CN110966004B - Coal mine intelligent working face multi-information fusion mining method and system - Google Patents
Coal mine intelligent working face multi-information fusion mining method and system Download PDFInfo
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Abstract
The embodiment of the invention discloses a multi-information fusion mining method and system for an intelligent working face of a coal mine, relates to the technical field of coal mining, and can improve the mining efficiency and safety of working face mining. The mining method comprises the following steps: acquiring state information of a coal mine underground mining site acquired by a sensor; judging a monitoring area where the sensor is located; determining coal mining key restriction factors associated with the monitoring area according to the determined monitoring area; calculating the current state value of the key restriction factor of coal mining according to the state information of the underground coal mining site acquired by a sensor, and determining the state value threshold interval of the key restriction factor of the current coal mining according to the state value; determining a control strategy corresponding to the state value threshold interval according to the determined state value threshold interval; and correspondingly controlling the mining state of the underground coal mine mining field according to the control strategy. The invention is suitable for underground mining of deep coal.
Description
Technical Field
The invention relates to the technical field of coal mining, in particular to a coal mine intelligent working face multi-information fusion mining method and system.
Background
In recent years, as the mining time goes on, the mining of coal resources in China gradually shifts to deep parts, and mining areas with abundant resources in shallow parts such as Shanxi, Neimeng, Shaanxi and the like gradually face the problem of deep part mining. The domestic expert and scholars are dedicated to the study on the stability of the deep coal resource exploitation surrounding rock for a long time, but a series of problems of strong mine pressure display of a working face, large deformation of a roadway, easy instability of a coal wall and the like are not fundamentally solved due to the complexity of a migration rule of the deep exploitation surrounding rock.
Disclosure of Invention
In view of this, the embodiment of the invention provides a coal mine intelligent working face multi-information fusion mining method and system, which are beneficial to improving the mining efficiency and safety of working face mining.
In a first aspect, an embodiment of the present invention provides a coal mine intelligent working face multi-information fusion mining method, including: acquiring state information of a coal mine underground mining site acquired by a sensor; judging a monitoring area where the sensor is located; determining coal mining key restriction factors associated with the monitoring area according to the determined monitoring area; calculating the current state value of the key restriction factor of coal mining according to the state information of the underground coal mining site acquired by the sensor, and determining the state value threshold interval of the key restriction factor of coal mining according to the state value; determining a control strategy corresponding to the state value threshold interval according to the determined state value threshold interval; and correspondingly controlling the mining state of the underground coal mine mining field according to the control strategy.
According to a specific embodiment of the invention, before acquiring the state information of the underground coal mine mining site acquired by a sensor, the mining method comprises the following steps: determining a first-level key restriction factor of the current intelligent working face mining; determining the second-level key restriction factor of the current intelligent working face mining according to the first-level key restriction factor and the influence weight on the safe and efficient mining of the intelligent working face; dividing the state information of each secondary key factor into more than two continuous state value threshold value intervals; setting a control strategy corresponding to each state value threshold interval; grouping the secondary key factors according to the state information characteristics of the secondary key factors to obtain secondary key factor groups; and dividing the intelligent working surface into different monitoring areas from high to low according to the secondary key factor group.
According to a specific embodiment of the present invention, the determining of the first-level key constraint factor of the current intelligent face mining includes: the occurrence conditions of the coal seam, the mine pressure of a stope, the mine pressure of a roadway and the working conditions of equipment are determined as the first-level key restriction factors of the current intelligent working face mining.
According to a specific embodiment of the present invention, the determining, according to the first-level key constraint factor and the influence weight on the safe and efficient mining of the current intelligent working face, a second-level key constraint factor for the mining of the current intelligent working face includes: determining the following factors as second-level key restriction factors of the current intelligent working face mining: the method comprises the following steps of wall instability area ratio, upper corner gas concentration, ore pressure index, pressure step pitch, support working resistance distribution, support movable column shrinkage, roadway roof rock stability, roadway two-side approaching amount, support initial supporting force, support left-right column ratio, support loaded resultant force action point position, coal cutter cutting motor load, floating bottom coal thickness, scraper conveyor motor load and scraper conveyor offset angle.
According to a specific embodiment of the present invention, the dividing the intelligent working plane into different monitoring areas from high to low according to the secondary key factor group includes: according to the secondary key factor group, dividing the intelligent working surface into the following monitoring areas from high to low: a transportation crossheading area, a return air crossheading area, a transport roadway advance area, an air roadway advance area, a front coal wall area, a working surface lower area, a working surface middle area and a working surface upper area; wherein each monitoring area corresponds to at least one secondary key factor group.
According to a specific embodiment of the present invention, the calculating a current state value of the key restriction factor for coal mining according to the state information of the underground coal mining site acquired by the sensor, and determining a state value threshold interval in which the key restriction factor for coal mining is located according to the state value includes:
according to the working face field data collected by the coal wall movement sensor and the camera, calculating the coal wall instability area ratio, and determining that the coal wall instability area ratio is within a threshold range of more than 20%, controlling the coal mining machine to automatically reduce the coal cutting height by a preset height value, and sending prompt information for enhancing support management and improving the coal body strength by adopting a grouting reinforcement mode;
according to the current gas concentration of the upper corner of the working face collected by the stope gas sensor, determining that the current gas concentration of the upper corner of the working face is within 0.8% -1% of a threshold range, and controlling the coal cutter to automatically reduce the coal cutting speed by a preset amplitude;
determining that the current descending speed S of the working face support plunger is within a threshold range of 5mm/min < S < 10mm/min and the current descending margin M of the support plunger is within a threshold range of 0.5M < M < 1.0M according to the descending speed and the descending margin of the working face support plunger acquired by the support descending sensor, controlling a coal mining machine to automatically increase the coal cutting height by a preset height value, and simultaneously sending prompt information for accelerating the advancing speed of the working face and strengthening the support overhauling strength;
according to the load ratio of the cutting motor of the coal mining machine acquired by a cutting load sensor of the coal mining machine, determining that the load ratio of the cutting motor of the current coal mining machine is within 80% -90% of a threshold range, and controlling the coal mining machine to automatically reduce the coal cutting height by a preset height value;
according to the thickness of the float bottom coal collected by the float bottom coal thickness monitoring sensor, determining that the current float bottom coal thickness is in a threshold range of more than 0.5m, and controlling the coal mining machine to automatically clean the float bottom coal;
determining the current motor load occupation ratio of the scraper conveyor to be in a threshold range larger than 90% according to the motor load occupation ratio of the scraper conveyor acquired by a load sensor of the scraper conveyor, controlling the scraper conveyor to automatically stop, and sending out prompt information for overhauling the scraper conveyor;
according to the position image of the scraper conveyor acquired by the working face camera, calculating the offset angle of the scraper conveyor, determining that the current offset angle of the scraper conveyor is in a threshold range of more than 5 degrees, controlling the coal mining machine and the scraper conveyor to stop simultaneously, and starting the automatic straightening function of the scraper conveyor to automatically straighten the scraper conveyor.
In a second aspect, an embodiment of the present invention further provides a coal mine intelligent working face multiple information fusion mining system, including: a transportation crossheading area, a return air crossheading area, a transport roadway advance area, an air roadway advance area, a front coal wall area, a working surface lower area, a working surface middle area and a working surface upper area;
arranging corresponding sensors in each area for collecting the state information of each monitoring area;
the monitoring center equipment is connected with the sensors of all the areas and is used for: acquiring state information of a coal mine underground mining site acquired by a sensor; judging a monitoring area where the sensor is located; determining coal mining key restriction factors associated with the monitoring area according to the determined monitoring area; calculating the current state value of the key restriction factor of coal mining according to the state information of the underground coal mining site acquired by the sensor, and determining the state value threshold interval of the key restriction factor of coal mining according to the state value; determining a control strategy corresponding to the state value threshold interval according to the determined state value threshold interval; and correspondingly controlling the mining state of the underground coal mine mining field according to the control strategy.
According to the method and the system for mining the coal mine intelligent working face through multi-information fusion, a monitoring area where a sensor is located is judged by obtaining state information of a coal mine underground mining site acquired by a working face sensor, coal mine mining key restriction factors related to the monitoring area are determined according to the determined monitoring area, a current state value of the coal mine mining key restriction factors is calculated according to the state information of the coal mine underground mining site acquired by the sensor, a state value threshold interval where the coal mine mining key restriction factors are located is determined according to the state value, a control strategy corresponding to the state value threshold interval is determined according to the determined state value threshold interval, and mining states of the coal mine underground mining site are correspondingly controlled according to the control strategy. Therefore, the working face abnormal state feedback, the real-time proposition of the coping strategy and the real-time adjustment of the working state of the key equipment can be realized based on the plurality of sensors of the intelligent working face, the real-time monitoring is realized, the regional control of each region of the working face is realized, the real-time performance, the effectiveness and the accuracy of the monitoring and the control of the working face are improved, the sensors of the working face are organically combined with the real-time monitoring (real-time performance), the control strategy (effectiveness) corresponding to the state value threshold value interval and the regional control (accuracy) of each region of the working face, and the mining efficiency and the safety of the mining of the working face are favorably improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a coal mine intelligent working face multi-information fusion mining method according to an embodiment of the invention;
FIG. 2 is a schematic flow chart of a coal mine intelligent working face multi-information fusion mining method according to another embodiment of the invention;
FIG. 3 is a top view of a working face upon which a method for multi-information fusion mining of an intelligent working face of a coal mine is based, in accordance with an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a multi-information fusion mining system for an intelligent working face of a coal mine according to an embodiment of the invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
It should be understood that the described embodiments are only some embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic flow chart of a multi-information fusion mining method for an intelligent working face of a coal mine according to an embodiment of the present invention, and the method of the present embodiment is suitable for deep mining (underground mining with a depth greater than 600 m), and is particularly suitable for coal mining of an intelligent working face of a deep coal mine. As shown in fig. 1, the method of the present embodiment may include the steps of:
s100, acquiring state information of a coal mine underground mining site acquired by a sensor.
The state information may include key equipment data, such as working condition data of equipment such as a coal mining machine, a hydraulic support, a roadway support structure and the like; the state information can also be coal seam occurrence conditions, stope mine pressure, roadway mine pressure and the like.
The underground coal mine mining site can be divided into a plurality of different monitoring areas, corresponding sensors are arranged in the monitoring areas and connected with monitoring center equipment, so that the collected state information of the monitoring areas is transmitted to the monitoring center equipment, and the monitoring center equipment can analyze and monitor the condition of a working face.
And S102, judging a monitoring area where the sensor is located.
After acquiring the state information of the underground coal mine mining site acquired by a sensor, the monitoring center equipment can judge the monitoring area where the sensor is located according to the number of the sensor according to a pre-established corresponding relation table of the number of the sensor and the position of the monitoring area.
And S104, determining coal mining key restriction factors associated with the monitoring area according to the determined monitoring area.
For each monitoring area, coal mining key restriction factors associated with each monitoring area are pre-established. The key restriction factor for coal mining is a restriction factor which has a great influence on the improvement of the mining efficiency or the safety guarantee of coal mining. For example, the stability of the roadway roof is a key constraint factor influencing the safety.
S106, calculating the current state value of the key restriction factor of coal mining according to the state information of the underground coal mining site acquired by the sensor, and determining the state value threshold interval of the key restriction factor of coal mining according to the state value.
The state value can be divided into a plurality of continuous state value threshold value areas according to the continuous change condition of the state value of the key restriction factor of coal mining in advance. The state values in different state value threshold value intervals have different influence degrees on mining efficiency and safety. Therefore, different state value threshold intervals correspond to different control strategies.
And S108, determining a control strategy corresponding to the state value threshold interval according to the determined state value threshold interval.
And calculating the current state value of the key restriction factor of coal mining according to the state information of the underground coal mining site acquired by the sensor, determining the state value threshold interval in which the key restriction factor of coal mining is located according to the state value, and determining the control strategy corresponding to the state value threshold interval in which the key restriction factor of coal mining is located according to the pre-established corresponding relationship between the state value threshold interval in which the key restriction factor of coal mining is located and the corresponding control strategy.
And S110, correspondingly controlling the mining state of the underground coal mine mining field according to the control strategy.
And correspondingly controlling the mining state of the corresponding monitoring area of the underground coal mine mining site according to the control strategy.
According to the method and the device, a monitoring area where a sensor is located is judged by obtaining state information of an underground coal mine mining site acquired by a working face sensor, coal mine mining key restriction factors related to the monitoring area are determined according to the determined monitoring area, a current state value of the coal mine mining key restriction factors is calculated according to the state information of the underground coal mine mining site acquired by the sensor, a state value threshold interval where the current coal mine mining key restriction factors are located is determined according to the state value, a control strategy corresponding to the state value threshold interval is determined according to the determined state value threshold interval, and mining states of the underground coal mine mining site are correspondingly controlled according to the control strategy. Therefore, the working face abnormal state feedback, the real-time proposition of the coping strategy and the real-time adjustment of the working state of the key equipment can be realized based on the plurality of sensors of the intelligent working face, the real-time monitoring is realized, the regional control of each region of the working face is realized, the real-time performance, the effectiveness and the accuracy of the monitoring and the control of the working face are improved, the sensors of the working face are organically combined with the real-time monitoring (real-time performance), the control strategy (effectiveness) corresponding to the state value threshold value interval and the regional control (accuracy) of each region of the working face, and the mining efficiency and the safety of the mining of the working face are favorably improved.
Fig. 2 is a schematic flow chart of a coal mine intelligent working face multi-information fusion mining method according to another embodiment of the present invention, and referring to fig. 2, the present embodiment is different from the embodiment shown in fig. 1 in that, in the present embodiment, before acquiring state information of a coal mine underground mining site acquired by a sensor (step S100), the mining method may include the steps of:
and S10, determining the first-level key restriction factor of the current intelligent working face mining.
In one embodiment, the occurrence conditions of the coal seam, mine pressure of a stope, mine pressure of a roadway and equipment working conditions can be determined as the first-level key restriction factors of the mining of the current intelligent working face.
And S12, determining the second-level key restriction factor of the current intelligent working face mining according to the influence weight of the first-level key restriction factor on the safe and efficient mining of the intelligent working face.
In an embodiment, according to the first-level key constraint factor, the influence weight on the safe and efficient mining of the current intelligent working face may be determined as a second-level key constraint factor of the mining of the current intelligent working face by:
the method comprises the following steps of wall instability area ratio, upper corner gas concentration, ore pressure index, pressure step pitch, support working resistance distribution, support movable column shrinkage, roadway roof rock stability, roadway two-side approaching amount, support initial supporting force, support left-right column ratio, support loaded resultant force action point position, coal cutter cutting motor load, floating bottom coal thickness, scraper conveyor motor load and scraper conveyor offset angle.
And S14, dividing the state information of each secondary key factor into more than two continuous state value threshold value intervals.
And S16, setting control strategies corresponding to the state value threshold intervals.
And S18, grouping the secondary key factors according to the state information characteristics of the secondary key factors to obtain a secondary key factor group.
And S20, dividing the intelligent working surface into different monitoring areas from high to low according to the secondary key factor group.
In an embodiment, the dividing the intelligent working plane into different monitoring areas from high to low according to the secondary key factor group may include: according to the secondary key factor group, dividing the intelligent working surface into the following monitoring areas from high to low: a transportation crossheading area, a return air crossheading area, a transport roadway advance area, an air roadway advance area, a front coal wall area, a working surface lower area, a working surface middle area and a working surface upper area; wherein each monitoring area corresponds to at least one secondary key factor group.
FIG. 3 is a top view of a working face based on the intelligent working face multi-information fusion mining method for a coal mine according to an embodiment of the invention, and 1-8 in FIG. 3 are working face partitions, 1-transportation gate areas; 2-return air crossheading area; 3-transporting lane advance area; 4-air way advance area; 5-front coal wall area; 6-lower region of working face; 7-working face middle area; 8-upper region of working face; 9-key restriction factor; 10-constraint control strategy.
In an embodiment, the calculating, according to the state information of the underground coal mining site acquired by the sensor, a current state value of the key restriction factor for coal mining, and determining, according to the state value, a state value threshold interval in which the key restriction factor for coal mining is located (step S106) includes:
according to the working face field data collected by the coal wall movement sensor and the camera, calculating the coal wall instability area ratio, and determining that the coal wall instability area ratio is within a threshold range of more than 20%, controlling the coal mining machine to automatically reduce the coal cutting height by a preset height value, and sending prompt information for enhancing support management and improving the coal body strength by adopting a grouting reinforcement mode;
according to the current gas concentration of the upper corner of the working face collected by the stope gas sensor, determining that the current gas concentration of the upper corner of the working face is within 0.8% -1% of a threshold range, and controlling the coal cutter to automatically reduce the coal cutting speed by a preset amplitude;
determining that the current descending speed S of the working face support plunger is within a threshold range of 5mm/min < S < 10mm/min and the current descending margin M of the support plunger is within a threshold range of 0.5M < M < 1.0M according to the descending speed and the descending margin of the working face support plunger acquired by the support descending sensor, controlling a coal mining machine to automatically increase the coal cutting height by a preset height value, and simultaneously sending prompt information for accelerating the advancing speed of the working face and strengthening the support overhauling strength;
according to the load ratio of the cutting motor of the coal mining machine acquired by a cutting load sensor of the coal mining machine, determining that the load ratio of the cutting motor of the current coal mining machine is within 80% -90% of a threshold range, and controlling the coal mining machine to automatically reduce the coal cutting height by a preset height value;
according to the thickness of the float bottom coal collected by the float bottom coal thickness monitoring sensor, determining that the current float bottom coal thickness is in a threshold range of more than 0.5m, and controlling the coal mining machine to automatically clean the float bottom coal;
determining the current motor load occupation ratio of the scraper conveyor to be in a threshold range larger than 90% according to the motor load occupation ratio of the scraper conveyor acquired by a load sensor of the scraper conveyor, controlling the scraper conveyor to automatically stop, and sending out prompt information for overhauling the scraper conveyor;
according to the position image of the scraper conveyor acquired by the working face camera, calculating the offset angle of the scraper conveyor, determining that the current offset angle of the scraper conveyor is in a threshold range of more than 5 degrees, controlling the coal mining machine and the scraper conveyor to stop simultaneously, and starting the automatic straightening function of the scraper conveyor to automatically straighten the scraper conveyor.
The present invention is further illustrated by the following specific examples.
Taking an intelligent working face of a certain mine deep well as an example, firstly analyzing the influence degree of four major factors such as coal seam occurrence conditions, stope mine pressure, roadway mine pressure and equipment working conditions on the mining of the intelligent working face, wherein the coal seam occurrence conditions comprise: coal seam inclination, coal wall stability, gas concentration, coal seam roof and floor conditions, coal seam buried depth, water inflow, spontaneous combustion tendency and other 7 secondary factors, and stope mine pressure factors include: the last resistance of support circulation, dynamic load coefficient, come to press stride, support working resistance distribution, support plunger down contract volume, come to press 6 second grade indexes such as duration, the tunnel mine pressure factor includes: 5 second grade indexes such as fore support working resistance, leading stress peak position, tunnel roof separation, tunnel two sides move near volume, stock (cable) working resistance, equipment operating mode factor includes: the support initial supporting force, the support upright post stress balance, the position of the support loaded resultant force action point, the load of a cutting motor of a coal mining machine, the thickness of floating bottom coal, the load of a motor of a scraper conveyor, the straightness of the scraper conveyor, the pitch angle of the support, the opening rate of a safety valve and other 9 secondary indexes. According to the analysis result, 15 indexes are selected as key constraint factors, including: (1) coal wall instability area ratio, (2) upper corner gas concentration, (3) ore pressure index, (4) incoming pressure step distance, (5) support working resistance distribution, (6) support movable column shrinkage amount, (7) roadway roof rock stratum stability, (8) roadway two-side approach amount, (9) support initial supporting force, (10) support left-right (front-back) column ratio, (11) support loaded resultant force action point position, (12) coal cutter motor load, (13) floating bottom coal thickness, (14) scraper conveyor motor load, (15) scraper conveyor offset angle and the like.
And obtaining the control strategy of each key factor according to the field measured data, as shown in the table 1.
TABLE 1 Key constraint factor control strategy
According to the situation, the deep well large mining height intelligent working face multi-information fusion partition control mining method is provided, the intelligent mining working face is divided into a conveying roadway advance support area, an air conveying two-roadway area, a working face upper area, a working face middle area, a working face lower area, a working face side area and the like, a coping strategy is provided in real time and the working state of key equipment is adjusted on the basis of real-time analysis conclusion of stope mine pressure, roadway mine pressure and equipment working condition data and the change situation of coal bed and surrounding rock conditions, and the partition control function of each area is achieved.
According to the embodiment of the invention, the influence degree of four major factors such as occurrence conditions of coal seams of the intelligent working face, mine pressure of stopes, mine pressure of roadways, working conditions of equipment and the like on the safe and efficient mining of the intelligent working face is analyzed, and a plurality of indexes which have the most serious influence are obtained as key restriction factors. And aiming at the conditions of the intelligent working face, dividing each key restriction factor into 2-3 grades, and providing control strategies of different grades of each key restriction factor. And selecting results and the influence degree according to key restriction factors, and dividing the working surface into a plurality of affected areas from high to low. And when a certain factor index meets the grade requirement, a control strategy of a corresponding area is proposed to guide the safe production.
In the embodiment of the invention, the intelligent mining working face is provided with an intelligent network and abundant sensors, so that not only can the key equipment data be acquired in real time and the control be realized, but also the surrounding rock state of the working face can be reflected by analyzing the equipment working condition data, and an effective way is provided for the research of the surrounding rock stability and the control technology. According to analysis of a plurality of restriction factors such as coal seam occurrence conditions, stope mine pressure, roadway mine pressure and equipment working condition monitoring, a stope face is divided into different areas, specific control strategies of abnormal states are provided according to influence degrees of the restriction factors on surrounding rock stability and equipment working conditions of the different areas of the working face, and mining efficiency and safety of an intelligent working face are guaranteed.
Fig. 4 is a schematic structural diagram of a coal mine intelligent working face multi-information fusion mining system according to an embodiment of the invention. Referring to fig. 4, an embodiment of the present invention further provides a coal mine intelligent working face multiple information fusion mining system, including: a transportation crossheading area 1, a return air crossheading area 2, a transport roadway advance area 3, an air roadway advance area 4, a front coal wall area 6, a working surface lower area 6, a working surface middle area 7 and a working surface upper area 8; corresponding sensors (not shown in the figure) are arranged in each area and used for collecting the state information of each monitoring area; a monitoring center 28 connected to the sensors of each zone for: acquiring state information of a coal mine underground mining site acquired by a sensor; judging a monitoring area where the sensor is located; determining coal mining key restriction factors associated with the monitoring area according to the determined monitoring area; calculating the current state value of the key restriction factor of coal mining according to the state information of the underground coal mining site acquired by the sensor, and determining the state value threshold interval of the key restriction factor of coal mining according to the state value; determining a control strategy corresponding to the state value threshold interval according to the determined state value threshold interval; and correspondingly controlling the mining state of the underground coal mine mining field according to the control strategy.
Before acquiring the state information of the underground coal mine mining site acquired by the sensor, the mining system can comprise: determining a first-level key restriction factor of the current intelligent working face mining; determining the second-level key restriction factor of the current intelligent working face mining according to the first-level key restriction factor and the influence weight on the safe and efficient mining of the intelligent working face; dividing the state information of each secondary key factor into more than two continuous state value threshold value intervals; setting a control strategy corresponding to each state value threshold interval; grouping the secondary key factors according to the state information characteristics of the secondary key factors to obtain secondary key factor groups; and dividing the intelligent working surface into different monitoring areas from high to low according to the secondary key factor group.
Wherein, the determination of the first-level key restriction factor of the current intelligent working face mining comprises the following steps: the occurrence conditions of the coal seam, the mine pressure of a stope, the mine pressure of a roadway and the working conditions of equipment are determined as the first-level key restriction factors of the current intelligent working face mining.
Determining the second-level key restriction factors of the current intelligent working face mining according to the first-level key restriction factors and the influence weight of the current intelligent working face safe and efficient mining, wherein the determining comprises the following steps: determining the following factors as second-level key restriction factors of the current intelligent working face mining: the method comprises the following steps of wall instability area ratio, upper corner gas concentration, ore pressure index, pressure step pitch, support working resistance distribution, support movable column shrinkage, roadway roof rock stability, roadway two-side approaching amount, support initial supporting force, support left-right column ratio, support loaded resultant force action point position, coal cutter cutting motor load, floating bottom coal thickness, scraper conveyor motor load and scraper conveyor offset angle.
Wherein, according to the second-level key factor group, the intelligent working surface is divided into different monitoring areas from high to low, and the method comprises the following steps: according to the secondary key factor group, dividing the intelligent working surface into the following monitoring areas from high to low: a transportation crossheading area, a return air crossheading area, a transport roadway advance area, an air roadway advance area, a front coal wall area, a working surface lower area, a working surface middle area and a working surface upper area; wherein each monitoring area corresponds to at least one secondary key factor group.
The method comprises the following steps of calculating the current state value of the key restriction factor of coal mining according to the state information of the underground coal mining site acquired by the sensor, and determining the state value threshold interval of the key restriction factor of coal mining according to the state value, wherein the step of: according to the working face field data collected by the coal wall movement sensor and the camera, calculating the coal wall instability area ratio, and determining that the coal wall instability area ratio is within a threshold range of more than 20%, controlling the coal mining machine to automatically reduce the coal cutting height by a preset height value, and sending prompt information for enhancing support management and improving the coal body strength by adopting a grouting reinforcement mode; according to the current gas concentration of the upper corner of the working face collected by the stope gas sensor, determining that the current gas concentration of the upper corner of the working face is within 0.8% -1% of a threshold range, and controlling the coal cutter to automatically reduce the coal cutting speed by a preset amplitude;
determining that the current descending speed S of the working face support plunger is within a threshold range of 5mm/min < S < 10mm/min and the current descending margin M of the support plunger is within a threshold range of 0.5M < M < 1.0M according to the descending speed and the descending margin of the working face support plunger acquired by the support descending sensor, controlling a coal mining machine to automatically increase the coal cutting height by a preset height value, and simultaneously sending prompt information for accelerating the advancing speed of the working face and strengthening the support overhauling strength;
according to the load ratio of the cutting motor of the coal mining machine acquired by a cutting load sensor of the coal mining machine, determining that the load ratio of the cutting motor of the current coal mining machine is within 80% -90% of a threshold range, and controlling the coal mining machine to automatically reduce the coal cutting height by a preset height value;
according to the thickness of the float bottom coal collected by the float bottom coal thickness monitoring sensor, determining that the current float bottom coal thickness is in a threshold range of more than 0.5m, and controlling the coal mining machine to automatically clean the float bottom coal;
determining the current motor load occupation ratio of the scraper conveyor to be in a threshold range larger than 90% according to the motor load occupation ratio of the scraper conveyor acquired by a load sensor of the scraper conveyor, controlling the scraper conveyor to automatically stop, and sending out prompt information for overhauling the scraper conveyor;
according to the position image of the scraper conveyor acquired by the working face camera, calculating the offset angle of the scraper conveyor, determining that the current offset angle of the scraper conveyor is in a threshold range of more than 5 degrees, controlling the coal mining machine and the scraper conveyor to stop simultaneously, and starting the automatic straightening function of the scraper conveyor to automatically straighten the scraper conveyor.
According to the system embodiment of the invention, a monitoring area where a sensor is located is judged by acquiring state information of an underground coal mine mining site acquired by a working face sensor, a coal mine mining key restriction factor associated with the monitoring area is determined according to the determined monitoring area, a current state value of the coal mine mining key restriction factor is calculated according to the state information of the underground coal mine mining site acquired by the sensor, a state value threshold interval where the current coal mine mining key restriction factor is located is determined according to the state value, a control strategy corresponding to the state value threshold interval is determined according to the determined state value threshold interval, and the mining state of the underground coal mine mining site is correspondingly controlled according to the control strategy. Therefore, the working face abnormal state feedback, the real-time proposition of the coping strategy and the real-time adjustment of the working state of the key equipment can be realized based on the plurality of sensors of the intelligent working face, the real-time monitoring is realized, the regional control of each region of the working face is realized, the real-time performance, the effectiveness and the accuracy of the monitoring and the control of the working face are improved, the sensors of the working face are organically combined with the real-time monitoring (real-time performance), the control strategy (effectiveness) corresponding to the state value threshold value interval and the regional control (accuracy) of each region of the working face, and the mining efficiency and the safety of the mining of the working face are favorably improved.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. The term "comprising", without further limitation, means that the element so defined is not excluded from the group consisting of additional identical elements in the process, method, article, or apparatus that comprises the element.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments.
In particular, as for the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
For convenience of description, the above devices are described separately in terms of functional division into various units/modules. Of course, the functionality of the units/modules may be implemented in one or more software and/or hardware implementations of the invention.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (5)
1. A coal mine intelligent working face multi-information fusion mining method is characterized by comprising the following steps:
determining a first-level key restriction factor of the current intelligent working face mining;
determining the second-level key restriction factor of the current intelligent working face mining according to the first-level key restriction factor and the influence weight on the safe and efficient mining of the intelligent working face;
dividing the state information of each secondary key factor into more than two continuous state value threshold value intervals;
setting a control strategy corresponding to each state value threshold interval;
grouping the secondary key factors according to the state information characteristics of the secondary key factors to obtain secondary key factor groups;
dividing the intelligent working face into different monitoring areas from high to low according to the secondary key factor group;
acquiring state information of a coal mine underground mining site acquired by a sensor;
judging a monitoring area where the sensor is located;
determining coal mining key restriction factors associated with the monitoring area according to the determined monitoring area;
calculating the current state value of the key restriction factor of coal mining according to the state information of the underground coal mining site acquired by the sensor, and determining the state value threshold interval of the key restriction factor of coal mining according to the state value;
determining a control strategy corresponding to the state value threshold interval according to the determined state value threshold interval;
correspondingly controlling the mining state of the underground coal mine mining field according to the control strategy;
the method comprises the following steps of calculating the current state value of the key restriction factor of coal mining according to the state information of the underground coal mining site acquired by the sensor, and determining the state value threshold interval of the key restriction factor of coal mining according to the state value, wherein the state value threshold interval comprises the following steps:
according to the working face field data collected by the coal wall movement sensor and the camera, calculating the coal wall instability area ratio, and determining that the coal wall instability area ratio is within a threshold range of more than 20%, controlling the coal mining machine to automatically reduce the coal cutting height by a preset height value, and sending prompt information for enhancing support management and improving the coal body strength by adopting a grouting reinforcement mode;
according to the current gas concentration of the upper corner of the working face collected by the stope gas sensor, determining that the current gas concentration of the upper corner of the working face is within 0.8% -1% of a threshold range, and controlling the coal cutter to automatically reduce the coal cutting speed by a preset amplitude;
determining that the current descending speed S of the working face support plunger is within a threshold range of 5mm/min < S < 10mm/min and the current descending margin M of the support plunger is within a threshold range of 0.5M < M < 1.0M according to the descending speed and the descending margin of the working face support plunger acquired by the support descending sensor, controlling a coal mining machine to automatically increase the coal cutting height by a preset height value, and simultaneously sending prompt information for accelerating the advancing speed of the working face and strengthening the support overhauling strength;
according to the load ratio of the cutting motor of the coal mining machine acquired by a cutting load sensor of the coal mining machine, determining that the load ratio of the cutting motor of the current coal mining machine is within 80% -90% of a threshold range, and controlling the coal mining machine to automatically reduce the coal cutting height by a preset height value;
according to the thickness of the float bottom coal collected by the float bottom coal thickness monitoring sensor, determining that the current float bottom coal thickness is in a threshold range of more than 0.5m, and controlling the coal mining machine to automatically clean the float bottom coal;
determining the current motor load occupation ratio of the scraper conveyor to be in a threshold range larger than 90% according to the motor load occupation ratio of the scraper conveyor acquired by a load sensor of the scraper conveyor, controlling the scraper conveyor to automatically stop, and sending out prompt information for overhauling the scraper conveyor;
according to the position image of the scraper conveyor acquired by the working face camera, calculating the offset angle of the scraper conveyor, determining that the current offset angle of the scraper conveyor is in a threshold range of more than 5 degrees, controlling the coal mining machine and the scraper conveyor to stop simultaneously, and starting the automatic straightening function of the scraper conveyor to automatically straighten the scraper conveyor.
2. The mining method of claim 1, wherein the determining a primary key constraint for current intelligent face mining comprises:
the occurrence conditions of the coal seam, the mine pressure of a stope, the mine pressure of a roadway and the working conditions of equipment are determined as the first-level key restriction factors of the current intelligent working face mining.
3. The mining method according to claim 1 or 2, wherein the determining of the secondary key constraint factors for the current intelligent face mining according to the weight of the influence of the primary key constraint factors on the current intelligent face safe and efficient mining comprises:
determining the following factors as second-level key restriction factors of the current intelligent working face mining:
the method comprises the following steps of wall instability area ratio, upper corner gas concentration, ore pressure index, pressure step pitch, support working resistance distribution, support movable column shrinkage, roadway roof rock stability, roadway two-side approaching amount, support initial supporting force, support left-right column ratio, support loaded resultant force action point position, coal cutter cutting motor load, floating bottom coal thickness, scraper conveyor motor load and scraper conveyor offset angle.
4. The mining method of claim 1, wherein the dividing the intelligent face into different monitoring zones from high to low according to the secondary key factor group comprises:
according to the secondary key factor group, dividing the intelligent working surface into the following monitoring areas from high to low:
a transportation crossheading area, a return air crossheading area, a transport roadway advance area, an air roadway advance area, a front coal wall area, a working surface lower area, a working surface middle area and a working surface upper area;
wherein each monitoring area corresponds to at least one secondary key factor group.
5. The utility model provides a many information fusion of colliery intelligence working face mining system which characterized in that includes: a transportation crossheading area, a return air crossheading area, a transport roadway advance area, an air roadway advance area, a front coal wall area, a working surface lower area, a working surface middle area and a working surface upper area;
arranging corresponding sensors in each area for collecting the state information of each monitoring area;
the monitoring center equipment is connected with the sensors of all the areas and is used for: determining a first-level key restriction factor of the current intelligent working face mining; determining the second-level key restriction factor of the current intelligent working face mining according to the first-level key restriction factor and the influence weight on the safe and efficient mining of the intelligent working face; dividing the state information of each secondary key factor into more than two continuous state value threshold value intervals; setting a control strategy corresponding to each state value threshold interval; grouping the secondary key factors according to the state information characteristics of the secondary key factors to obtain secondary key factor groups; dividing the intelligent working face into different monitoring areas from high to low according to the secondary key factor group; acquiring state information of a coal mine underground mining site acquired by a sensor; judging a monitoring area where the sensor is located; determining coal mining key restriction factors associated with the monitoring area according to the determined monitoring area; calculating the current state value of the key restriction factor of coal mining according to the state information of the underground coal mining site acquired by the sensor, and determining the state value threshold interval of the key restriction factor of coal mining according to the state value; determining a control strategy corresponding to the state value threshold interval according to the determined state value threshold interval; correspondingly controlling the mining state of the underground coal mine mining field according to the control strategy;
the method comprises the following steps of calculating the current state value of the key restriction factor of coal mining according to the state information of the underground coal mining site acquired by the sensor, and determining the state value threshold interval of the key restriction factor of coal mining according to the state value, wherein the state value threshold interval comprises the following steps:
according to the working face field data collected by the coal wall movement sensor and the camera, calculating the coal wall instability area ratio, and determining that the coal wall instability area ratio is within a threshold range of more than 20%, controlling the coal mining machine to automatically reduce the coal cutting height by a preset height value, and sending prompt information for enhancing support management and improving the coal body strength by adopting a grouting reinforcement mode;
according to the current gas concentration of the upper corner of the working face collected by the stope gas sensor, determining that the current gas concentration of the upper corner of the working face is within 0.8% -1% of a threshold range, and controlling the coal cutter to automatically reduce the coal cutting speed by a preset amplitude;
determining that the current descending speed S of the working face support plunger is within a threshold range of 5mm/min < S < 10mm/min and the current descending margin M of the support plunger is within a threshold range of 0.5M < M < 1.0M according to the descending speed and the descending margin of the working face support plunger acquired by the support descending sensor, controlling a coal mining machine to automatically increase the coal cutting height by a preset height value, and simultaneously sending prompt information for accelerating the advancing speed of the working face and strengthening the support overhauling strength;
according to the load ratio of the cutting motor of the coal mining machine acquired by a cutting load sensor of the coal mining machine, determining that the load ratio of the cutting motor of the current coal mining machine is within 80% -90% of a threshold range, and controlling the coal mining machine to automatically reduce the coal cutting height by a preset height value;
according to the thickness of the float bottom coal collected by the float bottom coal thickness monitoring sensor, determining that the current float bottom coal thickness is in a threshold range of more than 0.5m, and controlling the coal mining machine to automatically clean the float bottom coal;
determining the current motor load occupation ratio of the scraper conveyor to be in a threshold range larger than 90% according to the motor load occupation ratio of the scraper conveyor acquired by a load sensor of the scraper conveyor, controlling the scraper conveyor to automatically stop, and sending out prompt information for overhauling the scraper conveyor;
according to the position image of the scraper conveyor acquired by the working face camera, calculating the offset angle of the scraper conveyor, determining that the current offset angle of the scraper conveyor is in a threshold range of more than 5 degrees, controlling the coal mining machine and the scraper conveyor to stop simultaneously, and starting the automatic straightening function of the scraper conveyor to automatically straighten the scraper conveyor.
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