Integrating fiber optic sensors into metallic components for sensing in harsh environments

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Abstract

The integration of fiber optic sensors into high-temperature materials is critical for real-time monitoring and autonomous operation of engineering systems. This study demonstrated a spark plasma sintering (SPS)-assisted embedding process for integrating sapphire fiber optic sensors into stainless steel components during part fabrication. Optical fibers were encapsulated in stainless steel 316L powders which were sintered at different fabrication conditions using SPS to investigate the effects of sintering parameters on the embedment. Measurements of optical transmittance, combined with microstructural analysis (X-ray computed tomography and scanning electron microscopy) and mechanical testing (tensile and microhardness), were conducted to examine the fiber functionality, fiber–matrix bonding quality, and properties of the sintered materials. The results show that under suitable fabrication conditions, intact optical fibers can be encapsulated in highly-densified (>98 % relative density) stainless steel components. These conditions also led to a good bond at the fiber–matrix interface with micron-sized material interdiffusion across the interface. The sintering parameters were observed to affect fiber optical attenuation, where high temperature, pressure, and hold time during SPS enhanced fiber–matrix bonding and adversely affected optical transmission. Tensile testing confirmed the superior tensile strength and ductility of the matrix fabricated by SPS. Furthermore, the materials exhibited limited strength reduction (∼70 MPa) upon the integration of fibers. This study demonstrates the effectiveness of SPS for fiber-material integration for high-temperature applications.

Original languageEnglish
Article number110188
JournalOptics and Laser Technology
Volume170
Early online dateOct 11 2023
DOIs
StatePublished - Mar 2024

Keywords

  • Embedding
  • Fiber Optic Sensor
  • Sensing
  • Spark plasma sintering
  • Structural health monitoring

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