ENBIS-16 in Sheffield

11 – 15 September 2016; Sheffield Abstract submission: 20 March – 4 July 2016

Automatic Splat Detection in HVOF Spraying Processes

13 September 2016, 09:40 – 10:00

Abstract

Submitted by
Dominik Kirchhoff
Authors
Dominik Kirchhoff (TU Dortmund University), Sonja Kuhnt (Dortmund University of Applied Sciences and Arts)
Abstract
For the coating of a surface, thermal spraying processes are becoming increasingly popular. An interesting technique is high velocity oxygen fuel (HVOF) spraying, where a powder is fed into a jet, gets accelerated and heated up by means of a mixture of oxygen and fuel, and finally deposits as coating upon a substrate in form of small, about circular so-called splats.

To gain more information about the influence of the parameter setting and in-flight particle properties, one can analyze scanning electron microscope (SEM) images of splats. Here, we propose an algorithm that automatically detects splats in such images. Before, this was not trivially possible, since existing software for the detection of objects often requires the objects to be very similar and fore- as well as background to be homogenous. Splats, however, vary with regard to their shape, size, and structure, and the images tend to be quite noisy.

Our algorithm fits circles to the splats in an iterative manner, mainly using Rotational Difference Kernel Estimators (RDKE) to detect edges and circular clustering to find circles. We develop a measure to quantify the goodness of fit of a set of circles given manually assigned circles and conduct a small study in which we find that the algorithm works well, except for images with many overlapping splats. The algorithm drastically reduces the amount of time researchers spend on counting splats. As a next step, a shape classifier could be applied based on the found splat locations.
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