49results about How to "Solve mining problems" patented technology

The invention discloses a mechanical continuous mining method for a gently inclined thin ore body. Based on the principle of lengthening the slope distance to reduce the angle, ore blocks are arranged in an inclined way, so that an angle smaller than the original inclination angle can be formed between a working plane and the horizontal plane, thus creating an operating space for a drill jumbo and a scraper; a return air shaft is arranged at the corner of one ore room so as to be communicated with an upper horizontal return airway; each ore room is provided with an orepass used for the transmission of ores in the ore room; and a tunnel is respectively excavated along the strike direction above and below each ore room, the upper tunnel is used for ventilation connection, and the lower tunnel is used for ore removal connection. The invention is especially applicable to the mining of the gently inclined thin ore body of an underground mine, mining preparation has no requirements for undercutting projects, and the drill jumbos and scrapers are used for the operation, thereby achieving the characteristics of high degree of mechanization, high production efficiency, full-thickness continuous mining and low ore loss rate.

The invention relates to a flowing current separation process coal mine underground gangue dumping system. The technical scheme includes that a run-of-mine coal conveyor is mounted on one side of a feeding end of a roller screen, two ends of an on-screen selected raw material coal conveyor are connected with a front-screen chute of the roller screen and a feeding port of a flowing current separation machine respectively, a block coal of the flowing current separation machine is connected with a dewatering screen, an oversize material discharging end of the dewatering screen is sequentially connected with a block coal conveyor, a block coal transferring conveyor and a pulverized coal conveyor, a high frequency screen is mounted in the middle of the block coal conveyor, under-screen water of the dewatering screen is connected with a concentration tank through a pipeline, the concentration tank is connected with the high frequency screen, a gangue outlet of the flowing current separation machine is connected with a bucket elevator, a discharging end of the bucket elevator is sequentially connected with a gangue conveyor, a gangue transferring conveyor and a gangue warehousing conveyor, under-screen water of the high frequency screen and overflow of the concentration tank are connected with a circulating water tank through pipelines respectively, and the circulating water tank is connected with a water inlet of the flowing current separation machine through a circulating water pump and a pipeline. The flowing current separation process coal mine underground gangue dumping system is simple in process, good in separation effect, low in power consumption and low in operating cost.

The invention discloses a method for searching for and preventing mine water seepage of an Ordovician limestone mine field. The method comprises the following steps: drilling a first vertical well vertical to the ground in the center of a coal mine area by using a first drill bit, and stopping drilling and cementing the well until the depth of the vertical well is 8-12 m into bed rock; further drilling downwards by using a second drill bit, and stopping drilling and cementing the well until the second drill bit penetrates into a coal bed by 5-10 m; further drilling downwards by using a third drill bit slantly in multiple directions to form an inclined well, and horizontally drilling after the third drill bit enters Ordovician limestone; in the horizontal drilling process of the drill bit, searching an Ordovician limestone gap, and plugging the gap till the edge of the coal mine area. Compared with the conventional vertical-well drilling for grouting plugging, horizontal-well multi-branch plugging construction really reduces manpower investment, equipment investment, construction area and other investments; by the method, the problem of lower group coal mining can be safely and efficiently solved, the water blocking performance of each floor water-resisting layer is improved, and pressure mining is implemented; by the method, a lot of money for water control in coal mining can be saved and coal resources are further released.

The invention provides a massive search query log calculation and analysis system based on a cloud platform. The invention aims at characteristics and requirements of an internet e-commerce platform,designs a structured log of a search engine, and provides the structured log data for a log analysis system to be applied, so the space required by traditional log analysis and the workload of log cleaning work are greatly reduced; an efficient e-commerce platform search query log analysis system is realized in combination with a Hadoop distributed computing platform and a big data processing algorithm, thus mining data back value; key points and excavation potential are fully grasped by feature selection of the e-commerce platform, so massive log key extraction information currently needed bythe e-commerce platform can be clearly and visually displayed, enough expansion capacity can be provided for mining of various interested features of logs, website optimization and precision marketing are achieved by analyzing behavior logs of users, personalized services are provided, and the invention has huge utilization value.

The invention discloses a laneway repair machine which comprises a portal frame (1), a rotating oil cylinder (2), a large arm seat (3), a large arm (4), a large arm oil cylinder (5), a small arm oil cylinder (6), a small arm (8), a breaking hammer oil cylinder (9), a breaking hammer (11), a bucket oil cylinder (12), a link mechanism (13), a quick connector (14) and a bucket or hydraulic shear (15), wherein the small arm oil cylinder (6) is positioned below the large arm (4); the large arm oil cylinder (5) is arranged in a cavity of the large arm (4); the rear end of the breaking hammer (11) is provided with a slide block or idler wheel (7); the upper part of the breaking hammer oil cylinder (9) is provided with a sliding groove (10); the slide block or idler wheel (7) can move in the sliding groove (10); one end of the breaking hammer oil cylinder (9) is movably connected with the breaking hammer (11), and the other end is movably connected with the small arm (8); the quick connector (14) is arranged on the small arm (8); the link mechanism (13) is connected with the quick connector (14); and two grooves positioned on the quick connector (14) are closed and opened through a control mechanism, so that the fast replacement of the bucket (15) and the hydraulic shear (15) can be realized. The laneway repair machine disclosed by the invention has the advantages of realizing that breaking, shearing and assembling functions are integrated into a whole, simplifying the procedure of the mutual replacement of multiple equipment, reducing the construction auxiliary time and increasing the work efficiency of laneway excavation.

The invention discloses a recognition method for key sections of a highway network, which comprises the steps of firstly dividing the highway network into a plurality of sub community networks by using a community dividing algorithm; then modeling the highway network according to a probability assumption method, solving to acquire candidate key sections in each sub community network; and then finding out final key sections from the candidate key sections by adopting a dynamic planning method to act as key sections in the highway network, and enabling combinations investing the key section to realize the highest traffic efficiency of the highway network. According to the recognition method provided by the invention, key sections in the highway network are dug according to the traffic flow and highway network characteristics, the key sections in the highway network can be dug out accurately and efficiently, and a problem of key section digging is solved, thereby being capable of turning into an effective means of digging key sections in the highway network in practical application, being capable of providing a reference basis for overall planning of a transportation department, and providing a support means for the highway management staff to manage the highway network efficiently.

The invention provides a data association relationship mining method and application based on a search engine technology. The method comprises the following steps of establishing a full-text index database, the full-text index database comprising a data table and an object field list which have established a full-text index relation, and the object field list comprising at least one object category field corresponding to an object category; retrieving a database according to the object category fields, and obtaining an object list for each category of objects, the object list including at least one object field corresponding to the object; retrieving a database according to the object field, and obtaining associated data for each object; establishing an association relationship between theobject and the associated data; wherein the association relationship is at least the relationship between the data table main key value corresponding to the position of the associated data and the object main key information. The method aims at quickly and conveniently searching all the data of the whole library and the whole table according to the associated object and automatically establishingthe association relationship according to the retrieved data, so that the technical blank in the prior art is filled up.

The invention discloses a soft advertising data monitoring and mining system and a method thereof. The system comprises a client inquiring and subscribing module which is used for inquiring and subscription of the required hard advertising data and soft advertising data for a client; and a client terminal which is used for performing regular pushing of the data subscribed by the client in multiple modes. The method comprises the following steps of a data acquisition step which is used for performing video data acquisition on playing content of multiple television channels based on a step-by-step collection acquisition scheme; a data storage step which is used for compression and storage of the acquired video data; a data processing step which is used for performing feature matching on the compressed and stored video data based on the extracted features and completing identification processing of the video data and generating the hard advertising data and the soft advertising data respectively; and a data mining data which is used for performing data mining on the hard advertising data and the soft advertising data. The invention also discloses the soft advertising data monitoring and mining system.

The invention discloses a key path extraction method of the propagation network. An extra node is added to the propagation network, and bidirectional connection with each node of the propagation network is further established; the node similarity between any two nodes of the extra node propagation network is calculated; a node influence column vector is initialized based on the total quantity of the nodes of the extra node propagation network, a probability transfer matrix is further established, and global voting iteration is carried out to update the node influence column vector; traversal elimination of shortest paths of any two user nodes of the extra node propagation network is carried out, a path node influence row vector and a path node similarity row vector are established for eachshortest path; the comprehensive path influence of each shortest path is acquired through calculation to order each shortest path to acquire a key path. The method is advantaged in that a problem inmining the key propagation path on a social network platform is solved, and the method can be applied to the network information monitoring fields for public opinion monitoring and intervention and rumor detection.

The invention provides a layered gas collecting pipe column assembly and a gas collecting device having the same. The assembly includes a sleeve pipe, a double-tube packer, a drain pipe column and a gas collecting pipe column used for collecting gas; the sleeve pipe stretches into two gas collecting layers, and the internal of the sleeve pipe communicates with each gas collecting layer; the double-tube packer is arranged in the sleeve pipe and located between the two gas collecting layers to separate the two gas collecting layers; the drain pipe column passes through the double-tube packer andcommunicates with each gas collecting layer, and a plunger pump is arranged in the drain pipe column and can discharge liquid in each gas collecting layer; the gas collecting pipe column passes through the double-tube packer, and the inlet of the gas collecting pipe column communicates with the lower gas collecting layer and is closer to the double-tube packer relative to the lower part of the drain pipe column; and gas of the upper gas layer of the two gas collecting layers can be discharged through annulus between the sleeve pipe and the drain pipe column and the gas collecting pipe column,and the gas of the lower gas layer of the two gas collecting layers can be discharged through the gas collecting pipe column. Thus, gas mining problems, in the prior art, in high and low pressure layered oil and gas wells can be effectively solved.

The invention discloses a Hadoop-based network recommendation method. Specific to a network based on a Hadoop platform, the scale of a cluster is increased according to a practical computation requirement; a dynamic storage space is provided for mass data sets by using an HDFS (Hadoop Distributed File System) to store the ever-increasing mass data sets; big tasks are decomposed into small tasks through a MapReduce framework; the computation speed of an algorithm is increased through a parallel computation way; and network recommendation is realized by using a substance diffusion algorithm and a heat conduction algorithm. Through adoption of the Hadoop-based network recommendation method, the problem that a large electronic commerce website cannot be well reached since a conventional algorithm running in a standalone mode tends to be impeded easily by multiple computer hardware performance such as processor speed and storage capacity is solved; a system is reliably and efficiently recommended to perform calculation, analysis and mining through massive user dialogs; and the problems of high time consumption, poor expandability, polynomial increase of the complexity of the algorithm and worse and worse algorithm performance along with the increase of the numbers of users and goods, and the like in other recommendation algorithms are solved.

The invention discloses a tree excavating machine outer meshing rotating driving device. The tree excavating machine outer meshing rotating driving device comprises an upper bearing ring, a lower bearing ring, a driving motor, a worm and gear reducing mechanism and a transfer case. The lower bearing ring is rotationally installed at the bottom of the upper bearing ring. One side of the upper bearing ring and one side of the lower bearing ring are provided with openings with the same angle. The two ends of the transfer case are each rotationally provided with a transmission shaft. The lower ends of the transmission shafts are provided with gears respectively. The lower bearing ring is provided with an outer gear ring. The gears are meshed with the outer gear ring and located at the two sides of the opening in one side of the lower bearing ring. By means of the tree excavating machine outer meshing rotating driving device, it is guaranteed that an excavated soil ball is very round, a large tree root can be sawed off, stone and other barriers can be conveyed out through a chain, and the tree excavating machine outer meshing rotating driving device will not get stuck easily; it is guaranteed that a tree excavating machine can be provided with an angle adjusting device, the tree excavating machine can conduct excavating on the ground with certain slope, the excavated soil ball can meet the requirement for tree transplanting, and the problems of excavating and transplanting of seedlings on the conditions of hills, mountain slopes and the like are solved.

The present invention, a high-consistency crude oil dimension agent and the way of making it, belongs to oil area, especially when used in crude oil and oil production; it can be effectively decrease the viscidity of crude oil. The high-consistency crude oil dimension agent consists of six components: polyoxyethylenated alcohol vitriol ate of tartar (one share), acetyl tannic ace amide (6-12 shares), polyoxyethylated alkylphenol (2-8 shares ), isooctyl alcohol polyethenoxy ether (3-20 shares ), potassium citrate (6-10 shares), water (25-35 shares ), according to the weight. The viscidity is 250-350 map's to the temperature of 25Deg.c. The high-consistency crude oil dimension agent should be used as a density of 0.8-1.5%. The present invention is good for crude oil dimension, the function is stable, and it is widely adept. The present invention solves the problems in consistency oil production.

The invention relates to a greenhouse rail-mounted pseudo-ginseng harvester, and belongs to the technical field of agricultural harvesting mechanical equipment. The greenhouse rail-mounted pseudo-ginseng harvester comprises a walking system, a rail switching system, an excavating unit and a soil removing unit. The walking system is arranged on the front and rear ends of a frame, the rail switching system is arranged at two sides of the walking system, the frame is provided with a motor and a hydraulic pump, the excavating unit is arranged under the frame, and the soil removing unit is arranged behind the excavating unit. According to the invention, switching between ground walking and rail operating in the greenhouse can be achieved, the automation degree is high, and the harvesting effect is good; the rail switching system is employed in the harvester, the problem that pseudo-ginseng planted in the greenhouse is hard to excavate is solved, and excavation of pseudo-ginseng seeds and other root Chinese medicinal materials can be achieved at the same time; and the greenhouse rail-mounted pseudo-ginseng harvester has a relatively-low mechanical damage rate, and the pseudo-ginseng integrality is fully guaranteed.

The invention relates to a cutting device of a coal cutter, which mainly solves technical problems including both the floor-based quantity and the roof brushing quantity of the coal cutter. Technical schemes adopted in the invention comprise that a motor of the cutting device is in driven connection with a primary planetary gear train with large speed ratio, wherein the planetary gear train is in driven connection with a roller, and the motor is positioned in a cavity of the roller; and that a gap exists between an overhanging end line of the motor and an edge line of a ledge, and a gap exists between the overhanging end line of the motor and an edge line of a support front beam. Thus, the cutting device can better satisfy requirements for the floor-based quantity and the roof brushing quantity when the diameter of the roller is small, and is suitable for exploitation works in thin coal seams or relatively thin coal seams.

The invention provides a stock rise and fall prediction method based on multi-task self-supervised learning, which can automatically learn valuable features from original financial signals and predict the rise and fall of stocks by taking the features as signals. Specifically, the invention realizes a stock technical data sequence encoder based on Transform and an attention mechanism, designs a plurality of self-supervision auxiliary tasks to train the encoder, and encodes stock sequence data by using the trained encoder. Finally, based on the long-short-term memory neural network and the feedforward neural network, sequence representation is learned, and the rise and fall of the stock is predicted. A large number of experiments carried out on a real stock data set show that the features learned by the method are effective signals for predicting the rise and fall of the stock, and the method has leading accuracy in the aspect of predicting the rise and fall of the stock.

The invention belongs to the technical field of process mining, particularly discloses a method for mining a hybrid multi-concurrent structure based on a Petri network to improve business process efficiency, and aims to solve the technical problem of low business process efficiency due to the fact that an existing mining method cannot accurately mine a process model of the hybrid multi-concurrentstructure from incomplete event logs. The process mining method based on the Petri network, namely the AlphaMining method, comprises the following steps that firstly, all activities in an incomplete event log are obtained in an event system, and the activity conforming to the simplest second-degree short cycle structure is found out; respectively redefining the activities in the simplest two-degree cycle structure; secondly, according to the number characteristics and the position characteristics of the activities in the traces, correctly matching and identifying the same type of second-degreeshort-cycle structure by using a number marking matrix and a position marking matrix, and completing mining of a process model containing the hybrid multi-concurrent structure; and then, the mined process model is used for replaying the actual business process, so that the efficiency of the actual business process is improved.

The invention discloses an SSD face detection method based on deep learning, and the method comprises the steps: carrying out the candidate box extraction, target detection and bounding box regressionof to-be-detected face data based on a deep convolutional neural network; discretizing an output space of the target Bounding Box regression task into a priori box by utilizing an SSD strategy, and respectively setting priori boxes with various aspect ratios and sizes corresponding to each position in each detection layer; wherein the deep convolutional neural network generates a confidence coefficient of the to-be-measured face according to the priori frame, and corrects the position of the priori frame; and in combination with an SSD strategy, carrying out detection of a plurality of feature maps with different resolutions on the corrected position to obtain a final detection result. According to the SSD strategy provided by the invention, the difference between detection layer data isincreased, the generalization ability and robustness of the model are improved through data enhancement, the problem of difficult negative sample mining is solved, the purpose of balancing training set category distribution is achieved, and the precision and efficiency of small face detection are improved.

The invention relates to an oil well exploiting device, in particular to a water-adding viscosity-reducing device. The technical scheme is that the water-adding viscosity-reducing device is mainly composed of a well filed, an oil outlet pipe, a metering station and a water-adding pipe. The well filed is respectively connected with the oil outlet pipe and the water-adding pipe, the oil outlet pipe is connected with the metering station, the metering station comprises a metering separator and a heating furnace, the heating furnace is fixed on the oil outlet pipe, and the oil outlet pipe is connected with the metering separator through the heating furnace. The water-adding viscosity-reducing device has the advantages that the exploiting of high-viscosity crude oil is achieved, the water-adding viscosity-reducing device is put into production easily and is convenient to manage, production is stopped easily and is safe, the well filed and a main line are not provided with the heating furnace, fuel is saved, and back pressure is reduced effectively.