Finite element power flow energy transfer path analysis method and system, medium and equipment

Abstract

The invention discloses a finite element power flow energy transfer path analysis method and system based on a graph network, a medium and equipment, and the method comprises the steps: carrying out the finite element modeling of a to-be-analyzed structure to obtain a finite element structure, calculating the power flow vector distribution of the finite element structure through a power flow formula based on a finite element result, and obtaining the vector component of each node of the finite element structure; constructing a power flow graph network relationship, and forming a directed weighted graph by taking a node vector component as a network weight of connection between nodes; simplifying the directed weighted graph, calculating a forward graph network spanning tree of the simplified directed weighted network, calculating the traffic size proportion of each path in a reverse graph network spanning tree, and confirming the energy source of a root node of the reverse graph network spanning tree; and respectively calculating a node energy change trend curve on the energy flow path based on the forward graph network spanning tree and the reverse graph network spanning tree.

Description

Technical Field

[0001] The present invention relates to the technical field of mechanical structure dynamics, and in particular to a finite element power flow energy transfer path analysis method, system, medium and equipment based on a graph network. Background Art

[0002] In the field of engineering technology, particularly in industries such as aerospace, automotive engineering, and shipbuilding, structural vibration and the resulting noise have long been a hot topic and a challenge. Vibration is essentially the transfer of energy within a structure. Accurately analyzing and predicting the transmission paths of vibration energy is crucial for design optimization, vibration and noise reduction, and overall performance improvement. Currently, tools and methods for analyzing the transmission paths of vibration energy in complex structures are relatively limited. Traditional statistical energy analysis (SEA) performs well at high frequencies, but its application is limited in low-frequency bands and for complex structures. Furthermore, SEA relies on a series of assumptions, such as weak coupling, which can significantly differ from the actual structural state, leading to biased analysis results. Meanwhile, the finite element method (FEM), a well-established structural dynamics analysis method, excels in analyzing low-frequency bands and complex structures. However, the traditional FEM primarily focuses on structural response parameters such as displacement and stress, lacking direct support for analyzing the transmission paths of vibration energy. Therefore, a new approach combining the FEM and vibration energy transfer analysis is needed.

[0003] The above information disclosed in this Background section is only for enhancement of understanding of the background of the invention and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the Invention

[0004] The present invention provides a graph-network-based finite element power flow energy transfer path analysis method, system, medium, and equipment for evaluating and analyzing the vibration energy transfer state of finite element structures, significantly improving identification accuracy. Specifically, gas turbine base vibration, aircraft wing load transfer, and feedwater pump body flow-induced vibration can all be analyzed. Gas turbine base vibration transfer path analysis, aircraft wing load transfer path analysis, and feedwater pump body flow-induced vibration transfer path analysis are performed separately.

[0005] The finite element power flow energy transfer path analysis method based on graph network includes:

[0006] Step 1: Finite element analysis: Finite element modeling of the structure to be analyzed is performed to obtain a finite element structure. The finite element results of normal stress, shear stress, normal strain, and shear strain of the unit nodes are calculated using the finite element model. Among them, the vibration of the gas turbine base, the load transfer of the aircraft wing, and the flow-induced vibration of the feedwater pump body can all be structures to be analyzed.

[0007] Step 2: Based on the finite element results, the power flow formula is used to calculate the power flow vector distribution of the finite element structure and obtain the vector components of each node of the finite element structure;

[0008] Step 3: Construct the network relationship of the power flow graph, using the node vector component as the network weight of the node-to-node connection to form a directed weighted graph;

[0009] Step 4: Simplify the directed weighted graph. Use the Louvain algorithm to perform community mining and partitioning on the directed weighted graph, and use the partitioning results to form a simplified directed weighted network.

[0010] Step 5: Calculate the forward graph network spanning tree of the simplified directed weighted network, calculate the maximum spanning tree of all source points and calculate the flow of the spanning tree branches; after reverse processing the directed weighted graph, calculate the maximum spanning tree of all sinks; calculate the contribution of the spanning tree branches, calculate the flow ratio of each path in the forward graph network spanning tree, and confirm the direction of energy transfer; calculate the flow ratio of each path in the reverse graph network spanning tree, and confirm the energy source of the root node of the reverse graph network spanning tree;

[0011] Step 6: Visualization display, based on the forward graph network spanning tree and the reverse graph network spanning tree, respectively calculate the energy change trend curve of the nodes on the energy flow path.

[0012] In the finite element power flow energy transfer path analysis method based on graph network, in step 3, a directed weighted network is established in the power flow graph network relationship. ,in, Represents a set of finite element nodes, where the elements are Indicates that the nodes are distinguished and numbered by their coordinates; Represents a set of forward network connections, where the elements are Indicates a point Pointing Point The connection; Represents a connection The set of weights on , where the elements are Indicates a point Pointing Point The weight of the connection, for any node There are 6 directions for the nodes connected to it through the grid, and directed connection lines are formed for the nodes connected along the power component direction. , and the weights of the connecting lines are:

[0013] ,in, is the forward directed weighted network weight from the i-th node to the j-th node, is the forward directed weighted network weight from the i-th node to the k-th node, is the forward directed weighted network weight from the i-th node to the l-th node, is the power of node i in the x-axis direction, and node i is connected to node j in the x-axis direction, is the power of node i in the y-axis direction, and node i is connected to node k in the y-axis direction, is the power of node i in the z-axis direction, and node i is connected to node l in the z-axis direction,

[0014] Form a forward directed weighted network, and form directed connection lines for nodes that only need to be modified to connect in the opposite direction along the power component direction , and empower it to:

[0015] , to form a reverse directed weighted network, where is the reverse directed weighted network weight from the jth node to the i-th node.

[0016] In the graph network-based finite element power flow energy transfer path analysis method, in step 5, the difference between the outgoing and incoming weights of all communities is calculated, and communities with positive difference results are selected as source points, and a tree with the source point as the root node is constructed:

[0017] ,

[0018] in, Tree Network A collection of connecting lines, the elements of which are represented by express, Represents the root node. For any Node sequence from the start to the leaf node is called a stream, a node The starting point to the leaf node is a node that is not connected to any node other than the root node, and the size of all energy flows in the source point tree is calculated. , as the path energy capacity of the structure's transient energy transfer, the energy transfer direction is obtained.

[0019] In the graph network-based finite element power flow energy transfer path analysis method, in step 5, the contribution of all flows in the tree is calculated based on the path energy capacity:

[0020] ,

[0021] Sort all the flows of each source point by contribution and select the one with the largest contribution. The geometric centers of the node sets in the community are connected as nodes for energy flow transmission.

[0022] In the finite element power flow energy transfer path analysis method based on graph network, in step 6, the largest contribution of the front A stream sequence is drawn, with the coordinates of the center of the sequence community as the three-dimensional coordinate input, and the connection weights in the sequence The output is a thermal curve diagram, and the energy transfer loss is determined based on the rate of change of the curve node values.

[0023] A finite element power flow energy transfer path analysis system based on a graph network includes:

[0024] Finite element analysis unit, which is used for finite element analysis, obtains finite element structure by finite element modeling of the structure to be analyzed, and calculates finite element results of normal stress, shear stress, normal strain and shear strain of the unit node through the finite element model; among them, gas turbine base vibration, aircraft wing load transfer and feedwater pump body flow-induced vibration can all be structures to be analyzed;

[0025] A power flow vector distribution unit calculates the power flow vector distribution of the finite element structure using the power flow formula based on the finite element results, and obtains the vector components of each node of the finite element structure;

[0026] A construction unit constructs a power flow graph network relationship, using node vector components as network weights for node-to-node connections to form a directed weighted graph;

[0027] A simplification unit simplifies a directed weighted graph by using the Louvain algorithm to perform community mining and partitioning on the directed weighted graph, and uses the partitioning results to form a simplified directed weighted network;

[0028] A calculation unit calculates a simplified forward graph network spanning tree of a directed weighted network, calculates the maximum spanning tree of all source points and calculates the flow of the spanning tree branches; after reverse processing the directed weighted graph, calculates the maximum spanning tree of all sinks; calculates the contribution of the spanning tree branches, calculates the flow ratio of each path in the forward graph network spanning tree, and confirms the direction of energy transfer; calculates the flow ratio of each path in the reverse graph network spanning tree, and confirms the energy source of the root node of the reverse graph network spanning tree;

[0029] The visualization display unit calculates the energy change trend curve of nodes on the energy flow path based on the forward graph network spanning tree and the reverse graph network spanning tree.

[0030] In the system, the computing unit is a processor.

[0031] In the system, the visual display unit includes a touch screen.

[0032] A computer storage medium, wherein the storage medium includes computer instructions, which, when executed on a computer, cause the computer to perform the method described.

[0033] An electronic device, wherein the electronic device comprises:

[0034] A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein:

[0035] When the processor executes the program, the method described is implemented.

[0036] Compared with the existing technology, the present invention has the following advantages: the present invention further calculates and visualizes the traditional power flow method, simplifies the complex finite element node network through the community mining method, and replaces the power flow transmission between units with the node power flow vector; traces and separates the energy transmission of structural components through the forward and reverse path graph network generation tree, and determines the main transmission direction and contribution of the energy flow. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Various other advantages and benefits of the present invention will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiments below. The accompanying drawings are intended only to illustrate preferred embodiments and are not to be construed as limiting the present invention. It should be understood that the drawings described below are merely examples of the present invention, and that those skilled in the art will be able to derive other drawings from these drawings without inventive effort. Throughout the drawings, identical reference numerals are used to denote identical components.

[0038] In the attached figure:

[0039] Figure 1 This is a flow chart of a finite element power flow energy transfer path analysis method based on graph network;

[0040] Figure 2 This is the graph network model partitioning result obtained by Louvain algorithm based on the power vector;

[0041] Figure 3 This is a simplified graph network model based on the community division results of the Louvain algorithm;

[0042] Figure 4 The power transfer path diagram of the nodes after the maximum flow calculation of the simplified network in the case.

[0043] The present invention will be further explained below with reference to the accompanying drawings and embodiments. DETAILED DESCRIPTION

[0044] Specific embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although specific embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0045] It should be noted that certain words are used in the specification and claims to refer to specific components. Those skilled in the art should understand that technicians may use different nouns to refer to the same component. This specification and claims do not use the difference in nouns as a way to distinguish components, but use the difference in the functions of the components as the criterion for distinction. As mentioned throughout the specification and claims, "including" or "comprising" is an open term, so it should be interpreted as "including but not limited to". The subsequent description of the specification is a preferred embodiment of the present invention, but the description is based on the general principles of the specification and is not intended to limit the scope of the invention. The scope of protection of the present invention shall be as defined in the attached claims.

[0046] To facilitate understanding of the embodiments of the present invention, further explanation will be given below using specific embodiments as examples in conjunction with the accompanying drawings, and the accompanying drawings do not constitute a limitation on the embodiments of the present invention.

[0047] like Figures 1 to 4 As shown in FIG, the finite element power flow energy transfer path analysis method based on graph network includes the following steps:

[0048] Step 1: Finite element analysis: finite element modeling of the structure to be analyzed is performed to obtain a finite element structure, and the finite element results of normal stress, shear stress, normal strain and shear strain of the unit node are calculated through the finite element model;

[0049] Step 2: Based on the finite element results, the power flow formula is used to calculate the power flow vector distribution of the finite element structure and obtain the vector components of each node of the finite element structure;

[0050] Step 3: Construct the network relationship of the power flow graph, using the node vector component as the network weight of the node-to-node connection to form a directed weighted graph;

[0051] Step 4: Simplify the directed weighted graph. Use the Louvain algorithm to perform community mining and partitioning on the directed weighted graph, and use the partitioning results to form a simplified directed weighted network.

[0052] Step 5: Calculate the forward graph network spanning tree of the simplified directed weighted network, calculate the maximum spanning tree of all source points and calculate the flow of the spanning tree branches; after reverse processing the directed weighted graph, calculate the maximum spanning tree of all sinks; calculate the contribution of the spanning tree branches, calculate the flow ratio of each path in the forward graph network spanning tree, and confirm the direction of energy transfer; calculate the flow ratio of each path in the reverse graph network spanning tree, and confirm the energy source of the root node of the reverse graph network spanning tree;

[0053] Step 6: Visualization display, based on the forward graph network spanning tree and the reverse graph network spanning tree, respectively calculate the energy change trend curve of the nodes on the energy flow path.

[0054] In the preferred embodiment of the finite element power flow energy transfer path analysis method based on graph network, in step 3, a directed weighted network is established in the power flow graph network relationship. ,in, Represents a set of finite element nodes, where the elements are Indicates that the nodes are distinguished and numbered by their coordinates; Represents a set of forward network connections, where the elements are Indicates a point Pointing Point The connection; Represents a connection The set of weights on , where the elements are Indicates a point Pointing Point The weight of the connection, for any node There are 6 directions for the nodes connected to it through the grid, and directed connection lines are formed for the nodes connected along the power component direction. , and the weights of the connecting lines are:

[0055] ,in, is the forward directed weighted network weight from the i-th node to the j-th node, is the forward directed weighted network weight from the i-th node to the k-th node, is the forward directed weighted network weight from the i-th node to the l-th node, is the power of node i in the x-axis direction, and node i is connected to node j in the x-axis direction, is the power of node i in the y-axis direction, and node i is connected to node k in the y-axis direction, is the power of node i in the z-axis direction, and node i is connected to node l in the z-axis direction,

[0056] Form a forward directed weighted network, and form directed connection lines for nodes that only need to be modified to connect in the opposite direction along the power component direction , and empower it to:

[0057] , to form a reverse directed weighted network, where is the reverse directed weighted network weight from the jth node to the i-th node.

[0058] In a preferred embodiment of the graph network-based finite element power flow energy transfer path analysis method, in step 5, the difference between the outgoing weight and the incoming weight of all communities is calculated, and communities with positive difference results are selected as source points, and a tree with the source point as the root node is constructed:

[0059] ,

[0060] in, Tree Network A collection of connecting lines, the elements of which are represented by express, Represents the root node. For any Node sequence from the start to the leaf node is called a stream, a node The starting point to the leaf node is a node that is not connected to any node other than the root node, and the size of all energy flows in the source point tree is calculated. , as the path energy capacity of the structure's transient energy transfer, the energy transfer direction is obtained.

[0061] In a preferred embodiment of the graph network-based finite element power flow energy transfer path analysis method, in step 5, the contribution of all flows in the tree is calculated based on the path energy capacity:

[0062] ,

[0063] Sort all the flows of each source point by contribution and select the one with the largest contribution. The geometric centers of the node sets in the community are connected as nodes for energy flow transmission.

[0064] In the preferred embodiment of the finite element power flow energy transfer path analysis method based on graph network, in step 6, the front A stream sequence is drawn, with the coordinates of the center of the sequence community as the three-dimensional coordinate input, and the connection weights in the sequence The output is a thermal curve diagram, and the energy transfer loss is determined based on the rate of change of the curve node values.

[0065] A finite element power flow energy transfer path analysis system based on a graph network includes:

[0066] Finite element analysis unit, which is used for finite element analysis, performs finite element modeling of the structure to be analyzed to obtain a finite element structure, and calculates the finite element results of normal stress, shear stress, normal strain and shear strain of the unit node through the finite element model;

[0067] A power flow vector distribution unit calculates the power flow vector distribution of the finite element structure using the power flow formula based on the finite element results, and obtains the vector components of each node of the finite element structure;

[0068] A construction unit constructs a power flow graph network relationship, using node vector components as network weights for node-to-node connections to form a directed weighted graph;

[0069] A simplification unit simplifies a directed weighted graph by using the Louvain algorithm to perform community mining and partitioning on the directed weighted graph, and uses the partitioning results to form a simplified directed weighted network;

[0070] A calculation unit calculates a simplified forward graph network spanning tree of a directed weighted network, calculates the maximum spanning tree of all source points and calculates the flow of the spanning tree branches; after reverse processing the directed weighted graph, calculates the maximum spanning tree of all sinks; calculates the contribution of the spanning tree branches, calculates the flow ratio of each path in the forward graph network spanning tree, and confirms the direction of energy transfer; calculates the flow ratio of each path in the reverse graph network spanning tree, and confirms the energy source of the root node of the reverse graph network spanning tree;

[0071] The visualization display unit calculates the energy change trend curve of nodes on the energy flow path based on the forward graph network spanning tree and the reverse graph network spanning tree.

[0072] In a preferred embodiment of the system, the computing unit is a processor.

[0073] In a preferred embodiment of the system, the visual display unit includes a touch screen.

[0074] A computer storage medium, wherein the storage medium includes computer instructions, which, when executed on a computer, enable the computer to perform the method as described above.

[0075] An electronic device, wherein the electronic device comprises:

[0076] A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein:

[0077] When the processor executes the program, the method described is implemented.

[0078] In one embodiment, the method includes,

[0079] A thin plate model with a length of 40 cm, a width of 30 cm, and a thickness of 10 cm was created in finite element software. The model was divided into a grid model with a unit size of 5 × 5 × 5 cm. After applying a load, the instantaneous material stress and nodal velocity during the vibration process were calculated using the finite element software. According to the method described above, the following steps were followed:

[0080] For step 1, the displacement, velocity, acceleration, principal stress, and shear stress of each node of the finite element model are calculated based on the finite element model to form the three-dimensional equilibrium equation of the node:

[0081] (1)

[0082] By multiplying the left and right sides of the equal sign in the above equation by the difference in displacement in the corresponding direction of the node and simplifying it, we can get the vector expression:

[0083]

[0084] in, is the three-dimensional displacement of the node, is the density, It can be expressed as:

[0085]

[0086] If you assume is the structural mechanical energy, is the structural kinetic energy, is the structural potential energy, it can be expressed as:

[0087]

[0088] Combining formula 3 can be expressed as:

[0089]

[0090] The structural kinetic energy can be expressed as:

[0091]

[0092] According to the structural energy conservation, Equation 4 can be expressed in the form of power conservation:

[0093]

[0094] Combining formula 2, we can get:

[0095]

[0096] Writing Equation 8 in scalar form, we can get:

[0097] (9)

[0098] Obtain the simplified expression of the power expression of each node.

[0099] For step three, establish a directed weighted complex network ,in, Represents a set of finite element nodes, where the elements are Indicates that the nodes are distinguished and numbered by their coordinates; Represents a set of forward network connections, where the elements are Indicates a point Pointing Point The connection; Represents a connection The set of weights on , where the elements are Indicates a point Pointing Point The weight of the connection. In the grid divided by C3D8 unit, for any node There are 6 directions for the nodes connected to it through the grid, and directed connection lines are formed for the nodes connected along the power component direction. , and the weights of the connecting lines are:

[0100]

[0101] in, is the forward directed weighted network weight from the i-th node to the j-th node, is the forward directed weighted network weight from the i-th node to the k-th node, is the forward directed weighted network weight from the i-th node to the l-th node, is the power of node i in the x-axis direction, and node i is connected to node j in the x-axis direction, is the power of node i in the y-axis direction, and node i is connected to node k in the y-axis direction, is the power of node i in the z-axis direction, and node i is connected to node l in the z-axis direction.

[0102] The forward directed weighted complex network is formed by the above method. For the reverse directed weighted complex network, it is only necessary to modify the nodes connected in the opposite direction along the power component direction to form a directed connection line. , and empower it to:

[0103]

[0104] in, is the reverse directed weighted network weight from the jth node to the ith node, is the reverse directed weighted network weight from the kth node to the i-th node, is the reverse directed weighted network weight from the lth node to the i-th node, is the power of node i in the x-axis direction, and node i is connected to node j in the x-axis direction, is the power of node i in the y-axis direction, and node i is connected to node k in the y-axis direction, is the power of node i in the z-axis direction, and node i is connected to node l in the z-axis direction.

[0105] Specially, for the force application surface on the outer surface of the structure and support surface The node set in the single force surface is taken as an example. There is a power flow vector component along the normal direction of the force surface, which represents the energy flow out of the structure from the external load. However, since no effective node connection is formed, no weighted connection line is formed in the directed weighted network. Figure 1 The power transfer path diagram is shown.

[0106] According to the above calculation method, the directed weighted connections in the complex network are organized into the form of an adjacency matrix, forming a forward adjacency matrix and a reverse adjacency matrix respectively.

[0107] For step 4, the Louvain algorithm is used to perform community mining on the forward directed weighted network and the reverse directed weighted network respectively:

[0108] 1) Mark each node in the graph as an independent community, with the number of communities being the same as the number of nodes;

[0109] 2) Mark each node and its adjacent nodes as the same community in turn, and calculate the maximum modularity gain of the graph network. The modularity gain is expressed as:

[0110]

[0111] in, is the sum of the weights of the links within the community, is the sum of the link weights associated with the nodes in the community, Is associated with adjacent nodes The sum of the link weights of From the adjacent nodes The sum of the link weights of nodes associated with the community, is the sum of the weights of all links in the network;

[0112] 3) Repeat step 2) until the algorithm is stable, that is, the communities to which all vertices belong no longer change, that is, the value of formula 12 is no longer expressed;

[0113] 4) All nodes in each community are compressed into one node. The weight within the community is converted into the weight of the new node ring, and the weight between communities is converted into the weight of the new node edge.

[0114] 5) Repeat steps 1) to 3) until the algorithm is stable and a simplified community network is formed through the above method.

[0115] Through the above steps, Figure 2 The nodes in the figure are divided into 12 community categories, which are distinguished by the colors of the nodes in the figure. Figure 2 The community division result simplifies the community nodes into Figure 3 The network shown, where Figure 3 The midpoint coordinates are Figure 2 The mean of the node coordinates in the community forms a simplified network represented by 12 nodes.

[0116] For step five, Figure 4 As shown, the difference between the outbound weight and the inbound weight of all communities is calculated, and the communities with positive difference are selected as the source points. A tree with the source point as the root node is constructed:

[0117]

[0118] in, Tree Network A collection of connecting lines, the elements of which are represented by express, Represents the root node. For any A sequence of nodes starting from a leaf node (i.e., a node that is not connected to a node other than the root node) is called flow. Calculate the magnitude of all energy flows in the source tree , refer to the values ​​marked in the figure (note: these values ​​reflect the effect of the present invention), as the energy capacity of the path of transient energy transfer of the structure, the main destination of energy transfer is obtained. Figure 4 As shown, the maximum flow in the network is calculated to be the input of node 4, and the tree structure flowing to nodes 1, 3, 8, 7, and 5 is the maximum power flow direction of the model.

[0119] For step 5, repeat steps 2 to 4 for the reverse directed weighted graph network to calculate the size of all energy flows in the sink flow tree. , as the path energy capacity of the structure's transient energy transfer, the main source of energy transfer is obtained.

[0120] For step 5, the contribution of all flows in the tree is calculated based on the path energy capacity obtained in steps 4 and 5:

[0121]

[0122] Sort all the flows of each source point by contribution and select the one with the largest contribution. The geometric centers of the node sets in the community are connected as nodes for energy flow transmission.

[0123] For step six, for the top contributor with the highest contribution A stream sequence is drawn, with the coordinates of the center of the sequence community as the three-dimensional coordinate input, and the connection weights in the sequence This is the output thermal curve. The energy transfer loss can be determined based on the speed of change of the curve node values.

[0124] In one embodiment, the method aims to efficiently and intuitively evaluate and analyze the vibration energy transfer state in a complex structure. The method first calculates the displacement, velocity, acceleration, and stress parameters of the structural nodes through finite element analysis, and then constructs the node power flow vector distribution. Subsequently, a directed weighted complex network model is established to convert the power flow transfer relationship between nodes into edges and weights in a graph network. In order to simplify the network structure, the Louvain algorithm is used to perform community mining on the forward and reverse directed weighted networks to form a simplified community network. By calculating the spanning tree and energy flow path, the main energy transfer direction and source are determined. Finally, a thermal curve diagram is drawn to show the energy change trend on the energy transfer path, and the cause of energy loss is analyzed in combination with the spatial geometric relationship. The present invention not only improves the analysis efficiency and accuracy, but also provides a scientific basis and visualization tool for structural design optimization and vibration control.

[0125] Although the embodiments of the present invention have been described above with reference to the accompanying drawings, the present invention is not limited to the above-mentioned specific embodiments and application fields. The above-mentioned specific embodiments are merely illustrative and instructive, and are not restrictive. A person skilled in the art, guided by this specification and without departing from the scope of protection of the claims of the present invention, may also devise various forms, all of which fall within the scope of protection of the present invention.

Claims

1. A finite element power flow energy transfer path analysis method based on graph network, characterized in that: The steps include: Step 1: Finite element analysis: Finite element modeling of the structure to be analyzed is performed to obtain a finite element structure. The finite element results of normal stress, shear stress, normal strain, and shear strain of the unit nodes are calculated using the finite element model. Among them, the vibration of the gas turbine base, the load transfer of the aircraft wing, and the flow-induced vibration of the feedwater pump body can all be structures to be analyzed. Step 2: Based on the finite element results, the power flow formula is used to calculate the power flow vector distribution of the finite element structure and obtain the vector components of each node of the finite element structure; Step 3: Construct the network relationship of the power flow graph, using the node vector components as the network weights of the node-to-node connections to form a directed weighted graph; Step 4: Simplify the directed weighted graph. Use the Louvain algorithm to perform community mining and partitioning on the directed weighted graph, and use the partitioning results to form a simplified directed weighted network. Step 5: Calculate the forward graph network spanning tree of the simplified directed weighted network, calculate the maximum spanning tree of all source points and calculate the flow of the spanning tree branches; after reverse processing the directed weighted graph, calculate the maximum spanning tree of all sinks; calculate the contribution of the spanning tree branches, calculate the flow ratio of each path in the forward graph network spanning tree, and confirm the direction of energy transfer; calculate the flow ratio of each path in the reverse graph network spanning tree, and confirm the energy source of the root node of the reverse graph network spanning tree; Step 6: Visualization display, based on the forward graph network spanning tree and the reverse graph network spanning tree, respectively calculate the energy change trend curve of the nodes on the energy flow path.

2. The finite element power flow energy transfer path analysis method based on graph network according to claim 1, characterized in that: Preferably, in step 3, in constructing the power flow graph network relationship, a directed weighted network is established ,in, Represents a set of finite element nodes, where the elements are Indicates that the nodes are distinguished and numbered by their coordinates; Represents a set of forward network connections, where the elements are Indicates a point Pointing Point The connection; Represents a connection The set of weights on which the elements are Indicates a point Pointing Point The weight of the connection, for any node There are 6 directions for the nodes connected to it through the grid, and directed connection lines are formed for the nodes connected along the power component direction. , and the weights of the connecting lines are: ,in, is the forward directed weighted network weight from the i-th node to the j-th node, is the forward directed weighted network weight from the i-th node to the k-th node, is the forward directed weighted network weight from the i-th node to the l-th node, is the power of node i in the x-axis direction, and node i is connected to node j in the x-axis direction, is the power of node i in the y-axis direction, and node i is connected to node k in the y-axis direction, is the power of node i in the z-axis direction, and node i is connected to node l in the z-axis direction, Form a forward directed weighted network, and form directed connection lines for nodes that only need to be modified to connect in the opposite direction along the power component direction , and empower it to: , to form a reverse directed weighted network, where is the reverse directed weighted network weight from the jth node to the i-th node.

3. The finite element power flow energy transfer path analysis method based on graph network according to claim 1, characterized in that: In step 5, the difference between the outbound weight and the inbound weight of all communities is calculated. Communities with positive differences are selected as source nodes, and a tree with the source node as the root node is constructed: ， in, Tree Network A collection of connecting lines, the elements of which are represented by express, Represents the root node. For any Node sequence from the start to the leaf node is called a stream, a node The starting point to the leaf node is a node that is not connected to any node other than the root node, and the size of all energy flows in the source point tree is calculated. , as the path energy capacity of the structure's transient energy transfer, the energy transfer direction is obtained.

4. The graph network-based finite element power flow energy transfer path analysis method according to claim 3, characterized in that: In step 5, the contribution of all flows in the tree is calculated based on the path energy capacity: ， Sort all the flows of each source point by contribution and select the one with the largest contribution. The geometric centers of the node sets in the community are connected as nodes for energy flow transmission.

5. The finite element power flow energy transfer path analysis method based on graph network according to claim 4, characterized in that: In step 6, for the top Flow sequence, draw the three-dimensional coordinate input with the sequence community center coordinate, the connection weight in the sequence The output is a thermal curve diagram, and the energy transfer loss is determined based on the rate of change of the curve node values.

6. A finite element power flow energy transfer path analysis system based on graph network, characterized in that: include: Finite element analysis unit, which is used for finite element analysis, obtains finite element structure by finite element modeling of the structure to be analyzed, and calculates finite element results of normal stress, shear stress, normal strain and shear strain of the unit node through the finite element model; among them, gas turbine base vibration, aircraft wing load transfer and feedwater pump body flow-induced vibration can all be structures to be analyzed; A power flow vector distribution unit calculates the power flow vector distribution of the finite element structure using the power flow formula based on the finite element results, and obtains the vector components of each node of the finite element structure; A construction unit constructs a power flow graph network relationship, using node vector components as network weights for node-to-node connections to form a directed weighted graph; A simplification unit simplifies a directed weighted graph by using the Louvain algorithm to perform community mining and partitioning on the directed weighted graph, and uses the partitioning results to form a simplified directed weighted network; A calculation unit calculates a simplified forward graph network spanning tree of a directed weighted network, calculates the maximum spanning tree of all source points and calculates the flow of the spanning tree branches; after reverse processing the directed weighted graph, calculates the maximum spanning tree of all sinks; calculates the contribution of the spanning tree branches, calculates the flow ratio of each path in the forward graph network spanning tree, and confirms the direction of energy transfer; calculates the flow ratio of each path in the reverse graph network spanning tree, and confirms the energy source of the root node of the reverse graph network spanning tree; The visualization display unit calculates the energy change trend curve of nodes on the energy flow path based on the forward graph network spanning tree and the reverse graph network spanning tree.

7. The system according to claim 6, wherein: The computing unit is a processor.

8. The system according to claim 6, wherein: The visual display unit includes a touch screen.

9. A computer storage medium, characterized in that The storage medium includes computer instructions, which, when executed on a computer, enable the computer to execute the method according to any one of claims 1 to 5.

10. An electronic device, characterized in that: The electronic device comprises: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method according to any one of claims 1 to 5 is implemented.

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