Research On Cutting And Fracture Performance Of Different Cutter On Coals And Rocks

Coal is the main source of energy for daily living and labor in China,Which is a significant material for the production and development of heavy and light industries.The level of excavation of domestic coal resources is increasing with the development of technology and time.More and more coal mines face greater mining pressures,threatening the safety of coal mining and development.The nature and structure of coal and rock mass are the main causes of coal and rock mass damage.During the mining process,the stress state of coal and rock masses changes as the mining process progresses.Therefore,in order to research the feasibility of exploiting deep resources,testing the strength characteristics of coal and rock mass is essential to prevent and control coal mine disasters as much as possible.As coal mining continues,the environmental conditions around coal and rock masses are becoming more complex.The dynamic instability of coal and rock mass is a very significant topic in rock and soil mechanics.Nonlinear dynamic process is very complicated.Coal rock is not only affected by external normal stress and shear stress,but also the internal mechanical properties of coal rock play a crucial role in the microscopic level of its internal properties.Therefore,tensile strength simulation,uniaxial compressive strength simulation and triaxial compressive strength simulation are needed to reveal their micromechanical structural properties.The coal and rock mass is soft and brittle.At present,the domestic simulation stage has relatively few simulation analysisof coal and rock mass.The calculation of coal rock mass stability plays a crucial role in coal mining.The dynamic instability analysis of coal and rock mass provides a guiding direction for the safety aspect of coal mining.Tensile strength simulation,uniaxial compressive strength simulation and triaxial compressive strength simulation can provide theoretical and experimental basis for it,which is helpful to observe the microstructure of coal and rock mass and understand its strength and deformation mechanism.On this basis,the simulation method of cutting coal samples with knife-shaped picks was explored.By cutting and analyzing the cutting performance and load bearing characteristics of the tool under different linear cutting speeds,installation angles and cutting depths.The average and standard deviation of the cutting resistance assumed by the pick during this process were studied,and the optimal solution was selected.The cutting specific energy consumption changes with the cutting depth by calculating the volume of the coal wall particles intercepted by the cutting blade under different cutting depths under the same conditions.Studies have shown that as the depth of cut increases,the cutting energy consumption will continue to increase.On this basis,an entire simulation process of the broken rock of the disc hob is obtained through analysis,and the reasonable optimization simplifies the process of rolling the rock by the hob.Considering the friction of the hob,the rolling-cut rock mass model is established by the particle-shaped discrete element method.The results show the curves of rolling force,lateral force and normal force.The rock breaking characteristics of the disc hob are analyzed,and the rock breaking characteristics of the disc hob at different penetration degrees and different cutting speeds are discussed.The variation law of the rolling cutting simulation process is analyzed.The law is obtained by calculating the specific energy consumption of the disc hob at different penetration degrees and different cutting speeds.By analyzing and comparing,the best rock crushingrock is obtained.Penetration and cutting speed.Three neural networks(BP,ELM,RBF)were introduced to construct the model,and the appropriate function training simulation was selected.Part of the data obtained by particle flow simulation was intercepted,and the normal force of the disk hob was predicted,and several groups of nodes were randomly selected.Compare the error.According to the research on the prediction results,the ELM extreme learning machine has higher prediction accuracy.It can provide predictive analysis for test or simulation models,verify its correctness,and has certain guiding significance.