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Novel moiré‐based crack monitoring system with smartphone interface and cloud processing
Author(s) -
Ratnam Mani Maran,
Ooi Boon Yaik,
Yen Kin Sam
Publication year - 2019
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.2420
Subject(s) - cloud computing , moiré pattern , software , displacement (psychology) , computer science , interface (matter) , image processing , real time computing , computer vision , image (mathematics) , psychology , bubble , maximum bubble pressure method , parallel computing , psychotherapist , programming language , operating system
Summary A popular optical‐mechanical method used to monitor crack growth in concrete structures is based on the moiré effect. The moiré patterns are usually interpreted manually using a read‐out chart or by off‐line processing using custom‐made application software installed in a personal computer. Such methods are not convenient for on‐site crack inspection and measurement. In this work, cloud‐based application software has been developed that can be used to process moiré pattern images sent via a standard smartphone. The moiré pattern resulting from the overlapping of two circular gratings mounted across a crack is captured using the smartphone camera, cropped, and sent via Wi‐Fi or mobile data to cloud server. The cloud server software receives the moiré pattern image and processes it using an image processing algorithm to return the displacement magnitude and direction to the mobile device within a few seconds. The communication between the mobile software and cloud software is via Representational State Transfer protocol that allows further development to accommodate other client platforms. The accuracy of the algorithm has been tested by comparing the displacement data returned by the cloud server using controlled experiment. In the experiment, the gratings were subjected to in‐plane displacement along two orthogonal axes using 0.001‐mm resolution digital micrometers. The results show that the displacement magnitude and displacement direction can be determined within an accuracy of ±0.05 mm and ±5°, respectively. The smartphone interface with cloud processing of moiré patterns is shown to be a promising tool for on‐site crack inspection and monitoring.