CN117875900A - Electric power material digital employee cluster scheduling system and method - Google Patents
Electric power material digital employee cluster scheduling system and method Download PDFInfo
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Abstract
The invention belongs to the field of power material dispatching and provides a power material digital employee cluster dispatching system and method. The system comprises a dispatching center, an intelligent detection cluster, an intelligent storage cluster and an intelligent distribution cluster; the intelligent detection cluster is used for receiving quality inspection instructions issued by the dispatching center, locking sampling inspection materials from electric materials to be put in storage according to a sampling inspection plan, automatically executing sampling, sample sealing and sample preparing tasks, and flexibly configuring detection equipment according to the type of the electric materials to be inspected; the intelligent warehouse cluster is used for receiving a warehouse instruction issued by the dispatching center and automatically executing electric power material loading and unloading, picking, loading and unloading, checking and grouping operations on the electric power materials to be warehoused after quality inspection is completed; the intelligent distribution cluster is used for receiving the distribution instruction issued by the dispatching center, intelligently matching the transport vehicle with the electric power materials to be distributed from the warehouse by the dispatching center and forming a self-adaptive distribution scheme so as to distribute the electric power materials to a preset destination.
Description
Technical Field
The invention belongs to the field of power material dispatching, and particularly relates to a power material digital employee cluster dispatching system and method.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
In the current links of logistics, digital staff are used for participating in related activities instead of human staff. The digital employee here refers to a robotic device such as: picking robots in the traditional logistics industry, and the like.
However, the traditional logistics materials have the advantages of large number of small materials and single types, and the materials are delivered and sorted by means of universal robot equipment. The inventor finds that compared with the traditional logistics materials, the electric power materials have the characteristics of different sizes and various types, so that the traditional logistics robot equipment cannot be suitable for tasks such as warehouse-in and warehouse-out and sorting of the electric power materials, and part of business scenes still need intervention of operators, the problems that the traditional manual operation mode is high in labor intensity and low in efficiency, and the warehouse operation process management and control system and the inspection and distribution business system are lack to independently operate are still solved, and meanwhile, the information system only partially realizes cooperative operation, and a longitudinally through and transversely cooperative integrated platform is not formed.
Disclosure of Invention
In order to solve the technical problems in the background art, the invention provides a power material digital employee cluster scheduling system and a method, which can realize the integration cooperation of warehouse operation automation, real-time management and control in the warehouse operation process and inspection and storage allocation through the technologies of word employee cluster regulation and control, information logistics unified scheduling, intelligent Internet of things and digital twin.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
the first aspect of the invention provides a power material digital employee cluster scheduling system, which comprises a scheduling center, an intelligent detection cluster, an intelligent storage cluster and an intelligent distribution cluster;
the intelligent detection cluster is used for receiving quality inspection instructions issued by the dispatching center, locking sampling inspection materials from electric materials to be put in storage according to a sampling inspection plan, automatically executing sampling, sample sealing and sample preparation tasks, and flexibly configuring detection equipment according to the type of the electric materials to be inspected so as to realize full automation of the electric material quality and collaborative detection of people and machines;
the intelligent warehousing cluster is used for receiving warehousing instructions issued by the dispatching center and automatically executing electric power material loading and unloading, picking, loading and unloading, checking and grouping operations on the electric power materials to be warehoused after quality inspection is completed;
the intelligent distribution cluster is used for receiving distribution instructions issued by the dispatching center, starting a depth vision recognition task for the electric power materials to be distributed when the electric power materials are delivered out of the warehouse, reading the distributed electric power material information and transmitting the electric power material information to the dispatching center, and the dispatching center is used for intelligently matching with a transport vehicle and forming a self-adaptive distribution scheme so as to distribute the electric power materials to a preset destination.
As an embodiment, the scheduling center is further configured to: constructing a matched loading model of the electric power supplies and the vehicle according to the distributed electric power supply information and the vehicle information; and then, a load strategy is adaptively generated by taking the maximum utilization space of the vehicle as a target.
As one embodiment, the load strategy includes material loading order and placement location information.
As an implementation mode, the dispatching center embeds a warehouse panoramic digital twin scene, and the digital twin scene is guided into a subarea to display service information of each link of detection, storage and distribution.
As an implementation mode, the dispatching center is embedded with a digital twin engine, and the operation state, the detection parameters and the movement condition of the detection area intelligent quality inspection cluster of the detection equipment are mapped by taking the detection area digital model as a background.
As an implementation mode, the dispatching center is embedded with a digital twin engine, a digital model of warehouse storage is mapped by taking a warehouse area digital model as a background, and the operation state and the motion state of the intelligent warehouse cluster are mapped on transportation and stations.
As an implementation mode, the dispatching center is internally embedded with a digital twin engine, takes a distribution operation digital model as a background, maps each scene of a distribution link, loads operation actions of an intelligent distribution cluster and conditions of carrying goods and materials, and displays the operation actions and the conditions of carrying goods and materials.
As an implementation mode, the intelligent detection cluster is also used for recording the whole quality inspection process of the spot inspection materials and uploading detection results to a dispatching center for storage by using a block chain.
As an implementation mode, the intelligent warehouse cluster is used for carrying out warehouse-in management on electric power materials according to the principle of first things and then accounts.
As an implementation mode, the intelligent warehouse cluster is used for carrying out warehouse-out management on electric power materials according to the principle of billing before material.
As an embodiment, the smart warehouse cluster is configured to: and unloading the electric power materials to a temporary storage area or a conveying line, and checking the electric power materials.
As one implementation mode, the dispatching center is further used for receiving bin position information and dispatching the intelligent warehouse cluster to finish the loading of goods and materials, receiving a loading operation feedback result and generating a warehouse entry list.
As an implementation mode, the dispatching center is further used for generating a delivery bill, materials and bin position related information, and dispatching the intelligent storage cluster to finish delivery operation of the electric materials.
As an implementation mode, the intelligent distribution cluster is further used for starting the whole-process monitoring on-road electric power material task so as to ensure that the whole transportation process is safe and controllable.
As one implementation mode, the dispatching center is further connected with an intelligent park cluster, and the intelligent park cluster is used for receiving related instructions issued by the dispatching center based on the digital twin park model and executing intelligent traffic, intelligent security, intelligent resources, intelligent fire control and environmental sanitation management and control tasks.
A second aspect of the present invention provides a scheduling method based on the electric power material digital employee cluster scheduling system as described above, which includes:
the dispatching center issues a quality inspection instruction to the intelligent detection cluster, the intelligent detection cluster locks sampling inspection materials from electric materials to be put in storage according to a sampling inspection plan, automatically performs sampling, sample sealing and sample preparation tasks, and flexibly configures detection equipment according to the type of the electric materials to be inspected so as to realize full automation of the electric material quality and collaborative detection of a man-machine;
the dispatching center issues a warehousing instruction to the intelligent warehousing cluster, and the intelligent warehousing cluster automatically performs electric power material loading and unloading, picking, loading and unloading, checking and grouping operations on the electric power materials to be warehoused after quality inspection is completed;
the dispatching center sends a distribution instruction to the intelligent distribution cluster, the intelligent distribution cluster starts a depth vision recognition task for the electric power materials to be distributed when the electric power materials are delivered out of the warehouse, reads the distributed electric power material information and transmits the electric power material information to the dispatching center, and the dispatching center adopts an electric power material depth vision self-adaptive distribution method to intelligently match transport vehicles and form a self-adaptive distribution scheme so as to distribute the electric power materials to a preset destination.
Compared with the prior art, the invention has the beneficial effects that:
(1) The intelligent internet of things technology integrating the detection, storage and distribution of electric power materials is designed, the seamless combination of the detection, intelligent storage and active distribution of the electric power equipment is taken as a main line, the material flow existing in the whole process of detection, storage and distribution is taken as an organic whole based on robot clusters, intelligent internet of things and digital twin, a digital staff cluster scheduling system of the electric power materials is developed, the problems of high labor intensity and low independent operation of a detection, storage and distribution service system in the traditional manual operation mode are solved, the automation of storage operation and the real-time management and control of the operation process are realized, the integration cooperation of detection, storage and distribution is realized, and the field operation efficiency is improved.
(2) The depth vision self-adaptive load-carrying technology of the electric power supplies is designed, a load model of matching the electric power supplies with the vehicles is constructed according to the information of the electric power supplies and the information of the vehicles, a load-carrying strategy is generated in a self-adaptive mode, the problem of high labor intensity and low efficiency of the traditional manual operation mode is solved, intelligent matching of the electric power supplies with the transportation vehicles is realized, and the field operation efficiency is improved.
(3) The electric power material panoramic digital twin technology is designed, the distribution operation digital model is used as a background, each scene of a distribution link is mapped, the operation action of an intelligent distribution cluster and the condition of carrying materials are loaded, the problem of lack of management and control in the electric power material storage operation process is solved, the visualization of service information of each link of detection, storage and distribution is realized, and the real-time management and control efficiency is improved.
Additional aspects of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.
FIG. 1 is a schematic diagram of a power material digital employee cluster scheduling system according to an embodiment of the present invention;
fig. 2 is a flowchart of a scheduling method based on a power material digital employee cluster scheduling system according to an embodiment of the present invention.
Detailed Description
The invention will be further described with reference to the drawings and examples.
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
Example 1
Referring to fig. 1, the power material digital employee cluster scheduling system of the present embodiment includes a scheduling center, an intelligent detection cluster, an intelligent warehouse cluster, and an intelligent distribution cluster.
In one or more embodiments, the intelligent detection cluster is used for receiving a quality inspection instruction issued by the dispatching center, locking sampling inspection materials from electric materials to be put in storage according to a sampling inspection plan, automatically executing tasks of sampling, sealing and preparing samples, and flexibly configuring detection equipment according to the type of the electric materials to be inspected so as to realize full automation of the quality of the electric materials and collaborative detection of people and machines.
In some other embodiments, the intelligent detection cluster is further used for recording the whole quality inspection process of the spot check materials, and uploading the detection result to the dispatching center for storage by using the block chain.
In one or more embodiments, the intelligent warehouse cluster is configured to receive a warehouse instruction issued by a dispatching center, and automatically perform operations of loading, unloading, picking, loading and unloading, checking and grouping electric power materials to be warehoused after quality inspection is completed.
In a specific implementation, the intelligent warehouse cluster is used for carrying out warehouse management on electric power materials according to a principle of first things and then accounts. The intelligent warehouse cluster is used for carrying out warehouse-out management on electric power materials according to the principle of billing before material.
According to the embodiment, the power supplies and the bills are respectively delivered and stored according to the principle, so that the one-to-one correspondence between the power supplies and the bills can be ensured, and the accuracy of storage information of the power supplies is improved.
The intelligent warehouse cluster is used for: and unloading the electric power materials to a temporary storage area or a conveying line, and checking the electric power materials.
In other embodiments, the dispatching center is further configured to receive bin information and dispatch the intelligent warehouse cluster to finish loading the intelligent warehouse cluster to goods and materials, receive a loading operation feedback result and generate a warehouse entry list. The dispatching center is also used for generating a delivery bill, materials and bin position related information, and dispatching the intelligent storage cluster to finish delivery operation of the electric materials.
According to the embodiment, the state of the electric power supplies is recorded by using the delivery bill, and the accuracy of the storage information of the electric power supplies is improved.
In one or more embodiments, the intelligent distribution cluster is configured to receive a distribution instruction issued by the dispatching center, start a deep vision recognition task for delivering electric power supplies to be distributed, read information of the distributed electric power supplies, and transmit the information to the dispatching center, and the dispatching center is configured to intelligently match with a transport vehicle and form an adaptive distribution scheme to distribute the electric power supplies to a preset destination.
Specifically, the scheduling center is further configured to: constructing a matched loading model of the electric power supplies and the vehicle according to the distributed electric power supply information and the vehicle information; and then, a load strategy is adaptively generated by taking the maximum utilization space of the vehicle as a target.
The loading strategy comprises information such as loading sequence and placing position of materials. Therefore, the space information of the transport vehicle can be fully utilized, and the transport efficiency of electric power materials is improved.
In other embodiments, the intelligent distribution cluster is further configured to initiate a global monitoring on-transit power supply task to ensure that the overall transportation process is safe and controllable.
In some embodiments, the dispatch center is also coupled to a visualization device.
In the specific implementation process, the dispatching center embeds a warehouse panoramic digital twin scene, and the scene enters into a subarea through digital twin guidance, so that service information of each link of detection, storage and distribution is displayed on a visualization device.
Specifically, the visualization device is further used for displaying the core operation and health indexes of the warehouse, wherein the core operation and equipment health indexes comprise: detecting system operation data, such as detecting the perfection rate of the robot equipment, the current operation and idle quantity, displaying a task queue through a time graph, and displaying the expected completion time and the future task event; the data of the warehousing system, such as loading and unloading, picking and warehousing robot operation conditions, warehouse machine equipment integrity rate, current operation and idle quantity, showing the materials and project events of the current service through a time graph, and predicting the completion time, the materials and project events to be processed in queuing, planning events and predicting the completion time; warehouse operation data, such as occupancy of warehouse areas and operation areas, residual warehouse positions and warehouse area turnover rate, and warehouse out and warehouse in events and corresponding warehouse states thereof are displayed through a time graph; and calculating, storing and network resource conditions, such as application events which mainly occupy the calculation and network resources at present, and displaying the predicted completion time of the current event, the future planning event and nodes, the predicted completion time, the resource change and the like through a time graph.
Specifically, the dispatching center is embedded with a digital twin engine, and the operation state, the detection parameters and the movement condition of the detection area intelligent quality inspection cluster of the detection equipment are mapped and displayed on a visualization device by taking the detection area digital model as a background.
The visualization device is also used for displaying operation and prediction data, resource analysis results and prediction data of the intelligent quality inspection cluster. By clicking a device digital model in the digital twin engine, device monitoring and operation and maintenance module related device operation state data, in-process material information, health state assessment, life assessment, maintenance and calibration events and the like are displayed above the device in the form of a bullet frame. And displaying the detection data, the belonging project information, the production information and the current inspection, storage and distribution plan of the materials by clicking the three-dimensional model of the inspected materials.
Specifically, the dispatching center is embedded with a digital twin engine, a digital model of a warehouse storage position is mapped by taking a warehouse area digital model as a background, and the operation state and the motion state of the intelligent warehouse cluster are mapped on transportation and stations and displayed on a visualization device.
The screen of the visualization device also displays main operation indexes and available resource indexes of the warehouse. The digital model of the bin is selected, and the use amount, the residual amount, the use efficiency, the type, the name, the project, the place, the number, the time of the bin and the like of the materials stored in the bin are displayed. The method comprises the steps of selecting a digital model of a robot system in an intelligent storage cluster, and displaying operation data of the robot system, wherein the operation data comprises monitoring and operation indexes such as the number of robots, working states, the number of completed operation tasks, the number of processed materials, the free time-slag ratio of operation and the like, which are contained in the intelligent storage cluster.
Specifically, the dispatching center is embedded with a digital twin engine, takes a distribution operation digital model as a background, maps each scene of a distribution link, loads operation actions of an intelligent distribution cluster and conditions of carrying materials, and displays the operation actions and the conditions on a visualization device.
The visualization device can display the robot equipment number of the intelligent distribution cluster, the processing task, the departure place and destination (displayed by map route) and the processed material information. And displaying the quantity of the delivered materials, the delivery items, the processing business and material conditions and the available delivery resources on two sides of the large screen.
On the basis of fig. 1, in another embodiment, the dispatching center is further connected to a smart campus cluster, which is used for receiving related instructions issued by the dispatching center based on the digital twin campus model, and executing intelligent traffic, intelligent security, intelligent resources, intelligent fire protection and environmental sanitation management and control tasks.
Specifically, intelligent traffic realizes functions of dispatching, guiding, parking management and the like of delivery vehicles in a park based on technologies such as in-park positioning, information release, parking space management, video monitoring and the like. The manager can check the real-time position of each vehicle in the system in real time, and can perform manual intervention while the system automatically schedules the vehicles to finish manual scheduling of the appointed vehicles.
The park scheduling is to schedule vehicles in the park on the basis of grasping detailed information and distribution tasks of the vehicles in the park, allocate proper parking positions and driving routes for the vehicles and comprehensively schedule multiparty vehicles by comprehensively scheduling park resources.
The park guiding is based on park scheduling, and the information release, video monitoring and positioning system in the park is utilized to guide the vehicle in the running direction and the parking position, so that the vehicle is guided to quickly and accurately reach the target parking space.
The parking management is to allocate proper waiting space for the vehicles according to the tasks and vehicle information of the park vehicles, and guide the vehicles to stop by the park guide.
Specifically, wisdom security protection is based on the video monitoring system, perimeter defending, inspection robot, unmanned aerial vehicle and the entrance guard banister of the whole garden of coverage, warehouse of installation in the garden, realizes controlling the real-time of garden, import and export, bayonet socket, enclosure and warehouse inside, establishes unified video monitoring subsystem through network, optic fibre, 5G passageway, provides services such as panorama control, perimeter defending, entrance guard control, automatic patrol.
The panoramic monitoring realizes the functions of real-time video monitoring, video identification, key monitoring, video round robin and the like. The perimeter defending uses infrared, laser, microwave, electronic fence, vibration detection and other technologies to defend and alarm the perimeter of the park, and automatically pushes alarm videos through video linkage.
The entrance guard management and control realizes the management and control of personnel and vehicles entering a park, integrates with entrance guard, traffic, elevator control and the like, effectively confirms the identity of a visitor, manages and controls the entrance and exit area of the visitor, and performs key management on special objects, and mainly comprises functions of visitor management, visitor footprint, special personnel management and the like.
The automatic patrol function is based on autonomous navigation of a robot and an unmanned aerial vehicle, and the robot and the unmanned aerial vehicle are provided with a high-definition visible light camera and an infrared thermal imager, so that all-dimensional and all-terrain patrol and special patrol of a park can be realized. The inspection image can be sent to a background system in real time to replace manual inspection, and mainly comprises the inspection robot fixed inspection and the inspection unmanned aerial vehicle special inspection.
Specifically, the intelligent resource is based on comprehensive monitoring of various links such as water, electricity, heating, gas, photovoltaic, wind power, energy storage, grid connection and the like in the park, so that comprehensive control of energy consumption of the park is realized, the energy utilization rate is improved, and no carbonization of the park is realized.
Specifically, the intelligent fire control carries out unified management on functions such as smoke alarm, fire early warning, fire water monitoring, escape guiding and the like of a park, a warehouse, realizes centralized management and control on fire control of the park and the warehouse through the Internet of things and a 5G means, and guarantees daily production environment safety of the park and the warehouse.
Fire safety monitoring obtains fire alarm data through an alarm output interface, and simultaneously monitors the water pressure state of a fire hydrant pipe network, the water pressure state of a spraying pipe network, the liquid level state of a fire water tank/pool and the like in real time, so that the interconnection of a fire protection system and a security protection system is realized.
The escape guiding is used for arranging a quick escape route for the personnel in the park according to the fire alarm position and the personnel positioning in the park, and guiding the personnel in the park to leave a dangerous area quickly through public broadcasting and information release panels in the park.
Specifically, environmental sanitation management and control is through sensing devices such as temperature, humidity, atmospheric pressure, quality of water, infrared temperature measurement in each key region in the garden, accomplishes the perception of the environmental condition in the key region and the contactless temperature measurement of people that come and go, realizes monitoring and epidemic prevention management and control to the garden environment. The cleaning and sterilizing robot equipped in the park is used for regularly completing daily cleaning, sterilizing and disinfecting work on the park.
Example two
Referring to fig. 2, the scheduling method of the present embodiment based on the power material digital employee cluster scheduling system according to the first embodiment includes:
step 1: the dispatching center issues a quality inspection instruction to the intelligent detection cluster, the intelligent detection cluster locks sampling inspection materials from electric materials to be put in storage according to a sampling inspection plan, automatically performs sampling, sample sealing and sample preparation tasks, and flexibly configures detection equipment according to the type of the electric materials to be inspected so as to realize full automation of the electric material quality and collaborative detection of a man-machine;
step 2: the dispatching center issues a warehousing instruction to the intelligent warehousing cluster, and the intelligent warehousing cluster automatically performs electric power material loading and unloading, picking, loading and unloading, checking and grouping operations on the electric power materials to be warehoused after quality inspection is completed;
step 3: the dispatching center sends a distribution instruction to the intelligent distribution cluster, the intelligent distribution cluster starts a depth vision recognition task for the electric power materials to be distributed when the electric power materials are delivered out of the warehouse, reads the distributed electric power material information and transmits the electric power material information to the dispatching center, and the dispatching center adopts an electric power material depth vision self-adaptive distribution method to intelligently match transport vehicles and form a self-adaptive distribution scheme so as to distribute the electric power materials to a preset destination.
In the implementation process of the step 3, the electric power material depth vision self-adaptive load method comprises the following steps:
step 3.1: identifying electric power material information and vehicle information to be distributed based on the depth vision identification task;
step 3.2: constructing a loading model for matching the electric power materials with the vehicle according to the electric power material information (such as the type, the size, the number and the like of the electric power materials) to be distributed and the vehicle information (such as the vehicle type, the carriage size and the like);
step 3.3: and based on the matching loading model of the electric power supplies and the vehicle, the loading strategy is adaptively generated with the maximum utilization space of the vehicle as the target.
In one or more embodiments, the scheduling method further includes:
and embedding a digital twin engine in the dispatching center, constructing a distribution operation digital model by using an electric power material panoramic digital twin method, mapping each scene of a distribution link, and loading operation actions of an intelligent distribution cluster and carrying material conditions.
In other embodiments, a warehouse panoramic digital twin scene is embedded in a dispatching center, and business information of each link of detection, storage and distribution is displayed by digital twin guiding into a subarea.
In some other embodiments, a digital twin engine is embedded in the dispatch center, with the detection zone digital model as a background, mapping the operational status of the detection device, the detection parameters, and the motion of the detection zone intelligent quality inspection clusters.
In other embodiments, a digital twin engine is embedded in the dispatch center, with the warehouse area digital model as a background, maps the digital model of the warehouse storage locations, and maps the operational and movement states of the intelligent warehouse clusters on the transportation and stations.
According to the embodiment, the concept of 'digital staff' is used for replacing 'human staff', seamless combination of power equipment detection, intelligent storage and active distribution is used as a main line, the technologies of 'large cloud object intelligent shift chain quantity', robot clusters, intelligent thing networking, digital twin and the like are applied, the material flow existing in the whole process of detection, storage and distribution is managed as an organic whole, an integrated power material digital staff cluster dispatching system is built, the system integrates 'detection, storage and distribution integrated efficient operation, intelligent collaboration of digital staff scenes, comprehensive multi-level intelligent thing networking of a park and digital operation capability building and improving' into a whole, storage operation automation, real-time management and control of an operation process and detection, storage and distribution integrated collaboration are realized, a bridge of real objects and information links is built while on-site operation efficiency is improved, information flow, real flow and control flow fusion are promoted, and further operation mode innovation of each link of detection, storage and distribution is promoted from the technical level, and operation mode innovation of each link of detection, and management level are promoted.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (16)
1. The electric power material digital employee cluster scheduling system is characterized by comprising a scheduling center, an intelligent detection cluster, an intelligent storage cluster and an intelligent distribution cluster;
the intelligent detection cluster is used for receiving quality inspection instructions issued by the dispatching center, locking sampling inspection materials from electric materials to be put in storage according to a sampling inspection plan, automatically executing sampling, sample sealing and sample preparation tasks, and flexibly configuring detection equipment according to the type of the electric materials to be inspected so as to realize full automation of the electric material quality and collaborative detection of people and machines;
the intelligent warehousing cluster is used for receiving warehousing instructions issued by the dispatching center and automatically executing electric power material loading and unloading, picking, loading and unloading, checking and grouping operations on the electric power materials to be warehoused after quality inspection is completed;
the intelligent distribution cluster is used for receiving distribution instructions issued by the dispatching center, starting a depth vision recognition task for the electric power materials to be distributed when the electric power materials are delivered out of the warehouse, reading the distributed electric power material information and transmitting the electric power material information to the dispatching center, and the dispatching center is used for intelligently matching with a transport vehicle and forming a self-adaptive distribution scheme so as to distribute the electric power materials to a preset destination.
2. A power supply digital employee cluster scheduling system as in claim 1, wherein the scheduling center is further configured to: constructing a matched loading model of the electric power supplies and the vehicle according to the distributed electric power supply information and the vehicle information; and then, a load strategy is adaptively generated by taking the maximum utilization space of the vehicle as a target.
3. The electric asset digital employee cluster scheduling system of claim 2, wherein the load strategy includes asset loading order and placement location information.
4. The electric power material digital employee cluster scheduling system of claim 1, wherein the scheduling center embeds a warehouse panoramic digital twin scene, and the service information of each link of detection, warehousing and distribution is displayed by digital twin guidance into a subarea.
5. A digital staff cluster scheduling system for electric materials as set forth in claim 1 wherein said scheduling center embeds digital twin engine mapping the operation status of the detection equipment, detection parameters and the movement of the detection area intelligent quality inspection clusters against the digital model of the detection area.
6. The power supply digital employee cluster scheduling system of claim 1, wherein the scheduling center embeds a digital twin engine mapping the digital model of warehouse storage against the warehouse digital model, and maps the operational and movement status of the intelligent warehouse clusters on transportation and stations.
7. The electric power material digital employee cluster scheduling system of claim 1, wherein the scheduling center is embedded with a digital twin engine, and the scheduling center maps each scene of the distribution link with the distribution operation digital model as a background, loads the operation action of the intelligent distribution cluster and the condition of carrying the material and displays the operation action and the condition.
8. The electric materials digital employee cluster scheduling system of claim 1, wherein the intelligent detection cluster is further configured to record the whole process of quality inspection of the spot check materials and upload the detection result to the scheduling center for storage by using a blockchain.
9. The power supply digital employee cluster scheduling system of claim 1, wherein the intelligent warehouse cluster is configured to perform warehouse entry management on power supplies on a first-in-first-out basis;
or (b)
The intelligent warehouse cluster is used for carrying out warehouse-out management on electric power materials according to the principle of billing before material;
or (b)
The intelligent warehouse cluster is used for: and unloading the electric power materials to a temporary storage area or a conveying line, and checking the electric power materials.
10. The power supply digital employee cluster scheduling system of claim 1, wherein the scheduling center is further configured to receive bin information and schedule the intelligent warehouse cluster to finish loading the goods and materials, receive a loading operation feedback result, and generate a warehouse entry order.
11. The power supply digital employee cluster scheduling system of claim 1, wherein the scheduling center is further configured to generate a delivery bill, supply and bin related information, and schedule the intelligent warehouse cluster to complete the delivery operation of the power supply.
12. A power supply digital employee cluster scheduling system as in claim 1, wherein the intelligent distribution cluster is further configured to initiate a full-process monitoring power supply on-the-fly task to ensure that the overall process of transportation is safe and controllable.
13. The power supply digital employee cluster scheduling system of claim 1, wherein the scheduling center is further coupled to a smart campus cluster for receiving instructions associated with the scheduling center based on the digital twins model for performing smart transportation, smart security, smart resources, smart fire and environmental sanitation management tasks.
14. A scheduling method based on a power supply digital employee cluster scheduling system according to any one of claims 1-13, comprising:
the dispatching center issues a quality inspection instruction to the intelligent detection cluster, the intelligent detection cluster locks sampling inspection materials from electric materials to be put in storage according to a sampling inspection plan, automatically performs sampling, sample sealing and sample preparation tasks, and flexibly configures detection equipment according to the type of the electric materials to be inspected so as to realize full automation of the electric material quality and collaborative detection of a man-machine;
the dispatching center issues a warehousing instruction to the intelligent warehousing cluster, and the intelligent warehousing cluster automatically performs electric power material loading and unloading, picking, loading and unloading, checking and grouping operations on the electric power materials to be warehoused after quality inspection is completed; the dispatching center sends a distribution instruction to the intelligent distribution cluster, the intelligent distribution cluster starts a depth vision recognition task for the electric power materials to be distributed when the electric power materials are delivered out of the warehouse, reads the distributed electric power material information and transmits the electric power material information to the dispatching center, and the dispatching center adopts an electric power material depth vision self-adaptive distribution method to intelligently match transport vehicles and form a self-adaptive distribution scheme so as to distribute the electric power materials to a preset destination.
15. The scheduling method of claim 14, wherein the power asset depth vision adaptive load method comprises:
identifying electric power material information and vehicle information to be distributed based on the depth vision identification task;
according to the electric power material information and the vehicle information to be distributed, constructing a matched loading model of the electric power material and the vehicle;
and based on the matching loading model of the electric power supplies and the vehicle, the loading strategy is adaptively generated with the maximum utilization space of the vehicle as the target.
16. The scheduling method of claim 14, wherein the scheduling method further comprises:
embedding a digital twin engine in a dispatching center, constructing a distribution operation digital model by using an electric power material panoramic digital twin method, mapping each scene of a distribution link, and loading operation actions of an intelligent distribution cluster and carrying material conditions;
or embedding a warehouse panoramic digital twin scene in the dispatching center, leading the scene into a subarea through digital twin guidance, and displaying service information of each link of detection, storage and distribution;
or a digital twin engine is embedded in the dispatching center, and the operation state, the detection parameters and the movement condition of the intelligent quality inspection cluster of the detection area are mapped by taking the digital model of the detection area as a background;
or a digital twin engine is embedded in the dispatching center, a digital model of a warehouse storage position is mapped by taking a warehouse area digital model as a background, and the operation state and the motion state of the intelligent warehouse cluster are mapped on transportation and stations.
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