X-ray fluorescence spectrum quantitative analysis method based on LM-BP neural network

A technique of fluorescence spectroscopy and neural network, applied in neural learning methods, biological neural network models, material analysis using wave/particle radiation, etc., can solve problems such as unsatisfactory results

Inactive Publication Date: 2014-05-14
BEIJING RES CENT FOR AGRI STANDARDS & TESTING
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However, due to the constraints of the matrix effect and self-absorption effect, the accuracy of the predict

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  • X-ray fluorescence spectrum quantitative analysis method based on LM-BP neural network
  • X-ray fluorescence spectrum quantitative analysis method based on LM-BP neural network
  • X-ray fluorescence spectrum quantitative analysis method based on LM-BP neural network

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[0044] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0045] see figure 2 , the embodiment of the present invention provides a method for quantitative analysis of X-ray fluorescence spectrum based on LM-BP neural network, the method includes the following steps:

[0046] Step 101: collect the X-ray fluorescence spectrum of the training set sample, perform spectral data processing on it, and extract several data point intensity values ​​of a single spectral line of the X-ray fluorescence spectrum after processing...

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Abstract

The invention provides an X-ray fluorescence spectrum quantitative analysis method based on an LM-BP neural network. The method comprises the following steps: acquiring an X-ray fluorescence spectrum of a training set sample, performing spectrum data treatment, and extracting intensity values of a plurality of data points in a single spectral line after the treatment; measuring the content of corresponding target elements of the training set sample; with the intensity values as input layer data and the content of the corresponding target elements as output layer data, acquiring hidden layer data according to a transfer function of an input layer and a hidden layer so as to build a BP neural network model; training the BP neural network model by an LM algorithm; and acquiring the content of the corresponding target element of a prediction set sample by virtue of the trained LM-BP neural network model. The method can be used for performing quantitative analysis on elements by virtue of the X-ray fluorescence spectrum based on the LM-BP neural network.

Description

technical field [0001] The invention relates to the technical field of X-ray fluorescence spectrum detection, in particular to an X-ray fluorescence spectrum quantitative analysis method based on an LM-BP neural network. Background technique [0002] As a kind of atomic emission spectroscopy, X-ray Fluorescence Spectroscopy (XRF) is widely used in element determination. X-ray fluorescence spectroscopy uses X-rays to excite the outer electrons of elements, uses a spectrometer to obtain the fluorescence spectrum during electronic transitions, and conducts qualitative and quantitative analysis based on the energy and intensity of the spectral lines. [0003] X-ray fluorescence spectroscopy detection technology has the advantages of fast analysis speed, wide range of detection elements, simple pre-treatment, and non-destructive testing. It has been widely used in the detection of heavy metals in metallurgy, geology, petroleum and other fields, and has achieved extensive social a...

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Application Information

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IPC IPC(8): G01N23/223G06N3/08
Inventor 陆安祥王纪华李芳田晓琴付海龙
Owner BEIJING RES CENT FOR AGRI STANDARDS & TESTING
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