Vehicle noise source identification method and device and storage medium

Abstract

The invention provides a noise source identification method and device and a storage medium, and belongs to the technical field of automobile noise control. The method comprises the steps that noise signals of a vehicle seat and a subsystem corresponding to the seat are collected; the noise signals of the subsystems corresponding to the seats serve as input, the noise signals of the seats serve as output, partial coherence function calculation is carried out, and partial coherence coefficients corresponding to the subsystems are obtained; and determining a noise source according to the partial coherence coefficient. Noise signal calculation is based on the whole vehicle symmetry principle, so that redundant analysis is reduced, calculation time is saved, and noise source recognition efficiency is improved; the partial coherence analysis method is adopted for air noise source recognition, influences of various factors on noise sources can be analyzed under the condition of multiple non-independent noise sources, noise source characteristics under the actual working condition can be analyzed without changing the field sound environment, the method is suitable for recognition of the transient noise sources of the whole vehicle, and the method is suitable for popularization and application. And the noise source identification accuracy is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of automobile noise control, and in particular relates to a vehicle noise source identification method, device and storage medium. Background Art

[0002] In recent years, with the continuous improvement of people's living standards, the requirements for automobile comfort have also been continuously improved. In-car noise affects comfort, and improving in-car noise is an important issue in the process of automobile design and development. In the development and design stage, the noise inside and outside the car should be analyzed, predicted and statistically analyzed to provide noise performance prediction data that meets actual requirements and is relatively accurate, thereby avoiding a large number of prototype design modifications and repeated tests, shortening the development cycle and reducing development costs. As an interior part, the automotive acoustic package not only has a decorative effect, but also plays a role in isolating external noise and absorbing internal noise. Identifying the source and transmission path of the noise and reasonably arranging the acoustic package are conducive to improving the noise inside the car, so a noise identification and control method is designed.

[0003] Common noise source identification methods include subjective evaluation method, spectrum analysis method, sound intensity analysis method, etc. The subjective evaluation method is greatly affected by human factors, and it is difficult to give a quantitative evaluation of the noise source; the spectrum analysis method can determine the frequency distribution of the noise source and the source of the peak noise through the noise spectrum diagram. Its disadvantage is that it can only be performed on a single measuring point, and the analysis of the main noise source is based on the entire vehicle; the sound intensity analysis method is suitable for the identification of steady-state sound sources and stationary sound sources, but is not suitable for transient sound sources.

[0004] Therefore, it is urgent to study a noise source identification method suitable for the transient sound source of the whole vehicle. Summary of the invention

[0005] The purpose of the present invention is to solve the above-mentioned problems existing in the prior art and to provide a noise source identification method, device and storage medium, which are suitable for identifying transient noise sources of a whole vehicle and improve the efficiency and accuracy of noise source identification.

[0006] The present invention is achieved through the following technical solutions:

[0007] A first aspect of the present invention provides a noise source identification method, comprising:

[0008] Collect noise signals of vehicle seats and corresponding subsystems of seats;

[0009] Taking the noise signal of the subsystem corresponding to the seat as input and the noise signal of the seat as output, the partial coherence function is calculated to obtain the partial coherence coefficient corresponding to the subsystem;

[0010] The noise source is determined based on the partial coherence coefficient.

[0011] A further improvement of the present invention is:

[0012] The specific operations of collecting the noise signals of the vehicle seat and the subsystem corresponding to the seat include:

[0013] Collect the noise signals of the seats and their corresponding subsystems under steady-state operating conditions;

[0014] If the vehicle has two rows of seats, a microphone is arranged on the right side of the driver's seat headrest and in the middle of the second row seat's right headrest; and a microphone is arranged in the subsystems corresponding to the driver's seat and the rear seat.

[0015] A further improvement of the present invention is:

[0016] The subsystems corresponding to the driver's seat include: left front door, left rear side door, left front door glass, left rear side door glass, engine compartment, instrument panel, front top cover, front floor, front windshield and left front wheel cover; and / or,

[0017] The subsystems corresponding to the second row of seats include: right front door, right rear side door, right front door glass, right rear side door glass, rear roof, rear floor, spare wheel well, rear windshield, left / right rear wheel covers and right rear side panel.

[0018] A further improvement of the present invention is:

[0019] The specific operations of collecting the noise signals of the vehicle seat and the subsystem corresponding to the seat include:

[0020] Collect the noise signals of the seats and their corresponding subsystems under steady-state operating conditions;

[0021] If the vehicle has three rows of seats, a microphone is arranged on the right side of the driver's seat headrest, in the middle of the right headrest of the second row of seats, and in the middle of the third row of seats, and a microphone is arranged in each subsystem corresponding to the driver's seat, the second row of seats, and the third row of seats.

[0022] A further improvement of the present invention is:

[0023] The subsystems corresponding to the driver's seat include: left front door, left rear side door, left front door glass, left rear side door glass, engine compartment, instrument panel, front top cover, front floor, front windshield and left front wheel cover; and / or,

[0024] The subsystems corresponding to the second row of seats include: right front door, right rear side door, right front door glass, right rear side door glass, rear top cover, rear floor, spare wheel well, rear windshield, left / right rear wheel covers and right rear side panel; and / or;

[0025] The subsystems corresponding to the third row of seats include: left rear side door, left rear side door glass, rear roof, rear floor, spare wheel well, rear windshield, left / right rear wheel covers and left rear side panel.

[0026] A further improvement of the present invention is:

[0027] The noise signal of the subsystem corresponding to the seat is used as input, and the noise signal of the seat is used as output to calculate the partial coherence function and obtain the partial coherence coefficient corresponding to the subsystem. The specific operations include:

[0028] The noise signals collected by the microphones arranged at the left front door, left rear side door, left front door glass, left rear side door glass, engine compartment, instrument panel, front top cover, front floor, front windshield and left front wheel cover are taken as input, and the noise signal collected by the microphone arranged at the right side of the driver's seat headrest is taken as output. The partial coherence function is calculated to obtain the partial coherence coefficients corresponding to each subsystem of the driver's seat.

[0029] A further improvement of the present invention is:

[0030] The noise signal of the subsystem corresponding to the seat is used as input, and the noise signal of the seat is used as output to calculate the partial coherence function and obtain the partial coherence coefficient corresponding to the subsystem. The specific operations also include:

[0031] The noise signals collected by the microphones arranged at the right front door, right rear side door, right front door glass, right rear side door glass, rear roof, rear floor, spare wheel well, rear windshield, left / rear wheel cover and right rear side panel are taken as input, and the noise signals collected by the microphone arranged in the middle of the headrest of the second row right seat are taken as output. The partial coherence function is calculated to obtain the partial coherence coefficients corresponding to each subsystem of the second row seat.

[0032] A further improvement of the present invention is:

[0033] The noise signal of the subsystem corresponding to the seat is used as input, and the noise signal of the seat is used as output to calculate the partial coherence function and obtain the partial coherence coefficient corresponding to the subsystem. The specific operations also include:

[0034] The noise signals collected by the microphones arranged at the left rear door, left rear door glass, rear roof, rear floor, spare wheel well, rear windshield, left / right rear wheel cover and left rear side panel are taken as input, and the microphone arranged in the middle position of the third row is taken as output. The partial coherence function is calculated to obtain the partial coherence coefficients corresponding to each subsystem of the third row of seats.

[0035] A second aspect of the present invention provides a noise source identification device, comprising:

[0036] A signal acquisition unit, used for collecting noise signals of vehicle seats and subsystems corresponding to the seats;

[0037] A calculation unit, used to calculate a partial coherence function by taking a noise signal of a subsystem corresponding to the seat as input and taking the noise signal of the seat as output, so as to obtain a partial coherence coefficient corresponding to the subsystem;

[0038] The determination unit is used to determine the noise source according to the partial coherence coefficient.

[0039] According to a third aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores at least one computer-executable program, and when the at least one program is executed by the computer, the computer executes the steps in the noise source identification method.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] The noise signal calculation in the present invention is based on the symmetry principle of the whole vehicle. The influencing factor on the right side of the driver's seat adopts the noise signal collected by the microphone arranged on the left side of the vehicle body and near the front end. The influencing factor of the second row of seats adopts the noise signal collected by the microphone arranged on the right side of the vehicle body and near the rear end. The influencing factor of the third row of seats adopts the noise signal collected by the microphone arranged on the left side of the vehicle body and near the rear end, so as to reduce redundant analysis, save calculation time and improve the efficiency of noise source identification.

[0042] The present invention adopts the partial coherence method to identify the air noise source. The partial coherence function can analyze the influence of various factors on the noise source under the conditions of multiple non-independent noise sources. It does not need to change the on-site sound environment, and can analyze the noise source characteristics under actual working conditions. It is suitable for the identification of transient noise sources of the whole vehicle and improves the accuracy of noise source identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 is a flow chart of the noise source identification method of the present invention;

[0044] Figure 2 A schematic diagram of the arrangement of loudspeakers on each seat when the vehicle has two rows of seats;

[0045] Figure 3 A schematic diagram of the arrangement of the loudspeakers on each seat when the vehicle has three rows of seats;

[0046] Figure 4 Conditional analysis model for multi-input single-output system;

[0047] Figure 5 This is the result of the driver's seat partial coherence analysis under the condition of 120Km / h constant speed driving;

[0048] Figure 6 The partial coherence analysis results of the second row seats under the condition of 120Km / h constant speed driving;

[0049] Figure 7 Optimize results. DETAILED DESCRIPTION

[0050] The present invention is further described in detail below in conjunction with the accompanying drawings:

[0051] The embodiment of the present invention provides a noise source identification method, such as Figure 1 As shown, the specific steps include:

[0052] Step 1, collecting noise signals of each seat of the vehicle and the subsystem corresponding to each seat;

[0053] Specific operations include:

[0054] Microphones are arranged at each seat of the vehicle and the subsystem corresponding to each seat. The vehicle is placed in a high gear, such as D gear for automatic transmission or the highest gear for manual transmission. Noise signals of each seat and the subsystem corresponding to each seat are collected under stable operating conditions (constant speed or acceleration, etc.). Preferably, the noise signal collection time is at least 10 seconds.

[0055] like Figure 2 As shown, if the vehicle has two rows of seats, a microphone is arranged on the right side of the driver's seat headrest and in the middle of the right side of the second row seat headrest; and a microphone is arranged in each of the subsystems corresponding to the driver's seat and the second row seat, and the distance between the microphone and the subsystem is 10-15cm. Among them, the subsystem corresponding to the driver's seat includes: left front door, left rear side door, left front door glass, left rear side door glass, engine compartment, dashboard, front top cover, front floor, front windshield and left front wheel cover; the subsystem corresponding to the second row seat includes: right front door, right rear side door, right front door glass, right rear side door glass, rear top cover, rear floor, spare wheel well, rear windshield, left / rear wheel cover and right rear side wall.

[0056] like Figure 3 As shown, if the vehicle has three rows of seats, a microphone is arranged on the right side of the driver's seat headrest, in the middle of the right headrest of the second row seat, and in the middle of the third row seat, and a microphone is arranged in each of the subsystems corresponding to the driver's seat, the second row seat, and the third row seat, and the distance between the microphone and the subsystem is 10-15cm. Among them, the subsystem corresponding to the driver's seat includes: left front door, left rear side door, left front door glass, left rear side door glass, engine compartment, instrument panel, front top cover, front floor, front windshield, and left front wheel cover; the subsystem corresponding to the second row seat includes: right front door, right rear side door, right front door glass, right rear side door glass, rear top cover, rear floor, spare wheel well, rear windshield, left / right rear wheel cover, and right rear side wall; the subsystem corresponding to the third row seat includes: left rear side door, left rear side door glass, rear top cover, rear floor, spare wheel well, rear windshield, left / right rear wheel cover, and left rear side wall.

[0057] The noise signal calculation in the present invention is based on the symmetry principle of the whole vehicle. The influencing factors on the right side of the driver's seat adopt the noise signals collected by the microphones arranged on the left side of the vehicle body and near the front end, such as the noise signals of the subsystems of the left front door, the left rear side door, the left front door glass, the left rear side door glass, the engine compartment, the instrument panel, the front top cover, the front floor, the front windshield and the left front wheel cover; the influencing factors of the second row of seats adopt the noise signals collected by the microphones arranged on the right side of the vehicle body and near the rear end, such as the noise signals of the subsystems of the right front door, the right rear side door, the right front door glass, the right rear side door glass, the rear top cover, the rear floor, the spare wheel well, the rear windshield, the left / rear wheel cover and the right rear side surround; the influencing factors of the third row of seats adopt the noise signals collected by the microphones arranged on the left side of the vehicle body and near the rear end, such as the noise signals of the subsystems of the left rear side door, the left rear side door glass, the rear top cover, the rear floor, the spare wheel well, the rear windshield, the left / right rear wheel cover and the left rear side surround, so as to reduce redundant analysis, save calculation time and improve the efficiency of noise source identification.

[0058] Step 2, using the noise signal of the subsystem corresponding to each seat as input and the noise signal of each seat as output, performing partial coherence function calculation to obtain a partial coherence coefficient;

[0059] Specific operations include:

[0060] The noise signals collected by the microphones arranged at the left front door, the left rear side door, the left front door glass, the left rear side door glass, the engine compartment, the instrument panel, the front top cover, the front floor, the front windshield and the left front wheel cover are used as input, and the noise signals collected by the microphone arranged at the right side of the driver's seat headrest are used as output, and the partial coherence function is calculated to obtain the partial coherence coefficients of each subsystem corresponding to the driver's seat;

[0061] The noise signals collected by the microphones arranged at the right front door, the right rear side door, the right front door glass, the right rear side door glass, the rear top cover, the rear floor, the spare wheel well, the rear windshield, the left / rear wheel covers and the right rear side wall are used as input, and the noise signals collected by the microphone arranged in the middle of the headrest of the second row right seat are used as output, and the partial coherence function is calculated to obtain the partial coherence coefficients of each subsystem corresponding to the second row seat;

[0062] The noise signals collected by the microphones arranged at the left rear door, left rear door glass, rear roof, rear floor, spare wheel well, rear windshield, left / right rear wheel cover and left rear side panel are taken as input, and the microphone arranged in the middle position of the third row is taken as output. The partial coherence function is calculated to obtain the partial coherence coefficients of each subsystem corresponding to the third row of seats.

[0063] The present invention adopts the partial coherence method to identify the air noise source. The partial coherence function can analyze the influence of various factors on the noise source under the conditions of multiple non-independent noise sources. It does not need to change the on-site sound environment, and can analyze the noise source characteristics under actual working conditions. It is suitable for the identification of transient noise sources of the whole vehicle and improves the accuracy of noise source identification.

[0064] Partial coherence analysis is developed based on coherence theory. It makes up for the deficiency of coherence analysis theory that it cannot identify non-independent multi-input noise sources. It calculates the correlation between the residual signal and the input and improves the accuracy of noise source identification.

[0065] The partial coherence function removes the coherent part of the signal of each input channel, which can accurately represent the independent influence of different input channels on the output result. Figure 4 The conditional model can derive the relationship between the conditional cross-spectrum and the conditional auto-spectrum, as shown in formulas (1) and (2) respectively:

[0066]

[0067] Iterate formula (1) and (2) to obtain the partial coherence function, see formula (3):

[0068]

[0069] in, is the partial coherence function, G iy·(i-1)！ is the conditional cross-spectral density function after removing the rest of the input coherence effect, G ii·(i-1)！ is the conditional autospectral density function after removing the rest of the input coherence effect. yy·(i-1)！ is to remove x1(t) to x (i-1) (t) Conditional autospectral density function after correlation effect.

[0070] Step 3, determining the noise source according to the partial coherence coefficient;

[0071] Specific operations include:

[0072] The input with a large partial coherence coefficient contributes greatly. The noise source is determined by the size of the partial coherence coefficient. The partial coherence coefficients of the subsystems corresponding to the seat are sorted from large to small or from small to large, and the first two subsystems with larger partial coherence coefficients are found, which are determined to be the noise source.

[0073] Before determining the noise source based on the partial coherence coefficient, it also includes:

[0074] Convert the collected seat noise signal into a spectrum of sound pressure level and frequency; find out the frequency band where the subjective sound is abnormal through audio playback;

[0075] When there is a peak in the spectrum graph and an abnormal sound can be heard during audio playback, when determining the noise source, the partial coherence coefficient corresponding to the peak frequency band is selected, and the first two subsystems with larger partial coherence coefficients are found, which are determined to be the noise source;

[0076] When the peak of the spectrum graph is not obvious, but an abnormal sound can be heard during audio playback, when determining the noise source, the partial coherence coefficient corresponding to the frequency band of the abnormal sound is selected, and the first two subsystems with larger partial coherence coefficients are found, which are determined to be the noise source;

[0077] When there is no peak in the spectrum graph and no abnormal sound is heard during audio playback, when determining the noise source, select the partial coherence coefficient corresponding to the full frequency band, find the first two subsystems with the largest partial coherence coefficients, and determine them as the noise source.

[0078] Microphones are arranged on the right side of the driver's headrest and the corresponding subsystem, in the middle of the second row's right headrest and the corresponding subsystem. Under a constant speed of 120 km / h, the noise signals of each seat and its corresponding subsystem are collected, and partial coherence analysis is performed. Figure 5 As shown in , the noise signal on the right side of the driver's headrest is used as the output, and the partial coherence coefficients in the dashboard and the left front door glass are relatively large, which are the main influencing factors of the noise; Figure 6 As shown, the noise signal in the middle of the right headrest of the second row of seats is taken as the output, and the partial coherence coefficients of the right rear door glass and the right rear side surround are relatively large, which are the main influencing factors of the noise.

[0079] According to the above noise source identification results, the scheme optimization is carried out for the instrument panel, left front door glass, right front door glass, left rear door glass, right rear door glass, left rear side panel and right rear side panel, such as Figure 7 As shown, the uniform speed noise was improved after the implementation of the scheme, and the subjective evaluation was obvious.

[0080] The embodiment of the present invention further provides a noise source identification device, comprising:

[0081] The signal acquisition unit is used to collect noise signals of vehicle seats and subsystems corresponding to the seats; the specific operations include:

[0082] Microphones are arranged on vehicle seats and subsystems corresponding to the seats respectively, and the vehicle is placed in a high gear, such as D gear for automatic transmission or the highest gear for manual transmission, and noise signals of the seats and subsystems corresponding to the seats are collected under stable operating conditions (constant speed or acceleration, etc.). Preferably, the noise signal collection time is at least 10 seconds.

[0083] like Figure 2As shown, if the vehicle has two rows of seats, a microphone is arranged on the right side of the driver's seat headrest and in the middle of the right side of the second row seat headrest; and a microphone is arranged in each of the subsystems corresponding to the driver's seat and the second row seat, and the distance between the microphone and the subsystem is 10-15cm. Among them, the subsystem corresponding to the driver's seat includes: left front door, left rear side door, left front door glass, left rear side door glass, engine compartment, dashboard, front top cover, front floor, front windshield and left front wheel cover; the subsystem corresponding to the second row seat includes: right front door, right rear side door, right front door glass, right rear side door glass, rear top cover, rear floor, spare wheel well, rear windshield, left / rear wheel cover and right rear side wall.

[0084] like Figure 3 As shown, if the vehicle has three rows of seats, a microphone is arranged on the right side of the driver's seat headrest, in the middle of the second row right seat headrest and in the middle of the third row seat, and a microphone is arranged in each of the subsystems corresponding to the driver's seat, the second row seat and the third row seat, and the distance between the microphone and the subsystem is 10-15cm. Among them, the subsystem corresponding to the driver's seat includes: left front door, left rear side door, left front door glass, left rear side door glass, engine compartment, instrument panel, front top cover, front floor, front windshield and left front wheel cover; the subsystem corresponding to the second row seat includes: right front door, right rear side door, right front door glass, right rear side door glass, rear top cover, rear floor, spare wheel well, rear windshield, left / right rear wheel cover and right rear side wall; the subsystem corresponding to the third row seat includes: left rear side door, left rear side door glass, rear top cover, rear floor, spare wheel well, rear windshield, left / right rear wheel cover and left rear side wall.

[0085] The calculation unit is used to calculate the partial coherence function by taking the noise signal of the subsystem corresponding to the seat as input and the noise signal of the seat as output to obtain the partial coherence coefficient. The specific operations include:

[0086] The noise signals collected by the microphones arranged at the left front door, the left rear side door, the left front door glass, the left rear side door glass, the engine compartment, the instrument panel, the front top cover, the front floor, the front windshield and the left front wheel cover are used as input, and the noise signals collected by the microphone arranged at the right side of the driver's seat headrest are used as output, and the partial coherence function is calculated to obtain the partial coherence coefficients of each subsystem corresponding to the driver's seat;

[0087] The noise signals collected by the microphones arranged at the right front door, the right rear side door, the right front door glass, the right rear side door glass, the rear top cover, the rear floor, the spare wheel well, the rear windshield, the left / rear wheel covers and the right rear side wall are used as input, and the noise signals collected by the microphone arranged in the middle of the headrest of the second row right seat are used as output, and the partial coherence function is calculated to obtain the partial coherence coefficients of each subsystem corresponding to the second row seat;

[0088] The noise signals collected by the microphones arranged at the left rear door, left rear door glass, rear roof, rear floor, spare wheel well, rear windshield, left / right rear wheel cover and left rear side panel are taken as input, and the microphone arranged in the middle position of the third row is taken as output. The partial coherence function is calculated to obtain the partial coherence coefficients of each subsystem corresponding to the third row of seats.

[0089] The determination unit is used to determine the noise source according to the partial coherence coefficient. The specific operations include: the input with a large partial coherence coefficient has a large contribution, and the noise source is determined by the size of the partial coherence coefficient. The partial coherence coefficients of the subsystems corresponding to the seat are sorted from large to small or from small to large, and the first two subsystems with larger partial coherence coefficients are found, which are the noise sources.

[0090] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores at least one program executable by a computer, and when the at least one program is executed by the computer, the computer executes the steps in the noise source identification method.

[0091] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0092] The above technical solution is only one implementation mode of the present invention. For those skilled in the art, it is easy to make various types of improvements or modifications based on the principles disclosed in the present invention, and it is not limited to the technical solution described in the above specific embodiments of the present invention. Therefore, the above description is only preferred and does not have a restrictive meaning.

Claims

1. A noise source identification method, characterized in that: include: Collect noise signals of vehicle seats and corresponding subsystems of seats; Taking the noise signal of the subsystem corresponding to the seat as input and the noise signal of the seat as output, the partial coherence function is calculated to obtain the partial coherence coefficient corresponding to the subsystem; The noise source is determined based on the partial coherence coefficient.

2. The noise source identification method according to claim 1, characterized in that: The specific operations of collecting the noise signals of the vehicle seat and the subsystem corresponding to the seat include: Collect the noise signals of the seats and their corresponding subsystems under steady-state operating conditions; If the vehicle has two rows of seats, a microphone is arranged on the right side of the driver's seat headrest and in the middle of the second row seat's right headrest; and a microphone is arranged in each subsystem corresponding to the driver's seat and the rear seat.

3. The noise source identification method according to claim 2, characterized in that: The subsystems corresponding to the driver's seat include: left front door, left rear side door, left front door glass, left rear side door glass, engine compartment, instrument panel, front top cover, front floor, front windshield and left front wheel cover; and / or, The subsystems corresponding to the second row of seats include: right front door, right rear side door, right front door glass, right rear side door glass, rear roof, rear floor, spare wheel well, rear windshield, left / right rear wheel covers and right rear side panel.

4. The noise source identification method according to claim 1, characterized in that: The specific operations of collecting the noise signals of the vehicle seat and the subsystem corresponding to the seat include: Collect the noise signals of the seats and their corresponding subsystems under steady-state operating conditions; If the vehicle has three rows of seats, a microphone is arranged on the right side of the driver's seat headrest, in the middle of the right headrest of the second row of seats, and in the middle of the third row of seats, and a microphone is arranged in each subsystem corresponding to the driver's seat, the second row of seats, and the third row of seats.

5. The noise source identification method according to claim 2, characterized in that: The subsystems corresponding to the driver's seat include: left front door, left rear side door, left front door glass, left rear side door glass, engine compartment, instrument panel, front top cover, front floor, front windshield and left front wheel cover; and / or, The subsystems corresponding to the second row of seats include: right front door, right rear side door, right front door glass, right rear side door glass, rear top cover, rear floor, spare wheel well, rear windshield, left / right rear wheel covers and right rear side panel; and / or; The subsystems corresponding to the third row of seats include: left rear side door, left rear side door glass, rear roof, rear floor, spare wheel well, rear windshield, left / right rear wheel covers and left rear side panel.

6. The noise source identification method according to claim 3 or 5, characterized in that: The noise signal of the subsystem corresponding to the seat is used as input, and the noise signal of the seat is used as output to calculate the partial coherence function and obtain the partial coherence coefficient corresponding to the subsystem. The specific operations include: The noise signals collected by the microphones arranged at the left front door, left rear side door, left front door glass, left rear side door glass, engine compartment, instrument panel, front top cover, front floor, front windshield and left front wheel cover are taken as input, and the noise signal collected by the microphone arranged at the right side of the driver's seat headrest is taken as output. The partial coherence function is calculated to obtain the partial coherence coefficients corresponding to each subsystem of the driver's seat.

7. The noise source identification method according to claim 3 or 5, characterized in that: The noise signal of the subsystem corresponding to the seat is used as input, and the noise signal of the seat is used as output to calculate the partial coherence function and obtain the partial coherence coefficient corresponding to the subsystem. The specific operations also include: The noise signals collected by the microphones arranged at the right front door, right rear side door, right front door glass, right rear side door glass, rear roof, rear floor, spare wheel well, rear windshield, left / rear wheel cover and right rear side panel are taken as input, and the noise signals collected by the microphone arranged in the middle of the headrest of the second row right seat are taken as output. The partial coherence function is calculated to obtain the partial coherence coefficients corresponding to each subsystem of the second row seat.

8. The noise source identification method according to claim 5, characterized in that: The noise signal of the subsystem corresponding to the seat is used as input, and the noise signal of the seat is used as output to calculate the partial coherence function and obtain the partial coherence coefficient corresponding to the subsystem. The specific operations also include: The noise signals collected by the microphones arranged at the left rear door, left rear door glass, rear roof, rear floor, spare wheel well, rear windshield, left / right rear wheel cover and left rear side panel are taken as input, and the microphone arranged in the middle position of the third row is taken as output. The partial coherence function is calculated to obtain the partial coherence coefficients corresponding to each subsystem of the third row of seats.

9. A noise source identification device, characterized in that: include: A signal acquisition unit, used for collecting noise signals of vehicle seats and subsystems corresponding to the seats; A calculation unit, used to calculate a partial coherence function by taking a noise signal of a subsystem corresponding to the seat as input and taking the noise signal of the seat as output, so as to obtain a partial coherence coefficient corresponding to the subsystem; The determination unit is used to determine the noise source according to the partial coherence coefficient.

10. A computer-readable storage medium storing at least one computer-executable program, wherein when the at least one program is executed by the computer, the computer according to any one of claims 1 to 8 executes the steps in the noise source identification method.

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