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Real-time signal processing for sub-THz range grating-based distributed fiber sensing.

Zheyi Yao1, Tao Wei1, Gerald Hefferman2

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Summary
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This study introduces a novel computing architecture to accelerate distributed optical fiber sensor data processing. The new design enables real-time sensing applications by significantly reducing processing time and data storage needs.

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Area of Science:

  • Optoelectronics and Sensor Technology
  • High-Performance Computing
  • Signal Processing

Background:

  • Distributed optical fiber sensors are valuable for collecting strain and temperature data.
  • Large data volumes generated by these sensors hinder real-time applications.
  • Existing methods face challenges in processing speed and data management.

Purpose of the Study:

  • To develop a parallel and pipelined computing architecture for accelerating signal processing in sub-terahertz fiber sensor arrays.
  • To enable real-time sensing and control applications by overcoming data processing limitations.
  • To maintain high spatial resolution during data acquisition.

Main Methods:

  • Implementation of a parallel and pipelined computing architecture on a field-programmable gate array (FPGA) chip.
  • Design focused on high-speed signal processing for sub-terahertz fiber sensor arrays.
  • Elimination of the need for storing raw or intermediate data.

Main Results:

  • The implemented computing architecture achieved signal processing for the entire array in just 12 system clock cycles.
  • High spatial resolution was maintained throughout the processing.
  • The design successfully removed the requirement for storing large datasets.

Conclusions:

  • The developed computing architecture significantly enhances the processing speed of distributed optical fiber sensors.
  • This advancement facilitates the expansion of real-time, in situ sensing and control applications.
  • The FPGA-based solution offers an efficient and data-storage-free approach for fiber sensor data processing.