Control method, device and equipment of mine ventilation system and storage medium

Abstract

The invention provides a control method, device and equipment for a mine ventilation system and a storage medium, and the method comprises the steps: determining a first target branch based on a complete incidence matrix corresponding to a mine ventilation network diagram and the branch weight of each branch in the mine ventilation network diagram; acquiring target air volume data of the first target branch, and acquiring branch air volume data of each branch based on the target air volume data; obtaining a second target branch corresponding to an independent path in the mine ventilation network diagram based on the complete incidence matrix; obtaining target resistance data of the second target branch, and obtaining branch resistance data of each branch based on the target resistance data; based on the branch air volume data and the branch resistance data, wind resistance adjustment data and wind resistance data are obtained; obtaining actual wind resistance data based on the wind resistance data and the wind resistance adjustment data; and dynamically controlling the mine ventilation system based on the branch resistance, the air volume monitoring data and the actual air resistance data. And the ventilation system can be adjusted as required.

Description

Technical Field

[0001] The present application relates to the technical field of mine ventilation, and in particular to a control method, device, equipment and storage medium for a mine ventilation system. Background Art

[0002] In the related technology, the main task of the mine ventilation environment parameter monitoring system is to monitor the basic airflow parameters in the ventilation system, invert the ventilation status of the entire mine in real time, and ensure the safe and stable operation of the ventilation system. From graph theory and mine ventilation theory, it can be seen that the wind flow parameters of the branches satisfy the balance equation of loop wind pressure and node air volume, and there is no need to install sensors in each lane. Since too many monitoring sensors will seriously affect the monitoring efficiency of the mine safety monitoring system, it is necessary to reasonably deploy underground sensors so that the ventilation system can be controlled on demand based on the monitoring data of the sensors. Summary of the invention

[0003] The present application aims to solve one of the technical problems in the related art at least to some extent.

[0004] In the first aspect, the present application proposes a control method for a mine ventilation system, the method comprising: determining a first target branch based on a complete association matrix corresponding to a mine ventilation network diagram and a branch weight of each branch in the mine ventilation network diagram; obtaining target air volume data of the first target branch, and obtaining branch air volume data of each branch based on the target air volume data; obtaining a second target branch corresponding to an independent passage in the mine ventilation network diagram based on the complete association matrix; obtaining target resistance data of the second target branch, and obtaining branch resistance data of each branch based on the target resistance data; obtaining wind resistance adjustment data and wind resistance data of each branch based on the branch air volume data and the branch resistance data; obtaining actual wind resistance data based on the wind resistance data and the wind resistance adjustment data; and dynamically controlling the mine ventilation system based on the branch resistance, the air volume monitoring data and the actual wind resistance data.

[0005] In one implementation, the complete association matrix is ​​established through the following steps: establishing an initial mine ventilation network corresponding to the mine ventilation system; dividing the initial mine ventilation network into at least one subnetwork; determining the subnetwork type of each subnetwork based on the branch topological relationship of each subnetwork; simplifying the subnetwork based on the subnetwork type of each subnetwork and the wind distribution nodes and wind collection nodes corresponding to each subnetwork to obtain the mine ventilation network; obtaining the initial state of the mine ventilation system; and establishing the complete association matrix based on the initial state and the mine ventilation network.

[0006] In one implementation, the first target branch is determined based on the complete association matrix corresponding to the mine ventilation network diagram and the branch weight of each branch in the mine ventilation network diagram, including: obtaining sensitivity information and importance weight corresponding to each of the branches; determining the branch weight of the branch based on the sensitivity information and the importance weight corresponding to each of the branches; using the minimum spanning tree method in combination with the branch weight to obtain the corresponding minimum spanning tree; obtaining the remaining tree branches corresponding to the minimum spanning tree; and determining the first target branch based on the remaining tree branches.

[0007] In an optional implementation, the obtaining of the sensitivity information corresponding to each of the branches includes: obtaining the branch flow, branch flow resistance and additional resistance corresponding to each of the branches; establishing a branch sensitivity equation group based on the branch flow, the branch flow resistance and the additional resistance; solving the branch sensitivity equation group to obtain the sensitivity matrix corresponding to each of the branches as the sensitivity information corresponding to each of the branches.

[0008] In one implementation, the wind resistance adjustment data is obtained based on the branch wind volume data and the branch resistance data, including: establishing a branch wind volume error equation matrix based on the branch wind volume data, and establishing a branch error equation matrix based on the branch resistance data; establishing a first objective function based on the branch wind volume error equation matrix, and establishing a second objective function based on the branch error equation matrix; solving the first objective function to obtain wind volume adjustment data, and solving the second objective function to obtain resistance adjustment data; obtaining the wind resistance adjustment data based on the wind volume adjustment data and the resistance adjustment data.

[0009] In an optional implementation, solving the first objective function to obtain wind volume adjustment data includes: obtaining element information of non-zero matrix elements in the branch wind volume error equation matrix; establishing at least one element information array based on the element information; solving the first objective function based on the element information data to obtain the wind volume adjustment data.

[0010] In the second aspect, the present application proposes a control device for a mine ventilation system, the device comprising: a first processing module, used to determine a first target branch based on a complete association matrix corresponding to a mine ventilation network diagram and a branch weight of each branch in the mine ventilation network diagram; a second processing module, used to obtain target air volume data of the first target branch, and to obtain branch air volume data of each branch based on the target air volume data; a third processing module, used to obtain a second target branch corresponding to an independent passage in the mine ventilation network diagram based on the complete association matrix; a fourth processing module, used to obtain target resistance data of the second target branch, and to obtain branch resistance data of each branch based on the target resistance data; a fifth processing module, used to obtain wind resistance adjustment data and wind resistance data of each branch based on the branch air volume data and the branch resistance data; a sixth processing module, used to obtain actual wind resistance data based on the wind resistance data and the wind resistance adjustment data; a control module, used to dynamically control the mine ventilation system based on the branch resistance, the air volume monitoring data and the actual wind resistance data.

[0011] In one implementation, the device may also include a seventh processing module, which is used to: establish an initial mine ventilation network corresponding to the mine ventilation system; divide the initial mine ventilation network into at least one sub-network; determine the sub-network type of each sub-network based on the branch topological relationship of each sub-network; simplify the sub-network based on the sub-network type of each sub-network, and the wind distribution nodes and wind collection nodes corresponding to each sub-network to obtain the mine ventilation network; obtain the initial state of the mine ventilation system; and establish the complete association matrix based on the initial state and the mine ventilation network.

[0012] In one implementation, the first processing module can be used to: obtain sensitivity information and importance weight corresponding to each of the branches; determine the branch weight of the branch based on the sensitivity information and the importance weight corresponding to each of the branches; use the minimum spanning tree method combined with the branch weight to obtain the corresponding minimum spanning tree; obtain the remaining tree branches corresponding to the minimum spanning tree; and determine the first target branch based on the remaining tree branches.

[0013] In an optional implementation, the first processing module can be used to: obtain the branch flow, branch flow resistance and additional resistance corresponding to each of the branches; establish a branch sensitivity equation group based on the branch flow, the branch flow resistance and the additional resistance; solve the branch sensitivity equation group to obtain the sensitivity matrix corresponding to each of the branches as the sensitivity information corresponding to each of the branches.

[0014] In one implementation, the fifth processing module can be used to: establish a branch air volume error equation matrix based on the branch air volume data, and establish a branch error equation matrix based on the branch resistance data; establish a first objective function based on the branch air volume error equation matrix, and establish a second objective function based on the branch error equation matrix; solve the first objective function to obtain wind volume adjustment data, and solve the second objective function to obtain resistance adjustment data; obtain the wind resistance adjustment data based on the wind volume adjustment data and the resistance adjustment data.

[0015] In an optional implementation, the fifth processing module can be used to: obtain element information of non-zero matrix elements in the branch wind volume error equation matrix; establish at least one element information array based on the element information; solve the first objective function based on the element information data to obtain the wind volume adjustment data.

[0016] In a third aspect, the present application proposes an electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the control method for the mine ventilation system as described in the first aspect.

[0017] In a fourth aspect, the present application proposes a computer-readable storage medium for storing instructions, which, when executed, enables the method described in the first aspect to be implemented.

[0018] In a fifth aspect, the present application proposes a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the method for controlling a mine ventilation system as described in the first aspect.

[0019] The control method, device, equipment and storage medium of the mine ventilation system provided by the present application can determine the first target branch based on the complete association matrix corresponding to the mine ventilation network diagram and the branch weight of each branch in the mine ventilation network diagram, so as to obtain the branch air volume data of each branch based on the air volume data of the first target branch, and obtain the branch resistance data of each branch based on the resistance data corresponding to the second target branch corresponding to the independent path in the mine ventilation network diagram, so as to obtain the branch wind resistance data based on the branch air volume data and the branch resistance data, and then dynamically control the mine ventilation system based on the branch resistance, air volume monitoring data and actual wind resistance data. It can realize the optimal configuration and on-demand adjustment of the ventilation system.

[0020] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0022] Figure 1 It is a flow chart of a control method of a mine ventilation system provided in an embodiment of the present application;

[0023] Figure 2 It is a flow chart of another method for controlling a mine ventilation system provided in an embodiment of the present application;

[0024] Figure 3 It is a flow chart of another method for controlling a mine ventilation system provided in an embodiment of the present application;

[0025] Figure 4 is a schematic diagram of a control scheme for a mine ventilation system provided in an embodiment of the present application;

[0026] Figure 5 It is a structural schematic diagram of a control device for a mine ventilation system provided in an embodiment of the present application;

[0027] Figure 6 is a schematic structural diagram of another control device for a mine ventilation system provided in an embodiment of the present application;

[0028] Figure 7 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0030] The following describes a control method and device for a mine ventilation system according to an embodiment of the present application with reference to the accompanying drawings.

[0031] Figure 1 Schematic diagram of a control method for a mine ventilation system provided in an embodiment of the present application. Figure 1 As shown, the method may include but is not limited to the following steps:

[0032] Step S101: Determine a first target branch based on a complete association matrix corresponding to a mine ventilation network diagram and a branch weight of each branch in the mine ventilation network diagram.

[0033] Exemplarily, based on the complete association matrix formed by the mine ventilation network diagram and the initial state of the mine ventilation network, the branch weights of each branch in the mine ventilation network diagram are combined to perform branch weight sorting, and the branch whose branch weight is greater than a preset threshold is obtained as the first target branch.

[0034] Step S102: acquiring target air volume data of a first target branch, and acquiring branch air volume data of each branch based on the target air volume data.

[0035] Exemplarily, the target air volume data of the first target branch is obtained by setting a sensor on the first target branch, and inversion is performed based on the target air volume data to obtain branch air volume data of other branches except the first target branch, and then the branch air volume data of each branch is obtained.

[0036] Step S103: Based on the complete association matrix, obtain the second target branch corresponding to the independent path in the mine ventilation network diagram.

[0037] Exemplarily, independent pathways in the mine ventilation network diagram are obtained based on the complete association matrix, and the branches corresponding to the independent pathways are used as the second target branches.

[0038] Step S104: acquiring target resistance data of the second target branch, and acquiring branch resistance data of each branch based on the target resistance data.

[0039] Exemplarily, the target resistance data of the second target branch is obtained by setting a sensor on the second target branch, and inversion is performed based on the target resistance data to obtain branch resistance data of other branches except the second target branch, thereby obtaining branch resistance data of each branch.

[0040] Step S105: Based on the branch wind volume data and the branch resistance data, obtain wind resistance adjustment data and wind resistance data of each branch.

[0041] Exemplarily, the wind resistance data of each branch is calculated based on the branch wind volume data and branch resistance data corresponding to each branch, and the branch wind volume adjustment data and branch resistance adjustment data are obtained based on the difference between the above data and the corresponding actual measurement data, and then the wind resistance adjustment data is calculated based on the branch wind volume adjustment data and the branch resistance adjustment data.

[0042] Step S106: Obtain actual wind resistance data based on the wind resistance data and the wind resistance adjustment data.

[0043] Exemplarily, the wind resistance data is corrected based on the wind resistance adjustment data to obtain actual wind resistance data.

[0044] Step S107: Dynamically control the mine ventilation system based on the branch resistance, air volume monitoring data and actual wind resistance data.

[0045] Exemplarily, the mine ventilation environment parameters are dynamically reconstructed based on the branch resistance, air volume monitoring data and actual wind resistance data, thereby dynamically controlling the mine ventilation system.

[0046] By implementing the embodiment of the present application, the first target branch can be determined based on the complete association matrix corresponding to the mine ventilation network diagram and the branch weight of each branch in the mine ventilation network diagram, so as to obtain the branch air volume data of each branch based on the air volume data of the first target branch, and obtain the branch resistance data of each branch based on the resistance data corresponding to the second target branch corresponding to the independent path in the mine ventilation network diagram, so as to obtain the branch wind resistance data based on the branch air volume data and the branch resistance data, and then dynamically control the mine ventilation system based on the branch resistance, air volume monitoring data and actual wind resistance data. It is possible to achieve the optimal configuration and on-demand adjustment of the ventilation system.

[0047] In some embodiments, the complete incidence matrix is ​​established by the following steps:

[0048] A1: Establish the initial mine ventilation network corresponding to the mine ventilation system.

[0049] A2: Divide the initial mine ventilation network into at least one sub-network.

[0050] For example, assuming that G ′ is a sub-network of the initial mine ventilation network G, then the set corresponding to the sub-connected graph can be expressed as follows:

[0051]

[0052] In the formula, E ′ is the branch set of the sub-network, V ′ is the node set of the sub-network, e i ′ is the i-th branch, v i ′ is the i-th node, n ′ =|E ′ |≥2 is the number of branches, m ′ =|V ′ |≥2 is the number of nodes, and i is a positive integer.

[0053] A3: Based on the branch topology relationship of each sub-network, determine the sub-network type of each sub-network.

[0054] Exemplarily, according to the branch topology relationship in the subnet, the subnet is divided into three types: parallel connection, series connection and angle connection.

[0055] As an example, please refer to Table 1, which is an example table of sub-node type division provided in an embodiment of the present application.

[0056] Table 1 Example of subnet node type classification

[0057]

[0058] A4: Based on the subnetwork type of each subnetwork and the wind distribution nodes and wind collection nodes corresponding to each subnetwork, the subnetwork is simplified to obtain the mine ventilation network.

[0059] A5: Get the initial state of the mine ventilation system.

[0060] Exemplarily, the ventilation resistance of the entire mine is measured to obtain the initial state of the ventilation system.

[0061] A6: Establish a complete correlation matrix based on the initial state and the mine ventilation network.

[0062] In some embodiments, the first target branch can be determined based on the weight of each branch in the mine ventilation system in multiple aspects. As an example, see Figure 2 , Figure 2 Schematic diagram of a control method for a mine ventilation system provided in an embodiment of the present application. Figure 2 As shown, the method may include but is not limited to the following steps:

[0063] Step S201: Obtain sensitivity information and importance weight corresponding to each branch.

[0064] Exemplarily, the response sensitivity information of the air volume of each branch to the change of wind resistance and the importance weight of the lane wind measurement of the lane corresponding to each branch are obtained.

[0065] In some embodiments, the sensitivity information corresponding to each branch may be obtained by the following steps:

[0066] B1: Obtain the branch flow, branch flow resistance and additional resistance corresponding to each branch.

[0067] B2: Based on branch flow, branch flow resistance and additional resistance, a group of branch sensitivity equations is established.

[0068] For example, when the wind resistance of branch j is r j The occurrence size is Δr j When the flow rate q of branch i in the ventilation network changes i A corresponding change of size Δq occurs i When |Δr j |→0 hours

[0069]

[0070] The above formula is the flow change Δq of branch i i Wind resistance change Δr relative to branch j j sensitivity, i and j are positive integers.

[0071] From this, the following branch sensitivity partial differential equations can be established:

[0072]

[0073] Where m is the number of nodes in the ventilation network, n is the number of branches in the ventilation network, c is the number of independent loops in the ventilation network, and q i is the flow rate of branch i, r j is the flow resistance of branch j, h ai is the additional resistance on branch i, is the additional resistance of branch i to the wind resistance r j The partial derivative of ki is the flow coefficient of branch i connected to node k in the ventilation network.

[0074]

[0075] Among them, b li It is the flow coefficient of branch i in independent loop l, based on the direction of the remaining branches.

[0076]

[0077] B3: Solve the branch sensitivity equation group and obtain the sensitivity matrix corresponding to each branch as the sensitivity information corresponding to each branch.

[0078] Exemplarily, by solving the branch sensitivity equation group, the sensitivity matrix of each branch can be obtained as the sensitivity information corresponding to each branch.

[0079] Step S202: Determine the branch weight of the branch based on the sensitivity information and importance weight corresponding to each branch.

[0080] Step S203: using a minimum spanning tree method in combination with branch weights to obtain a corresponding minimum spanning tree.

[0081] Exemplarily, for obtaining a weighted connectivity graph by combining the branch weights with the ventilation network graph, the Prim algorithm and the Kruskal algorithm are used to search the weighted connectivity graph to generate a minimum spanning tree.

[0082] As an example, suppose that the mine ventilation system has m nodes and n branches, where m and n are both natural numbers. The network topology diagram of the numbered mine ventilation system is G = (V, E), where V is the node set, V = {v1 , v 2 , ..., v m}, V is the node set; E is the lane set, E={e 1 , e 2 ,……,e n}. Initialized to vertex set V new ={x},

[0083] Branch Collection Where x is any node in the node set V. Prim's algorithm is used to start from a single vertex and gradually expand the number of vertices contained in the tree according to the following steps until all vertices of the ventilation network graph are covered.

[0084] C1: Select the edge with the smallest weight value in the lane set E (v i , v j ), where v i For the set V new The elements in v j V is not added to V new vertex.

[0085] It should be noted that if there are multiple edges with the same minimum weight, any one can be selected.

[0086] C2: v i Add to collection V new In the i , v j )Add to set E new middle.

[0087] C3: If V new =V, then stop and return to branch E new ; Otherwise, return to step B1.

[0088] Step S204: Obtain the remaining branches corresponding to the minimum spanning tree.

[0089] Exemplarily, for a network graph with m nodes and n edges, the number of branches of the corresponding minimum spanning tree is m-1, and the number of branches of the co-spanning tree is n-m+1.

[0090] Step S205: Determine a first target branch based on the remaining branches of the tree.

[0091] For example, if the number of branches constituting the minimum spanning tree is m-1, and the remaining branches of the minimum spanning tree are n-m+1, the branches corresponding to the alleys corresponding to the n-m+1 remaining branches are taken as the first target branches, and a wind speed sensor is set in the first target branch to realize the air volume monitoring of the entire ventilation network.

[0092] Step S206: acquiring target air volume data of the first target branch, and acquiring branch air volume data of each branch based on the target air volume data.

[0093] In the embodiments of the present application, step S206 can be implemented by any of the methods in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0094] Step S207: Based on the complete association matrix, obtain the second target branch corresponding to the independent path in the mine ventilation network diagram.

[0095] In the embodiments of the present application, step S207 can be implemented by any of the methods in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0096] Step S208: acquiring target resistance data of the second target branch, and acquiring branch resistance data of each branch based on the target resistance data.

[0097] In the embodiments of the present application, step S208 can be implemented in any of the ways in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0098] Step S209: Based on the branch wind volume data and the branch resistance data, obtain wind resistance adjustment data and wind resistance data of each branch.

[0099] In the embodiments of the present application, step S209 can be implemented in any of the ways in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0100] Step S2010: Obtain actual wind resistance data based on the wind resistance data and wind resistance adjustment data.

[0101] In the embodiments of the present application, step S2010 can be implemented in any of the ways in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0102] Step S2011: Dynamically control the mine ventilation system based on branch resistance, air volume monitoring data and actual wind resistance data.

[0103] In the embodiments of the present application, step S2011 can be implemented in any of the ways in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0104] By implementing the embodiments of the present application, the branch weight can be determined based on the sensitivity information and importance weight corresponding to each branch, and then the first target branch can be determined by using the minimum spanning tree method based on the branch weight and the complete association matrix. Thus, wind speed data can be obtained based on the detection of the first target branch. This can achieve the optimal layout of wind speed sensors in complex ventilation networks.

[0105] In some embodiments, wind resistance adjustment data can be obtained based on the branch wind volume data and branch resistance data of each branch. As an example, see Figure 3 , Figure 3 FIG. 1 is a flow chart of another method for controlling a mine ventilation system provided in an embodiment of the present application. Figure 3 As shown, the method may include but is not limited to the following steps:

[0106] Step S301: Determine a first target branch based on the complete association matrix corresponding to the mine ventilation network diagram and the branch weight of each branch in the mine ventilation network diagram.

[0107] In the embodiments of the present application, step S301 can be implemented in any of the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0108] Step S302: acquiring target air volume data of a first target branch, and acquiring branch air volume data of each branch based on the target air volume data.

[0109] In the embodiments of the present application, step S302 can be implemented by any of the methods in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0110] Step S303: Based on the complete association matrix, obtain the second target branch corresponding to the independent path in the mine ventilation network diagram.

[0111] In the embodiments of the present application, step S303 can be implemented by any of the methods in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0112] Step S304: acquiring target resistance data of the second target branch, and acquiring branch resistance data of each branch based on the target resistance data.

[0113] In the embodiments of the present application, step S304 can be implemented by any of the methods in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0114] Step S305: establishing a branch air volume error equation matrix based on the branch air volume data, and establishing a branch error equation matrix based on the branch resistance data.

[0115] For example, taking the establishment of a branch air volume error equation matrix based on the branch air volume data as an example, the vector representation of the branch air volume data is X=(X 1 , X 2 , ...X n ) T The vector of the adjusted value is expressed as X′=(X′ 1 , X′ 2 ...X′ n ) T , then the corresponding correction value vector is ΔX = X′-X. According to the wind flow law, the following m independent error equations can be established:

[0116]

[0117] The corresponding matrix form is:

[0118] AΔX=E

[0119] Where E is the unbalanced error vector, E = (E 1 , E 2 , ...E m ) T , A is a coefficient matrix of rank m×n, and m is the number of equations.

[0120] It should be noted that the specific implementation method of establishing the branch error equation matrix based on the branch resistance data may be the same as the above-mentioned method of establishing the branch air volume error equation matrix based on the branch air volume data, which will not be repeated in this application.

[0121] Step S306: establishing a first objective function based on the branch air volume error equation matrix, and establishing a second objective function based on the branch error equation matrix.

[0122] For example, as in the aforementioned step S305, if A is equal to the node independent association matrix, X represents the mass flow rate of the wind flow, then the above independent error equation is the equation number m=M-1 of the node wind volume imbalance error equation group. If A is an independent loop matrix, X represents the branch resistance, then the above independent error equation is the equation number m=(n-M+1) of the independent loop wind pressure imbalance error.

[0123] In order to obtain the correction value vector ΔX, the least squares method can be used, the Lagrange multiplier normal vector K is introduced, and the following objective function is established:

[0124]

[0125] Among them, W x is the measurement accuracy weight matrix.

[0126] Step S307: Solve the first objective function to obtain wind volume adjustment data, and solve the second objective function to obtain resistance adjustment data.

[0127] In some embodiments, solving the first objective function to obtain wind volume adjustment data may include the following steps:

[0128] D1: Get the element information of non-zero matrix elements in the branch air volume error equation matrix.

[0129] The above-mentioned element information includes at least one of the following: element value, row position of the element in the matrix, column position of the element in the matrix,

[0130] D2: Establish at least one element information array based on the element information.

[0131] For example, taking a 4-order matrix as an example, we can get:

[0132]

[0133] Arrange all non-zero elements in the matrix in the order of "first column from top to bottom, second column from top to bottom, ... last column from top to bottom" to form a one-dimensional array A = [11, 22, 42, 13, 23, 33, 14, 44], and according to the sequence position of each element in array A, generate an array B = [1, 2, 4, 1, 2, 3, 1, 4] based on the row position corresponding to each element, and generate an array C = [1, 2, 2, 3, 3, 3, 4, 4] based on the column position corresponding to each element.

[0134] D3: Solve the first objective function based on the element information data to obtain wind volume adjustment data.

[0135] Step S308: Obtain wind resistance adjustment data and wind resistance data of each branch based on the wind volume adjustment data and the resistance adjustment data.

[0136] In the embodiments of the present application, step S308 can be implemented in any of the ways in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0137] Step S309: Obtain actual wind resistance data based on the wind resistance data and wind resistance adjustment data.

[0138] In the embodiments of the present application, step S309 can be implemented in any of the ways in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0139] Step S3010: Dynamically control the mine ventilation system based on branch resistance, air volume monitoring data and actual wind resistance data.

[0140] In the embodiments of the present application, step S3010 can be implemented in any of the ways in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0141] By implementing the embodiment of the present application, a corresponding equation matrix can be established based on the branch air volume data and branch resistance data of each branch, and a corresponding objective function can be established based on the equation matrix, so as to solve the objective function to obtain air volume adjustment data and resistance adjustment data, and obtain wind resistance adjustment data based on the air volume adjustment data and resistance adjustment data. It is possible to achieve the optimal layout of wind speed sensors in complex ventilation networks.

[0142] See also Figure 4 , Figure 4 Schematic diagram of a control scheme for a mine ventilation system provided in an embodiment of the present application. Figure 4 As shown, the scheme can simplify the ventilation network based on the node type of each node of the ventilation system and the type of the subnetwork, and form a complete correlation matrix based on the simplified ventilation network combined with the initial state of the ventilation network; the sensitivity information and importance weight of each lane are normalized to obtain the weight of each branch, so as to sort the branch weights, and the residual branches of the minimum spanning tree are obtained based on the minimum spanning tree principle, and the air volume is obtained by placing sensors in the lanes corresponding to the residual branches, and then the branch air volume of each branch of the ventilation system is obtained by inversion.

[0143] An independent pathway matrix is ​​established based on the complete association matrix, and the lanes where pressure sensors are deployed are determined based on the independent pathway matrix. Based on the branch resistance obtained through monitoring, the branch resistance of each branch of the ventilation network is inverted to obtain the branch resistance. Finally, based on the branch air volume and branch resistance of each branch, the mine ventilation environment parameters are dynamically reconstructed.

[0144] See also Figure 5 , Figure 5 Schematic diagram of the structure of a control device for a mine ventilation system provided in an embodiment of the present application. Figure 5As shown, the device 500 includes: a first processing module 501, which is used to determine the first target branch based on the complete association matrix corresponding to the mine ventilation network diagram and the branch weight of each branch in the mine ventilation network diagram; a second processing module 502, which is used to obtain the target air volume data of the first target branch, and obtain the branch air volume data of each branch based on the target air volume data; a third processing module 503, which is used to obtain the second target branch corresponding to the independent path in the mine ventilation network diagram based on the complete association matrix; a fourth processing module 504, which is used to obtain the target resistance data of the second target branch, and obtain the branch resistance data of each branch based on the target resistance data; a fifth processing module 505, which is used to obtain the wind resistance adjustment data and the wind resistance data of each branch based on the branch air volume data and the branch resistance data; a sixth processing module 501, which is used to obtain the actual wind resistance data based on the wind resistance data and the wind resistance adjustment data; a control module 501, which is used to dynamically control the mine ventilation system based on the branch resistance, the air volume monitoring data and the actual wind resistance data.

[0145] In one implementation, the above device may further include a seventh processing module. As an example, see Figure 6 , Figure 6 FIG. 1 is a schematic diagram of another control scheme for a mine ventilation system provided in an embodiment of the present application. Figure 6 As shown, the device also includes a seventh processing module 608, which is used to: establish an initial mine ventilation network corresponding to the mine ventilation system; divide the initial mine ventilation network into at least one subnetwork; determine the subnetwork type of each subnetwork based on the branch topology relationship of each subnetwork; simplify the subnetwork based on the subnetwork type of each subnetwork, and the wind distribution nodes and wind collection nodes corresponding to each subnetwork to obtain the mine ventilation network; obtain the initial state of the mine ventilation system; and establish the complete association matrix based on the initial state and the mine ventilation network. Among them, Figure 6 Modules 601 to 607 in Figure 5 Modules 501 to 507 in the embodiment have the same structure and function.

[0146] In one implementation, the first processing module 501 can be used to: obtain sensitivity information and importance weight corresponding to each of the branches; determine the branch weight of the branch based on the sensitivity information and the importance weight corresponding to each of the branches; use the minimum spanning tree method combined with the branch weight to obtain the corresponding minimum spanning tree; obtain the remaining tree branches corresponding to the minimum spanning tree; and determine the first target branch based on the remaining tree branches.

[0147] In an optional implementation, the first processing module 501 can be used to: obtain the branch flow, branch flow resistance and additional resistance corresponding to each of the branches; establish a branch sensitivity equation group based on the branch flow, the branch flow resistance and the additional resistance; solve the branch sensitivity equation group to obtain the sensitivity matrix corresponding to each of the branches as the sensitivity information corresponding to each of the branches.

[0148] In one implementation, the fifth processing module 505 can be used to: establish a branch air volume error equation matrix based on the branch air volume data, and establish a branch error equation matrix based on the branch resistance data; establish a first objective function based on the branch air volume error equation matrix, and establish a second objective function based on the branch error equation matrix; solve the first objective function to obtain wind volume adjustment data, and solve the second objective function to obtain resistance adjustment data; obtain the wind resistance adjustment data based on the wind volume adjustment data and the resistance adjustment data.

[0149] In an optional implementation, the fifth processing module 505 can be used to: obtain element information of non-zero matrix elements in the branch wind volume error equation matrix; establish at least one element information array based on the element information; solve the first objective function based on the element information data to obtain the wind volume adjustment data.

[0150] Through the device of the embodiment of the present application, the first target branch can be determined based on the complete association matrix corresponding to the mine ventilation network diagram and the branch weight of each branch in the mine ventilation network diagram, so as to obtain the branch air volume data of each branch based on the air volume data of the first target branch, and obtain the branch resistance data of each branch based on the resistance data corresponding to the second target branch corresponding to the independent path in the mine ventilation network diagram, so as to obtain the branch wind resistance data based on the branch air volume data and the branch resistance data, and then dynamically control the mine ventilation system based on the branch resistance, the air volume monitoring data and the actual wind resistance data. It is possible to achieve on-demand adjustment of the ventilation system.

[0151] It should be noted that the aforementioned explanation of the embodiment of the control method for a mine ventilation system is also applicable to the control device for the mine ventilation system of this embodiment, and will not be repeated here.

[0152] In order to implement the above embodiment, the present application also proposes an electronic device. Figure 7 , Figure 7 Schematic diagram of the structure of the electronic device provided in the embodiment of the present application. Figure 7As shown, the electronic device 700 includes: a processor 701, and a memory 702 communicatively connected to the processor 701; the memory 702 stores computer-executable instructions; the processor 701 executes the computer-executable instructions stored in the memory to implement the method provided in the aforementioned embodiment.

[0153] In order to implement the above embodiments, the present application also proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the methods provided by the above embodiments.

[0154] In the description of this application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; “and / or” in this article is merely a way to describe the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0155] In the description of the aforementioned embodiments, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0156] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0157] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0158] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0159] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0160] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0161] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0162] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A control method for a mine ventilation system, characterized in that: include: Determine a first target branch based on a complete association matrix corresponding to the mine ventilation network diagram and a branch weight of each branch in the mine ventilation network diagram; Acquire target air volume data of the first target branch, and acquire branch air volume data of each of the branches based on the target air volume data; Based on the complete association matrix, obtaining a second target branch corresponding to an independent path in the mine ventilation network diagram; Acquire target resistance data of the second target branch, and acquire branch resistance data of each of the branches based on the target resistance data; Based on the branch wind volume data and the branch resistance data, obtaining wind resistance adjustment data and wind resistance data of each branch; Based on the wind resistance data and the wind resistance adjustment data, actual wind resistance data is obtained; Based on the branch resistance, the air volume monitoring data and the actual wind resistance data, the mine ventilation system is dynamically controlled.

2. The method according to claim 1, characterized in that The complete incidence matrix is ​​established by the following steps: Establishing an initial mine ventilation network corresponding to the mine ventilation system; dividing the initial mine ventilation network into at least one sub-network; Determining a subnetwork type of each subnetwork based on a branch topology relationship of each subnetwork; Simplifying the subnetwork based on the subnetwork type of each subnetwork and the wind distribution node and wind collection node corresponding to each subnetwork to obtain the mine ventilation network; Obtaining an initial state of the mine ventilation system; The complete incidence matrix is ​​established based on the initial state and the mine ventilation network.

3. The method according to claim 1, characterized in that The determining of the first target branch based on the complete association matrix corresponding to the mine ventilation network diagram and the branch weight of each branch in the mine ventilation network diagram comprises: Obtaining sensitivity information and importance weight corresponding to each of the branches; Determine the branch weight of the branch based on the sensitivity information and the importance weight corresponding to each branch; Using a minimum spanning tree method in combination with the branch weights to obtain a corresponding minimum spanning tree; Obtain the remaining tree branches corresponding to the minimum spanning tree; Based on the remaining branches of the tree, the first target branch is determined.

4. The method according to claim 3, characterized in that The obtaining the sensitivity information corresponding to each of the branches includes: Obtaining the branch flow, branch flow resistance and additional resistance corresponding to each branch; Establishing a branch sensitivity equation group based on the branch flow, the branch flow resistance and the additional resistance; The branch sensitivity equation group is solved to obtain a sensitivity matrix corresponding to each branch as sensitivity information corresponding to each branch.

5. The method according to claim 1, characterized in that The step of obtaining wind resistance adjustment data based on the branch wind volume data and the branch resistance data comprises: Establishing a branch air volume error equation matrix based on the branch air volume data, and establishing a branch error equation matrix based on the branch resistance data; Establishing a first objective function based on the branch air volume error equation matrix, and establishing a second objective function based on the branch error equation matrix; Solving the first objective function to obtain wind volume adjustment data, and solving the second objective function to obtain resistance adjustment data; The wind resistance adjustment data is obtained based on the wind volume adjustment data and the resistance adjustment data.

6. The method according to claim 5, characterized in that The step of solving the first objective function to obtain wind volume adjustment data includes: Obtaining element information of non-zero matrix elements in the branch air volume error equation matrix; Establish at least one element information array based on the element information; The first objective function is solved based on the element information data to obtain the wind volume adjustment data.

7. A control device for a mine ventilation system, characterized in that: include: A first processing module is used to determine a first target branch based on a complete association matrix corresponding to a mine ventilation network diagram and a branch weight of each branch in the mine ventilation network diagram; A second processing module, configured to obtain target air volume data of the first target branch, and obtain branch air volume data of each of the branches based on the target air volume data; A third processing module is used to obtain a second target branch corresponding to an independent path in the mine ventilation network diagram based on the complete association matrix; a fourth processing module, configured to obtain target resistance data of the second target branch, and obtain branch resistance data of each of the branches based on the target resistance data; A fifth processing module, configured to obtain wind resistance adjustment data and wind resistance data of each branch based on the branch wind volume data and the branch resistance data; A sixth processing module, configured to obtain actual wind resistance data based on the wind resistance data and the wind resistance adjustment data; A control module is used to dynamically control the mine ventilation system based on the branch resistance, the air volume monitoring data and the actual wind resistance data.

8. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that The method comprises a computer program, which implements the method according to any one of claims 1 to 6 when being executed by a processor.

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