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Plasma parameter diagnosis method based on BP neural network

A BP neural network and plasma technology, applied in the field of electromagnetism, can solve problems such as inability to fit curves

Pending Publication Date: 2021-11-16
XIAN UNIV OF TECH +1
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Problems solved by technology

This method can only obtain the electron density information of the rising edge of the double Gaussian distribution, and it cannot fit the complete curve, which has certain limitations.

Method used

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  • Plasma parameter diagnosis method based on BP neural network
  • Plasma parameter diagnosis method based on BP neural network
  • Plasma parameter diagnosis method based on BP neural network

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Embodiment Construction

[0036] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0037] see figure 1 , the present invention is a method for estimating and diagnosing plasma sheath electron density based on BP neural network, based on the principle that:

[0038] Firstly, the reflection coefficient amplitude and phase corresponding to different electron density distributions in the plasma are obtained by the HMM method, and according to the interval of the sampling frequency of 0.1GHZ, that is, the reflection coefficient amplitude and phase of 40 frequency points are a group of samples, which are respectively used as neurons. The characteristics of the network x1, x2; the plasma model with a sheath thickness of 15cm is divided into 100 layers, and the electron density distribution value corresponding to each layer is used as the label y. Based on the BP neural network gradient descent method, through the use of Adam opti...

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Abstract

The invention discloses a plasma parameter diagnosis method based on a BP neural network. The plasma parameter diagnosis method comprises the following steps: step 1, collecting data; step 2, preprocessing the data; step 3, importing and dividing the data; step 4, constructing a network model; step 5, training the model; and step 6, testing and evaluating the model Through an Adam gradient descent optimization algorithm, an adaptive learning rate adjustment strategy, cross validation and other methods, all frequency point information is fully utilized, a BP neural network is combined with the plasma electron density, and the electron density is estimated and diagnosed through the reflection coefficient amplitude and phase.

Description

technical field [0001] The invention belongs to the technical field of electromagnetism, and in particular relates to a plasma parameter diagnosis method based on a BP neural network. Background technique [0002] The "black barrier" phenomenon will lead to deterioration of communication quality, and in severe cases, communication interruption will affect the transmission quality and reliability of measurement and control communication signals. Studies have shown that the essential reason for the "black barrier" phenomenon is the attenuation of electromagnetic waves by the plasma sheath and the impact on the antenna system, resulting in a low signal-to-noise ratio of the signal entering the receiver, and the receiver cannot detect and extract the signal. cause interruption of signal transmission. In order to effectively solve the black barrier problem, it is necessary to study the electromagnetic wave propagation characteristics of the plasma sheath. First, it is necessary ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/08H05H1/00
CPCG06N3/08H05H1/0006
Inventor 刘江凡蒋菁焦子涵白光辉李铮高世琦席晓莉
Owner XIAN UNIV OF TECH
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