Real-time prediction method of mine gas concentration in short and medium terms based on radial basis function neural network integration

A gas concentration, neural network technology, applied in mining installations, mining equipment, earthwork drilling, etc., can solve problems such as prediction failure and affecting model prediction accuracy.

Inactive Publication Date: 2011-02-16
ZHONGBEI UNIV
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Problems solved by technology

Gas concentration information is continuously collected and transmitted. If the offline prediction model cannot be corrected and

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  • Real-time prediction method of mine gas concentration in short and medium terms based on radial basis function neural network integration
  • Real-time prediction method of mine gas concentration in short and medium terms based on radial basis function neural network integration
  • Real-time prediction method of mine gas concentration in short and medium terms based on radial basis function neural network integration

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Embodiment Construction

[0064] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments (see figure 1 ).

[0065] The first step is to arrange the gas wireless monitoring sensors in front of the coal wall, on the mining equipment and on the operators to reflect the real situation of the gas emission at the front of the working face during the continuous movement of the excavator, and set them 50 to 100 meters away The mobile base station receives the gas concentration information and transmits the gas concentration to the historical database X of the ground monitoring system through the underground communication network lib ,Have

[0066] X lib ={x i |i=1,2,...,l}(l=n+2p) (1)

[0067] In the second step, according to the Takens theorem, for the appropriate embedding dimension m and time delay τ, the "trajectory" of the reconstruction space in the embedding space is dynamically equivalent to the original system in the sense of dif...

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Abstract

The invention discloses a real-time prediction method of mine gas concentration in short and medium terms based on radial basis function neural network integration. The method comprises the following steps of: taking mine gas concentration data as a chaotic time series to construct a plurality of prediction sub-models of radial basis function (RBF) neural networks, and taking a weighted mean of synchronous prediction results of all prediction sub-models as an integrated prediction value to realize prediction model initializtion of RBF neural network integration; then realizing prediction of the gas concentration in the range of from a short term to a medium term through setting an integrated capacity parameter (the integrated capacity parameter is also equal to an RBF network prediction step-length); and obtaining a new prediction sub-model by utilizing an incremental training mode aiming at the characteristics that gas concentration information is continuously collected, and realizing updating of the RBF neural network integration according to a first in first out queue sequence so as to improve real-time prediction precision of the gas concentration, therefore, a proper compromise can be obtained between prediction range and prediction precision requirements, and the technical requirement on a mine gas information management system is satisfied.

Description

technical field [0001] The invention belongs to the field of mine gas concentration prediction. In view of the real-time performance of a mine gas concentration monitoring system and the short-term to medium-term prediction requirements, the invention particularly relates to a medium- and short-term real-time prediction of mine gas concentration based on radial basis function neural network integration technology. method. Background technique [0002] The National "Energy Medium and Long-term Development Plan Outline (2004-2020)" determined that China will "adhere to an energy strategy with coal as the theme, electricity as the center, and comprehensive development of oil and gas and new energy." Obviously, coal and coal industry are still my country's energy themes and basic industries. With the growth of my country's demand for energy, coal production has also increased rapidly, bringing considerable economic benefits to the coal industry. However, accidents are frequent ...

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Application Information

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IPC IPC(8): E21F17/18
Inventor 孟江安坤
Owner ZHONGBEI UNIV
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