Study On Numerical Simulation Of Blasting And Deep-hole Blasting Parameter Optimization In Underground Sedimentary Rock Mine

Wulagen lead-zinc is a rare and large sedimentary type mine in domestic mines, whichmainly adopts non-pillar sublevel caving mining method. Due to the stratabound lead-zincdeposit sand rocks, poor geological condition, weak ore-bearing rock physical and mechanicalproperties, the mud and calcium cementation joint fissure development between rock particlesmade the complex geological conditions and the mining condition is also pretty complicated.Meanwhile, the blasting parameters of fan-shaped deep-hole in preliminary mining design hasmany problems with the actual production situation. Failed to adjust the blasting parameterstimely in different area, which leads to poor blasting effect and the ore block can not meet therequirement, when the front holes blasting would badly damage the back holes and makes thesubsequent holes difficult to charge, which causes low efficiency and high cost of the blasting,even lead some security problems such as roof fall accident. At the same time, ore-drawingonly by experience and the disorder management during the ore-drawing process, whichresult serious ore dilution loss. In order to achieve the5000t/d production plan, this paperfully grasp the basic geological conditions and economic conditions of mining technology inthe wulagen lead-zinc deposit, combined industrial experiments with the theory of BP neuralnetwork to establish a mode in optimizing blasting parameters and reducing blasting cost, andthen use the technology of numerical simulation in blasting to study the optimized blastingparameters and guide blasting mining process. The main contents and conclusions are asfollows:Crushing mechanism of fan-shaped deep-hole blasting have analyzed based on thetheory of broken rock blasting. Carried out the standard cast blasting funnel test under theconditions of mining geological conditions and technical level, initially identified theexplosives consumption is0.84kg/m3.On the basis of the standard cast blasting funnel test, it have carried out the orthogonalindustrial test to determine the actual explosive consumption, row space, bottom of the holespace and ore caving interval. The various parameters are roughly determined through the test,how to adjust the blasting parameters in different lithology areas has also been cleared.Due to the BP neural network’s powerful nonlinear mapping, good fault tolerance andstrong adaptive capacity, through the blasting parameters determined by above tests, based on the BP neural network to establish a control and forecast model to make the blastingparameters of non-pillar sublevel caving mining method have a further optimization. Takingfully considered of input and output in the optimization model, which makes the model fullyreflected the influence of the blasting parameters on blasting property. Through training andoptimizing forecast, the model meets the requirement of optimization prediction, and finallyachieved the excellent blasting parameters.Using ANSYS/LS-DYNA explosion simulation technology to reproduce and study thestress wave and blasting mechanism characteristics of hole-mouth priming, hole-bottompriming and hole-bottom delay blasting, which under the optimized blasting parameters. Thethree different initiation modes of simulation have verified that optimized blasting parametersis scientific.