Online non-contact surface finish measurement in machining using graph theory-based image analysis Academic Article uri icon

abstract

  • © 2016 The Society of Manufacturing Engineers This work addresses the following open research question: what non-contact measurement techniques and analytical approaches are required to assess the surface finish of a workpiece in situ during conventional machining without stopping the machine tool? The goal is to track variations in surface finish during conventional machining without stopping the machine tool so that quick compensatory action can be taken in case of a process drift. In pursuit of this goal, the objective of this work is non-contact, vision-based online measurement of surface finish in a conventional machining operation, such as outside diameter (OD) turning on a lathe. To realize the foregoing objective, algebraic graph theoretic image processing is used. The approach is based on converting an image of a surface into an unweighted and undirected network graph. The graph theoretic invariant, Fiedler number (λ2), is estimated, and subsequently invoked as a discriminant of workpiece surface roughness. The advantage of the proposed approach is that it eschews complex image filtering and segmentation steps. The central hypothesis is that the graph-based topological quantifier Fiedler number (λ2) estimates surface finish in a conventional machining operation with accuracy Sa ± 2 μm (arithmetic average areal surface roughness, μm) when Sa is in the range of 1-10 μm. This hypothesis is tested on conventional cylindrical (outside diameter) turning of shafts by using an optical imaging setup (CCD camera) incorporated into a lathe machine. Through statistical modeling it is demonstrated that the Fiedler number (λ2) tracks surface finish variations in situ for steel and aluminum alloy shafts (4340 and 6061 grades, respectively) in near real-time with a maximum error of approximately Sa ± 2 μm. This measurement error was verified to be within 15% of the actual measured surface finish. Tests were also carried out under three different rotational speeds (0 rpm, 45 rpm, 245 rpm); and the approach was consequently attested to be robust to rotational speeds. The computational time for estimating the surface finish from this approach was assessed to be within tenth of a second, thus validating its practical applicability.

author list (cited authors)

  • Tootooni, M. S., Liu, C., Roberson, D., Donovan, R., Rao, P. K., Kong, Z., & Bukkapatnam, S.

citation count

  • 17

publication date

  • October 2016