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Primary testing of an instrumented tool holder for brush deburring of milled workpieces

Ramsauer Christoph, Oswald Ralf, Schörghofer Paul, Leder Norbert, Schmitz Tony, Bleicher Friedrich

Journal of Machine Engineering

2022

Vol. 22, No. 2

99--107

Brush deburring requires consistent contact pressure between brush and workpiece. Automating adjustments to control contact pressure has proven difficult, as the sensors available in machine tools are usually not suitable to observe the small amplitude signals caused by this low force process. Additionally, both the power consumption and the vibration signal caused by the process strongly depend on the workpiece surface features. This paper describes a test setup using an instrumented tool holder and presents the corresponding measurement results, aiming to quantify the axial feed of the brush. It also discusses the interpretation of different signal components and provides an outlook on the utilization of the data for tool wear estimation.

Feature generation from digital images using pseudo-fractal algorithm and its four modifications

Janaszewski M., Kącki E.

Machine Graphics and Vision

2007

Vol. 16, No. 1/2

117-138

The main aim of the paper is to present the authors' original method of feature generation from digital images and to report on a comparison of five various algorithms, which implemented that method. The algorithms are based on an idea by the same authors', which consists in producing a quantitative description of similarity intensity between various parts of an image in various scales. To develop it the algorithms take advantage of fractal coding based on an Iterated Function System. Therefore, the generated features can rightly be called similarity features. In this paper we show that similarity features, when combined with other well known ones, can improve recognition results in some image classification tasks. After presenting how the algorithm works, we compare their properties and report the classification results obtained in two different pattern recognition experiments. Moreover, the paper contains a discussion of the obtained results, and of possible future applications of the similarity features.