白倩

个人信息Personal Information

副教授

博士生导师

硕士生导师

性别:女

毕业院校:伦敦帝国理工学院

学位:博士

所在单位:机械工程学院

学科:机械制造及其自动化. 材料加工工程

办公地点:知方楼5007

联系方式:13842856182

电子邮箱:baiqian@dlut.edu.cn

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Methods for Detection of Subsurface Damage: A Review

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论文类型:期刊论文

发表时间:2018-12-01

发表刊物:CHINESE JOURNAL OF MECHANICAL ENGINEERING

收录刊物:SCIE

卷号:31

期号:1

ISSN号:1000-9345

关键字:Subsurface damage; Hard and brittle material; Taper polishing; Measurement; Laser scattering

摘要:Subsurface damage is easily induced in machining of hard and brittle materials because of their particular mechanical and physical properties. It is detrimental to the strength, performance and lifetime of a machined part. To manufacture a high quality part, it is necessary to detect and remove the machining induced subsurface damage by the subsequent processes. However, subsurface damage is often covered with a smearing layer generated in a machining process, it is rather difficult to directly observe and detect by optical microscopy. An efficient detection of subsurface damage directly leads to quality improvement and time saving for machining of hard and brittle materials. This paper presents a review of the methods for detection of subsurface damage, both destructive and non-destructive. Although more reliable, destructive methods are typically time-consuming and confined to local damage information. Non-destructive methods usually suffer from uncertainty factors, but may provide global information on subsurface damage distribution. These methods are promising because they can provide a capacity of rapid scan and detection of subsurface damage in spatial distribution.