CN114844925B - Unmanned mine universe intelligent monitoring system - Google Patents
Unmanned mine universe intelligent monitoring system Download PDFInfo
- Publication number
- CN114844925B CN114844925B CN202210472816.9A CN202210472816A CN114844925B CN 114844925 B CN114844925 B CN 114844925B CN 202210472816 A CN202210472816 A CN 202210472816A CN 114844925 B CN114844925 B CN 114844925B
- Authority
- CN
- China
- Prior art keywords
- edge
- data
- subsystem
- environment
- monitoring
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 130
- 238000004891 communication Methods 0.000 claims abstract description 48
- 238000004458 analytical method Methods 0.000 claims abstract description 44
- 238000004519 manufacturing process Methods 0.000 claims abstract description 39
- 230000007613 environmental effect Effects 0.000 claims description 32
- 230000002159 abnormal effect Effects 0.000 claims description 16
- 238000005065 mining Methods 0.000 claims description 16
- 238000012423 maintenance Methods 0.000 claims description 14
- 230000008447 perception Effects 0.000 claims description 9
- 238000012549 training Methods 0.000 claims description 4
- 238000005457 optimization Methods 0.000 claims description 3
- 230000004888 barrier function Effects 0.000 claims 1
- 230000036962 time dependent Effects 0.000 claims 1
- 238000007726 management method Methods 0.000 abstract description 21
- 238000000034 method Methods 0.000 abstract description 16
- 230000008569 process Effects 0.000 abstract description 14
- 230000000694 effects Effects 0.000 abstract description 7
- 238000005516 engineering process Methods 0.000 abstract description 6
- 230000005856 abnormality Effects 0.000 description 23
- 230000032683 aging Effects 0.000 description 13
- 230000008439 repair process Effects 0.000 description 13
- 238000010586 diagram Methods 0.000 description 6
- 230000005540 biological transmission Effects 0.000 description 5
- 230000033001 locomotion Effects 0.000 description 5
- 238000001514 detection method Methods 0.000 description 4
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 4
- 239000000428 dust Substances 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 238000009825 accumulation Methods 0.000 description 2
- 238000009412 basement excavation Methods 0.000 description 2
- 238000003709 image segmentation Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000003062 neural network model Methods 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 241001300198 Caperonia palustris Species 0.000 description 1
- 241001465754 Metazoa Species 0.000 description 1
- 235000000384 Veronica chamaedrys Nutrition 0.000 description 1
- 238000012098 association analyses Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 125000004122 cyclic group Chemical group 0.000 description 1
- 230000000994 depressogenic effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000015654 memory Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000004576 sand Substances 0.000 description 1
- 230000006403 short-term memory Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000005507 spraying Methods 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
- 238000009966 trimming Methods 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/30—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
- G01W1/00—Meteorology
- G01W1/02—Instruments for indicating weather conditions by measuring two or more variables, e.g. humidity, pressure, temperature, cloud cover or wind speed
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
- H04L67/125—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/44—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Physics & Mathematics (AREA)
- Medical Informatics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Environmental & Geological Engineering (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Computational Linguistics (AREA)
- Software Systems (AREA)
- Evolutionary Computation (AREA)
- Molecular Biology (AREA)
- General Engineering & Computer Science (AREA)
- Biophysics (AREA)
- Mathematical Physics (AREA)
- Data Mining & Analysis (AREA)
- Biomedical Technology (AREA)
- Artificial Intelligence (AREA)
- Atmospheric Sciences (AREA)
- Biodiversity & Conservation Biology (AREA)
- Ecology (AREA)
- Environmental Sciences (AREA)
- Traffic Control Systems (AREA)
Abstract
The application provides an unmanned mine universe intelligent monitoring system belongs to the computer technology field. The system comprises: the center cloud end, the edge end and the operation equipment end; the central cloud end is in communication connection with the edge end and the operation equipment end, and the edge end is in communication connection with the operation equipment end; the central cloud end is used for sending environment data to the operation equipment end and sending operation instructions to the edge end and the operation equipment end respectively according to preset production rules and the environment data; the edge end is used for acquiring the operation data of the operation equipment end after the operation is executed according to the operation instruction and acquiring the environment data of the operation environment of the operation equipment end; the central cloud is also used for calling a corresponding analysis model according to the operation data to obtain a mine monitoring result. The method and the device can improve accuracy and comprehensiveness of monitoring the operation process, and further can achieve the effect of improving management reliability and efficiency of each operation device.
Description
Technical Field
The application relates to the technical field of computers, in particular to an unmanned mine universe intelligent monitoring system.
Background
With the development of scientific technology, the industrial and mining industry has entered the time of the internet of things, and related technicians can monitor and schedule the operation environment and each operation device through the internet of things.
In the related art, during the operation of the industrial and mining industry, a related technician may monitor operation information of each operation device, such as whether there is an obstacle on an operation path of each operation device or a moving speed of each operation device, by installing a sensor or a camera on each operation device. In addition, the related technician can also monitor environmental information of the working environment in real time, such as temperature or humidity of the working environment, by installing a sensor in the working environment, and then transmit the monitored environmental information to each working device. Each job device may adjust a job task currently being executed based on the job information and the environment information.
In the actual working process, the possible abnormal situation in the working environment and the possible emergency situation encountered by each working device are very complex, however, the detection mode in the related technical scheme is single, and the working task of each working device can only be adjusted. Therefore, the related technical scheme has the problems of imperfect and inaccurate monitoring of the working process in the industrial and mining industry, and further causes the problems of poor management reliability and low efficiency of each working device.
Disclosure of Invention
The utility model aims at providing an unmanned mine universe intelligent monitoring system can improve accuracy and the comprehensiveness to operation process monitoring, and then can reach the effect that improves the management reliability and the efficiency to each operation equipment.
Embodiments of the present application are implemented as follows:
in a first aspect of the embodiments of the present application, there is provided an unmanned mine global intelligent monitoring system, the system including: the center cloud end, the edge end and the operation equipment end; the central cloud end is in communication connection with the edge end and the operation equipment end, and the edge end is in communication connection with the operation equipment end;
the central cloud end is used for sending environment data to the operation equipment end and sending operation instructions to the edge end and the operation equipment end respectively according to preset production rules and the environment data;
the edge end is used for acquiring the operation data of the operation equipment end after the operation is executed according to the operation instruction and acquiring the environment data of the operation environment of the operation equipment end;
the central cloud end is used for calling a corresponding analysis model according to the operation data to obtain mine monitoring results, wherein the analysis model carries out training optimization according to the preset production rules, the environment data and the operation data.
Optionally, the edge end includes one or more of: the intelligent road side intelligent monitoring system comprises a target perception and understanding edge subsystem, a functional area intelligent monitoring edge subsystem, a production environment monitoring edge subsystem and an intelligent road side cooperative edge subsystem;
the target perception and understanding edge subsystem is used for perceiving and predicting obstacle information;
the intelligent monitoring edge subsystem of the functional area is used for monitoring field data of a designated area, wherein the field data comprises the operation state of the designated area;
the production environment monitoring edge subsystem is used for monitoring operation environment data, and the operation environment data comprises: ground data, retaining wall data, slope data and weather data;
the intelligent road side cooperative edge subsystem is used for supporting control and scheduling management according to the operation instruction, and is used for controlling and scheduling management of other subsystems of the edge end except the intelligent road side cooperative edge subsystem and/or the operation equipment end according to the obstacle information, the field data and the operation environment data.
Optionally, the working equipment end includes: a mining car end and an auxiliary operation end;
The production environment monitoring edge subsystem comprises a camera and/or a laser radar, and is particularly used for scanning the pavement of the operation area through the camera and/or the laser radar to obtain pavement leveling information of the operation area; when the road surface leveling information indicates that the road surface does not meet the leveling condition, an operation and maintenance instruction is sent to the auxiliary operation end;
the production environment monitoring edge subsystem comprises a sensor for detecting weather data of the working environment, and is particularly used for monitoring the temperature, humidity, wind direction, wind speed and weather of the working environment through the sensor for detecting the weather data of the working environment.
Optionally, the functional area intelligent monitoring edge subsystem includes an image acquisition device and/or a laser radar, and is specifically configured to acquire a field image of the specified area and/or point cloud data of the specified area as the field data, analyze the field image and/or the point cloud data of the specified area through a preset algorithm, and determine whether the specified area has illegal operation; and carrying out real-time occupation analysis, scene identification and operation progress analysis on the appointed area according to the on-site image and/or the point cloud data of the appointed area, and obtaining an analysis result.
Optionally, multimode communication is adopted between the central cloud end and the edge end, so as to switch the communication mode according to the size of the data to be transmitted.
Optionally, multimode communication is adopted between the central cloud end and the edge end, so that a communication mode is switched according to the aging requirement of data to be transmitted.
Optionally, the edge further includes: a system operation monitoring subsystem;
the system operation monitoring subsystem is used for monitoring the operation state of each subsystem in the edge end; and determining whether each subsystem in the edge terminal is abnormal according to the running state, and transmitting abnormal information to the central cloud.
Optionally, the edge further includes: a prompting subsystem;
the prompting subsystem is used for outputting prompting information under the condition that the system operation monitoring subsystem determines that each subsystem in the edge end is abnormal.
Optionally, the central cloud is further configured to store the environmental data and the operation data, monitor operations of the edge end and the operation equipment end, configure and manage the central cloud, the edge end and the operation equipment end, and remotely update the edge end and the operation equipment end.
The beneficial effects of the embodiment of the application include:
the embodiment of the application provides an unmanned mine universe intelligent monitoring system, be provided with central cloud, marginal end, operation equipment end in unmanned mine universe intelligent monitoring system. The operation data of each operation device in the operation device end and the environment data of the operation environment of the operation device end are monitored through the edge end, and the environment data can comprise the temperature, humidity, wind direction, wind speed, weather, a road on which each operation device runs or moves in the operation environment of the operation device end, an obstacle on the road, an area where each operation device is parked or installed in the operation environment of the operation device end, and the operation data can comprise the real-time speed, the real-time running route, the real-time loading capacity and the real-time temperature of each operation device in the operation device end. Therefore, the operation process and the operation environment of the industrial and mining industry can be accurately and comprehensively monitored in real time.
In addition, the central cloud terminal calls a corresponding analysis model according to the operation data to obtain a mine monitoring result, sends operation instructions to the edge end and the operation equipment end respectively according to preset production rules and environment data, calls the corresponding analysis model according to the operation data to obtain the mine monitoring result, generates the operation instructions according to the mine monitoring result, and sends the operation instructions to the operation equipment end in real time. Therefore, the operation equipment end can be scheduled or controlled in time according to the data monitored or acquired by the edge end. In addition, the automatic control of the operation equipment end by the central cloud according to the data acquired by the edge end can be realized, and the management efficiency of each operation equipment is greatly improved.
Therefore, the accuracy and the comprehensiveness of monitoring the operation process can be improved, and the effects of improving the management reliability and the management efficiency of each operation device can be further achieved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered limiting the scope, and that other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic structural diagram of a first unmanned mine global intelligent monitoring system according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a second unmanned mine global intelligent monitoring system according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a third unmanned mine global intelligent monitoring system according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a fourth unmanned mine global intelligent monitoring system according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a fifth unmanned mine global intelligent monitoring system according to an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, which are generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, as provided in the accompanying drawings, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.
In the related art, during the operation of the industrial and mining industry, a related technician may monitor operation information of each operation device, such as whether there is an obstacle on the operation path of each operation device or the moving speed of each operation device, by installing a sensor or a camera on each operation device. In addition, the related technician can also monitor environmental information of the working environment in real time, such as temperature or humidity of the working environment, by installing a sensor in the working environment, and then transmit the monitored environmental information to each working device. Each job device may adjust a job task currently being executed based on the job information and the environment information. In the actual working process, the possible abnormal situation in the working environment and the possible emergency situation encountered by each working device are very complex, however, the detection mode in the related technical scheme is single, and the working task of each working device can only be adjusted. Therefore, the related technical scheme has the problems of imperfect and inaccurate monitoring of the working process in the working condition industry, and further causes the problems of poor management reliability and low efficiency of each working device.
Therefore, the embodiment of the application provides an unmanned mine universe intelligent monitoring system so as to improve the accuracy and comprehensiveness of monitoring the operation process, and further achieve the effect of improving the management reliability and efficiency of each operation device.
The embodiment of the application is illustrated by taking an unmanned mine universe intelligent monitoring system applied to the industrial and mining industry as an example. But it is not shown that the embodiments of the present application can only be applied to monitoring management in the industrial and mining industry.
The unmanned mine universe intelligent monitoring system provided by the embodiment of the application is explained in detail below.
Fig. 1 is a schematic structural diagram of an unmanned mine global intelligent monitoring system provided in the present application, referring to fig. 1, an embodiment of the present application provides an unmanned mine global intelligent monitoring system, and the system includes: the cloud center 101, the edge end 102 and the operation equipment end 103.
The central cloud 101 is in communication connection with an edge end 102 and an operation equipment end 103, and the edge end 102 is in communication connection with the operation equipment end 103.
Optionally, the central cloud 101 is configured to send environmental data to the operation device 103, and send operation instructions to the edge 102 and the operation device 103 according to preset production rules and the environmental data, respectively.
The preset production rule may be preconfigured with a task, a task environment, a task mode, etc. that need to be executed, which is not limited herein, and the environmental data may be matched with the preset production rule, but not limited thereto, and the environmental data may affect the specific operation instruction, etc. sent by the central cloud 101.
The edge terminal 102 is used for acquiring job data after the job device terminal 103 executes the job according to the job instruction.
And the central cloud 101 is further configured to call a corresponding analysis model according to the operation data, and obtain a mine monitoring result.
The central cloud 101 may be a computer device with processing, control, and storage functions. The computer device may be any terminal device or server, which is not limited in this embodiment of the present application.
Alternatively, the edge 102 may be a system of at least one subsystem. The edge 102 may specifically include various electronic devices such as a collection device, a communication device, a positioning device, a computing device, a time service device, and a power supply device.
Illustratively, the edge 102 may include one or more acquisition devices such as a temperature sensor, a humidity sensor, an infrared sensor, a speed sensor, a laser radar sensor, an image acquisition device, etc., a communication module supporting 5G communication, a communication module supporting V2X (Vehicle to Everything) technology, a communication module supporting a message queue telemetry transmission (Message Queuing Telemetry Transport, abbreviated as MQTT) protocol, a positioning device supporting a global positioning system (Global Positioning System, abbreviated as GPS), or a positioning device supporting a beidou satellite navigation system (BeiDou Navigation Satellite System, abbreviated as BDS).
The edge 102 may further include a computing device such as a micro control unit (Microcontroller Unit, abbreviated as MCU) and any time service device that can provide an accurate time service function for the unmanned mine global intelligent monitoring system.
In addition, the power may be supplied to the edge 102 by a dc battery or a power generating device, or may be directly supplied to the edge 102 by a mains supply, which is not limited in the embodiment of the present application.
Alternatively, the work equipment end 103 may include a variety of work equipment suitable for use in the industrial and mining industries, such as mine cars responsible for transportation tasks and machinery responsible for auxiliary tasks such as excavation, as the embodiments of the present application are not limited in this regard.
In general, each working device may be an unmanned device or a device requiring an operation by a technician.
In addition, the edge 102 may also be used to obtain environmental data of the work environment of the work equipment 103.
In addition, when the edge 102 obtains the operation device and/or the environmental data, the edge 102 may send the operation data and/or the environmental data to the central cloud 101.
The environmental data may include temperature, humidity, wind direction, wind speed, weather, roads on which each of the working devices travels or moves in the working environment of the working device end 103, obstacles present on the roads, whether the roads are frozen or water is present, areas in the working environment of the working device end 103 where each of the working devices is parked or installed, and the like. Of course, the environmental data may also include any other possible data, which is not limited in this embodiment of the present application.
The preset production rule may be a production rule set in advance by a related technician to be suitable for the industrial and mining industry. The preset production rules may include job tasks corresponding to each of the job devices in the job device side 103. The job task may be used to indicate a job object, a job type, a job start time, a job end time, a job start point, a job end point, and/or a job route for each job device, which is not limited in this embodiment.
If the job device is an immovable mechanical device responsible for an auxiliary task, the job task may include only a job object, a job type, a job start time, and a job end time, which is not limited in the embodiment of the present application.
Optionally, the job instruction is used to instruct or control each job device in the job device side 103 to perform a corresponding job task. The job instruction may instruct or control only one job device in the job device side 103, or may instruct or control a plurality of job devices in the job device side 103 at the same time.
Alternatively, the job data may include real-time speed, real-time travel route, real-time load, real-time temperature, or any other possible data for each of the work devices in work device end 103.
Optionally, the analysis model may be a cyclic neural network model based on Long short-term memory (LSTM), and specifically may be obtained by training with preset sample data according to analysis requirements. For example, the operation flow of the unmanned mine car has a certain time sequence relationship, and then the analysis model may also be a neural network model for performing time sequence association analysis, which is not limited in the embodiment of the application.
The analysis model can be a single model or a combined model with a plurality of sub-models, and each sub-model can respectively realize different functions.
In addition, the mine monitoring result may be a result generated from the job data acquired by the edge 102 to indicate the environmental data and the job data. For example, the mine monitoring result may be used to indicate the current temperature, humidity, wind direction, wind speed, weather, whether a road on which each working device is running or moving in the working environment of the working device end 103 is flat, whether an obstacle is present on the road, whether a space is left in an area on the working environment of the working device end 103 where each working device is parked or installed, real-time speed of each working device, real-time running route, real-time load, real-time temperature, and the like.
The analysis model can be trained and optimized according to the preset production rules, the environment data and the operation data.
Illustratively, the central cloud 101 may perform sensing, scheduling, decision making, planning, control, prediction, simulation, etc. according to the preset production rule, the environmental data, and the job data, so as to implement training optimization on the analysis model. In this way, the analysis model can be optimized in time according to the environmental data and the operation data acquired by the edge 102, so that the effect of improving the accuracy of acquiring the mine monitoring result can be achieved.
The central cloud 101 may also generate the operation instruction according to the mine monitoring result, and send the operation instruction to the operation equipment 103 in real time. Thus, the working equipment end 103 can be scheduled or controlled according to the data monitored or acquired by the edge end 102 in time.
Job device side 103 may also schedule or control itself based on the environmental data and/or the job data.
For example, if the environmental data indicates that an obstacle exists on a road for each working device to travel or move in the working environment of the working device end 103, in the case that the central cloud 101 sends the environmental data to the working device end 103, each working device in the working device end 103 may adjust the travel route of each working device to bypass the road with the obstacle.
For another example, when the central cloud 101 receives information such as 3D pose, semantic tag, predicted track, and the like of related technicians and mining vehicles, excavators, water spraying vehicles, and other operation devices in each area in the operation environment acquired by the edge 102, the central cloud 101 may evaluate collision risks among the operation devices by invoking a dynamic target collision early warning sub-model in the analysis model, if the collision risks among the related operation devices are determined after the evaluation, information such as collision warning identifications, suggested speeds, and the like is issued to the related operation devices in real time, and the central cloud 101 may analyze congestion conditions of loading areas, unloading areas, crushing stations, and the like in the operation environment by invoking a congestion detection sub-model in the analysis model. Thus, the central cloud 101 can timely adjust the operation tasks of each operation device according to the congestion condition of each area, and issue updated operation path information to each operation device, so as to improve the management efficiency of each operation device.
In addition, the central cloud 101 may combine the high-precision map by calling a corresponding analysis model, collect semantic category information, 3D pose, speed, predicted track and other information of each operation device on the road in the operation environment uploaded by the edge 102, form a dynamic traffic layer through the analysis model, and then combine the position of each operation device to issue the position information and collision risk of the target near the operation environment in real time, so that the unmanned mine car can realize beyond-view sensing, and adjust the driving path or speed in advance to avoid.
In the embodiment of the application, a central cloud 101, an edge end 102 and an operation equipment end 103 are arranged in an unmanned mine universe intelligent monitoring system. The operation data of each operation device in the operation device side 103 and the environmental data of the operation environment of the operation device side 103 are monitored by the edge side 102, and the environmental data may include the temperature, humidity, wind direction, wind speed, weather, a road on which each operation device runs or moves in the operation environment of the operation device side 103, an obstacle existing on the road, an area in the operation environment of the operation device side 103 where each operation device is parked or installed, and the operation data may include the real-time speed, the real-time running route, the real-time load, and the real-time temperature of each operation device in the operation device side 103. Therefore, the operation process and the operation environment of the industrial and mining industry can be accurately and comprehensively monitored in real time.
In addition, the central cloud 101 invokes a corresponding analysis model according to the operation data to obtain a mine monitoring result, sends operation instructions to the edge 102 and the operation equipment 103 according to preset production rules and environment data, invokes a corresponding analysis model according to the operation data to obtain a mine monitoring result, generates an operation instruction according to the mine monitoring result, and sends the operation instruction to the operation equipment 103 in real time. Thus, the work equipment end 103 can be scheduled or controlled according to the data monitored or acquired by the edge end 102 in time. In addition, the central cloud 101 can automatically control the operation equipment end 103 according to the data acquired by the edge end 102, so that the management efficiency of each operation equipment is greatly improved.
Therefore, the accuracy and the comprehensiveness of monitoring the operation process can be improved, and the effects of improving the management reliability and the management efficiency of each operation device can be further achieved.
In a possible implementation manner, referring to fig. 2, on the basis of fig. 1, the edge 102 includes one or more of the following: target perception and understanding edge subsystem 1021, functional area intelligent monitoring edge subsystem 1022, production environment monitoring edge subsystem 1023, intelligent roadside collaborative edge subsystem 1024.
Wherein the target perception and understanding edge subsystem 1021 may be used to perceive and predict obstacle information.
The functional area intelligent monitoring edge subsystem 1022 may be used to monitor field data for a designated area.
Production environment monitoring edge subsystem 1023 may be used to monitor operating environment data.
Intelligent roadside cooperative edge subsystem 1024 may be used to support control and scheduling management in accordance with the job instructions.
The environmental data may include the obstacle information, the site data, and the work environment data.
Optionally, the field data includes a job status of the specified area. The job status of the designated area may be used to indicate whether the designated area is occupied, the progress of the job task being performed by the designated area, and whether the designated area is any area set in advance by a relevant technician. The job status of the specified area may also be used to indicate information such as a name, a number, etc. of the specified area, which is not limited in the embodiment of the present application.
Optionally, the job environment data may include: ground data, retaining wall data, slope data and weather data. The ground data may be used to indicate whether the ground is depressed, whether the ground is collapsed, whether the road is icy or there is water accumulation. The wall data may be used to indicate whether the wall is slumped. The slope data may be used to indicate whether the slope is landslide. The weather data includes temperature, humidity, wind direction, wind speed, weather, etc. of the work environment.
Optionally, the target awareness and understanding edge subsystem 1021 may be capable of obstacle awareness for areas in the work environment, such as transportation roads, intersections, loading and unloading areas, mountain blind areas, charging areas, fueling areas, parking areas, etc. in an open stope. For example, the target awareness and understanding edge subsystem 1021 may be aware of whether there are obstacles in each zone that affect travel, movement, or operation of each work device in the work device end 103.
The target perception and understanding edge subsystem 1021 may also perceive geometric parameters such as the size, shape, etc. of the obstacle. Specifically, the obstacle may be perceived through an image segmentation algorithm and a semantic recognition algorithm, which is not limited in the embodiments of the present application.
In addition, the target perception and understanding edge subsystem 1021 may also perform motion prediction for any target in any region of the surface mine. The targets may include work equipment in work equipment end 103 and may include other pedestrians, animals, or other objects in the work environment.
Specifically, the motion prediction may be performed by an optical flow algorithm, which is not limited in the embodiments of the present application.
Alternatively, the designated area may be at least one area of the above-described work environment set in advance by a relevant technician, such as a loading and unloading area in an open pit mine.
The field data may include an image of the specified area and information obtained from analysis of the image of the specified area, which is not limited in this embodiment of the present application.
The functional area intelligent monitoring edge subsystem 1022 can be used for real-time occupancy analysis, scene recognition, job progress analysis of the designated area.
Illustratively, the functional area intelligent monitoring edge subsystem 1022 may analyze whether a loading and unloading area in the open-air mine is occupied, may also analyze the progress of an ongoing work task of the loading and unloading area in the open-air mine, and the functional area intelligent monitoring edge subsystem 1022 may also identify whether the designated area is a loading and unloading area in the open-air mine or is any area previously set by a relevant technician.
The progress of the ongoing work task may be determined by analyzing the number of objects to be loaded or the number of objects to be unloaded in a loading and unloading zone in an open pit, which is not limited in this embodiment of the present application.
Optionally, the production environment monitoring edge subsystem 1023 may be specifically configured to be responsible for real-time monitoring of important areas such as ground, retaining walls, slopes, etc. in the working environment. For example, it is possible to monitor whether the ground is dented, whether the ground is collapsed, whether the retaining wall is collapsed, and whether the slope is landslide.
Production environment monitoring edge subsystem 1023 may specifically monitor such environmental data of the work environment, such as temperature, humidity, wind direction, wind speed, weather, etc.
The production environment monitoring edge subsystem 1023 can be deployed with equipment such as cameras, laser radars, millimeter wave radars, meteorological sensors and the like to perform key monitoring on the pavement, retaining wall, side slope, weather and the like of the surface mine so as to provide early warning services for information such as ground collapse, pit detection, side slope landslide, bad weather and the like.
In addition, the production environment monitoring edge subsystem 1023 may directly send the monitored environment data or operation environment data to each operation device currently located in the corresponding area, or may send the monitored environment data or operation environment data to the central cloud 101, and the central cloud 101 regenerates a corresponding operation instruction to send the operation instruction to each operation device currently located in the corresponding area.
Optionally, the intelligent roadside cooperative edge subsystem 1024 may also be used to control and schedule other subsystems of the edge terminal 102 other than the intelligent roadside cooperative edge subsystem 1024 and/or the work equipment terminal 103 based on the obstacle information, the field data, and the work environment data.
Illustratively, the intelligent roadside cooperative edge subsystem 1024 may complete the environmental awareness assistance, decision-making planning and guidance control for each operation device in the operation device end 103 according to the real-time environmental awareness data of the edge end 102 in combination with the operation instructions issued by the central cloud 101 to each operation device in the operation device end 103. The intelligent roadside cooperative edge subsystem 1024 may also schedule and manage traffic in the area without signal lights according to the operation route, the operation end point, the running speed and the traffic flow state of the area without signal lights of each operation device, which is not limited in the embodiment of the present application.
It should be noted that, by performing obstacle sensing, motion prediction, occupation analysis, scene recognition, operation progress analysis, and monitoring of the operation environment data and the environment data on each region in the operation environment by the target sensing and understanding edge subsystem 1021, the functional area intelligent monitoring edge subsystem 1022, the production environment monitoring edge subsystem 1023, and the intelligent road side cooperative edge subsystem 1024 in the edge terminal 102, the operation process and the operation environment in the industrial and mining industry can be monitored accurately and comprehensively in real time, and each subsystem in the edge terminal 102 can send the monitored data or information to the central cloud 101, and the central cloud 101 can schedule or control the operation equipment terminal 103 according to the data monitored or acquired by the edge terminal 102 in time.
In a possible implementation manner, referring to fig. 3, on the basis of fig. 2, the working device side 103 includes: mine car end 1031, auxiliary working end 1032.
Optionally, the mine car end 1031 includes a mine car for load transportation tasks therein. Included in the auxiliary work end 1032 are mechanical devices responsible for auxiliary tasks, such as loaders responsible for auxiliary excavation tasks, scoopers responsible for road finishing tasks, and the like.
The production environment monitoring edge subsystem 1023 includes a camera and/or a lidar, and is specifically configured to scan a road surface of a work area with the camera and/or the lidar to obtain road surface leveling information of the work area. And when the road surface leveling information indicates that the road surface does not meet the leveling condition, an operation and maintenance instruction is sent to the auxiliary operation end.
The lidar may be referred to as the lidar sensor described above.
The camera may be a depth camera.
The working area can be any area in the working environment, such as a transportation road, an intersection, a loading and unloading area, a mountain shielding blind area, a charging area, a refueling area, a parking area and the like in an open stope.
Alternatively, the operation instruction may be one of the above-described job instructions. The operation and maintenance instructions may be used to control a scraper in the auxiliary work end 1032 that is responsible for finishing road surface tasks, repair equipment that is responsible for maintaining other equipment, in particular.
The road surface leveling information may be used to indicate whether the road surface of each working area is level or whether the road surface of each working area satisfies a leveling condition.
The leveling condition may be set in advance by the relevant technician. For example, the leveling condition may refer to that a difference between an average height of each point on any road surface on any plane and a height of any point on the road surface on the plane is less than a preset threshold, which is not limited in the embodiment of the present application.
In addition, in the case of scanning the road surface of the work area by the lidar, 3D scanning may be performed on any road surface with the lidar to obtain a dense point cloud image of such a road surface. The point cloud data in the dense point cloud image is then projected as a two-dimensional feature image in the Bird Eye View (BEV) direction, and the value in each grid of the two-dimensional feature image is taken as the height average value of all the point cloud points projected to the grid. Then, the height values in the grid are used as random variables, gaussian distribution of the height values is calculated, and probability values except the statistical mean value + -3 x sigma are used as measurement indexes of flatness. In this case, the flattening condition may be that a probability value other than the statistical mean ± 3 x sigma is less than or equal to a preset probability threshold. The preset probability threshold may be set in advance by a related technician, which is not limited in the embodiment of the present application.
In addition, the road surface of the working area may be scanned by the camera, which is not limited in the embodiment of the present application.
If it is determined that the road surface of each working area does not meet the leveling condition, the production environment monitoring edge subsystem 1023 may send the road surface position information or the area position information with abnormal ground flatness to the central cloud 101, and the central cloud 101 sends a corresponding operation and maintenance instruction to the scraper responsible for trimming the road surface task in the auxiliary working end 1032, so as to control the scraper to travel to the road surface with abnormal ground flatness for road surface operation and maintenance.
And scanning the road surface of the working area through the camera and/or the laser radar, acquiring road surface leveling information of the working area, and sending an operation and maintenance instruction to the working equipment in the auxiliary working end 1032 when the road surface leveling information indicates that the road surface does not meet the leveling condition so as to control the corresponding working equipment to perform road surface maintenance. Thus, the uneven road surface can be timely found, and the maintenance of the uneven road surface can be timely carried out. Thus, the reliability and efficiency of management of each working device can be improved.
The millimeter wave radar in the production environment monitoring edge subsystem 1023 can also monitor the position and movement of objects in each area to ensure the operation safety.
Optionally, the production environment monitoring edge subsystem 1023 may further include a sensor for detecting weather data of the working environment, and the production environment monitoring edge subsystem 1023 may be further configured to monitor the temperature, humidity, wind direction, wind speed, weather, etc. of the working environment by using the sensor for detecting weather data of the working environment.
Optionally, the sensor for detecting weather data of the working environment may include a temperature sensor, a humidity sensor, a wind speed and direction sensor, a weather sensor, a dust sensor, and other sensors that may detect weather data, which is not limited in the embodiment of the present application.
In addition, the meteorological sensor can also detect the ground or road in the working environment to determine whether the ground or road in the working environment is frozen or water accumulation exists.
For example, weather sensors may be installed in any area of the surface mine to detect temperature, humidity, wind direction, wind speed, weather in each area. The weather sensor can monitor weather of the surface mine as sunny days, overcast days, rainy days, snowy days, sand storm or fog days and the like.
In addition, dust sensors may be installed in any area of the surface mine to detect the content or concentration of dust in each area.
In a possible implementation manner, the functional area intelligent monitoring edge subsystem 1022 includes an image acquisition device and/or a laser radar, and is specifically configured to acquire a field image of the specified area and/or point cloud data of the specified area as the field data, analyze the field image and/or the point cloud data of the specified area through a preset algorithm, determine whether the specified area has illegal operation, and perform real-time occupation analysis, scene recognition, operation progress analysis on the specified area according to the field image and/or the point cloud data of the specified area, so as to obtain an analysis result.
Alternatively, the image acquisition device may be an industrial camera or a depth camera. The image acquisition device may continuously acquire continuous multi-frame live images of the specified area, or may acquire one frame of live images of the specified area at intervals, which is not limited in the embodiment of the present application.
The lidar may be used to collect point cloud data for the designated area.
The preset algorithm may be an image segmentation algorithm and/or a semantic recognition algorithm.
Alternatively, the illegal job may refer to a job that does not satisfy the job condition.
The operating conditions may be set in advance by the relevant technician. The operation condition may be that each pedestrian in the designated area needs to wear a helmet, or that each pedestrian in the designated area needs to be located in the designated safety area under the condition of operation of each operation device, or any other possible condition, which is not limited in the embodiment of the present application.
The analysis results are used to indicate whether a loading bay in the open pit is occupied, the progress of an ongoing work task at the loading bay in the open pit, whether the designated area is a loading bay in the open pit or is any area previously set by the relevant technician.
In the case that the analysis result is obtained, the functional area intelligent monitoring edge subsystem 1022 may send the analysis result to the central cloud 101 or each of the working devices currently located in the corresponding area. In this case, the central cloud 101 may generate a corresponding job instruction according to the analysis result and send the job instruction to each of the job devices currently located in the corresponding area, or each of the job devices may schedule or control itself according to the analysis result.
It should be noted that, in the case that it is determined that the specific area has the illegal operation, the functional area intelligent monitoring edge subsystem 1022 may send the location information of the specific area and the field image of the specific area acquired by the image acquisition device to the central cloud 101, and store the location information and the field image by the central cloud 101 and send the stored field image to other terminal devices or servers that may be communicatively connected to the central cloud 101, so as to prompt the relevant technician that the specific area has the illegal operation.
In addition, the real-time occupation analysis, scene recognition and job progress analysis are performed on the designated area according to the field image, so that the real-time state of the designated area can be accurately determined, and suitable scheduling can be performed on each job device, for example, if the designated area is occupied, each job device is scheduled to other areas, or if the job progress of the designated area is analyzed to be lower, more idle job devices can be controlled or scheduled to assist the job in the designated area, so that the job progress is accelerated.
Thus, the accuracy and the comprehensiveness of monitoring the operation process can be improved. In addition, the safety and the efficiency of the operation process in the industrial and mining industry can be improved.
In a possible implementation manner, multi-mode communication is adopted between the central cloud 101 and the edge 102, so as to switch the communication modes according to the size of the data to be transmitted.
Optionally, the communication modes adopted between the central cloud 101 and the edge 102 may include a V2X (Vehicle to Everything) communication mode, a 5G communication mode, a message queue telemetry transport (Message Queuing Telemetry Transport, MQTT) protocol communication mode, and the like, which is not limited in the embodiments of the present application.
The data to be transmitted may be environmental data, operation environmental data, image or video data, etc. acquired or acquired by each subsystem of the edge 102, which is not limited in this embodiment of the present application.
If the data amount of the data to be transmitted is smaller than the preset data amount, the data to be transmitted can be determined to be the data to be transmitted with small data amount, and if the data amount of the data to be transmitted is larger than or equal to the preset data amount, the data to be transmitted can be determined to be the data to be transmitted with large data amount.
For example, the edge 102 may transmit small data amount of data to be transmitted to the central cloud 101 through the V2X communication mode, and the edge 102 may transmit large data amount of data to be transmitted to the central cloud 101 through the 5G communication mode or the MQTT protocol communication mode.
For example, if the data to be transmitted is video or image data, a video encoding and decoding technology may be further used to compress the data to be transmitted, and then a 5G communication mode or an MQTT protocol communication mode is used to transmit the data to be transmitted to the central cloud 101.
In general, the target perception and understanding edge subsystem 1021 and production environment monitoring edge subsystem 1023 in edge 102 monitor and acquire data as small data volume data to be transmitted. The functional area intelligent monitoring edge subsystem 1022 and the intelligent roadside cooperative edge subsystem 1024 in the edge 102 monitor and acquire data that is to be transmitted with a large data volume, which is not limited in this embodiment of the present application.
In one possible manner, the central cloud 101 and the edge 102 use multi-mode communication to switch the communication modes according to the aging requirement of the data to be transmitted.
Optionally, the aging requirement of the data to be transmitted may be used to indicate the transmission speed required by the edge 102 to transmit the data to the central cloud 101.
Generally, the higher the aging requirement of the data to be transmitted, the faster the transmission speed required for the edge 102 to transmit the data to the central cloud 101. Otherwise, the slower the transmission speed required by the characterization edge 102 to transmit data to the central cloud 101.
For example, the edge 102 may transmit the data to be transmitted with higher aging requirement to the central cloud 101 in the V2X communication mode or the 5G communication mode, and the edge 102 may transmit the data to be transmitted with lower aging requirement to the central cloud 101 in the MQTT protocol communication mode.
In addition, if the data to be transmitted is small in data size and has a high aging requirement, the data to be transmitted can be transmitted to the central cloud 101 in a V2X communication mode. If the data to be transmitted is large in data amount and the aging requirement is high, the data to be transmitted can be transmitted to the central cloud 101 in a 5G communication mode. If the data to be transmitted is large in data amount and the aging requirement is low, the data to be transmitted can be transmitted to the central cloud 101 by adopting an MQTT protocol communication mode.
Generally, the data monitored and acquired by the target sensing and understanding edge subsystem 1021, the functional area intelligent monitoring edge subsystem 1022 and the production environment monitoring edge subsystem 1023 in the edge 102 are data to be transmitted with higher time-consuming requirements. The data monitored and acquired by the cooperative edge subsystem 1024 of the intelligent roadside in the edge 102 is to be transmitted with low aging requirement, which is not limited in the embodiment of the present application.
For example, the environmental awareness analysis result monitored and obtained by the edge 102 is small data volume data with higher aging requirement, and then the environmental awareness analysis result can be directly transmitted to the central cloud 101 by adopting a V2X communication mode. The video stream data monitored and acquired by the edge 102 is generally large data volume data with higher aging requirement, so that the video stream data can be compressed by adopting a video encoding and decoding technology and then transmitted to the central cloud 101 by adopting a 5G communication technology. The system configuration information and the log information monitored and acquired by the edge 102 are generally data with lower aging requirements, and then the system configuration information and the log information can be packaged and transmitted to the central cloud 101 by adopting an MQTT protocol communication mode, but the method is not limited thereto.
In addition, the communication modes adopted between the central cloud 101 and the operation device 103 may also include multiple modes such as a V2X communication mode, a 5G communication mode, and an MQTT protocol communication mode.
Notably, the multi-mode communication between the central cloud 101 and the edge 102 can improve flexibility of data transmission and management efficiency of each operation device.
In a possible implementation manner, referring to fig. 4, on the basis of fig. 3, the edge 102 further includes: the system operates a monitoring subsystem 1025.
The system operation monitoring subsystem 1025 is used to monitor the operation status of each subsystem in the edge 102.
The system operation monitoring subsystem 1025 is further configured to determine whether each subsystem in the edge 101 has an abnormality according to the operation state, and transmit the abnormality information to the central cloud 101.
Optionally, the anomaly information is information such as a name, a number of a subsystem in which the anomaly exists, a device or equipment in which the anomaly exists in each subsystem, and a time when the anomaly exists.
In addition, the system operation monitoring subsystem 1025 may analyze the mode of solving the abnormality according to the operation state of each subsystem and the abnormality information, generate a solution, and transmit the solution to the central cloud 101, which is not limited in the embodiment of the present application.
The system operation monitoring subsystem 1025 may determine the operation status of each subsystem by heartbeat monitoring of each subsystem in the edge 102.
In addition, the system operation monitoring subsystem 1025 can also capture the abnormal information of each subsystem in real time, collect the abnormal information of each subsystem and store the collected abnormal information in a local log of the system operation monitoring subsystem 1025 for recording and backup, and report the abnormal information of each subsystem to the central cloud 101 in real time so that relevant technicians can timely perform corresponding processing after receiving the fault information.
The abnormality information may be actively issued by each subsystem, or may be generated by the system operation monitoring subsystem 1025 after the system operation monitoring subsystem 1025 monitors that the abnormality exists in each subsystem, which is not limited in the embodiment of the present application.
Specifically, the system operation monitoring subsystem 1025 may be specifically configured to monitor whether each subsystem in the edge 102 can normally collect data, can normally communicate, can normally transmit data, and the like.
If the system operation monitoring subsystem 1025 monitors that any subsystem in the edge 102 cannot normally collect data, cannot normally communicate or cannot normally transmit data, it can be determined that an abnormality exists in the subsystem.
In this way, the abnormality of each subsystem in the edge 102 can be timely found and transmitted to the central cloud 101, so that relevant technicians can perform corresponding processing. Thus, the effect of improving the management reliability of each working device can be achieved.
In a possible implementation manner, referring to fig. 5, on the basis of fig. 4, the edge 102 further includes: a prompt subsystem 1026.
The prompt subsystem 1026 is configured to output prompt information when the system operation monitoring subsystem 1025 determines that an abnormality exists in each subsystem in the edge 102.
Optionally, the prompt subsystem 1026 may transmit the prompt information to the central cloud 101, and then the central cloud 101 sends a corresponding operation instruction to the repair device responsible for maintaining other devices in the auxiliary operation end 1032, so as to control the repair device responsible for maintaining other devices to repair or maintain the subsystem with an abnormality. The central cloud 101 may also send the prompt information to other terminal devices or servers that may be communicatively connected to the central cloud 101, so as to notify related technicians to repair or maintain the subsystem with the abnormality.
In addition, the alert subsystem 1026 may transmit the alert information to other terminal devices or servers that may be communicatively connected to the alert subsystem 1026, so as to notify the relevant technician to repair or maintain the subsystem with the abnormality, which is not limited in the embodiment of the present application.
Optionally, the prompt information may be in the form of text, image, light, sound, etc., which is not limited in the embodiment of the present application.
The hint information may be used to hint the relevant technician to repair or maintain the subsystem for which the anomaly exists. The hint information may include information such as the name or number of the subsystem in which the abnormality exists, the time when the abnormality exists, the device or equipment in which the abnormality exists in each subsystem, the location where the device or equipment in each subsystem is installed, the name or job number of the relevant technician responsible for repairing or maintaining the subsystem in which the abnormality exists, the planned repair time, etc.
The alert subsystem 1026 may also be configured to output the alert message when the edge 102 detects an obstacle, a ground depression, a ground collapse, a slope landslide, and/or a violation of the designated area in the work environment.
In this case, the prompt information may also be used to prompt the relevant technician to stop the current operation to adjust the current operation route and/or to perform the operation according to the operation conditions.
The prompt message may include text content as follows, but is not limited thereto. If the alert subsystem 1026 determines, at 2022, 4/2/12:00 that there is an abnormality in the image capturing device Z in the functional area intelligent monitoring edge subsystem 1022 in the edge 102, the job number of the relevant technician responsible for repairing or maintaining the functional area intelligent monitoring edge subsystem 1022 is 001. Then, the prompt message may be "2022, 4, 2, 12:00 finds that the image capturing device Z in the intelligent monitoring edge subsystem of the functional area in the edge has an abnormality", please ask the technician with the work number 001 to complete repair before 2022, 4, 2, 18:00.
In this way, the subsystems in the edge 102 that are in the presence of anomalies may be maintained or repaired in a timely manner. Thus, the reliability and efficiency of management of each working device and the safety of the work can be improved.
In a possible implementation manner, the central cloud 101 is further configured to store the environmental data and the job data, monitor operations of the edge 102 and the job device 103, configure and manage the edge 102 and the job device 103, and remotely update the edge 102 and the job device 103.
For example, the central cloud 101 may store the job data and/or the environment data sent by the edge 102, and the central cloud 101 may delete the job data and/or the environment data stored in the central cloud 101 once every predetermined time. Generally, the preset duration may be set longer, for example, 20 days or one month, and of course, the preset duration may be set to any duration, which is not limited in the embodiment of the present application.
For example, the central cloud 101 may further monitor the working states of each of the working devices in the edge 102, such as the target sensing and understanding edge subsystem 1021, the functional area intelligent monitoring edge subsystem 1022, the production environment monitoring edge subsystem 1023, the intelligent roadside cooperative edge subsystem 1024, and the working device 103, and determine, according to the working states, whether each of the working devices in the edge 1021, the functional area intelligent monitoring edge subsystem 1022, the production environment monitoring edge subsystem 1023, the intelligent roadside cooperative edge subsystem 1024, and the working device 103 is abnormal, and analyze the abnormal manner according to the abnormality occurring in each subsystem or each working device, and generate a maintenance scheme.
The central cloud 101 may also generate maintenance information according to the maintenance scheme, the name and number of the subsystem or the operation device with the abnormality, the time for determining the abnormality, and the like, and generate and send a corresponding operation instruction to the repair device responsible for maintaining other devices in the auxiliary operation end 1032 according to the maintenance information, so as to control the repair device responsible for maintaining other devices to repair or maintain the subsystem or the operation device with the abnormality, or send the maintenance information to other terminal devices or servers that may be communicatively connected with the central cloud 101, so as to notify related technicians to repair or maintain the subsystem or the operation device with the abnormality.
For another example, the central cloud 101 may further perform configuration management on the central cloud 101, the edge end 102 and the operation device end 103 to associate each subsystem in the central cloud 101 and the edge end 102 with each operation device in the operation device end 103, and may set each subsystem in the central cloud 101 and the edge end 102 and each operation device in the operation device end 103, so as to ensure that the unmanned mine global intelligent monitoring system may operate normally.
For another example, the central cloud 101 may specifically remotely update each subsystem in the edge 102, a device or equipment in each subsystem, and a software resource stored in a memory of each operation equipment in the operation equipment 103, and may also remotely perform firmware upgrade on each subsystem in the edge 102, a device or equipment in each subsystem, and each operation equipment in the operation equipment 103.
Thus, the collaboration of the central cloud 101, the edge 102 and the operation device 103 can be improved.
The foregoing is merely a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes or substitutions are covered in the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
The foregoing description is only of the preferred embodiments of the present application and is not intended to limit the same, but rather, various modifications and variations may be made by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.
Claims (8)
1. An unmanned mine universe intelligent monitoring system, characterized in that the system comprises: the center cloud end, the edge end and the operation equipment end; the central cloud end is in communication connection with the edge end and the operation equipment end, and the edge end is in communication connection with the operation equipment end;
the central cloud end is used for receiving the environment data sent by the edge end, sending the environment data to the operation equipment end so that the operation equipment end can schedule or control the operation equipment end according to the environment data, and sending an operation instruction to the edge end according to a preset production rule and the environment data;
the central cloud end is further configured to receive the operation data sent by the edge end, call a corresponding analysis model according to the operation data, obtain a mine monitoring result, generate the operation instruction according to the mine monitoring result, and send the operation instruction to the operation equipment end so as to schedule or control the operation equipment end, where the analysis model performs training optimization according to the preset production rule, the environment data and the operation data;
the edge end is used for acquiring the operation data of the operation equipment end after the operation is executed according to the operation instruction and acquiring the environment data of the operation environment of the operation equipment end;
The edge comprises one or more of the following: the intelligent road side intelligent monitoring system comprises a target perception and understanding edge subsystem, a functional area intelligent monitoring edge subsystem, a production environment monitoring edge subsystem and an intelligent road side cooperative edge subsystem; wherein,
the target perception and understanding edge subsystem is used for perceiving and predicting barrier information;
the intelligent monitoring edge subsystem of the functional area is used for monitoring field data of a designated area, wherein the field data comprises the operation state of the designated area;
the production environment monitoring edge subsystem is used for monitoring operation environment data, and the operation environment data comprises: ground data, retaining wall data, slope data and weather data;
the intelligent road side cooperative edge subsystem is used for supporting control and scheduling management according to the operation instruction, and is used for controlling and scheduling management of other subsystems of the edge end except the intelligent road side cooperative edge subsystem and/or the operation equipment end according to the obstacle information, the field data and the operation environment data.
2. The unmanned mining universe intelligent monitoring system of claim 1, wherein the working equipment end comprises: a mining car end and an auxiliary operation end;
The production environment monitoring edge subsystem comprises a camera and/or a laser radar, and is particularly used for scanning the pavement of the operation area through the camera and/or the laser radar to obtain pavement leveling information of the operation area; when the road surface leveling information indicates that the road surface does not meet the leveling condition, an operation and maintenance instruction is sent to the auxiliary operation end;
the production environment monitoring edge subsystem further comprises a sensor for detecting weather data of the working environment, and the sensor is specifically used for detecting the temperature, the humidity, the wind direction, the wind speed and the weather of the working environment.
3. The unmanned mine universe intelligent monitoring system as claimed in claim 1, wherein the functional area intelligent monitoring edge subsystem comprises an image acquisition device and/or a laser radar, and is specifically used for acquiring a field image of the specified area and/or point cloud data of the specified area as the field data, analyzing the field image and/or the point cloud data of the specified area through a preset algorithm, and determining whether illegal operation exists in the specified area; and carrying out real-time occupation analysis, scene identification and operation progress analysis on the appointed area according to the on-site image and/or the point cloud data of the appointed area, and obtaining an analysis result.
4. The unmanned mine universe intelligent monitoring system of claim 2 wherein the central cloud and the edge end adopt multimode communication to switch communication modes according to the size of data to be transmitted.
5. The unmanned mine universe intelligent monitoring system of claim 2, wherein the central cloud end and the edge end adopt multi-mode communication to switch communication modes according to time-dependent requirements of data to be transmitted.
6. The unmanned mine universe intelligent monitoring system of claim 1, wherein the edge further comprises: a system operation monitoring subsystem;
the system operation monitoring subsystem is used for monitoring the operation state of each subsystem in the edge end; and determining whether each subsystem in the edge terminal is abnormal according to the running state, and transmitting abnormal information to the central cloud.
7. The unmanned mine universe intelligent monitoring system of claim 6, wherein the edge further comprises: a prompting subsystem;
the prompting subsystem is used for outputting prompting information under the condition that the system operation monitoring subsystem determines that each subsystem in the edge end is abnormal.
8. The unmanned mine universe intelligent monitoring system of any one of claims 1 to 7, wherein the central cloud is further configured to store the environmental data and the job data, monitor operation of the edge side and the job device side, configure and manage the central cloud, the edge side and the job device side, and remotely update the edge side and the job device side.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210472816.9A CN114844925B (en) | 2022-04-29 | 2022-04-29 | Unmanned mine universe intelligent monitoring system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210472816.9A CN114844925B (en) | 2022-04-29 | 2022-04-29 | Unmanned mine universe intelligent monitoring system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114844925A CN114844925A (en) | 2022-08-02 |
| CN114844925B true CN114844925B (en) | 2024-04-05 |
Family
ID=82567680
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210472816.9A Active CN114844925B (en) | 2022-04-29 | 2022-04-29 | Unmanned mine universe intelligent monitoring system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114844925B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115328171B (en) * | 2022-10-11 | 2023-02-10 | 青岛慧拓智能机器有限公司 | Method, device, chip, terminal, equipment and medium for generating position of loading point |
Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110262421A (en) * | 2019-06-21 | 2019-09-20 | 深圳市美兆环境股份有限公司 | The control method and device of production equipment |
| CN211061895U (en) * | 2019-11-14 | 2020-07-21 | 北京国电通网络技术有限公司 | Job site edge calculation thing allies oneself with analysis alarm system based on thing networking |
| CN111754082A (en) * | 2020-06-01 | 2020-10-09 | 湖南大学 | Intelligent delivery system |
| CN111784026A (en) * | 2020-05-28 | 2020-10-16 | 国网信通亿力科技有限责任公司 | Cloud-side cooperative sensing-based all-dimensional physical examination system for electrical equipment of transformer substation |
| CN112087522A (en) * | 2020-09-18 | 2020-12-15 | 北京航空航天大学 | Edge cloud collaborative flow arrangement system for industrial robot data processing |
| CN112913262A (en) * | 2018-09-07 | 2021-06-04 | 诺基亚通信公司 | Flexible usage data collection for environmental sensing capabilities in shared spectrum |
| CN113342382A (en) * | 2021-06-30 | 2021-09-03 | 北京京东乾石科技有限公司 | Data verification method and system and edge terminal equipment |
| CN113378947A (en) * | 2021-06-21 | 2021-09-10 | 北京踏歌智行科技有限公司 | Vehicle road cloud fusion sensing system and method for unmanned transportation in open-pit mining area |
| JP2021154115A (en) * | 2020-02-16 | 2021-10-07 | オリジン ワイヤレス, インコーポレイテッドOrigin Wireless, Inc. | Method, apparatus, and system for wireless monitoring |
| CN113872328A (en) * | 2021-09-26 | 2021-12-31 | 国网安徽省电力有限公司铜陵供电公司 | Transformer substation remote intelligent inspection method and system based on neural network |
| CN113888871A (en) * | 2021-10-20 | 2022-01-04 | 上海电科智能系统股份有限公司 | Automatic handling linkage system and method for highway traffic incident |
| CN113920061A (en) * | 2021-09-09 | 2022-01-11 | 中国科学院自动化研究所 | Industrial robot operation method and device, electronic equipment and storage medium |
| CN113935645A (en) * | 2021-10-22 | 2022-01-14 | 中国海洋石油集团有限公司 | High-risk operation management and control system and method based on identification analysis technology |
| CN113949703A (en) * | 2021-09-18 | 2022-01-18 | 国网上海市电力公司 | Cloud edge cooperative system for electric power artificial intelligence |
| CN114115392A (en) * | 2021-10-20 | 2022-03-01 | 中通服和信科技有限公司 | Intelligent classroom control system and method based on 5G cloud edge combination |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3108420A4 (en) * | 2014-02-21 | 2017-08-02 | Safety Key Solutions FZ - LLC | Worksite monitoring and management systems and platforms |
-
2022
- 2022-04-29 CN CN202210472816.9A patent/CN114844925B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112913262A (en) * | 2018-09-07 | 2021-06-04 | 诺基亚通信公司 | Flexible usage data collection for environmental sensing capabilities in shared spectrum |
| CN110262421A (en) * | 2019-06-21 | 2019-09-20 | 深圳市美兆环境股份有限公司 | The control method and device of production equipment |
| CN211061895U (en) * | 2019-11-14 | 2020-07-21 | 北京国电通网络技术有限公司 | Job site edge calculation thing allies oneself with analysis alarm system based on thing networking |
| JP2021154115A (en) * | 2020-02-16 | 2021-10-07 | オリジン ワイヤレス, インコーポレイテッドOrigin Wireless, Inc. | Method, apparatus, and system for wireless monitoring |
| CN111784026A (en) * | 2020-05-28 | 2020-10-16 | 国网信通亿力科技有限责任公司 | Cloud-side cooperative sensing-based all-dimensional physical examination system for electrical equipment of transformer substation |
| CN111754082A (en) * | 2020-06-01 | 2020-10-09 | 湖南大学 | Intelligent delivery system |
| CN112087522A (en) * | 2020-09-18 | 2020-12-15 | 北京航空航天大学 | Edge cloud collaborative flow arrangement system for industrial robot data processing |
| CN113378947A (en) * | 2021-06-21 | 2021-09-10 | 北京踏歌智行科技有限公司 | Vehicle road cloud fusion sensing system and method for unmanned transportation in open-pit mining area |
| CN113342382A (en) * | 2021-06-30 | 2021-09-03 | 北京京东乾石科技有限公司 | Data verification method and system and edge terminal equipment |
| CN113920061A (en) * | 2021-09-09 | 2022-01-11 | 中国科学院自动化研究所 | Industrial robot operation method and device, electronic equipment and storage medium |
| CN113949703A (en) * | 2021-09-18 | 2022-01-18 | 国网上海市电力公司 | Cloud edge cooperative system for electric power artificial intelligence |
| CN113872328A (en) * | 2021-09-26 | 2021-12-31 | 国网安徽省电力有限公司铜陵供电公司 | Transformer substation remote intelligent inspection method and system based on neural network |
| CN113888871A (en) * | 2021-10-20 | 2022-01-04 | 上海电科智能系统股份有限公司 | Automatic handling linkage system and method for highway traffic incident |
| CN114115392A (en) * | 2021-10-20 | 2022-03-01 | 中通服和信科技有限公司 | Intelligent classroom control system and method based on 5G cloud edge combination |
| CN113935645A (en) * | 2021-10-22 | 2022-01-14 | 中国海洋石油集团有限公司 | High-risk operation management and control system and method based on identification analysis technology |
Non-Patent Citations (4)
| Title |
|---|
| Iot Based Edge And Cloud Computing For Smart Environmental Engineering Applications;Weisong Shi，Yongli Zhang;《digitalcommons》;全文 * |
| 智慧矿山边缘云协同计算技术架构与基础保障关键技术探讨;姜德义;魏立科;王翀;范金洋;任奕玮;;煤炭学报(01);全文 * |
| 智能矿山车联网体系架构与关键技术;阎俊豪;贾宗璞;李东印;;煤炭科学技术(07);全文 * |
| 金属矿山风险监测物联网关键技术研究现状与发展趋势;谭爱平;刘春德;邓庆绪;;金属矿山(01);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114844925A (en) | 2022-08-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10048700B1 (en) | Generating state information for autonomous vehicles | |
| CN113581211B (en) | Vehicle driving control method, system and device and readable storage medium | |
| US11702070B2 (en) | Autonomous vehicle operation with explicit occlusion reasoning | |
| US20200211376A1 (en) | Systems and Methods to Enable a Transportation Network with Artificial Intelligence for Connected and Autonomous Vehicles | |
| CN112382131B (en) | Airport scene safety collision avoidance early warning system and method | |
| CN111383456B (en) | Localized artificial intelligence system for intelligent road infrastructure system | |
| CN114489122B (en) | UAV and matching airport-based automatic highway inspection method and system | |
| KR102595886B1 (en) | Multi-modal segmentation network for enhanced semantic labeling in mapping | |
| CN112562409A (en) | Autonomous parking system and method based on multi-access edge calculation | |
| US11816992B2 (en) | Real time fleet management for autonomous vehicles using puddle mapping | |
| KR102631726B1 (en) | Environmental limitation and sensor anomaly system and method | |
| CN213461826U (en) | Autonomous parking system based on multi-access edge calculation | |
| CN114844925B (en) | Unmanned mine universe intelligent monitoring system | |
| CN114501385A (en) | Collaborative automatic driving system applied to intelligent network connection traffic system | |
| CN114387785A (en) | Safety management and control method and system based on intelligent highway and storable medium | |
| Poornima et al. | Fog robotics-based intelligence transportation system using line-of-sight intelligent transportation | |
| US10953871B2 (en) | Transportation infrastructure communication and control | |
| US20200401149A1 (en) | Corner case detection and collection for a path planning system | |
| CN110641473A (en) | Transport infrastructure communication and control | |
| CN111427063B (en) | Mobile device traffic control method, device, equipment, system and medium | |
| CN116341845A (en) | Automatic early warning and intelligent supplying method and system for sanitation vehicle resources | |
| CN114103994B (en) | Control method, device and equipment based on automatic road surface cleaning of vehicle and vehicle | |
| Petkova | Deploying drones for autonomous detection of pavement distress | |
| US20240017744A1 (en) | Operational weather management | |
| CN117612140B (en) | Road scene identification method and device, storage medium and electronic equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information |
Address after: 266000 room 206-1, building D, Pangu maker space, No. 100 Torch Road, Qingdao high tech Industrial Development Zone, Qingdao, Shandong Province Applicant after: QINGDAO VEHICLE INTELLIGENCE PIONEERS Inc. Applicant after: Zhongke huituo (Shaanxi) Technology Co.,Ltd. Address before: 266000 room 206-1, building D, Pangu maker space, No. 100 Torch Road, Qingdao high tech Industrial Development Zone, Qingdao, Shandong Province Applicant before: QINGDAO VEHICLE INTELLIGENCE PIONEERS Inc. Applicant before: Shaanxi huituo infinite Technology Co.,Ltd. |
|
| CB02 | Change of applicant information | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |