Methods for thermally compensated measurements of large structures

Thermal deformations are often the dominant source of uncertainty for high accuracy measurements of large structures. This open access paper published in the International Journal of Metrology and Quality Engineering presents a hybrid approach to compensation for the resulting errors. This involves temperature measurements at discrete points on the part which is undergoing thermal deformation. Finite Element Analysis (FEA) is then used to first estimate the full temperature field based on the discrete point measurements of temperature. A second FEA is then used to estimate the thermal strain and predict the nominal state of the part at a uniform reference temperature. Repeating this process at a number of thermal loading states can be used to refine and verify the predictions made.

Paper Title: Thermal compensation for large volume metrology and structures

Authors: Bingru Yang, David Ross-Pinnock, Jody Muelaner, and Glen Mullineux
University of Bath

Published in: International Journal of Metrology and Quality Engineering, 2017, 8(21)

Download the full paper…


Ideally metrology is undertaken in well-defined ambient conditions. However, in the case of the assembly of large aerospace structures, for example, measurement often takes place in large uncontrolled production environments, and this leads to thermal distortion of the measurand. As a result, forms of thermal (and other) compensation are applied to try to produce what the results would have been under ideal conditions. The accuracy obtained from current metrology now means that traditional compensation schemes are no longer useful. The use of finite element analysis is proposed as an improved means for undertaking thermal compensation. This leads to a “hybrid approach” in which the nominal and measured geometry are handled together. The approach is illustrated with a case study example


Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.