A Fiber Bragg Grating (FBG)-Enabled Smart Washer for Bolt Pre-Load Measurement: Design, Analysis, Calibration, and Experimental Validation.
Sensors (Basel)
; 18(8)2018 Aug 07.
Article
em En
| MEDLINE
| ID: mdl-30087281
A washer is a common structural element that is directly used along the loading path of a bolted connection. Pre-load on a bolted connection directly impacts its load bearing capacity and pre-load monitoring is an important aspect of structural health monitoring (SHM). With the change of the pre-load on a bolted connection, the loading force on the washer will change and, therefore, the outer diameter and outer circumferential length of the washer will change. Taking advantage of the high sensitivity and the small size of a Fiber Bragg Grating (FBG) sensor, we propose an innovative smart washer encircled by an FBG sensor that can directly measure the circumferential strain change and, therefore, the pre-load on the washer. For protection, the FBG is embedded in a pre-machined groove along the circumferential surface of the washer. A theoretical approach is used to derive the linear relationship between the applied load and the circumferential strain of the washer. To validate the functionality of the FBG-enabled smart sensor for in situ bolt pre-load monitoring, a simple but effective testing apparatus is designed and fabricated. The apparatus involves a bolt, the FBG-enabled washer, a metal plate, and a nut. The bolt has an embedded FBG along its axial direction for precise axial strain and, therefore, force measurement. With the calibrated axial force measuring bolt, in situ experiments on the FBG-enabled smart washers are conducted. Experimental results reveal the linear relationship between the pre-load and the wavelength of the FBG sensor encircling the washer. Both analytical and experimental results demonstrate that the proposed novel approach is sensitive to the bolt pre-load and can monitor in real time the bolt looseness in the entire loading range.
Texto completo:
1
Bases de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Sensors (Basel)
Ano de publicação:
2018
Tipo de documento:
Article
País de afiliação:
China