Comprehensive scheduling method and system for mining equipment based on multi-dimensional intelligent IoT data

Abstract

The present invention relates to a comprehensive scheduling method and system for mining equipment based on multi-dimensional intelligent Internet of Things data. The method includes collecting mining equipment information and environmental information, uploading to the core scheduling software unit for analysis and judgment, calculating the scheduling intensity of a single mining equipment, and optimizing and solving the optimal coefficient combination based on the comprehensive scheduling intensity obtained by comprehensive calculation, and generating scheduling instructions. If a scheduling task is required, the mining equipment performs scheduling operations according to the instructions and updates the status information in real time. The system realizes accurate scheduling of mining equipment, optimizes scheduling plans, and stores scheduling data for subsequent decision-making through analysis modules and optimization modules. The present invention improves mining operation efficiency, reduces equipment wear and energy consumption, and improves operation safety, and is suitable for intelligent scheduling management in complex mining environments.

Description

Technical Field

[0001] The present invention belongs to the technical field of mine equipment scheduling, and specifically relates to a mine equipment comprehensive scheduling method and system based on multi-dimensional intelligent Internet of Things data. Background Art

[0002] In the field of mining, the scheduling and management of equipment is a key link to ensure the smooth operation of mining operations. Traditional mining equipment scheduling methods usually rely on manual experience or simple rule settings. This method often has many shortcomings when dealing with complex and changeable mining environments. For example, manual scheduling often makes it difficult to grasp the status of all equipment and environmental changes in real time, resulting in low equipment utilization, waste of resources, and potential safety risks. At the same time, traditional scheduling methods cannot fully consider multi-dimensional factors such as equipment load, wear, and environmental conditions, making it difficult to achieve accurate optimization of scheduling tasks.

[0003] With the rapid development of the Internet of Things, big data analysis and intelligent technology, mine management is gradually moving towards intelligence and automation. By conducting a multi-dimensional comprehensive analysis of mine equipment information and environmental information, the dispatching system can monitor in real time and dynamically adjust the dispatching plan to maximize equipment utilization, reduce operating costs and ensure operational safety. However, the existing intelligent dispatching system still faces many challenges in processing massive data and optimizing complex dispatching tasks, especially in how to effectively integrate multi-dimensional information such as equipment status, environmental conditions, and task requirements to achieve accurate and efficient dispatching decisions. There is still much room for improvement.

[0004] However, the mine production scheduling in the prior art still has the following problems:

[0005] Inaccurate or untimely information: If the information on which production scheduling is based is inaccurate or cannot be updated in a timely manner, it may cause the plan to be inconsistent with the actual situation, thereby affecting production progress and efficiency.

[0006] Unbalanced resource allocation: Production scheduling may result in unreasonable resource allocation, resulting in excess resources in some areas or work surfaces, while insufficient resources in other areas, affecting overall production efficiency.

[0007] Human intervention affects scheduling accuracy: If production scheduling is interfered with by human factors or subjective intervention, it may lead to instability and accuracy of the plan.

[0008] Equipment failure and maintenance: Equipment failure and maintenance may affect production scheduling, delay production progress, and increase production costs.

[0009] Environmental changes affect scheduling: Changes in the mine production environment (such as geological structure changes, climate change, etc.) may affect the accuracy and stability of production scheduling.

[0010] Improper resource management: If personnel are not managed properly, it may lead to unreasonable scheduling, affecting production efficiency and safety. Summary of the invention

[0011] In view of the shortcomings of the prior art, the present invention proposes a comprehensive scheduling method and system for mining equipment based on multi-dimensional intelligent Internet of Things data, aiming to accurately optimize the scheduling tasks of mining equipment through the collection and analysis of multi-dimensional data, so as to improve the overall efficiency and safety of mining operations.

[0012] Purpose of the invention: To provide a mine production scheduling system and method based on multi-dimensional parameter analysis of intelligent IoT devices to solve the above-mentioned problems.

[0013] Technical solution: A comprehensive scheduling method for mining equipment based on multi-dimensional intelligent IoT data, the comprehensive scheduling method comprising the following steps:

[0014] S1. Collecting comprehensive mine information and reporting it to the core scheduling software unit; the comprehensive mine information includes mine equipment information and environmental information;

[0015] The mining equipment information at least includes the equipment status, current load, travel distance, equipment wear degree, estimated completion time, equipment failure rate, tire wear degree, position coordinates, speed, acceleration, fuel consumption rate, and rated load capacity related to the electric shovel unit, truck unit, and loading and unloading unit;

[0016] The environmental information includes at least: temperature, rainfall, wind speed, visibility, rock hardness, ore density, road slipperiness, slope, obstacle density, personnel working hours, air quality index, dust concentration, and noise level;

[0017] S2, the core scheduling software unit analyzes and judges based on the collected information and calculates the scheduling intensity of a single mining equipment;

[0018] S3. Comprehensively calculate the comprehensive dispatching intensity of all mining equipment, optimize and solve the comprehensive dispatching coefficient, and obtain the optimal coefficient combination;

[0019] S4. Determine whether a task needs to be scheduled based on the optimal coefficient combination;

[0020] S5. If it is determined that the dispatching task is not required, the work continues according to the current task; if it is determined that the dispatching task is required, when the truck is loaded, a dispatching instruction is applied to the core dispatching software unit, and the truck is dispatched according to the instruction;

[0021] S5. When the truck unloading is completed, the truck status is updated and empty truck dispatch is performed.

[0022] Furthermore, in step S2, the scheduling intensity of a single mining equipment is calculated based on the following multi-dimensional parameter model:

[0023] ;

[0024] in, Indicates the serial number is The scheduling intensity of mining equipment, Indicates that the sequence number is Mining equipment related Items of mining equipment information; express Equipment weight coefficient; Indicates that the sequence number is Mining equipment related Items of environmental information; express Environmental weight coefficient.

[0025] Furthermore, step S3 specifically includes:

[0026] S31. The comprehensive dispatching intensity of all mining equipment is calculated based on the following comprehensive multi-dimensional parameter model:

[0027] ;

[0028] ;

[0029] in, Represents the comprehensive scheduling intensity of all mining equipment, and Respectively indicate the serial number The mining equipment is in the serial number The required working time and unit time comprehensive cost on the scheduling path; Represents the set of required working times of all optional scheduling paths; Indicates the serial number is The coordination coefficient of mining equipment in calculating the comprehensive dispatching coefficient;

[0030] S32. Optimize and solve the comprehensive scheduling intensity of all mining equipment to meet the following requirements:

[0031] ;

[0032] in, represents the minimization algorithm; Indicates , and As the comprehensive scheduling intensity of all mining equipment The independent variable is solved so that The smallest value , and , and the optimal combination of scheduling paths , assigned to the optimal coefficient combination ; Indicates the serial number is A scheduling path combination of mining equipment. Represents the combination of all optional scheduling paths.

[0033] Furthermore, step S4 specifically includes:

[0034] S41. Calculate the current coefficient vector of a single mining equipment to satisfy:

[0035] ;

[0036] in, , and Respectively indicate the serial number The current equipment weight coefficient, current environment weight coefficient and current coordination coefficient of the mining equipment; represents the current coefficient vector;

[0037] S42. Calculate the optimal coefficient vector of a single mining equipment, satisfying:

[0038] ;

[0039] in, , and Respectively indicate the serial number The optimal equipment weight coefficient, optimal environment weight coefficient and optimal coordination coefficient of mining equipment; represents the optimal coefficient vector;

[0040] S43, calculate the coefficient difference vector and calculate the vector value, satisfying:

[0041] ;

[0042] ;

[0043] in, and Respectively indicate the serial number The difference vector of mine equipment coefficient and its vector value;

[0044] S44, determine whether it is necessary to schedule a task; the determination is based on:

[0045] ;

[0046] in, Indicates the preset task call judgment threshold.

[0047] Furthermore, in step S6, the method for dispatching empty vehicles is consistent with the method for dispatching loaded vehicles, and the dispatching information is stored in a database and read and executed by the system.

[0048] The present invention also provides a comprehensive scheduling system for mining equipment based on multi-dimensional intelligent IoT data, which is used to execute the comprehensive scheduling method for mining equipment based on multi-dimensional intelligent IoT data. The system includes:

[0049] Mining equipment information collection unit, environmental information collection unit, core scheduling software unit, data storage unit and scheduling execution unit;

[0050] The core scheduling software unit is used to analyze the collected information, calculate the scheduling intensity of mining equipment, and generate scheduling instructions;

[0051] The data storage unit is used to store the scheduling instructions; the scheduling execution unit is used to execute the scheduling operation according to the scheduling instructions.

[0052] Furthermore, the core scheduling software unit includes an analysis module and an optimization module; the analysis module is used to calculate the scheduling intensity of a single mining equipment based on the mining equipment information and environmental information; the optimization module is used to comprehensively calculate the comprehensive scheduling intensity of all mining equipment and optimize the scheduling plan.

[0053] Furthermore, the optimization module performs multi-dimensional optimization of the scheduling plan according to the scheduling intensity, working hours and environmental factors of the mining equipment.

[0054] Furthermore, the data storage unit is used to record the historical scheduling data and real-time status of the mining equipment for the core scheduling software unit to perform scheduling analysis and decision support.

[0055] Furthermore, the scheduling execution unit receives scheduling instructions via wireless communication, and controls the working path and task execution of the mining equipment according to the instructions.

[0056] The beneficial effects of the present invention are as follows:

[0057] 1. Improve scheduling efficiency: By collecting multi-dimensional information on mining equipment and environment, the core scheduling software unit can analyze and calculate the scheduling intensity in real time to ensure that each device performs the optimal task at the right time, reduce equipment idle time, and improve overall scheduling efficiency.

[0058] 2. Optimize resource utilization: The present invention optimizes the comprehensive scheduling intensity of all mining equipment in multiple dimensions through the optimization module, comprehensively considering multiple parameters such as equipment status, environmental factors and working hours, so as to achieve optimal resource allocation and reduce energy consumption and equipment wear.

[0059] 3. Improve safety: Through real-time collection and analysis of environmental information, such as temperature, rainfall, rock hardness and other factors, the present invention can timely adjust the scheduling plan under harsh conditions, reduce potential safety hazards, and ensure the safety of mining operations.

[0060] 4. Intelligent decision support: By recording and analyzing the historical dispatching data and real-time status of mining equipment, the present invention provides intelligent decision support for dispatchers, helping them to make better dispatching decisions and reduce human errors.

[0061] 5. Efficient empty vehicle scheduling: After completing the task, the present invention can automatically update the equipment status and execute empty vehicle scheduling, further improving the utilization rate of the equipment and reducing the waste of resources caused by unreasonable scheduling.

[0062] 6. Easy to integrate and expand: The system architecture of the present invention is simple in design and has clear functional modules, which is easy to integrate with the existing mine management system. It can also flexibly expand new functions according to actual needs, thereby improving the applicability and flexibility of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 It is a schematic diagram of the steps of the comprehensive scheduling method of the present invention.

[0064] Figure 2 It is a schematic diagram of the optional path combination of the present invention.

[0065] Figure 3 It is a schematic diagram of production truck scheduling of the present invention. DETAILED DESCRIPTION

[0066] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0067] Embodiment 1

[0068] like Figure 1 As shown, a comprehensive scheduling method for mining equipment based on multi-dimensional intelligent IoT data includes the following steps:

[0069] S1. Collecting comprehensive mine information and reporting it to the core scheduling software unit; the comprehensive mine information includes mine equipment information and environmental information;

[0070] The mining equipment information at least includes the equipment status, current load, travel distance, equipment wear degree, estimated completion time, equipment failure rate, tire wear degree, position coordinates, speed, acceleration, fuel consumption rate, and rated load capacity related to the electric shovel unit, truck unit, and loading and unloading unit;

[0071] The environmental information includes at least: temperature, rainfall, wind speed, visibility, rock hardness, ore density, road slipperiness, slope, obstacle density, personnel working hours, air quality index, dust concentration, and noise level;

[0072] S2, the core scheduling software unit analyzes and judges based on the collected information and calculates the scheduling intensity of a single mining equipment;

[0073] S3. Comprehensively calculate the comprehensive dispatching intensity of all mining equipment, optimize and solve the comprehensive dispatching coefficient, and obtain the optimal coefficient combination;

[0074] S4. Determine whether a task needs to be scheduled based on the optimal coefficient combination;

[0075] S5. If it is determined that the dispatching task is not required, the work continues according to the current task; if it is determined that the dispatching task is required, when the truck is loaded, a dispatching instruction is applied to the core dispatching software unit, and the truck is dispatched according to the instruction;

[0076] S5. When the truck unloading is completed, the truck status is updated and empty truck dispatch is performed.

[0077] In step S2, the scheduling intensity of a single mining equipment is calculated based on the following multi-dimensional parameter model: ;

[0078] in, Indicates the serial number is The scheduling intensity of mining equipment, Indicates that the sequence number is Mining equipment related Items of mining equipment information; express Equipment weight coefficient; Indicates that the sequence number is Mining equipment related Items of environmental information; express Environmental weight coefficient.

[0079] Step S3 specifically includes:

[0080] S31. The comprehensive dispatching intensity of all mining equipment is calculated based on the following comprehensive multi-dimensional parameter model: ;

[0081] ;

[0082] in, Represents the comprehensive scheduling intensity of all mining equipment, and Respectively indicate the serial number The mining equipment is in the serial number The required working time and unit time comprehensive cost on the scheduling path; Represents the set of required working times of all optional scheduling paths; Indicates the serial number is The coordination coefficient of mining equipment in calculating the comprehensive dispatching coefficient;

[0083] S32. Optimize and solve the comprehensive scheduling intensity of all mining equipment to meet the following requirements: ;

[0084] in, represents the minimization algorithm; Indicates , and As the comprehensive scheduling intensity of all mining equipment The independent variable is solved so that The smallest value , and , and the optimal combination of scheduling paths , assigned to the optimal coefficient combination ; Indicates the serial number is A scheduling path combination of mining equipment. Represents the combination of all optional scheduling paths, such as Figure 2 As shown, Figure 2 In the figure, B1 to B4 are mining faces. The electric shovel unit shovels the ore from the mining face to the loading area and loads it onto the truck unit. C is the loading area. The truck unit can drive into the loading area to load the ore. The ore can also be transferred between different loading areas to avoid too much ore being piled up in a loading area. Figure 2 It is represented by the line connecting C and C; D is the path node, different path node combinations lead to different unloading areas, A1 to A7 are unloading areas, and the truck unit unloads the ore in the unloading area.

[0085] Step S4 specifically includes:

[0086] S41. Calculate the current coefficient vector of a single mining equipment to satisfy: ;

[0087] in, , and Respectively indicate the serial number The current equipment weight coefficient, current environment weight coefficient and current coordination coefficient of the mining equipment; represents the current coefficient vector;

[0088] S42. Calculate the optimal coefficient vector of a single mining equipment, satisfying: ;

[0089] in, , and Respectively indicate the serial number The optimal equipment weight coefficient, optimal environment weight coefficient and optimal coordination coefficient of mining equipment; represents the optimal coefficient vector;

[0090] S43, calculate the coefficient difference vector and calculate the vector value, satisfying: ;

[0091] ;

[0092] in, and Respectively indicate the serial number The difference vector of mine equipment coefficient and its vector value;

[0093] S44, determine whether it is necessary to schedule a task; the determination is based on: ;

[0094] in, Indicates the preset task call judgment threshold.

[0095] In step S6, the method of dispatching empty vehicles is consistent with the method of dispatching loaded vehicles, and the dispatching information is stored in the database and read and executed by the system, such as Figure 3 shown.

[0096] Embodiment 2

[0097] In a certain mine, there are many types of equipment, including electric shovel units, truck units, loading and unloading units, etc. In order to improve the efficiency of mine operations, reduce equipment wear and ensure safe operation, the mine management department decided to introduce an equipment comprehensive scheduling system based on multi-dimensional intelligent IoT data.

[0098] Collection of comprehensive mine information:

[0099] The system collects mine equipment information and environmental information in real time through multiple sensors and IoT devices. Equipment information includes equipment status, current load, travel distance, equipment wear, estimated completion time, failure rate, tire wear, location coordinates, speed, acceleration, fuel consumption rate and rated load, etc. Environmental information includes temperature, rainfall, wind speed, visibility, rock hardness, ore density, road slipperiness, slope, obstacle density, personnel working hours, air quality index, dust concentration and noise level, etc.

[0100] Information upload and preliminary analysis:

[0101] The collected comprehensive mine information is transmitted to the core dispatch software unit through the wireless communication network. The software unit includes an analysis module and an optimization module. The analysis module first performs preliminary processing on the collected information and calculates the dispatch intensity of each mining equipment. The calculation of the dispatch intensity takes into account the current load of the equipment, the degree of wear and tear, and environmental factors such as the wetness and slope of the road surface.

[0102] Scheduling Optimization:

[0103] The optimization module calculates the overall scheduling intensity of the entire mine based on the scheduling intensity of all mining equipment. The system further optimizes the scheduling plan, solves the optimal coefficient combination, and generates scheduling instructions. During the optimization process, the system fully considers factors such as equipment wear, environmental complexity, and task urgency to ensure that the scheduling plan minimizes equipment loss and energy consumption while maximizing equipment operating efficiency.

[0104] Scheduling instruction execution:

[0105] When a truck has completed loading, the system determines whether it needs to be dispatched. If dispatch is required, the core dispatch software unit will generate a new dispatch instruction, which will be sent to the truck unit through the wireless communication network. After receiving the instruction, the truck will perform the work according to the specified path and task. After the truck completes the unloading task, the status information will be updated, and the empty truck dispatch will continue to be performed according to the new dispatch instruction.

[0106] Data storage and scheduling decision support:

[0107] All dispatch instructions and equipment status information are stored in the data storage unit. This unit records historical dispatch data and real-time status information to provide data support for subsequent dispatch decisions. The core dispatch software unit can call these historical data at any time to optimize subsequent dispatch decisions.

[0108] Implementation effect:

[0109] This embodiment achieves accurate scheduling of mining equipment by introducing the collection and analysis of multi-dimensional intelligent IoT data. The system can dynamically adapt to the changing operating environment and equipment status, improve the efficiency of mining operations, reduce equipment wear and energy consumption, and enhance operational safety. After actual application verification, this method significantly improves the comprehensive utilization rate of mining equipment, optimizes the operating process, and effectively reduces operating costs.

[0110] Obviously, the above embodiments are merely examples for clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived from them are still within the protection scope of the invention.

Claims

1. A comprehensive scheduling method for mining equipment based on multi-dimensional intelligent IoT data, characterized in that: The comprehensive scheduling method comprises the following steps: S1, collect comprehensive mine information and report it to the core scheduling software unit; The comprehensive mine information includes mine equipment information and environmental information; The mining equipment information at least includes the equipment status, current load, travel distance, equipment wear degree, estimated completion time, equipment failure rate, tire wear degree, position coordinates, speed, acceleration, fuel consumption rate, and rated load capacity related to the electric shovel unit, truck unit, and loading and unloading unit; The environmental information includes at least: temperature, rainfall, wind speed, visibility, rock hardness, ore density, road slipperiness, slope, obstacle density, personnel working hours, air quality index, dust concentration, and noise level; S2. The core scheduling software unit analyzes and judges based on the collected information and calculates the scheduling intensity of a single mining equipment. The scheduling intensity of a single mining equipment is calculated based on the following multi-dimensional parameter model: ; in, Indicates the serial number is The scheduling intensity of mining equipment, Indicates that the sequence number is Mining equipment related Items of mining equipment information; express Equipment weight coefficient; Indicates that the sequence number is Mining equipment related Items of environmental information; express Environmental weight coefficient S3. Comprehensively calculate the comprehensive dispatching intensity of all mining equipment, optimize and solve the comprehensive dispatching coefficients, and obtain the optimal coefficient combination; specifically including: S31. The comprehensive dispatching intensity of all mining equipment is calculated based on the following comprehensive multi-dimensional parameter model: ； ； in, Represents the comprehensive scheduling intensity of all mining equipment, and Respectively indicate the serial number The mining equipment is in the serial number The required working time and unit time comprehensive cost on the scheduling path; Represents the set of required working times of all optional scheduling paths; Indicates the serial number is The coordination coefficient of mining equipment in calculating the comprehensive dispatching coefficient; S32. Optimize and solve the comprehensive scheduling intensity of all mining equipment to meet the following requirements: ; in, represents the minimization algorithm; Indicates , and As the comprehensive scheduling intensity of all mining equipment The independent variable is solved so that The smallest value , and , and the optimal combination of scheduling paths , assigned to the optimal coefficient combination ; Indicates the serial number is A scheduling path combination of mining equipment. Represents the combination of all optional scheduling paths; S4. Determine whether a task needs to be scheduled based on the optimal coefficient combination; S5. If it is determined that the dispatching task is not required, the work continues according to the current task; if it is determined that the dispatching task is required, when the truck is loaded, a dispatching instruction is applied to the core dispatching software unit, and the truck is dispatched according to the instruction; S6. When the truck unloading is completed, the truck status is updated and empty truck dispatch is performed.

2. According to claim 1, a comprehensive scheduling method for mining equipment based on multi-dimensional intelligent IoT data is characterized in that: Step S4 specifically includes: S41. Calculate the current coefficient vector of a single mining equipment to satisfy: ; in, , and Respectively indicate the serial number The current equipment weight coefficient, current environment weight coefficient and current coordination coefficient of the mining equipment; represents the current coefficient vector; S42. Calculate the optimal coefficient vector of a single mining equipment, satisfying: ; in, , and Respectively indicate the serial number The optimal equipment weight coefficient, optimal environment weight coefficient and optimal coordination coefficient of mining equipment; represents the optimal coefficient vector; S43, calculate the coefficient difference vector and calculate the vector value, satisfying: ; ； in, and Respectively indicate the serial number The difference vector of mine equipment coefficient and its vector value; S44, determine whether it is necessary to schedule a task; the determination is based on: ; in, Indicates the preset task call judgment threshold.

3. The comprehensive scheduling method for mining equipment based on multi-dimensional intelligent IoT data according to claim 2 is characterized in that: In step S6, the method of empty vehicle scheduling is consistent with the method of full vehicle scheduling, and the scheduling information is stored in the database and read and executed by the system.

4. A comprehensive scheduling system for mining equipment based on multi-dimensional intelligent IoT data, used to execute a comprehensive scheduling method for mining equipment based on multi-dimensional intelligent IoT data as described in any one of claims 1 to 3, characterized in that: The system comprises: Mining equipment information collection unit, environmental information collection unit, core scheduling software unit, data storage unit and scheduling execution unit; The core scheduling software unit is used to analyze the collected information, calculate the scheduling intensity of mining equipment, and generate scheduling instructions; The data storage unit is used to store the scheduling instructions; the scheduling execution unit is used to execute the scheduling operation according to the scheduling instructions.

5. The comprehensive scheduling system for mining equipment based on multi-dimensional intelligent IoT data according to claim 4 is characterized in that: The core scheduling software unit includes an analysis module and an optimization module; The analysis module is used to calculate the scheduling intensity of a single mining equipment based on the mining equipment information and environmental information; the optimization module is used to comprehensively calculate the comprehensive scheduling intensity of all mining equipment and optimize the scheduling plan.

6. The integrated dispatching system for mining equipment based on multi-dimensional intelligent IoT data according to claim 5 is characterized in that: The optimization module optimizes the scheduling plan in multiple dimensions according to the scheduling intensity, working hours and environmental factors of the mining equipment.

7. The integrated dispatching system for mining equipment based on multi-dimensional intelligent IoT data according to claim 6 is characterized in that: The data storage unit is used to record the historical dispatching data and real-time status of the mining equipment for the core dispatching software unit to perform dispatching analysis and decision support.

8. The integrated dispatching system for mining equipment based on multi-dimensional intelligent IoT data according to claim 7 is characterized in that: The scheduling execution unit receives the scheduling instruction through wireless communication, and controls the working path and task execution of the mining equipment according to the instruction.

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