Blasting scheme selection method based on neural network optimization genetic algorithm

A neural network and genetic algorithm technology, applied in the field of blasting plan selection based on neural network optimization genetic algorithm, can solve problems such as lack of theoretical basis and poor effect.
CN103778469AInactive Publication Date: 2014-05-07LIAONING TECHNICAL UNIVERSITY
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Patent Information

Authority / Receiving Office
CN ยท China
Current Assignee / Owner
LIAONING TECHNICAL UNIVERSITY
Publication Date
2014-05-07
Estimated Expiration
Not applicable ยท inactive patent

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Abstract

This invention discloses a blasting scheme selection method based on neural network optimization genetic algorithm and is characterized by using blasting impact factors and blasting hazard forms as an input value and an output value of the neural network to practice, and the practiced neural network is used as a fitness function for the genetic algorithm. The blasting impact factor include : blasthole (HL), spacing ((i)S( / i)), charge deepness ((i)B(i)), blocking deepness ((i)ST( / I)), specific charge ((i)PF( / i)), and hole drilling rate ((i)SD( / i)), and the blasting hazard forms include overbreak deepness ((i)B( / i)) and a distance of flying rocks ((i)FR( / i)). The genetic algorithm (GA) is used to find the best overbreak deepness ((i)B( / i)) and the distance of flying rocks ((i)FR( / i)) so as to optimize the blasting scheme parameters. The blasting scheme parameter optimization comprises data collection, fitness function construction based on genetic algorithm of ANN, blasting scheme parameter preference based on the genetic algorithm (GA) and determination of the final result of the blasting optimization scheme according to Pareto picture. The blasting scheme selection method can be widely applicable to the blasting scheme optimization selection during an exploitation of a strip mine.
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Description

Technical field

[0001] The invention involves An open -air mining blasting scheme selection, Especially involved Blasting scheme selection method based on neural network optimization of genetic algorithms. Background technique

[0002] The formulation of the blasting plan is an important part of mining work.The parameters in the plan are affected by many factors.The blasting schemes used in different mining areas are different, mainly to consider yield, geological conditions, physical mechanical properties of rocks, and groundwater environment.

[0003] The determination of blasting parameters should meet the requirements of security, technology and economic.No one will have serious accidents, of which ultra -explosive depth (BB) and flying stone distance (FR) (FR) (hereinafter referred to as ultra -explosive and flying stone) are one of the most common and dangerous accidents.The ultra -explosion is the phenomenon of blasting depth caused by inappropriate parameter settin...

Claims

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