Modal recognition analysis method and device for body-in-white

Abstract

A modal recognition analysis method and apparatus for a body-in-white belongs to the field of vehicle technology. The modal recognition analysis apparatus determines multiple observation units on the body-in-white model based on user-triggered selection commands. These observation units correspond one-to-one with multiple observation nodes, with each observation node being the center point of its corresponding observation unit. The apparatus creates modal recognition analysis cards corresponding to the multiple observation nodes based on received modal recognition analysis parameters. These cards record the modal recognition analysis parameters. The apparatus then performs modal recognition analysis on the multiple observation nodes based on the corresponding modal recognition analysis cards. Compared to traditional technologies, this application involves less manual intervention and fewer repetitive manual operations during the body-in-white analysis process, resulting in higher efficiency and reduced error rates in modal recognition analysis.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and in particular to a modal recognition and analysis method and apparatus for a body-in-white. Background Technology

[0002] Body-in-white refers to the body of a vehicle that has been welded but not yet painted. Generally, in the early development stages of a vehicle project, modal identification analysis is required to determine the modal frequencies of the body-in-white. The modal frequencies of the body-in-white must meet certain target values; otherwise, the modal frequencies may easily approach the external excitation frequencies, leading to resonance.

[0003] Currently, modal identification analysis of body-in-white mainly examines the first-order torsional mode, first-order bending mode, and some large sheet metal modes, including the front fender, front roof beam, middle floor, and rear floor. However, modal identification analysis results for the same examination item (i.e., the examination area) often show multiple similar mode shapes, making it difficult to determine which specific mode shape corresponds to the examination item. Therefore, it is necessary to conduct modal identification analysis for each of the multiple examination items individually. Specifically, firstly, several examination elements are manually selected in each examination area (if the structural characteristics of the examination area are complex, a sufficient number of examination elements are needed to characterize the features of this examination area). Then, a rigid bar element (RBE) is manually created for each examination element. Next, load set cards, load case cards (including modal range cards, excitation frequency cards, dynamic load table function cards, damping cards, dynamic load cards, and dynamic load assembly cards), load step cards, and control cards are manually created for each RBE. Finally, a unit load is manually applied to each RBE according to the load set card of the RBE (the load direction varies depending on the area under investigation), and the response signal of the RBE after the unit load is applied is obtained according to the working condition card, load step card and control card of the RBE.

[0004] It is evident that the current modal identification analysis process for body-in-white relies heavily on manual intervention, resulting in a time-consuming, labor-intensive, inefficient, and error-prone process. Furthermore, with multiple versions of the body-in-white, manual intervention is required to repeat the modal identification analysis process for each new version, leading to numerous repetitive manual operations. Summary of the Invention

[0005] This application provides a modal recognition and analysis method and apparatus for a body-in-white. The analysis process involves minimal human intervention and repetitive manual operations, resulting in high efficiency and low error rate in modal recognition and analysis. The technical solution of this application is as follows.

[0006] Firstly, a modal recognition and analysis method for a white body is provided, the method comprising:

[0007] Based on the selection command triggered by the user, multiple inspection units on the body-in-white model are determined. The selection command is used to select the multiple inspection units on the body-in-white model. The multiple inspection units correspond one-to-one with multiple inspection nodes. Each inspection node is the center point of the corresponding inspection unit. The body-in-white model is created for the body-in-white and is used to characterize the structural features of the body-in-white.

[0008] Based on the received modality recognition analysis parameters, modality recognition analysis cards are created corresponding to the plurality of observation nodes. The modality recognition analysis cards are used to record the modality recognition analysis parameters. Each observation node corresponds to a plurality of modality recognition analysis cards, and different modality recognition analysis cards corresponding to the same observation node record different modality recognition analysis parameters.

[0009] Modal recognition analysis is performed on the multiple examination nodes based on the modal recognition analysis cards corresponding to the multiple examination nodes.

[0010] Optionally, the step of creating modal recognition analysis cards corresponding to the multiple investigation nodes based on the received modal recognition analysis parameters includes: creating multiple load set cards corresponding one-to-one with the multiple investigation nodes in batches based on the received load parameters, wherein the load set cards are used to record the load parameters, wherein the modal recognition analysis parameters include the load parameters, and the modal recognition analysis cards include the load set cards.

[0011] Optionally, the step of creating modal recognition analysis cards corresponding to the plurality of observation nodes based on the received modal recognition analysis parameters further includes: creating working condition cards corresponding to the plurality of observation nodes based on the received working condition parameters, wherein the working condition cards are used to record the working condition parameters, and the modal recognition analysis parameters include the working condition parameters, and the modal recognition analysis cards include the working condition cards.

[0012] Optionally, the operating condition parameters include at least one of modal output range, excitation frequency range, damping parameters, and dynamic load table function, wherein the dynamic load table function is a table function used to generate dynamic loads related to frequency and time; the operating condition card includes at least one of modal range card, excitation frequency card, damping card, and dynamic load table function card.

[0013] The modal range card is used to record the modal output range;

[0014] The excitation frequency card is used to record the excitation frequency range;

[0015] The damping card is used to record the damping parameters;

[0016] The dynamic load table function card is used to record the dynamic load table function.

[0017] Optionally, the step of creating working condition cards corresponding to the multiple inspection nodes based on the received working condition parameters includes at least one of the following:

[0018] Based on the received modal output range, create modal range cards corresponding to the plurality of examination nodes, wherein the plurality of examination nodes correspond to the same modal range card;

[0019] Based on the received excitation frequency range, create excitation frequency cards corresponding to the plurality of observation nodes, wherein the plurality of observation nodes correspond to the same excitation frequency card;

[0020] Based on the received damping parameters, damping cards are created corresponding to the plurality of inspection nodes, wherein the plurality of inspection nodes correspond to the same damping card;

[0021] Based on the received dynamic load table function, dynamic load table function cards corresponding to the plurality of examination nodes are created, wherein the plurality of examination nodes correspond to the same dynamic load table function card.

[0022] Optionally, the step of creating working condition cards corresponding to the plurality of inspection nodes based on the received working condition parameters further includes: creating a plurality of dynamic load cards corresponding one-to-one with the plurality of inspection nodes based on the plurality of load set cards and the dynamic load table function card, wherein the dynamic load card corresponding to each of the plurality of inspection nodes is used to associate the load set card corresponding to each inspection node with the dynamic load table function card, and the working condition card further includes the dynamic load card.

[0023] Optionally, the step of creating working condition cards corresponding to the multiple inspection nodes based on the received working condition parameters further includes: creating dynamic load assembly cards based on the multiple dynamic load cards, wherein the dynamic load assembly cards are used to associate the multiple dynamic load cards.

[0024] Optionally, the step of creating modal recognition analysis cards corresponding to the multiple examination nodes based on the received modal recognition analysis parameters further includes: creating load step cards based on the dynamic load assembly cards.

[0025] Optionally, the step of creating modality recognition analysis cards corresponding to the plurality of observation nodes based on the received modality recognition analysis parameters further includes: creating mode control cards corresponding to the plurality of observation nodes based on the received mode control parameters, wherein the mode control cards are used to record the mode control parameters, the modality recognition analysis parameters include the mode control parameters, and the modality recognition analysis cards include the mode control cards.

[0026] Optionally, the step of creating modal recognition analysis cards corresponding to the multiple observation nodes based on the received modal recognition analysis parameters further includes: creating a global control card based on the modal range card, the excitation frequency card, and the damping card, wherein the global control card is used to associate the modal range card, the excitation frequency card, and the damping card.

[0027] Secondly, a modal recognition and analysis device for a body-in-white is provided, the device comprising:

[0028] The determination module is used to determine multiple inspection units on the body-in-white model according to the selection command triggered by the user. The selection command is used to select the multiple inspection units on the body-in-white model. The multiple inspection units correspond one-to-one with multiple inspection nodes. Each inspection node is the center point of the corresponding inspection unit. The body-in-white model is created for the body-in-white and is used to characterize the structural features of the body-in-white.

[0029] A creation module is used to create modal recognition analysis cards corresponding to the multiple observation nodes based on the received modal recognition analysis parameters. The modal recognition analysis cards are used to record the modal recognition analysis parameters. Each observation node corresponds to multiple modal recognition analysis cards, and different modal recognition analysis cards corresponding to the same observation node record different modal recognition analysis parameters.

[0030] The analysis module is used to perform modal recognition analysis on the multiple observation nodes based on the modal recognition analysis cards corresponding to the multiple observation nodes.

[0031] Optionally, the creation module is used to: create multiple load set cards corresponding to the multiple examination nodes in batches according to the received load parameters, wherein the load set cards are used to record the load parameters, wherein the modal recognition analysis parameters include the load parameters, and the modal recognition analysis cards include the load set cards.

[0032] Optionally, the creation module is further configured to: create working condition cards corresponding to the multiple observation nodes based on the received working condition parameters, wherein the working condition cards are used to record the working condition parameters, and the modal recognition analysis parameters include the working condition parameters, and the modal recognition analysis cards include the working condition cards.

[0033] Optionally, the operating condition parameters include at least one of modal output range, excitation frequency range, damping parameters, and dynamic load table function, wherein the dynamic load table function is a table function used to generate dynamic loads related to frequency and time; the operating condition card includes at least one of modal range card, excitation frequency card, damping card, and dynamic load table function card.

[0034] The modal range card is used to record the modal output range;

[0035] The excitation frequency card is used to record the excitation frequency range;

[0036] The damping card is used to record the damping parameters;

[0037] The dynamic load table function card is used to record the dynamic load table function.

[0038] Optionally, the creation module is configured to perform at least one of the following:

[0039] Based on the received modal output range, create modal range cards corresponding to the plurality of investigation nodes, wherein the plurality of investigation nodes correspond to the same modal range card;

[0040] Based on the received excitation frequency range, create excitation frequency cards corresponding to the plurality of observation nodes, wherein the plurality of observation nodes correspond to the same excitation frequency card;

[0041] Based on the received damping parameters, damping cards are created corresponding to the plurality of inspection nodes, wherein the plurality of inspection nodes correspond to the same damping card;

[0042] Based on the received dynamic load table function, dynamic load table function cards corresponding to the plurality of examination nodes are created, wherein the plurality of examination nodes correspond to the same dynamic load table function card.

[0043] Optionally, the creation module is further configured to: create a plurality of dynamic load cards corresponding one-to-one with the plurality of load set cards and the dynamic load table function cards, wherein the dynamic load card corresponding to each of the plurality of inspection nodes is used to associate the load set card corresponding to each inspection node with the dynamic load table function card, and the working condition card further includes the dynamic load card.

[0044] Optionally, the creation module is further configured to: create a dynamic load assembly card based on the plurality of dynamic load cards, wherein the dynamic load assembly card is used to associate the plurality of dynamic load cards.

[0045] Optionally, the creation module is further configured to: create a load step card based on the dynamic load assembly card.

[0046] Optionally, the creation module is further configured to: create mode control cards corresponding to the plurality of observation nodes according to the received mode control parameters, wherein the mode control cards are used to record the mode control parameters, the modality recognition analysis parameters include the mode control parameters, and the modality recognition analysis cards include the mode control cards.

[0047] Optionally, the creation module is further configured to: create a global control card based on the modal range card, the excitation frequency card, and the damping card, wherein the global control card is used to associate the modal range card, the excitation frequency card, and the damping card.

[0048] Thirdly, a modal recognition and analysis device for a white body is provided, including a memory and a processor, wherein the memory stores a computer program that, when executed by the processor, implements the method provided by the first aspect or any optional implementation thereof.

[0049] Fourthly, a computer-readable storage medium is provided that stores a computer program, which, when executed (e.g., by a processor, a modal recognition and analysis device for a body-in-white, etc.), implements the method provided by the first aspect or any optional implementation thereof.

[0050] Fifthly, a computer program product is provided, including a computer program / instruction that, when executed (e.g., executed by a processor, a modal recognition and analysis device for a body-in-white, etc.), implements the method provided by the first aspect or any optional implementation of the first aspect.

[0051] The modal recognition analysis method and apparatus for a body-in-white provided in this application are as follows: The modal recognition analysis method is executed by the modal recognition analysis apparatus. The modal recognition analysis apparatus determines multiple observation units on the body-in-white model based on user-triggered selection instructions. These observation units correspond one-to-one with multiple observation nodes, and each observation node is the center point of the corresponding observation unit. The modal recognition analysis apparatus creates modal recognition analysis cards corresponding to the multiple observation nodes based on received modal recognition analysis parameters. These modal recognition analysis cards record the modal recognition analysis parameters. Each observation node corresponds to multiple modal recognition analysis cards, and different modal recognition analysis cards corresponding to the same observation node record different modal recognition analysis parameters. The modal recognition analysis apparatus performs modal recognition analysis on the multiple observation nodes based on the modal recognition analysis cards corresponding to them. Therefore, compared to traditional technologies (such as those described in the background section of this application), this application involves less manual intervention and fewer repetitive manual operations during the analysis of the body-in-white, resulting in higher efficiency and less error-prone modal recognition analysis. Attached Figure Description

[0052] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0053] Figure 1 This is a flowchart of a modal recognition and analysis method for a body-in-white provided in an embodiment of this application;

[0054] Figure 2 This is a flowchart of another modal recognition and analysis method for a body-in-white provided in an embodiment of this application;

[0055] Figure 3 This is a schematic diagram of a modal recognition and analysis device for a body-in-white provided in an embodiment of this application;

[0056] Figure 4 This is a schematic diagram of another modal recognition and analysis device for a body-in-white provided in an embodiment of this application.

[0057] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0059] In the early development stages of vehicle projects, modal identification analysis of the body-in-white (BIS) is typically required. Traditionally, this process involves significant manual intervention, resulting in a time-consuming, labor-intensive, inefficient, and error-prone process. Furthermore, with multiple BIS versions, manual analysis of each version requires repeating the process from the previous version, leading to numerous repetitive operations. Therefore, this application provides a method and apparatus for modal identification analysis of the BIS. The modal identification analysis method is executed by a modal identification analysis apparatus. The apparatus determines multiple observation units on the BIS model based on user-triggered selection instructions. These observation units correspond one-to-one with multiple observation nodes, where each observation node is the center point of the corresponding observation unit. This BIS model is created specifically for the BIS and is used to characterize its structural features. The modal recognition and analysis device creates modal recognition and analysis cards corresponding to the multiple examination nodes based on the received modal recognition and analysis parameters. These cards record the modal recognition and analysis parameters, and each examination node corresponds to multiple modal recognition and analysis cards. Different modal recognition and analysis cards for the same examination node record different modal recognition and analysis parameters. The modal recognition and analysis device performs modal recognition and analysis on the multiple examination nodes based on the corresponding modal recognition and analysis cards. Therefore, compared to traditional technologies, this embodiment of the application involves less manual intervention and fewer repetitive manual operations during the analysis of the body-in-white, resulting in higher efficiency and less error-prone modal recognition and analysis.

[0060] Please refer to Figure 1 The diagram illustrates a flowchart of a modal recognition analysis method for a body-in-white according to an embodiment of this application. This modal recognition analysis method is executed by a modal recognition analysis device. The modal recognition analysis device may be a computer device or a functional component within a computer device. See also... Figure 1 The modality recognition and analysis method includes the following steps S101 to S103.

[0061] S101. Based on the selection command triggered by the user, determine multiple inspection units on the body-in-white model. The selection command is used to select the multiple inspection units on the body-in-white model. The multiple inspection units correspond one-to-one with multiple inspection nodes. Each inspection node is the center point of the corresponding inspection unit. The body-in-white model is created for the body-in-white and is used to characterize the structural features of the body-in-white.

[0062] The body-in-white model can be a geometric model created using a hypermesh application to characterize the structural features of the body-in-white. This model can be a meshed model with multiple mesh elements, which can be rectangular in shape. The observation cells on the body-in-white model can be the mesh elements selected by the user. Observation nodes can be the intersection of the two diagonals of the observation cell. Observation nodes can be rigid bar elements (RBEs).

[0063] In an optional embodiment, the modal recognition and analysis device displays the body-in-white model on a display interface. The user selects a mesh cell on the body-in-white model displayed by the modal recognition and analysis device to trigger a selection command. The modal recognition and analysis device receives the selection command triggered by the user. Based on the user-triggered selection command, the modal recognition and analysis device determines the mesh cell selected by the user, and identifies the selected mesh cell as the unit of investigation. In one embodiment, the body-in-white model is a model created using the HyperMesh application, and the modal recognition and analysis device displays the body-in-white model on the HyperMesh application's display interface. The user selects a mesh cell on the body-in-white model displayed by the modal recognition and analysis device by clicking or other means. The clicking can be done via a mouse or a touch component (e.g., a touchscreen).

[0064] In an optional embodiment, the body-in-white model includes multiple inspection areas (or inspection items), with the multiple inspection units located within the same inspection area. For example, the multiple inspection areas include the front fender, front roof crossbeam, middle floor, rear floor, etc. In one embodiment, the user selects multiple inspection units in each inspection area, and the inspection units within each inspection area are used to characterize the structural features of that inspection area.

[0065] In an optional embodiment, after the modal recognition and analysis device determines the aforementioned plurality of examination units according to the selection command triggered by the user, the modal recognition and analysis device determines a plurality of examination nodes corresponding one-to-one with the plurality of examination units. Specifically, for each of the plurality of examination units: the modal recognition and analysis device determines the center point of the examination unit, and the modal recognition and analysis device determines the center point of the examination unit as the examination node corresponding to the examination unit. In one embodiment, the plurality of examination units are all grid units. For each of the plurality of examination units: the modal recognition and analysis device determines the intersection of the two diagonals of the examination unit (the intersection of the two diagonals of the examination unit is the center point of the examination unit), and the modal recognition and analysis device determines the intersection of the two diagonals of the examination unit as the examination node corresponding to the examination unit.

[0066] In an optional embodiment, after the modal recognition and analysis device determines the plurality of examination nodes corresponding one-to-one with the plurality of examination units, the modal recognition and analysis device displays the plurality of examination nodes on the body-in-white model. For example, the modal recognition and analysis device highlights the plurality of examination nodes on the body-in-white model. This highlighting can be done using a specific color, and this embodiment of the application does not limit this.

[0067] In an optional embodiment, after the user selects the aforementioned multiple examination units on the body-in-white model, the user adjusts the examination units based on their needs. For example, the user can reselect examination units on the body-in-white model displayed by the modal recognition analysis device by clicking or other means to adjust the examination units. After the user adjusts the examination units, the modal recognition analysis device determines the examination nodes based on the adjusted examination units. The modal recognition analysis device then executes the following steps S102 to S103 for the examination nodes corresponding to the adjusted examination units.

[0068] S102. Based on the received modal recognition analysis parameters, create modal recognition analysis cards corresponding to the multiple examination nodes. The modal recognition analysis cards are used to record the modal recognition analysis parameters. Each of the multiple examination nodes corresponds to multiple modal recognition analysis cards, and different modal recognition analysis cards corresponding to the same examination node record different modal recognition analysis parameters.

[0069] Users can input modal recognition and analysis parameters into the modal recognition and analysis device through its human-computer interaction component, and the modal recognition and analysis device receives these parameters. For example, users can input modal recognition and analysis parameters into the device via command line. The human-computer interaction component includes, but is not limited to, touch components, display components, keyboards, and mice.

[0070] In an optional embodiment, after receiving the modal recognition and analysis parameters, the modal recognition and analysis device creates a blank card and records the modal recognition and analysis parameters on the blank card to obtain a modal recognition and analysis card. In one embodiment, the user triggers the modal recognition and analysis device to display a parameter setting interface, where the user inputs the modal recognition and analysis parameters, and the modal recognition and analysis device receives the modal recognition and analysis parameters input by the user in the parameter setting interface.

[0071] In an optional embodiment, the modal recognition analysis parameters include load parameters, and the modal recognition analysis cards include load set cards, which are used to record load parameters. The modal recognition analysis device creates multiple load set cards corresponding to the multiple examination nodes in batches based on the received load parameters. For example, the modal recognition analysis device creates multiple load set cards corresponding to the multiple examination nodes sequentially based on the received load parameters. In a specific embodiment, the user triggers the modal recognition analysis device to display a load parameter setting interface. The user inputs load parameters in the load parameter setting interface. After receiving the load parameters input by the user in the load parameter setting interface, the modal recognition analysis device creates multiple blank cards corresponding to the multiple examination nodes. The modal recognition analysis device records the load parameters in the multiple blank cards to obtain multiple load set cards corresponding to the multiple examination nodes. For example, the load parameters include the amplitude of multiple load signals and the frequency of the multiple load signals. The amplitude of the load signals is also called the magnitude of the load signals. The frequency of the multiple load signals is determined based on the starting frequency of the load signals input by the user, the frequency interval of the load signals, and the number of frequency intervals. The amplitudes of different load signals can be the same or different. Different load signals can have the same or different frequencies. At least one of the amplitude and frequency must be different for different load signals. A load signal is also called a unit load.

[0072] In an optional embodiment, the modal recognition analysis parameters further include operating condition parameters, and the modal recognition analysis card further includes an operating condition card, which is used to record the operating condition parameters. The modal recognition analysis device creates operating condition cards corresponding to the multiple observation nodes based on the received operating condition parameters. For example, the modal recognition analysis device creates blank cards, and records the operating condition parameters on the blank cards to obtain the operating condition cards.

[0073] In this embodiment, the operating condition parameters include at least one of modal output range, excitation frequency range, damping parameters, and dynamic load table function. Correspondingly, the operating condition card includes at least one of modal range card, excitation frequency card, damping card, and dynamic load table function card. The modal range card records the modal output range. The excitation frequency card records the excitation frequency range. The damping card records the damping parameters. The dynamic load table function card records the dynamic load table function. The modal output range is a frequency limit range used to obtain the modal identification signal based on the load signal. For example, the load parameters include the frequencies of multiple load signals, the upper limit of the modal output range is greater than 1.5 times the maximum frequency among the multiple load signals, and the lower limit of the modal output range is 0 Hz. The dynamic load table function is a table function used to generate dynamic loads related to frequency and time. The dynamic load table function is used by the modal identification analysis device to calculate the modal identification signal whose frequency is within the modal output range based on the load signal and damping parameters.

[0074] In an optional embodiment, the modal identification and analysis device creates working condition cards corresponding to the plurality of test nodes based on the received working condition parameters, including at least one of the following: the modal identification and analysis device creates modal range cards corresponding to the plurality of test nodes based on the received modal output range, wherein the plurality of test nodes correspond to the same modal range card; the modal identification and analysis device creates excitation frequency cards corresponding to the plurality of test nodes based on the received excitation frequency range, wherein the plurality of test nodes correspond to the same excitation frequency card; the modal identification and analysis device creates damping cards corresponding to the plurality of test nodes based on the received damping parameters, wherein the plurality of test nodes correspond to the same damping card; the modal identification and analysis device creates dynamic load table function cards corresponding to the plurality of test nodes based on the received dynamic load table function, wherein the plurality of test nodes correspond to the same dynamic load table function card.

[0075] The following six examples illustrate the process of creating condition cards using a modal recognition and analysis device.

[0076] The first embodiment: The operating condition parameters include modal output ranges, and the operating condition cards include modal range cards. The modal range cards are used to record the modal output ranges. The modal recognition and analysis device creates modal range cards corresponding to the multiple observation nodes based on the received modal output ranges. Specifically, the multiple observation nodes correspond to the same modal range card; that is, the correspondence between modal range cards and observation nodes is one-to-many. In a specific embodiment, the user triggers the modal recognition and analysis device to display the modal output range setting interface. The user inputs the modal output range in the modal output range setting interface. After receiving the modal output range input by the user in the modal output range setting interface, the modal recognition and analysis device creates a blank card and records the modal output range in the blank card to obtain the modal range cards corresponding to the multiple observation nodes.

[0077] The second embodiment: The operating condition parameters include the excitation frequency range, and the operating condition card includes an excitation frequency card, which is used to record the excitation frequency range. The modal recognition analysis device creates excitation frequency cards corresponding to the multiple observation nodes based on the received excitation frequency range. The multiple observation nodes correspond to the same excitation frequency card; that is, the correspondence between the excitation frequency card and the observation node is one-to-many. In a specific embodiment, the user triggers the modal recognition analysis device to display the excitation frequency range setting interface. The user inputs the excitation frequency range in the excitation frequency range setting interface. After receiving the excitation frequency range input by the user in the excitation frequency range setting interface, the modal recognition analysis device creates a blank card and records the excitation frequency range in the blank card to obtain the excitation frequency cards corresponding to the multiple observation nodes.

[0078] The third embodiment: The operating condition parameters include damping parameters, and the operating condition card includes a damping card, which is used to record the damping parameters. The modal recognition and analysis device creates damping cards corresponding to the multiple test nodes based on the received damping parameters. Each of the multiple test nodes corresponds to the same damping card; that is, the correspondence between the damping card and the test node is one-to-many. In a specific embodiment, the user triggers the modal recognition and analysis device to display the damping parameter setting interface. The user inputs the damping parameters in the interface. After receiving the input damping parameters, the modal recognition and analysis device creates a blank card and records the damping parameters in this blank card to obtain the damping cards corresponding to the multiple test nodes.

[0079] Fourth embodiment: The operating condition parameters include dynamic load table functions, and the operating condition card includes a dynamic load table function card, which is used to record the dynamic load table functions. The modal recognition and analysis device creates dynamic load table function cards corresponding to the multiple examination nodes based on the received dynamic load table functions. The multiple examination nodes correspond to the same dynamic load table function card; that is, the correspondence between the dynamic load table function card and the examination node is one-to-many. In a specific embodiment, the user triggers the modal recognition and analysis device to display the dynamic load table function setting interface. The user inputs the dynamic load table function in the interface. After receiving the input, the device creates a blank card and records the dynamic load table function in this blank card to obtain the dynamic load table function cards corresponding to the multiple examination nodes.

[0080] Fifth embodiment: The working condition card also includes a dynamic load card, which is used to associate the load set card with the dynamic load table function card. The modal recognition analysis device creates multiple dynamic load cards corresponding to the multiple examination nodes based on the multiple load set cards corresponding to the multiple examination nodes and the dynamic load table function card. The dynamic load card corresponding to each of the multiple examination nodes is used to associate the load set card corresponding to each examination node with the dynamic load table function card. In a specific embodiment, the modal recognition analysis device creates a dynamic load card corresponding to each examination node based on the load set card corresponding to each examination node and the dynamic load table function card. In a specific embodiment, the modal recognition analysis device creates multiple blank cards corresponding to the multiple examination nodes, and records the identifier of the load set card and the identifier of the dynamic load table function card of each examination node in the blank card corresponding to each examination node to obtain the dynamic load card corresponding to that examination node.

[0081] Sixth embodiment: The working condition card also includes a dynamic load assembly card, which is used to associate multiple dynamic load cards corresponding to the multiple examination nodes one-to-one. The modal recognition analysis device creates the dynamic load assembly card based on the multiple dynamic load cards. In a specific embodiment, the modal recognition analysis device creates a blank card, and records the identifiers of the multiple dynamic load cards in the blank card to associate the multiple dynamic load cards to obtain the dynamic load assembly card.

[0082] In an optional embodiment, the modal recognition analysis card further includes a load step card, which the modal recognition analysis device creates based on the dynamic load assembly card. In a specific embodiment, the modal recognition analysis device creates a blank card in which it records the identifier of the dynamic load assembly card.

[0083] In optional embodiments, the modal recognition analysis parameters further include pattern control parameters, and the modal recognition analysis card further includes a pattern control card, which is used to record the pattern control parameters. The modal recognition analysis device creates pattern control cards corresponding to the multiple examination nodes based on the received pattern control parameters. The multiple examination nodes correspond to the same pattern control card; that is, the correspondence between the pattern control card and the examination node is one-to-many. In a specific embodiment, the user triggers the modal recognition analysis device to display a pattern setting interface. The user inputs the pattern control parameters in the pattern setting interface. After receiving the pattern control parameters input by the user in the pattern setting interface, the modal recognition analysis device creates a blank card and records the pattern control parameters in the blank card to obtain the pattern control cards corresponding to the multiple examination nodes. The pattern control parameters are used by the modal recognition analysis device to determine the calculation mode for obtaining the modal recognition signal based on the load signal. In this embodiment, the calculation mode includes an accelerated mode or a normal mode. In the accelerated mode, the modal recognition analysis device does not need to check whether the modal recognition signal of the examination node is abnormal during the process of obtaining the modal recognition signal based on the load signal. In normal mode, the modal identification analysis device needs to check whether the modal identification signal of the examined node is abnormal during the process of obtaining the modal identification signal based on the load signal. The modal identification signal can be the vibration frequency (i.e., modal frequency). In an optional embodiment, the mode setting interface includes an acceleration mode option and a normal mode option. The user selects the acceleration mode by operating (e.g., clicking) the acceleration mode option, or the user selects the normal mode by operating (e.g., clicking) the normal mode option. The modal identification analysis device records the mode control parameters of the calculation mode selected by the user in a blank card to obtain a mode control card.

[0084] In an optional embodiment, the modal recognition analysis card further includes a global control card. The global control card is used to associate the modal range card, excitation frequency card, and damping card. The modal recognition analysis device creates the global control card based on the modal range card, excitation frequency card, and damping card. In a specific embodiment, the modal recognition analysis device creates a blank card. The modal recognition analysis device records the identifiers of the modal range card, the excitation frequency card, and the damping card in the blank card to associate the modal range card, the excitation frequency card, and the damping card.

[0085] As described above in S102, the modal identification analysis card corresponding to each of the multiple examination nodes can include a load set card, a modal range card, an excitation frequency card, a damping card, a dynamic load table function card, a dynamic load card, a dynamic load assembly card, a load step card, a mode control card, and a global control card. Furthermore, each of the two types of cards, the load set card and the dynamic load card, corresponds one-to-one with an examination node. The correspondence between each of the seven types of cards—dynamic load table function card, modal range card, excitation frequency card, damping card, dynamic load assembly card, load step card, mode control card, and global control card—and the examination nodes is a one-to-many correspondence. That is, the multiple examination nodes correspond to the same dynamic load table function card, the same modal range card, the same excitation frequency card, the same damping card, the same dynamic load assembly card, the same load step card, the same mode control card, and the same global control card. This embodiment of the application does not limit this.

[0086] S103. Perform modal recognition analysis on the multiple examination nodes based on the modal recognition analysis cards corresponding to the multiple examination nodes.

[0087] After the modal recognition analysis device creates modal recognition analysis cards corresponding to the multiple observation nodes, the device can perform modal recognition analysis on the multiple observation nodes according to the modal recognition analysis cards to obtain the modal recognition results of the multiple observation nodes. The modal recognition result for each of the multiple observation nodes may include the vibration frequency (i.e., modal frequency).

[0088] In an optional embodiment, for each of the plurality of observation nodes: the modal identification and analysis device applies a load signal (e.g., unit load) to the observation node according to the load parameters recorded on the load set card corresponding to the observation node; the modal identification and analysis device obtains the modal identification signal of the observation node under the action of the load signal according to the working condition parameters recorded on the working condition card corresponding to the observation node, the mode control parameters recorded on the mode control card corresponding to the observation node, and the global control card. The modal identification signal of each observation node can be the vibration frequency signal (i.e., modal frequency signal) of the observation node.

[0089] In a specific embodiment, for each of the plurality of examination nodes: the modal identification and analysis device determines the amplitude and frequency of the plurality of load signals applied to the examination node based on the load parameters recorded in the load set card corresponding to the examination node; the modal identification and analysis device determines the modal output range, excitation frequency range, dynamic load table function, damping parameter, and mode control parameter of the modal identification signal of the examination node based on the working condition parameters recorded in the working condition card corresponding to the examination node and the mode control parameters recorded in the mode control card corresponding to the examination node; the modal identification and analysis device applies the plurality of load signals to the examination node sequentially according to the amplitude and frequency of the plurality of load signals; each time the modal identification and analysis device applies a load signal to the examination node, the modal identification and analysis device calculates the modal identification signal (e.g., the vibration frequency signal of the examination node) of the examination node under the action of the load signal based on the amplitude, modal output range, excitation frequency range, dynamic load table function, damping parameter, and mode control parameter of the load signal.

[0090] In an optional embodiment, for each of the plurality of examination nodes, the user triggers a modal recognition analysis command for that examination node based on the modal recognition analysis interface; the modal recognition analysis device obtains the load set card, the operating condition card, and the mode control card corresponding to the examination node based on the modal recognition analysis command; then, the modal recognition analysis device determines the amplitude and frequency of the plurality of load signals applied to the examination node based on the load parameters recorded in the load set card corresponding to the examination node; the modal recognition analysis device determines the modal output range, excitation frequency range, dynamic load table function, damping parameter, and mode control parameter of the modal recognition signal of the examination node based on the operating condition parameters recorded in the operating condition card and the mode control parameters recorded in the mode control card corresponding to the examination node. In a specific embodiment, the modal recognition analysis device sequentially applies multiple load signals to the observation node according to the amplitude and frequency of the multiple load signals, including: the modal recognition analysis device applies the load signal to the observation node based on the amplitude and frequency of each load signal; during the process of applying the load signal to the observation node, the modal recognition analysis device determines whether the duration of applying the load signal to the observation node reaches a preset duration; when the duration of applying the load signal to the observation node reaches the preset duration, the modal recognition analysis device stops applying the load signal to the observation node and applies the next load signal to the observation node. For example, the multiple load signals include load signal 1 and load signal 2, and the multiple observation nodes include observation node B. The modal recognition analysis device applies load signal 1 to observation node B based on the amplitude and frequency of load signal 1. During the application of load signal 1 to observation node B, the modal recognition analysis device determines whether the duration of applying load signal 1 to observation node B has reached a preset duration. When the duration of applying load signal 1 to observation node B reaches the preset duration, the modal recognition analysis device stops applying load signal 1 to observation node B, and begins applying load signal 2 to observation node B based on the amplitude and frequency of load signal 2. The implementation process of the modal recognition analysis device applying load signal 2 to observation node B can be referred to the implementation process of the modal recognition analysis device applying load signal 1 to observation node B, and will not be repeated here.

[0091] In an optional embodiment, for each of the plurality of observation nodes: the modal recognition analysis device determines the modal output range, excitation frequency range, dynamic load table function, damping parameter, and mode control parameter of the modal recognition signal of the observation node based on the operating condition parameters recorded on the operating condition card corresponding to the observation node and the mode control parameters recorded on the mode control card corresponding to the observation node; the modal recognition analysis device calculates the modal recognition signal of the observation node under the action of the load signal based on the amplitude of each load signal applied to the observation node, the modal output range, the excitation frequency range, the dynamic load table function, the damping parameter, and the mode control parameter. For example, the plurality of observation nodes includes observation node B, and the calculation mode of observation node B is acceleration mode. During the process of the modal recognition analysis device applying load signal 1 to observation node B, observation node B will vibrate under the action of load signal 1. During the vibration of observation node B, the modal recognition analysis device collects the vibration frequency (i.e., modal frequency, modal recognition signal) of observation node B at each collection moment. Specifically, during the vibration observation of node B, the modal identification analysis device uses the finite element method to calculate the modal identification signal of node B at each acquisition time, based on the amplitude and frequency of load signal 1, the damping parameter, and the dynamic load table function. The calculation process uses the modal output range as a constraint, ensuring that the calculated modal identification signal remains within that range. Furthermore, the modal identification analysis device does not check for anomalies in the modal identification signal of node B during the calculation. The process of calculating the modal identification signal of node B under load signal 2 can be referenced in the above description of the process of calculating the modal identification signal of node B under load signal 1, and will not be repeated here.

[0092] The above example illustrates how the modal recognition analysis device calculates the modal recognition signal of the examined node B. The implementation process of the modal recognition analysis device calculating the modal recognition signal of any examined node can refer to the implementation process of the modal recognition analysis device calculating the modal recognition signal of the examined node B, and will not be elaborated here.

[0093] In an optional embodiment, after the modal recognition analysis device acquires the modal recognition signals of the plurality of observation nodes, the modal recognition analysis device generates a calculation file based on the modal recognition signals of the plurality of observation nodes, and the calculation file records the modal recognition signal of each of the plurality of observation nodes.

[0094] In an optional embodiment, after acquiring the modal recognition signals of the plurality of observation nodes, the modal recognition analysis device determines the modal recognition curve of the target observation node based on the modal recognition signal of the target observation node among the plurality of observation nodes, and displays the modal recognition curve of the target observation node. The modal recognition curve can be the vibration frequency curve (also called modal frequency) of the target observation node under the action of a load signal. The target observation node is the observation node determined by the user according to the analysis requirements. In a specific embodiment, the user inputs the identifier of the target observation node in the curve display interface. The modal recognition analysis device searches for the modal recognition signal of the target observation node in the storage space based on the identifier of the target observation node, generates the modal recognition curve of the target observation node based on the modal recognition signal of the target observation node, and displays the modal recognition curve of the target observation node.

[0095] It should be noted that the multiple examination units described in S101 are located within the same examination area (also called examination item), and the multiple examination nodes described in S101 to S103, which correspond one-to-one with the multiple examination units, are located within the same examination area. This application embodiment uses modal recognition analysis of examination nodes within the same examination area as an example (i.e., modal recognition analysis of one examination area as an example). The implementation process of modal recognition analysis for each examination area within multiple examination areas can be referred to the description in this application embodiment, and will not be elaborated upon here.

[0096] In summary, the technical solution provided in this application involves a modal recognition and analysis device that determines multiple observation units on a body-in-white model based on a user-triggered selection command. Each observation unit corresponds one-to-one with multiple observation nodes. The modal recognition and analysis device creates modal recognition and analysis cards corresponding to these observation nodes based on received modal recognition and analysis parameters. These cards record the modal recognition and analysis parameters, and each observation node corresponds to multiple modal recognition and analysis cards. Different modal recognition and analysis cards for the same observation node record different modal recognition and analysis parameters. The modal recognition and analysis device performs modal recognition and analysis on these observation nodes based on the modal recognition and analysis cards corresponding to them. Compared to traditional technologies, this application's embodiment involves less manual intervention and fewer repetitive manual operations during the body-in-white analysis process, resulting in higher efficiency and less error-prone modal recognition and analysis.

[0097] For ease of understanding, the modal recognition and analysis method for the body-in-white is described below using an embodiment. This modal recognition and analysis method is performed by a modal recognition device for the body-in-white.

[0098] like Figure 2As shown, the modal recognition and analysis device determines multiple observation units on the body-in-white model based on user-triggered selection commands. These observation units are located within the same observation area. The device then determines observation nodes corresponding to each observation unit, with each observation node being the center point of its corresponding observation unit. The device adjusts the observation units according to user requirements. Based on the adjusted observation units, the device determines the corresponding observation nodes, with the adjusted observation units located within the observation area. The device receives modal recognition and analysis parameters. Based on the received parameters, the device creates modal recognition and analysis cards corresponding to the multiple observation nodes, which are located within the observation area. The device performs modal recognition and analysis on these nodes using the corresponding cards to obtain their modal recognition signals. Finally, the device stores these modal recognition signals in storage space according to a storage path.

[0099] The modal recognition and analysis device acquires the identifier of the target observation node. Based on this identifier, the device searches for the modal recognition signal of the target observation node in the storage space. The device then acquires the modal recognition signal of the target observation node. Finally, based on the modal recognition signal, the device generates a modal recognition curve for the target observation node.

[0100] in, Figure 2 For a detailed explanation and beneficial effects of the modal recognition analysis method for the white body shown, please refer to [reference needed]. Figure 1 The explanation of the modal recognition analysis method for the white body shown is omitted here.

[0101] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0102] Please refer to Figure 3 This illustration shows a schematic diagram of a modal recognition and analysis device 300 for a body-in-white provided in an embodiment of this application. The modal recognition and analysis device 300 is used to perform... Figure 1 or Figure 2 The method provided in the illustrated embodiment. The modal recognition and analysis device 300 may be a computer device or a functional component within a computer device. See also Figure 3 The modal recognition and analysis device 300 includes: a determination module 301, a creation module 302, and an analysis module 303.

[0103] The determination module 301 is used to determine multiple inspection units on the body-in-white model according to the selection command triggered by the user. The selection command is used to select the multiple inspection units on the body-in-white model. The multiple inspection units correspond one-to-one with multiple inspection nodes. Each inspection node is the center point of the corresponding inspection unit. The body-in-white model is created for the body-in-white and is used to characterize the structural features of the body-in-white.

[0104] The creation module 302 is used to create modal recognition analysis cards corresponding to the multiple examination nodes based on the received modal recognition analysis parameters. The modal recognition analysis cards are used to record the modal recognition analysis parameters. Each of the multiple examination nodes corresponds to multiple modal recognition analysis cards, and different modal recognition analysis cards corresponding to the same examination node record different modal recognition analysis parameters.

[0105] Analysis module 303 is used to perform modal recognition analysis on the multiple examination nodes based on the modal recognition analysis cards corresponding to the multiple examination nodes.

[0106] Optionally, the creation module 302 is used to: create multiple load set cards corresponding to the multiple investigation nodes in batches according to the received load parameters. The load set cards are used to record load parameters, wherein the modal identification analysis parameters include load parameters, and the modal identification analysis cards include load set cards.

[0107] Optionally, the creation module 302 is also used to: create working condition cards corresponding to the multiple observation nodes based on the received working condition parameters. The working condition cards are used to record the working condition parameters, wherein the modal recognition analysis parameters include the working condition parameters, and the modal recognition analysis cards include the working condition cards.

[0108] Optionally, the operating condition parameters include at least one of modal output range, excitation frequency range, damping parameters, and dynamic load table function, wherein the dynamic load table function is a table function used to generate dynamic loads related to frequency and time; the operating condition card includes at least one of modal range card, excitation frequency card, damping card, and dynamic load table function card; the modal range card is used to record the modal output range; the excitation frequency card is used to record the excitation frequency range; the damping card is used to record the damping parameters; and the dynamic load table function card is used to record the dynamic load table function.

[0109] Optionally, create module 302 to perform at least one of the following:

[0110] Based on the received modal output range, create modal range cards corresponding to the multiple examination nodes, wherein the multiple examination nodes correspond to the same modal range card;

[0111] Based on the received excitation frequency range, create excitation frequency cards corresponding to the multiple observation nodes, wherein the multiple observation nodes correspond to the same excitation frequency card;

[0112] Based on the received damping parameters, create damping cards corresponding to the multiple inspection nodes, wherein the multiple inspection nodes correspond to the same damping card;

[0113] Based on the received dynamic load table function, create dynamic load table function cards corresponding to the multiple examination nodes, wherein the multiple examination nodes correspond to the same dynamic load table function card.

[0114] Optionally, the creation module 302 is further configured to: create multiple dynamic load cards corresponding one-to-one with the multiple load set cards and the dynamic load table function card, wherein the dynamic load card corresponding to each of the multiple test nodes is used to associate the load set card corresponding to each test node with the dynamic load table function card, and the working condition card also includes the dynamic load card.

[0115] Optionally, the creation module 302 is also used to: create a dynamic load assembly card based on the plurality of dynamic load cards, the dynamic load assembly card being used to associate the plurality of dynamic load cards.

[0116] Optionally, module 302 is also used to: create load step cards based on dynamic load assembly cards.

[0117] Optionally, the creation module 302 is also used to: create mode control cards corresponding to the multiple observation nodes based on the received mode control parameters. The mode control cards are used to record mode control parameters, and the modal recognition analysis parameters include mode control parameters. The modal recognition analysis cards include mode control cards.

[0118] Optionally, the creation module 302 is also used to: create a global control card based on the modal range card, the excitation frequency card, and the damping card, the global control card being used to associate the modal range card, the excitation frequency card, and the damping card.

[0119] In summary, the technical solution provided in this application involves a modal recognition and analysis device that determines multiple observation units on a body-in-white model based on a user-triggered selection command. Each observation unit corresponds one-to-one with multiple observation nodes. The modal recognition and analysis device creates modal recognition and analysis cards corresponding to these observation nodes based on received modal recognition and analysis parameters. These cards record the modal recognition and analysis parameters, and each observation node corresponds to multiple modal recognition and analysis cards. Different modal recognition and analysis cards for the same observation node record different modal recognition and analysis parameters. The modal recognition and analysis device performs modal recognition and analysis on these observation nodes based on the modal recognition and analysis cards corresponding to them. Compared to traditional technologies, this application's embodiment involves less manual intervention and fewer repetitive manual operations during the body-in-white analysis process, resulting in higher efficiency and less error-prone modal recognition and analysis.

[0120] This application provides a modal recognition and analysis device for a body-in-white, comprising a memory and a processor. The memory stores a computer program. When executed by the processor, the computer program implements... Figure 1 or Figure 2 The illustrated embodiment provides a modal recognition and analysis method for a body-in-white. The modal recognition and analysis device can be a computer device or a functional component within a computer device.

[0121] As an example, please refer to Figure 4 , Figure 4 This is a schematic diagram of another modal recognition and analysis device 400 for a body-in-white provided in this application embodiment. The modal recognition and analysis device 400 may be a computer device or a functional component within a computer device, and is used to perform actions such as... Figure 1 or Figure 2 The method provided in the illustrated embodiment.

[0122] Typically, the modality recognition and analysis device 400 includes a processor 401 and a memory 402.

[0123] Processor 401 may include one or more processing cores, such as a quad-core processor, an octa-core processor, etc. Processor 401 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Processor 401 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, processor 401 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, processor 401 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0124] The memory 402 may include one or more computer-readable storage media, which may be non-transitory. The memory 402 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 402 is used to store a computer program, which includes at least one instruction, and the computer program (e.g., the at least one instruction) is executed by the processor 401 to implement the modal recognition and analysis method for the body-in-white provided in the embodiments of this application.

[0125] In some embodiments, the modal recognition and analysis device 400 may optionally include: a peripheral device interface 403 and at least one peripheral device. The processor 401, memory 402, and peripheral device interface 403 can be connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface 403 via a bus, signal line, or circuit board. Specifically, the peripheral device includes at least one of: a radio frequency circuit 404, a display screen 405, a camera 406, an audio circuit 407, a positioning component 408, and a power supply 409.

[0126] Peripheral device interface 403 can be used to connect at least one I / O (Input / Output) related peripheral device to processor 401 and memory 402. In some embodiments, processor 401, memory 402 and peripheral device interface 403 are integrated on the same chip or circuit board; in some other embodiments, any one or two of processor 401, memory 402 and peripheral device interface 403 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0127] The radio frequency (RF) circuit 404 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The RF circuit 404 communicates with communication networks and other communication devices via electromagnetic signals. The RF circuit 404 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals back into electrical signals. Optionally, the RF circuit 404 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, etc. The RF circuit 404 can communicate with other terminals through at least one wireless communication protocol. This wireless communication protocol includes, but is not limited to: the World Wide Web, metropolitan area networks, intranets, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and / or WiFi (Wireless Fidelity) networks. In some embodiments, the RF circuit 404 may also include circuitry related to NFC (Near Field Communication), which is not limited in this application embodiment.

[0128] Display screen 405 is used to display a UI (User Interface). This UI may include graphics, text, icons, videos, and any combination thereof. When display screen 405 is a touch display screen, it also has the ability to collect touch signals on or above its surface. These touch signals can be input as control signals to processor 401 for processing. In this case, display screen 405 can also be used to provide virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments, there may be one display screen 405, serving as the front panel of the modal recognition analysis device 400; in other embodiments, there may be at least two display screens 405, respectively disposed on different surfaces of the modal recognition analysis device 400 or in a folded design; in still other embodiments, display screen 405 may be a flexible display screen, disposed on a curved or folded surface of the modal recognition analysis device 400. Furthermore, display screen 405 may be configured as a non-rectangular irregular shape, i.e., a non-rectangular screen. Display screen 405 may be made of materials such as LCD (Liquid Crystal Display) or OLED (Organic Light-Emitting Diode).

[0129] The camera assembly 406 is used to acquire images or videos. Optionally, the camera assembly 406 includes a front-facing camera and a rear-facing camera. Typically, the front-facing camera is located on the front panel of the terminal, and the rear-facing camera is located on the back of the terminal. In some embodiments, there are at least two rear-facing cameras, which are any one of a main camera, a depth-sensing camera, a wide-angle camera, and a telephoto camera, to achieve background blurring by fusion of the main camera and the depth-sensing camera, panoramic shooting by fusion of the main camera and the wide-angle camera, VR (Virtual Reality) shooting, or other fusion shooting functions. In some embodiments, the camera assembly 406 may also include a flash. The flash can be a single-color temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm light flash and a cool light flash, which can be used for light compensation at different color temperatures.

[0130] The audio circuit 407 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, converting the sound waves into electrical signals that are input to the processor 401 for processing, or input to the radio frequency circuit 404 to achieve voice communication. For stereo sound acquisition or noise reduction purposes, multiple microphones may be used, each positioned at a different location in the modal recognition and analysis device 400. The microphone may also be an array microphone or an omnidirectional microphone. The speaker is used to convert the electrical signals from the processor 401 or the radio frequency circuit 404 into sound waves. The speaker may be a conventional thin-film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can convert electrical signals not only into audible sound waves but also into inaudible sound waves for purposes such as distance measurement. In some embodiments, the audio circuit 407 may also include a headphone jack.

[0131] The positioning component 408 is used by the positioning modality recognition and analysis device 400 to determine the geographic location for navigation or LBS (Location Based Service). The positioning component 408 can be a positioning component based on the Global Positioning System (GPS), BeiDou system, or Galileo system.

[0132] Power supply 409 supplies power to the various components in modal recognition and analysis device 400. Power supply 409 can be AC ​​power, DC power, a disposable battery, or a rechargeable battery. When power supply 409 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is charged via a wired connection, while a wireless rechargeable battery is charged via a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0133] In some embodiments, the modal recognition and analysis device 400 further includes one or more sensors 410. The one or more sensors 410 include, but are not limited to: an accelerometer 411, a gyroscope 412, a pressure sensor 413, a fingerprint sensor 414, and an optical sensor 415.

[0134] Accelerometer 411 can detect the magnitude of acceleration on the three coordinate axes of a coordinate system established by modal recognition and analysis device 400. For example, accelerometer 411 can be used to detect the components of gravitational acceleration on the three coordinate axes. Processor 401 can control display screen 405 to display the user interface in either a landscape or portrait view based on the gravitational acceleration signal acquired by accelerometer 411. Accelerometer 411 can also be used for games or for acquiring user motion data.

[0135] The gyroscope sensor 412 can detect the body orientation and rotation angle of the modal recognition and analysis device 400. The gyroscope sensor 412 can work in conjunction with the accelerometer sensor 411 to collect the user's 3D movements on the modal recognition and analysis device 400. Based on the data collected by the gyroscope sensor 412, the processor 401 can perform the following functions: motion sensing (e.g., changing the UI based on the user's tilt operation), image stabilization during shooting, game control, and inertial navigation.

[0136] The pressure sensor 413 can be disposed on the side bezel of the modal recognition and analysis device 400 and / or on the lower layer of the display screen 405. When the pressure sensor 413 is disposed on the side bezel of the modal recognition and analysis device 400, it can detect the user's grip signal on the modal recognition and analysis device 400, and the processor 401 can perform left / right hand recognition or quick operation based on the grip signal collected by the pressure sensor 413. When the pressure sensor 413 is disposed on the lower layer of the display screen 405, the processor 401 can control the operable controls on the UI interface based on the user's pressure operation on the display screen 405. The operable controls include at least one of button controls, scroll bar controls, icon controls, and menu controls.

[0137] The fingerprint sensor 414 is used to collect the user's fingerprint. The processor 401 identifies the user's identity based on the fingerprint collected by the fingerprint sensor 414, or the fingerprint sensor 414 identifies the user's identity based on the collected fingerprint. When the user's identity is identified as trusted, the processor 401 authorizes the user to perform relevant sensitive operations, including unlocking the screen, viewing encrypted information, downloading software, making payments, and changing settings. The fingerprint sensor 414 can be located on the front, back, or side of the display screen 405. When the display screen 405 has physical buttons or a manufacturer's logo, the fingerprint sensor 414 can be integrated with the physical buttons or manufacturer's logo.

[0138] An optical sensor 415 is used to collect ambient light intensity. In one embodiment, the processor 401 can control the display brightness of the display screen 405 based on the ambient light intensity collected by the optical sensor 415. Specifically, when the ambient light intensity is high, the display brightness of the display screen 405 is increased; when the ambient light intensity is low, the display brightness of the display screen 405 is decreased. In another embodiment, the processor 401 can also dynamically adjust the shooting parameters of the camera assembly 406 based on the ambient light intensity collected by the optical sensor 415.

[0139] In some embodiments, a computer-readable storage medium is also provided, which stores a computer program that, when executed (e.g., by a processor, a modal recognition analysis device for a body-in-white, etc.), implements all or part of the steps of the modal recognition analysis method for a body-in-white described above.

[0140] It is worth noting that the computer-readable storage medium mentioned in the embodiments of this application can be a non-volatile storage medium, in other words, it can be a non-transient storage medium.

[0141] It should be understood that all or part of the steps of the above embodiments can be implemented by software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented in whole or in part as a computer program product. A computer program product includes one or more computer instructions. The computer instructions can be stored in the above-described computer-readable storage medium.

[0142] In some embodiments, this application also provides a computer program product, including a computer program / instruction, which, when executed (e.g., by a processor, a modal recognition analysis device for a body-in-white, etc.), implements all or part of the steps of the modal recognition analysis method for the body-in-white described above.

[0143] It should be understood that "at least one" as mentioned herein refers to one or more, and "multiple" refers to two or more. In the description of the embodiments of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B; "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. In addition, in order to clearly describe the technical solutions of the embodiments of this application, the terms "first," "second," etc., are used in the embodiments of this application to distinguish identical or similar items with substantially the same function and effect. Those skilled in the art will understand that the terms "first," "second," etc., do not limit the quantity or execution order, and the terms "first," "second," etc., are not necessarily different.

[0144] The method embodiments and device embodiments provided in this application can be referenced interchangeably, and this application does not limit them. The order of operations in the method embodiments provided in this application can be appropriately adjusted, and operations can be added or removed as needed. Any variations that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the protection scope of this application, and therefore will not be elaborated further.

[0145] In the corresponding embodiments provided in this application, it should be understood that the disclosed devices, etc., can be implemented by other configurations. For example, the device embodiments described above are merely illustrative. For instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0146] The modules described as separate components may or may not be physically separate, and the components described as modules may or may not be physical modules. Some or all of the modules can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0147] It should be noted that all information (including but not limited to modal recognition analysis parameters), data (including but not limited to data used for analysis, collected data, and stored data), and signals (including but not limited to the aforementioned modal recognition signals) involved in this application have been authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. For example, the location information and modal recognition analysis parameters involved in this application were obtained with full authorization.

[0148] The above are merely optional embodiments of this application and are not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A modal recognition and analysis method for a white body, characterized in that, The method includes: Based on the selection command triggered by the user, multiple inspection units on the body-in-white model are determined. The selection command is used to select the multiple inspection units on the body-in-white model. The multiple inspection units correspond one-to-one with multiple inspection nodes. Each inspection node is the center point of the corresponding inspection unit. The body-in-white model is created for the body-in-white and is used to characterize the structural features of the body-in-white. Based on the received modality recognition analysis parameters, modality recognition analysis cards are created corresponding to the plurality of observation nodes. The modality recognition analysis cards are used to record the modality recognition analysis parameters. Each observation node corresponds to a plurality of modality recognition analysis cards, and different modality recognition analysis cards corresponding to the same observation node record different modality recognition analysis parameters. Modal recognition analysis is performed on the multiple examination nodes based on the modal recognition analysis cards corresponding to the multiple examination nodes.

2. The method according to claim 1, characterized in that, The step of creating modality recognition analysis cards corresponding to the multiple observation nodes based on the received modality recognition analysis parameters includes: Based on the received load parameters, multiple load set cards are created in batches, each corresponding to one of the multiple investigation nodes. The load set cards are used to record the load parameters, wherein the modal identification and analysis parameters include the load parameters, and the modal identification and analysis cards include the load set cards.

3. The method according to claim 2, characterized in that, The step of creating modality recognition analysis cards corresponding to the multiple observation nodes based on the received modality recognition analysis parameters further includes: Based on the received operating condition parameters, operating condition cards are created corresponding to the multiple observation nodes. The operating condition cards are used to record the operating condition parameters. The modal recognition analysis parameters also include the operating condition parameters, and the modal recognition analysis cards also include the operating condition cards.

4. The method according to claim 3, characterized in that, The operating condition parameters include at least one of modal output range, excitation frequency range, damping parameters, and dynamic load table function, wherein the dynamic load table function is a table function used to generate dynamic loads related to frequency and time; the operating condition card includes at least one of modal range card, excitation frequency card, damping card, and dynamic load table function card. The modal range card is used to record the modal output range; The excitation frequency card is used to record the excitation frequency range; The damping card is used to record the damping parameters; The dynamic load table function card is used to record the dynamic load table function.

5. The method according to claim 4, characterized in that, The step of creating working condition cards corresponding to the multiple inspection nodes based on the received working condition parameters includes at least one of the following: Based on the received modal output range, create modal range cards corresponding to the plurality of investigation nodes, wherein the plurality of investigation nodes correspond to the same modal range card; Based on the received excitation frequency range, create excitation frequency cards corresponding to the plurality of observation nodes, wherein the plurality of observation nodes correspond to the same excitation frequency card; Based on the received damping parameters, damping cards are created corresponding to the plurality of inspection nodes, wherein the plurality of inspection nodes correspond to the same damping card; Based on the received dynamic load table function, dynamic load table function cards corresponding to the plurality of examination nodes are created, wherein the plurality of examination nodes correspond to the same dynamic load table function card.

6. The method according to claim 5, characterized in that, The step of creating working condition cards corresponding to the multiple inspection nodes based on the received working condition parameters further includes: Based on the plurality of load set cards and the dynamic load table function cards, a plurality of dynamic load cards are created that correspond one-to-one with the plurality of examination nodes. The dynamic load card corresponding to each of the plurality of examination nodes is used to associate the load set card corresponding to each examination node with the dynamic load table function card. The working condition card also includes the dynamic load card.

7. The method according to claim 6, characterized in that, The step of creating working condition cards corresponding to the multiple inspection nodes based on the received working condition parameters further includes: A dynamic load assembly card is created based on the plurality of dynamic load cards, and the dynamic load assembly card is used to associate the plurality of dynamic load cards.

8. The method according to claim 7, characterized in that, The step of creating modality recognition analysis cards corresponding to the multiple observation nodes based on the received modality recognition analysis parameters further includes: Create a load step card based on the dynamic load assembly card.

9. The method according to claim 4, characterized in that, The step of creating modality recognition analysis cards corresponding to the multiple observation nodes based on the received modality recognition analysis parameters further includes: Based on the received mode control parameters, mode control cards are created corresponding to the multiple observation nodes. The mode control cards are used to record the mode control parameters. The modality recognition and analysis parameters include the mode control parameters, and the modality recognition and analysis cards include the mode control cards.

10. The method according to any one of claims 4-9, characterized in that, The step of creating modality recognition analysis cards corresponding to the multiple observation nodes based on the received modality recognition analysis parameters further includes: A global control card is created based on the modal range card, the excitation frequency card, and the damping card. The global control card is used to associate the modal range card, the excitation frequency card, and the damping card.

11. A modal recognition and analysis device for a white body, characterized in that, The device includes: The determination module is used to determine multiple inspection units on the body-in-white model according to the selection command triggered by the user. The selection command is used to select the multiple inspection units on the body-in-white model. The multiple inspection units correspond one-to-one with multiple inspection nodes. Each inspection node is the center point of the corresponding inspection unit. The body-in-white model is created for the body-in-white and is used to characterize the structural features of the body-in-white. A creation module is used to create modal recognition analysis cards corresponding to the multiple observation nodes based on the received modal recognition analysis parameters. The modal recognition analysis cards are used to record the modal recognition analysis parameters. Each observation node corresponds to multiple modal recognition analysis cards, and different modal recognition analysis cards corresponding to the same observation node record different modal recognition analysis parameters. The analysis module is used to perform modal recognition analysis on the multiple observation nodes based on the modal recognition analysis cards corresponding to the multiple observation nodes.

12. The apparatus according to claim 11, characterized in that, The creation module is used for: Based on the received load parameters, multiple load set cards are created in batches, each corresponding to one of the multiple investigation nodes. The load set cards are used to record the load parameters, wherein the modal identification and analysis parameters include the load parameters, and the modal identification and analysis cards include the load set cards.

13. The apparatus according to claim 12, characterized in that, The creation module is also used for: Based on the received operating condition parameters, operating condition cards are created corresponding to the multiple observation nodes. The operating condition cards are used to record the operating condition parameters. The modal recognition analysis parameters include the operating condition parameters, and the modal recognition analysis cards include the operating condition cards.

14. The apparatus according to claim 13, characterized in that, The operating condition parameters include at least one of modal output range, excitation frequency range, damping parameters, and dynamic load table function, wherein the dynamic load table function is a table function used to generate dynamic loads related to frequency and time; the operating condition card includes at least one of modal range card, excitation frequency card, damping card, and dynamic load table function card. The modal range card is used to record the modal output range; The excitation frequency card is used to record the excitation frequency range; The damping card is used to record the damping parameters; The dynamic load table function card is used to record the dynamic load table function.

15. The apparatus according to claim 14, characterized in that, The creation module is used to perform at least one of the following: Based on the received modal output range, create modal range cards corresponding to the plurality of investigation nodes, wherein the plurality of investigation nodes correspond to the same modal range card; Based on the received excitation frequency range, create excitation frequency cards corresponding to the plurality of observation nodes, wherein the plurality of observation nodes correspond to the same excitation frequency card; Based on the received damping parameters, damping cards are created corresponding to the plurality of inspection nodes, wherein the plurality of inspection nodes correspond to the same damping card; Based on the received dynamic load table function, dynamic load table function cards corresponding to the plurality of examination nodes are created, wherein the plurality of examination nodes correspond to the same dynamic load table function card.

16. The apparatus according to claim 15, characterized in that, The creation module is also used for: Based on the plurality of load set cards and the dynamic load table function cards, a plurality of dynamic load cards are created that correspond one-to-one with the plurality of examination nodes. The dynamic load card corresponding to each of the plurality of examination nodes is used to associate the load set card corresponding to each examination node with the dynamic load table function card. The working condition card also includes the dynamic load card.

17. The apparatus according to claim 16, characterized in that, The creation module is also used for: A dynamic load assembly card is created based on the plurality of dynamic load cards, and the dynamic load assembly card is used to associate the plurality of dynamic load cards.

18. The apparatus according to claim 17, characterized in that, The creation module is also used for: Create a load step card based on the dynamic load assembly card.

19. The apparatus according to claim 14, characterized in that, The creation module is also used for: Based on the received mode control parameters, mode control cards are created corresponding to the multiple observation nodes. The mode control cards are used to record the mode control parameters. The modality recognition and analysis parameters include the mode control parameters, and the modality recognition and analysis cards include the mode control cards.

20. The apparatus according to any one of claims 14-19, characterized in that, The creation module is further configured to: create a global control card based on the modal range card, the excitation frequency card, and the damping card, wherein the global control card is used to associate the modal range card, the excitation frequency card, and the damping card.

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