Abnormal sound prediction method and device for vehicle seat, equipment and medium

Abstract

The invention provides an abnormal sound prediction method and device for a vehicle seat, equipment and a medium, and the method comprises the steps: carrying out the friction abnormal sound test of a seat sample, obtaining a correlation matrix for the seat sample, and enabling the correlation matrix to be used for representing the mapping relation between a plurality of initial abnormal sound values of the seat sample and abnormal sound test parameters; carrying out whole vehicle simulation analysis on the seat sample to obtain abnormal sound induction factors of the seat sample; matching the abnormal sound inducing factors with the correlation matrix to obtain a target abnormal sound value of the seat sample; and performing judgment according to the target abnormal sound value and a preset threshold value, and outputting an abnormal sound prediction result of the seat sample, thereby realizing abnormal sound prediction on the seat in a seat development stage, avoiding the problem of abnormal sound of the vehicle seat in advance, determining generation of abnormal sound of the seat under different test conditions through the correlation matrix, and improving the test efficiency. The abnormal sound problem of the seat in actual use can be predicted more accurately and quickly by further combining actual test and whole vehicle simulation analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of abnormal noise prediction, and in particular to a method for predicting abnormal noise of a vehicle seat, a device for predicting abnormal noise of a vehicle seat, an electronic device and a computer-readable storage medium. Background Art

[0002] In the modern automobile industry, the comfort and quietness of seats are one of the key indicators of product quality. As consumers' requirements for the quality of the vehicle's internal environment increase, the problem of abnormal seat noise has gradually become the focus of manufacturers. Abnormal noise not only affects the passengers' riding experience, but may also indicate potential defects in materials or structures.

[0003] The existing technology for abnormal noise detection of vehicle seats mainly involves bench testing of seats or subjective evaluation of the entire vehicle after the seat module is produced. It may not be possible to fully discover all potential abnormal noise problems, and once abnormal noise problems are discovered in later tests, rectification will become very difficult and time-consuming, which will not only affect the product's time to market, but also lead to additional cost expenditures. There are problems such as insufficient problem discovery, untimely problem rectification and high testing costs. Summary of the invention

[0004] The embodiments of the present invention provide a method, device, equipment and medium for predicting abnormal noise of a vehicle seat, so as to solve the problem of low efficiency and accuracy in predicting abnormal noise of a vehicle seat in the prior art.

[0005] The embodiment of the present invention discloses a method for predicting abnormal noise of a vehicle seat, the method comprising:

[0006] Performing a friction noise test on a seat sample to obtain a correlation matrix for the seat sample, wherein the correlation matrix is ​​used to characterize a mapping relationship between a plurality of initial noise values ​​of the seat sample and noise test parameters;

[0007] Performing a whole vehicle simulation analysis on the seat sample to obtain the abnormal noise inducing factors of the seat sample;

[0008] Matching the abnormal noise inducing factors with the correlation matrix to obtain a target abnormal noise value of the seat sample;

[0009] A judgment is made based on the target abnormal noise value and the preset threshold, and the abnormal noise prediction result of the seat sample is output.

[0010] Optionally, performing a friction noise test on the seat sample to obtain a correlation matrix for the seat sample includes:

[0011] Acquiring abnormal noise test parameters for the seat sample;

[0012] Performing a friction noise test on the seat sample according to the noise test parameters to obtain an initial noise value of the seat sample;

[0013] The initial abnormal sound value and the abnormal sound test parameter corresponding to the initial abnormal sound value are combined to obtain the correlation matrix.

[0014] Optionally, the abnormal noise test parameters include at least a first positive pressure and a first relative movement speed, and the performing of the friction abnormal noise test on the seat sample to obtain a correlation matrix for the seat sample includes:

[0015] Performing a friction noise test on the seat sample according to the first positive pressure and the first relative movement speed to obtain the initial noise value;

[0016] The initial abnormal sound value is combined with the first positive pressure and the first relative movement speed to obtain the correlation matrix.

[0017] Optionally, before performing the whole vehicle simulation analysis on the seat sample, the method further includes:

[0018] Acquire a test vehicle, and perform a road noise test on the test vehicle to obtain a time domain signal generated by the test vehicle during the road noise test;

[0019] The time domain signal is used as an excitation condition for performing a whole vehicle simulation analysis on the seat sample.

[0020] Optionally, performing a whole vehicle simulation analysis on the seat sample to obtain the abnormal noise inducing factors of the seat sample includes:

[0021] A whole vehicle simulation analysis is performed on the seat sample according to the excitation condition to obtain a second positive pressure and a second relative motion speed generated by the seat sample during the whole vehicle simulation analysis.

[0022] Optionally, matching the abnormal noise inducing factor with the correlation matrix to obtain a target abnormal noise value of the seat sample includes:

[0023] An initial abnormal sound value corresponding to a first positive pressure and a first relative movement speed which are equal to the second positive pressure and the second relative movement speed is used as the target abnormal sound value.

[0024] Optionally, judging according to the target abnormal sound value and a preset threshold value and outputting the abnormal sound prediction result of the seat sample includes:

[0025] If the target abnormal noise value is greater than the preset threshold value, the seat sample has an abnormal noise risk;

[0026] If the target abnormal noise value is less than the preset threshold value, there is no abnormal noise risk for the seat sample.

[0027] The embodiment of the present invention further provides a device for predicting abnormal noise of a vehicle seat, the device comprising:

[0028] A correlation matrix determination module, used for performing a friction noise test on a seat sample to obtain a correlation matrix for the seat sample, wherein the correlation matrix is ​​used for representing a mapping relationship between a plurality of initial noise values ​​of the seat sample and noise test parameters;

[0029] A simulation analysis module, used for performing a whole vehicle simulation analysis on the seat sample to obtain the abnormal noise inducing factors of the seat sample;

[0030] A target abnormal sound value determination module, used for matching the abnormal sound inducing factor with the correlation matrix to obtain a target abnormal sound value of the seat sample;

[0031] The prediction result output module is used to make a judgment based on the target abnormal sound value and the preset threshold, and output the abnormal sound prediction result of the seat sample.

[0032] Optionally, the correlation matrix determination module includes:

[0033] A test parameter acquisition module, used to acquire abnormal noise test parameters for the seat sample;

[0034] A friction noise test module, used for performing a friction noise test on the seat sample according to the noise test parameters to obtain an initial noise value of the seat sample;

[0035] The correlation matrix generating module is used to combine the initial abnormal sound value with the abnormal sound test parameter corresponding to the initial abnormal sound value to obtain the correlation matrix.

[0036] Optionally, the abnormal sound test parameters include at least a first positive pressure and a first relative movement speed;

[0037] The friction abnormal noise testing module is specifically used to perform a friction abnormal noise test on the seat sample according to the first positive pressure and the first relative movement speed to obtain the initial abnormal noise value;

[0038] The correlation matrix generation module is specifically used to combine the initial abnormal sound value with the first positive pressure and the first relative movement speed to obtain the correlation matrix.

[0039] Optionally, the device further comprises:

[0040] The road noise test module is used to obtain a test vehicle and perform a road noise test on the test vehicle to obtain a time domain signal generated by the test vehicle during the road noise test; and use the time domain signal as an excitation condition for whole vehicle simulation analysis of the seat sample.

[0041] Optionally, the simulation analysis module is specifically used to perform a whole-vehicle simulation analysis on the seat sample according to the excitation conditions, and obtain a second positive pressure and a second relative movement speed generated by the seat sample during the whole-vehicle simulation analysis.

[0042] Optionally, the target abnormal sound value determination module is specifically configured to use an initial abnormal sound value corresponding to a first positive pressure and a first relative movement speed that are equal to the second positive pressure and the second relative movement speed as the target abnormal sound value.

[0043] Optionally, the abnormal noise prediction result output module is specifically used to determine that if the target abnormal noise value is greater than the preset threshold, then the seat sample has an abnormal noise risk; if the target abnormal noise value is less than the preset threshold, then the seat sample does not have an abnormal noise risk.

[0044] The embodiment of the present invention further discloses an electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0045] The memory is used to store computer programs;

[0046] The processor is used to implement the method described in the embodiment of the present invention when executing the program stored in the memory.

[0047] The embodiment of the present invention further discloses a computer-readable storage medium having instructions stored thereon, which, when executed by one or more processors, enables the processors to execute the method described in the embodiment of the present invention.

[0048] Compared with the prior art, the embodiments of the present invention have the following advantages:

[0049] In an embodiment of the present invention, a seat sample is subjected to a friction noise test to obtain a correlation matrix for the seat sample, the correlation matrix being used to characterize a mapping relationship between multiple initial noise values ​​of the seat sample and noise test parameters; a whole vehicle simulation analysis is performed on the seat sample to obtain noise inducing factors of the seat sample; the noise inducing factors are matched with the correlation matrix to obtain a target noise value of the seat sample; a judgment is made based on the target noise value and a preset threshold, and a noise prediction result of the seat sample is output, thereby realizing noise prediction of the seat in the seat development stage, avoiding the problem of vehicle seat noise in advance, avoiding the problem of untimely rectification of subsequent problems and high testing costs, the correlation matrix obtained through actual testing can clarify the noise generation of the seat under different test conditions, and the whole vehicle simulation analysis can predict the behavioral characteristics of the seat in actual use without a large number of actual tests, and further combining actual testing and simulation analysis can more accurately, quickly and comprehensively predict the noise problem of the seat in actual use. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0051] Figure 1 is a flowchart of the steps of a method for predicting abnormal noise of a vehicle seat provided by an embodiment of the present invention;

[0052] Figure 2 is a schematic diagram of a scenario of performing a friction noise test on a seat sample provided by an embodiment of the present invention;

[0053] Figure 3 It is a structural block diagram of an abnormal noise prediction device for a vehicle seat provided by an embodiment of the present invention;

[0054] Figure 4 is a block diagram of an electronic device provided in an embodiment of the present invention;

[0055] Figure 5 is a schematic diagram of a computer-readable storage medium provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] As an example, seats are usually tested for abnormal noise before a vehicle is launched on the market. The existing technology is to conduct friction and abnormal noise tests on seats after they are mass-produced, or after the seats are installed in the vehicle, the developers conduct a subjective evaluation of the entire vehicle to identify problems and make corrections. It may not be possible to fully discover all potential abnormal noise problems, and if abnormal noise problems are found in subsequent abnormal noise tests, it will not only affect the product's time to market, but also lead to additional cost expenditures. There are problems such as insufficient problem discovery, untimely problem rectification and high testing costs.

[0058] In this regard, the advantages of the present invention over the prior art are that it can predict abnormal noises in seats during the seat development stage, thereby avoiding the problem of abnormal noises in vehicle seats in advance and avoiding the problems of untimely rectification of subsequent problems and high testing costs. The correlation matrix obtained through actual testing can clearly identify the abnormal noises generated by seats under different test conditions, and the whole vehicle simulation analysis can predict the behavioral characteristics of seats in actual use without the need for a large number of actual tests. Further combining actual testing and simulation analysis can more accurately, quickly and comprehensively predict the problem of abnormal noises in seats in actual use.

[0059] Reference Figure 1 , shows a flowchart of a method for predicting abnormal noise of a vehicle seat provided in an embodiment of the present invention, which may specifically include the following steps:

[0060] Step 101: Perform a friction noise test on a seat sample to obtain a correlation matrix for the seat sample, wherein the correlation matrix is ​​used to characterize a mapping relationship between a plurality of initial noise values ​​of the seat sample and noise test parameters;

[0061] In an embodiment of the present invention, during the product development stage, a seat sample is selected from a design prototype for abnormal noise prediction to determine whether the seat sample has an abnormal noise risk. If so, the seat sample can be optimized in time to identify and solve potential abnormal noise problems in the early stage of product development, thereby ensuring the quality of the final product. In an embodiment of the present invention, first, in a controlled laboratory environment, a friction test is performed on the seat sample by setting different abnormal noise test parameters to simulate various friction conditions that the seat may encounter during use, and the initial abnormal noise value generated by the seat sample under specific conditions is obtained. The initial abnormal noise value can be determined by the loudness value measured during the test, that is, the initial abnormal noise value reflects the loudness generated by the seat during friction, and is correlated with the set test parameters. The initial abnormal noise value is combined with the corresponding test parameters to obtain a correlation matrix for the initial abnormal noise value of the seat sample. The abnormal noise value generated by the seat sample under different test conditions and the influence of the test parameters on the abnormal noise value can be intuitively known through the correlation matrix.

[0062] In a preferred embodiment of the present invention, step 101, performing a friction noise test on a seat sample to obtain a correlation matrix for the seat sample, includes: obtaining noise test parameters for the seat sample; performing a friction noise test on the seat sample according to the noise test parameters to obtain an initial noise value of the seat sample; combining the initial noise value with the noise test parameters corresponding to the initial noise value to obtain the correlation matrix.

[0063] In an embodiment of the present invention, abnormal noise test parameters are set for seat samples to determine the test conditions of the seat samples, and then the seat samples are tested according to the abnormal noise test parameters by means of a testing device. During the test, the testing device will record and convert the sound signals generated by the seat during the friction process to obtain the abnormal noise values ​​of the seat samples under specific test parameters, and the test results, i.e., the abnormal noise values, and the corresponding abnormal noise test parameters are combined into a correlation matrix, and then the abnormal noise characteristics of the seat samples can be systematically evaluated through the correlation matrix.

[0064] In a preferred embodiment of the present invention, the abnormal noise test parameters include at least a first positive pressure and a first relative movement speed, and the seat sample is subjected to a friction abnormal noise test according to the first positive pressure and the first relative movement speed to obtain the initial abnormal noise value; the initial abnormal noise value is combined with the first positive pressure and the first relative movement speed to obtain the correlation matrix.

[0065] In the embodiment of the present invention, the selection of abnormal noise test parameters is crucial for accurately evaluating the abnormal noise characteristics of the seat. The abnormal noise test parameters include at least the first positive pressure and the first relative movement speed. The first positive pressure refers to the positive pressure acting vertically on the seat surface, which is used to simulate the positive pressure that the seat is subjected to during actual use, and the first relative movement speed refers to the sliding speed of the seat surface relative to the opponent material, such as the relative movement speed between the seat sample and other seats or the relative movement speed between the seat sample and human clothing. The positive pressure and relative movement speed are the key factors for the abnormal noise generated by the friction of the seat during use. The abnormal noise test parameters can also include friction stroke, number of frictions, sound monitoring points, test environment noise, etc., which are not limited by the present invention.

[0066] As an example, combining Figure 2 , a schematic diagram of a scenario of performing a friction noise test on a seat sample provided by an embodiment of the present invention is shown, and performing the friction noise test on the seat sample includes the following steps:

[0067] S201, selecting the seat material A to be tested, the seat foam material and the opponent material;

[0068] S202, attaching the seat foam material to the upper friction table surface of the friction noise tester, further attaching the seat material A to be tested to the surface of the foam material, and attaching the counterpart material to the lower friction table surface of the friction noise tester;

[0069] S203. Set the test parameters: the positive pressure test range is 1N-80N, the relative movement speed is 5mm / s-10m / s, the friction stroke is ≥5mm, the number of frictions is 1-3 times, the sound monitoring point is 20-50mm away from the seat material to be tested, and the experimental environment noise is ≤30dB;

[0070] S204, the friction noise tester performs a friction noise test according to the test parameters, outputs a loudness curve, and takes the average value of the peak value of the loudness curve as the noise value;

[0071] S205, replacing the same seat material A to be tested, repeating the friction noise test, and taking the maximum noise value as the noise value under the test condition;

[0072] S206. Construct a correlation matrix according to the test results, as shown in Table 1, a correlation matrix of friction noise test of seat material A.

[0073] Table 1 Correlation matrix of friction noise test of seat material A

[0074]

[0075] Step 102: Perform a whole vehicle simulation analysis on the seat sample to obtain the abnormal noise inducing factors of the seat sample;

[0076] In an embodiment of the present invention, computer simulation technology is used to simulate the actual use of seat samples in a whole vehicle environment, and the triggering factors that cause abnormal noises generated by seat samples under various actual use conditions are identified, such as vibration and noise generated by friction generated by road excitation during actual use of the seat samples, and the positive pressure and relative movement speed of the friction position of the seat during actual use. The characteristics of the seat samples in actual use are obtained through simulation analysis, and the triggering conditions that may cause abnormal noises to be generated by the seat samples are identified. The number and cost of actual tests can be reduced through simulation analysis.

[0077] In a preferred embodiment of the present invention, before step 102, performing a whole vehicle simulation analysis on the seat sample to obtain the abnormal noise inducing factors of the seat sample, it includes: obtaining a test vehicle, and performing a road noise test on the test vehicle to obtain a time domain signal generated by the test vehicle during the road noise test; and using the time domain signal as an excitation condition for performing a whole vehicle simulation analysis on the seat sample.

[0078] In an embodiment of the present invention, a test vehicle is used to conduct a field road noise test, collect road spectrum information and time domain signals generated by the test vehicle under different road excitations, such as vibration signals generated by the test vehicle during the road noise test, use the road spectrum information as an excitation condition for simulation analysis, and then simulate the response of the seat sample when it is subjected to these road excitation conditions in the whole vehicle environment without a large number of actual tests. Specifically, the test vehicle can be a mule car, obtain a mule car for testing and verification, and install sensors on the chassis or other positions of the mule car to obtain time domain signals, and conduct road noise tests on various road surfaces such as Belgian roads, round cake roads, cobblestone roads, impact roads, and rope roads. The time domain signals generated by the mule car during the road noise test are collected as excitation signals for simulation analysis, and the vibration response of the seat sample in the whole vehicle environment is simulated, and the actual time domain signals are used as excitation conditions for the whole vehicle simulation analysis of the seat sample, which can improve the accuracy and reliability of the simulation, and the simulation results will be closer to the actual use situation, which helps to more accurately predict the noise risk of the seat sample during actual use.

[0079] In a preferred embodiment of the present invention, a whole vehicle simulation analysis is performed on the seat sample according to the excitation condition to obtain a second positive pressure and a second relative motion speed generated by the seat sample during the whole vehicle simulation analysis.

[0080] In an embodiment of the present invention, the time domain signal of the road noise test is used as an excitation condition for the whole vehicle simulation analysis. Through the simulation analysis, the positive pressure and relative movement speed of the seat under actual use conditions can be predicted.

[0081] Step 103, matching the abnormal noise inducing factor with the correlation matrix to obtain a target abnormal noise value of the seat sample;

[0082] In an embodiment of the present invention, the inducing factors that may cause abnormal noise generated by the seat sample during actual use are simulated, and the abnormal noise inducing factors are matched with the correlation matrix. The abnormal noise test parameters corresponding to the abnormal noise inducing factors are found in the correlation matrix, so as to obtain the initial abnormal noise value corresponding to the abnormal noise inducing factor, and use it as the target abnormal noise value that will be generated by the seat sample during actual use.

[0083] In a preferred embodiment of the present invention, step 103, matching the abnormal noise inducing factors and the correlation matrix to obtain the target abnormal noise value of the seat sample, includes: taking the initial abnormal noise value corresponding to the first positive pressure and the first relative movement speed equal to the second positive pressure and the second relative movement speed as the target abnormal noise value.

[0084] In an embodiment of the present invention, the positive pressure and relative movement speed to which the seat is subjected in the whole vehicle simulation analysis, i.e., under actual use conditions, are matched with the correlation matrix, and the same positive pressure and relative movement speed in the correlation matrix are obtained, and the corresponding initial abnormal noise value is used as the target abnormal noise value. The target abnormal noise value characterizes the abnormal noise level that the seat may generate in actual use. That is, the correlation matrix is ​​used as a benchmark. After the positive pressure and relative movement speed to which the seat is subjected under actual use conditions are obtained, the abnormal noise value of the seat sample in actual use can be determined through the correlation matrix. By combining the actual use characteristics of the seat sample obtained by simulation analysis with the characteristics of the seat sample in actual testing, the abnormal noise value of the seat sample can be determined, thereby improving the accuracy and efficiency of predicting the seat abnormal noise performance.

[0085] Step 104: judging according to the target abnormal sound value and the preset threshold, and outputting the abnormal sound prediction result of the seat sample;

[0086] In an embodiment of the present invention, the abnormal noise value for the seat sample obtained by combining the actual friction abnormal noise test and the whole vehicle simulation analysis is compared with the preset threshold value to determine whether the seat sample has the risk of abnormal noise during actual use. If there is a risk of abnormal noise, design optimization is required, which can be done by adjusting the foaming material, changing the structural design of the seat, etc., wherein the preset threshold value can be determined according to industry standards, internal standards, market demand or according to expert experience, and the present invention is not limited to this.

[0087] In a preferred embodiment of the present invention, in step 104, a judgment is made based on the target abnormal sound value and the preset threshold, and the abnormal sound prediction result of the seat sample is output, including: if the target abnormal sound value is greater than the preset threshold, then the seat sample has an abnormal sound risk; if the target abnormal sound value is less than the preset threshold, then the seat sample does not have an abnormal sound risk.

[0088] In an embodiment of the present invention, if the target abnormal sound value obtained after simulation analysis and correlation matrix comparison exceeds the preset threshold, this means that the abnormal sound level generated by the seat sample under specific use conditions exceeds the acceptable range, so there is a risk of abnormal sound. In this case, the design team needs to take measures to optimize the seat design to reduce the abnormal sound level and ensure that the product meets quality standards and user expectations; on the contrary, if the target abnormal sound value is less than or equal to the preset threshold, this indicates that the abnormal sound level generated by the seat sample under the same conditions is within an acceptable range, so there is no risk of abnormal sound. In this case, the seat sample can be considered to meet the design requirements, and subsequent quality control and production processes can be continued. For example, assuming that the preset threshold is 3sones (sones, a unit of loudness), if the target abnormal sound value of the seat sample is 2sones<3sones, then the seat sample has no abnormal sound risk, and if the target abnormal sound value of the seat sample is 4sones>3sones, then the seat sample has an abnormal sound risk and needs to be optimized.

[0089] In a preferred embodiment of the present invention, after constructing a correlation matrix of abnormal noise values ​​for the seat sample based on the friction noise test results of the seat sample, the seat sample name and the mark of the handpiece material corresponding to the correlation matrix are added to the correlation matrix, and a mark of abnormal noise risk or no abnormal noise risk is added to each initial abnormal noise value according to a preset threshold. Then, the mark of the initial abnormal noise value corresponding to the positive pressure and relative movement speed generated by the seat during use can be directly obtained, so as to intuitively obtain whether the seat sample has the risk of abnormal noise when subjected to the current positive pressure and relative movement speed, thereby improving the efficiency of abnormal noise prediction.

[0090] For example, the seat sample A is subjected to a friction noise test with the counterpart material A to obtain the correlation matrix A (see Table 2) between the seat sample A and the counterpart material A. If it is necessary to predict whether the seat sample A will produce noise when subjected to a positive pressure of 10N and 10mm / s during the friction process with the counterpart material A, the correlation matrix A can be directly compared to obtain the initial noise value corresponding to 10N and 10mm / s and marked as 0, indicating no noise risk. It is determined that the seat sample A will not produce noise when subjected to a positive pressure of 10N and 10mm / s during the friction process with the counterpart material A. Optionally, the letter marks in the correlation matrix can be added or modified to color marks, such as green for no noise risk and red for noise risk. Then, the user can more intuitively judge the noise risk of the seat sample under different positive pressures and relative movement speeds through the color marks, and quickly scan the correlation matrix to identify key information. Specifically, the present invention is not limited to this.

[0091] Table 2 Correlation matrix A between seat sample A and counterpart material A

[0092]

[0093] In an embodiment of the present invention, a seat sample is subjected to a friction noise test to obtain a correlation matrix for the seat sample, the correlation matrix being used to characterize a mapping relationship between multiple initial noise values ​​of the seat sample and noise test parameters; a whole vehicle simulation analysis is performed on the seat sample to obtain noise inducing factors of the seat sample; the noise inducing factors are matched with the correlation matrix to obtain a target noise value of the seat sample; a judgment is made based on the target noise value and a preset threshold, and a noise prediction result of the seat sample is output, thereby realizing noise prediction of the seat in the seat development stage, avoiding the problem of vehicle seat noise in advance, avoiding the problem of untimely rectification of subsequent problems and high testing costs, the correlation matrix obtained through actual testing can clarify the noise generation of the seat under different test conditions, and the whole vehicle simulation analysis can predict the behavioral characteristics of the seat in actual use without the need for a large number of actual tests, and further combining actual testing and simulation analysis can more accurately and quickly predict the noise problem of the seat in actual use.

[0094] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0095] Reference Figure 3 , shows a structural block diagram of an abnormal noise prediction device for a vehicle seat provided in an embodiment of the present invention, which may specifically include the following modules:

[0096] A correlation matrix determination module 301 is used to perform a friction noise test on a seat sample to obtain a correlation matrix for the seat sample, wherein the correlation matrix is ​​used to characterize a mapping relationship between a plurality of initial noise values ​​of the seat sample and noise test parameters;

[0097] A simulation analysis module 302 is used to perform a whole vehicle simulation analysis on the seat sample to obtain the abnormal noise inducing factors of the seat sample;

[0098] A target abnormal sound value determination module 303 is used to match the abnormal sound inducing factor with the correlation matrix to obtain a target abnormal sound value of the seat sample;

[0099] The prediction result output module 304 is used to make a judgment based on the target abnormal noise value and the preset threshold value, and output the abnormal noise prediction result of the seat sample.

[0100] In one embodiment of the present invention, the correlation matrix determination module 301 includes:

[0101] A test parameter acquisition module, used to acquire abnormal noise test parameters for the seat sample;

[0102] A friction noise test module, used for performing a friction noise test on the seat sample according to the noise test parameters to obtain an initial noise value of the seat sample;

[0103] The correlation matrix generating module is used to combine the initial abnormal sound value with the abnormal sound test parameter corresponding to the initial abnormal sound value to obtain the correlation matrix.

[0104] In one embodiment of the present invention, the abnormal sound test parameters include at least a first positive pressure and a first relative movement speed;

[0105] The friction abnormal noise testing module is specifically used to perform a friction abnormal noise test on the seat sample according to the first positive pressure and the first relative movement speed to obtain the initial abnormal noise value;

[0106] The correlation matrix generation module is specifically used to combine the initial abnormal sound value with the first positive pressure and the first relative movement speed to obtain the correlation matrix.

[0107] In one embodiment of the present invention, the device further comprises:

[0108] The road noise test module is used to obtain a test vehicle and perform a road noise test on the test vehicle to obtain a time domain signal generated by the test vehicle during the road noise test; and use the time domain signal as an excitation condition for whole vehicle simulation analysis of the seat sample.

[0109] In one embodiment of the present invention, the simulation analysis module is specifically used to perform a whole vehicle simulation analysis on the seat sample according to the excitation condition to obtain a second positive pressure and a second relative motion speed generated by the seat sample during the whole vehicle simulation analysis.

[0110] In one embodiment of the present invention, the target abnormal sound value determination module is specifically configured to use an initial abnormal sound value corresponding to a first positive pressure and a first relative movement speed equal to the second positive pressure and the second relative movement speed as the target abnormal sound value.

[0111] In one embodiment of the present invention, the abnormal noise prediction result output module is specifically used to determine that if the target abnormal noise value is greater than the preset threshold, then the seat sample has an abnormal noise risk; if the target abnormal noise value is less than the preset threshold, then the seat sample does not have an abnormal noise risk.

[0112] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0113] In addition, an embodiment of the present invention further provides an electronic device, such as Figure 4 As shown, it includes a processor 401, a communication interface 402, a memory 403 and a communication bus 404, wherein the processor 401, the communication interface 402, and the memory 403 communicate with each other through the communication bus 404.

[0114] Memory 403, used for storing computer programs;

[0115] The processor 401 is used to implement the method described in the above embodiment when executing the program stored in the memory 403.

[0116] The communication bus mentioned in the above terminal can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0117] The communication interface is used for communication between the above terminal and other devices.

[0118] The memory may include a random access memory (RAM) or a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0119] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0120] like Figure 5 As shown, in another embodiment provided by the present invention, a computer-readable storage medium 501 is also provided, in which instructions are stored. When the computer-readable storage medium is run on a computer, the computer executes the model training method described in the above embodiment.

[0121] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk Solid State Disk (SSD)), etc.

[0122] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0123] Each embodiment in this specification is described in a related manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0124] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.

Claims

1. A method for predicting abnormal noise of a vehicle seat, characterized in that: The method comprises: Performing a friction noise test on a seat sample to obtain a correlation matrix for the seat sample, wherein the correlation matrix is ​​used to characterize a mapping relationship between a plurality of initial noise values ​​of the seat sample and noise test parameters; Performing a whole vehicle simulation analysis on the seat sample to obtain the abnormal noise inducing factors of the seat sample; Matching the abnormal noise inducing factors with the correlation matrix to obtain a target abnormal noise value of the seat sample; A judgment is made based on the target abnormal noise value and the preset threshold, and the abnormal noise prediction result of the seat sample is output.

2. The method according to claim 1, characterized in that: The performing of a friction noise test on the seat sample to obtain a correlation matrix for the seat sample includes: Acquiring abnormal noise test parameters for the seat sample; Performing a friction noise test on the seat sample according to the noise test parameters to obtain an initial noise value of the seat sample; The initial abnormal sound value and the abnormal sound test parameter corresponding to the initial abnormal sound value are combined to obtain the correlation matrix.

3. The method according to claim 2, characterized in that: The abnormal noise test parameters at least include a first positive pressure and a first relative movement speed, and the abnormal noise test on the seat sample is performed to obtain a correlation matrix for the seat sample, including: Performing a friction noise test on the seat sample according to the first positive pressure and the first relative movement speed to obtain the initial noise value; The initial abnormal sound value is combined with the first positive pressure and the first relative movement speed to obtain the correlation matrix.

4. The method according to claim 3, characterized in that: Before performing the whole vehicle simulation analysis on the seat sample, the method further includes: Acquire a test vehicle, and perform a road noise test on the test vehicle to obtain a time domain signal generated by the test vehicle during the road noise test; The time domain signal is used as an excitation condition for performing a whole vehicle simulation analysis on the seat sample.

5. The method according to claim 4, characterized in that: The performing of whole vehicle simulation analysis on the seat sample to obtain the abnormal noise inducing factors of the seat sample includes: A whole vehicle simulation analysis is performed on the seat sample according to the excitation condition to obtain a second positive pressure and a second relative motion speed generated by the seat sample during the whole vehicle simulation analysis.

6. The method according to claim 5, characterized in that: The step of matching the abnormal noise inducing factor with the correlation matrix to obtain a target abnormal noise value of the seat sample includes: An initial abnormal sound value corresponding to a first positive pressure and a first relative movement speed which are equal to the second positive pressure and the second relative movement speed is used as the target abnormal sound value.

7. The method according to claim 1, characterized in that: The step of judging according to the target abnormal noise value and the preset threshold and outputting the abnormal noise prediction result of the seat sample includes: If the target abnormal noise value is greater than the preset threshold value, the seat sample has an abnormal noise risk; If the target abnormal noise value is less than the preset threshold value, there is no abnormal noise risk for the seat sample.

8. A vehicle seat abnormal noise prediction device, characterized in that: The device comprises: A correlation matrix determination module, used for performing a friction noise test on a seat sample to obtain a correlation matrix for the seat sample, wherein the correlation matrix is ​​used for characterizing a mapping relationship between a plurality of initial noise values ​​of the seat sample and noise test parameters; A simulation analysis module, used for performing a whole vehicle simulation analysis on the seat sample to obtain the abnormal noise inducing factors of the seat sample; a target abnormal sound value determination module, used for matching the abnormal sound inducing factor with the correlation matrix to obtain a target abnormal sound value of the seat sample; The prediction result output module is used to make a judgment based on the target abnormal sound value and the preset threshold, and output the abnormal sound prediction result of the seat sample.

9. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; The memory is used to store computer programs; The processor is used to implement the method according to any one of claims 1 to 7 when executing the program stored in the memory.

10. A computer-readable storage medium having instructions stored thereon, which, when executed by one or more processors, cause the processors to perform the method according to any one of claims 1 to 7.

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