An edible oil transverse relaxation signal feature extraction method based on a 2D-CNN

A technology of transverse relaxation and signal characteristics, which is applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve the problems affecting the classification results and the generation of invalid features, and achieve fast time, good robustness, and calculation accuracy high effect

Active Publication Date: 2019-06-18
UNIV OF SHANGHAI FOR SCI & TECH
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Problems solved by technology

However, in the inversion process, invalid features may be generated due to different

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  • An edible oil transverse relaxation signal feature extraction method based on a 2D-CNN
  • An edible oil transverse relaxation signal feature extraction method based on a 2D-CNN
  • An edible oil transverse relaxation signal feature extraction method based on a 2D-CNN

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[0034] According to the attached Figure 1 to Figure 5 , give a preferred embodiment of the present invention, and give a detailed description, so that the functions and characteristics of the present invention can be better understood.

[0035] see figure 1 , a kind of 2D-CNN-based edible oil transverse relaxation signal feature extraction method of the embodiment of the present invention, comprises the steps:

[0036] S1: Read the CPMG raw data collected by the low-field nuclear magnetic resonance equipment, and invert the CPMG raw data to obtain the inversion data.

[0037] S2: Preprocess the CPMG original data and inversion data respectively.

[0038] Wherein, the S2 step further includes the steps of:

[0039] S21: Judging the complete decay time of the transverse relaxation decay curves of different types of edible oils in the CPMG raw data, taking the maximum complete decay time as the cut-off time to intercept all CPMG raw data, and for signals that decay before the...

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Abstract

The invention provides an edible oil transverse relaxation signal feature extraction method based on a 2D-CNN. The method comprises the following steps: S1, reading CPMG original data, and carrying out inversion to obtain inversion data; S2, respectively preprocessing the CPMG original data and the inversion data; S3, drawing a transverse relaxation attenuation curve and a multi-component relaxation spectrum; S4, constructing a two-dimensional convolutional neural network; S5, extracting data from the self-transverse relaxation attenuation curve and the multi-component relaxation spectrum to form a training set and a test set; S6, inputting the training set into a two-dimensional convolutional neural network; S7, inputting the test set into the trained two-dimensional convolutional neuralnetwork; And S8, obtaining a classification result. 2D-based method of the invention According to the CNN edible oil transverse relaxation signal feature extraction method, edible oil transverse relaxation is directly subjected to feature extraction and classification through the two-dimensional convolutional neural network model, ineffective features can be effectively prevented from being generated, and the accuracy of a classification result is guaranteed.

Description

technical field [0001] The invention relates to the field of deep learning and nuclear magnetic resonance signal processing, in particular to a 2D-CNN-based feature extraction method for lateral relaxation signals of edible oil. Background technique [0002] The safety of edible oil has become a common topic of concern to the common people. However, due to the lack of an accurate, simple and rapid detection method for the authenticity of edible oils, the quality and safety of edible oils still presents a state of repeated prohibitions. Traditional and effective detection methods are not only expensive, but also complicated to operate and maintain. Therefore, the establishment of an accurate, simple and rapid detection method to identify the authenticity of edible oil provides technical support for law enforcement officers, which will help speed up the formulation and improvement of national standards for edible oil, prevent the occurrence of edible oil quality and safety is...

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Application Information

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IPC IPC(8): G06K9/00
Inventor 侯学文苏冠群王广利王欣聂生东
Owner UNIV OF SHANGHAI FOR SCI & TECH
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