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

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Abstract

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.

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Acknowledgments

The authors appreciate the support from the China Scholarship Council (CSC) and Prof. Paul Chung in Loughborough University (UK) on this work.

Funding

The support was from the National Natural Science Foundation of China, undertaking this research work under the grant number of 51374063 and the Fundamental Research Funds for the Central Universities under the grant number of N140303008, N141008001 and N150308001.

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Authors and Affiliations

  1. Faculty of Mechanical Engineering & Mechanics, Ningbo University, Ningbo, 315211, China

    Yong Jie Zhao & Dong Tai Liang

  2. School of Mechanical Engineering & Automation, Northeastern University, Shenyang, 110819, China

    Ke Chen Song & Yun Hui Yan

  3. School of Aerospace, The University of Nottingham Ningbo China, Ningbo, 315100, China

    Hao Nan Li

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  1. Yong Jie Zhao
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Correspondence to Hao Nan Li.

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Zhao, Y.J., Liang, D.T., Song, K.C. et al. Automatic measurement of grinding-induced white layer in titanium alloys based on image processing technique. Int J Adv Manuf Technol 105, 1483–1496 (2019). https://doi.org/10.1007/s00170-019-04390-x

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