The Method and Experiment of Detecting the Strength of Structural Components Utilizing the Distributed Strain of Sensing Optical Fibers Demodulated by OFDR

Author:

Chen Bin1ORCID,Yang Jun1,Zhang Dezhi1,Liu Wenxiang1,Li Jin1,Zhang Min1,Li Ang1,Wang Zhao1

Affiliation:

1. National Key Laboratory of Intense Pulsed Radiation Simulation and Effect, Northwest Institute of Nuclear Technology, Xi’an 710024, China

Abstract

Defects occurring during the welding process of metal structural components directly affect their overall strength, which is crucial to the load-bearing capacity and durability of the components. This signifies the importance of accurate measurement and assessment of weld strength. However, traditional non-destructive testing methods such as ultrasonic and non-contact camera inspection have certain technical limitations. In response to these issues, this paper analyzes the detection principle of weld strength, revealing that weld defects reduce the effective area of the structural bearing section and cause stress concentration around them. Through repeated experimental data analysis of samples, strain distribution data along the one-dimensional direction caused by defects such as slag inclusion and porosity were obtained. Experimental results show that this method can identify defect types in welds, including slag inclusion, porosity, and unevenness, and accurately measure the location and size of defects with a precision of 0.64 mm, achieving qualitative analysis of weld defects. Additionally, by deploying distributed optical fiber sensors (DOFS) at different vertical distances along the weld direction, the propagation law of stress induced by different types of weld defects on samples was thoroughly analyzed. This further validates the advantages of this method in weld strength detection, including high spatial resolution, high sensitivity, and non-destructive measurement.

Funder

Northwest Institute of Nuclear Technology

Publisher

MDPI AG

Reference20 articles.

1. Application of Laser welding Technology in aviation industry machinery manufacturing;An;Mod. Ind. Econ. Inf. Technol.,2024

2. Huang, W., and Kovacevic, R. (2011). A Laser-Based Vision System for Weld Quality Inspection. Sensors, 11.

3. Gao, B., Peng, G., Wang, X.-C., Wang, W., Chen, C.-X., Feng, J.-C., and Liu, Y. (2020). Design of Circular Ring Shaper and Numerical Simulation of Shaping Effect. Mod. Appl. Phys., 11.

4. Wang, B., Liu, Q., Feng, Q., Wang, X., Yang, Z., Dai, L., Huo, X., Wang, D., Yu, J., and Chen, J. (2024). Influence of welding defects on hydrogen embrittlement sensitivity of girth welds in X80 pipelines. Int. J. Electrochem. Sci., 19.

5. Wang, M.-J., Shen, J.-H., Chen, B., Katsuyoshi, K., and Li, Y.-L. (2021). Dynamic Mechanical Behavior and Strain Rate Effect of Al-based Carbon Nanotubes Reinforced Composites. Mod. Appl. Phys., 12.

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