Vision-based modal analysis of cutting tools.

[Display omitted] • Vision-based cutting tool motion registration methods are presented. • Tool motion is recorded with low- and high-speed cameras with high resolutions. • Motion is estimated using edge detection, optical flow, and DIC schemes. • Tool motion from vision-based measurements agree with integrated accelerations. • Modal parameters from vision-based response compare well with standard procedures. This paper presents the use of vision-based methods for cutting tool motion registration and modal analysis. Motion of three illustrative tools were recorded using low- and high-speed cameras with sufficiently high resolutions. The tool's own features are used to register motion. Pixels within images from recordings of the vibrating tools are treated as non-contact motion sensors. Comparative analysis of three different methods of motion registration are presented to evaluate their suitability for the application of interest. These include variants of expanded edge detection and tracking schemes, expanded optical flow-based schemes, and established digital image correlation methods. Performance of different methods was observed to be governed by the tool's own features, illumination conditions, noise, and the image acquisition parameters. Extracted motion was benchmarked against twice integrated measured tool point accelerations, and motion was generally observed to compare well. Modal parameters extracted from vision-based measurements were also observed to agree with those extracted using more traditional experimental modal analysis procedures using a contact type accelerometer as the transducer. Since methods presented are generalized, they can suitably be adapted for other applications of interest. [ABSTRACT FROM AUTHOR]