Multi-process collaborative decision-making control system for coal mine tunneling operations

Abstract

The present invention relates to a multi-process collaborative decision-making control system for coal mine excavation operations, and belongs to the field of intelligent coal mine technology. It comprises: a multi-process time-space constraint model construction module for constructing a multi-process time-space constraint model; a multi-process collaborative decision-making module for importing an excavation work event set, an adjacency list, and an in-degree array at the beginning of the current excavation cycle, and determining the next executable optimal process based on the in-degree array, and sending a control instruction to the execution device corresponding to the next executable optimal process; a process perception module for real-time perception and sending a process execution status signal; and a multi-process collaborative decision-making module for updating the in-degree array when determining that the process execution is completed, and deciding the next executable optimal process based on the updated in-degree array. The optimal process decision method provided by the present invention is not limited by the time relationship constraint threshold range and abnormal or complex working conditions, and can dynamically adapt to real-time underground mining conditions.

Description

Technical Field

[0001] The present invention relates to the field of intelligent coal mine technology, and in particular to a multi-process collaborative decision-making control system for coal mine excavation operations. Background Art

[0002] Coal mine excavation operations are complex processes involving numerous steps, and the sequencing, responsiveness, and accuracy of these steps are crucial. With the deployment of numerous intelligent sensors underground and the increasing adoption of computer technology, real-time early warning of the excavation face environment and online monitoring of the operating status of excavation equipment groups have become possible. Individual equipment can now be automatically controlled with minimal or no human intervention. However, excavation operations involve multiple processes and the coordinated operation of various types of equipment. Due to the harsh underground mining environment, unexpected situations may occur during the execution of each process, resulting in significant delays.

[0003] Patent CN114967456A discloses a multi-behavior collaborative control decision-making method for an intelligent coal mine tunneling robot. This proposed multi-behavior collaborative control decision-making method solves the optimal timing sequence that satisfies the constraints by presetting a threshold range for the time relationships between various tunneling actions. However, the technical solution in the aforementioned patent and traditional automated multi-process collaborative decision-making systems typically only set the time constraints between each process to a fixed range threshold based on experience. This system does not consider adjusting the control method in the event of abnormal or complex operating conditions, and is unable to dynamically adapt to real-time underground mining conditions, resulting in poor practical application capabilities. Summary of the Invention

[0004] To solve the above technical problems, the present invention provides a multi-process collaborative decision-making control system for coal mine excavation operations. The technical solution of the present invention is as follows:

[0005] A multi-process collaborative decision-making control system for coal mine excavation operations includes a multi-process collaborative decision-making module, which is communicatively connected to a multi-process time-space constraint model construction module and a process perception module:

[0006] A multi-process time-space constraint model construction module is used to construct a multi-process time-space constraint model based on the actual mining situation of the excavation working face. The multi-process time-space constraint model includes an excavation work event set, an adjacency list, and an in-degree array.

[0007] The multi-process collaborative decision-making module is used to import the excavation work event set, adjacency list and in-degree array at the beginning of the current excavation cycle, determine the next executable optimal process based on the in-degree array, and send control instructions to the execution device corresponding to the next executable optimal process;

[0008] The process perception module is used to perceive the process execution status signal in real time during the execution of the equipment execution control instruction, and send the process execution status signal to the multi-process collaborative decision module in real time;

[0009] The multi-process collaborative decision-making module is also used to record the process execution time, update the in-degree array, and decide the next executable best process based on the updated in-degree array when the process execution is completed according to the process execution status signal sent by the process perception module, until the current excavation cycle ends.

[0010] Optionally, the multi-process time-space constraint model construction module is used to:

[0011] The excavation process event set of the current excavation cycle is constructed based on the actual mining situation of the excavation working face. The excavation process event set uses nodes to represent processes and edges to represent the time and space constraints of the execution of two processes. It includes multiple process constraint binary tuples, expressed as {u, v}, where u→v means that process u must be executed before process v.

[0012] Determine the adjacency list of all nodes in the excavation process event set, and determine the in-degree array of all nodes based on the adjacency list of all nodes; wherein, the adjacency list is the set of nodes that can continue to execute the next process after completing the current process, and the in-degree array includes the in-degree value of each node; the in-degree value indicates the number of processes that need to be executed if the current process is to be executed.

[0013] Optionally, when determining the adjacency lists of all nodes in the tunneling process event set, the multi-process time-space constraint model building module is used to:

[0014] First, obtain the previous node u and the next node v1 in the first process constraint tuple {u, v1} in the excavation process event set, then create an adjacency list about node u, put node v1 into the adjacency list of u, and continue to traverse the excavation process event set. If there is a new process constraint tuple {u, v2} about node u, then continue to put v2 into the adjacency list of u until all process constraint tuples about node u are processed, indicating that the adjacency list of node u is completed, and then continue to process the remaining process constraint tuples backward in the order of each process constraint tuple in the excavation process event set until the adjacency list of all nodes in the excavation process event set is completed.

[0015] Optionally, the multi-process space constraint model building module is used to:

[0016] First, the initialization value of the in-degree value of all nodes is set to 0, and then the adjacency list of the first node is traversed. Whenever a node in the adjacency list of the first node is read, the in-degree value of the node is increased by 1; then the next adjacency list is traversed and the same operation is performed until the adjacency lists of all nodes are traversed. The in-degree values ​​of all nodes are obtained, and the in-degree arrays of all nodes are constructed based on the in-degree values ​​of all nodes.

[0017] Optionally, when determining the next optimal executable process based on the in-degree array, the multi-process collaborative decision module is used to:

[0018] Traverse the nodes with in-degree value 0 in the in-degree array, add the nodes with in-degree value 0 to the execution queue, and determine the process corresponding to the node with in-degree value 0 as the next best executable process based on the preset correspondence between nodes and processes.

[0019] Optionally, the multi-process collaborative decision module is used to update the in-degree array:

[0020] Get the adjacency list of the node with indegree value 0 from the indegree array, update the indegree value of the node with indegree value 0 to -1, and reduce the indegree value of each node in the adjacency list of the node with indegree value 0 by 1 to obtain the updated indegree array.

[0021] Optionally, when deciding the next optimal executable process based on the updated in-degree array, the multi-process collaborative decision module is used to:

[0022] Determine whether the in-degree values ​​of all nodes in the updated in-degree array are -1. If so, the current excavation cycle is determined to be over. If not, continue to traverse the nodes with in-degree values ​​of 0 in the updated in-degree array, and take the process corresponding to the node with in-degree value of 0 as the next best executable process, until the in-degree values ​​of all nodes in the updated in-degree array are -1, and the current excavation cycle is determined to be over.

[0023] Optionally, the multi-process collaborative decision module is also used to place the nodes corresponding to the processes that are executed successively into the collaborative control queue, and record the execution time of each process and the total time of the current excavation cycle.

[0024] Optionally, the multi-process time-space constraint model construction module is further used to update the excavation work event set in the multi-process time-space constraint model according to the collaborative control queue.

[0025] All the above optional technical solutions can be combined arbitrarily, and the present invention does not provide detailed descriptions of the structures after each combination.

[0026] By means of the above solution, the beneficial effects of the present invention are as follows:

[0027] By constructing a multi-process spatiotemporal constraint model through the multi-process spatiotemporal constraint model construction module, the execution order of numerous processes in the complex tunneling process can be effectively constrained, and the latest process execution status can be dynamically updated based on the execution process. The multi-process collaborative decision-making module makes collaborative decisions on all processes involved in the entire tunneling process based on the perception results of the multi-process spatiotemporal constraint model and the process perception module, and can automatically solve for the next executable optimal process. This ensures that the provided optimal process decision-making method is not restricted by the time relationship constraint threshold range and abnormal or complex working conditions during the execution of each process. It can dynamically adapt to real-time underground mining conditions and has good practical application capabilities.

[0028] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and implement it according to the contents of the specification, the following is a detailed description of the preferred embodiments of the present invention with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a schematic diagram of the composition structure of a multi-process collaborative decision-making control system for coal mine excavation operations provided by an embodiment of the present invention.

[0030] Figure 2 This is a workflow diagram of a multi-process collaborative decision-making control system for coal mine excavation operations provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0031] The following embodiments of the present invention are described in further detail with reference to the accompanying drawings and examples. The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0032] The main task of the multi-process collaborative decision-making and control system for coal mine excavation operations provided by the embodiment of the present invention is to study the dynamic relationship between each process and each device during the excavation process, analyze the time and space constraints of the processes executed by each device, obtain the optimal process planning with forward and backward related actions, and finally obtain the optimal process planning result.

[0033] like Figure 1 As shown, the multi-process collaborative decision-making control system for coal mine excavation operations provided by the embodiment of the present invention includes a multi-process collaborative decision-making module, which is communicatively connected to a multi-process time-space constraint model construction module and a process perception module:

[0034] A multi-process time-space constraint model construction module is used to construct a multi-process time-space constraint model based on the actual mining situation of the excavation working face. The multi-process time-space constraint model includes an excavation work event set, an adjacency list, and an in-degree array.

[0035] The multi-process collaborative decision-making module is used to import the excavation work event set, adjacency list and in-degree array at the beginning of the current excavation cycle, determine the next executable optimal process based on the in-degree array, and send control instructions to the execution device corresponding to the next executable optimal process;

[0036] The process perception module is used to perceive the process execution status signal in real time during the execution of the equipment execution control instruction, and send the process execution status signal to the multi-process collaborative decision module in real time;

[0037] The multi-process collaborative decision-making module is also used to record the process execution time, update the in-degree array, and decide the next executable best process based on the updated in-degree array when the process execution is completed according to the process execution status signal sent by the process perception module, until the current excavation cycle ends.

[0038] The multi-process temporal and spatial constraint model is used to define the execution order of each process, preventing major safety accidents caused by improper operation. For example, if a roadheader continues to advance after cutting the coal wall without providing support in the roof and sidewalls, this could result in an excessively large void area, potentially causing a roof fall or sidewall spalling. The multi-process temporal and spatial constraint model leverages tunneling safety regulations and human experience to constrain the execution order of each process during actual underground tunneling, ensuring the safety of tunneling operations.

[0039] Specifically, the multi-process collaborative decision-making module and the process perception module can be connected via a wired or wireless connection. The multi-process collaborative decision-making module and the multi-process time-space constraint model construction module can be integrated on different terminals or located on the same terminal.

[0040] The excavation process is divided into three categories: excavation, transportation, and support, as shown in Table 1, which shows a correspondence between each process and node in the excavation cycle.

[0041]

[0042] In a specific embodiment, the multi-process spatial constraint model construction module is used to:

[0043] First, the excavation process event set of the current excavation cycle is constructed based on the actual mining situation of the excavation working face. The excavation process event set uses nodes to represent processes and edges to represent the time and space constraints of the execution of two processes. The excavation process event set includes multiple process constraint binary tuples, which are expressed as {u, v}, where u→v means that process u needs to be executed before process v. Then, the adjacency list of all nodes in the excavation process event set is determined, and the in-degree array of all nodes is determined based on the adjacency list of all nodes. Among them, the adjacency list is the set of nodes that can continue to execute the next process after executing the current process, and the in-degree array includes the in-degree value of each node. The in-degree value indicates the number of processes that need to be executed if the current process is to be executed.

[0044] Specifically, the excavation process event set for each excavation cycle is determined based on the spatiotemporal constraints of each process during the excavation process. These event sets can be the same or different. For example, after one excavation cycle, the excavation process event set for the next excavation cycle can be adjusted based on the execution status of the processes in that excavation cycle. Embodiments of the present invention only need to ensure that, when the current excavation cycle is executed, the excavation process event set for the current excavation cycle has been established based on the actual mining conditions at the excavation working face. The actual mining conditions at the excavation working face can include the execution order of each process defined in the excavation process safety operating regulations, the execution order of each process manually determined based on historical excavation cycles, and other contents.

[0045] For example, combining the correspondence between processes and nodes shown in Table 1 and some excavation cycles that have been executed in history, the excavation process event set of some excavation cycles is determined. eages It is expressed as {{1, 2}, {1, 3} {2, 4}, {3, 4}, {4, 5}, {5, 6}, {6, 8}, {8, 17}, {8, 18}, {17, 9}, {17, 10}, {18, 9}, {18, 10}, {18, 13}, {13, 14} {14, 15}, {14, 16}...}. Among them, {1, 2} means that process 1 must be executed before process 2.

[0046] In a specific embodiment, the multi-process time-space constraint model construction module is used to determine the adjacency list of all nodes in the excavation process event set: first obtain the previous node u and the next node v1 in the first process constraint binary tuple {u, v1} in the excavation process event set, then create an adjacency list about node u, put node v1 into the adjacency list of u, and continue to traverse the excavation process event set. If there is a new process constraint binary tuple {u, v2} about node u in the excavation process event set, then continue to put v2 into the adjacency list of u until all process constraint binary tuples about node u are processed, indicating that the adjacency list construction of node u is completed, and then continue to process the remaining process constraint binary tuples backward in the order of each process constraint binary tuple in the excavation process event set until the adjacency list of all nodes in the excavation process event set is completed.

[0047] The above excavation process event set eages For example, the node 1 in the adjacency table Graph [1]={2,3}, which means that after process 1 is completed, process 2 or 3 can be executed. Similarly, Graph [2]={4}, Graph [3]={4}, Graph [4]={5}, Graph [5]={6}, and so on.

[0048] Specifically, the in-degree value of a node represents the number of other processes that must be executed before the process corresponding to the current node is executed. When the in-degree value of a node is 0, it means that the process corresponding to the node can be executed directly without any constraints from other processes. When the in-degree value is greater than 0, the process corresponding to the current node cannot be executed yet and must wait until the processes corresponding to other nodes in the time-space constraint model have completed their execution.

[0049] In a specific embodiment, the multi-process time-space constraint model construction module is used to determine the in-degree arrays of all nodes based on the adjacency lists of all nodes: first, the initialization value of the in-degree value of all nodes is set to 0, and then the adjacency list of the first node is traversed, and whenever a node in the adjacency list of the first node is read, the in-degree value of the node is increased by 1; then the next adjacency list is traversed and the same operation is performed (that is, whenever a node in the adjacency list of the next node is read, the in-degree value of the node is increased by 1), until the adjacency lists of all nodes are traversed, the in-degree values ​​of all nodes are obtained, and the in-degree arrays of all nodes are constructed according to the in-degree values ​​of all nodes.

[0050] Specifically, the in-degree array records each node and its corresponding in-degree value.

[0051] With the above GraphTaking [1]={2, 3} as an example, when traversing the adjacency table, nodes 2 and 3 can be read, and the in-degree values ​​of nodes 2 and 3 are increased by 1 respectively.

[0052] Based on the above content, in a specific embodiment, when determining the next executable optimal process based on the in-degree array, the multi-process collaborative decision module is used to: traverse the nodes with in-degree values ​​of 0 in the in-degree array, add the nodes with in-degree values ​​of 0 to the execution queue, and determine the process corresponding to the node with in-degree value of 0 as the next executable optimal process based on the preset correspondence between nodes and processes (Table 1).

[0053] It should be noted here that when there are multiple nodes with an in-degree value of 0 in the in-degree array, the processes corresponding to the multiple nodes can be executed in parallel.

[0054] Furthermore, the execution devices corresponding to each process on the tunneling face may be different. For example, the execution device for "moving forward to the tunneling face" is a tunneling machine, the execution device for "temporary support retraction" is a bolter, and so on. It should be noted that each execution device is equipped with at least one sensor or other sensing device, which can detect in real time the execution status signal of the process as the execution device executes the process. After the multi-process collaborative decision module determines the next optimal process, it obtains the execution device corresponding to the next optimal process based on the preset correspondence between processes and execution devices and sends a control instruction to the execution device. After receiving the control instruction, the execution device corresponding to the next optimal process executes the next optimal process according to the control instruction. During this process, the sensing device installed on the execution device corresponding to the next optimal process detects the process execution status signal in real time and sends the process execution status signal to the multi-process collaborative decision module in real time. After receiving the process execution status signal, the multi-process collaborative decision module determines the process execution status in real time based on the process execution status signal and, upon determining that the process execution is complete, performs subsequent operations such as updating the in-degree array.

[0055] In a specific embodiment, when updating the in-degree array, the multi-process collaborative decision module is used to: obtain the adjacency list of the node with an in-degree value of 0 from the in-degree array, update the in-degree value of the node with an in-degree value of 0 to -1, and subtract 1 from the in-degree value of each node in the adjacency list of the node with an in-degree value of 0 to obtain an updated in-degree array.

[0056] For example, take the adjacency list of node 1 GraphTaking [1]={2, 3} as an example, when the multi-process collaborative decision module updates the in-degree array, it subtracts 1 from the in-degree values ​​of nodes 2 and 3 in the adjacency list of node 1. For example, if the in-degree values ​​of nodes 2 and 3 in the adjacency list of node 1 are 2 and 1 respectively before the update, then the in-degree values ​​of nodes 2 and 3 in the adjacency list of node 1 become 1 and 0 respectively after the update.

[0057] After updating the in-degree value of each node in the adjacency list of all nodes, the updated in-degree array is obtained.

[0058] Furthermore, when determining the next optimal executable process based on the updated in-degree array, the multi-process collaborative decision-making module is configured to: determine whether the in-degree values ​​of all nodes in the updated in-degree array are -1. If the in-degree values ​​of all nodes in the in-degree array are -1, the current excavation cycle is determined to have ended. If the in-degree value of any node in the in-degree array is not -1, the module continues to traverse the nodes with in-degree values ​​of 0 in the updated in-degree array, selects the process corresponding to the node with in-degree value 0 as the next optimal executable process, and sends a control instruction to the execution device corresponding to the next optimal executable process. The execution device corresponding to the next optimal executable process executes the control instruction and, during the execution of the instruction, uses the sensing device installed on it to sense the execution status signal of the process in real time. The multi-process collaborative decision-making module repeats this decision-making process multiple times until the in-degree values ​​of all nodes in the updated in-degree array are -1, at which point the current excavation cycle is determined to have ended.

[0059] In a specific embodiment, the multi-process collaborative decision module is further used to put the nodes corresponding to the processes that have been executed in sequence into the collaborative control queue. queue ={1, 3, ...}, and record the execution time of each process and the total time of the current excavation cycle.

[0060] Furthermore, the multi-process time-space constraint model construction module is also used to update the excavation work event set in the multi-process time-space constraint model according to the collaborative control queue.

[0061] Specifically, each node in the collaborative control queue can represent the order of execution of each process to a certain extent. Therefore, when the order of each node in the collaborative control queue shows that the order of some nodes may need to be adjusted, the excavation work event set in the multi-process time-space constraint model can be updated according to the collaborative control queue as the excavation work event set for the subsequent excavation cycle.

[0062] In summary, the multi-process collaborative decision-making control system for coal mine excavation operations provided by an embodiment of the present invention includes the following steps when working: S1, constructing a multi-process time-space constraint model, wherein the multi-process time-space constraint model includes an excavation work event set, an adjacency list and an in-degree array; S2, the multi-process collaborative decision-making module imports the excavation work event set, the adjacency list and the in-degree array at the beginning of the current excavation cycle, and determines the next executable optimal process according to the in-degree array, and sends a control instruction to the execution device corresponding to the next executable optimal process; S3, the process perception module perceives the process execution status signal in real time during the process of the execution device executing the control instruction, and sends the process execution status signal to the multi-process collaborative decision-making module in real time; S4, when the multi-process collaborative decision-making module determines that the process execution is completed according to the process execution status signal, it records the process execution time, updates the in-degree array, and decides the next executable optimal process according to the updated in-degree array until the current excavation cycle ends.

[0063] The multi-process collaborative decision-making control system for coal mine excavation operations provided by the embodiments of the present invention has the following characteristics:

[0064] 1. By constructing a multi-process time-space constraint model, the execution order of numerous processes in a complex tunneling process can be effectively constrained, and the latest process execution status (in-degree array) can be dynamically updated according to the execution process.

[0065] 2. The multi-process collaborative decision-making module can make collaborative decisions on all processes involved in the entire excavation process based on the multi-process time-space constraint model and the perception results of the process perception module, and automatically solve the next executable optimal process.

[0066] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A multi-process collaborative decision-making control system for coal mine excavation operations, characterized in that: It includes a multi-process collaborative decision-making module, which is connected to the multi-process spatial constraint model construction module and the process perception module: A multi-process time-space constraint model construction module is used to construct a multi-process time-space constraint model based on the actual mining situation of the excavation working face. The multi-process time-space constraint model includes an excavation process event set, an adjacency list, and an in-degree array. The multi-process collaborative decision-making module is used to import the excavation process event set, adjacency list and in-degree array at the beginning of the current excavation cycle, determine the next executable optimal process based on the in-degree array, and send control instructions to the execution device corresponding to the next executable optimal process; The process perception module is used to perceive the process execution status signal in real time during the execution of the equipment execution control instruction, and send the process execution status signal to the multi-process collaborative decision module in real time; The multi-process collaborative decision module is also used to record the process execution time, update the in-degree array, and decide the next optimal executable process based on the updated in-degree array when the process execution status signal sent by the process perception module is determined to be completed, until the current excavation cycle ends; The multi-process time-space constraint model construction module is used to: construct the excavation process event set of the current excavation cycle according to the actual mining situation of the excavation working face, and use the edge to represent the time-space constraints of the execution of the two processes, including multiple process constraint binary tuples, expressed as {u, v}, u→v means that process u must be executed before process v; determine the adjacency list of all nodes in the excavation process event set, and determine the in-degree array of all nodes based on the adjacency list of all nodes; wherein the adjacency list is the set of nodes that can continue to execute the next process after executing the current process, and the in-degree array includes the in-degree value of each node; the in-degree value indicates the number of processes that need to be executed if the current process is to be executed; The multi-process time-space constraint model construction module is used to determine the in-degree arrays of all nodes based on the adjacency lists of all nodes: first, the initialization value of the in-degree value of all nodes is set to 0, and then the adjacency list of the first node is traversed. Whenever a node in the adjacency list of the first node is read, the in-degree value of the node is increased by 1; then the next adjacency list is traversed and the same operation is performed until the adjacency lists of all nodes are traversed, and the in-degree values ​​of all nodes are obtained, and the in-degree arrays of all nodes are constructed according to the in-degree values ​​of all nodes; When determining the next best executable process based on the in-degree array, the multi-process collaborative decision-making module is used to: traverse the nodes with in-degree values ​​of 0 in the in-degree array, add the nodes with in-degree values ​​of 0 to the execution queue, and determine the process corresponding to the node with in-degree value of 0 as the next best executable process based on the preset correspondence between nodes and processes.

2. The multi-process collaborative decision-making control system for coal mine excavation operations according to claim 1 is characterized in that: The multi-process time-space constraint model building module is used to determine the adjacency list of all nodes in the tunneling process event set: First, obtain the previous node u and the next node v1 in the first process constraint tuple {u, v1} in the excavation process event set, then create an adjacency list about node u, put node v1 into the adjacency list of u, and continue to traverse the excavation process event set. If there is a new process constraint tuple {u, v2} about node u, then continue to put v2 into the adjacency list of u until all process constraint tuples about node u are processed, indicating that the adjacency list of node u is completed, and then continue to process the remaining process constraint tuples backward in the order of each process constraint tuple in the excavation process event set until the adjacency list of all nodes in the excavation process event set is completed.

3. The multi-process collaborative decision-making control system for coal mine excavation operations according to claim 1 is characterized in that: The multi-process collaborative decision module is used to update the in-degree array: Get the adjacency list of the node with indegree value 0 from the indegree array, update the indegree value of the node with indegree value 0 to -1, and reduce the indegree value of each node in the adjacency list of the node with indegree value 0 by 1 to obtain the updated indegree array.

4. The multi-process collaborative decision-making control system for coal mine excavation operations according to claim 3 is characterized in that: The multi-process collaborative decision module is used to determine the next optimal executable process based on the updated in-degree array: Determine whether the in-degree values ​​of all nodes in the updated in-degree array are -1. If so, the current excavation cycle is determined to be over. If not, continue to traverse the nodes with in-degree values ​​of 0 in the updated in-degree array, and take the process corresponding to the node with in-degree value of 0 as the next best executable process, until the in-degree values ​​of all nodes in the updated in-degree array are -1, and the current excavation cycle is determined to be over.

5. The multi-process collaborative decision-making control system for coal mine excavation operations according to claim 1 is characterized in that: The multi-process collaborative decision-making module is also used to place the nodes corresponding to the processes that have been executed successively into the collaborative control queue, and record the execution time of each process and the total time of the current excavation cycle.

6. The multi-process collaborative decision-making control system for coal mine excavation operations according to claim 5 is characterized in that: The multi-process time-space constraint model construction module is also used to update the excavation process event set in the multi-process time-space constraint model according to the collaborative control queue.

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