Correction of rigid body motion in deformation measurement of rotating objects

• Published in: Measurement : journal of the International Measurement Confederation Vol. 129; pp. 436 - 444
• Main Authors: Sousa, Pedro J., Tavares, João Manuel R.S., Tavares, Paulo J.S., Moreira, Pedro M.G.P.
• Format: Journal Article
• Language: English
• Published: London Elsevier Ltd 01.12.2018; Elsevier Science Ltd
• Subjects: Angle of attack; Coordinates; Data acquisition; Deformation; Digital image correlation; Helicopter blade deformation; Image acquisition; Image processing; Image processing systems; Knowledge acquisition; Methodology; Movement; Point cloud processing; Rigid structures; Rigid-body dynamics; Rotating bodies; Rotation; Tracking; Helicopter blade deformation; Point cloud processing; Image processing; Digital image correlation
• ISSN: 0263-2241; 1873-412X
• DOI: 10.1016/j.measurement.2018.07.049

[Display omitted] •Proposed methodology enables the correction of rigid rotations.•A coordinate system is defined from the calculated rotation axis.•Deformations are obtainable in the new coordinate system.•The methodology was validated experimentally.•The results confirm the methodology competence. When using image-based measurement solutions for monitoring the displacement of rotating objects, it is necessary to trigger the image acquisition system at precise positions. Triggering errors lead to artificial rigid motions in the output that are hard to remove independently. Thus, a methodology was developed to enable the removal of these errors while maintaining the true rotations, such as those relating to the angle of attack. The proposed methodology involves detecting an object’s axis and centre of rotation and then using that knowledge to correct acquired deformation data. Additionally, it also enables the representation of displacements in a more representative coordinate system, i.e., one that includes the rotation axis. While common solutions for this problem use either manually positioned references or track a single-point’s rotation, the proposed methodology is based on a least-squares approach. This results in a more accurate measurement of the rotation axis and, thus, improves the quality of the results. The methodology was experimentally validated and it was shown that its implementation is accurate, with errors below 3%. Additionally, it was applied to an actual experimental situation and the results were compared to the uncorrected data, while highlighting the most relevant improvements.