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Fast γ Photon Imaging for Inner Surface Defects Detecting.

Min Yao1,2, Guangdong Luo1,2, Min Zhao1,2

  • 1College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.

Sensors (Basel, Switzerland)
|December 10, 2021
PubMed
Summary
This summary is machine-generated.

A novel gamma-ray imaging method detects internal defects in complex structures. Combining filtered back projection and maximum likelihood expectation maximization algorithms improves imaging speed and accuracy for structural integrity monitoring.

Keywords:
field-programmable gate arrayimage reconstructioninternal defect detectioniteration algorithmpositron emission computed tomography

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Area of Science:

  • Non-destructive testing
  • Advanced imaging techniques
  • Materials science

Background:

  • Limited effective methods for internal defect detection in complex structures.
  • Need for robust techniques with strong penetration and anti-interference capabilities.

Purpose of the Study:

  • Propose a new gamma-ray based measurement method for inner surface defect detection.
  • Develop and validate advanced image reconstruction algorithms for improved accuracy and speed.
  • Adapt algorithms for FPGA implementation for real-time defect analysis.

Main Methods:

  • Utilized positron emission computed tomography (PET) principles for gamma-ray detection.
  • Combined filtered back projection (FBP) with maximum likelihood expectation maximization (MLEM) for image reconstruction.
  • Developed a back projection maximum likelihood (BPML) algorithm optimized for Field-Programmable Gate Arrays (FPGAs).

Main Results:

  • Achieved reduced iteration counts for image reconstruction with comparable quality.
  • Successfully implemented and tested the BPML algorithm on an FPGA.
  • Demonstrated effective edge detection and defect recognition on reconstructed inner images.

Conclusions:

  • The proposed gamma-ray imaging method offers a viable solution for internal defect detection.
  • The hybrid FBP-MLEM and FPGA-adapted BPML algorithms enhance detection efficiency and speed.
  • Experimental validation confirms the method's effectiveness and the FPGA's performance for structural monitoring.