State sensing of composite structures with complex curved surface based on distributed optical fiber sensor
Source abstract
Abstract
Composite structures with complex curved surface are typical important external structures of aircraft. Residual strain will be formed due to complex manufacturing processes, resulting in the weakness of structural strength. In addition, there are great security implications that various mechanisms used for aircraft safety may cause failures on service, such as fiber fracture, matrix cracking, stratification, and debonding. In this article, methods of structural state sensing on composite structures with complex curved surface are researched. This article established a method of strain monitoring on composite structures and strategy of damage identification based on distributed optical fiber sensors. First, strategies of high spatial resolution strain measurement are studied, and the criteria of damage identification on composite laminates based on strain information are deduced, which could be used on accurate positioning of crack tips. Finally, strain measurement and damage identification tests of composite structures with complex curved surface under uniform load condition were conducted. The results indicate that the distributed optical fiber sensor installed on the composite structures with complex curved surface can be used to measure strain precisely and identify damage in the neighborhood of fiber installation path accurately.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Fiber Optic Sensors · Railway Engineering and Dynamics · Advanced Measurement and Detection Methods
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
State Key Laboratory of Structural Analysis for Industrial Equipment and Department of Engineering Mechanics, Dalian University of Technology, Dalian, P.R. China
Funding
National Natural Science Foundation of China · national basic research program of china · Fundamental Research Funds for the Central Universities · Natural fund of Liaoning Province
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