Accuracy and sensibility analysis of strain measurement based on microimages captured by smartphone with a microscope

Abstract

Strain measurement is an essential part of structural health monitoring (SHM). The objective of the study is to propose a new method to measure strain on the surface of a structure. The speeded-up robust feature (SURF) method was applied to detect and trace feature points in microimages that were obtained using a smartphone with a compact microscope. Subsequently, the average displacement of feature points in microimages was calculated before and after deformation. Finally, the average strain of a certain distance in the structure surface was obtained. An experiment was performed to measure the average strain in an optical fiber of certain length and compare the data with that measured by the fiber Bragg granting (FBG) to verify the accuracy of the proposed method. Additionally, a water drop loading experiment was performed on the optical fiber to test the sensitivity of the proposed method. The results indicated that the strain measured by the smartphone with a compact microscope was in agreement with the FBG data. The error analysis illustrates the maximum error of the data measured by the two methods is 6με, and this can satisfy the requirements of civil engineering. The result of the water drop experiment reveals that the entire process of loading via water drops can be measured by the proposed method, and strain increases with the drops of water. The experimental results verify that the feasibility of the proposed method can satisfy the needs of structural health monitoring for general buildings.