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极端环境下7055铝合金摩擦磨损及表面质量研究 被引量:8

Friction, Wear and Surface Quality of 7055 Aluminum Alloy under Extreme Conditions
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摘要 本文在–60℃和300℃两种极端环境下对经过二次时效处理的7055铝合金进行高速切削试验,采用超景深三维显微系统对刀具磨损形貌进行分析,用探针式三维表面形貌仪对切削加工表面形貌进行分析,并对切削前后的7055铝合金进行TEM微观组织分析,研究了7055铝合金在两种极端环境下的刀具摩擦磨损及表面质量.研究结果表明:在–60℃时,刀具磨损的主要形式为磨粒磨损,并出现崩刃,在300℃时,刀具磨损主要形式为氧化磨损和黏着磨损;在–60℃时,材料经过了深冷处理,硬度、脆性增强,切削加工表面质量较差;在300℃时,材料经过了回归热处理,脆硬性降低,韧性增强,切削过程中不断生成氧化膜,极大程度上提高了表面质量,延长了刀具寿命;–60℃时,TEM微观组织显示,材料弥散相变细小,在300℃时,TEM微观组织显示,材料弥散相出现大量消失,即发生回归现象. In this study, high speed cutting experiment of 7055 aluminum alloy treated by low temperature progressive aging was conducted under the extreme conditions at –60 ℃ and 300 ℃. Super depth of three-dimensional microscopic system was used to examine the tool worn surface morphology. The milling processing surface topography was explored by 3D probe-type Surface Plasmon Resonance Analyzer. The microstructures of 7055 aluminum before and after the cutting were comparatively investigated by using transmission electron microscopy. The results show that the main wear form of tool was abrasive wear with brittle tipping at –60 ℃. The main wear form of tool was oxidative wear and adhesive wear at 300 ℃. It is found that the high hardness and brittleness of 7055 aluminum alloy due to the cryogenic treatment at –60 ℃ led to the poor quality of processing surface. In contrast, the lower hardness and brittleness and higher toughness and ductility of material owing to the retrogression heat treatment at 300 ℃ were beneficial to the good quality of the processing surface.And the tool life was prolonged. By observing the TEM microstructure of the materials,it is shown that the discrete grain phases of 7055 aluminum alloy became tiny and fine after high speed cutting at –60 ℃.Most of the discrete phases of 7055 aluminum alloy disappeared after high speed cutting at 300 ℃. The microstructure retrogression phenomenon emerged.
出处 《摩擦学学报》 EI CAS CSCD 北大核心 2016年第2期254-260,共7页 Tribology
基金 国家自然科学基金项目(51175275 51575289)~~
关键词 极端环境 刀具磨损 表面质量 弥散相 回归现象 extreme condition tool wear quality of the surface discrete phase regression
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