- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
To develop mobile calibration equipment for gamma-ray dose or dose rate meters in the field of radiation protection, a minitype reference radiation (MRR) of 0.5 m×0.5 m×0.5 m cube was set up and used for investigation. Two types, which add up to 12 daily used gamma-ray dose rate meters, were used as samples to determine the conventional true value of air kerma (CAK) at the point of test in the MRR. A gamma-ray spectrometer was also used to monitor the scattering gamma rays in the MRR, which were applied further to characterize the disturbance of scattering gamma ray in CAK determination. On the basis of the sample data sets of CAKs, scattering gamma spectra and air kerma values at the point of test without sample meters, a CAK prediction model at the point of test was developed by the least square support vector machine, which is a multiple nonlinear regression method. For reducing the amount of data and improving the regression efficiency, principal component analysis (PCA) was used to extract feature components from the scattering gamma-ray spectra before regression. A relative standard uncertainty of 4.65% was achieved in determining CAK in the MRR using the constructed prediction model.
This study showed the feasibility of determining the CAK of a calibrated dosimeter in a 0.5 m×0.5 m×0.5 m MRR. The technology developed in this study may provide a novel way to calibrate fixed and field dosimeters or calibrate dosimeters in a mobile way, which is equivalent to the method regulated in ISO 4037 series relied on an SRR and will meet in principle the regulation requirement of IEC-60846 for radiation protection instrumentation. Compared with a normal SRR, a small MRR has a weight of several hundred kilograms and dimension of less than 1 m. In an MRR, scattering gamma-ray spectra and their feature components can be used to characterize the probe's interference to the radiation field. PCA is an effective tool to extract scattering features from original scattering gamma-ray spectra. We believe that the use of more typical and large amount of sample dosimeters can enable to extract more representative feature components. Among the two types of CAK prediction models constructed by LS-SVM, SIPM had better CAK prediction accuracy than CIPM and it can reach the best value of 5% relative measurement error. The relative combined standard uncertainty of 4.65% was reached by evaluation, and it might be improved by further work. The scattering gamma-ray spectrum measurement, energy response errors of dosimeters, and their indication value errors are three primary elements influencing the measurement uncertainties, and there are possibilities to improve them in the future. However, much research needs to be conducted for some dosimeters, especially for those that significantly differ in the type, probe physical dimension, and shape from the sample dosimeters. Briefly, this study showed the feasibility of calibrating fixed or field dosimeters using an MRR, or a mobile way of calibrating dosimeters, which significantly differ from the normal calibration with a fixed SRR