Method and system for analyzing impurity content in oxide

By constructing a reference impurity database and using dynamic time warping technology, combined with a deep learning model, the problems of expensive equipment and complex operation in existing technologies have been solved, and efficient identification and concentration analysis of impurities in oxides have been achieved.

CN120913712APending Publication Date: 2025-11-07EASTERN GANSU UNIVERSITY
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Patent Information

Application Number
CN202511062774.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-07-31
Publication Date
2025-11-07

AI Technical Summary

Technical Problem

Existing technologies are expensive, complex to operate, and time-consuming to pre-process samples. They also have limited ability to identify complex background interference, resulting in low accuracy in impurity identification and concentration analysis.

Method used

By constructing a reference impurity database, fluorescence emission spectra of oxide impurity samples were collected using quantum dot fluorescent probes. Peak normalization, background noise removal, and filtering were performed. Combined with dynamic time warping and spectral difference weighted distance techniques, an event chain of the spectrum to be tested was constructed, and impurity analysis was performed using a deep learning model.

Benefits of technology

It improves the accuracy and robustness of feature extraction in spectral recognition under interference conditions, realizes integrated intelligent reasoning processing of impurity identification and concentration analysis, and improves the accuracy of impurity identification.

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Abstract

The invention relates to the field of oxide impurity analysis, in particular to a method and system for analyzing the content of impurities in oxide. The method comprises the following steps: setting oxide impurity samples, constructing a reference impurity database through the oxide impurity samples, and analyzing the reference impurity database to obtain a reference impurity data set; the method comprises the following steps: acquiring a to-be-detected spectrogram sequence of a to-be-detected oxide sample, analyzing the to-be-detected spectrogram sequence to obtain to-be-detected spectrogram subsequences, and constructing a to-be-detected spectrogram event chain; analyzing the spectrogram event chain to be detected to obtain a de-noised spectrogram event chain; analyzing the de-noised spectrogram event chain in combination with a reference impurity data set to obtain a matched impurity data set and an unmatched impurity data set of the to-be-detected oxide sample; and analyzing the matched impurity data set and the unmatched impurity data set to obtain an impurity analysis result of the to-be-detected oxide sample. According to the invention, the impurity identification precision can be improved.
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