喷射成形多喷嘴扫描沉积界面行为模型与智能调控方法

doi:10.12141/j.issn.1000-565X.250059

摘要/Abstract

摘要：

轻质高性能铝合金材料对航空航天装备轻量化具有重要意义，由此喷射成形快速凝固技术在高强铝合金制备方面的应用受到了越来越多的关注。为满足航空航天大尺寸构件的研制需求，需要采用多喷嘴协同工作方式以获得更大的锭坯直径。多个喷嘴形成了多个雾化锥，以一定的倾角在沉积界面进行扫描。在此过程中，确保熔体物质分布均匀，以及锭坯顶部沉积界面平整且稳定生长，是获得高质量、组织致密均匀的沉积坯的关键。沉积过程中多喷嘴的相关工艺参数直接影响雾化熔滴在界面上的扫描轨迹与物质沉积状态，对锭坯生长起到决定性作用。因此，以形成形貌一致、沉积质量均匀的大规格锭坯为目标，基于微尺度扫描沉积高度，考虑多喷嘴雾化锥扫描过程中出现沉积区域交叉重叠的问题，建立多喷嘴沉积界面行为模型（DSBM模型）。选择喷嘴初始倾角、喷嘴偏心距、熔体质量流率为可调整参数，根据实际工况建立约束，形成基于DSBM的参数调控方法。以锭坯沉积面不平整度的高度差H为优化目标，利用沉积界面GA-DSBM智能调控方法对沉积过程中的相关工艺参数进行仿真计算与优化。通过4喷嘴喷射成形试验对寻优得到的工艺参数进行了验证，试验所得到的直径600 mm锭坯的表面不平整高度差为7.52 mm，符合工艺设计要求，同时锭坯顶部不平整度大大降低，沉积界面物质均匀性得到改善，有效降低了锭坯孔隙率。试验过程验证了智能调控与优化方法的可行性。

关键词: 喷射成形, 多喷嘴, 沉积界面, 沉积均匀

Abstract:

Lightweight and high-performance aluminum alloys are crucial for the weight reduction design of aerospace equipment, thus spray forming with rapid solidification technology has garnered increasing attention for the fabrication of high-strength aluminum alloys. To meet the demands of large-scale aerospace components, a multi-nozzle collaborative system is required to achieve larger billet diameters. During the scanning and deposition process of atomization cones formed by multiple nozzles at a certain inclination angle on the deposition interface, ensuring uniform distribution of the molten material, a flat deposition interface at the top of the billet, and stable growth are key to obtaining high-quality, dense, and uniform deposited billet structures. These factors are key to producing high-quality billets with dense and uniform microstructures. The process parameters associated with multi-nozzle configurations directly influence the scanning trajectories of atomized droplets and the material deposition state at the interface, playing a decisive role in billet growth. Accordingly, by targeting the fabrication of large-size billets with consistent surface morphology and uniform deposition quality, a multi-nozzle deposition surface behavior model (DSBM) at the micro-scale was established based on the scanned deposition height, taking into account the overlap and intersection of deposition regions that arise during scanning of the multi-nozzle atomization cones. The initial nozzle tilt angle, nozzle eccentric offset, and melt mass flow rate were selected as adjustable parameters; constraints were set according to the actual operating conditions to construct a DSBM-based control model. Using the height difference H of the billet’s deposition-surface unevenness as the optimization objective, the GA-DSBM intelligent control method for the deposition interface was employed to simulate and optimize the relevant process para-meters during deposition. A four-nozzle spray-forming experiment was conducted to verify the optimized parameters. The resulting billet, with a diameter of 600 mm, exhibited a surface unevenness height difference of 7.52 mm, meeting the process design requirements. Meanwhile, the top-surface unevenness of the billet was markedly reduced, interfacial material uniformity was improved, and the billet porosity was effectively lowered—thereby validating the feasibility of the proposed intelligent control and optimization method.

Key words: spray forming, multi-nozzle, deposition surface, uniform deposition

中图分类号:

TF821

冷晟, 黄海泽, 蒋增华, 鹿华锐, 马万太. 喷射成形多喷嘴扫描沉积界面行为模型与智能调控方法[J]. 华南理工大学学报(自然科学版), 2026, 54(1): 124-133.

LENG Sheng, HUANG Haize, JIANG Zenghua, LU Huarui, MA Wantai. DSBM of Multi-Nozzle Scanning for Spray Forming and Its Intelligent Optimization Approach[J]. Journal of South China University of Technology(Natural Science Edition), 2026, 54(1): 124-133.

图/表 14

图1

图2

图3

图4

图5

图6

表1

已确定的工艺参数"

喷嘴	$β / (°)$	$v 0 / (m m ∙ s - 1)$	$ω$ $/ (r a d ∙ s - 1)$	$f / H z$	$h 0$ $/ m m$
P₁	3	0.4	$83$ π	6	600
P₂	3	0.4	$83$ π	6	600
P₃	3	0.4	$83$ π	6	600
P₄	3	0.4	$83$ π	6	600

表1

表2

参数寻优前DSBM模型的调控参数"

喷嘴	$e i / m m$	$α i / (°)$	$ψ i / (k g ∙ m i n - 1)$
P₁	179.54	12.18	4.050
P₂	239.90	8.91	8.670
P₃	303.19	10.57	9.037
P₄	365.89	11.61	11.611

表2

表3

参数寻优后DSBM模型的调控参数"

喷嘴	$e i / m m$	$α i / (°)$	$ψ i / (k g ∙ m i n - 1)$
P₁	200.00	15.04	4.10
P₂	290.00	13.41	10.34
P₃	368.00	11.71	11.53
P₄	400.00	11.57	12.90

表3

图7

图8

图9

图10

图11

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