prediction accuracy inspection and control
[0093] Import the process data of the pre-processing module into the mechanical property prediction module to pre...
Embodiment 3
[0101] Taking 1.5mm high-strength galvanized steel DOGAL800DP / super-drawn steel BUSD tailor-welded blank as an example, the welding process adopts single-sided welding and double-sided forming. The welding process parameters are: laser power 900-1400W, welding speed 1-2m / min, the spot diameter is 0.3-1.0mm, the absorption rate is 0.7, and the focal length of the welding lens is 127mm. Its modeling and optimization process and steps are the same as those in Example 1.
[0102] Step 1: Call a group (≥9) of relevant process data randomly, as shown in Table 9.
[0103] Table 9 Relevant process data of weldment samples
[0104]
[0105] After steps 2 to 4 described in Example 1, a PLS prediction model group of mechanical properties is obtained, as shown below.
[0106] Tailored welded blank yield strength y 1 for:
[0107] the y 1 =-0.0187x 1 +9.0000x 2 -13.8739x 3 +250.9757
[0108] Tailored welded blank tensile strength y 2 for:
[0109] the y 2 =-0.0193x 1 +10.3...
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