Proof-of-concept study of bolt connection status monitoring using fiber Bragg grating curvature sensor
Autor(en): |
Shaohua Deng
Tao Wang Bohai Tan Wei Yu Guangtao Lu |
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Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Smart Materials and Structures, September 2022, n. 11, v. 31 |
Seite(n): | 114001 |
DOI: | 10.1088/1361-665x/ac9566 |
Abstrakt: |
For connection status monitoring of bolted joint groups, a novel method with fiber Bragg grating (FBG)-based curvature sensor is proposed. An FBG curvature sensor with an inextensible elastic matrix and an offset grating is adopted and clamped between a fixed support and the monitored bolt in a plane bending status. Based on the shape deformation of the FBG curvature sensor induced by the bolt loosening, the bending curvature change of the elastic matrix is measured by the FBG. By detecting the wavelength shift of the FBG induced by the matrix curvature variation, the relationship between the bolt loosening angle and the wavelength shift of FBG can be obtained, and hence the bolt connection status can be determined by the wavelength shift of FBG. Details of the proposed method are presented, and a surface-bonded FBG curvature sensor is designed, fabricated, and experimentally studied to verify the proposed method, and the parameters on sensing performance are also investigated. Experimental results show that the proposed method can monitor bolt loosening angle with high sensitivity and linear output by adjusting the parameters of the FBG curvature sensor. The looseness angle resolution of the proposed sensor can reach 0.0767°. This paper presents the first attempt to monitor bolt loosening angle using an FBG curvature sensor. With the advantages of high sensitivity and resolution, strong applicability, convenience and reusability for the maintenance of bolts, and ease of forming quasi-distributed sensor networks, the proposed method is able to provide a general solution for the on-line monitoring of bolt connection status for large-span distributed bolted-joint groups. |
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Datenseite - Reference-ID
10695324 - Veröffentlicht am:
11.12.2022 - Geändert am:
11.12.2022