Unlock instant, AI-driven research and patent intelligence for your innovation.

Mine ventilation system fault judging method based on hereditary neural network

A genetic neural network and ventilation system technology, applied in the field of fault judgment of mine ventilation system, can solve problems such as influence and incomplete information

Inactive Publication Date: 2010-11-24
NORTHERN ENG & TECH CORP MCC
View PDF0 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although various information of the mine ventilation system can be obtained through various means, the information provided by these limited real-time monitoring data is incomplete and affected by many factors

Method used

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
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Mine ventilation system fault judging method based on hereditary neural network
  • Mine ventilation system fault judging method based on hereditary neural network
  • Mine ventilation system fault judging method based on hereditary neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] The specific implementation manner of the present invention will be further described below in conjunction with the accompanying drawings.

[0028] like figure 1 , 2 Shown, the mine ventilation system fault judgment method based on genetic neural network of the present invention is characterized in that:

[0029] 1) According to the analysis and collation of the original data of the mine ventilation system and combined with the index system of the mine ventilation system, a three-layer backpropagation neural network fault judgment model (BP) composed of input layer, hidden layer and output layer was established (see figure 2 ),

[0030] 2) Initialize the neural network,

[0031] 3) Use 100 instance samples to train the neural network, and use the other 3 samples for instance verification,

[0032] 4) The sample acts on the input layer and is input from the input layer to the hidden layer, and the output of each unit of the hidden layer is input to the output layer,...

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

PUM

No PUM Login to View More

Abstract

The invention relates to the mine ventilation system fault judging technical field, in particular to a mine ventilation system fault judging method based on hereditary neural network. According to original data analysis and arrangement on the mine ventilation system and combing with the index system of mine ventilation system, a three-layer backpropagation neural network fault judging model (BP) composed of an input layer, a hidden layer and an output layer is established, neural network is initialized, example sample is used for training the neural network, sample acts on the input layer, is input into the hidden layer and output layer, errors of each unit output by each unit of the output layer are checked, weight number correction is carried out according to the error, whether the error is less than the specified value or not is judged, if yes, result is output, if not, next cycle is started. Network training is successful if security level of verification sample conforms with the reality. The weight number of network of the invention is adjusted by error feedback, and the actual output is closer to the expected output by continuous correction of weight number.

Description

technical field [0001] The invention relates to the technical field of mine ventilation system fault judgment, in particular to a mine ventilation system fault judgment method based on a genetic neural network. Background technique [0002] The safety state of the mine ventilation system is closely related to the operating state and changes of other systems in the mine. It is an important production auxiliary system that determines the safety of mine production in the entire mine. The operating characteristics and status of the mine ventilation system are directly related to the operation and safety status of the entire mine. Although various information of the mine ventilation system can be obtained through various means, the information provided by these limited real-time monitoring data is incomplete and affected by many factors. Therefore, the mine ventilation system is a complex non-sufficiency problem, and its fault judgment is a wide-ranging and comprehensive work. I...

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

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06F19/00G06N3/10
Inventor 张斌梁琼孙海涛
Owner NORTHERN ENG & TECH CORP MCC