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Automatic measurement of grinding-induced white layer in titanium alloys based on image processing technique

机译:基于图像处理技术的钛合金研磨诱导的白色层的自动测量

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摘要

Titanium alloys is a key kind of materials in both aerospace industry and biomedical engineering. However, mechanical grinding process of Ti alloys easily leads to the featureless white layer (WL) extending tens of micrometers beneath the ground surface. Although many relevant studies have been reported so far, the WL quantification in most previous studies was performed by human raw eyes. To fill this gap, this paper proposes an image-processing-based method which can automatically recognise and measure the grinding-induced WL in the Ti alloy workpiece. By comparing the results separately obtained by the proposed method and manual measurement, it shows that the method can recognise and measure the WL region accurately (the maximum absolute error of 0.09?μm) and quickly (1.65?s per micrograph). More importantly, the method does not require any parameter presetting and has good robustness in terms of (i) varied WL region thicknesses, (ii) different workpiece placements and (iii) the interference from the noise pixels. The method therefore is believed to be not only meaningful and helpful to automatically measure the WL thickness in Ti alloys in large quantities, but also transferable to other industrial applications.
机译:钛合金是航空航天工业和生物医学工程中的主要材料。然而,Ti合金的机械研磨过程容易导致延伸在地面下方数十微米的无特色白色层(WL)。虽然到目前为止已经报告了许多相关研究,但以前研究的WL量化是由人类的生眼睛进行的。为了填补这种差距,本文提出了一种基于图像处理的方法,其可以在Ti合金工件中自动识别和测量研磨诱导的WL。通过比较通过所提出的方法和手动测量分别获得的结果,表明该方法可以精确地识别和测量WL区域(最大绝对误差为0.09≤μm)并快速(每显微照片1.65Ω秒)。更重要的是,该方法不需要任何参数预设,并且在(i)变化的WL区域厚度方面具有良好的鲁棒性,(ii)不同的工件放置和(iii)来自噪声像素的干扰。因此,该方法被认为不仅是有意义的,并且有助于在大量的Ti合金中自动测量WL厚度,而且可以转移到其他工业应用。

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