A Fault Rescheduling Method, Device, Equipment and Storage Medium for Metal Mine Operations

Abstract

The present invention relates to a method, device, equipment and storage medium for fault rescheduling in metal mine operations. The method includes: obtaining an initial plan and a historical plan for multi-equipment simultaneous operations; determining the probability of equipment failures according to the historical plan, and determining the equipment failure time periods in the initial plan based on the probability of equipment failures; determining all rescheduling time periods according to the intersection of all equipment failure time periods; constructing a rescheduling plan compilation model based on all rescheduling time periods; optimizing the rescheduling plan compilation model in a preset order according to a preset optimization algorithm to obtain a target rescheduling plan; and scheduling multi-equipment for operations according to the target rescheduling plan. The method for fault rescheduling in metal mine operations provided by the present invention guides the scheduling operations of equipment without increasing the number of equipment when equipment failures occur, improves the equipment utilization efficiency of mine equipment and the completion rate of the original planned scheme, and thus improves the production revenue of the mine.

Description

Technical Field

[0001] The present invention relates to the technical field of underground metal mine operation scheduling, and particularly to a metal mine operation fault rescheduling method, device, equipment and storage medium. Background Art

[0002] The short-term operation plan of an underground mine belongs to the flexible job problem, that is, the cyclic operation of multiple equipment between different stopes and ore passes. It is an important link in the green and intelligent mining of the mine. Affected by factors such as the mine mining environment, equipment performance, and personnel quality, abnormal situations such as equipment failures and safety accidents will inevitably occur during the mine production process, resulting in the inability to smoothly complete the original scheduling plan, and further affecting the overall production progress of the mine and the economic benefits of the enterprise. Therefore, how to solve the problem of re-scheduling underground mine operation equipment under abnormal conditions and complete the original operation plan scheme to the greatest extent has become a new research hotspot in the field of green and intelligent mining.

[0003] In the actual production process of the mine, for the situation of equipment failure, the scheduling schemes of the existing technologies are divided into the cases of not adding equipment and adding equipment. Among them, when not adding equipment, the operation plans of other equipment are not changed, and after the failure equipment is repaired, the failure equipment continues to execute the original plan; when increasing the number of equipment, the added equipment is used to replace the operation plan of the failure equipment, so as to ensure the smooth progress of the original plan.

[0004] However, the method of not adding mining equipment does not re-schedule other normally operating equipment during the failure repair period, which will reduce the equipment utilization rate and the completion rate of the production plan; while the method of adding mining equipment will increase the cost of metal mine operation. Summary of the Invention

[0005] In view of this, it is necessary to provide a metal mine operation fault rescheduling method, device, equipment and storage medium, which can achieve the purpose of re-scheduling normally operating equipment without adding mining equipment during the failure repair period.

[0006] To achieve the above technical objectives, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides a metal mine operation fault rescheduling method, including:

[0008] Obtain the initial plan and historical plan of multi-equipment simultaneous operation;

[0009] Determine the equipment failure probability according to the historical plan, and determine the equipment failure time period in the initial plan according to the equipment failure probability;

[0010] Determine all rescheduling time periods according to the intersection of all equipment failure time periods;

[0011] Construct a rescheduling plan compilation model according to all rescheduling periods;

[0012] Optimize the rescheduling plan compilation model in a preset order according to a preset optimization algorithm to obtain a target rescheduling plan;

[0013] Dispatch multiple pieces of equipment for operation according to the target rescheduling plan.

[0014] Preferably, according to the equipment failure probability, determine the equipment failure periods in the original plan of simultaneous operation of multiple pieces of equipment, including:

[0015] Divide the underground metal mine operation time into several time periods;

[0016] Collect historical equipment failure data and determine the failure prediction probability of each piece of equipment in each time period;

[0017] According to the random failure probability and failure prediction probability in each time period, determine whether there are failures in all time periods;

[0018] In all time periods with failures, obtain the failure occurrence time of each failure time period, and determine the equipment failure period of each failure time period according to the failure occurrence time of each failure time period and the preset maintenance time.

[0019] Preferably, the rescheduling period is an inserted rescheduling period and / or a complete rescheduling period; according to the intersection situation of all equipment failure periods, determine all rescheduling periods, including:

[0020] Obtain the intersection situation of the failure period of any piece of equipment with the failure periods of all other pieces of equipment;

[0021] When there is an intersection point between any failure period of any piece of equipment and any failure period of all other pieces of equipment, determine the intersection points of all equipment failure periods, and divide the equipment failure periods into several rescheduling periods according to the intersection points of all equipment failure periods to obtain inserted rescheduling periods;

[0022] When there is no intersection point between any failure period of any piece of equipment and any failure period of all other pieces of equipment, determine the moment when any piece of equipment first fails, and divide all subsequent time periods of any piece of equipment into rescheduling periods according to the moment when any piece of equipment first fails to obtain complete rescheduling periods.

[0023] Preferably, constructing a rescheduling plan compilation model according to all rescheduling periods includes:

[0024] Obtain metal mine parameters according to the metal mine attributes, and obtain equipment parameters according to the equipment information;

[0025] Determine the first fitness value, the second fitness value, and the constraint conditions of the rescheduling plan according to the metal mine parameters, equipment parameters, and the initial plan;

[0026] Construct a rescheduling plan compilation model according to the first fitness value, the second fitness value, and the constraint conditions of the rescheduling plan.

[0027] Preferably, construct a rescheduling plan compilation model according to all rescheduling periods, including:

[0028] Determine the ore grade fluctuation, the ore extraction volume completion rate, and the constraint conditions within each rescheduling period according to the metal mine parameters, equipment parameters, and the initial plan;

[0029] Among them, the ore grade fluctuation within each rescheduling period is the first fitness value;

[0030] The ore extraction volume completion rate within each rescheduling period is the second fitness value;

[0031] The constraint conditions are that the ore quantity transported out from each stope within each rescheduling period is not greater than the ore quantity that has not been transported out from this stope in the initial plan, the ore quantity transported to each ore pass within each rescheduling period is not greater than the ore quantity that has not been transported to this ore pass in the initial plan, and the rescheduling plan duration within each rescheduling period is not greater than the duration of this period.

[0032] Preferably, optimize the rescheduling plan compilation model in a preset order according to a preset optimization algorithm to obtain the target rescheduling plan, including:

[0033] Judge the type to which the current rescheduling period belongs;

[0034] Determine the target rescheduling plan for each piece of equipment in the current rescheduling period in the rescheduling plan compilation model according to the preset optimization algorithm;

[0035] Determine the target rescheduling plan for each piece of equipment in the next rescheduling period according to the target rescheduling plan for each piece of equipment in the current rescheduling period until the target rescheduling plan for each piece of equipment in all rescheduling periods is determined.

[0036] Preferably, determine the target rescheduling plan for each piece of equipment in the current rescheduling period in the rescheduling plan compilation model according to the preset optimization algorithm, including:

[0037] Determine the population of the preset optimization algorithm according to the rescheduling period and initialize the population;

[0038] Determine the optimal individual in the initialized population according to the first fitness value and the second fitness value;

[0039] Determine the exploration individuals in the initialized population. The exploration individuals move around according to the first fitness value, and update the positions of the exploration individuals and the optimal individual;

[0040] Determine the excellent individuals in the population. The excellent individuals move towards the optimal individual, and update the optimal individual according to the first fitness value of the excellent individuals and the first fitness value of the optimal individual. The excellent individuals move towards the optimal individual again until the preset number of moves is reached or the distance between the excellent individuals and the optimal individual is less than the preset distance, and then update the positions of the excellent individuals;

[0041] According to the update result of the positions of the excellent individuals, update the positions of all individuals in the population according to the preset movement rules, eliminate the individuals that do not meet the requirements of the preset fitness value, and add new individuals.

[0042] In a second aspect, the present invention further provides a metal mine operation fault rescheduling device, including:

[0043] An acquisition module, configured to acquire the initial plan and historical plan of the multi-equipment simultaneous operation;

[0044] A fault determination module, configured to determine the equipment fault occurrence probability according to the historical plan, and determine the equipment fault period in the initial plan according to the equipment fault occurrence probability;

[0045] A rescheduling determination module, configured to determine all rescheduling periods according to the intersection of all equipment fault periods;

[0046] A modeling module, configured to construct a rescheduling plan compilation model according to all rescheduling periods;

[0047] An optimization module, configured to optimize the rescheduling plan compilation model in a preset order according to a preset optimization algorithm to obtain a target rescheduling plan;

[0048] A scheduling module, configured to schedule the multi-equipment to perform operations according to the target rescheduling plan.

[0049] In a third aspect, the present invention further provides an electronic device, including a memory and a processor, wherein,

[0050] The memory is used to store programs;

[0051] The processor is coupled to the memory and is configured to execute the programs stored in the memory to implement the steps in the metal mine operation fault rescheduling method in any of the above implementation manners.

[0052] In a fourth aspect, the present invention further provides a computer-readable storage medium, configured to store computer-readable programs or instructions. When the programs or instructions are executed by a processor, the steps in the metal mine operation fault rescheduling method in any of the above implementation manners can be implemented.

[0053] The beneficial effects of adopting the above embodiments are as follows: A metal mine operation fault rescheduling method, device, equipment and storage medium provided by the present invention simulate by using historical solutions and initial solutions, that is, there is no need to increase mining equipment, thereby reducing the mining cost; and by simulating equipment failures, a rescheduling plan compilation model is constructed in each different rescheduling period, and the preset optimization algorithm is used to solve the plan compilation model of each rescheduling period in the chronological order of the rescheduling periods, so that the constructed rescheduling plan compilation model has a fast convergence speed and high robustness. Then, by integrating the rescheduling plan solutions of each period, the metal mine equipment is scheduled, and finally the purpose of reconstructing and scheduling the normally operating equipment without increasing mining equipment during the fault repair period is achieved, improving the completion rate of the mine mining plan volume, stabilizing the quality of the mined ore, and reducing the mining cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a schematic flowchart of an embodiment of the metal mine operation fault rescheduling method provided by the present invention;

[0055] Figure 2 It is a schematic flowchart of an embodiment of step S101 provided by the present invention;

[0056] Figure 3 It is a schematic state diagram of an embodiment of the cross situation of equipment failure periods provided by the present invention;

[0057] Figure 4 It is a schematic flowchart of an embodiment of the preset optimization algorithm provided by the present invention;

[0058] Figure 5 It is a schematic state diagram of an embodiment of the insertion rescheduling plan compilation provided by the present invention;

[0059] Figure 6 It is a schematic structural diagram of an embodiment of the metal mine operation fault rescheduling device provided by the present invention;

[0060] Figure 7 It is a schematic structural diagram of the electronic device provided by the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0061] The preferred embodiments of the present invention will be specifically described below in conjunction with the drawings, where the drawings form a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, rather than to limit the scope of the present invention.

[0062] Before elaborating on the embodiments of the present invention, the relevant terms are explained:

[0063] Ore grade: Also known as the average grade of mined ore, it refers to the proportion of useful components (or useful minerals) in the mined ore volume, that is, the average grade of the ore discharged from the stope after mining in the mine, so it is called the original ore geological grade.

[0064] Full bucket coefficient: It refers to the ratio of the volume of loose ore and rock dug into the bucket to the rated volume of the bucket.

[0065] Ore grade: It refers to the content of useful components or useful minerals in a unit volume or unit weight of ore.

[0066] Ore bulking factor: It refers to the ratio of the volume of loose ore to the natural volume of the ore before loosening, reflecting the degree of looseness of the ore from the natural state to after blasting, and is generally determined by on-site measurement.

[0067] In the description of the present application, "a plurality of" means two or more, unless otherwise specifically defined.

[0068] Referring to "embodiment" herein means that the specific features, structures or characteristics described in connection with the embodiment can be included in at least one embodiment of the present invention. The phrase appearing in various positions in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0069] The present invention provides a method, device, equipment and storage medium for rescheduling metal mine operation failures, which will be described separately below.

[0070] Please refer to Figure 1 , Figure 1 is a schematic flowchart of an embodiment of the metal mine operation failure rescheduling method provided by the present invention. A specific embodiment of the present invention discloses a metal mine operation failure rescheduling method, including:

[0071] S101. Obtain the initial plan and historical plan for multi-equipment simultaneous operation;

[0072] S102. Determine the equipment failure probability according to the historical plan, and determine the equipment failure period in the initial plan according to the equipment failure probability;

[0073] S103. Determine all rescheduling periods according to the intersection of all equipment failure periods;

[0074] S104. Construct a rescheduling plan compilation model according to all rescheduling periods;

[0075] S105. Optimize the rescheduling plan compilation model in a preset order according to a preset optimization algorithm to obtain the target rescheduling plan;

[0076] S106. Schedule multiple pieces of equipment for operation according to the target rescheduling plan.

[0077] In a specific embodiment of the present invention, in the historical plan of simultaneous operation of multiple pieces of equipment in step S101, there are situations where equipment has historical failures. By analyzing the historical plan, the probability of failure occurrence can be simulated. The initial plan can be an actual plan to be scheduled or a simulated plan. Determine the failure situation for this initial plan and perform rescheduling.

[0078] In a specific embodiment of the present invention, in step S102, obtain the original planned plan for the simultaneous operation of multiple pieces of equipment, and then determine the probability of equipment failure. Simulate the possibility of multiple pieces of equipment failing during simultaneous operation based on the probability of equipment failure. For the corresponding equipment with failures, further determine the possible time of failure occurrence, so as to obtain the equipment failure time period in the original planned plan.

[0079] In a specific embodiment of the present invention, in step S103, after determining the failure time periods of all equipment, judge whether the equipment failure time periods cross. Since the processing methods for crossed and non-crossed equipment failure time periods are different, and the equipment failure time periods also determine the rescheduling time periods, determine all rescheduling time periods according to the crossing situation of all equipment failure time periods.

[0080] In a specific embodiment of the present invention, in step S104, the scheduling plan within the rescheduling time period is different from the original scheduling plan. For the constructed rescheduling plan compilation model, some requirements in the original scheduling plan need to be considered, such as the mining volume, etc., to meet the mining tasks of the original plan, so as to ensure the basic mining demand even in case of failures.

[0081] In a specific embodiment of the present invention, in step S105, optimize the rescheduling plan compilation model through a preset optimization algorithm. The preset order is the time order of the rescheduling plan. Since the change of a certain rescheduling plan will affect the subsequent scheduling, optimize from near to far in the time order of the rescheduling plan.

[0082] In a specific embodiment of the present invention, in step S106, the arrangement of the rescheduling plan has been completed, and the metal ore operation equipment can be directly scheduled according to the rescheduling plan.

[0083] Compared with the prior art, a metal mine operation fault rescheduling method provided in this embodiment simulates by using historical solutions and initial solutions, that is, there is no need to increase mining equipment, thereby reducing the mining cost; and by simulating equipment failures, a rescheduling plan compilation model is constructed in each different rescheduling period, and the plan compilation models of each rescheduling period are solved by using a preset optimization algorithm in the chronological order of the rescheduling periods, so that the constructed rescheduling plan compilation model has a fast convergence speed and high robustness. Then, by integrating the rescheduling plan solutions of each period, the metal mine equipment is scheduled, and finally, the purpose of reconstructing and scheduling the normally operating equipment without increasing mining equipment during the fault repair period is achieved, the completion rate of the mine mining plan is improved, the quality of the mined ore is stabilized, and the mining cost is reduced.

[0084] Please refer to Figure 2 , Figure 2 which is a schematic flowchart of an embodiment of step S101 provided by the present invention. In some embodiments of the present invention, according to the equipment failure probability, the equipment failure period in the original plan of multi-equipment simultaneous operation is determined, including:

[0085] S201. Divide the underground metal mine operation time into several time periods;

[0086] S202. Collect historical equipment failure data and determine the failure prediction probability of each equipment in each time period;

[0087] S203. Determine whether there are failures in all time periods according to the random failure probability and the failure prediction probability in each time period;

[0088] S204. In all time periods with failures, obtain the failure occurrence time of each failure time period, and determine the equipment failure period of each failure time period according to the failure occurrence time of each failure time period and the preset repair time.

[0089] In a specific embodiment of the present invention, step S201 determines the underground metal mine operation time, and then divides the underground metal mine operation time into T time periods. Dividing the operation time into multiple time periods can facilitate the division of failures and repair times, divide the entire operation time into operation time periods and failure repair time periods, and is beneficial to scheduling each equipment.

[0090] In a specific embodiment of the present invention, in step S202, by collecting a large amount of historical equipment failure data, the probability P of each equipment failing in each time period is analyzed tk , that is, the failure prediction probability, indicating the failure probability of the kth equipment in the tth time period. As a preferred embodiment, assume that the change curve of the failure probability of the transportation equipment with time is Ptk = 1 - 1.05 -t , where t ≥ 1 and is an integer, assuming that this change curve can accurately simulate the occurrence of a fault.

[0091] In a specific embodiment of the present invention, in the t-th time period of step S203, a random number R is randomly generated for each piece of equipment tk , which is the random failure probability, representing the random failure probability of the k-th piece of equipment in the t-th time period, where t ∈ [1, T]. The random failure probability R of the k-th piece of equipment in the t-th time period tk is compared with the failure probability P tk . If R tk > P tk , then the k-th piece of equipment does not fail in the t-th time period; otherwise, it is considered that a failure has occurred.

[0092] In a specific embodiment of the present invention, for step S204, the specific equipment failure time point W k will be randomly obtained again from the original plan in this time period, and the failure repair time t w is determined from historical equipment failure data. As a preferred embodiment, the preset failure repair time is 4h. The repair end time is W k + t w . According to the repair end time, the time period t' where the repair end time is located is determined, and then t starts from t' + 1 to calculate the repair end time and the time period where the repair end time is located in the next time period until all the repair end times and the time periods where the repair end times are located are determined.

[0093] Please refer to Figure 3 , Figure 3 , which is a schematic diagram of the state of an embodiment of the cross - situation of the equipment failure time period provided by the present invention. In some embodiments of the present invention, the rescheduling period is the inserted rescheduling period and / or the complete rescheduling period; according to the cross - situation of all equipment failure time periods, all rescheduling periods are determined, including:

[0094] Obtain the cross - situation of the failure time period of any piece of equipment with the failure time periods of all other pieces of equipment;

[0095] When there is an intersection point between any failure time period of any piece of equipment and any failure time period of all other pieces of equipment, determine the intersection points of all equipment failure time periods. According to the intersection points of all equipment failure time periods, divide the equipment failure time periods into several rescheduling periods to obtain the inserted rescheduling period;

[0096] When there is no intersection between any fault period of any equipment and any fault period of all other equipment, determine the moment when any equipment first fails. According to the moment when any equipment first fails, divide all subsequent time periods of any equipment into rescheduling periods to obtain complete rescheduling periods.

[0097] In the above embodiments, when there are intersections in the time lines of the fault repair time periods of each equipment, according to the intersection situation of the fault times, using the intersection points of the fault time periods of each equipment and the fault occurrence and repair end times of each equipment as boundaries, divide the fault time periods of each equipment into multiple inserted rescheduling periods, and then implement inserted rescheduling plan compilation within each inserted rescheduling period; when there are no intersections in the time lines of the fault repair times of each equipment, when a certain equipment has its first fault within the daily planned cycle, starting from the moment when the first fault occurs, divide all subsequent time periods into multiple complete rescheduling periods, and then implement complete rescheduling plan compilation within each rescheduling period.

[0098] In some embodiments of the present invention, according to all rescheduling periods, construct a rescheduling plan compilation model, including:

[0099] Obtain metal ore parameters according to the metal ore attributes, and obtain equipment parameters according to the equipment information;

[0100] According to the metal ore parameters, equipment parameters, and initial plan, determine the first fitness value, second fitness value, and constraint conditions of the rescheduling plan;

[0101] Construct a rescheduling plan compilation model according to the first fitness value, second fitness value, and constraint conditions of the rescheduling plan.

[0102] In the above embodiments, the mining of metal ore is to transport the ore of the property to the ore pass. According to the survey of the metal ore field, metal ore parameters can be obtained; the mining equipment parameters can be directly obtained from the instruction manual or nameplate of the mining equipment, and the formulation of the mining plan is closely related to the metal ore parameters and equipment parameters.

[0103] In some embodiments of the present invention, according to all rescheduling periods, construct a rescheduling plan compilation model, including:

[0104] Determine the ore grade fluctuation, ore mining volume completion rate, and constraint conditions within each rescheduling period according to the metal ore parameters, equipment parameters, and initial plan;

[0105] Among them, the ore grade fluctuation within each rescheduling period is the first fitness value;

[0106] The ore mining volume completion rate within each rescheduling period is the second fitness value;

[0107] The constraint conditions are that the ore output volume of each stope within each rescheduling period is not greater than the ore volume that has not been transported out of the stope in the initial plan, the ore volume transported to each ore pass within each rescheduling period is not greater than the ore volume that has not been transported to the ore pass in the initial plan, and the rescheduling plan duration within each rescheduling period is not greater than the duration of that period.

[0108] In the above embodiment, the metal ore parameters include the ore looseness coefficient, ore grade, etc., and the equipment parameters include the capacity of the equipment, the full bucket coefficient of the equipment, etc. The first fitness value is the ore output grade fluctuation within each period, and taking the minimum ore output grade fluctuation within each period as the main objective function, the expression is:

[0109]

[0110] In the formula, F1 is the ore output grade fluctuation within each rescheduling period; n tmi is the number of times the m-th piece of equipment transports ore from the i-th stope in the t-th rescheduling period; C m is the capacity of the m-th piece of equipment; D m is the full bucket coefficient of the m-th piece of equipment; S i is the ore looseness coefficient of the i-th stope; p i is the ore grade of the i-th stope; YP t is the original ore output grade in the t-th rescheduling period; is the set of equipment participating in the operation in the original planned task, is the set of stopes participating in the operation in the original planned task,

[0111] The second fitness value is the ore extraction volume completion rate within each period, and taking the maximization of the ore extraction volume completion rate within each period as the secondary objective function, the expression is:

[0112]

[0113] In the formula, F2 is the ore extraction volume completion rate within each rescheduling period; Yore t is the total ore extraction volume in the t-th rescheduling period.

[0114] According to the cross situation of the fault repair time periods on the time line, the constraint conditions are divided into the insertion and complete rescheduling plan compilation conditions, and the specific expressions are as follows:

[0115] Insertion rescheduling plan compilation condition:

[0116]

[0117]

[0118]

[0119] Full rescheduling plan compilation conditions:

[0120]

[0121]

[0122]

[0123] In the formula, n cmij is the number of times the m-th piece of equipment transports from the i-th stope to the j-th ore pass in the c-th inserted rescheduling period; n cmji is the number of times the m-th piece of equipment transports from the j-th ore pass to the i-th stope in the c-th inserted rescheduling period; v ci is the originally planned ore quantity to be transported out from the i-th stope in the c-th inserted rescheduling period; u cj is the originally planned ore quantity to be transported to the j-th ore pass in the c-th inserted rescheduling period; z mij is the heavy vehicle driving time of the m-th piece of equipment from the i-th stope to the j-th ore pass; q mji is the light vehicle driving time of the m-th piece of equipment from the j-th ore pass to the i-th stope; n wmij is the number of times the m-th piece of equipment transports from the i-th stope to the j-th ore pass in the w-th full rescheduling period; n wmji is the number of times the m-th piece of equipment transports from the j-th ore pass to the i-th stope in the w-th full rescheduling period; v wi is the uncompleted ore quantity that was originally planned to be transported out from the i-th stope in the original daily plan during the w-th full rescheduling period; u wj is the uncompleted ore quantity that was originally planned to be transported to the j-th ore pass in the original daily plan during the w-th full rescheduling period; T c is the duration of the c-th inserted rescheduling period; T w is the duration of the w-th full rescheduling period; is the set of ore passes participating in the operation in the original planned task, c = {1,..., C}; w = {1,..., W}; represents any value.

[0124] Among them, the first constraint condition in the inserted rescheduling plan compilation conditions indicates that the ore quantity transported out from each stope in each inserted rescheduling period cannot be greater than the ore quantity transported out during that period in the original planned task.

[0125] The second constraint condition indicates that the ore quantity transported to each ore pass in each inserted rescheduling period cannot be greater than the original daily planned task.

[0126] The third constraint indicates that the scheduling plan duration of each piece of equipment in each inserted rescheduling period cannot be greater than the duration of that period.

[0127] In the first constraint condition of the complete rescheduling plan compilation condition, the amount of ore transported out of each stope in each complete rescheduling period cannot be greater than the amount of ore that has not been transported out of that stope in the original planned task.

[0128] The second constraint condition indicates that the amount of ore transported to each ore pass in each complete rescheduling period cannot be greater than the amount of ore that has not been transported to that ore pass in the original daily planned task.

[0129] The third constraint condition indicates that the scheduling plan duration of each piece of equipment in each complete rescheduling period cannot be greater than the duration of that period.

[0130] In some embodiments of the present invention, the rescheduling plan compilation model includes an inserted rescheduling plan compilation model and a complete rescheduling plan compilation model; according to all rescheduling periods, a rescheduling plan compilation model is constructed, including:

[0131] In the inserted rescheduling plan compilation model, when a certain piece of equipment fails, the original scheduling plan within the maintenance time period of this equipment is re-compiled.

[0132] In the complete rescheduling plan compilation model, when a certain piece of equipment fails, the original scheduling plans of all subsequent unfinished ones within the maintenance time period of this equipment are re-compiled, and after the equipment maintenance is completed, the original scheduling plans of all subsequent unfinished ones are still re-compiled.

[0133] In the above embodiments, whether there are intersections in the failure periods of each piece of equipment has different effects on the rescheduling plan. For the inserted rescheduling plan, only the original scheduling plan within the maintenance time period of the equipment needs to be re-compiled, which only affects the original scheduling plan within the maintenance time period of the equipment; while for the complete rescheduling plan, not only the original scheduling plan within the maintenance time period of this equipment needs to be re-compiled, but also the original scheduling plans of all subsequent unfinished ones after the equipment maintenance is completed need to be re-compiled, affecting the maintenance time period and all subsequent unfinished original scheduling plans.

[0134] In some embodiments of the present invention, according to a preset optimization algorithm, the rescheduling plan compilation model is optimized in a preset order to obtain a target rescheduling plan, including:

[0135] Judge the type to which the current rescheduling period belongs;

[0136] According to the preset optimization algorithm, determine the target rescheduling plan of each piece of equipment in the current rescheduling period in the rescheduling plan compilation model.

[0137] According to the target rescheduling plan of each equipment in the current rescheduling period, determine the target rescheduling plan of each equipment in the next rescheduling period until the target rescheduling plans of all equipment in all rescheduling periods are determined.

[0138] In the above embodiment, the preset optimization algorithm is an improved wolf pack optimization algorithm. Since the types of rescheduling periods are different, the rescheduling plans are different. First, it is necessary to determine the type to which the current rescheduling period belongs, and then use the improved wolf pack optimization algorithm to solve the model of this period to obtain the scheduling plans of each equipment in this period. Then, update the model of the (t + 1)-th rescheduling period according to the scheduling plan of the t-th rescheduling period until the models of all rescheduling periods are solved.

[0139] Please refer to Figure 4 , Figure 4 which is a schematic flowchart of an embodiment of the preset optimization algorithm provided by the present invention. In some embodiments of the present invention, according to the preset optimization algorithm, determining the target rescheduling plan of each equipment in the current rescheduling period in the rescheduling plan compilation model includes:

[0140] S401. According to the rescheduling period, determine the population of the preset optimization algorithm and initialize the population;

[0141] S402. Determine the optimal individual in the initialized population according to the first fitness value and the second fitness value;

[0142] S403. Determine the exploratory individuals in the initialized population. The exploratory individuals move around according to the first fitness value and update the positions of the exploratory individuals and the optimal individual;

[0143] S404. Determine the excellent individuals in the population. The excellent individuals move towards the optimal individual, and update the optimal individual according to the first fitness value of the excellent individuals and the first fitness value of the optimal individual. The excellent individuals move towards the optimal individual again until the preset number of moves is reached or the distance between the excellent individuals and the optimal individual is less than the preset distance, and then update the positions of the excellent individuals;

[0144] S405. According to the update result of the positions of the excellent individuals, update the positions of all individuals in the population according to the preset movement rule, eliminate the individuals that do not meet the requirements of the preset fitness value, and add new individuals.

[0145] In a specific embodiment of the present invention, the chromosome in step S401 adopts character coding. One chromosome in each rescheduling period represents the scheduling plan of an equipment in this period. Then, multiple chromosomes in this period form an artificial wolf individual, and the initial population is randomly generated according to the constraints of each period.

[0146] In a specific embodiment of the present invention, in step S402, the first fitness values of each artificial wolf in the solution space are first compared. If there are multiple artificial wolves with the optimal first fitness value, then the second fitness values are compared. If there are multiple cases where the second fitness values are equal, then among the artificial wolves with equal first and second fitness values, an artificial wolf is randomly selected as the lead wolf.

[0147] In a specific embodiment of the present invention, in step S403, all the artificial wolves in the solution space are sorted from excellent to inferior, and then the relatively excellent artificial wolves with a population size half except the lead wolf are used as exploring wolves. First, calculate the prey odor concentration X at the current position of exploring wolf a a , if X a is greater than the prey odor concentration X lead perceived by the lead wolf, then X lead = X a , and exploring wolf a replaces the lead wolf and initiates a summoning behavior; if X a ≤ X lead , then exploring wolf a takes one step forward in h directions respectively and records the prey odor concentration perceived after each step forward and then returns to the original position. It should be noted that the prey odor concentration X a is also the first fitness value.

[0148] The way for the exploring wolf to move forward in h directions is: randomly select h gene positions among all the chromosomes of this exploring wolf individual. The step size is set to 2, that is, each time it wanders and takes one step forward, the number of genes whose positions are exchanged left and right at the selected gene position is increased by 1.

[0149] To prevent the algorithm from falling into a local solution, when the exploring wolf wanders in h directions and still remains in place after reaching the wandering times, then this exploring wolf selects a position in one of the h directions to move to by the roulette method. The fitness in the roulette method only selects fitness1.

[0150] In a specific embodiment of the present invention, all the artificial wolves in the solution space except the lead wolf and the exploring wolves are fierce wolves. When the exploring wolf initiates a summoning behavior, or when the exploring wolf does not update the lead wolf at the maximum wandering times, then the lead wolf initiates a summoning behavior. Once the lead wolf initiates a summoning behavior, all the fierce wolves start to rush towards the position of the lead wolf. During the rush, if the prey odor concentration X b > X lead perceived by fierce wolf b, then X lead = X b , when all the fierce wolves complete this rush, this fierce wolf transforms into the lead wolf, and then initiates a summoning behavior again, and the rush times are not recalculated; if X b ≤ X lead , fierce wolf b continues to rush. When the maximum rush times are reached, or when the distance between a fierce wolf and the lead wolf is less than l, a siege behavior starts.

[0151] The charging method of the fierce wolf is as follows: First, set the charging step length to 2. Then, randomly select the gene exchange position b of each chromosome of the fierce wolf b, and exchange the genes on both sides of this gene position with the genes of the lead wolf at this position. As the number of charging times increases, the number of exchanged genes also increases.

[0152] The distance l between the fierce wolf and the lead wolf b The calculation formula of is: l b = |fitness1 i -fitness1 lead |.

[0153] In a specific embodiment of the present invention, when the fierce wolf that has charged is close to the prey in step S405, the fierce wolf should cooperate with the scout wolf to closely surround the prey in order to capture it. The position of the lead wolf is regarded as the moving position of the prey.

[0154] The surrounding method of the artificial wolf pack is as follows: Set the surrounding step length to 2. When each artificial wolf in the wolf pack participates in the surrounding behavior, first randomly determine a gene position, and then update the position of the artificial wolf pack according to the position update method of the charging behavior.

[0155] The prey is distributed according to the principle of "from strong to weak", resulting in the elimination of the weak wolves. In order to maintain the population diversity of the individuals in the wolf pack, 40% of the artificial wolf individuals with relatively poor fitness in the fitness comparison are eliminated, and then new artificial wolf individuals are generated again.

[0156] In a specific embodiment of the present invention, a certain mine uses the caving method for mining. The grades of each stope being mined at the present stage are shown in Table 1, and the heavy-load and no-load operation times of the load-haul-dump (LHD) vehicle between the stope and the ore pass are shown in Tables 2 and 3. The partial original planned scheduling tasks of each LHD vehicle on a certain day are shown in Table 4, where Roman numerals represent the stope numbers and capital letters represent the ore pass numbers. There are 7 stopes, 2 ore passes, and 3 LHD vehicles in this slice during a certain production period. The equipment capacity of the LHD vehicle is 5 tons, the full bucket coefficient is 0.95, and the ore block dispersion is 0.83.

[0157] Table 1 Grade table of each stope

[0158]

[0159]

[0160] Table 2 Heavy-load operation time of the LHD vehicle between the stope and the ore pass / s

[0161]

[0162] Table 3 No-load operation time of the LHD vehicle between the stope and the ore pass / s

[0163]

[0164] Table 4 Operating Routes of Some Load-haul-dump Machines

[0165]

[0166]

[0167] From the operating plans of each load-haul-dump machine, the ore extraction volume, daily ore grade (Table 5), and the ore volume transported to the ore pass (Table 6) for that day can be calculated.

[0168] Table 5 Ore Extraction Volume and Daily Ore Grade of Each Stope

[0169]

[0170] Table 6 Ore Volume Transported to Each Ore Pass

[0171]

[0172] The failure times and the end times of failure repair of each equipment obtained through the random failure algorithm (Table 7).

[0173] Table 7 Simulated Failure Occurrence Times and End Times of Failure Repair of Each Equipment

[0174]

[0175] Please refer to Figure 5 , Figure 5 , which is a state schematic diagram of an embodiment for preparing the insertion rescheduling plan provided by the present invention. Among them, time periods 1, 2, 3, 4, and 5 are the insertion rescheduling time periods. When preparing the rescheduling plan, each time period is carried out in sequence, and the plan preparation for the next time period can only be carried out after the rescheduling plan for the previous time period is optimized.

[0176] The optimization of the rescheduling plan is achieved by programming the improved wolf pack algorithm code using MATLAB software. With the planned task volume of the original plan in each period as the constraint and the ore grade deviation and ore output in each period as the objectives, the optimized rescheduling plan for each period is solved. In the wolf pack algorithm, the initial population size is 40, the number of evolutionary generations is 200, the wandering step size, raiding step size, and siege step size are all set to 2, and the distance threshold l between the fierce wolves and the lead wolf is determined according to the magnitude of the first fitness value of the lead wolf in each generation, which can be set within 10 times of it. When solving the planning model for each rescheduling period, it is necessary to re-initialize the population and reset the values of each parameter. The solution results of each period are shown in Tables 8, 9, 10, and 11. In the 3rd rescheduling period, all equipment is in a fault state, so there is no need to prepare a rescheduling plan. By inserting the solution results of each rescheduling period into the original plan, a complete rescheduling plan for each piece of equipment is obtained. By calculating the complete rescheduling plan, the total daily ore extraction volume, daily ore grade (Table 12), and the ore volume transported to each ore pass (Table 13) can be obtained for that day.

[0177] Table 8 Optimization Plan for the 1st Rescheduling Period

[0178]

[0179] Table 9 Optimization Plan for the 2nd Rescheduling Period

[0180]

[0181]

[0182] Table 10 Optimization Plan for the 4th Rescheduling Period

[0183]

[0184] Table 11 Optimization Plan for the 5th Rescheduling Period

[0185]

[0186] Table 12 Ore Extraction Volume and Daily Ore Grade of Each Stope in the Rescheduling Plan

[0187]

[0188] Table 13 Ore Volume Transported to Each Ore Pass in the Rescheduling Plan

[0189]

[0190] As can be seen from Table 14, by comparing the rescheduling plan optimized by the wolf pack algorithm with the traditional scheduling plan, the optimization results show that when equipment fails, for the rescheduled plan, the daily ore production grade increases by 0.74% with less fluctuation, and while the ore quality is improved, the completion rate of the mining plan increases by 7.31%.

[0191] Table 14 Data Comparison of Each Plan

[0192]

[0193] To better implement the metal mine operation fault rescheduling method in the embodiments of the present invention, based on the metal mine operation fault rescheduling method, correspondingly, please refer to Figure 6 , Figure 6 which is a schematic structural diagram of an embodiment of the metal mine operation fault rescheduling device provided by the present invention. The embodiments of the present invention provide a metal mine operation fault rescheduling device 600, including:

[0194] An acquisition module 601, configured to acquire an initial plan and a historical plan for simultaneous operation of multiple pieces of equipment;

[0195] A fault determination module 602, configured to determine the equipment fault occurrence probability according to the historical plan, and determine the equipment fault time period in the initial plan according to the equipment fault occurrence probability;

[0196] A rescheduling determination module 603, configured to determine all rescheduling time periods according to the intersection of all equipment fault time periods;

[0197] A modeling module 604, configured to construct a rescheduling plan compilation model according to all rescheduling time periods;

[0198] An optimization module 605, configured to optimize the rescheduling plan compilation model in a preset order according to a preset optimization algorithm to obtain a target rescheduling plan;

[0199] A scheduling module 606, configured to schedule multiple pieces of equipment to operate according to the target rescheduling plan.

[0200] It should be noted here that: the device 600 provided in the above embodiment can implement the technical solutions described in the above method embodiments. The specific implementation principles of the above modules or units can be referred to the corresponding content in the above method embodiments, and will not be elaborated here.

[0201] Please refer to Figure 7 , Figure 7A schematic structural diagram of the electronic device provided by the embodiment of the present invention. Based on the above metal mine operation fault rescheduling method, the present invention also correspondingly provides a metal mine operation fault rescheduling device, and the metal mine operation fault rescheduling device can be a computing device such as a mobile terminal, a desktop computer, a notebook, a palm computer, and a server. The metal mine operation fault rescheduling device includes a processor 710, a memory 720, and a display 730. Figure 7 Only some components of the electronic device are shown, but it should be understood that it is not required to implement all the shown components, and more or fewer components can be alternatively implemented.

[0202] In some embodiments, the memory 720 can be an internal storage unit of the metal mine operation fault rescheduling device, such as the hard disk or memory of the metal mine operation fault rescheduling device. In some other embodiments, the memory 720 can also be an external storage device of the metal mine operation fault rescheduling device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. equipped on the metal mine operation fault rescheduling device. Further, the memory 720 can also include both the internal storage unit and the external storage device of the metal mine operation fault rescheduling device. The memory 720 is used to store the application software installed on the metal mine operation fault rescheduling device and various types of data, such as the program code installed on the metal mine operation fault rescheduling device. The memory 720 can also be used to temporarily store the data that has been output or will be output. In one embodiment, a metal mine operation fault rescheduling program 740 is stored on the memory 720, and the metal mine operation fault rescheduling program 740 can be executed by the processor 710, so as to implement the metal mine operation fault rescheduling method of each embodiment of the present application.

[0203] In some embodiments, the processor 710 can be a Central Processing Unit (CPU), a microprocessor, or other data processing chips, and is used to run the program code stored in the memory 720 or process data, such as executing the metal mine operation fault rescheduling method, etc.

[0204] In some embodiments, the display 730 can be an LED display, a liquid crystal display, a touch liquid crystal display, and an OLED (Organic Light-Emitting Diode) toucher, etc. The display 730 is used to display the information on the metal mine operation fault rescheduling device and is used to display a visual user interface. The components 710-730 of the metal mine operation fault rescheduling device communicate with each other through a system bus.

[0205] In one embodiment, when the processor 710 executes the metal mine operation fault rescheduling program 740 in the memory 720, the steps in the metal mine operation fault rescheduling method as described above are implemented.

[0206] This embodiment also provides a computer-readable storage medium, on which a metal mine operation fault rescheduling program is stored. When the metal mine operation fault rescheduling program is executed by a processor, the following steps are implemented:

[0207] Obtain the initial plan and historical plan for multi-equipment simultaneous operation;

[0208] Determine the equipment failure probability according to the historical plan, and determine the equipment failure period in the initial plan according to the equipment failure probability;

[0209] Determine all rescheduling periods according to the cross situation of all equipment failure periods;

[0210] Construct a rescheduling plan compilation model according to all rescheduling periods;

[0211] According to the preset optimization algorithm, optimize the rescheduling plan compilation model in the preset order to obtain the target rescheduling plan;

[0212] Schedule multi-equipment for operation according to the target rescheduling plan.

[0213] In summary, a metal mine operation fault rescheduling method, device, equipment and storage medium provided by this embodiment simulate through the historical plan and the initial plan, that is, there is no need to increase mining equipment, thus reducing the mining cost; and by simulating equipment failures, a rescheduling plan compilation model is constructed in each different rescheduling period, and the plan compilation model of each rescheduling period is solved by using the preset optimization algorithm in the time order of the rescheduling periods, so that the constructed rescheduling plan compilation model converges quickly and has high robustness. Then, by integrating the rescheduling plan schemes of each period, the metal mine equipment is scheduled, and finally the purpose of reconstructing and scheduling the normally operating equipment without increasing mining equipment during the fault repair period is achieved, the completion rate of the mine mining plan volume is improved, the quality of the mined ore is stabilized, and the mining cost is reduced.

[0214] The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered by the protection scope of the present invention.

Claims

1. A method for rescheduling failures in metal ore operations, characterized in that Including: Obtain the initial plan and historical plan for multi-equipment simultaneous operation; Determine the equipment failure probability according to the historical plan, and determine the equipment failure time period in the initial plan according to the equipment failure probability; Determine all rescheduling time periods according to the intersection of all the equipment failure time periods; Construct a rescheduling plan compilation model according to all the rescheduling time periods; Optimize the rescheduling plan compilation model in a preset order according to a preset optimization algorithm to obtain a target rescheduling plan; Schedule multi-equipment for operation according to the target rescheduling plan; Among them, determining the equipment failure time period in the original plan for multi-equipment simultaneous operation according to the equipment failure probability includes: Divide the underground metal mine operation time into several time periods; Collect historical equipment failure data and determine the failure prediction probability of each equipment in each time period; Determine whether there are failures in all time periods according to the random failure probability and the failure prediction probability in each time period; In all time periods with failures, obtain the failure occurrence time of each failure time period, and determine the equipment failure time period of each failure time period according to the failure occurrence time of each failure time period and the preset repair time; The rescheduling time period is an inserted rescheduling time period and / or a complete rescheduling time period; determining all the rescheduling time periods according to the intersection of all the equipment failure time periods includes: Obtain the intersection of the failure time periods of any equipment and all other equipment; When there is an intersection point between any failure time period of the any equipment and any failure time period of all other equipment, determine the intersection points of all equipment failure time periods, and divide the equipment failure time periods into several rescheduling time periods according to the intersection points of all equipment failure time periods to obtain the inserted rescheduling time period; When there is no intersection point between any failure time period of the any equipment and any failure time period of all other equipment, determine the moment when the any equipment first fails, and divide all subsequent time periods of the any equipment into rescheduling time periods according to the moment when the any equipment first fails to obtain a complete rescheduling time period.

2. The method for fault rescheduling in metal mine operations according to claim 1, wherein Constructing a rescheduling plan compilation model according to all the rescheduling time periods includes: Obtain metal mine parameters according to the metal mine attributes, and obtain equipment parameters according to the equipment information; Determine the first fitness value, the second fitness value and the constraint conditions of the rescheduling plan according to the metal mine parameters, the equipment parameters and the initial plan; Construct a rescheduling plan compilation model according to the first fitness value, the second fitness value and the constraint conditions of the rescheduling plan.

3. The method for rescheduling metal mine operation faults according to claim 2, characterized in that Constructing a rescheduling plan compilation model according to all the rescheduling time periods includes: Determine the ore grade fluctuation, the ore extraction volume completion rate and the constraint conditions within each rescheduling time period according to the metal mine parameters, the equipment parameters and the initial plan; Among them, the ore grade fluctuation within each rescheduling time period is the first fitness value; The ore extraction volume completion rate within each rescheduling time period is the second fitness value; The amount of ore transported out of each stope within each rescheduling period is not greater than the amount of ore that has not been transported out of the stope in the initial plan, the amount of ore transported to each ore pass within each rescheduling period is not greater than the amount of ore that has not been transported to the ore pass in the initial plan, and the duration of the rescheduling plan within each rescheduling period is not greater than the duration of that period are the constraints.

4. The method for rescheduling metal mine operation faults according to claim 2, characterized in that According to the preset optimization algorithm, optimizing the rescheduling plan compilation model in a preset order to obtain the target rescheduling plan, including: Judging the type to which the current rescheduling period belongs; According to the preset optimization algorithm, determining the target rescheduling plan for each piece of equipment in the current rescheduling period in the rescheduling plan compilation model; According to the target rescheduling plan for each piece of equipment in the current rescheduling period, determining the target rescheduling plan for each piece of equipment in the next rescheduling period until the target rescheduling plans for each piece of equipment in all rescheduling periods are determined.

5. The method for rescheduling metal mine operation failures according to claim 4, wherein According to the preset optimization algorithm, determining the target rescheduling plan for each piece of equipment in the current rescheduling period in the rescheduling plan compilation model, including: According to the rescheduling period, determining the population of the preset optimization algorithm and initializing the population; According to the first fitness value and the second fitness value, determining the optimal individual in the initialized population; Determining the exploration individual in the initialized population, the exploration individual wandering according to the first fitness value and updating the position of the exploration individual and the optimal individual; Determining the excellent individuals in the population, the excellent individuals moving towards the optimal individual and updating the optimal individual according to the first fitness value of the excellent individuals and the first fitness value of the optimal individual, the excellent individuals moving towards the optimal individual again until the preset number of moves is reached or the distance between the excellent individuals and the optimal individual is less than the preset distance, and then updating the position of the excellent individuals; According to the update result of the position of the excellent individuals, updating the positions of all individuals in the population according to the preset movement rule, eliminating the individuals that do not meet the requirements of the preset fitness value, and adding new individuals.

6. A fault rescheduling device for metal mine operations, characterized in that, Including: An acquisition module for acquiring the initial plan and the historical plan of multi-equipment simultaneous operation; A fault determination module for determining the equipment fault occurrence probability according to the historical plan and determining the equipment fault period in the initial plan according to the equipment fault occurrence probability; A rescheduling determination module for determining all rescheduling periods according to the intersection of all the equipment fault periods; A modeling module for constructing a rescheduling plan compilation model according to all the rescheduling periods; An optimization module for optimizing the rescheduling plan compilation model in a preset order according to the preset optimization algorithm to obtain the target rescheduling plan; A scheduling module for scheduling multi-equipment to operate according to the target rescheduling plan; The rescheduling period is an inserted rescheduling period and / or a complete rescheduling period; According to the intersection of all the equipment fault periods, determining all the rescheduling periods, including: Obtaining the intersection of the fault periods of any piece of equipment and all other pieces of equipment; When there is an intersection point between any fault period of any one of the said equipment and any fault period of all other equipment, determine the intersection points of the fault periods of all equipment. According to the intersection points of the fault periods of all equipment, divide the equipment fault periods into several rescheduling periods to obtain the inserted rescheduling periods; When there is no intersection point between any fault period of any one of the said equipment and any fault period of all other equipment, determine the moment when the said equipment first fails. According to the moment when the said equipment first fails, divide all subsequent time periods of the said equipment into rescheduling periods to obtain complete rescheduling periods.

7. An electronic device, characterized in that, Comprising a memory and a processor, wherein, The memory is used for storing programs; The processor is coupled to the memory and is used for executing the programs stored in the memory to implement the steps in the metal mine operation fault rescheduling method according to any one of claims 1 to 5 above.

8. A computer-readable storage medium, characterized in that, For storing computer-readable programs or instructions, when the programs or instructions are executed by a processor, the steps in the metal mine operation fault rescheduling method according to any one of claims 1 to 5 above can be implemented.

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