Error characterization for digital image correlation measurements in industrial environments

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.advisor Bossuyt, Sven
dc.contributor.author McCluskey, Michael
dc.date.accessioned 2017-09-04T12:58:23Z
dc.date.available 2017-09-04T12:58:23Z
dc.date.issued 2017-08-28
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/27973
dc.description.abstract Digital image correlation (DIC) is a non-contact, full field displacement measurement technique. It is primarily suited to making high precision and high accuracy measurements, and is therefore commonly used in laboratories for experimental work. However, in recent years, improvements to technology and commercial interest in the industrial internet have created the potential for methods such as DIC to be utilized widely in industry. This thesis makes a preliminary investigation of errors that are likely to occur when DIC is performed in an uncontrolled environment. The characteristics of displacement and strain field measurements affected by camera motion, changing focus and inconsistent illumination are compared. To achieve this, computer graphics software is used to simulate a scene in which a stationary plate is viewed by a stereo imaging system. Animations of systematic changes to camera position, focus and lighting are made, and a ray-tracing render engine is used to produce the resultant photo-realistic images. In later simulations, the plate is substituted for a cylinder in different orientations, to investigate how error characteristics vary with surface angle and distance. The DIC algorithms are found to be robust, allowing viable measurements even when significant changes are made to the imaging environment. Changes to illumination and focus are seen to produce random noise, most likely resulting from incorrect matching of subsets. Conversely, camera motion is seen to result in systematic error, with each transformation component displaying distinct characteristics. This observation is significant, since it indicates a possibility for identifying and correcting for such errors in industrial applications. Surface curvature is found to have minimal impact on the error characteristics for most camera transformations, but significant differences are observed for camera translations along the y-axis and rotations around the x-axis. en
dc.format.extent 65+10
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.title Error characterization for digital image correlation measurements in industrial environments en
dc.type G2 Pro gradu, diplomityö fi
dc.contributor.school Insinööritieteiden korkeakoulu fi
dc.subject.keyword DIC en
dc.subject.keyword digital image correlation en
dc.subject.keyword industrial internet en
dc.subject.keyword ray tracing en
dc.subject.keyword computer vision en
dc.subject.keyword structural health monitoring en
dc.identifier.urn URN:NBN:fi:aalto-201709046872
dc.programme.major Mechanical Engineering fi
dc.programme.mcode IA3027 fi
dc.type.ontasot Master's thesis en
dc.type.ontasot Diplomityö fi
dc.contributor.supervisor Bossuyt, Sven
dc.programme Master’s Programme in Mechanical Engineering (MEC) fi
local.aalto.electroniconly yes
local.aalto.openaccess yes


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