DocumentCode :
738213
Title :
Multi-Damage Identification System of CFRP by Using FBG Sensors and Multi-Classification RVM Method
Author :
Lu, Shizeng ; Jiang, Mingshun ; Sui, Qingmei ; Dong, Huijun ; Sai, Yaozhang ; Jia, Lei
Author_Institution :
School of Control Science and Engineering, Shandong University, Jinan, China
Volume :
15
Issue :
11
fYear :
2015
Firstpage :
6287
Lastpage :
6293
Abstract :
Multi-damage identification of carbon fiber reinforced plastics (CFRP) structure is very important to ensure the structural safety. In this paper, the multi-damage identification system of CFRP using fiber Bragg grating (FBG) sensors and multi-classification relevance vector machine (RVM) method was proposed. First, the multi-damage identification method was researched by an active actuation method. In addition, the structural dynamic response signals were detected by the FBG sensors. Then, the multi-damage characteristics extraction was completed by Fourier transform, reliefF, and principal component analysis algorithms. With the multi-damage characteristics as the input and their corresponding multi-damage state as the output, the multi-classification RVM model was trained to identify the multi-damage state. Finally, the multi-damage identification system was established and verified on a CFRP plate with dimensions of 500 mm \\times ,, 500 mm \\times ,, 2 mm. The results showed that the proposed multi-damage identification method can accurately identify the CFRP structural multi-damage state. This paper provided a reliable method for the CFRP structural multi-damage identification.
Keywords :
Fiber gratings; Optical sensors; Principal component analysis; Sensor phenomena and characterization; Training; Fiber Bragg grating sensors; carbon fiber reinforced plastics; characteristics extraction; fiber Bragg grating sensors; multi-classification RVM; multi-damage identification;
fLanguage :
English
Journal_Title :
Sensors Journal, IEEE
Publisher :
ieee
ISSN :
1530-437X
Type :
jour
DOI :
10.1109/JSEN.2015.2456333
Filename :
7156069
Link To Document :
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