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Research of Carborne γ-Ray Energe Spectrum Radiation Dose Rate Based on FFT-BP Network Model |
XU Li-peng1, 2, GE Liang-quan1*, DENG Xiao-qin2, CHEN Li2, ZHAO Qiang2, LI Bin2, WANG Liang2 |
1. College of Nuclear Technology and Automation Engineering,Chengdu University of Technology,Chengdu 610059,China
2. Sichuan Management and Monitoring Center Station of Radioactive Environment,Chengdu 611139,China
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Abstract In order to measure the radiation dose rate accurately with carborne γ spectrometer patrol system, proposed a modified back-propagation network(BP network) model basised on fast fourier transform background deduct method(FFT-BP network model). Using γ-ray energy spectrum analysis method to test the carborne γ-ray energe spectrum of Cs-137 of different spacings, adopting FFT method to deduct the background of spectrum data then get new spectrum data. The modified B-P network model is applied to qualitatively predict the radiation dose rate of unknow dose carborne γ spectrum, by comparing the predicted results with fitting results of 3 function models to verify the effect of FFT-BP network model. The results show the FFT deduct method can weaken the influence of the scattering background on γ spectrum and reduce spectrum background effectively. The correlation coefficients between characteristic peak area and net area getting from new spectrum are 0.99 (p<0.05), which shows a remarkable correlation. In the process of model fitting, FFT-BP network model shows strong ability of learning and generalization, the prediction of experimental results is ideal, relative error and accumulative error are below 0.6% and 9% respectively, it has better effect than mathematical methods and gamma spectra method and it also can reduce the error of radiation dose rate analized by γ-spectra analysis method, improve the work efficiency effectively. There fore, FFT-BP network model can apply to predictive analysis of γ-ray energy spectrum radiation dose, which provide a new and efficient method for carborne γ spectrometer patrol system to measure radiation dose.
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Received: 2017-05-04
Accepted: 2017-09-24
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Corresponding Authors:
GE Liang-quan
E-mail: glq@cdut.edu.cn
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