Parameter monitoring point determination method and device, electronic equipment and storage medium

Abstract

The invention provides a parameter monitoring point determination method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a ventilation network diagram, numbering nodes and branches contained in the ventilation network diagram, and obtaining a node identifier set, a branch identifier set, and a topological relation between node identifiers and branch identifiers; according to the wind measurement importance level and the wind resistance sensitivity degree corresponding to each branch, determining the weight corresponding to the branch; determining a first branch forming a minimum spanning tree corresponding to the ventilation network diagram based on the topological relation and the weight; determining a second branch in the ventilation network diagram according to the identifier of the first branch and the branch identifier set; and determining the position of each second branch in the ventilation network diagram as an air volume parameter monitoring point. Therefore, the underground air flow parameter monitoring equipment can be reasonably and effectively arranged, the monitoring cost is reduced, and support is provided for improving the monitoring efficiency of air flow parameters, the real-time calculation capability of a ventilation network and the like.

Description

Technical Field

[0001] The present application relates to the technical field of coal mine underground ventilation environment parameter monitoring, and in particular to a method, device, electronic equipment and storage medium for determining parameter monitoring points. Background Art

[0002] The main task of the mine ventilation environment parameter monitoring system is to monitor the basic airflow parameters (such as air volume, resistance, etc.) of each tunnel in the ventilation network, and to invert the ventilation status of the entire mine in real time to ensure the safe and stable operation of the ventilation system.

[0003] However, when designing a ventilation environment parameter monitoring system, how to determine the installation location and number of sensors has always been a difficult problem to solve. If the number of sensors installed is too small, it is easy to fail to obtain complete and accurate information to effectively monitor the underground air volume. If the number of sensors is too large, it will increase the difficulty of safety management and operating costs, and affect the monitoring efficiency of the monitoring system. Therefore, a method for determining parameter monitoring points is needed to determine the minimum number of sensors and the optimal point arrangement that can cover the parameter monitoring of the entire ventilation network, save operating costs, and improve efficiency. Summary of the invention

[0004] The present application aims to solve one of the technical problems in the related art at least to some extent.

[0005] To this end, the first purpose of this application is to propose a method for determining parameter monitoring points so as to determine the optimal number and location of underground wind flow parameter monitoring equipment, reduce monitoring costs, and provide support for improving the monitoring efficiency of wind flow parameters and the real-time solution capabilities of ventilation networks.

[0006] The second objective of the present application is to provide a device for determining parameter monitoring points.

[0007] The third objective of the present application is to provide an electronic device.

[0008] A fourth objective of the present application is to provide a computer-readable storage medium.

[0009] A fifth object of the present application is to provide a computer program product.

[0010] To achieve the above-mentioned purpose, the first embodiment of the present application proposes a method for determining a parameter monitoring point, including:

[0011] Acquire a ventilation network graph, number the nodes and branches contained in the ventilation network graph, obtain a node identification set, a branch identification set, and a topological relationship between the node identifications and the branch identifications, wherein the node identification set includes a first number of nodes, and the branch identification set includes a second number of branches;

[0012] Determine the weight corresponding to each branch according to the wind measurement importance level and wind resistance sensitivity corresponding to each branch;

[0013] Based on the topological relationship and the weight, determining a first branch constituting a minimum spanning tree corresponding to the ventilation network graph, wherein the number of the first branches is the first number minus 1;

[0014] Determining, according to the identifier of the first branch and the branch identifier set, a second branch in the ventilation network diagram, wherein the number of the second branches is the second number minus the number of the first branches;

[0015] The position of each of the second branches in the ventilation network diagram is determined as an air volume parameter monitoring point.

[0016] To achieve the above-mentioned purpose, the second embodiment of the present application proposes a device for determining parameter monitoring points, including:

[0017] A first acquisition module is used to acquire a ventilation network diagram, number the nodes and branches contained in the ventilation network diagram, and obtain a node identification set, a branch identification set, and a topological relationship between the node identifications and the branch identifications, wherein the node identification set includes a first number of nodes, and the branch identification set includes a second number of branches;

[0018] A first determination module is used to determine the weight corresponding to each branch according to the wind measurement importance level and wind resistance sensitivity corresponding to each branch;

[0019] A second determination module is used to determine, based on the topological relationship and the weight, a first branch constituting a minimum spanning tree corresponding to the ventilation network graph, wherein the number of the first branches is the first number minus 1;

[0020] A third determination module is used to determine the second branches in the ventilation network diagram according to the identifier of the first branch and the branch identifier set, wherein the number of the second branches is the second number minus the number of the first branches;

[0021] The fourth determination module is used to determine the position of each second branch in the ventilation network diagram as an air volume parameter monitoring point.

[0022] To achieve the above-mentioned purpose, the third aspect of the present application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0023] The memory stores computer-executable instructions;

[0024] The processor executes the computer-executable instructions stored in the memory to implement the method for determining parameter monitoring points as described in the embodiment of the first aspect.

[0025] To achieve the above-mentioned purpose, the fourth aspect embodiment of the present application proposes a computer-readable storage medium, in which computer execution instructions are stored. When the computer execution instructions are executed by a processor, they are used to implement the method for determining parameter monitoring points as described in the first aspect embodiment.

[0026] To achieve the above-mentioned purpose, the fifth aspect of the present application proposes a computer program product, including a computer program, which, when executed by a processor, implements the method for determining parameter monitoring points as described in the first aspect of the embodiment.

[0027] The parameter monitoring point determination method, device, electronic device and storage medium provided in the present application determine the number and positions of branches other than the minimum spanning tree in a weighted ventilation network diagram, and then determine the minimum number of sensors that need to be installed in the ventilation system and the optimal monitoring point locations, so that the underground wind flow parameter monitoring equipment can be arranged more reasonably, which can effectively reduce the monitoring cost and provide support for improving the monitoring efficiency of wind flow parameters and the real-time solution capability of the ventilation network.

[0028] 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

[0029] 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:

[0030] Figure 1 A flow chart of a method for determining parameter monitoring points provided in an embodiment of the present application;

[0031] Figure 2 A flow chart of another method for determining parameter monitoring points provided in an embodiment of the present application;

[0032] Figure 3 A schematic diagram of a flow chart of another method for determining parameter monitoring points provided in an embodiment of the present application;

[0033] Figure 4 A schematic diagram of the structure of a device for determining parameter monitoring points provided in an embodiment of the present application. DETAILED DESCRIPTION

[0034] The 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.

[0035] The following describes the method and device for determining parameter monitoring points in an embodiment of the present application with reference to the accompanying drawings.

[0036] Figure 1 A flow chart of a method for determining parameter monitoring points provided in an embodiment of the present application.

[0037] like Figure 1 As shown, the method for determining the parameter monitoring point includes the following steps:

[0038] Step 101, obtain a ventilation network diagram, number the nodes and branches contained in the ventilation network diagram, and obtain a node identifier set, a branch identifier set, and a topological relationship between the node identifiers and the branch identifiers.

[0039] Among them, nodes refer to the connection points and ventilation shafts between lanes in the ventilation system, and each node can be connected to at least one branch. Branches refer to lanes in the ventilation system, which can be directed line segments in the ventilation network diagram. The direction of the line segment indicates the direction of the airflow in the lane.

[0040] The node identification set includes a first number of nodes, and the branch identification set includes a second number of branches.

[0041] In an embodiment of the present application, a mine ventilation network diagram can be drawn for any mine ventilation system, or a ventilation network diagram of the mine ventilation system during design and construction can be directly obtained. After obtaining the ventilation network diagram, all nodes and branches in the ventilation network diagram are numbered respectively to obtain a node identification set and a branch identification set. And based on the connection relationship between nodes and branches, a topological relationship between node identification and branch identification can be constructed, and the topological relationship can be described by a complete association matrix.

[0042] For example, the mine ventilation system has m nodes and n branches, where m and n are both natural numbers. Number the nodes and branches in the ventilation network graph G = (V, E) of the mine ventilation system to obtain a node identification set V = {v1, v2, ..., v m}, and the branch identification set E = {e1, e2, ..., e n}.

[0043] It should be noted that after obtaining the ventilation network diagram and initializing the state of the ventilation system, the ventilation network can be simplified by utilizing basic network connection forms (such as series, parallel and diagonal connection, etc.) and special structures or transformation forms (such as triangle, star and Y type, etc.), which makes it easier to determine its corresponding topological relationship.

[0044] Step 102: Determine the weight corresponding to each branch according to the wind measurement importance level and wind resistance sensitivity corresponding to the branch.

[0045] The importance level of wind measurement can be determined based on the degree of influence of the wind flow state of each lane on the entire ventilation system, or by the empirical judgment of experts. The wind resistance sensitivity refers to the sensitivity of the flow change in each lane to the wind resistance change of other branches. It can be determined by calculating using historical wind flow parameter values. Under a specific ventilation system state, the wind resistance sensitivity corresponding to each lane is fixed.

[0046] In the embodiment of the present application, since the sensors should be arranged at the characteristic position of the parameter to be monitored, the measurement value or the position with a large gradient, the weight corresponding to the branch can be determined according to the wind measurement importance level and wind resistance sensitivity corresponding to each branch. The wind measurement importance level is proportional to the weight, and the higher the importance level, the higher the weight; the wind resistance sensitivity is also proportional to the weight, and the higher the sensitivity, the higher the weight.

[0047] Step 103: Determine the first branch of the minimum spanning tree corresponding to the ventilation network graph based on the topological relationship and the weight.

[0048] The number of the first branches is the first number minus 1.

[0049] In an embodiment of the present application, in a ventilation network diagram, a minimum spanning tree that passes through all nodes and has the smallest sum of branch weights connecting all nodes can be determined based on the topological relationship between each node and branch, and each branch constituting the minimum spanning tree is a first branch.

[0050] It should be noted that, in the present application, the minimum spanning tree of the ventilation network graph may be searched by any one of the Prim algorithm, Kruskal algorithm, edge cut method, Dijkstra algorithm and the like.

[0051] For example, the essence of Prim's algorithm is a greedy algorithm: starting from any node in the ventilation network graph, the next node selected each time is the other end point of the branch with the smallest weight among all candidate branches connected to the current node, until all vertices are selected. That is, for a weighted connected graph G = (V, E), initialized to the node set V new ={x}, branch set Enew is an empty set, where x is any node in the set V (starting node). Prim's algorithm starts from this node and gradually expands the number of nodes contained in the tree according to the following steps until all nodes in the connected graph are covered. The process may include:

[0052] The first step is to select the branch with the smallest weight in the 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 Node (if there are multiple branches with the same minimum weight, you can choose any one);

[0053] The second step is to set v j Add to collection V new In the i , v j )Add to set E new middle;

[0054] Step 3: If V new =V, then stop and return to branch set E new , then the branch set E new All branches and nodes in V new All nodes in form a minimum spanning tree; if V new If it is not equal to V, return to the first step.

[0055] It can be understood that since the minimum spanning tree is a subgraph of all nodes in the ventilation network graph, it contains the minimum number of branches while ensuring that all nodes are connected. Therefore, in a graph with m nodes, to ensure that all nodes are connected, at least m-1 branches are required, and the number of the first branch in the minimum spanning tree is the first number minus 1.

[0056] Step 104: Determine a second branch in the ventilation network diagram according to the identifier of the first branch and the branch identifier set.

[0057] The second branch is a branch other than the first branch of the minimum spanning tree in the ventilation network diagram, and can also be called a residual branch or residual branch. The number of the second branches is the second number minus the number of the first branches.

[0058] In the embodiment of the present application, according to the identifier of the first branch used to constitute the minimum spanning tree, in the branch identifier set corresponding to the ventilation network diagram, the branch identifier that is not the first branch can be screened and determined as the second branch.

[0059] For example, for a ventilation network graph with m nodes and n branches, the number of first branches constituting its minimum spanning tree is m-1, and the number of second branches is n-(m-1)=n-m+1.

[0060] Step 105: determine the position of each second branch in the ventilation network diagram as an air volume parameter monitoring point.

[0061] In the embodiment of the present application, since the weight of the second branch is relatively high, it is necessary to directly use the sensor to monitor the air volume in order to ensure the reliability of the parameter monitoring results, and each second branch can form a loop network structure with the first branch in the minimum spanning tree, so the air volume at all first branches can be calculated by the air volume at the second branch through the node air volume balance law. Therefore, in the present application, the position of each second branch in the ventilation network diagram can be determined as an air volume parameter monitoring point.

[0062] For example, for a ventilation network diagram with m nodes and n branches, the number of second branches is n-(m-1)=n-m+1, then (n-m+1) air volume parameter monitoring points can be determined in the ventilation network diagram, and the position of each second branch in the ventilation network diagram is an air volume parameter monitoring point.

[0063] Optionally, the second branch air volume monitored by the sensor at each air volume parameter monitoring point can be obtained, and then the air volume of each first branch can be calculated based on the ventilation network diagram and the second branch air volume using the air volume balance law. This can achieve air volume monitoring of the entire lane in the ventilation network, improve monitoring efficiency, and reduce monitoring costs.

[0064] In this embodiment, the ventilation network diagram is first obtained, and the nodes and branches contained in the ventilation network diagram are numbered to obtain a node identification set, a branch identification set, and a topological relationship between the node identification and the branch identification. Then, according to the wind measurement importance level and wind resistance sensitivity corresponding to each branch, the weight corresponding to the branch is determined, and based on the topological relationship and weight, the first branch constituting the minimum spanning tree corresponding to the ventilation network diagram is determined. After that, according to the identification of the first branch and the branch identification set, the second branch in the ventilation network diagram is determined, and the position of each second branch in the ventilation network diagram is determined as an air volume parameter monitoring point. Therefore, by determining the number and position of branches other than the minimum spanning tree in the weighted ventilation network diagram, and then determining the minimum number of sensors that need to be installed in the ventilation system and the optimal monitoring point position, the underground wind flow parameter monitoring equipment can be arranged more reasonably, which can effectively reduce the monitoring cost, and provide support for improving the monitoring efficiency of wind flow parameters and the real-time solution capability of the ventilation network.

[0065] Figure 2A flowchart of another method for determining parameter monitoring points provided in an embodiment of the present application.

[0066] like Figure 2 As shown, the method for determining the parameter monitoring point may include the following steps:

[0067] Step 201 , obtaining a ventilation network diagram, numbering the nodes and branches contained in the ventilation network diagram, and obtaining a node identifier set, a branch identifier set, and a topological relationship between the node identifiers and the branch identifiers.

[0068] For a detailed description of the above step 201, please refer to other embodiments of the present disclosure and will not be repeated here.

[0069] Step 202: Determine the wind measurement importance level corresponding to each branch according to the type of each branch.

[0070] The type of branch can refer to the connection form of the branch with other branches in the ventilation network (such as series connection, parallel connection, angle connection, etc.), or it can also refer to the function of the branch in the ventilation system (such as main air inlet lane, return air lane, auxiliary lane, etc.).

[0071] In the embodiment of the present application, the wind measurement importance level corresponding to the branch can be determined according to whether the wind flow state of different types of branches in the actual mine environment has a decisive influence on the ventilation effect of the overall system. Alternatively, the wind measurement importance level corresponding to each branch can be set according to the lanes where the air volume must be monitored as stipulated by mine safety and other regulations.

[0072] Step 203, determining the wind resistance sensitivity of the branch according to the sensitivity of the wind volume of the branch to the wind resistance change of other branches.

[0073] In the embodiment of the present application, since the change of wind resistance in any branch of the ventilation network may cause the flow change of itself and related branches or even all branches in the network, the sensitivity of the air volume of any branch to the wind resistance change of all other branches can be obtained. Afterwards, the sum, maximum value or average value of all sensitivities corresponding to any branch can be determined as the wind resistance sensitivity corresponding to the branch.

[0074] It should be noted that in the present application, the sensitivity of the air volume of each branch to the change of wind resistance of other branches can be obtained by calculating the sensitivity matrix of each branch in the ventilation network. The sensitivity matrix is ​​an inherent property of the ventilation system. Under a specific ventilation system state, the sensitivity matrix is ​​uniquely determined. It is only related to the ventilation network structure and the state of the system, and has nothing to do with the selection of independent loops. Under a certain state, the elements in the sensitivity matrix can be positive or negative, large or small. The positive or negative value reflects the structure of the ventilation network. The absolute value of the sensitivity reflects the sensitivity of the branch air volume to the change of branch wind resistance. The larger the absolute value, the greater the response of the branch air volume to the change of branch wind resistance.

[0075] Optionally, the first flow direction coefficient between the branch and each node may be determined based on the topological relationship of the ventilation network and the first wind flow direction of each branch.

[0076] In the embodiment of the present application, the calculation formula of the first flow coefficient is shown in the following formula (1):

[0077]

[0078] Among them, k = 1, 2, ..., m, m is the number of nodes in the network, i = 1, 2, ..., n, n is the number of branches in the network.

[0079] That is to say, when the first wind flow direction of branch i points to node k, it can be determined that the fluid of branch i flows into node k, and the first flow coefficient between branch i and node k is 1. When the first wind flow direction of branch i does not point to node k, it can be determined that the fluid of branch i flows out of node k, and the first flow coefficient between branch i and node k is -1. When it can be seen from the topological relationship of the ventilation network that branch i is not connected to node k, the first flow coefficient between branch i and node k is 0.

[0080] Then, based on the topological relationship of the ventilation network, independent loops in the ventilation network and the first branch and the second branch contained in each independent loop are determined.

[0081] In an embodiment of the present application, the minimum spanning tree in the ventilation network and a co-branch (i.e., the second branch) can be combined into an independent loop, so the number of independent loops in the ventilation network is equal to the number of second branches, and each independent loop can contain all the first branches and one second branch.

[0082] Then, in each independent loop, based on the first wind flow direction of the first branch and the second wind flow direction of the second branch, a second flow direction coefficient of each first branch in the independent loop is determined.

[0083] In the embodiment of the present application, the calculation formula of the second flow coefficient is shown in the following formula (2):

[0084]

[0085] Wherein, l=1, 2, ..., c, c is the number of independent loops in the network, and the positive and negative directions are based on the second wind flow direction of the second branch in the independent loop.

[0086] That is, when the first wind flow direction of any branch i is the same as the second wind flow direction of the second branch in a certain independent loop l, it can be determined that the flow direction of the branch i in the independent loop l is positive, and the second flow coefficient is 1; or, when the first wind flow direction of any branch i is opposite to the second wind flow direction of the second branch in the independent loop l, it can be determined that the flow direction of the branch i in the independent loop l is negative, and the second flow coefficient is -1. Alternatively, there may be a situation where branch i is the second branch and the independent loop l does not include branch i, in which case the second flow coefficient is 0.

[0087] Afterwards, the reference air volume, reference fluid resistance and reference additional resistance corresponding to all branches in the ventilation network at any historical moment are obtained, and then a first set of equations is constructed based on the first quantity, the second quantity, the reference air volume, the reference fluid resistance, the reference additional resistance, the first flow coefficient and the second flow coefficient.

[0088] The first set of equations is shown in equation (3):

[0089]

[0090] Where i = 1, 2, ..., n; j = 1, 2, ..., n; k = 1, 2, ..., m; l = 1, 2, ..., c; m is the number of nodes in the network; n is the number of branches in the network; c is the number of independent loops in the network; q i is the reference flow of branch i; r j is the reference fluid resistance of branch j; h ai Add resistance to the reference on branch i; The reference additional resistance of branch i to the reference flow resistance r j The partial derivative of . ki is the first flow coefficient of the i-th branch connected to the k-th node in the network. li is the second flow coefficient of branch i in independent loop l.

[0091] It should be noted that when the wind resistance of a branch is j Δr occurs j When the flow rate q of any branch i in the network changes i A Δq also occurs accordingly i , then when |Δr j When | approaches 0, the flow change of branch i is Δqi Wind resistance change Δr relative to branch j j The sensitivity can be expressed as follows:

[0092]

[0093] Therefore, by solving the first set of equations, the sensitivity of the air volume of each branch to the change of wind resistance of other branches can be obtained.

[0094] Step 204 , normalize the wind measurement importance level and wind resistance sensitivity to obtain the weight corresponding to the branch.

[0095] In an embodiment of the present application, in order to avoid the influence of the dimensions of the wind measurement importance level and the wind resistance sensitivity level on the weight, the wind measurement importance level and the wind resistance sensitivity level can be normalized, and then based on the normalized result, the wind measurement importance level and the wind resistance sensitivity level of each branch are comprehensively considered to obtain the weight corresponding to the branch.

[0096] Step 205: Determine the first branch of the minimum spanning tree corresponding to the ventilation network graph based on the topological relationship and the weight.

[0097] Step 206: Determine the second branch in the ventilation network diagram according to the identifier of the first branch and the branch identifier set.

[0098] Step 207: determine the position of each second branch in the ventilation network diagram as an air volume parameter monitoring point.

[0099] For detailed description of the above steps 205 to 207, please refer to other embodiments of the present disclosure and will not be repeated here.

[0100] In this embodiment, the wind measurement importance level corresponding to the branch is first determined according to the type of each branch, and the wind resistance sensitivity corresponding to the branch is determined according to the sensitivity of the branch wind volume to the wind resistance change of other branches, and then the wind measurement importance level and wind resistance sensitivity are normalized to obtain the weight corresponding to the branch. Therefore, by calculating the branch weight based on the type of each branch and the sensitivity of the branch wind volume to the wind resistance change of other branches, the branch weight is reasonable and reliable, which provides conditions for improving the accuracy of parameter monitoring point determination.

[0101] This embodiment also provides another method for determining parameter monitoring points. Figure 3 A flowchart of another method for determining parameter monitoring points provided in an embodiment of the present application.

[0102] like Figure 3 As shown, the method for determining the parameter monitoring point may include the following steps:

[0103] Step 301 , obtaining a ventilation network diagram, numbering the nodes and branches contained in the ventilation network diagram, and obtaining a node identifier set, a branch identifier set, and a topological relationship between the node identifiers and the branch identifiers.

[0104] For a detailed description of the above step 301, please refer to the above embodiments of the present disclosure, which will not be repeated here.

[0105] Step 302: Determine the number of independent pathways in the ventilation network and the branch identifiers contained in each independent pathway according to the topological structure of the ventilation network graph.

[0106] In the embodiment of the present application, the independent path can be searched by depth-first search method according to the topological structure of the ventilation network diagram. The independent path refers to a non-repeated path from the air inlet point to the air outlet point in the ventilation network. Therefore, in the process of searching for independent paths, the independent paths determined later need to contain at least one branch that the independent paths determined earlier do not contain.

[0107] It should be noted that in the ventilation network diagram, each second branch that is not included in the minimum spanning tree can be regarded as part of a potential independent path, so when each second branch is combined with a branch in the minimum spanning tree, a new independent path can be formed. And the fan plays a role in promoting air flow in the ventilation network. When adding fans, new wind flow paths and possible independent paths will be introduced. Therefore, in this application, the number of independent paths in the ventilation network is the number of second branches plus the number of fans in the ventilation system.

[0108] For example, for a ventilation network diagram including m nodes and n branches, and the preset number of fans is L, the number of independent channels is n-m+1+L.

[0109] Step 303: construct an independent path matrix based on the number of independent paths, the second number, and the branch identifiers included in each independent path.

[0110] In an embodiment of the present application, an independent path matrix with the number of independent paths rows and the second number of columns can be constructed, and each element in the independent path matrix is ​​used to represent whether the a-th (a is a natural number, and the maximum value is the number of independent paths) independent path contains the b-th (b is a natural number, and the maximum value is the second number) branch. If it is included, the element value is 1, and if it is not included, the element value is 0.

[0111] Step 304: construct a second set of equations based on the independent passage matrix and the preset pressure value of the fan.

[0112] In the embodiment of the present application, a non-homogeneous linear equation system (i.e., the second equation system) PH=H can be constructed. f, where P is the independent channel matrix, H is the coefficient matrix to be determined (representing the pressure on each branch), and f is the known pressure of the preset fan.

[0113] Step 305, solving the second system of equations to determine the rank of the second system of equations.

[0114] In the embodiment of the present application, after performing row transformation simplification on the matrix of the second set of equations, it can be determined that the rank of the coefficient matrix of the second set of equations is the same as the rank of the augmented matrix, and the value of the rank is equal to the number of independent paths.

[0115] Step 306, calculating the difference between the second quantity and the rank, randomly selecting branches of the difference quantity in the ventilation network diagram, and determining the position of each branch as a resistance parameter monitoring point.

[0116] For example, the rank of the second equation group is n-m+1+L. Since n-m+1+L is less than n, it can be said that the original second equation group has infinite solutions. And it can be determined that the number of free unknown branches in the second equation group is n-(n-m+1+L)=m-1-L, so m-1-L branches can be randomly selected from all branches as unknown quantities to be monitored, and the position of each branch is determined as a resistance parameter monitoring point, so that full coverage of ventilation network resistance without blind spots can be achieved.

[0117] Optionally, the branch resistance monitored by the sensor at each resistance parameter monitoring point can be obtained first, and then, according to the branch identifier corresponding to the branch resistance, each branch resistance can be substituted into the unknown quantity corresponding to the branch identifier in the second set of equations, and then the second set of equations can be solved to obtain the branch resistances corresponding to other branches respectively.

[0118] In this embodiment, first, according to the topological structure of the ventilation network diagram, the number of independent passages in the ventilation network and the branch identifiers contained in each independent passage are determined. Then, based on the number of independent passages, the second number and the branch identifiers contained in each independent passage, an independent passage matrix is ​​constructed. After that, based on the independent passage matrix and the pressure value of the preset fan, a second set of equations is constructed, and the second set of equations is solved to determine the rank of the second set of equations. After that, the difference between the second number and the rank is calculated, and the number of branches of the difference number in the ventilation network diagram is randomly selected, and the position of each branch is determined as a resistance parameter monitoring point. Thus, by solving the rank of the coefficient matrix for the set of equations constructed by the independent passage matrix in the ventilation network diagram, the number of branches that need to measure the resistance is determined according to the difference between the rank and the total number of branches, and then the positions of the corresponding number of branches are randomly selected as resistance parameter monitoring points, which can make the number of underground wind flow parameter monitoring equipment more optimal, can effectively reduce the monitoring cost, and provide support for improving the monitoring efficiency of wind flow parameters and the real-time solution capability of the ventilation network.

[0119] In order to implement the above embodiment, the present application also proposes a device for determining parameter monitoring points.

[0120] Figure 4 A schematic diagram of the structure of a device for determining parameter monitoring points provided in an embodiment of the present application.

[0121] like Figure 4 As shown, the parameter monitoring point determination device 400 includes:

[0122] The first acquisition module 401 is used to acquire a ventilation network diagram, number the nodes and branches contained in the ventilation network diagram, and obtain a node identification set, a branch identification set, and a topological relationship between the node identifications and the branch identifications, wherein the node identification set includes a first number of nodes, and the branch identification set includes a second number of branches;

[0123] A first determination module 402 is used to determine the weight corresponding to each branch according to the wind measurement importance level and wind resistance sensitivity corresponding to the branch;

[0124] The second determination module 403 is used to determine the first branch of the minimum spanning tree corresponding to the ventilation network diagram based on the topological relationship and the weight, wherein the number of the first branches is the first number minus 1;

[0125] A third determination module 404 is used to determine the second branch in the ventilation network diagram according to the identifier of the first branch and the branch identifier set, wherein the number of the second branches is the second number minus the number of the first branches;

[0126] The fourth determination module 405 is used to determine the position of each second branch in the ventilation network diagram as an air volume parameter monitoring point.

[0127] Optionally, the fourth determining module 405 may also be used to:

[0128] Obtaining the second branch air volume monitored by the sensor at each air volume parameter monitoring point;

[0129] According to the ventilation network diagram and the air volume of the second branch, use the air volume balance law to calculate the air volume of each first branch.

[0130] Optionally, the first determining module 402 may be specifically configured to:

[0131] According to the type of branch, determine the wind measurement importance level corresponding to the branch;

[0132] According to the sensitivity of the wind volume of the branch to the wind resistance change of other branches, the wind resistance sensitivity of the branch is determined;

[0133] The importance level of wind measurement and the sensitivity of wind resistance are normalized to obtain the weights corresponding to the branches.

[0134] Optionally, the first determining module 402 may also be used to:

[0135] According to the topological relationship of the ventilation network diagram and the first wind flow direction of each branch, a first flow direction coefficient between the branch and each node is determined;

[0136] Based on the topological relationship of the ventilation network, determining independent loops in the ventilation network, and a first branch and a second branch included in each independent loop;

[0137] In each independent loop, based on the first wind flow direction of the first branch and the second wind flow direction of the second branch, determine the second flow direction coefficient of each first branch in the independent loop;

[0138] Obtain the reference air volume, reference fluid resistance and reference additional resistance corresponding to all branches in the ventilation network at any historical moment;

[0139] Constructing a first set of equations based on the first quantity, the second quantity, the reference air volume, the reference fluid resistance, the reference additional resistance, the first flow coefficient, and the second flow coefficient;

[0140] The first set of equations is solved to obtain the sensitivity of the air volume of each branch to the change of wind resistance of other branches.

[0141] Optionally, the parameter monitoring point determination device 400 may further include:

[0142] A fifth determination module is used to determine the number of independent pathways in the ventilation network and the branch identifiers contained in each independent pathway according to the topological structure of the ventilation network graph;

[0143] A first generating module is used to construct an independent pathway matrix based on the number of independent pathways, the second number, and branch identifiers included in each independent pathway;

[0144] A second generation module is used to construct a second set of equations based on the independent channel matrix and a preset pressure value of the fan;

[0145] A sixth determination module solves the second set of equations to determine the rank of the second set of equations;

[0146] The seventh determination module calculates the difference between the second quantity and the rank, randomly selects branches of the difference quantity in the ventilation network diagram, and determines the position of each branch as a resistance parameter monitoring point.

[0147] Optionally, the seventh determining module may also be used to:

[0148] Obtaining the branch resistance monitored by the sensor at each resistance parameter monitoring point;

[0149] According to the branch identification corresponding to the branch resistance, the branch resistance is substituted into the second set of equations to obtain the branch resistances corresponding to other branches respectively.

[0150] It should be noted that the above explanation of the embodiment of the method for determining parameter monitoring points is also applicable to the device for determining parameter monitoring points of this embodiment, and will not be repeated here.

[0151] In this embodiment, by determining the number and positions of branches other than the minimum spanning tree in the weighted ventilation network diagram, and then determining the minimum number of sensors that need to be installed in the ventilation system and the optimal monitoring point locations, the underground wind flow parameter monitoring equipment can be arranged more reasonably, which can effectively reduce the monitoring cost and provide support for improving the monitoring efficiency of wind flow parameters and the real-time solution capability of the ventilation network.

[0152] In order to implement the above embodiments, the present application also proposes an electronic device, including: a processor, and a memory connected to the processor for communication; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method for determining parameter monitoring points provided in the above embodiments.

[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 method for determining parameter monitoring points provided in the above embodiments.

[0154] In order to implement the above embodiments, the present application also proposes a computer program product, including a computer program, which, when executed by a processor, implements the method for determining parameter monitoring points provided in the above embodiments.

[0155] The collection, storage, use, processing, transmission, provision and disclosure of user personal information involved in this application are in compliance with relevant laws and regulations and do not violate public order and good morals.

[0156] It should be noted that personal information from users should be collected for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. In addition, such collection / sharing should be carried out after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign the agreement / authorization including authorization of relevant user information before the user uses the function. In addition, any necessary steps should be taken to protect and safeguard access to such personal information data and ensure that others who have access to personal information data comply with its privacy policy and procedures.

[0157] The present application is expected to provide an implementation scheme for users to selectively block the use or access of personal information data. That is, the present disclosure is expected to provide hardware and / or software to prevent or block access to such personal information data. Once the personal information data is no longer needed, the risk can be minimized by limiting data collection and deleting the data. In addition, when applicable, such personal information is de-identified to protect the privacy of the user.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] 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 method for determining parameter monitoring points, characterized in that: include: Acquire a ventilation network graph, number the nodes and branches contained in the ventilation network graph, obtain a node identification set, a branch identification set, and a topological relationship between the node identifications and the branch identifications, wherein the node identification set includes a first number of nodes, and the branch identification set includes a second number of branches; Determine the weight corresponding to each branch according to the wind measurement importance level and wind resistance sensitivity corresponding to each branch; Based on the topological relationship and the weight, determining a first branch constituting a minimum spanning tree corresponding to the ventilation network graph, wherein the number of the first branches is the first number minus 1; Determining, according to the identifier of the first branch and the branch identifier set, a second branch in the ventilation network diagram, wherein the number of the second branches is the second number minus the number of the first branches; The position of each of the second branches in the ventilation network diagram is determined as an air volume parameter monitoring point.

2. The method according to claim 1, characterized in that After determining the position of each second branch in the ventilation network diagram as an air volume parameter monitoring point, the method further includes: Acquire the second branch air volume monitored by the sensor at each air volume parameter monitoring point; According to the ventilation network diagram and the air volume of the second branch, the air volume of each first branch is calculated using the air volume balance law.

3. The method according to claim 1, characterized in that Determining the weight corresponding to each branch according to the wind measurement importance level and wind resistance sensitivity corresponding to each branch includes: Determining the wind measurement importance level corresponding to the branch according to the type of the branch; Determine the wind resistance sensitivity of the branch according to the sensitivity of the wind volume of the branch to the wind resistance change of other branches; The wind measurement importance level and the wind resistance sensitivity are normalized to obtain weights corresponding to the branches.

4. The method according to claim 3, characterized in that Before determining the wind resistance sensitivity of the branch according to the sensitivity of the wind volume of the branch to the wind resistance change of other branches, the method further includes: Determine a first flow direction coefficient between the branch and each node according to the topological relationship of the ventilation network diagram and the first wind flow direction of each branch; Based on the topological relationship of the ventilation network, determining independent loops in the ventilation network, and first branches and second branches contained in each of the independent loops; In each of the independent loops, based on a first wind flow direction of the first branch and a second wind flow direction of the second branch, determining a second flow direction coefficient of each of the first branches in the independent loop; Obtaining reference air volume, reference fluid resistance and reference additional resistance corresponding to all branches in the ventilation network at any historical moment; Constructing a first set of equations based on the first number, the second number, the reference air volume, the reference fluid resistance, the reference additional resistance, the first flow coefficient, and the second flow coefficient; The first set of equations is solved to obtain the sensitivity of the air volume of each branch to the change of wind resistance of other branches.

5. The method according to claim 1, characterized in that After obtaining a ventilation network diagram, numbering the nodes and branches included in the ventilation network diagram, and obtaining a node identifier set, a branch identifier set, and a topological relationship between the node identifiers and the branch identifiers, the method further includes: Determine the number of independent pathways in the ventilation network and the branch identifiers contained in each independent pathway according to the topological structure of the ventilation network diagram; constructing an independent pathway matrix based on the number of independent pathways, the second number, and branch identifiers included in each independent pathway; Constructing a second set of equations based on the independent passage matrix and a preset pressure value of the fan; Solving the second system of equations to determine the rank of the second system of equations; The difference between the second number and the rank is calculated, and branches of the difference number in the ventilation network diagram are randomly selected, and the position of each branch is determined as a resistance parameter monitoring point.

6. The method according to claim 5, characterized in that After randomly selecting the difference branches in the ventilation network diagram and determining the position of each branch as a resistance parameter monitoring point, the method further includes: Acquire the branch resistance monitored by the sensor at each resistance parameter monitoring point; According to the branch identifier corresponding to the branch resistance, the branch resistance is substituted into the second set of equations to obtain the branch resistances corresponding to other branches respectively.

7. A device for determining parameter monitoring points, characterized in that: include: A first acquisition module is used to acquire a ventilation network diagram, number the nodes and branches contained in the ventilation network diagram, and obtain a node identification set, a branch identification set, and a topological relationship between the node identifications and the branch identifications, wherein the node identification set includes a first number of nodes, and the branch identification set includes a second number of branches; A first determination module is used to determine the weight corresponding to each branch according to the wind measurement importance level and wind resistance sensitivity corresponding to each branch; A second determination module is used to determine, based on the topological relationship and the weight, a first branch constituting a minimum spanning tree corresponding to the ventilation network graph, wherein the number of the first branches is the first number minus 1; A third determination module is used to determine the second branches in the ventilation network diagram according to the identifier of the first branch and the branch identifier set, wherein the number of the second branches is the second number minus the number of the first branches; The fourth determination module is used to determine the position of each second branch in the ventilation network diagram as an air volume parameter monitoring point.

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 for determining a parameter monitoring point 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 for determining a parameter monitoring point according to any one of claims 1 to 6.

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

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