1713results about "Slitting machines" patented technology

The present disclosure provides a method and system for monitoring a coal shearer status based on digital twinning, and an electronic device, and relates to the technical field of real-time status monitoring. The method includes: obtaining physical parameters, real-time driving data, and real-time status data of a coal shearer physical entity, where the physical parameters include geometric parameters, material properties, and positional parameters; the real-time driving data includes a real-time position, a real-time speed, and a real-time angle of a rocker arm; and the real-time status data includes real-time vibration information; building a coal shearer digital twin model on a Unity3D engine according to the physical parameters of the coal shearer physical entity; and updating a status of the coal shearer digital twin model based on the real-time driving data and the real-time status data. The present disclosure achieves visual monitoring of a coal shearer status.

The invention discloses an intelligent safety monitoring method and system for coal mine excavation, and belongs to the technical field of coal mine safety, and the method specifically comprises the steps: deploying a plurality of adaptive sensing nodes in an excavation area, each node comprising an environment state collection unit and an equipment vibration collection unit, and collecting environment data and mechanical vibration waveforms respectively; then, according to the position of the mining machine and the tunnel structure change, node physical connection is adjusted to form a dynamic topology network, and when mechanical movement exceeds a threshold value, adjacent nodes are subjected to high-density monitoring; then, synchronously generating a coupling data stream according to the collected data timestamps, inputting the coupling data stream into a pre-constructed model, and predicting the overlap ratio of mechanical vibration abnormity and a target gas accumulation area space; when the overlap ratio exceeds a critical value, an emergency response is triggered, the speed is reduced firstly, inert gas is released, and power is cut off if set duration is continued; and finally, reversely correcting surrounding rock stress parameters in the model according to emergency data. According to the invention, the accuracy and response timeliness of early warning of coal mine disasters are improved.

The invention discloses a heading equipment cutting head position calibration method based on image acquisition, which comprises the following steps: S1, acquiring image data and preprocessing the image data; s2, extracting cutting head feature points, and constructing a two-dimensional feature point set; s3, calculating a three-dimensional coordinate by using perspective transformation, and generating a point cloud set; s4, performing rigid registration on the point cloud set and a standard structure model of the tunneling equipment, and iteratively solving a rotation matrix and a translation vector to obtain pose parameters; s5, simulating change tracks of the feature points in continuous frames, constructing a time consistency constraint, and optimizing pose parameters; s6, the optimized three-dimensional coordinates are converted to a reference coordinate system, space alignment is completed, and a position calibration result is generated; and S7, outputting a calibration result for control instruction generation and path planning. According to the invention, high-precision and non-contact three-dimensional position calibration of the cutting head of the tunneling equipment is realized, and operation automation and control precision are improved.

The invention belongs to the technical field of lithology identification, and discloses a coal cutter self-adaptive regulation and control method for coal rock identification based on cutting pick stress monitoring, so as to realize accurate and efficient identification of coal rock and self-adaptive regulation and control of a coal cutter based on cutting pick stress data and in combination with operation parameters of the coal cutter. According to the coal mining machine self-adaptive regulation and control method based on cutting pick stress monitoring and coal rock recognition, the pressure sensors arranged at the roots of all the cutting picks are used for obtaining cutting pick stress original data in real time, the coal rock interface is accurately and efficiently recognized by combining the operation parameters of the coal mining machine and utilizing a data processing and analysis algorithm, and the coal mining machine self-adaptive regulation and control method is high in practicability. And the cutting parameters of the coal mining machine are dynamically adjusted, so that safe, efficient and high-precision coal rock identification and self-adaptive regulation and control of the coal mining machine are realized, the intelligentization of coal mining operation is improved, the coal mining efficiency is improved, the abrasion of equipment is reduced, and the safety and stability of the mining operation are guaranteed.

The invention discloses an efficient thin seam coaling roller for a coal mining machine and a using method, and relates to the field of coal mining equipment. A thin seam efficient coaling roller for a coal mining machine comprises a coal mining spiral roller which is fixedly installed at the power output end of a driving rocker arm of the coal mining machine through a fixing bolt; the mounting cover is fixedly mounted at the position, close to the coal mining spiral drum, of the coal mining machine driving rocker arm; while the coal mining spiral drum rotates to mine coal, water spraying at the rocker arm of the coal mining machine, water spraying at the cutting tooth seat and mist curtains sprayed by the wide-angle fan-shaped atomizing nozzles work cooperatively, the dust falling effect is enhanced, a water mist cover is rapidly formed under the assistance of the mounting cover, and the water mist cover can effectively isolate coal dust inside, so that the dust falling effect is improved. And the coal dust diffusion is greatly reduced, the body health of miners is guaranteed, the occupational health risk is reduced, the abrasion of the coal dust to equipment is reduced, the service life of the equipment is prolonged, the maintenance frequency and cost of the equipment are reduced, and the comprehensive benefits of coal mining operation are improved.

The invention discloses a mining equipment positioning system and method based on radar, ultra wide band and inertial navigation, and the system is characterized in that a multi-source sensor unit, a data synchronization and collection module and a preprocessing module are connected in sequence, and a state fusion module is connected with the preprocessing module, a UWB ranging error compensation module, a radar motion estimation module and a pose output module; the upper computer is connected with the pose output module; the method comprises the steps of collecting multi-source data; timestamp alignment and format conversion processing are carried out, and feature and speed constraint information extraction is carried out on the point cloud data; fitting correction is carried out on the ranging data by adopting a weighted least square method, and position information is obtained through an error weighted average algorithm; feature matching is carried out, and in combination with a KISS-ICP point cloud registration method, a speed estimation result is obtained; carrying out data fusion, and obtaining a pose estimation result by adopting an extended Kalman filtering algorithm; and outputting equipment position and attitude information. According to the invention, high-precision real-time estimation of the attitude and position information of the mining equipment can be realized.

The invention discloses a shield pressure relief drill tool for a protruding coal seam and an out-of-hole closed slag discharge system. The drill tool is composed of a plurality of sieve hole drill rods, a transition drill rod and a plug-in drill bit. The sieve hole drill rod and the transition drill rod are composed of different special-shaped outer tubes, inner tubes and tapered hole strips. The axial space between the outer tube and the inner tube is a flow supply channel of the drill tool. The central hole of the inner tube is an internal slag discharge channel of the drill tool. The slag discharge sieve hole is arranged in an axial groove of the special-shaped outer tube and is connected with the internal slag discharge channel. The tapered hole strip is welded in the axial groove of the special-shaped outer tube and the tapered hole is coaxially aligned with the slag discharge sieve hole. Male buckles and female buckles are arranged at both ends of the sieve hole drill rod. A female buckle connected to the male buckle of the sieve hole drill rod is arranged at one end of the transition drill rod, and a plug-in interface connected to the plug-in drill bit is arranged at the other end of the transition drill rod. The out-of-hole closed slag discharge system comprises a sliding closed tube placed in the inner cavity of the out-of-hole sieve hole drill rod, a sealing hole pipe moving device installed at the hole mouth and a hollow slag discharge water (wind) tail connected to the tail of the drill rod.

The invention is applicable to the technical field of coal mine tunneling, and provides a coal mine tunneling working method based on a digital twinning system, which comprises the following steps: S1, constructing a three-dimensional dynamic geological twinning model integrating geological radar, measurement while drilling and optical fiber sensing; s2, in the three-dimensional dynamic geological twinborn model, rock stratum characteristic changes are predicted through a digital twinborn body, and a self-adaptive cutting control instruction is generated; s3, simulating gas diffusion and roof stress distribution in real time while the control instruction is sent out, and triggering a grading early warning mechanism; s4, optimizing cutting parameters and emergency plans in a virtual environment according to early warning conditions, reversely controlling physical equipment, setting geological-equipment two-way closed-loop control, breaking through a traditional one-way data acquisition mode, realizing real-time two-way interaction between a geological model and tunneling equipment, establishing a digital twinning driven tunneling process parameter optimization standard library, and realizing real-time two-way interaction between the geological model and the tunneling equipment. Data support is provided for iteration of the technology, and improvement of coal mine tunneling work is facilitated.

The present invention provides a support assembly and a tunnel boring machine. The support assembly is applied to the tunnel boring machine and includes: a base; a drive assembly, one end of which is connected to the tunnel boring machine and the other end of which is connected to the base, for driving the base to move; a support plate, which is arranged on the base and is used to support the anchor net; and a support beam assembly, which is arranged on the base and is used to lift and support the top beam. The present application integrates the support beam assembly on the support assembly, improves the functional integration of the tunnel boring machine, saves equipment space, improves the production efficiency of the equipment, and saves the production cost of the equipment. In addition, the support plate and the support beam assembly share a set of drive assemblies, thus saving a set of drive assemblies. Compared with the separate arrangement of temporary support and support beam device, the number of components is greatly simplified, and the contradiction that the temporary support and support beam device cannot be installed on the tunnel boring machine at the same time due to the overlapping installation positions of the temporary support and the support beam device is resolved, providing more operating space for the anchoring operation and beam erection operation of the tunnel boring machine.

The vertical feeding coal mining machine comprises a rack, a traction part and a cutting assembly, the traction part is connected with the rack so as to be used for dragging the rack to move, the cutting assembly comprises a roller body and cutting teeth, the roller body comprises a cylinder body, an end disc and an end cover, the end disc is arranged on the cylinder body, and the cutting teeth are arranged on the end disc. The end disc is arranged on the outer circumferential wall of the roller body in a sleeving mode, the end disc and the first end of the roller body are arranged in a flush mode, the end cover is connected with the inner circumferential wall of the roller body, a groove is defined between the end cover and the roller body, the multiple cutting teeth are arranged in the circumferential direction of the center line of the roller body at intervals, and the cutting teeth are arranged in the groove. One part of the plurality of cutting teeth is connected with the end disc, and the other part of the plurality of cutting teeth is connected with the end cover. According to the vertical feeding coal mining machine, the arrangement positions of the cutting picks are optimized, the possibility of abrasion of the cutting picks is reduced, and the cutting efficiency is improved.

The invention discloses an intelligent working face remote monitoring method and system based on coal machine equipment, and the method comprises the steps: collecting the operation data and environment data of the coal machine equipment, and carrying out the preprocessing; and analyzing the preprocessed data according to a multi-level hybrid integrated deep neural network algorithm to obtain a current risk coefficient. Different measures are taken for different risk conditions, and one-time monitoring is completed. According to the intelligent working face remote monitoring method and system based on the coal machine equipment provided by the invention, spatial and temporal features are extracted by using a convolutional layer in a deep learning model, a recursive layer captures a time sequence dependency relationship, and different weights are given to different features by an attention mechanism, so that the operation state and potential risks of the equipment are accurately evaluated. According to the step, the fusion analysis of high-dimensional data is realized through the multi-level design of the deep neural network model, and the accuracy and real-time performance of risk assessment are remarkably improved.

The invention relates to the field of coal mining, in particular to an ultra-narrow multifunctional reversed loader suitable for a coal mine tunnel, and aims to solve the problem that an excavator in the prior art is inconvenient to convey a coal mine in a narrow pipeline. The crawler walking assembly is mounted at the bottom of the saddle, the mounting frame is fixed to the top of the saddle, and a conveying space is formed between the mounting frame and the top of the saddle; the excavating mechanism comprises a rotary table rotationally connected to the top of the mounting frame, an excavating arm assembly mounted on the rotary table and a driving part mounted on the top surface of the mounting frame and used for driving the rotary table to rotate; and the material conveying mechanism comprises a fixing frame mounted at the top of the saddle, a conveying belt mounted on the fixing frame and a material receiving table mounted at the head of the fixing frame. According to the excavator, excavated coal in the bucket can be conveniently conveyed to the rear portion of the excavator through the conveying belt, and coal cinder adhering to the material guide plate can be conveniently cleaned.

Systems and methods for industrial robotic platforms. Squads of industrial robots autonomously communicate and work together. A control center may monitor the autonomous operations. Software at the control center, squad, and robot levels forms a distributed control system that analyzes various data related to the platform for monitoring of the various systems. Artificial intelligence, such as machine learning, is implemented at the control center, squad, and / or robot levels for swarm behavior driven by intelligent decision making. Each robot may include a universal platform attached to a task-specific tooling system. A robot may be elected as a squad leader, cartographer leader, or task planning leader. A squad leader, cartographer leader, or task planning leader may perform specialized planning functions for a squad of robots. Information generated by robots performing a task may be transmitted to the control center for further development of machine learning models.

The invention relates to a fully mechanized coal mining face respirable dust concentration management limit value determination method, belongs to the technical field of coal mine dust treatment, and is used for solving the problem of inaccurate respirable dust control caused by the fact that a traditional fixed threshold value cannot adapt to a multi-dust-source coupling working condition. The method comprises the following steps: acquiring dust falling efficiency data of multiple dustproof measures, establishing a mathematical model of dustproof parameters and dust concentration, calculating a dynamic management limit value by combining an industrial standard threshold value, and performing self-adaptive adjustment by monitoring and triggering parameters such as spraying pressure and dust removal air volume in real time. Compared with a traditional method, the dynamic limit value enables the respirable dust concentration to be reduced by 40% or above, the multi-measure cooperative dust falling efficiency is improved to 85%, water is saved by 15%-20%, the equipment energy consumption is reduced by 10%, and intelligent and precise dust treatment is achieved.

The invention provides a scraper conveyor coal flow real-time monitoring system and method, and belongs to the technical field of coal flow monitoring. The problem that the coal flow on the scraper conveyor is not uniformly distributed due to the fact that the coal cutting amount and the coal sweeping amount are not organically combined in the coal flow monitoring of the scraper conveyor in the prior art is solved. Comprising coal flow monitoring devices used for collecting coal flow data generated by coal cutting or coal sweeping of a left rocker arm or a right rocker arm in the coal mining process in real time, the two coal flow monitoring devices are connected with a coal flow resolver, and the coal flow resolver communicates with a coal mining machine control system and a scraper conveyor control system. The coal flow resolver is used for receiving data acquired by the coal flow monitoring devices on the left / right rocker arm, resolving the acquired data into actual coal flow, and sending the coal flow of the left / right rocker arm and total coal flow data to the coal mining machine control system and the scraper conveyor control system; the method is applied to monitoring and adjusting the coal flow of the scraper conveyor on the fully mechanized coal mining face.

The invention provides a construction method of a self-adaptive cutting guide control system of a coal mining machine based on digital twinning, and relates to the technical field of self-adaptive cutting of coal mining machines. The method specifically comprises the following steps: designing a complex dirt band thin coal seam coal mining machine cutting state sensing method and a complex dirt band thin coal seam coal mining machine self-adaptive control strategy; the method comprises the following steps: based on a complex dirt band thin coal seam coal mining machine cutting state sensing method and a complex dirt band thin coal seam coal mining machine self-adaptive control strategy, establishing a complex dirt band thin coal seam coal mining machine self-adaptive cutting digital twinborn model for simulating the self-adaptive cutting process of the complex dirt band thin coal seam coal mining machine; and constructing a mechanism characteristic life prediction model driven by a digital model and a digital twinborn monitoring model for the adaptive cutting dynamic reliability of the coal mining machine for the complex dirt band thin coal seam, wherein the model is used for evaluating the reliability of the adaptive cutting process of the coal mining machine for the complex dirt band thin coal seam in real time. According to the invention, the adaptive capacity of the coal mining machine to the complex dirt band thin coal seam can be effectively improved.

The invention discloses a high-pressure jet flow intelligent mining self-adaptive monitoring control system which comprises a jet flow rock breaking dynamic monitoring module, a rock mass analysis and data processing module, a neural network deep learning module and a mining machine controller. The jet flow rock breaking dynamic monitoring module is used for obtaining jet flow parameters, calculating jet flow axial reverse thrust, obtaining the three-dimensional shape of a mining face and obtaining cutting and crack shapes. Wherein the three-dimensional shape of the mining face at least comprises cutting depth information; the rock mass analysis and data processing module is used for acquiring three-dimensional coordinates of the mining machine in a working environment, calculating rock mass confining pressure and acquiring rock mass characteristics; the neural network deep learning module establishes a jet cutting process parameter and mining process parameter intelligent model; the mining machine controller is used for generating a mining machine control instruction. According to the invention, the high-pressure jet mining equipment can be safely and efficiently controlled to carry out self-adaptive cutting on the ore / rock mass.

The invention discloses an intelligent bottom-along tunneling control method and system for a tunneling and anchoring all-in-one machine, and relates to the technical field of intelligent control, and the method comprises the following steps: obtaining a cutting instruction set for roadway coal rock; according to the cutting instruction set, manual teaching memory is carried out by a worker, and then a memory automatic cutting stage is entered; in the automatic operation process of the digging and anchoring all-in-one machine, the ground penetrating radar obtains monitoring data in real time and carries out noise reduction processing, and therefore clear roadway floor radar image signals are obtained; inputting the obtained roadway floor radar image signal into a preset roadway floor coal seam thickness estimation model to obtain the thickness of the roadway floor remaining coal; the multi-sensor information fusion technology is adopted, cutting medium attributes in the tunneling process of the tunneling and anchoring all-in-one machine are recognized on line, dynamic optimization control is conducted on the cutting action of the tunneling and anchoring all-in-one machine according to the recognition result, and a comprehensive cutting state monitoring and intelligent cutting solution is provided for a roadway tunneling face.

The invention discloses a low seam few-person fully mechanized coal mining face mining system and method, the system comprises a coal mining machine automatic control system and a hydraulic support electrohydraulic control system, the coal mining machine automatic control system realizes position information transmission and height adjustment of a coal mining machine; the hydraulic support electro-hydraulic control system achieves hydraulic support pulling, pushing and sliding, machine following and support moving and automatic control over actions of the hydraulic support, and the remote control system conducts three-machine linkage control over key production equipment of the fully mechanized coal mining face, automatic control, locking, sudden stop, fault diagnosis, automatic liquid supplementing and data information transmission on the hydraulic support. Coal face equipment has the functions of coal wall video monitoring and the like, and the production process is automatically completed; the coal mining process is intelligent, data transmission is informationized, and on-site operators operate and produce with few persons, so that manual intervention is reduced as much as possible, and high-yield, efficient and safe production is ensured.

The invention discloses a mining-while-digging earthquake advanced detection system based on distributed optical fiber acoustic sensing. Relates to the technical field of seismic exploration. On the basis of a distributed optical fiber acoustic sensing technology, mining-while-digging seismic detection of a working face is realized by utilizing vibration generated by cutting a coal rock stratum by mining machinery. In the production process, the detector collects vibration data of mining machinery and transmits the vibration data to the server through a network; optical cables are arranged on two sides of a coal face upper and lower crossheading or two sides of a driving face roadway; the demodulator emits pulse laser and transmits the pulse laser to the working face optical cable through the industrial looped network or the independent fiber core, vibration of measuring points at equal intervals of the optical cable is measured, and a measuring data packet is returned to the demodulator through the industrial looped network or the independent fiber core; the demodulator demodulates vibration waveform data and uploads the vibration waveform data to the server; server data processing software carries out noise reduction processing on the waveform, then stores and images the waveform, carries out real-time intelligent interpretation, and realizes detection of a geological structure and an abnormal area in front of a working face.

The invention discloses an ultra-long working face mining method which comprises the following steps: S1, moving a first coal mining machine to a first end, forming a second notch in the middle of an ultra-long working face by utilizing a self-notching machine at the same time, and enabling a second coal mining machine to enter the second notch; s2, the first coal mining machine cuts coal from the first end to the second notch, and the second coal mining machine cuts coal from the second notch to the second end; s3, a first notch is formed in the middle of the super-long working face through the self-notching machine, the first coal mining machine enters the first notch after cutting through the coal wall, and the second coal mining machine moves to the second end after cutting through the coal wall; s4, the first coal mining machine cuts coal from the first notch to the first end, and the second coal mining machine cuts coal from the second end to the first notch; and S5, the step S1 to the step S4 are repeated, and mining of the ultra-long working face is achieved. According to the mining method for the ultra-long working face, the coal mining machine can enter the coal wall to normally cut coal in the middle of the ultra-long working face without adopting a beveling feed mode, so that the advancing speed of the ultra-long working face is increased.

The invention discloses a multi-sensor fusion-based driving and anchoring all-in-one machine operation state detection method and system, and relates to the technical field of mining equipment, and the method comprises the steps: monitoring a driving and anchoring all-in-one machine in real time through a multi-sensor terminal, and obtaining hydraulic, mechanical and electrical monitoring sequences with operation node identifiers; constructing a credible state grid space according to the operation control decision; guiding anomaly detection according to the node identifier to obtain a ternary anomaly detection result; after historical fault deduction is combined, a bolter miner coupling fault prediction model is introduced for prediction, and a detection map is obtained. The technical problems that in the operation process of an existing digging and anchoring all-in-one machine, multi-sensing data are isolated, the anomaly detection precision is low, and multi-dimensional fault trend deduction cannot be achieved are solved, multi-source data fusion analysis of the digging and anchoring all-in-one machine is achieved, the anomaly detection accuracy of the digging and anchoring all-in-one machine is improved, and the fault probability of the digging and anchoring all-in-one machine is lowered. And the technical effect of accurate fault prediction of the digging and anchoring all-in-one machine is realized.

The invention discloses an underground large-water mine fine ore recovery technology, and relates to the technical field of fine ore recovery. The method comprises the steps that S1, underground equipment is prepared and arranged; s2, collecting fine ore in the stope; s3, ore screening and material preparation; s4, determining the diameter of the pipeline; s5, calculating the pressure loss of the pipeline; s6, stirring and modifying the ore pulp; and S7, ore screening and wastewater recycling. The process belongs to active recovery of the fine ore, all the fine ore produced in the mine can be recovered, the intermediate transportation and crushing steps of the recovered fine ore are omitted, and the problem that the ore slurry formed after the fine ore meets water blocks a draw shaft and a drainage channel is solved. And the fine ore is directly recovered and passes through the crushing stage, so that the loss of the fine ore in the transportation process is effectively reduced, and the resource recovery rate is greatly improved. Compared with the prior art, fine ore can be actively recycled, and the recycling efficiency is high. Equipment used in the process is more flexible, and there is no need to excavate more laneway projects for treating the fine ore.

The present invention discloses a device and method for breaking coal, relieving pressure and increasing permeability by using a pneumatic flexible tool in a soft coal seam, which comprises: a drilling rig, in which a drill rod is installed, and the shaft of the drill rod is provided with an air flow cavity of a columnar structure, and the outer ring wall of the top end of the drill rod at the outermost end is provided with a partial thread; an air compressor pump, the output end of which is sealed and connected to the air flow cavity through a high-pressure air pipe; pneumatic slitting equipment, which comprises a pneumatic rotating device and a slitting device, the left end of the pneumatic rotating device is installed on the top end of the drill rod at the outermost end, and the right end of the pneumatic rotating device is installed with the slitting device, and the drill rod, the pneumatic rotating device and the slitting device are all coaxially arranged.

The invention discloses a coal mining machine dust source tracking intelligent dust removal method and system integrated with a hydraulic support, and belongs to the technical field of coal mine dust removal. The system comprises a wet dust collector arranged on the inner side of a hydraulic support shield beam, a telescopic air duct on a top beam and a control system. The wet dust collector is connected with the telescopic air duct through a dust suction pipeline arranged in the support, and a dust suction opening of the telescopic air duct is driven by the lifting mechanism to ascend and descend and suck dust dynamically along with a roller of the coal mining machine. The control system obtains position signals of the coal mining machine, adjusts the position of a dust suction opening and controls the dust remover to be started and stopped, and precise dust source treatment is achieved. According to the method, the dust source is tracked circularly by recognizing the coal cutting state of the coal cutter and dynamically adjusting the height of a dust suction inlet and operation of a fan. The support structure is used for protecting equipment from being smashed and damaged, the device adapts to thin and medium-thickness coal seam space, the dust removal efficiency and reliability are remarkably improved, the dust concentration and the maintenance cost are reduced, miner health and operation safety are guaranteed, and wide application prospects are achieved.

A mixed feed efficient mining method includes the steps that firstly, an air way, a machine way and a cutting hole are formed, a coal pillar is reserved at the left end of a working face, the length of the reserved coal pillar is larger than that of a single-drum coal mining machine, a machine nest is formed in the right side of the reserved coal pillar, and the length of the machine nest is not smaller than the sum of the length of a double-drum coal mining machine and the length of beveling feed; the single-drum coal mining machines are arranged in the roadways at the two ends of the fully mechanized coal mining face, the double-drum coal mining machines are arranged on the scraper conveyor at the machine nest section, when the double-drum coal mining machines run to be close to the left end or the right end of the fully mechanized coal mining face, reverse beveling feeding is directly carried out for next coal cutting, and it is not needed that coal is cut back and forth after conventional beveling feeding is carried out; coal pillars left at the two ends of the working face are cut by the two-end single-drum coal mining machine through vertical feeding, coal mining at the two ends and the middle section of the working face is achieved at the same time, the mining efficiency is greatly improved, the number of arranged working faces is reduced, the labor time of workers is shortened, and the economic benefits of enterprises are increased.

The invention discloses movable ore extraction equipment with a dust falling function, and relates to the technical field of plate type ore extraction, the movable ore extraction equipment comprises a heading machine body, a driving mechanism is mounted on one side of the heading machine body, and a cutting head is fixedly connected to one side of the driving mechanism. The pretreatment device is arranged, a first motor reversely runs, a percussion drill body is far away from ore, at the moment, an expansion cracking device body begins to move towards the direction of the ore, after the expansion cracking device body reaches a designated position, a corresponding hydraulic cylinder is started, the expansion cracking device body is pushed to go deep into a drill hole, then the expansion cracking device body is started, cracks in the ore are expanded through hydraulic pressure, and thus the ore is fractured. And after expansion cracking is completed, the first motor is started again, so that the expansion cracking device body is reset to the initial position, the pretreatment mode effectively reduces the strength of ore, the follow-up operation of the cutting head is smoother, the overall working efficiency of mining equipment is improved, meanwhile, the abrasion of the cutting head is reduced, and the service life of the cutting head is prolonged.

The invention discloses an intelligent control method and system for a tunneling path of a tunneling machine, and relates to the technical field of tunneling machine control, and the method comprises the steps: building a tunneling space risk distribution model; performing hierarchical surrounding collision detection on the tunneling space risk distribution model, and constructing a safe tunneling motion space model; performing tunneling path planning on the safe tunneling motion space model, and building a first tunneling path planning domain; performing overrun feedback optimization on the first tunneling path planning domain, and establishing a second tunneling path planning domain; joint optimization is carried out, and a tunneling path optimization result is determined; and performing tunneling path tracking control on the tunneling machine. The technical problems of poor safety and low efficiency of tunneling operation caused by insufficient risk prejudgment of the tunneling area and insufficient consideration of technical parameters and tunneling targets of the tunneling machine in path planning in the prior art are solved, accurate path tracking control of the tunneling machine is realized, and the tunneling efficiency is improved. And the technical effects of safety and high efficiency of tunneling operation are improved.

The invention belongs to the field of coal mine dust removal, and relates to a coal mining machine onboard integrated efficient dust remover and a filtering method thereof, an air inlet, a nozzle, a multi-stage filter screen, a corrugated plate demister, a centrifugal fan and other components are integrated to form an efficient dust removal system. During operation, dust-containing air enters through the air inlet, water mist is sprayed out of the nozzles to preliminarily wet dust, and then the dust with different particle sizes is effectively captured through multi-stage filtration of the coarse-efficiency filter screen, the medium-efficiency filter screen and the high-efficiency filter screen. And then the air is dehydrated by a demister, and clean air is discharged by a centrifugal fan. The equipment is provided with a dust cleaning brush and a differential pressure sensor, the filter screen can be automatically cleaned, and the filtering effect is guaranteed. The system has the advantages of efficient dust fall, water saving, environmental protection, intelligent monitoring, compact structure and convenient maintenance, can obviously reduce the dust concentration of the working face, improves the working environment, ensures the health of miners, and is a preferable scheme for dust control of the fully mechanized coal mining working face.

The invention discloses a fully-mechanized face mining method based on mining and exploring at the same time. The method is implemented according to the following steps that a data monitoring substation is arranged, and stress and micro-seismic data are received from an underground stress monitoring system; current stope stress and roof and floor conditions are obtained through stress and micro-seismic data, and a working face is guided to advance; the method comprises the following steps: establishing a transparent geologic model by using coal seam geologic information and three-dimensional space information of a working face, fusing spatial position information and working state information of fully-mechanized coal mining equipment into the transparent geologic model to obtain a mining data model, and controlling a coal mining machine by combining inertial navigation and a coal mining machine cutting curve correction model; and along with advancing of the working face, new geological information is obtained, the steps 1-3 are repeated, and the mining data model is dynamically updated. By means of the real-time dynamic monitoring and exploring while mining technology, geological exploration, data analysis and inertial navigation are integrated, sub-meter advanced high-precision exploration, geological model dynamic updating and self-adaptive planning mining are achieved, geological prediction accuracy is improved, and real-time geological navigation and stable guarantee are provided.