Design and Optimization of FBG Implantable Flexible Morphological Sensor to Realize the Intellisense for Displacement

Sensors

Hanpeng Wang¹  Qingmei Sui²  Zhengfang Wang²  Yijia Li²  Changbin Tian²  Jing Wang²  Lei Jia²  Yanan Dong²  Mingjuan Han² 

[1] Geo &School of Control Science and Engineering, Shandong University, Jinan 250061, China;

关键词: FBG flexible sensor;    morphological sensing;    classification morphological correction method;    conjugate gradient method;    ELM;   

DOI  :  10.3390/s18072342

来源: DOAJ

【 摘 要 】

The measurement accuracy of the intelligent flexible morphological sensor based on fiber Bragg grating (FBG) structure was limited in the application of geotechnical engineering and other fields. In order to improve the precision of intellisense for displacement, an FBG implantable flexible morphological sensor was designed in this study, and the classification morphological correction method based on conjugate gradient method and extreme learning machine (ELM) algorithm was proposed. This study utilized finite element simulations and experiments, in order to analyze the feasibility of the proposed method. Then, following the corrections, the results indicated that the maximum relative error percentages of the displacements at measuring points in different bending shapes were determined to be 6.39% (Type 1), 7.04% (Type 2), and 7.02% (Type 3), respectively. Therefore, it was confirmed that the proposed correction method was feasible, and could effectively improve the abilities of sensors for displacement intellisense. In this paper, the designed intelligent sensor was characterized by temperature self-compensation, bending shape self-classification, and displacement error self-correction, which could be used for real-time monitoring of deformation field in rock, subgrade, bridge, and other geotechnical engineering, presenting the vital significance and application promotion value.

【 授权许可】

Unknown