TY - JOUR
T1 - Visual–inertial displacement sensing using data fusion of vision-based displacement with acceleration
AU - Park, Jong Woong
AU - Moon, Do Soo
AU - Yoon, Hyungchul
AU - Gomez, Fernando
AU - Spencer, Billie F.
AU - Kim, Jong R.
N1 - Funding Information:
This research was supported by the Basic Science Research Program of the National Research Foundation of Korea (NRF) from the Ministry of Education, Science and Technology (NRF‐2017R1C1B5018231) and the Federal Railroad Administration (FRA) under contract DTFR53‐15‐C‐00014.
PY - 2018/3/1
Y1 - 2018/3/1
N2 - In recognition of the importance of the displacement associated with assessing structural condition, many displacement measurement methods have been proposed to date. With advances in optics and electronics, displacement measurement relying on computer-vision techniques to convert pixel movement into structural displacement has drawn much attention recently, thanks to its simplicity in installation and relatively inexpensive cost. Despite numerous advantages, 2 major obstacles that prohibit the use of vision-based method are (a) resolution, which is a function of distance between the camera and the structure, and (b) limited frame rate, which both lower dynamic displacement-capturing capability. In this paper, to enhance the quality of vision-based displacement measurement, data fusion with acceleration measurement is proposed to improve the dynamic range of displacements while lowering signal noise. To achieve fusion between vision-based displacement and acceleration, complementary filters and a time synchronization method between 2 different sources were proposed. The proposed methods were verified through numerical analysis and an experimental test, the results of which showed the validity of proposed data fusion.
AB - In recognition of the importance of the displacement associated with assessing structural condition, many displacement measurement methods have been proposed to date. With advances in optics and electronics, displacement measurement relying on computer-vision techniques to convert pixel movement into structural displacement has drawn much attention recently, thanks to its simplicity in installation and relatively inexpensive cost. Despite numerous advantages, 2 major obstacles that prohibit the use of vision-based method are (a) resolution, which is a function of distance between the camera and the structure, and (b) limited frame rate, which both lower dynamic displacement-capturing capability. In this paper, to enhance the quality of vision-based displacement measurement, data fusion with acceleration measurement is proposed to improve the dynamic range of displacements while lowering signal noise. To achieve fusion between vision-based displacement and acceleration, complementary filters and a time synchronization method between 2 different sources were proposed. The proposed methods were verified through numerical analysis and an experimental test, the results of which showed the validity of proposed data fusion.
KW - complementary filter
KW - computer vision
KW - displacement measurement
KW - sensor fusion
KW - structural health monitoring
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U2 - 10.1002/stc.2122
DO - 10.1002/stc.2122
M3 - Article
AN - SCOPUS:85041681047
VL - 25
JO - Structural Control and Health Monitoring
JF - Structural Control and Health Monitoring
SN - 1545-2255
IS - 3
M1 - e2122
ER -