废旧航铝材精细分选及高效除杂关键技术数据集
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航空铝合金废料堆放量的不断增加造成了铝资源浪费且带来严重环境压力。由于分选水平及预处理技术的限制，目前仅有部分航空铝合金废料作为低品质的铝废料降级再生铸造铝合金，其原有价值无法得到完全利用，因此亟需开发航空铝合金保级再生技术。本课题通过研发磁-涡电流-光谱-重介质等分选除杂系统集成、低氧动态绿色热脱除水油等技术及装备，建立除杂智能管控系统，实现航铝废材绿色高效精细分选除杂，磁选除铁率≥99.8%，油水脱除率＞99%。具体地，本文通过废旧航铝材氧化特性研究，使用扫描电子显微镜对航空铝合金表面的微观形貌进行观察，同时使用EDS能谱仪得到废旧航铝材表面元素组成；利用XRD、XRF、ICP、FT-IR、直读光谱仪等表征手段，获得废旧航铝材成分与热导率等基础理化数据；采用响应曲面法优化蒸馏时间、蒸馏温度及航铝屑装料厚度等参数对废旧航铝油水热脱除效率的影响，获得不同工艺下油水的脱除效率数据；并建立了废旧航铝材精细分选及高效除杂关键技术数据库。以上数据结果将为废旧航铝材精细分选及高效除杂提供技术参考。
The increasing stockpile of aerospace aluminum alloy scraps leads to waste of aluminum resources and poses severe environmental pressure. Limited by sorting capabilities and pretreatment technologies, only a portion of aerospace aluminum alloy scraps are currently downcycled into low-quality aluminum scraps for cast aluminum alloy production, and their original value cannot be fully utilized. Therefore, there is an urgent need to develop grade-retaining recycling technologies for aerospace aluminum alloys. This project develops integrated sorting and impurity removal systems combining magnetic, eddy current, spectral, and heavy medium sorting technologies, as well as technologies and equipment such as low-oxygen dynamic green thermal removal of water and oil, and establishes an intelligent impurity removal control system to realize green, efficient and precise sorting and impurity removal of aerospace aluminum alloy scraps. The magnetic iron removal rate reaches ≥99.8%, and the oil and water removal rate exceeds 99%. Specifically, this study investigates the oxidation characteristics of waste aerospace aluminum materials, observes the microscopic morphology of the aerospace aluminum alloy surface using a scanning electron microscope (SEM), and obtains the elemental composition of the waste aerospace aluminum material surface via an energy-dispersive X-ray spectroscopy (EDS) analyzer. Using characterization methods including X-ray diffraction (XRD), X-ray fluorescence (XRF), inductively coupled plasma (ICP), Fourier-transform infrared spectroscopy (FT-IR), and direct-reading spectrometers, basic physicochemical data such as composition and thermal conductivity of waste aerospace aluminum materials are collected. Response surface methodology (RSM) is adopted to optimize the impacts of parameters including distillation time, distillation temperature and charging thickness of aerospace aluminum chips on the thermal oil and water removal efficiency of waste aerospace aluminum materials, and obtain oil and water removal efficiency data under different processes. Moreover, a database of key technologies for precise sorting and efficient impurity removal of waste aerospace aluminum materials is established. The above data and results will provide technical references for the precise sorting and efficient impurity removal of waste aerospace aluminum materials.
