Dutta, Samik and Pal, Surjya K. and Sen, Ranjan (2016) Progressive tool flank wear monitoring by applying discrete wavelet transform on turned surface images. Measurement, 77. pp. 388-401.

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In this paper, a method for on-machine tool progressive monitoring of tool flank wear by processing the turned surface images in micro-scale has been proposed. Micro-scale analysis of turned surface has been performed by using discrete wavelet transform. A novel methodology for proper selection of mother wavelets and its decomposition level dependent on the feed rate parameter has also been shown in this research. The selected mother wavelets are utilized to decompose the turned surface images at the chosen decomposition level and two features, namely, GRMS and Energy are extracted as the highly repeatable descriptors of tool flank wear. An exponential correlation of GRMS and Energy values with progressive tool flank wear are found with average coefficient of determination values as 0.953 and 0.957, respectively.

Item Type: Article
Subjects: Image processing for tool condition monitoring
Depositing User: Dr. Sarita Ghosh
Date Deposited: 10 Jul 2017 10:34
Last Modified: 10 Jul 2017 10:34
URI: http://cmeri.csircentral.net/id/eprint/408

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