In-situ XRF reading evaluation and screening method based on data structure

Abstract

The invention discloses an in-situ XRF reading evaluation and screening method based on a data structure. The method comprises the following steps: a) determining the detection limit of each element;b) performing in-situ measurement; c) standardizing all readings (readings / detection limits) with the respective detection limit of each element; d) segmenting the result of c) at certain intervals; e) counting the frequency of the reading of each section; f) drawing a data structure chart by taking the segmented intervals as abscissa and frequency as ordinate; and g) evaluating, screening and standardizing the data structure of each element reading according to the data structure of each element reading, the larger the data span interval is, the more suitable the measurement result is, and ifthe data structure of each element reading is only in one interval, the data distribution is centralized, and the measurement result should be carefully used for trend analysis. According to the method, rapid evaluation and screening of in-situ XRF readings can be realized, and an effective data processing scheme is provided for lithology description, mineral exploration, pollution investigationand other applications related to element concentration trend searching. The method is suitable for batch data processing of instruments with an in-situ XRF analysis function, such as a portable X-rayfluorescence analyzer (PXRF), a core scanner (ITRAX) and the like.

Description

technical field [0001] The invention belongs to the technical field of XRF data processing, and in particular relates to a method for evaluating and screening in-situ XRF readings based on a data structure. Background technique [0002] Based on good instrument performance, uniform sample state, ideal working environment, and adequate quality control measures, indoor XRF can give quantitative and accurate analysis and test results. In-situ XRF, such as portable XRF, core scanners equipped with XRF, etc., need to directly analyze solid and liquid substances such as rocks, soil, cultural relics, and wastewater without sample preparation process. On the one hand, it is non-destructive, in-situ, convenient, and efficient. On the other hand, there are shortcomings such as the test results are not as accurate as indoor XRF and the test results are difficult to evaluate effectively. At present, the evaluation of in-situ XRF results is mostly done by using it to measure powder samp...

AI Technical Summary

Problems solved by technology

In-situ XRF, such as portable XRF, core scanners equipped with XRF, etc., need to directly analyze solid and liquid substances such as rocks, soil, cultural relics, and wastewater without sample preparation process. On the one hand, it is non-destructive, in-situ, convenient, and efficient. On the other hand, there are also shortcomings such as the test results are not as accurate as indoor XRF and the test results are difficult to evaluate effectively.

At present, the evaluation of in-situ XRF results is mostly done by using it to measure powder samples returned from the laboratory, comparing the results of in-situ XRF and other laboratory methods, etc. However, this method has limitations: the range of in-situ XRF measurement is limited (millimeter or centimeter radius), while sampling and sending samples to the laboratory often get mixed results in a larger range. In the case of inhomogeneous samples to be tested, the results of the two may have large differences.

The detection effect of in-situ XRF on low-content samples is worse than that on high-content samples. For elements whose content is close to the detection limit, the in-situ XRF readings often have poor correctness and precision, and the content is 7 times higher or higher. For elements with 10 times the detection limit, even if the accuracy may be biased, the precision is usually high, which means that in-situ XRF has a relatively stable detection capability

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