Adjusting Accuracy of Digital Image Correlation Through Variable Subsets and Application in Airship Envelope

The stratospheric airship is affected by harsh conditions in the stratosphere environment. To ensure the safety of the airship, it is necessary to detect the material state of the airship envelope. Since digital image correlation possesses non-contact strain measurement ability, this paper explores the influence of different shapes of the subset on measurement accuracy. Through the results, it is found that increasing the aspect ratio of subsets can improve the strain accuracy measured in the x -direction, and reducing the aspect ratio can improve the strain accuracy measured in the y -direction. This trend becomes more obvious as the strain increases. Based on this discovery, a subset adaptive algorithm is proposed. The feasibility of the algorithm is verified by experiments, and the precision of strain measurement can be effectively improved by adjusting the threshold value. Therefore, the algorithm can be utilized to increase the measurement accuracy in the larger strain direction without changing the size of the subset.