CN112228083B - Rock breaking path selection method for small-section tunneling machine of coal mine - Google Patents
Rock breaking path selection method for small-section tunneling machine of coal mine Download PDFInfo
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- CN112228083B CN112228083B CN202011246294.8A CN202011246294A CN112228083B CN 112228083 B CN112228083 B CN 112228083B CN 202011246294 A CN202011246294 A CN 202011246294A CN 112228083 B CN112228083 B CN 112228083B
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- 239000011435 rock Substances 0.000 title claims abstract description 69
- 239000003245 coal Substances 0.000 title claims abstract description 19
- 230000005641 tunneling Effects 0.000 title claims abstract description 16
- 238000010187 selection method Methods 0.000 title description 3
- 238000005520 cutting process Methods 0.000 claims abstract description 50
- 238000005314 correlation function Methods 0.000 claims abstract description 20
- 238000000034 method Methods 0.000 claims abstract description 17
- 230000003068 static effect Effects 0.000 claims abstract description 10
- 238000004088 simulation Methods 0.000 claims abstract description 8
- 238000012360 testing method Methods 0.000 claims abstract description 8
- 230000008859 change Effects 0.000 claims description 6
- 230000006835 compression Effects 0.000 claims description 6
- 238000007906 compression Methods 0.000 claims description 6
- 230000036346 tooth eruption Effects 0.000 claims description 6
- 238000010801 machine learning Methods 0.000 claims description 4
- 230000009471 action Effects 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000003993 interaction Effects 0.000 claims description 3
- 238000010008 shearing Methods 0.000 claims description 3
- 238000012549 training Methods 0.000 claims description 3
- 238000002474 experimental method Methods 0.000 claims 1
- 230000008569 process Effects 0.000 abstract description 5
- 230000010354 integration Effects 0.000 description 3
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 238000009864 tensile test Methods 0.000 description 2
- 238000004873 anchoring Methods 0.000 description 1
- 238000009412 basement excavation Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21D—SHAFTS; TUNNELS; GALLERIES; LARGE UNDERGROUND CHAMBERS
- E21D9/00—Tunnels or galleries, with or without linings; Methods or apparatus for making thereof; Layout of tunnels or galleries
- E21D9/003—Arrangement of measuring or indicating devices for use during driving of tunnels, e.g. for guiding machines
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
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- General Engineering & Computer Science (AREA)
- Geometry (AREA)
- Computer Hardware Design (AREA)
- Geochemistry & Mineralogy (AREA)
- Medical Informatics (AREA)
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- Computer Vision & Pattern Recognition (AREA)
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- General Life Sciences & Earth Sciences (AREA)
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- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Investigating Strength Of Materials By Application Of Mechanical Stress (AREA)
Abstract
The invention discloses a method for selecting a rock breaking path of a small-section tunneling machine for a coal mine, which comprises the following steps of: 1) Testing dynamic load mechanical parameters of surrounding rocks of the roadway; 2) Testing static loading mechanical parameters of surrounding rocks of the roadway; 3) Numerically simulating the cutting working state of the heading machine; 4) And 3) establishing a correlation function of the cutting working state parameters of the heading machine and the crushing efficiency of the rocks with different lithologies according to the simulation result of the step 3), and selecting and determining the optimal cutting path of the rocks with different lithologies according to the maximum rock crushing efficiency. According to the method for selecting the rock breaking path of the coal mine small-section heading machine, the optimal cutting path is automatically selected in the heading process of the heading machine by establishing the correlation function of the cutting working state parameters of the heading machine and the rock breaking efficiency of different lithologies, and the small-section heading efficiency of the coal mine rock roadway can be improved.
Description
Technical Field
The invention relates to an underground space, in particular to the technical field of coal mine tunneling, and particularly relates to a small-section roadway tunneling method.
Background
The development of the intelligent development of the tunneling machine is rapid, and the mechanical types and the functions thereof are also changed from a single tunneling machine to highly integrated and intelligent machine types such as tunneling-anchoring integration, tunneling-exploring integration, tunneling-supporting integration and the like. However, the existing heading machine only has functions of monitoring a section and the like, but cannot automatically select an optimized cutting path in the heading and cutting process, and the optimization of the cutting path has an important influence on the improvement of the heading efficiency.
Disclosure of Invention
In view of the above, the invention aims to provide a method for selecting a rock breaking path of a small-section tunneling machine for a coal mine, so as to solve the technical problems that the cutting path cannot be automatically selected and optimized in the tunneling process of the existing tunneling machine, and the cutting efficiency is low.
The invention discloses a rock breaking path selection method of a coal mine small-section heading machine, which comprises the following steps of:
1) Testing dynamic load mechanical parameters of surrounding rocks of the roadway:
measuring dynamic failure strength of the coal rock and failure rules of different lithologic rocks under different impact loads, impact frequencies and impact angles by adopting a Hopkinson pressure bar;
2) Testing static loading mechanical parameters of the surrounding rocks of the roadway:
obtaining basic physical mechanical parameters of the rock through uniaxial compression, shearing and tensile tests, wherein the basic physical mechanical parameters comprise uniaxial compression strength, tensile strength, internal friction angle and cohesive force of the rock;
3) The cutting working state of the numerical simulation heading machine is as follows:
based on the dynamic and static mechanical parameters of the rocks with different lithological properties measured in the steps 1) and 2), adopting a numerical simulation heading machine to cut a path, analyzing the dynamic and static interaction between cutting teeth of a cutting head of the heading machine and the rocks, and analyzing the stress states of the rocks and the cutting teeth under the action of different cutting angles, speeds and loads;
4) Establishing a correlation function:
establishing a correlation function of cutting working state parameters and different lithologic rock crushing efficiencies of the cutting head of the heading machine in different cutting paths according to the simulation result of the step 3);
5) Determining an optimal rock breaking path:
and selecting a corresponding correlation function according to the lithology of the surrounding rock of the current tunneling roadway and the maximum rock crushing efficiency, and determining a current optimal cutting path according to the correlation function and the current cutting working state parameter of the tunneling machine.
Further, under the condition that the current working state parameters of the heading machine are unknown, the method also comprises the steps of utilizing the cutting working state parameters and surrounding rock stress change data of the heading machine in the early stage of the target mine as training data, establishing a heading path machine learning model, calculating the current working state parameters and surrounding rock stress change data of the heading machine according to the model, and determining the optimal cutting path of the current roadway by combining the machine calculation result and the correlation function.
The invention has the beneficial effects that:
according to the method for selecting the rock breaking path of the coal mine small-section heading machine, the optimal cutting path is automatically selected in the heading process of the heading machine by establishing the correlation function of the cutting working state parameters of the heading machine and the rock breaking efficiency of different lithologies, and the small-section heading efficiency of the coal mine rock roadway can be improved.
Detailed Description
The method for selecting the rock breaking path of the coal mine small-section heading machine comprises the following steps:
1) Testing dynamic load mechanical parameters of the surrounding rocks of the roadway:
the dynamic failure strength of the coal rock and the failure rules of different lithologic rocks under different impact loads, impact frequencies and impact angles are measured by adopting a Hopkinson pressure bar;
2) Testing static loading mechanical parameters of surrounding rocks of the roadway:
obtaining basic physical mechanical parameters of the rock through uniaxial compression, shearing and tensile tests, wherein the basic physical mechanical parameters comprise uniaxial compression strength, tensile strength, internal friction angle and cohesive force of the rock;
3) The cutting working state of the numerical simulation heading machine is as follows:
based on the dynamic and static mechanical parameters of the rocks with different lithologies measured in the steps 1) and 2), simulating the cutting path of the heading machine by adopting a numerical value, analyzing the dynamic and static interaction between cutting teeth of a cutting head of the heading machine and the rocks, and analyzing the stress states of the rocks and the cutting teeth under the action of different cutting angles, speeds and loads;
4) Establishing a correlation function:
establishing a correlation function of cutting working state parameters and different lithologic rock crushing efficiencies of the cutting head of the heading machine in different cutting paths according to the simulation result of the step 3);
5) Determining an optimal rock breaking path:
and selecting a corresponding correlation function according to the lithology of the surrounding rock of the current excavation roadway and the maximum rock crushing efficiency, and determining a current optimal cutting path according to the correlation function and the current cutting working state parameter of the excavator.
In the specific implementation, the lithology of the current tunneling roadway is sampled and analyzed in advance, then a corresponding correlation function is selected according to the lithology and the maximum rock crushing efficiency, and then the optimal cutting path in the tunneling process of the tunneling machine is determined.
According to the method for selecting the rock breaking path of the coal mine small-section heading machine, the optimal cutting path is automatically selected in the heading process of the heading machine by establishing the correlation function of the cutting working state parameters of the heading machine and the rock breaking efficiency of different lithologies, and the small-section heading efficiency of the coal mine rock roadway can be improved.
As an improvement to the above embodiment, the method for selecting the rock breaking path of the coal mine small-section heading machine further includes establishing a heading path machine learning model by using the cutting working state parameters and the surrounding rock stress change data of the target mine early-stage heading machine as training data, calculating the current working state parameters and the surrounding rock stress change data of the heading machine according to the model, and determining the optimal cutting path of the current roadway by combining the machine calculation result and the correlation function. By means of machine learning, the heading machine can be helped to automatically optimize a cutting path under the condition that parameters of the current cutting working state of the heading machine are unknown, and cutting efficiency is improved.
Finally, the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all of them should be covered in the claims of the present invention.
Claims (2)
1. A method for selecting a rock breaking path of a coal mine small-section heading machine is characterized by comprising the following steps:
1) Testing dynamic load mechanical parameters of surrounding rocks of the roadway:
measuring dynamic failure strength of the coal rock and failure rules of different lithologic rocks under different impact loads, impact frequencies and impact angles by adopting a Hopkinson pressure bar;
2) Testing static loading mechanical parameters of surrounding rocks of the roadway:
obtaining basic physical mechanical parameters of the rock through uniaxial compression, shearing and tensile experiments, wherein the basic physical mechanical parameters comprise uniaxial compression strength, tensile strength, internal friction angle and cohesive force of the rock;
3) The cutting working state of the numerical simulation heading machine is as follows:
based on the dynamic and static mechanical parameters of the rocks with different lithologies measured in the steps 1) and 2), simulating the cutting path of the heading machine by adopting a numerical value, analyzing the dynamic and static interaction between cutting teeth of a cutting head of the heading machine and the rocks, and analyzing the stress states of the rocks and the cutting teeth under the action of different cutting angles, speeds and loads;
4) Establishing a correlation function:
establishing a correlation function of cutting working state parameters and different lithologic rock crushing efficiencies of the cutting head of the heading machine in different cutting paths according to the simulation result of the step 3);
5) Determining an optimal rock breaking path:
and selecting a corresponding correlation function according to the lithology of the surrounding rock of the current tunneling roadway and the maximum rock crushing efficiency, and determining a current optimal cutting path according to the correlation function and the current cutting working state parameter of the tunneling machine.
2. The method for selecting the rock breaking path of the coal mine small-section heading machine according to claim 1, which is characterized in that: under the condition that the current working state parameters of the heading machine are unknown, the method further comprises the steps of utilizing the cutting working state parameters and surrounding rock stress change data of the heading machine in the early stage of the target mine as training data, establishing a heading path machine learning model, calculating the current working state parameters and the surrounding rock stress change data of the heading machine according to the model, and determining the optimal cutting path of the current roadway by combining the machine calculation result and the correlation function.
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| CN202011246294.8A CN112228083B (en) | 2020-11-10 | 2020-11-10 | Rock breaking path selection method for small-section tunneling machine of coal mine |
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| CN101839133B (en) * | 2010-04-26 | 2012-07-04 | 山西潞安环保能源开发股份有限公司王庄煤矿 | Development machine coal rock identification automatic cutting control method and system |
| CN103310056A (en) * | 2013-06-14 | 2013-09-18 | 山东科技大学 | Parametric modeling method for longitudinal axis heading machine cutting head |
| CN107044282B (en) * | 2017-06-02 | 2019-02-12 | 辽宁工程技术大学 | A kind of Vertical Axis Road-header virtual prototype cutterhead LOAD FOR and loading method |
| CN109754130A (en) * | 2019-03-15 | 2019-05-14 | 中国矿业大学(北京) | Boom-type roadheader cutting track planing method based on topological map |
| CN110795804A (en) * | 2019-11-19 | 2020-02-14 | 山西大学 | Analysis method and device for dynamic load of cutting head of heading machine |
| CN110836824A (en) * | 2019-11-19 | 2020-02-25 | 山西大学 | Method for identifying rock hardness based on hydraulic cylinder pressure signal and identification platform thereof |
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