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An online monitoring method of dioxin emissions based on neural network

A neural network and neural network model technology, applied in the field of online monitoring of dioxin emissions based on neural network, can solve the problem of lack of clear correlation between dioxin concentration and toxic equivalent, inability to provide accurate and reliable results, and insufficient generalization ability of the model To achieve the effect of improving generalization ability and accuracy, ensuring data timeliness, and realizing real-time monitoring

Active Publication Date: 2021-10-01
ZHEJIANG UNIV
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AI Technical Summary

Problems solved by technology

Dioxins are trace pollutants and difficult to detect
The input features of these soft-sensing methods are not directly related to dioxin production and have no clear and stable correlation with dioxin concentration and toxic equivalents, which makes the generalization ability of the model insufficient to provide accurate and reliable results

Method used

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  • An online monitoring method of dioxin emissions based on neural network
  • An online monitoring method of dioxin emissions based on neural network
  • An online monitoring method of dioxin emissions based on neural network

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Embodiment

[0063] Such as image 3 A neural network-based online monitoring method for dioxin emissions is shown, which uses thermal desorption gas chromatography coupled with tunable laser time-of-flight mass spectrometry to detect the concentration of dioxin indicators online, and combines the neural network model to predict dioxin emissions; Among them, the specific construction steps of the neural network model are as follows:

[0064] Step 1: Build a database; collect and analyze dioxin emissions at the end of the solid waste incineration system, and detect single congeners of chlorobenzene and chlorophenol as dioxin indicators. The specific process includes the following points:

[0065] S1: Use EPA23a method to detect dioxin emission data, as the original data,

[0066] y=[y 1 ,y 2 ,y 3 ...y n ];

[0067] Among them, y represents the dioxin concentration or dioxin toxic equivalent, and y n Indicates the nth sample of dioxin concentration or dioxin toxic equivalent.

[0068...

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Abstract

A neural network-based online monitoring method for dioxin emissions, belonging to the field of environmental protection technology, including a neural network model and thermal desorption gas chromatography coupled with tunable laser time-of-flight mass spectrometry, said thermal desorption gas chromatography coupled with tunable laser time-of-flight Mass spectrometry detects the concentration of dioxin indicator on-line, and the neural network model receives the concentration of dioxin indicator, and outputs the predicted value of dioxin concentration or dioxin toxic equivalent; the present invention uses the neural network model and thermal desorption gas chromatography The combination of coupled tunable laser time-of-flight mass spectrometry online detection can realize real-time monitoring, effectively reduce costs, ensure data timeliness, and at the same time, improve the generalization ability and accuracy of the original correlation model while ensuring the training speed.

Description

technical field [0001] The invention belongs to the technical field of environmental protection, and in particular relates to an online monitoring method for dioxin discharge based on a neural network. Background technique [0002] The solid waste incineration process will produce and discharge a large amount of organic pollutants, among which dioxin is one of the pollutants most concerned by the public because of its strong carcinogenicity, teratogenicity and mutagenicity. Dioxins are trace pollutants that are difficult to detect. The currently internationally recognized method for the detection of dioxins is the use of isotope dilution high-resolution gas chromatography coupled with high-resolution mass spectrometry. However, this method covers complex sample collection and sample pretreatment processes, and has disadvantages such as high economic cost and high time lag, which limits the number of detections and cannot truly reflect the emission level of dioxins and the o...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/06G06N3/04G06N3/08G06Q50/26
CPCG06Q10/06393G06N3/08G06Q50/26G06N3/045
Inventor 陆胜勇陈垦李晓东彭亚旗严建华
Owner ZHEJIANG UNIV
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