DC Field | Value | Language |
---|---|---|
dc.contributor.author | Choi, Jaemook | ko |
dc.contributor.author | Ma, Zhanxiong | ko |
dc.contributor.author | Kim, Kiyoung | ko |
dc.contributor.author | Sohn, Hoon | ko |
dc.date.accessioned | 2023-06-27T05:01:47Z | - |
dc.date.available | 2023-06-27T05:01:47Z | - |
dc.date.created | 2023-06-26 | - |
dc.date.issued | 2023-05 | - |
dc.identifier.citation | SENSORS, v.23, no.11 | - |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.uri | http://hdl.handle.net/10203/310062 | - |
dc.description.abstract | With the rapid development of computer vision, vision cameras have been used as noncontact sensors for structural displacement measurements. However, vision-based techniques are limited to short-term displacement measurements because of their degraded performance under varying illumination and inability to operate at night. To overcome these limitations, this study developed a continuous structural displacement estimation technique by combining measurements from an accelerometer with vision and infrared (IR) cameras collocated at the displacement estimation point of a target structure. The proposed technique enables continuous displacement estimation for both day and night, automatic optimization of the temperature range of an infrared camera to ensure a region of interest (ROI) with good matching features, and adaptive updating of the reference frame to achieve robust illumination-displacement estimation from vision/IR measurements. The performance of the proposed method was verified through lab-scale tests on a single-story building model. The displacements were estimated with a root-mean-square error of less than 2 mm compared with the laser-based ground truth. In addition, the applicability of the IR camera for displacement estimation under field conditions was validated using a pedestrian bridge test. The proposed technique eliminates the need for a stationary sensor installation location by the on-site installation of sensors and is therefore attractive for long-term continuous monitoring. However, it only estimates displacement at the sensor installation location, and cannot simultaneously estimate multi-point displacements which can be achieved by installing cameras off-site. | - |
dc.language | English | - |
dc.publisher | MDPI | - |
dc.title | Continuous Structural Displacement Monitoring Using Accelerometer, Vision, and Infrared (IR) Cameras | - |
dc.type | Article | - |
dc.identifier.wosid | 001003862800001 | - |
dc.identifier.scopusid | 2-s2.0-85161544626 | - |
dc.type.rims | ART | - |
dc.citation.volume | 23 | - |
dc.citation.issue | 11 | - |
dc.citation.publicationname | SENSORS | - |
dc.identifier.doi | 10.3390/s23115241 | - |
dc.contributor.localauthor | Sohn, Hoon | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | displacement estimation | - |
dc.subject.keywordAuthor | infrared camera | - |
dc.subject.keywordAuthor | vision camera | - |
dc.subject.keywordAuthor | accelerometer | - |
dc.subject.keywordAuthor | multirate adaptive Kalman filter | - |
dc.subject.keywordAuthor | continuous monitoring | - |
dc.subject.keywordPlus | VIBRATION | - |
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