Cement chimney NOX prediction method based on multivariable time sequence deep network model

A deep network and prediction method technology, applied in biological neural network models, neural learning methods, special data processing applications, etc., can solve problems such as reducing the accuracy of prediction models, achieve good prediction of NOX content in chimneys, reduce variable dimensions, and enhance essence The effect of a characteristic's ability
CN113268871AActive Publication Date: 2021-08-17YANSHAN UNIV
6 Cites 1 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
YANSHAN UNIV
Publication Date
2021-08-17

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention discloses a cement chimney NOX prediction method based on a multivariable time sequence deep network model. The method comprises the following specific steps: selecting 13 variables as input variables of cement chimney NOX prediction according to a cement NOX generation mechanism, a denitration process and an emission flow process, and uniformly carrying out normalization processing on a multivariable time sequence; then establishing a deep learning LSTM (Long Short Term Memory)-based feature reconstruction model to perform essential feature extraction of the NOX generation process according to features of a multivariable time sequence expressed in a time domain in the cement NOX generation process; establishing a cement chimney NOX prediction model (MT-LSTMs) based on a multivariable time sequence long-short term neural network (LSTM) according to the overall process flow of NOX of the cement chimney; determining the initial parameters of the model and performing forward training on the network model, then training the model by utilizing network dominant cost function error reverse fine tuning, and optimizing model parameters through error correction.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The invention relates to the field of cement chimney NOX prediction, in particular to a cement chimney NOX prediction method based on a multivariate time-series deep network model. Background technique

[0002] my country is the world's largest cement producer, accounting for more than 60% of the world's total cement production. Since the localization of new dry process cement production lines in the 1990s, my country's cement production scale has expanded rapidly. The fuel calcination in cement factories is mainly coal-fired, causing the air to be polluted by gases such as nitrogen oxides or sulfur dioxide. With the continuous increase of coal burning, my country's air pollution is not optimistic. In order to alleviate the air pressure, the concentration of NOX emission in the cement industry has dropped from 800mg / Nm3 to 400mg / Nm3. From this, it can be seen that my country's NOX emission requirements for cement plants are becoming more and more stri...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More