Novel digital positioning and intelligent scheduling management method and device for mine material vehicle

Abstract

The application discloses a novel mine material vehicle digital positioning and intelligent scheduling management method and device, relates to the technical field of intelligent scheduling of mine vehicles, and specifically discloses the following technical scheme: through a mobile terminal, a vehicle code acquisition instruction is scanned, material or unloading information is input, three-dimensional binding data is generated and is uploaded in real time; a fusion positioning method is used to acquire the position of a vehicle in a mine, and a multi-dimensional feature system is constructed in combination with the binding data; according to the features and dynamic constraints, a multi-objective optimization algorithm is used to calculate a supply and recovery path, and an optimal scheduling scheme is generated; the scheme is introduced into digital twin verification, is corrected, is issued to a terminal and is used to update the state of the vehicle, and a closed-loop traceability is realized. The application can realize high-precision positioning of a vehicle in a mine and full-process traceability, improve information accuracy and timeliness, reduce the empty running rate and transportation cost through dynamic scheduling and twin pre-control, and improve scheduling response speed and operation safety.

Description

Technical Field

[0001] This invention relates to the field of intelligent dispatching technology for mining vehicles, and in particular to a novel digital positioning and intelligent dispatching management method and device for mining material vehicles. Background Technology

[0002] Coal, as a core guarantee of national energy security, relies heavily on its underground transportation system, considered the "lifeblood" of mine production and directly determining overall production efficiency. With the deepening of intelligent transformation in mines, related technologies, through collaborative operations of positioning perception, data interaction, and scheduling decisions, have constructed a comprehensive management system covering material binding, trajectory tracking, and path planning. Specifically, this system relies on RFID or a single communication network to achieve closed-loop control from surface loading to underground unloading, a key link in improving mine logistics efficiency.

[0003] However, existing technical solutions, which directly employ a single GPS or fixed barcode scanning terminal, fail to address challenges such as signal obstruction and low recognition rates caused by high dust levels and strong multipath effects underground. This can lead to significant delays in synchronizing vehicle and material binding information, a lack of dynamic optimization mechanisms for empty vehicle scheduling, or broken tracking of special materials and waste recovery trajectories. The lack of multi-source data fusion and environmental adaptability not only results in high empty-running rates and uncontrolled transportation costs but also makes it difficult to meet the mandatory requirements of the "Coal Mine Safety Regulations" for accurate traceability of hazardous materials throughout the entire process, severely hindering the improvement of inherent safety levels in mines. Summary of the Invention

[0004] The main objective of this invention is to provide a novel method for digital positioning and intelligent scheduling management of mining material vehicles.

[0005] Another objective of this invention is to propose a novel digital positioning and intelligent scheduling management device for mining material vehicles.

[0006] The third objective of this invention is to provide an electronic device.

[0007] The fourth objective of this invention is to provide a non-transitory computer-readable storage medium.

[0008] To achieve the above objectives, a first aspect of the present invention proposes a novel digital positioning and intelligent scheduling management method for mining material vehicles, comprising:

[0009] S1: Obtain binding instructions by scanning the vehicle identification code through a mobile terminal, enter material information or unloading information, generate three-dimensional binding data containing vehicle status, material attributes and location information and upload it in real time. S2, based on fusion positioning technology, obtains real-time location data of vehicles in the mine, and combines it with three-dimensional binding data to construct a multi-dimensional feature system covering vehicle distribution, waste accumulation and environmental safety parameters; S3, based on the multi-dimensional feature system and downhole dynamic constraints, calculates the nearest supply path for empty cars and the waste recycling path through a multi-objective optimization algorithm, and generates the optimal scheduling scheme that includes transportation routes and scheduling instructions. S4 maps the optimal scheduling scheme to a digital twin model for feasibility verification, corrects the scheduling instructions based on the verification results and sends them to the mobile terminal, while updating the vehicle operation status to achieve closed-loop traceability of the entire process.

[0010] Optionally, the binding instruction can be obtained by scanning the vehicle identification code with a mobile terminal, material information or unloading information can be entered, and three-dimensional binding data containing vehicle status, material attributes and location information can be generated and uploaded in real time, including: Ground staff use the smart dispatch sub-app on their smart explosion-proof mobile phones to scan a pre-set fixed QR code label to obtain the vehicle's unique identifier, triggering the binding interface and entering the material name, specifications, quantity, destination, and responsible person information. After confirmation, the loading binding data is uploaded in real time via a 5G link, with a synchronization delay of less than or equal to 5 seconds and a binding accuracy rate of greater than or equal to 99.9%. During the unloading process, underground workers scan the same preset fixed QR code label using the smart dispatch sub-App on their deployed smart explosion-proof mobile phones. This triggers the data entry interface, allowing them to fill in the actual unloading quantity, time, location, and acceptance personnel information. The unloading data is then uploaded via a 5G and LoRa dual-mode link, and the vehicle status is automatically updated to empty. The data entry delay is less than or equal to 8 seconds, and the error rate is less than or equal to 0.1%. When a vehicle finishes unloading but is not recorded in time, staff manually mark the empty vehicle status using the smart dispatch sub-app on the smart explosion-proof mobile phone, and upload the waste type, loading amount and recycling destination information after the waste recycling vehicle is loaded to generate an environmental traceability ledger.

[0011] Optionally, real-time vehicle location data underground can be obtained based on fusion positioning technology, and combined with 3D binding data to construct a multi-dimensional feature system covering vehicle distribution, waste accumulation, and environmental safety parameters, including: The 5G positioning unit performs coarse positioning operations with an accuracy of 5 to 10 meters throughout the entire mine to obtain global vehicle position perception data. At the same time, the UWB positioning unit, which integrates a roadway multipath interference suppression algorithm, performs precise positioning operations with a static accuracy of less than or equal to 0.8 meters and a dynamic accuracy of less than or equal to 2.5 meters in key areas such as roadways, loading and unloading points, and waste accumulation points to obtain precise local vehicle position data. The main control chip is used to perform weighted average fusion processing on the coarse positioning data output by the 5G positioning unit and the precise positioning data output by the UWB positioning unit. The weight of UWB data is set to 0.7 and the weight of 5G data is set to 0.3. The final positioning result with an effectiveness of greater than or equal to 99.5% is output, and the positioning update frequency of empty vehicle and waste recycling vehicle is set to once every 5 seconds. The final positioning results are spatiotemporally aligned with the three-dimensional binding data to construct a six-dimensional feature system that includes binding status, unloading completion rate, empty car location, waste accumulation, gas concentration change, and mine pressure impact cycle, which is used to support subsequent scheduling decisions.

[0012] Optionally, based on the multi-dimensional feature system and downhole dynamic constraints, a multi-objective optimization algorithm is used to calculate the nearest supply path for empty vehicles and the waste recovery path, generating an optimal scheduling scheme that includes transportation routes and scheduling instructions, including: Constructing a multi-objective optimization function based on a particle swarm genetic hybrid algorithm:

[0013] in, For the decision variable vector, For safety weights, Safety compliance indicator functions For efficiency weighting, System operating efficiency index function As a cost weight, This is a function representing the system operating cost index. For environmental protection weight, For environmental compliance indicator functions; The specific formula for calculating safety compliance indicators is as follows:

[0014] in, The gas exceedance coefficient, For leakage current safety protection factor, The gas concentration penalty coefficient, The upper limit threshold for safe gas concentration. This is the upper limit threshold for the safe leakage current. The specific formula for calculating the transportation efficiency index is as follows:

[0015] in, For standard transportation time, This refers to the actual transportation time. This is a time efficiency weighting coefficient. For rated load, This refers to empty cargo volume; The specific formula for calculating transportation cost indicators is as follows:

[0016] in, The actual cost of electricity consumption. For additional costs, This is the rated budget cost; The specific formula for calculating environmental compliance indicators is as follows:

[0017] in, For the safe recycling and storage of waste, To allow the maximum emission duration, For the amount of resources recovered, The total amount of recyclable resources; Introducing an adaptive factor for mining pressure constraints:

[0018] in, For real-time mining pressure, set The maximum allowable mining pressure threshold; Through population initialization, fitness calculation, particle velocity and position update, crossover mutation, and iteration termination steps, the fitness is optimized after 25 to 30 iterations or when the fitness error is less than [value missing]. Output the optimal scheduling scheme in real time.

[0019] Optionally, the optimal scheduling scheme is mapped to a digital twin model for feasibility verification. Based on the verification results, the scheduling instructions are revised and sent to the mobile terminal, while the vehicle operating status is updated to achieve closed-loop traceability throughout the entire process, including: A digital twin model was constructed using the Unity3D engine and Surpac geological modeling software. A four-source fusion modeling formula was used to integrate geological data, real-time monitoring data, mobile interaction data, and waste recycling data to generate a virtual mine environment. The specific formula is as follows:

[0020] in, For geological data, To monitor data in real time, For mobile interactive data, Data on waste recycling; The optimal scheduling scheme is mapped to the virtual mine environment for virtual-real linkage control simulation. If a collision risk or path blockage is detected, a correction command is automatically fed back. The correction response time is less than or equal to 10 seconds, which improves the scheduling accuracy by 25%. Predicting roof deformation risk using roof displacement prediction formula:

[0021] in, This represents the initial displacement of the top plate. This is the displacement proportionality coefficient. This is the real-time mine pressure value. The time power exponent, The dip angle of the rock strata.

[0022] To achieve the above objectives, a second aspect of the present invention provides a novel digital positioning and intelligent scheduling management device for mining material vehicles, comprising: The binding module is used to obtain binding instructions by scanning the vehicle identification code through a mobile terminal, enter material information or unloading information, generate three-dimensional binding data containing vehicle status, material attributes and location information and upload it in real time. The module is used to acquire real-time location data of vehicles in the mine based on fusion positioning technology, and combine it with 3D binding data to build a multi-dimensional feature system covering vehicle distribution, waste accumulation and environmental safety parameters. The calculation module is used to calculate the nearest supply path for empty cars and the waste recycling path based on the multi-dimensional feature system and the dynamic constraints in the well, and to generate the optimal scheduling scheme that includes transportation routes and scheduling instructions. The adjustment module is used to map the optimal scheduling scheme to the digital twin model for feasibility verification, correct the scheduling instructions based on the verification results and send them to the mobile terminal, and update the vehicle operation status to achieve full-process closed-loop traceability.

[0023] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0024] To achieve the above objectives, a third aspect of this application provides an electronic device, including a processor and a memory; wherein the processor reads executable program code stored in the memory to run a program corresponding to the executable program code, so as to implement the novel digital positioning and intelligent scheduling management method for mining material vehicles as described in the first aspect embodiment.

[0025] To achieve the above objectives, the fourth aspect of this application proposes a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the novel digital positioning and intelligent scheduling management method for mining material vehicles as described in the first aspect embodiment.

[0026] The embodiments of the present invention have the following beneficial effects: This invention enables high-precision positioning and closed-loop traceability of underground material vehicles, significantly improving the accuracy and timeliness of vehicle-material binding and information entry; through multi-objective dynamic optimization scheduling and digital twin pre-control, it effectively reduces empty running rate and transportation costs, and improves scheduling response speed and mine operation safety. Attached Figure Description

[0027] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 A flowchart illustrating a novel digital positioning and intelligent scheduling management method for mining material vehicles provided in this embodiment of the invention; Figure 2 A framework diagram of a novel digital positioning and intelligent dispatch management system for mining material vehicles provided in an embodiment of the present invention; Figure 3 This is a simulation interface diagram of the digital twin fusion subsystem of the present invention; Figure 4 This is the algorithm logic diagram of the AI ​​scheduling subsystem of the present invention; Figure 5 This is a circuit diagram of the digital positioning system for the mining truck of the present invention; Figure 6 This is a circuit diagram of the intelligent scheduling system of the present invention; Figure 7 This is a structural diagram of a novel digital positioning and intelligent scheduling management device for mining material vehicles provided in an embodiment of the present invention. Detailed Implementation

[0028] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0029] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0030] The following description, with reference to the accompanying drawings, describes a novel digital positioning and intelligent scheduling management method and apparatus for mining material vehicles according to embodiments of the present invention.

[0031] Example 1 This invention provides a novel digital positioning and intelligent scheduling management method for mining material vehicles, such as... Figure 1As shown, the method includes the following steps: S1 obtains binding instructions by scanning the vehicle identification code through a mobile terminal, enters material information or unloading information, generates three-dimensional binding data containing vehicle status, material attributes and location information and uploads it in real time.

[0032] To achieve accurate binding, efficient entry, and safe traceability of vehicle and material information, this application establishes a mobile interactive subsystem that enables registration and data uploading via an explosion-proof mobile app, and connects to a multi-device collaborative interface to ensure stable and reliable transmission.

[0033] The overall operation mode of this application is based on the shared vehicle dispatch model. After scanning the vehicle's QR code with an explosion-proof mobile app, staff can view the real-time vehicle status information of each underground yard on the digital twin scenario interface. They can also select and execute operations such as loading information entry, unloading information entry, empty vehicle demand application, and material demand application through the function menu. After the relevant demand data is uploaded to the dispatch center, the system performs intelligent overall calculation, and then issues material loading lists and vehicle dispatch instructions, while simultaneously completing operational data analysis and cost statistics.

[0034] In this embodiment, this step is mainly implemented by the mobile interaction subsystem. As the core innovative unit of the entire intelligent dispatch management system, the mobile interaction subsystem is the key interactive carrier for realizing the digital positioning and intelligent dispatch of mining material vehicles. With the already deployed intelligent explosion-proof mobile terminal intelligent dispatch sub-App as the core, a mobile and precise data interaction channel adapted to the complex working conditions underground is built to ensure the efficient transmission and accurate correlation of core data such as vehicles, materials, and locations.

[0035] This application achieves real-time recording and uploading of material loading, unloading, and empty vehicle status by binding the material vehicle's location information with the vehicle's QR code. The system uses a mining explosion-proof smartphone dispatch management app as the terminal interaction platform for data entry, viewing material demand lists, and receiving special vehicle dispatch instructions; at the same time, it relies on the coal mine dispatch center server platform system for unified management, realizing the functions of material list generation, material consumption statistics, and performance statistics.

[0036] In this embodiment, to ensure the unique identification and traceability of each mining material vehicle and waste recycling vehicle, each vehicle is equipped with a unique PET QR code label as a preset fixed QR code. This QR code label is processed with a special process and has a 50μm polycarbonate protective film on its surface. It not only has excellent dust-proof performance, but can also withstand high and low temperature environments of -40℃ to 85℃, and can adapt to the harsh working conditions of large temperature difference and high dust in the mine. The label is stably affixed to a conspicuous and wear-resistant position on the vehicle, which facilitates quick scanning operation by ground and underground personnel, while avoiding damage to the label due to friction and collision during vehicle operation, thus ensuring the stability of identification.

[0037] In this embodiment, during the loading process, ground staff can quickly obtain the vehicle's unique identifier by scanning the preset fixed QR code label using the deployed intelligent explosion-proof mobile app. The system automatically triggers the binding interface, where staff accurately enter key information such as material name, specifications, quantity, destination, and responsible person. After confirmation, the relevant information is uploaded to the system backend in real time via the underground 5G link, forming complete loading binding data. This application optimizes the data transmission protocol to ensure that the synchronization delay of this process is less than or equal to 5 seconds, and the binding accuracy is greater than or equal to 99.9%, effectively avoiding scheduling chaos caused by data delays and binding errors. Simultaneously, this application supports each team to upload the required material list in real time via the underground explosion-proof mobile app. The system analyzes and processes the uploaded data, automatically generating a detailed material consumption ledger for each team.

[0038] In this embodiment, during the unloading process, underground workers scan the same preset fixed QR code label using the same deployed smart explosion-proof mobile terminal intelligent dispatch sub-App. The system automatically triggers the unloading information input interface, where workers supplement and input information such as the actual unloading quantity, unloading time, unloading location, and acceptance personnel. Considering that the 5G signal is weak in some areas underground, this application uses a 5G and LoRa dual-mode link to complete the unloading data upload. The underground prioritizes the use of the LoRa link to ensure data transmission and ensure the stability of data upload. After the data upload is completed, the system automatically updates the vehicle status to empty vehicle status, which facilitates subsequent empty vehicle dispatch. The delay of this input process is less than or equal to 8 seconds, and the error rate is less than or equal to 0.1%, minimizing the impact of manual input errors on dispatch efficiency.

[0039] In this embodiment, to address the special situation where vehicles have completed unloading but relevant information has not been entered in a timely manner, this application includes a manual marking function for empty vehicle status. Workers can manually mark vehicles as empty via a smart explosion-proof mobile app, ensuring timely updates to empty vehicle information, guaranteeing the timeliness of empty vehicle dispatch, and avoiding problems such as idle empty vehicles and untimely dispatch due to information lag. Simultaneously, for waste recycling vehicles, after loading, workers scan the corresponding preset fixed QR code label on the vehicle using the app, entering information such as waste type, loading volume, and recycling destination. The system automatically generates an environmental traceability ledger, achieving full traceability of the waste recycling process and meeting underground environmental management requirements.

[0040] For the recycling of oil-based hazardous chemical waste, the system establishes a separate electronic ledger for trajectory tracking, which can completely record the information of the entire process of hazardous chemical materials from loading and transportation to recycling and disposal, in accordance with the relevant requirements of the new "Coal Mine Safety Regulations" regarding environmental protection and safety management.

[0041] In this embodiment of the application, considering the security and confidentiality of downhole data, all interactive data in this application adopts AES-256 encryption transmission method to effectively prevent data from being stolen or tampered with during transmission. The encrypted data is stored in a distributed database to realize closed-loop traceability of the entire process of binding, unloading, empty vehicle status and waste recycling. The traceability rate of special materials and waste transportation trajectories reaches 100%, and relevant data can be retrieved at any time for verification, ensuring the standardization and traceability of scheduling management.

[0042] Meanwhile, in this embodiment, to further enhance the system's synergy and coverage, a multi-device collaboration interface is configured. This interface can achieve efficient data collaboration with the mining humanoid safety management robot. The communication protocol adopts Modbus TCP / IP, and the data interaction format is JSON, ensuring the compatibility and stability of data interaction. It can effectively integrate ground three-dimensional perception data to achieve coverage of more than 98% of key areas underground. For areas with weak signals underground, the LoRa link ensures a stable data transmission rate of greater than or equal to 10Mbps, effectively solving the problems of data transmission interruption and delay caused by unstable signals underground, and further ensuring the stability and reliability of three-dimensional binding data upload.

[0043] In this embodiment of the application, the mobile interaction subsystem and multi-device collaborative interface enable accurate binding, secure uploading, and full-process closed-loop traceability of vehicle material information, laying the foundation for the subsequent construction of a multi-dimensional feature system.

[0044] S2 uses fusion positioning technology to obtain real-time location data of vehicles in the mine, and combines it with three-dimensional binding data to construct a multi-dimensional feature system covering vehicle distribution, waste accumulation and environmental safety parameters.

[0045] In order to obtain the accurate real-time location of underground vehicles and construct a multi-dimensional scheduling feature system, this application adopts a 5G and UWB integrated positioning scheme, and provides an environmental adaptation unit to ensure stable and reliable positioning.

[0046] In this embodiment of the application, this step is implemented through a positioning sensing unit, such as... Figure 5 The diagram shown is a digital positioning circuit diagram of the mining truck in this application. This unit adopts a 5G and UWB integrated positioning solution, which can provide stable and reliable accurate position support for material transportation, empty vehicle scheduling and waste recycling without switching.

[0047] In this embodiment, the 5G positioning unit utilizes the 5G network deployed underground to achieve coarse positioning with an accuracy of 5 to 10 meters across the entire mine. This enables rapid acquisition of global vehicle location perception data, meeting the system's real-time monitoring requirements for the overall vehicle distribution. In this embodiment, the UWB positioning unit integrates a roadway multipath interference suppression algorithm, effectively mitigating signal interference from the complex underground roadway environment. This allows for precise positioning in key operational areas such as roadways, loading / unloading points, and waste accumulation points, achieving static accuracy of less than or equal to 0.8 meters and dynamic accuracy of less than or equal to 2.5 meters. This provides accurate local vehicle location data, ensuring accurate vehicle location identification during critical processes such as loading / unloading and recycling.

[0048] In this embodiment, the system uses a main control chip to perform weighted average fusion processing on the coarse positioning data output by the 5G positioning unit and the precise positioning data output by the UWB positioning unit. The weight of UWB data is set to 0.7 and the weight of 5G data is set to 0.3, giving full play to the advantages of UWB's high precision and 5G's wide coverage. The final output has an effectiveness rate of greater than or equal to 99.5%. At the same time, the positioning update frequency of empty vehicles and waste recycling vehicles is set to once every 5 seconds to ensure that the location data is refreshed in real time and to provide timely location information for scheduling decisions.

[0049] After completing the acquisition of positioning data, this application performs spatiotemporal alignment processing on the final positioning results and the three-dimensional binding data generated by S1 to construct a six-dimensional feature system that includes binding status, unloading completion rate, empty vehicle location, waste accumulation amount, gas concentration change and mine pressure impact cycle. This system comprehensively integrates multi-dimensional information such as vehicles, materials and environment, providing comprehensive and reliable data support for subsequent intelligent scheduling calculations.

[0050] Furthermore, in this embodiment, the system is equipped with an environmental adaptation unit. The core equipment uses an Ex d I Ma-level explosion-proof enclosure, and the already deployed explosion-proof smartphones meet the Ex ib I Mb-level explosion-proof standard. Both meet the requirements of GB 3836.1-2021 standard and can operate safely and stably in flammable and explosive underground environments with a gas concentration of less than or equal to 1.2% VOL. The equipment enclosure adopts an IP68 protection rating design, with a 50μm graphene-modified polytetrafluoroethylene composite coating on the surface. Combined with a double-lip seal and pressure relief valve structure, it has excellent waterproof, oil-resistant, and dust-resistant properties, and can adapt to harsh underground working conditions. At the same time, the system adopts an anti-static design, controlling the surface resistance of the core equipment to within 10 ohms. 6 -10 8 The Ω smart explosion-proof mobile phone screen uses anti-static tempered glass, which can effectively reduce dust adhesion and signal attenuation, further ensuring the continuity and stability of positioning data collection.

[0051] In this embodiment, the precise location of the vehicle is obtained and a six-dimensional feature system is constructed through the 5G and UWB fusion positioning and environment adaptation unit, laying the foundation for obtaining the optimal scheduling scheme of transportation routes and scheduling instructions.

[0052] S3, based on the multi-dimensional feature system and downhole dynamic constraints, calculates the nearest supply path for empty cars and the waste recycling path through a multi-objective optimization algorithm, and generates the optimal scheduling scheme that includes transportation routes and scheduling instructions.

[0053] In order to balance safety, efficiency, cost and environmental protection and avoid underground risks, this application generates the optimal vehicle scheduling scheme through an AI scheduling subsystem and a hybrid algorithm.

[0054] In this embodiment of the application, this step is performed by the AI ​​scheduling subsystem, such as... Figure 4 The diagram shows the algorithm logic of the AI ​​scheduling subsystem of this application. The system completes model training based on 15,000 pieces of underground working condition data. It can respond in real time to various data information uploaded by the mobile interaction subsystem, and construct a multi-objective optimization function adapted to complex underground working conditions by combining particle swarm genetic hybrid algorithm, so as to realize intelligent optimization calculation of empty car supply and waste recycling paths.

[0055] In this embodiment of the application, the multi-objective optimization function is defined as follows:

[0056] in, For the decision variable vector, For safety weighting, a value of 0.35 is used. Safety compliance indicator functions As an efficiency weight, it takes a value of 0.25. System operating efficiency index function As a cost weight, it takes a value of 0.2. This is a function representing the system operating cost index. For environmental protection weight, This is a function for environmental compliance indicators.

[0057] The safety compliance indicator function is:

[0058] in, The gas over-limit penalty coefficient is set to 0.6. The leakage current safety protection factor is set to 0.4. The gas concentration penalty coefficient, The safe upper limit threshold for gas concentration is set at 0.8% VOL. The upper limit threshold for leakage current is set at 30mA. The safety compliance index is used to comprehensively evaluate the downhole safety adaptability of the scheduling path.

[0059] The transportation efficiency index function is:

[0060] in, For standard transportation time, This refers to the actual transportation time. The time efficiency weighting coefficient is set to 0.5. For rated load, For empty transport volume, transport efficiency indicators are used to quantify the transport timeliness and load utilization efficiency of scheduling schemes.

[0061] The transportation cost indicator function is:

[0062] in, The actual cost of electricity consumption. For additional costs, As the rated budget cost, the transportation cost indicator is used to measure the level of operational cost control during the scheduling process.

[0063] The environmental compliance indicator function is as follows:

[0064] in, For the safe recycling and storage of waste, The maximum allowable emission duration is set at 24 hours. For the amount of resources recovered, The total amount of recyclable resources is used as an environmental compliance indicator to achieve a standardized evaluation of waste discharge and recycling.

[0065] In this embodiment of the application, to further improve the security of the scheduling scheme, an adaptive factor for mining pressure constraints is introduced:

[0066] in, For real-time mining pressure, set To allow the maximum mine pressure threshold, 30 MPa is selected. This factor is used to dynamically adjust the route planning, effectively avoiding the scheduling route from crossing areas with high mine pressure risk.

[0067] In this embodiment, the algorithm execution flow is as follows: population initialization, fitness calculation, particle velocity and position update, crossover and mutation, and iteration termination. When the number of iterations reaches 25 to 30, or the fitness error is less than 10^(-4), the system terminates the iteration and outputs the optimal scheduling scheme. This AI scheduling subsystem can automatically trigger a recalculation of the scheduling scheme after receiving new operating data. The recalculation time is less than or equal to 3.5 minutes. Based on the previously constructed six-dimensional feature system, the scheduling matching degree is improved by 30%, and vehicle allocation is optimized through the logic of supplying empty vehicles nearby, reducing the vehicle empty-running rate to below 12%.

[0068] In this embodiment, the system generates a scheduling plan in less than or equal to 5 minutes. Compared with existing technologies, the scheduling time is reduced by 30%, the cost saving rate is increased by 8%, the timeliness rate of emergency material transportation is greater than or equal to 98%, and the compliance rate of waste recycling reaches 100%. Figure 6 The circuit diagram shown is of the intelligent scheduling system of this application. This circuit can stably support algorithm operation and scheduling instruction output, providing hardware guarantee for the efficient execution of multi-objective optimization calculation.

[0069] In this embodiment, an optimal scheduling scheme is generated by combining an AI scheduling subsystem with a hybrid algorithm and a multi-objective optimization function, thereby improving scheduling efficiency and ensuring the safety and compliance of underground transportation.

[0070] In this embodiment, an optimal scheduling scheme is generated by combining an AI scheduling subsystem with a hybrid algorithm and a multi-objective optimization function, thereby improving scheduling efficiency and laying the foundation for subsequent full-process closed-loop traceability.

[0071] S4 maps the optimal scheduling scheme to a digital twin model for feasibility verification, corrects the scheduling instructions based on the verification results and sends them to the mobile terminal, while updating the vehicle operation status to achieve closed-loop traceability of the entire process.

[0072] To verify the feasibility of the scheduling scheme and provide early warning of downhole risks, this application establishes a digital twin fusion subsystem to achieve simulation verification and full-process closed-loop traceability.

[0073] In this embodiment of the application, this step is completed through a digital twin fusion subsystem, such as... Figure 3 The diagram shows the simulation interface of the digital twin fusion subsystem of this application. The digital twin model is mainly used to view the real-time operating status of vehicles in each depot and to realize safety monitoring of the underground transportation process. This subsystem is built based on the Unity3D engine and Surpac geological modeling software, and can realize underground working condition mapping, safety hazard pre-control, and emergency dispatch optimization, providing a reliable virtual simulation environment for the feasibility verification of the dispatch scheme of this application.

[0074] In this embodiment, a four-source fusion modeling formula is used to weightedly fuse geological data, real-time monitoring data, mobile interaction data, and waste recycling data to construct a virtual mine environment that closely resembles actual working conditions. The specific formula is as follows:

[0075] in, For geological data, To monitor data in real time, For mobile interactive data, This modeling method provides data for waste recycling. It achieves a modeling accuracy of 0.1m, with mapping errors controlled within 2%. It also supports 2K resolution VR display, a rendering frame rate of no less than 30fps, and a field of view of no less than 100°. In the VR interface, it can clearly display the vehicle binding status, empty vehicle distribution, waste accumulation point location, and the running trajectory of the waste recycling vehicle in real time.

[0076] In this embodiment, the optimal scheduling scheme generated by S3 is mapped to the constructed virtual mine environment to carry out virtual-real linkage control simulation. If vehicle collision risk or roadway blockage is detected during the simulation, the system will automatically send a correction instruction to the AI ​​scheduling subsystem. The correction response time is no more than 10 seconds, which can effectively improve the scheduling accuracy by 25%.

[0077] In this embodiment, the application also uses a roof displacement prediction formula to accurately predict the risk of roof deformation in the well. The specific formula is as follows:

[0078] in, This represents the initial displacement of the top plate, taken as 0.2 mm. This is the displacement proportionality coefficient, with a value of 0.05 mm / (MPa). h^a), This is the real-time mine pressure value. The time power exponent, The dip angle of the rock strata is given. The system sets the early warning threshold to be u(t) greater than 1.5 mm or displacement rate greater than 0.1 mm / h. The early warning accuracy of this prediction method is no less than 99.5%, and it can provide early warning of roof collapse risk 72 to 76 hours in advance.

[0079] In this embodiment, the system is also equipped with an emergency simulation model, which can simulate typical underground accidents such as fire spread and water inrush. Based on the simulation results, it outputs the optimal personnel evacuation route and equipment shutdown sequence, and pushes emergency notifications to underground workers through a smart explosion-proof mobile app, which can improve the data collection efficiency in emergency scenarios by more than 30%.

[0080] In this embodiment, after verifying the feasibility of the scheduling scheme and correcting the scheduling instructions, the system sends the finalized scheduling instructions to the mobile terminal, and simultaneously updates the vehicle's operating status. Combined with the binding data, location data, and scheduling data from S1 to S3, a complete closed-loop traceability system is formed. Figure 1 The flowchart shown is a process flow of a novel digital positioning and intelligent scheduling management method for mining material vehicles provided in an embodiment of this application. The flowchart fully presents the entire process logic from data acquisition, positioning fusion, intelligent scheduling to digital twin verification, ensuring that the entire transportation and scheduling management process of mining material vehicles is safe, efficient, and fully traceable.

[0081] In this embodiment, the scheduling scheme simulation verification and risk warning are completed through the digital twin fusion subsystem, realizing closed-loop traceability and improving the safety and scheduling accuracy of underground transportation.

[0082] Example 2 This invention provides a novel digital positioning and intelligent scheduling management device 10 for mining material vehicles, such as... Figure 7 As shown, the device includes: The binding module 100 is used to obtain binding instructions by scanning the vehicle identification code through a mobile terminal, enter material information or unloading information, generate three-dimensional binding data containing vehicle status, material attributes and location information and upload it in real time. Module 200 is used to acquire real-time location data of vehicles in the mine based on fusion positioning technology, and to build a multi-dimensional feature system covering vehicle distribution, waste accumulation and environmental safety parameters by combining three-dimensional binding data. The calculation module 300 is used to calculate the nearest supply path for empty cars and the waste recycling path through a multi-objective optimization algorithm based on the multi-dimensional feature system and the dynamic constraints in the well, and to generate the optimal scheduling scheme that includes the transportation route and scheduling instructions. The adjustment module 400 is used to map the optimal scheduling scheme to the digital twin model for feasibility verification, correct the scheduling instructions based on the verification results and send them to the mobile terminal, and update the vehicle operation status to achieve full-process closed-loop traceability.

[0083] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0084] Example 3 To implement the methods of the above embodiments, the present invention also provides an electronic device, which includes a memory and a processor; wherein the processor reads executable program code stored in the memory to run a program corresponding to the executable program code, so as to implement the various steps of the methods described above.

[0085] Example 4 To implement the above embodiments, this application also proposes a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method described in the foregoing embodiments.

[0086] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0087] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0088] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

Claims

1. A novel digital positioning and intelligent scheduling management method for mining material vehicles, characterized in that, include: S1: Obtain binding instructions by scanning the vehicle identification code through a mobile terminal, enter material information or unloading information, generate three-dimensional binding data containing vehicle status, material attributes and location information and upload it in real time. S2, based on fusion positioning technology, obtains real-time location data of vehicles in the mine, and combines it with three-dimensional binding data to construct a multi-dimensional feature system covering vehicle distribution, waste accumulation and environmental safety parameters; S3, based on the multi-dimensional feature system and downhole dynamic constraints, calculates the nearest supply path for empty cars and the waste recycling path through a multi-objective optimization algorithm, and generates the optimal scheduling scheme that includes transportation routes and scheduling instructions. S4 maps the optimal scheduling scheme to a digital twin model for feasibility verification, corrects the scheduling instructions based on the verification results and sends them to the mobile terminal, while updating the vehicle operation status to achieve closed-loop traceability of the entire process.

2. The method according to claim 1, characterized in that, The process of obtaining binding instructions by scanning vehicle identification codes with a mobile terminal, entering material information or unloading information, generating three-dimensional binding data containing vehicle status, material attributes, and location information, and uploading it in real time includes: Ground staff use the smart dispatch sub-app on their smart explosion-proof mobile phones to scan a pre-set fixed QR code label to obtain the vehicle's unique identifier, triggering the binding interface and entering the material name, specifications, quantity, destination, and responsible person information. After confirmation, the loading binding data is uploaded in real time via a 5G link, with a synchronization delay of less than or equal to 5 seconds and a binding accuracy rate of greater than or equal to 99.9%. During the unloading process, underground workers scan the same preset fixed QR code label using the smart dispatch sub-App on their deployed smart explosion-proof mobile phones. This triggers the data entry interface, allowing them to fill in the actual unloading quantity, time, location, and acceptance personnel information. The unloading data is then uploaded via a 5G and LoRa dual-mode link, and the vehicle status is automatically updated to empty. The data entry delay is less than or equal to 8 seconds, and the error rate is less than or equal to 0.1%. When a vehicle finishes unloading but is not recorded in time, staff manually mark the empty vehicle status using the smart dispatch sub-app on the smart explosion-proof mobile phone, and upload the waste type, loading amount and recycling destination information after the waste recycling vehicle is loaded to generate an environmental traceability ledger.

3. The method according to claim 1, characterized in that, The method involves acquiring real-time vehicle location data underground using fusion positioning technology, and combining this data with 3D binding data to construct a multi-dimensional feature system encompassing vehicle distribution, waste accumulation, and environmental safety parameters, including: The 5G positioning unit performs coarse positioning operations with an accuracy of 5 to 10 meters throughout the entire mine to obtain global vehicle position perception data. At the same time, the UWB positioning unit, which integrates a roadway multipath interference suppression algorithm, performs precise positioning operations with a static accuracy of less than or equal to 0.8 meters and a dynamic accuracy of less than or equal to 2.5 meters in key areas such as roadways, loading and unloading points, and waste accumulation points to obtain precise local vehicle position data. The main control chip is used to perform weighted average fusion processing on the coarse positioning data output by the 5G positioning unit and the precise positioning data output by the UWB positioning unit. The weight of UWB data is set to 0.7 and the weight of 5G data is set to 0.

3. The final positioning result with an effectiveness of greater than or equal to 99.5% is output, and the positioning update frequency of empty vehicle and waste recycling vehicle is set to once every 5 seconds. The final positioning results are spatiotemporally aligned with the three-dimensional binding data to construct a six-dimensional feature system that includes binding status, unloading completion rate, empty car location, waste accumulation, gas concentration change, and mine pressure impact cycle, which is used to support subsequent scheduling decisions.

4. The method according to claim 1, characterized in that, Based on a multi-dimensional feature system and downhole dynamic constraints, a multi-objective optimization algorithm is used to calculate the nearest supply path for empty vehicles and the waste recovery path, generating an optimal scheduling scheme that includes transportation routes and scheduling instructions, including: Constructing a multi-objective optimization function based on a particle swarm genetic hybrid algorithm: in, For the decision variable vector, For safety weights, Safety compliance indicator functions For efficiency weighting, System operating efficiency index function As a cost weight, This is a function representing the system operating cost index. For environmental protection weight, For environmental compliance indicator functions; The specific formula for calculating safety compliance indicators is as follows: in, The gas exceedance coefficient, For leakage current safety protection factor, The gas concentration penalty coefficient, The upper limit threshold for safe gas concentration. This is the upper limit threshold for the safe leakage current. The specific formula for calculating the transportation efficiency index is as follows: in, For standard transportation time, This refers to the actual transportation time. This is a time efficiency weighting coefficient. For rated load, This refers to empty cargo volume; The specific formula for calculating transportation cost indicators is as follows: in, The actual cost of electricity consumption. For additional costs, This is the rated budget cost; The specific formula for calculating environmental compliance indicators is as follows: in, For the safe recycling and storage of waste, To allow the maximum emission duration, For the amount of resources recovered, The total amount of recyclable resources; Introducing an adaptive factor for mining pressure constraints: in, For real-time mining pressure, set The maximum allowable mining pressure threshold; Through population initialization, fitness calculation, particle velocity and position update, crossover mutation, and iteration termination steps, the fitness is optimized after 25 to 30 iterations or when the fitness error is less than [value missing]. Output the optimal scheduling scheme in real time.

5. The method according to claim 1, characterized in that, The process of mapping the optimal scheduling scheme to a digital twin model for feasibility verification, correcting scheduling instructions based on the verification results and issuing them to mobile terminals, and simultaneously updating vehicle operating status to achieve full-process closed-loop traceability includes: A digital twin model was constructed using the Unity3D engine and Surpac geological modeling software. A four-source fusion modeling formula was used to integrate geological data, real-time monitoring data, mobile interaction data, and waste recycling data to generate a virtual mine environment. The specific formula is as follows: in, For geological data, To monitor data in real time, For mobile interactive data, Data on waste recycling; The optimal scheduling scheme is mapped to the virtual mine environment for virtual-real linkage control simulation. If a collision risk or path blockage is detected, a correction command is automatically fed back. The correction response time is less than or equal to 10 seconds, which improves the scheduling accuracy by 25%. Predicting roof deformation risk using roof displacement prediction formula: in, This represents the initial displacement of the top plate. This is the displacement proportionality coefficient. This is the real-time mine pressure value. The time power exponent, The dip angle of the rock strata.

6. A novel digital positioning and intelligent scheduling management device for mining material vehicles, characterized in that, include: The binding module is used to obtain binding instructions by scanning the vehicle identification code through a mobile terminal, enter material information or unloading information, generate three-dimensional binding data containing vehicle status, material attributes and location information and upload it in real time. The module is used to acquire real-time location data of vehicles in the mine based on fusion positioning technology, and combine it with 3D binding data to build a multi-dimensional feature system covering vehicle distribution, waste accumulation and environmental safety parameters. The calculation module is used to calculate the nearest supply path for empty cars and the waste recycling path based on the multi-dimensional feature system and the dynamic constraints in the well, and to generate the optimal scheduling scheme that includes transportation routes and scheduling instructions. The adjustment module is used to map the optimal scheduling scheme to the digital twin model for feasibility verification, correct the scheduling instructions based on the verification results and send them to the mobile terminal, and update the vehicle operation status to achieve full-process closed-loop traceability.

7. An electronic device, characterized in that, Including processor and memory; The processor reads executable program code stored in the memory to run a program corresponding to the executable program code, so as to implement the method as described in any one of claims 1-5.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-5.

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