Adaptive Vision Based Condition Monitoring and Fault Detection Method for Multi Robots at Production Lines in Industrial Systems

Year 2016, Special Issue (2016), 271 - 276, 01.12.2016

Hasan Yetiş , Mehmet Karaköse

https://doi.org/10.18100/ijamec.270410

Cited By: 11

Abstract

Continuity
of production is a highly important in the days that manufacturing is becoming
bigger and serial. The mistakes done while producing process cause fail on
products and it may bring about even big losses for the facility. Furthermore,
hitches on robots at production line may also cause crucial damages that may give
rise to high repair costs and discontinuance of production. In this study, it is aimed to obtain
alive bird's eye view map of production lines, which are big and impossible to
be monitored with only one camera, by using multi cameras and stitching
algorithms. Finding the similar scenes of input images, estimation of
homography, warping and blending operations, which are the steps used in feature
based image-stitching algorithms, are applied respectively on images that are
taken by cameras. The assignment of second nearest neighbor distance rate
adaptively makes the results more qualified. After obtaining single stitched image
movement detection is actualized by using the difference of sequential frames, and
anomaly movements are determined. As a result, the robots at the long production
lines can be monitored in one screen, and with processing the obtained image,
faults on robots that may cause damage at non-cheap machines can be handled before
time.

Keywords

Condition monitoring, Multi robots, Production lines, Image mosaicing, Image processing, Fault Diagnosis

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