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Gamma energy spectrum set analysis method for deducting background based on WTSVD algorithm

A technology for deducting background and analysis methods, applied in the field of measurement, to achieve the effects of good compatibility, high efficiency, and improved analysis efficiency

Active Publication Date: 2020-04-14
CHENGDU UNIVERSITY OF TECHNOLOGY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

All the above-mentioned methods aim at the energy spectrum itself, and use numerical calculation and analysis to process a single energy spectrum. However, there are a lot of uncertainties in the energy spectrum measurement process. How to minimize the uncertainty cannot be accomplished through a single energy spectrum measurement. of

Method used

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  • Gamma energy spectrum set analysis method for deducting background based on WTSVD algorithm
  • Gamma energy spectrum set analysis method for deducting background based on WTSVD algorithm
  • Gamma energy spectrum set analysis method for deducting background based on WTSVD algorithm

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Embodiment 1

[0028] like figure 1 and figure 2 As shown, a γ-energy spectral set analysis method based on the WTSVD algorithm to subtract the background includes the following steps:

[0029] S1. Grading according to the adaptive degree of wavelet transform;

[0030] S2, analyze the time domain and frequency domain of wavelet, judge whether there is artificial nuclide interference, if yes, then enter in step S3, if not, then directly enter in step S4;

[0031] S3. Eliminate data interfered by artificial nuclides, and perform supplementary measurements;

[0032] S4. Construct background training matrix B n×p , and decompose the wavelet by Mallat;

[0033] S5. Measure the gamma energy spectrum and construct the gamma energy spectrum set S;

[0034] S6. For background training matrix B n×p Perform SVD decomposition, that is, unitary matrix decomposition, to extract the principal component matrix U;

[0035] S7. Based on the principal component matrix U, denoise the power spectrum data...

Embodiment 2

[0037] like figure 1 and figure 2 Shown, present embodiment is on the basis of embodiment 1, and the Mallat decomposition formula in step S4 is:

[0038] f m (n)=∑ k h(2n-k)f m+1 (k)

[0039] d m (n)=∑ k g((2n-k)f m+1 (k)

[0040] where f 0 , identifies the original signal vector, f m (m=-1,-2,...,-M) is the approximation signal after decomposition, d m (m=-1,-2,...,-M)) is the decomposed detail signal, h and g are the impulse response sequence of the low-pass filter and the high-pass filter respectively.

Embodiment 3

[0042] like figure 1 and figure 2 Shown, present embodiment is on the basis of embodiment 1, and the decomposition formula in the step S6 is:

[0043]

[0044] (1) The wavelet transform has strong adaptability, can be graded, and has both time domain and frequency domain analysis, which can effectively judge artificial nuclide interference. When the background energy spectrum is interfered by artificial nuclide, the background measurement is eliminated and supplementary measurement is performed. , to construct the background training matrix B n×p , the present invention uses Mallat wavelet decomposition, such as figure 2 shown, where f 0 , identifies the original signal vector, f m (m=-1,-2,...,-M) is the approximation signal after decomposition, d m (m=-1,-2,...,-M) is the decomposed detail signal, and the operation formula is:

[0045] f m (n)=∑ k h(2n-k)f m+1 (k) (1)

[0046] d m (n)=∑ k g(2n-k)f m+1 (k) (2)

[0047] Here h and g are the impulse response ...

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Abstract

The invention discloses a gamma energy spectrum set analysis method for deducting a background based on a WTSVD algorithm. The gamma energy spectrum set analysis method comprises the following steps:S1, performing grading according to a wavelet transform adaptive degree; S2, analyzing the time domain and the frequency domain of the wavelet, judging whether artificial nuclide interference exists or not, if yes, entering the step S3, and if not, directly entering the step S4; S3, eliminating data interfered by artificial nuclide, and performing supplementary measurement; S4, constructing a background training matrix Bn * p, and decomposing the wavelet through Mallat; S5, measuring a gamma energy spectrum, and constructing a gamma energy spectrum set S; S6, performing SVD decomposition, namely unitary matrix decomposition, on the background training matrix Bn * p, and extracting a principal component matrix U; and S7, performing noise reduction on the energy spectrum data set S through bit operation based on the principal component matrix U to obtain a noise reduction energy spectrum set D. The influence of artificial nuclide on the background energy spectrum is accurately reduced through wavelet transform analysis.

Description

technical field [0001] The invention relates to the field of measurement technology, in particular to a gamma energy spectral set analysis method based on WTSVD algorithm to subtract background. Background technique [0002] The processing of gamma energy spectrum data is an important prerequisite for energy spectrum analysis. Due to the inherent statistical fluctuations of gamma rays and radiation detectors and the influence of electronic noise, gamma energy spectrum data has large statistical fluctuations. The noise reduction methods for energy spectrum data generally include the center of gravity method and the least squares fitting method (Chen Liangbo, Zheng Yaqing. Research on curve fitting based on the least squares method[J]. Atomic Energy Science and Technology, 2012,11(5):52-55.) , Gaussian function method (Zhong Wenfeng, Zhou Shumin. Application research and implementation of smoothing in spectrum analysis [J]. Intelligent Computer and Application, 2013,3(3):72-74...

Claims

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Application Information

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IPC IPC(8): G06F17/14G06F17/16G01T1/36
CPCG06F17/148G06F17/16G01T1/36Y02E30/30
Inventor 曾晨浩赖万昌冯孝杰范晨陈杰毫
Owner CHENGDU UNIVERSITY OF TECHNOLOGY
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