Intelligentized rapid tunneling system for rock roadway

Abstract

The application discloses a kind of rock roadway intelligentization rapid excavation system, specifically relates to mechanized mining technical field, the image of rock is collected and analyzed, so as to obtain the fracture excavation value of rock fracture and the rock excavation value corresponding to rock volume, the final excavation adjustment value is obtained by calculating and processing fracture excavation value and rock excavation value, the final excavation adjustment value is substituted into the preset value range, set each value range respectively corresponding one control level of fully mechanized mining machine, according to the control level obtained, the parameters of fully mechanized mining machine are adjusted once, simultaneously in the process of excavation, the sound signal of cutter and the temperature change of driving end are collected and analyzed, obtain the mechanical state value in the process of fully mechanized mining machine operation, and according to the adjustment parameter corresponding to mechanical state value, the parameters of fully mechanized mining machine are adjusted twice, so as to improve the efficiency of excavation while avoiding fully mechanized mining machine to issue damage or fault.

Description

TECHNICAL FIELD

[0001] The present application relates to the mechanized technology field of fully mechanized mining, and in particular to a rock roadway intelligent rapid tunneling system. BACKGROUND

[0002] In coal mine operation, rock roadway tunneling construction is required, and through hard rock fully mechanized mining machines, dry dust removal fans and other processes, the mechanized continuous operation of coal mine rock roadway tunneling is realized, avoiding the traditional construction of "close combat", greatly improving the safety factor, and reducing the labor intensity of workers.

[0003] However, the rock roadway tunneling system in the prior art has the following defects in use:

[0004] 1. The parameters of the fully mechanized mining machine cannot be adjusted according to the rock state of the tunneling face and the working state during tunneling, the efficiency is not high, the fully mechanized mining machine is easily damaged, and there is a certain risk of accidents;

[0005] 2. The power of the dust removal fan cannot be adjusted according to the dust concentration change during tunneling, affecting the efficiency of tunneling.

[0006] Therefore, a rock roadway intelligent rapid tunneling system is provided. SUMMARY

[0007] In view of the problem that the parameters of the fully mechanized mining machine cannot be adjusted according to the rock state of the tunneling face and the working state during tunneling in the prior art, the efficiency is not high, and the fully mechanized mining machine is easily damaged, the present application provides a rock roadway intelligent rapid tunneling system.

[0008] The purpose of the present application can be achieved by the following technical scheme: a rock roadway intelligent rapid tunneling system, comprising an unmanned fully mechanized mining machine body and a control system for controlling the unmanned fully mechanized mining machine to perform tunneling operation, the control system comprising a remote communication module and a controller, the remote communication module being used to connect the controller and the unmanned fully mechanized mining machine body and transmit data, the control system further comprising:

[0009] A data acquisition module is used to acquire geological parameters of the fully mechanized mining machine during driving and send them to an analysis module, and the data acquisition module acquires the geological parameters through an image acquisition unit;

[0010] The analysis module analyzes and processes the geological parameters through an environment analysis unit, and the specific analysis process is as follows:

[0011] Step one: obtain the rock image information inside the rock roadway during the operation of the fully mechanized mining machine, divide the obtained rock image into different regions, use a segmentation algorithm to separate the fracture region of the rock from other rock regions, and thus obtain the fracture region information and the rock type region information;

[0012] Step two: analyze the information of the fracture area, count the number of fractures and mark them, measure the straight-line distance between the upper and lower points of the fracture, measure the length of the fracture along the trajectory, calculate the fracture angle value H1 of the corresponding fracture by using the trigonometric function of the straight-line distance and the length of the trajectory, that is, the fracture angle value = arctan (length of trajectory / straight-line distance), obtain the fracture displacement value H2 of the corresponding fracture by the length of the trajectory - straight-line distance, calculate the horizontal distance between the left and right points at different positions of the fracture to obtain the fracture width value H3, extract the maximum fracture width value and mark it, and substitute the fracture angle value H1, fracture displacement value H2 and fracture width value H3 into the formula And calculate to obtain the fracture value HU1 of the corresponding fracture, wherein λ1, λ2 and λ3 are the preset weight factors of the fracture angle value H1, the fracture displacement value H2 and the fracture width value H3 respectively, and α is a preset correction factor.

[0013] Step three: compare the fracture value HU1 corresponding to different fractures with the preset threshold range, when the fracture value HU1 is higher than the preset threshold range, mark the fracture value HU1 as an over-standard fracture value, calculate the over-standard difference value between the obtained over-standard fracture value and the highest range value in the threshold range, match each over-standard difference value in the preset range, set each preset range to correspond to a preset coefficient, multiply each over-standard difference value with the corresponding preset coefficient to obtain a high fracture value, add all the high fracture values and take the average to obtain a high fracture average value HU2, when the fracture value HU1 is in the preset threshold range, mark the fracture value HU1 as a normal fracture value, set the threshold range to correspond to a preset coefficient, multiply each normal fracture value with the preset coefficient to obtain a medium fracture value, add all the medium fracture values after removing one maximum value and one minimum value and take the average to obtain a medium fracture average value HU3, substitute the high fracture average value HU2 and the medium fracture average value HU3 into the formula TLB = (HU2 × aq1 + HU3 × aq2 + 0.32) × β, and calculate to obtain the fracture driving value TLB of the rock region, wherein aq1 and aq2 are the preset weight factors of the high fracture average value HU2 and the medium fracture average value HU3 respectively, and β is a preset correction factor.

[0014] Step four: analyze the rock type area, after digital processing of the collected rock type area image, the characteristic information of the rock is extracted, so as to obtain the type of the rock, it is assumed that different types of rocks correspond to an intensity parameter value Qi, i = 1, 2, 3, 4, the protrusion value of different types of rocks is calculated respectively, the protrusion value is obtained by calculating the distance between the protruding part and the tunneling face, after measuring the area of the rock, the area corresponding to the rock is multiplied by the protrusion value to obtain the volume value Y of the protruding part, the intensity parameter value Qi corresponding to the rock is substituted into the formula QD1 = [(Qi × p1) 1.12 + Y × p2] × χ, to obtain the rock strength value QD1 of this type of rock, wherein p1 and p2 are respectively the preset weight factors of the intensity parameter value Qi and the volume value Y, and χ is a preset correction factor;

[0015] It should be noted that the collected rock image is digitally processed, including image enhancement, edge detection, segmentation, etc., the characteristic information of the rock can be extracted, such as color, texture, etc., wherein the rock types are mainly limestone, sandstone, granite and shale, and the intensity parameter value is obtained by experimental measurement of different types of rocks.

[0016] Step five: set a preset coefficient corresponding to the rock strength value QD1 of different types of rocks, multiply the rock strength value QD1 of the same type of rock by the corresponding preset coefficient to obtain the rock shape value YSi of the same type of rock, add all the rock shape values YSi of the same type of rock and take the average to obtain the rock shape average YZi, calculate the rock shape average YZi of different types, that is, YZ1, YZ2, YZ3 and YZ4, and substitute all the rock shape averages YZi into the formula to calculate the rock tunneling value TLC of the rock region, wherein v1, v2, v3 and v4 represent the preset weight factors of different types of rock shape averages YZi, and η is a preset weight factor;

[0017] It should be noted that limestone, sandstone, granite and shale correspond to YZ1, YZ2, YZ3 and YZ4 respectively.

[0018] Step six: substitute the fracture tunneling value TLB and the rock tunneling value TLC into the formula to calculate the tunneling adjustment value JUT, wherein m1 and m2 are respectively the preset weight factors of TLB and TLC, and κ is a preset correction factor, and the obtained tunneling adjustment value JUT is sent to the instruction generation module;

[0019] The instruction generation module is used to receive the tunneling adjustment value JUT and execute the corresponding steps:

[0020] When the generated tunneling adjustment value JUT is received, the tunneling adjustment value JUT is substituted into the corresponding preset value range, each value range is set to correspond to a control level of the fully-mechanized coal mining machine, and a corresponding adjustment instruction is generated and sent to the instruction execution module;

[0021] It should be noted that, assuming that the preset value ranges are 0-20, 20-25, 25-30, 30-35, and the like in turn, the control levels of the fully-mechanized coal mining machine are divided into X levels, and these levels one by one correspond to the above-mentioned value ranges, when the tunneling adjustment value JUT is 23.12, and the control level corresponding to the second value range is matched, and each mechanical parameter of the fully-mechanized coal mining machine is adjusted according to the control level;

[0022] The instruction execution module is configured to receive the corresponding instruction and execute the corresponding operation through the tunneling adjustment unit, specifically:

[0023] When the adjustment instruction is received, each value of the fully-mechanized coal mining machine is adjusted according to the adjustment parameter, including the tunneling speed, the cutting force of the cutter head, the hydraulic system, the support parameter, and the propulsion force, and in the tunneling process, the temperature change of the driving end of the fully-mechanized coal mining machine and the wear condition of the cutter are collected and analyzed to obtain a mechanical state value JUB in the tunneling process, and each value of the fully-mechanized coal mining machine is secondarily adjusted according to the obtained mechanical state value JUB;

[0024] The specific process of analyzing the temperature change of the driving end of the fully-mechanized coal mining machine and the wear condition of the cutter through the equipment analysis unit is as follows:

[0025] Step one: obtain the sound data in the working process of the fully-mechanized coal mining machine and substitute it into the frequency spectrum diagram for representation, substitute a preset threshold into the diagram to represent the threshold line, mark the sound exceeding the threshold line as abnormal sound, count the number of sounds exceeding the threshold line and mark it as N1, calculate the shadow area formed between the sound signal exceeding the threshold line and the threshold line, add all the obtained shadow areas to obtain a total area N2, substitute the total area N2 and the sound number N1 into the formula to obtain the cutter wear value DS1, wherein and are preset weight factors of the total area N2 and the sound number N1, respectively;

[0026] Step two: obtain the driving end temperature value at different time in the preset time zone, mainly the temperature value of the cutting tool and the internal motor during operation, analyze the driving end temperature value, set the normal threshold range of the temperature value, if the temperature value is higher than the normal threshold range, mark the temperature value as an abnormal temperature value, add all the abnormal temperature values and take the average to obtain the abnormal temperature average UZ1, mark the time zone where the temperature value is not in the normal threshold range as the abnormal temperature time length, count all the abnormal temperature time lengths and add them to obtain the abnormal temperature total time length UZ3 in the preset time zone, and the abnormal temperature average UZ1, the number of abnormal temperature values UZ2 and the abnormal temperature total time length UZ3 are substituted into the formula to calculate the working temperature value DS2 and VBG, wherein DS2 and VBG represent the cutting tool working temperature value and the motor working temperature value respectively, g1, g2 and g3 are preset weight factors of the abnormal temperature average UZ1, the number of abnormal temperature values UZ2 and the abnormal temperature total time length UZ3 respectively, and v is a preset correction factor;

[0027] Step three: substitute the cutting tool loss value DS1 and the cutting tool working temperature value DS2 into the formula DSC=DS1 x ew1+DS2 x ew2-0.73 to calculate the cutting tool state value DSC, wherein ew1 and ew2 are preset weight factors of the cutting tool loss value DS1 and the cutting tool working temperature value DS2, and the cutting tool state value DSC and the motor working temperature value VBG are substituted into the formula to calculate the mechanical state value POA, wherein gv1 and gv2 are preset weight factors of the cutting tool state value DSC and the motor working temperature value VBG, and o is a preset correction factor, and the mechanical state value POA is sent to the instruction generation module;

[0028] Step four: when the instruction generation module receives the generated mechanical state value POA, the mechanical state value POA is substituted into the corresponding preset value range, different value ranges are set to correspond to one adjustment parameter of the fully mechanized coal mining machine, and a secondary adjustment instruction is generated and sent to the instruction execution module, and the instruction execution module receives the secondary adjustment instruction and adjusts the parameters of the fully mechanized coal mining machine through the tunneling adjustment unit.

[0029] It should be noted that the preset value ranges are assumed to be 30-40, 40-50, 50-60 and the like, the control level of the fully mechanized coal mining machine is divided into Y levels, and these levels correspond to the above value ranges one by one, when the mechanical state value POA is 53.71, the control parameters corresponding to the third value range are matched, and the mechanical parameters of the fully mechanized coal mining machine are further adjusted according to the control parameters.

[0030] Further, the data acquisition module is used to acquire the environmental parameters of the fully mechanized coal mining machine during driving and send them to the analysis module, and the data acquisition module acquires the environmental parameters through the dust acquisition unit;

[0031] The analysis module analyzes and processes the geological parameters through the environment analysis unit, and the specific analysis process is as follows:

[0032] Step one: obtain the dust concentration values at different times in the specified time zone and substitute them into the broken line chart, set a weight threshold line for the time in the specified time zone, set two weight coefficients corresponding to the two divided time zones respectively, multiply the concentration values in the first / second time zone with the corresponding weight coefficients respectively to obtain the corrected concentration values, add the corrected concentration values and take the average to obtain the concentration average ND1;

[0033] Step two: compare the concentration value with the concentration threshold value, when the concentration value is greater than the concentration threshold value, mark the concentration value as an abnormal concentration value, count the number of all abnormal concentration values as J1, respectively calculate the difference between the abnormal concentration value and the concentration threshold value to obtain the exceeding concentration value, match each exceeding concentration value with the corresponding preset range, each preset range corresponds to a preset coefficient, multiply the exceeding concentration value with the corresponding preset coefficient to obtain the abnormal dust value, sum all the abnormal dust values and take the average to obtain the abnormal dust average J2, substitute the number of abnormal concentration values J1 and the abnormal dust average J2 into the formula ND2=1.67 J1×fs1 +J2fs2 to obtain the dust value ND2, wherein fs1 and fs2 are the preset weight factors of the number of abnormal concentration values J1 and the abnormal dust average J2 respectively;

[0034] Step three: substitute the concentration average ND1, the dust value ND2 and the concentration peak value ND3 into the formula to obtain the dust removal value CFG, wherein mu1, mu2 and mu3 are the preset weight factors of the concentration average ND1, the dust value ND2 and the concentration peak value ND3 respectively, and sigma is a preset correction factor, and the obtained dust removal value CFG is sent to the instruction generation module;

[0035] When the instruction generation module receives the generated dust removal value, the dust removal value is substituted into the preset value range, different value ranges correspond to a dust removal fan control level respectively, and the corresponding control instruction is generated and sent to the instruction execution module;

[0036] When the instruction execution module receives the regulation instruction, the dust removal adjustment unit adjusts the parameters of the dry fan according to the regulation level in the regulation instruction, including the fan speed, the opening degree of the inlet and outlet, and analyzes the pressure difference between the two sides of the fan filter in real time during the use of the dust removal fan, specifically: adding the pressure differences at different times and taking the mean value to obtain the pressure mean value, calculating the difference between each pressure difference and the pressure mean value and taking the absolute value to obtain the gap value, adding all the gap values and taking the mean value to obtain the gap mean value KS1, calculating the difference between the highest pressure difference and the lowest pressure difference to obtain the variation value KS2, substituting the gap mean value KS1 and the variation value KS2 into the formula KSZ=KS1*ho1+KS2*ho2, wherein ho1 and ho2 are the preset weight factors of the gap mean value KS1 and the variation value KS2, respectively, to obtain the cleaning filter value KSZ, and comparing the obtained cleaning filter value KSZ with the preset threshold range, when the cleaning filter value KSZ is in the preset threshold range, a filter cleaning instruction is generated and sent to the instruction execution module to clean the filter, and when it is higher than the preset threshold range, a filter replacement instruction is generated to replace the filter.

[0037] Compared with the prior art, the beneficial effects of the present application are:

[0038] 1、The present application collects and analyzes the image of the rock to obtain the fracture excavation value of the fracture of the rock and the rock excavation value corresponding to the volume of the rock, calculates and processes the fracture excavation value and the rock excavation value to obtain the final excavation adjustment value, substitutes the final excavation adjustment value into the preset value range, sets each value range to correspond to a regulation level of the fully mechanized mining machine, adjusts the parameters of the fully mechanized mining machine according to the obtained regulation level, collects the sound signal of the cutter and the temperature change of the driving end during the excavation process, analyzes the mechanical state value of the fully mechanized mining machine during the operation process, and adjusts the parameters of the fully mechanized mining machine according to the adjustment parameters corresponding to the mechanical state value, thereby solving the problem that the parameters of the fully mechanized mining machine cannot be adjusted according to the rock state of the excavation face and the working state during the excavation process in the prior art, the efficiency is not high, and the fully mechanized mining machine is easily damaged.

[0039] 2、The application obtains the dust removal value in the rock roadway by collecting and analyzing the dust concentration in the rock roadway, sets multiple value ranges corresponding to the regulation level of one dust removal fan by substituting the dust removal value into the preset value range, adjusts the fan speed of the dust removal fan and the opening degree of the air port according to the obtained regulation level, collects the pressure difference value of the filter during the use of the fan, analyzes the pressure difference value to obtain the cleaning filter value after the operation is completed, and compares the obtained cleaning filter value with the preset threshold value, so that the filter is cleaned or replaced after the operation is completed when the cleaning filter value is in or higher than the preset threshold value range, thereby avoiding affecting the efficiency of the next tunneling operation. BRIEF DESCRIPTION OF DRAWINGS

[0040] In the following description of the example embodiments in conjunction with the accompanying drawings, more details, features and advantages of the application are disclosed, in which:

[0041] Figure 1 It is a principle block diagram of the application;

[0042] Figure 2 It is a simulation diagram in the tunneling process;

[0043] Figure 3 It is a cutter sound change spectrum diagram;

[0044] Figure 4 It is a dust concentration change line graph. DETAILED DESCRIPTION

[0045] In order for those skilled in the art to better understand the application scheme, the technical solutions in the embodiments of the application will be described clearly and completely in conjunction with the drawings in the embodiments of the application. Obviously, the described embodiments are only a part of the embodiments of the application, not all. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor should belong to the scope of protection of the application.

[0046] It should be noted that the terms "first", "second" and the like in the specification and claims of the application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not necessarily limit to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0047] The accompanying drawings are included to provide a further understanding of the application, and are incorporated in and constitute a part of this specification. Figures 1-4 The application will be described in further detail below:

[0048] Embodiment 1

[0049] Please refer to Figures 1-3 As shown in the drawings, an intelligent rapid tunneling system for rock roadway includes an unmanned fully-mechanized tunneling machine body and a control system for controlling the unmanned fully-mechanized tunneling machine to perform tunneling operation. The control system includes a remote communication module and a controller. The remote communication module is used to connect the controller and the unmanned fully-mechanized tunneling machine body and transmit data. The control system further includes:

[0050] A data acquisition module is used to acquire geological parameters of the fully-mechanized tunneling machine during driving and send them to an analysis module. The data acquisition module acquires the geological parameters through an image acquisition unit.

[0051] The analysis module analyzes and processes the geological parameters through an environment analysis unit. The specific analysis process is as follows:

[0052] Step 1: Obtain rock image information inside the rock roadway during operation of the fully-mechanized tunneling machine, divide the obtained rock image into different regions, and use a segmentation algorithm to separate the fracture region of the rock from other rock regions, thereby obtaining fracture region information and rock type region information.

[0053] Step 2: Analyze the fracture region information, count and mark the number of fractures, measure the straight-line distance between the upper and lower points of the fracture, measure the length of the fracture along the trajectory, calculate the fracture inclination value H1 of the corresponding fracture through the straight-line distance and the length of the trajectory by using a trigonometric function, i.e., fracture inclination value = arctan (length of trajectory / straight-line distance), obtain the fracture displacement value H2 of the corresponding fracture through the length of the trajectory - straight-line distance, calculate the horizontal distance between the left and right points at different positions of the fracture to obtain the fracture width value H3, extract and mark the maximum fracture width value, and substitute the fracture inclination value H1, fracture displacement value H2, and fracture width value H3 into the formula and calculate to obtain the fracture value HU1 of the corresponding fracture, where λ1, λ2, and λ3 are preset weight factors of the fracture inclination value H1, fracture displacement value H2, and fracture width value H3, respectively, and α is a preset correction factor.

[0054] Step three: comparing the broken value HU1 corresponding to different breaking points with the preset threshold range, when the broken value HU1 is higher than the preset threshold range, marking the broken value HU1 as an over-standard broken value, calculating the over-standard difference value between the obtained over-standard broken value and the highest range value in the threshold range, matching each over-standard difference value with the preset range, setting each preset range corresponding to a preset coefficient, multiplying each over-standard difference value with the corresponding preset coefficient to obtain a high broken value, adding all the high broken values and taking the average to obtain a high broken average value HU2, when the broken value HU1 is in the preset threshold range, marking the broken value HU1 as a normal broken value, setting the threshold range corresponding to a preset coefficient, multiplying each normal broken value with the preset coefficient to obtain a medium broken value, adding all the medium broken values after removing a maximum value and a minimum value and taking the average to obtain a medium broken average value HU3, substituting the high broken average value HU2 and the medium broken average value HU3 into the formula TLB=(HU2×aq1+HU3×aq2+0.32)×β to obtain the breaking value TLB of the rock region, wherein aq1 and aq2 are preset weight factors of the high broken average value HU2 and the medium broken average value HU3 respectively, and β is a preset correction factor;

[0055] Step four: analyzing the rock type region, after digital processing of the collected rock type region image, the characteristic information of the rock is extracted, so as to obtain the type of the rock, and the rock of different types corresponds to an intensity parameter value Qi, i=1, 2, 3, 4, the protruding value of different types of rock is calculated respectively, the protruding value is obtained by calculating the distance between the protruding part and the tunneling face, after measuring the area of the rock, the area corresponding to the rock is multiplied with the protruding value to obtain the volume value Y of the protruding part, and the intensity parameter value Qi corresponding to the rock is substituted into the formula to obtain the rock strength value QD1 of the rock of this type, wherein p1 and p2 are preset weight factors of the intensity parameter value Qi and the volume value Y respectively, and χ is a preset correction factor.

[0056] It should be noted that the digital processing of the collected rock image includes image enhancement, edge detection, segmentation, etc., and the characteristic information of the rock can be extracted, such as color, texture, etc., wherein the rock types are mainly limestone, sandstone, granite and shale, and the intensity parameter value is obtained by experimental measurement of different types of rock.

[0057] Step five: set the rock strength value QD1 of different kinds of rocks respectively corresponding to a preset coefficient, multiply the rock strength value QD1 of the same kind of rock and the corresponding preset coefficient to obtain the rock value YSi of the kind of rock, add all the rock values YSi of the kind of rock and take the average to obtain the rock average value YZi, calculate the rock average value YZi of different kinds, that is, YZ1, YZ2, YZ3 and YZ4, and substitute all the rock average values YZi into the formula to obtain the rock tunneling value TLC of the rock area, wherein v1, v2, v3 and v4 respectively represent the preset weight factor of the rock average value YZi of different kinds, and η is a preset weight factor;

[0058] It should be noted that the limestone, sandstone, granite and shale correspond to YZ1, YZ2, YZ3 and YZ4 respectively.

[0059] Step six: substitute the fracture tunneling value TLB and the rock tunneling value TLC into the formula to obtain the tunneling adjustment value JUT, wherein m1 and m2 are the preset weight factors of TLB and TLC respectively, and κ is a preset correction factor, and the obtained tunneling adjustment value JUT is sent to the instruction generation module;

[0060] The instruction generation module is used to receive the tunneling adjustment value JUT and execute the corresponding steps:

[0061] When the generated tunneling adjustment value JUT is received, the tunneling adjustment value JUT is substituted into the corresponding preset value range, it is set that each value range corresponds to a control level of the fully mechanized coal mining machine, and the corresponding adjustment instruction is generated and sent to the instruction execution module;

[0062] It should be noted that the preset value range is assumed to be 0-20, 20-25, 25-30, 30-35 and the like in turn, the control level of the fully mechanized coal mining machine is set to X levels, and these levels correspond to the above value ranges one by one, when the tunneling adjustment value JUT is 23.12, the control level corresponding to the second value range is matched, and the mechanical parameters of the fully mechanized coal mining machine are adjusted according to the control level;

[0063] The instruction execution module is used to receive the corresponding instruction and execute the corresponding operation through the tunneling adjustment unit, specifically:

[0064] When receiving the adjustment instruction, the various values of the fully-mechanized coal mining machine are adjusted according to the adjustment parameters, including the tunneling speed, the cutting force of the cutter head, the hydraulic system, the support parameters and the pushing force, and in the tunneling process, the temperature change of the driving end of the fully-mechanized coal mining machine and the wear condition of the cutter are collected and analyzed to obtain the mechanical state value JUB in the tunneling process, and the various values of the fully-mechanized coal mining machine are secondarily adjusted according to the obtained mechanical state value JUB;

[0065] The specific process of analyzing the temperature change of the driving end of the fully-mechanized coal mining machine and the wear condition of the cutter by the equipment analysis unit is as follows:

[0066] Step one: obtaining the sound data in the working process of the fully-mechanized coal mining machine and representing it in the frequency spectrum, substituting the preset threshold value into the graph to represent it with a threshold line, marking the sound exceeding the threshold line as abnormal sound, counting the number of sounds exceeding the threshold line and marking it as N1, calculating the shadow area formed between the sound signal exceeding the threshold line and the threshold line, adding all the obtained shadow areas to obtain the total area N2, and substituting the total area N2 and the sound number N1 into the formula to obtain the cutter wear value DS1, wherein and are the preset weight factors of the total area N2 and the sound number N1, respectively;

[0067] Step two: obtaining the driving end temperature values at different times in the preset time zone, the driving end mainly being the temperature values of the cutter and the internal motor of the fully-mechanized coal mining machine in the running process, analyzing the driving end temperature values, setting the normal threshold range of the temperature, marking the temperature value higher than the normal threshold range as an abnormal temperature value, adding all the abnormal temperature values and taking the average to obtain the abnormal temperature average UZ1, marking the time zone in which the temperature value is not in the normal threshold range as the abnormal temperature time length, counting and adding all the abnormal temperature time lengths to obtain the abnormal temperature total time length UZ3 in the preset time zone, and substituting the abnormal temperature average UZ1, the number of abnormal temperature values UZ2 and the abnormal temperature total time length UZ3 into the formula to obtain the working temperature values DS2 and VBG, wherein DS2 and VBG respectively represent the cutter working temperature value and the motor working temperature value, g1, g2 and g3 are respectively the preset weight factors of the abnormal temperature average UZ1, the number of abnormal temperature values UZ2 and the abnormal temperature total time length UZ3, and v is a preset correction factor;

[0068] Step three: substituting the cutter wear value DS1 and the cutter working temperature value DS2 into the formula DSC=DS1×ew1+DS2×ew2-0.73 to obtain the cutter state value DSC, wherein ew1 and ew2 are respectively the preset weight factors of the cutter wear value DS1 and the cutter working temperature value DS2, and substituting the cutter state value DSC and the motor working temperature value VBG into the formula A mechanical state value POA is calculated, wherein gv1 and gv2 are preset weight factors of the tool state value DSC and the motor working temperature value VBG respectively, and o is a preset correction factor, and is sent to the instruction generation module;

[0069] Step four: when the instruction generation module receives the generated mechanical state value POA, the mechanical state value POA is substituted into the corresponding preset value range, different value ranges are set to correspond to the adjustment parameters of the fully-mechanized coal mining machine, and a secondary adjustment instruction is generated and sent to the instruction execution module. After receiving the secondary adjustment instruction, the instruction execution module adjusts the parameters of the fully-mechanized coal mining machine through the tunneling adjustment unit.

[0070] It should be noted that the preset value ranges are assumed to be 30-40, 40-50, 50-60, and the like in turn, the control level of the fully-mechanized coal mining machine is divided into Y levels, and these levels correspond to the above-mentioned value ranges one by one. When the mechanical state value POA is 53.71, the control parameters corresponding to the third value range are matched, and the mechanical parameters of the fully-mechanized coal mining machine are further adjusted according to the control parameters.

[0071] Embodiment 2

[0072] Please refer to Figure 1 and Figure 4 The data acquisition module is used to acquire the environmental parameters of the fully-mechanized coal mining machine during driving and send them to the analysis module. The data acquisition module acquires the environmental parameters through the dust acquisition unit.

[0073] The analysis module analyzes and processes the geological parameters through the environmental analysis unit. The specific analysis process is as follows:

[0074] Step one: acquire the dust concentration values at different times in the specified time zone and substitute them into the broken line graph. Set the time weight threshold line in the specified time zone. Set the weight coefficients corresponding to the two time zones after segmentation. Multiply the concentration values in the first / second time zone with the corresponding weight coefficients to obtain the corrected concentration values. Add the corrected concentration values and take the average to obtain the concentration average ND1.

[0075] Step two: compare the concentration value with the concentration threshold value. When the concentration value is greater than the concentration threshold value, mark the concentration value as an abnormal concentration value. Count the number of all abnormal concentration values and mark it as J1. Calculate the difference between the abnormal concentration value and the concentration threshold value to obtain the exceeding concentration value. Match each exceeding concentration value with the corresponding preset range. Each preset range corresponds to a preset coefficient. Multiply the exceeding concentration value with the corresponding preset coefficient to obtain the abnormal dust value. Sum all abnormal dust values and take the average to obtain the abnormal dust average J2. Substitute the number of abnormal concentration values J1 and the abnormal dust average J2 into the formula ND2=1.67J1×fs1 +J2×fs2 to calculate a dustiness value ND2, wherein fs1 and fs2 are preset weight factors of the number of abnormal concentration values J1 and the average dustiness value J2, respectively;

[0076] Step three: substituting the concentration average value ND1, the dustiness value ND2 and the concentration peak value ND3 into the formula to calculate a dedusting value CFG, wherein mu1, mu2 and mu3 are preset weight factors of the concentration average value ND1, the dustiness value ND2 and the concentration peak value ND3, respectively, and σ is a preset correction factor, and the obtained dedusting value CFG is sent to the instruction generation module;

[0077] When the instruction generation module receives the generated dedusting value, the dedusting value is substituted into a preset value range, different value ranges correspond to a dedusting fan control level, respectively, and corresponding control instructions are generated and sent to the instruction execution module;

[0078] When the instruction execution module receives the control instruction, the dedusting adjustment unit adjusts each parameter of the dedusting fan according to the control level in the control instruction, including the fan speed, the opening degree of the inlet and the outlet, and real-time collects and analyzes the pressure difference between the two sides of the fan filter during the use of the dedusting fan. Specifically, the pressure average value is obtained by adding and averaging the pressure difference values at different times, the difference value is calculated between each pressure difference value and the pressure average value, and the absolute value is taken to obtain the gap value, the gap average value KS1 is obtained by adding and averaging all the gap values, and the difference value KS2 is obtained by calculating the difference between the highest pressure difference value and the lowest pressure difference value. Substituting the gap average value KS1 and the difference value KS2 into the formula KSZ=KS1×ho1+KS2×ho2, wherein ho1 and ho2 are preset weight factors of the gap average value KS1 and the difference value KS2, respectively, to calculate a clean filter value KSZ. The clean filter value KSZ is compared with the preset threshold range. When the clean filter value KSZ is within the preset threshold range, a filter cleaning instruction is generated and sent to the instruction execution module to clean the filter. When it is higher than the preset threshold range, a filter replacement instruction is generated to replace the filter.

[0079] The preferred embodiments disclosed above are only used to help explain the present application. The preferred embodiments do not describe all the details and do not limit the present application to the specific embodiments. Obviously, many modifications and variations can be made according to the content of the present application. The present application is selected and described in detail to better explain the principles and practical applications of the present application, so that those skilled in the art can well understand and utilize the present application. The present application is limited by the claims and their entire scope and equivalents.

Claims

1. A rock roadway intelligent rapid excavation system, comprising an unmanned fully-mechanized excavator body and a control system for controlling the unmanned fully-mechanized excavator to perform an excavation operation, the control system comprising a remote communication module and a controller, the remote communication module being configured to connect the controller and the unmanned fully-mechanized excavator body and transmit data, characterized in that, The control system further comprises: a data acquisition module for acquiring geological parameters and environmental parameters of the fully-mechanized mining machine during driving and sending to the analysis module; the analysis module is configured to analyze and process the geological parameters and the environmental parameters to obtain corresponding parameter values, wherein the parameter values include a rock tunneling value and a dust removal value, and the specific analysis process comprises: Step one: obtaining rock image information inside the rock roadway during operation of the fully-mechanized mining machine, segmenting the obtained rock image into different regions, and separating the fracture region of the rock from other rock regions using a segmentation algorithm to obtain fracture region information and rock type region information; Step two: analyzing the fracture region information, counting and marking the number of fractures, measuring the straight-line distance between the upper and lower points of the fracture, measuring the length of the fracture along the trajectory to obtain the fracture trajectory length, calculating the fracture angle value of the corresponding fracture by using a trigonometric function on the straight-line distance and the length of the trajectory, obtaining the fracture displacement value of the corresponding fracture by using the length of the trajectory-straight-line distance, calculating the horizontal distance between the left and right points at different positions of the fracture to obtain the fracture width value, extracting and marking the maximum fracture width value, and calculating the fracture value of the corresponding fracture by using the fracture angle value, the fracture displacement value, and the fracture width value; Step three: comparing the broken value corresponding to different breaking points with the preset threshold range, when the broken value is higher than the preset threshold range, marking the broken value as an over-standard broken value, calculating the over-standard difference value between the obtained over-standard broken value and the highest range value in the threshold range, matching each over-standard difference value in the corresponding preset range, setting each preset range corresponding to a preset coefficient, multiplying each over-standard difference value with the corresponding preset coefficient to obtain a high broken value, adding all the obtained high broken values and taking the average to obtain a high broken average value, when the broken value is in the preset threshold range, marking the broken value as a normal broken value, setting the threshold range corresponding to a preset coefficient, multiplying each normal broken value with the preset coefficient to obtain a medium broken value, adding all the obtained medium broken values after removing a maximum value and a minimum value and taking the average to obtain a medium broken average value, and substituting the high broken average value HU2 and the medium broken average value HU3 into the formula to obtain the rock area broken driving value TLB, wherein aq1 and aq2 are preset weight factors of the high broken average value HU2 and the medium broken average value HU3, is a preset correction factor; Step four: analyzing the rock type region, extracting the feature information of the rock after digital processing of the collected rock type region image to obtain the type of the rock, predefining an intensity parameter value corresponding to each type of rock, calculating the protrusion value of each type of rock, obtaining the protrusion value by calculating the distance between the protruding part and the tunneling surface, multiplying the area of the corresponding rock by the protrusion value to obtain the volume value of the protruding part after measuring the area of the rock, and calculating the rock strength value of the rock of the type by using the intensity parameter value and the volume value of the corresponding rock; Step five: setting a preset coefficient corresponding to the rock strength value of each type of rock, multiplying the rock strength value of the same type of rock by the corresponding preset coefficient to obtain the rock value of the rock of the type, adding all the rock values of the rock of the type and taking the average to obtain the rock value, calculating the rock value of each type of rock, and calculating the rock tunneling value of the rock region by using all the rock values of the rock; Step six: put the breaking tunneling value TLB and the rock tunneling value TLC into the formula , and calculate the tunneling adjustment value JUT, wherein m1 and m2 are preset weight factors of TLB and TLC respectively, is a preset correction factor, and the obtained tunneling adjustment value is sent to the instruction generation module; an instruction generation module configured to receive the corresponding parameter values and execute corresponding steps: when receiving the generated tunneling adjustment value, substituting the tunneling adjustment value into a corresponding preset value range, setting each value range to correspond to a control level of the fully-mechanized mining machine, and generating a corresponding adjustment instruction and sending the adjustment instruction to the instruction execution module; the instruction execution module is configured to receive the adjustment instruction and execute corresponding operations, specifically: When receiving the adjustment instruction, the various values of the fully mechanized mining machine are adjusted according to the adjustment parameters, including the tunneling speed, the cutting force of the cutter head, the hydraulic system, the support parameters and the propulsion force, and in the tunneling process, the temperature change of the driving end of the fully mechanized mining machine and the wear of the cutter are collected and analyzed to obtain the mechanical state value in the tunneling process, and the various values of the fully mechanized mining machine are secondarily adjusted according to the obtained mechanical state value.

2. The intelligentized rapid tunneling system for rock roadway according to claim 1, characterized in that, The specific process of analyzing the temperature change of the driving end of the fully mechanized mining machine and the wear of the cutter is as follows: Step one: obtain the sound data in the working process of the fully mechanized mining machine and substitute it into the frequency spectrum diagram for representation, substitute the preset threshold value into the diagram and represent it with a threshold line, mark the sound exceeding the threshold line as abnormal sound, count the number of sounds exceeding the threshold line and mark them, calculate the shadow area formed between the sound signal exceeding the threshold line and the threshold line, add all the obtained shadow areas to obtain the total area, and calculate the total area and the number of sounds to obtain the cutter wear value; Step two: obtain the driving end temperature value at different times in the preset time zone, analyze the driving end temperature value, set the normal threshold range of the temperature, if the temperature value is higher than the normal threshold range, mark this temperature value as an abnormal temperature value, add all the abnormal temperature values and take the average to obtain the abnormal temperature average, mark the time region in which the temperature value is not in the normal threshold range as the abnormal temperature time length, count all the abnormal temperature time lengths and add them to obtain the abnormal temperature total time length in the preset time zone, and calculate the abnormal temperature average, the number of abnormal temperature values and the abnormal temperature total time length to obtain the cutter working temperature value and the motor working temperature value, respectively; Step three: calculate the cutter state value between the cutter wear value and the corresponding cutter working temperature value, calculate the mechanical state value between the cutter state value and the motor working temperature value, and send them to the instruction generation module; Step four: when the instruction generation module receives the generated mechanical state value, substitute the mechanical state value into the corresponding preset value range, set different value ranges corresponding to one adjustment parameter of the fully mechanized mining machine, generate a secondary adjustment instruction and send it to the instruction execution module, and the instruction execution module receives the secondary adjustment instruction and secondarily adjusts the various parameters of the fully mechanized mining machine.

3. The intelligentized rapid tunneling system for rock roadway according to claim 2, characterized in that, The specific analysis process of the analysis module on the environmental parameters is as follows: Step one: obtain the dust concentration value at different times in the specified time zone and substitute it into the line graph, set the time weight threshold line in the specified time zone, set the weight coefficient corresponding to each of the two divided time zones, multiply the concentration value in the first / second time zone with the corresponding weight coefficient to obtain the corrected concentration value, add the corrected concentration values and take the average to obtain the concentration average; Step two: obtain the dust concentration value at different times in the specified time zone and substitute it into the line graph, set the time weight threshold line in the specified time zone, set the weight coefficient corresponding to each of the two divided time zones, multiply the concentration value in the first / second time zone with the corresponding weight coefficient to obtain the corrected concentration value, add the corrected concentration values and take the average to obtain the concentration average; Step two: compare the concentration value with the concentration threshold value, when the concentration value is greater than the concentration threshold value, mark the concentration value as an abnormal concentration value, count the number of all abnormal concentration values and mark them, respectively calculate the difference between the abnormal concentration value and the concentration threshold value to obtain the exceeding concentration value, match each exceeding concentration value with the corresponding preset range respectively, each preset range corresponds to a preset coefficient, multiply the exceeding concentration value and the corresponding preset coefficient to obtain the dustiness value, sum all dustiness values and take the average to obtain the dustiness average, calculate the number of abnormal concentration values and the dustiness average to obtain the dustiness value; Step three: calculate the concentration average, dustiness value and concentration peak value to obtain the dust removal value, and send the obtained dust removal value to the instruction generation module.

4. The intelligentized rapid tunneling system for rock roadway according to claim 3, characterized in that, When the instruction generation module receives the generated dust removal value, the dust removal value is substituted into the preset value range, different value ranges correspond to a dust removal fan control level, and the corresponding control instruction is generated and sent to the instruction execution module; When the instruction execution module receives the control instruction, adjust the parameters of the dry fan according to the control level in the control instruction, including fan speed, inlet and outlet opening degree, and real-time collect and analyze the pressure difference of the fan filter during the use of the dust removal fan, specifically: add the pressure difference values at different times and take the average to obtain the pressure average, calculate the difference between each pressure difference value and the pressure average and take the absolute value to obtain the difference value, add all difference values and take the average to obtain the difference average, calculate the difference between the highest pressure difference value and the lowest pressure difference value to obtain the variation value, calculate the difference between the difference average and the variation value to obtain the cleaning filter value, compare the obtained cleaning filter value with the preset threshold value range, when the cleaning filter value is in the preset threshold value range, the filter cleaning instruction is generated and sent to the instruction execution module to clean the filter, and when it is higher than the preset threshold value range, the filter replacement instruction is generated to replace the filter.

5. The intelligentized rapid tunneling system for rock roadway according to claim 4, characterized in that, The controller includes a work planning module, which is used for workers to input the geographical data of the to-be-worked area and analyze the geographical data to generate a geographical model of the to-be-worked area.

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