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<p>Energy resolution calibration is crucial for gamma-ray spectral analysis, as measured using a scintillation detector. A locally constrained regularization method was proposed to determine the resolution calibration parameters. First, a Monte Carlo simulation model consistent with an actual measurement system was constructed to obtain the energy deposition distribution in the scintillation crystal. Subsequently, the regularization objective function is established based on weighted least squares and additional constraints. Additional constraints were designed using a special weighting scheme based on the incident gamma-ray energies. Subsequently, an intelligent algorithm was introduced to search for the optimal resolution calibration parameters by minimizing the objective function. The most appropriate regularization parameter was determined through mathematical experiments. When the regularization parameter was 30, the calibrated results exhibited the minimum RMSE. Simulations and test pit experiments were conducted to verify the performance of the proposed method. The simulation results demonstrate that the proposed algorithm can determine resolution calibration parameters more accurately than the traditional weighted least squares, and the test pit experimental results show that the <i>R</i>-squares between the calibrated and measured spectra are larger than 0.99. The accurate resolution calibration parameters determined by the proposed method lay the foundation for gamma-ray spectral processing and simulation benchmarking.</p>

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Gamma-ray spectral energy resolution calibration based on locally constrained regularization for scintillation detector response: methodology, numerical, and experimental analysis

  • 期刊论文

  • 发表日期：

    2025年2月25日

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  • Guo-Feng Yang,
  • Wen-Zheng Peng,
  • Dong-Ming Liu,
  • Xiao-Long Wu,
  • Meng Chen,
  • Xiang-Jun Liu

摘要

Energy resolution calibration is crucial for gamma-ray spectral analysis, as measured using a scintillation detector. A locally constrained regularization method was proposed to determine the resolution calibration parameters. First, a Monte Carlo simulation model consistent with an actual measurement system was constructed to obtain the energy deposition distribution in the scintillation crystal. Subsequently, the regularization objective function is established based on weighted least squares and additional constraints. Additional constraints were designed using a special weighting scheme based on the incident gamma-ray energies. Subsequently, an intelligent algorithm was introduced to search for the optimal resolution calibration parameters by minimizing the objective function. The most appropriate regularization parameter was determined through mathematical experiments. When the regularization parameter was 30, the calibrated results exhibited the minimum RMSE. Simulations and test pit experiments were conducted to verify the performance of the proposed method. The simulation results demonstrate that the proposed algorithm can determine resolution calibration parameters more accurately than the traditional weighted least squares, and the test pit experimental results show that the R-squares between the calibrated and measured spectra are larger than 0.99. The accurate resolution calibration parameters determined by the proposed method lay the foundation for gamma-ray spectral processing and simulation benchmarking.