Journal of Spectroscopy (Jan 2023)

Nonlinear Correction Methods of Temperature-Caused Peak Shift for a NaI(Tl) Gamma-Ray Spectrometer

  • Jinfei Wu,
  • Juan Zhai,
  • Wanchang Lai,
  • Hongjian Lin,
  • Chenhao Zeng,
  • Runqiu Gu,
  • Shaoqin Li,
  • Yunrui Jiang,
  • Jie Shi,
  • Bo Zhang

DOI
https://doi.org/10.1155/2023/1590667
Journal volume & issue
Vol. 2023

Abstract

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NaI(Tl) detectors are frequently operated under unstable temperature conditions when used in an open environment. Temperature changes would result in a peak shift and spectral distortion during measurement. Two easy-to-implement methodologies are proposed to stabilize the measured spectrum without the necessity of adjusting the gain, which are a correction algorithm for temperature-caused peak-shift based on multiple characteristic peak area weighting factors and an interpolation correction algorithm based on multicharacteristic peak sequence. Both of them can be used when the relative channel displacement of characteristic peaks in the spectrum due to temperature changes is not constant. Experimental data obtained under controlled temperature conditions in the laboratory were adopted to correct a spectrum, with joint consideration of some known characteristic peaks, such as 40K, U (214Bi), or Th (208Tl) peaks. Through constructing a reversible temperature coefficient matrix, one can easily obtain the coefficients of the n-th polynomial describing the influence of temperature on peak position, which presents their nonlinear mathematical relationship. Then, corrections of these two effects can also be easily calculated. Comparing the experimental results, peak positions before and after correction, it is proved that the interpolation correction algorithm based on multicharacteristic peak sequence has better correction accuracy, but the temperature-caused peak shift correction algorithm based on the multicharacteristic peak area weighting factor has a shorter calibration time.