In-vehicle noise positioning method, system, control device and vehicle

Abstract

The application discloses a kind of in-vehicle noise positioning in-vehicle noise positioning method, system, control device and vehicle, the in-vehicle noise in the cabin is collected, the in-vehicle noise is extracted, the target noise feature corresponding to the in-vehicle noise is determined, the positioning strategy corresponding to the target noise feature is used, the in-vehicle noise is positioned, the noise source position corresponding to the in-vehicle noise is determined, based on different positioning strategies, accurately complete the noise source positioning of in-vehicle noise.In addition, the in-vehicle noise can be collected using the vehicle microphone array assembled in the cabin, and the noise positioning can be completed, without the need for new noise collection means, and without the need for professional maintenance analysis of the vehicle, so that the vehicle itself can complete the noise positioning.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, and in particular to a method, system, control device, and vehicle for locating in-vehicle noise. Background Technology

[0002] As technology advances, cars are becoming more intelligent and increasingly sensitive to external sounds. However, they haven't addressed the sounds generated by the vehicle itself, particularly unusual noises such as various rattles, wind noise, and road noise. When these abnormal noises occur, consumers often lack the ability to identify their source, requiring repair shops. However, some very specific sounds are beyond the capabilities of repair shops, often necessitating the involvement of the OEM (Original Equipment Manufacturer) personnel. This process incurs significant time and financial costs, negatively impacting the car brand.

[0003] Therefore, improving in-vehicle sound recognition to enhance the automatic location of the vehicle's own noise sources has become an urgent problem to be solved. Summary of the Invention

[0004] This invention provides a method, system, control device, and vehicle for locating in-vehicle noise, in order to address the problem of how to improve in-vehicle sound recognition in order to enhance the automated location of the vehicle's own noise sources.

[0005] In a first aspect, the present invention provides a method for locating in-vehicle noise, comprising: Collect in-vehicle noise data from the passenger compartment; Feature extraction is performed on the in-vehicle noise to determine the target noise features corresponding to the in-vehicle noise; The in-vehicle noise is located using the localization strategy corresponding to the target noise features, thereby determining the location of the noise source corresponding to the in-vehicle noise.

[0006] In one embodiment, the step of extracting features from the in-vehicle noise and determining the target noise features corresponding to the in-vehicle noise includes: The in-vehicle noise was subjected to spectral analysis to obtain the order noise characteristics; The step of using a localization strategy corresponding to the target noise features to locate the in-vehicle noise and determine the location of the noise source corresponding to the in-vehicle noise includes: Based on the order noise characteristics and a pre-set order noise mapping table, the component that generates the order noise characteristics is determined as the noise source location corresponding to the in-vehicle noise.

[0007] Among them, the order noise angle is compared for order noise, so as to quickly and accurately determine the corresponding noise component and thus determine the location of the noise source.

[0008] In one embodiment, the step of extracting features from the in-vehicle noise and determining the target noise features corresponding to the in-vehicle noise includes: The resonant noise characteristics were obtained by performing spectral analysis on the in-vehicle noise. The step of using a localization strategy corresponding to the target noise features to locate the in-vehicle noise and determine the location of the noise source corresponding to the in-vehicle noise includes: Based on the resonant noise characteristics and a pre-set resonant noise mapping table, the component that generates the resonant noise characteristics is determined as the noise source location corresponding to the in-vehicle noise.

[0009] Among them, the resonant noise frequency is compared to quickly and accurately identify the corresponding noise component, thereby determining the location of the noise source.

[0010] In one embodiment, the in-vehicle noise includes a first raw noise collected by at least three microphones; The step of extracting features from the in-vehicle noise and determining the target noise features corresponding to the in-vehicle noise includes: Perform time-domain analysis on each first original noise to obtain the noise peak characteristics of the corresponding first original noise, and determine the first data position where the noise peak characteristics appear in each first original noise; The step of using a localization strategy corresponding to the target noise features to locate the in-vehicle noise and determine the location of the noise source corresponding to the in-vehicle noise includes: Based on the first data location where the noise peak characteristics appear in each first original noise, and the installation location of each microphone in the passenger compartment, the noise source location corresponding to the in-vehicle noise is determined.

[0011] Specifically, the vehicle-mounted microphone array must include at least three microphones, meaning microphones must be installed in at least three locations. This ensures that there are at least three locations where, based on the location of noise data throughout the vehicle, time difference and beamforming calculations can be performed to accurately determine the noise source location.

[0012] In one embodiment, performing time-domain analysis on each first original noise to obtain the noise peak characteristics corresponding to the first original noise, and determining the first data position where the noise peak characteristics appear in each first original noise, includes: For any given first original noise, perform time-domain data analysis on the first original noise to obtain the time-sound pressure level relationship curve; The time-sound pressure relationship curve is compared with a preset relationship curve without noise to obtain the peak value as the noise peak characteristic corresponding to the first original noise, and the position of the peak value is determined as the first data position in the first original noise.

[0013] The method employs a time-sound pressure level relationship curve analysis, which is then compared with a preset curve without noise. This allows for the determination of the peak location, i.e., finding the noise data and its position within the in-vehicle noise range. This enables rapid and accurate identification of noise data and determination of its location.

[0014] In one embodiment, the in-vehicle noise includes a second raw noise collected by at least three microphones; The step of extracting features from the in-vehicle noise and determining the target noise features corresponding to the in-vehicle noise includes: For each second original noise, the voiceprint is extracted to obtain the friction noise voiceprint features corresponding to the second original noise; The step of using a localization strategy corresponding to the target noise features to locate the in-vehicle noise and determine the location of the noise source corresponding to the in-vehicle noise includes: For any second original noise, the friction noise voiceprint features of the second original noise are compared with the voiceprints in the preset noise database to obtain the comparison results. Based on the comparison results, the second data location in which the friction noise acoustic signature appears in the second original noise is determined; Based on the second data location where the friction noise acoustic signature appears in each second original noise, and the installation location of each microphone in the passenger compartment, the noise source location corresponding to the in-vehicle noise is determined.

[0015] Among them, the noise inside the vehicle is compared with the soundprints in the preset noise database to analyze the noise generated by friction, such as the sound of metal friction, rubber friction, etc. By combining the principles of time difference and beamforming, the noise source location is located, improving the applicability of noise analysis.

[0016] In one embodiment, the step of extracting features from the in-vehicle noise and determining the target noise features corresponding to the in-vehicle noise includes: Based on the in-vehicle noise, a noise spectrum diagram is generated; The noise spectrum is subjected to graphic recognition to obtain the target noise characteristics.

[0017] This involves constructing a spectrum diagram of in-vehicle noise, performing image analysis on the spectrum diagram to determine order noise and / or resonance noise, determining the angle of order noise and the frequency of resonance noise, so that a lookup table can be performed with the subsequent mapping table to accurately identify the component that generates the noise.

[0018] In one embodiment, before collecting in-vehicle noise within the passenger compartment, the method further includes: Turn off the amplifier for the car's speakers.

[0019] By controlling the amplifier of the in-vehicle speakers, the accuracy of the collected in-vehicle noise can be improved, and the influence of other abnormal noises can be avoided.

[0020] In a second aspect, the present invention provides an in-vehicle noise localization system, comprising: The noise acquisition module is used to collect in-vehicle noise within the passenger compartment. The noise recognition module is used to extract features from the in-vehicle noise and determine the target noise features corresponding to the in-vehicle noise. The noise localization module is used to locate the in-vehicle noise using a localization strategy corresponding to the target noise characteristics, and to determine the location of the noise source corresponding to the in-vehicle noise.

[0021] Thirdly, this application provides a control device, including a processor and a memory, wherein the memory is used to store computer programs; A processor is configured to execute a program stored in the memory to implement the in-vehicle noise localization method as described in the first aspect.

[0022] Fourthly, this application provides a vehicle including the control device as described in the third aspect above.

[0023] The technical advantages of this invention compared to existing technologies are as follows: This invention collects in-vehicle noise from the passenger compartment, extracts features from the noise, determines the target noise features corresponding to the noise, and uses a localization strategy corresponding to the target noise features to locate the noise source. Based on different localization strategies, it accurately locates the noise source within the vehicle. Furthermore, the noise localization can be achieved using the existing in-vehicle microphone array installed in the passenger compartment, eliminating the need for designing new noise collection methods or professional vehicle maintenance and analysis; the vehicle itself can then perform the noise localization. Attached Figure Description

[0024] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a flowchart illustrating a method for locating in-vehicle noise according to Embodiment 1 of the present invention. Figure 2 This is a spectrum diagram of order noise provided in Embodiment 1 of the present invention; Figure 3 This is a schematic diagram of the spectrum of resonant noise provided in Embodiment 1 of the present invention; Figure 4 This is a flowchart illustrating a method for locating in-vehicle noise according to Embodiment 2 of the present invention; Figure 5 This is a schematic diagram of time-domain data of in-vehicle noise provided in Embodiment 2 of the present invention; Figure 6 This is a flowchart illustrating a method for locating in-vehicle noise according to Embodiment 3 of the present invention; Figure 7 This is a schematic diagram of the structure of an in-vehicle noise localization system provided in Embodiment 4 of the present invention; Figure 8 This is a schematic diagram of the structure of a control device provided by the present invention. Detailed Implementation

[0026] To make the technical problems solved, the technical solutions, and the beneficial effects of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0027] The microphones inside the vehicle are designed for human voice recognition and localization, specifically the voice localization of people inside the vehicle. The frequency range of voice signals is mainly concentrated between 300Hz and 3400Hz, while the noise inside a car covers a range of 20Hz-20kHz. Therefore, there is currently no function to use the microphones inside the vehicle to identify and locate noise generated during vehicle operation in real time.

[0028] like Figure 1The diagram shown illustrates a flowchart of an in-vehicle noise localization method according to Embodiment 1 of the present invention. This method is applied to a vehicle equipped with an in-vehicle microphone array. In some embodiments, this array may include one or two microphones, while in others, three or more microphones are required. The in-vehicle microphones are used to collect in-vehicle audio data, such as user interaction voice, thereby enabling voice control of the vehicle. Using these in-vehicle microphones avoids the need to install new microphones and eliminates the need to place the vehicle in special detection equipment for noise localization and identification, allowing the vehicle to have its own noise detection function, thus improving vehicle efficiency and user experience. Noise localization can be achieved simply by using the in-vehicle microphone array already installed in the passenger compartment to collect in-vehicle noise, without the need to design new noise collection methods or perform professional vehicle maintenance and analysis; the vehicle itself can then perform noise localization.

[0029] Of course, using a non-vehicle-mounted microphone can achieve the collection of in-vehicle noise, while using in-vehicle or external control devices to execute the method steps of the present invention to locate the noise source.

[0030] like Figure 1 As shown, the in-vehicle noise localization method may include the following steps: Step S101: Collect in-vehicle noise data from the passenger compartment.

[0031] The device for collecting in-vehicle noise can be an in-vehicle microphone array, which is a microphone array already installed and configured in the passenger compartment of the vehicle, including at least one microphone. In Embodiments 2 and 3 described below, at least three microphones are required. Of course, the device for collecting in-vehicle noise can be a non-in-vehicle device.

[0032] By controlling the operation of the vehicle-mounted microphone array, sound data inside the cockpit can be collected. This sound data will be processed as in-vehicle noise.

[0033] In one embodiment, before collecting in-vehicle noise within the passenger compartment, the method further includes: Turn off the amplifier for the car's speakers.

[0034] Since vehicles contain speakers and other devices that play sound, any sound emitted by these devices will be captured by the speakers and included in the vehicle's noise levels, potentially negatively impacting subsequent noise identification. Controlling the amplifiers of the vehicle's speakers can improve the accuracy of the noise levels collected within the passenger compartment and prevent the influence of other abnormal noises. Of course, in actual use, the driver and passengers should remain quiet inside the vehicle to avoid noise affecting noise localization.

[0035] The aforementioned in-vehicle microphone array, installed inside the vehicle, can still collect and analyze sound while the vehicle is in motion, eliminating the need to place the vehicle in special testing equipment, thereby further improving the authenticity and accuracy of the detection.

[0036] Step S102: Extract features from the in-vehicle noise to determine the target noise features corresponding to the in-vehicle noise.

[0037] Different identification methods can be used to identify in-vehicle noise, such as frequency domain analysis, time domain analysis, spectrogram analysis, peak analysis, and acoustic signature analysis. This allows for the identification of at least one noise data point and the noise category of each noise data point within the in-vehicle noise.

[0038] Noise categories are used to characterize noise caused by different reasons. For example, order noise and modal resonance noise can be generated by the movement of engines, electric drives and drive shafts, as well as by pipeline vibration; impact noise is the noise generated by stress deformation of parts; and continuous friction noise is the friction between metals, between metals and rubber, between rubbers, etc.

[0039] Step S103: Using the positioning strategy corresponding to the target noise features, the in-vehicle noise is located to determine the location of the noise source corresponding to the in-vehicle noise.

[0040] Among them, the localization strategy corresponds to the target noise characteristics. Different target noise characteristics can be matched with different localization strategies. For example, for order noise or modal resonance noise, the localization strategy can analyze the order characteristics of the order noise or the vibration frequency of the resonance noise. Since the characteristics of the noise generated by the corresponding component are fixed, the component that generates the noise can be determined by comparing the values, and the component can be used as the location of the noise source. For another example, for friction noise, the localization strategy can analyze the acoustic characteristics and locate the noise source by using the principle of sound propagation.

[0041] The principle of sound propagation can be derived by collecting the time difference of noise using multiple microphones and analyzing the microphone positions to determine the location of the noise source.

[0042] In one embodiment, the step of extracting features from the in-vehicle noise and determining the target noise features corresponding to the in-vehicle noise includes: The in-vehicle noise was subjected to spectral analysis to obtain the order noise characteristics; The step of using a localization strategy corresponding to the target noise features to locate the in-vehicle noise and determine the location of the noise source corresponding to the in-vehicle noise includes: Based on the order noise characteristics and a pre-set order noise mapping table, the component that generates the order noise characteristics is determined as the noise source location corresponding to the in-vehicle noise.

[0043] Among them, the order noise angle is compared for order noise, so as to quickly and accurately determine the corresponding noise component and thus determine the location of the noise source.

[0044] like Figure 2 The diagram shows the spectrum of order noise. In order noise, the angle or slope can characterize different orders of noise, and different orders of noise correspond to different noise sources. The preset mapping relationship between angle and noise source is shown in Table 1 below: Table 1 By comparing the angles in Table 1 above, the noise source can be determined.

[0045] In one embodiment, the step of extracting features from the in-vehicle noise and determining the target noise features corresponding to the in-vehicle noise includes: The resonant noise characteristics were obtained by performing spectral analysis on the in-vehicle noise. The step of using a localization strategy corresponding to the target noise features to locate the in-vehicle noise and determine the location of the noise source corresponding to the in-vehicle noise includes: Based on the resonant noise characteristics and a pre-set resonant noise mapping table, the component that generates the resonant noise characteristics is determined as the noise source location corresponding to the in-vehicle noise.

[0046] Among them, the resonant noise frequency is compared to quickly and accurately identify the corresponding noise component, thereby determining the location of the noise source.

[0047] Among them, the resonant noise frequency is compared to quickly and accurately identify the corresponding noise component, thereby determining the location of the noise source.

[0048] like Figure 3 The diagram shows the spectrum of resonant noise. In resonant noise, the frequency represents different frequencies, and different frequencies correspond to different noise sources. The preset mapping relationship between angles and noise sources is shown in Table 2 below. Table 2 By comparing the frequencies in Table 2 above, the noise source can be identified.

[0049] In one embodiment, the step of extracting features from the in-vehicle noise and determining the target noise features corresponding to the in-vehicle noise includes: Based on the in-vehicle noise, a noise spectrum diagram is generated; The noise spectrum is subjected to graphic recognition to obtain the target noise characteristics.

[0050] This process involves constructing a spectrum diagram of in-vehicle noise, performing image analysis on the spectrum diagram to determine order noise and / or resonant noise, identifying the angle of the order noise and the frequency of the resonant noise, and then using a lookup table to accurately identify the component generating the noise. For example... Figure 2 and Figure 3 As shown, by performing graphic recognition of the noise spectrum, we can determine whether it is a diagonal line or a straight line. The angle of the diagonal line and the frequency corresponding to the straight line can respectively characterize the corresponding order noise and resonant noise.

[0051] This invention collects in-vehicle noise from the passenger compartment, extracts features from the noise, identifies target noise features corresponding to the noise, and uses a localization strategy corresponding to the target noise features to locate the noise source. Based on different localization strategies, the noise source location is accurately achieved. Alternatively, the noise can be located using an existing in-vehicle microphone array installed in the passenger compartment, eliminating the need for new noise collection methods or professional vehicle maintenance and analysis; the vehicle itself can then locate the noise.

[0052] like Figure 4 The diagram shown is a flowchart illustrating a method for locating in-vehicle noise according to Embodiment 2 of the present invention. In this method, the in-vehicle microphone array must include at least three microphones, and the installation location of each microphone within the vehicle is known. The feature extraction of the in-vehicle noise in step S102 above, determining the target noise features corresponding to the in-vehicle noise, may include the following steps: Step S401: Perform time-domain analysis on each first original noise to obtain the noise peak characteristics of the corresponding first original noise, and determine the first data position where the noise peak characteristics appear in each first original noise.

[0053] If there is no order noise or resonance noise, it is necessary to analyze whether there is noise generated by instantaneous excitation such as impact in the vehicle interior. Of course, if order noise and resonance noise are not determined, the noise generated by instantaneous excitation can also be analyzed.

[0054] By performing time-domain data analysis on the in-vehicle noise and identifying abnormal peaks in the analysis results, it can be determined that the noise is of the impact type. The data position of the peak in each original noise is the first data position in the corresponding original noise.

[0055] In one embodiment, performing time-domain analysis on each first original noise to obtain the noise peak characteristics corresponding to the first original noise, and determining the first data position where the noise peak characteristics appear in each first original noise, includes: For any given first original noise, perform time-domain data analysis on the first original noise to obtain the time-sound pressure level relationship curve; The time-sound pressure relationship curve is compared with a preset relationship curve without noise to obtain the peak value as the noise peak characteristic corresponding to the first original noise, and the position of the peak value is determined as the first data position in the first original noise.

[0056] The method employs a time-sound pressure level relationship curve analysis, which is then compared with a preset curve without noise. This allows for the determination of the peak location, i.e., finding the noise data and its position within the in-vehicle noise range. This enables rapid and accurate identification of noise data and determination of its location.

[0057] like Figure 5 As shown, this invention provides a time-domain data analysis curve of in-vehicle noise to obtain the time sound pressure level relationship curve. By comparing the signal data without this noise, the system automatically marks the peak values ​​of the noise signal, namely signal 1 and signal 2, with signal 2 being closer to the noise source.

[0058] The step S103 above, which uses a localization strategy corresponding to the target noise features to locate the in-vehicle noise and determine the noise source location corresponding to the in-vehicle noise, may include the following steps: Step S402: Based on the first data location where the noise peak characteristics appear in each first original noise and the installation location of each microphone in the passenger compartment, determine the noise source location corresponding to the in-vehicle noise.

[0059] The installation location of the microphones in the vehicle's passenger compartment is known. The aforementioned in-vehicle noise is the sound information collected by each microphone. Therefore, for each microphone, the first data location represents the time when the noise data was received. When there is an array containing three or more microphones, the accurate location of the noise can be determined by using a time difference-based method.

[0060] The embodiments of the present invention require that the in-vehicle microphone array include at least three microphones, that is, microphones installed in at least three locations, so that there are at least three locations. Based on the data location of noise data throughout the vehicle, time difference and beamforming calculations can be performed to accurately obtain the noise source location of the noise data.

[0061] like Figure 6The diagram shown is a flowchart of a method for locating in-vehicle noise according to Embodiment 3 of the present invention. In step S102 above, feature extraction of the in-vehicle noise to determine the target noise features corresponding to the in-vehicle noise may further include the following steps: Step S601: Extract the voiceprint for each second original noise to obtain the friction noise voiceprint features of the corresponding second original noise.

[0062] For continuous noise signals, including but not limited to friction noise such as metal friction and rubber friction, it is necessary to extract the voiceprint. Then, the voiceprints of the corresponding noise signals are stored in the noise database in advance to compare the voiceprints of the in-vehicle noise, thereby determining the specific friction type and realizing the analysis of in-vehicle noise.

[0063] The step S103 above, which uses a localization strategy corresponding to the target noise features to locate the in-vehicle noise and determine the noise source location corresponding to the in-vehicle noise, may include the following steps: Step S602: For any second original noise, compare the friction noise voiceprint features of the second original noise with the voiceprints in the preset noise database to obtain the comparison result. Based on the comparison result, determine the second data position where the friction noise voiceprint features appear in the second original noise.

[0064] The comparison results characterize the voiceprint type corresponding to the friction noise voiceprint features, thereby enabling the determination of the second data position where the corresponding friction noise voiceprint features appear in the second original noise based on the comparison results.

[0065] Based on the comparison results, noise filtering is performed on the in-vehicle noise (i.e., the corresponding original noise). Different filtering methods are used for different specific friction categories to obtain accurate noise data, which in turn allows for the accurate determination of the data location.

[0066] Similar to the content in Embodiment 2 above, each microphone is analyzed independently during the analysis to determine the second data position corresponding to the noise data in each microphone, so that the noise source position can be calculated using the time difference.

[0067] Step S603: Based on the second data location where the friction noise acoustic signature appears in each second original noise and the installation location of each microphone in the passenger compartment, determine the noise source location corresponding to the in-vehicle noise.

[0068] The calculation method is the same as that in step S402 above, except for the difference in data location, which will not be repeated here.

[0069] In the absence of order noise, resonance noise, and impact noise, this invention compares in-vehicle noise with sound patterns in a preset noise database to analyze noise generated by friction, such as the sound of metal friction or rubber friction. By combining the principles of time difference and beamforming, the noise source location is located, thus improving the applicability of noise analysis.

[0070] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0071] In one embodiment, an in-vehicle noise localization system is provided, which corresponds one-to-one with the in-vehicle noise localization method described in the above embodiments. For example... Figure 7 As shown, the in-vehicle noise localization system 70 includes a noise acquisition module 710, a noise recognition module 720, and a noise localization module 730. Detailed descriptions of each functional module are as follows: The noise acquisition module 710 is used to collect in-vehicle noise in the passenger compartment. The noise recognition module 720 is used to extract features from the in-vehicle noise and determine the target noise features corresponding to the in-vehicle noise. The noise localization module 730 is used to locate the in-vehicle noise by employing a localization strategy corresponding to the target noise characteristics, and to determine the location of the noise source corresponding to the in-vehicle noise.

[0072] Optionally, the noise recognition module 720 includes: The order noise analysis unit is used to perform spectral analysis on the in-vehicle noise to obtain order noise characteristics; The noise localization module 730 includes: The first positioning unit is used to determine the location of the component that generates the order noise feature as the noise source corresponding to the in-vehicle noise, based on the order noise feature and a pre-set order noise mapping table.

[0073] Optionally, the noise recognition module 720 includes: The resonance noise analysis unit is used to perform spectral analysis on the in-vehicle noise to obtain resonance noise characteristics; The noise localization module 730 includes: The second positioning unit is used to determine the location of the component that generates the resonance noise feature as the noise source corresponding to the in-vehicle noise, based on the resonance noise feature and a pre-set resonance noise mapping table.

[0074] Optionally, the in-vehicle noise includes a first raw noise collected by at least three microphones; The noise recognition module 720 further includes: The impulse noise analysis unit is used to perform time-domain analysis on each first original noise, obtain the noise peak characteristics of the corresponding first original noise, and determine the first data position where the noise peak characteristics appear in each first original noise. The noise localization module 730 includes: The third positioning unit is used to determine the noise source location corresponding to the in-vehicle noise based on the first data location where the noise peak characteristics appear in each first original noise and the installation location of each microphone in the passenger compartment.

[0075] Optionally, the impact noise analysis unit includes: The sound pressure level relationship curve subunit is used to perform time-domain data analysis on any first original noise to obtain a time sound pressure level relationship curve. The first data position determination subunit is used to compare the time sound pressure relationship curve with a preset relationship curve without noise, obtain the peak value as the noise peak feature corresponding to the first original noise, and determine the position of the peak value as the first data position in the first original noise.

[0076] Optionally, the in-vehicle noise includes a second raw noise collected by at least three microphones; The noise recognition module 720 further includes: The voiceprint noise analysis unit is used to extract the voiceprint of each second original noise and obtain the friction noise voiceprint features of the corresponding second original noise. The noise localization module 730 includes: The voiceprint comparison unit is used to compare the friction noise voiceprint features of any second original noise with the voiceprints in a preset noise database to obtain the comparison result. The second data location determination unit is used to determine the second data location in which the friction noise acoustic feature appears in the second original noise based on the comparison result. The fourth positioning unit is used to determine the noise source location corresponding to the in-vehicle noise based on the second data location where the friction noise acoustic signature appears in each second original noise and the installation location of each microphone in the passenger compartment.

[0077] Optionally, the noise recognition module 720 includes: A spectrum generation unit is used to generate a noise spectrum based on the in-vehicle noise. The noise identification unit is used to perform graphic recognition on the noise spectrum to obtain the target noise characteristics.

[0078] Optionally, the in-vehicle noise localization system further includes: The power amplifier control module is used to control the in-vehicle speakers to stop amplifying before the in-vehicle noise in the passenger compartment is collected.

[0079] Specific limitations regarding the in-vehicle noise localization system can be found in the limitations of the in-vehicle noise localization method described above, and will not be repeated here. Each module in the aforementioned in-vehicle noise localization system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0080] In one embodiment, a control device is provided, please refer to Figure 8 It includes a memory 810 and a processor 820, wherein the memory 810 is used to store computer programs; the processor 820 is used to execute the programs stored in the memory 810 to implement the in-vehicle noise localization method described in any embodiment of this application, for example... Figure 1 Steps S101-S103 shown are omitted here to avoid repetition. Alternatively, the processor executes the computer program to implement the functions of each module / unit in this embodiment of the in-vehicle noise localization device, for example... Figure 7 The function of the in-vehicle noise location device shown is not described again here to avoid repetition.

[0081] In one embodiment, a vehicle is provided, the vehicle including the control device described above.

[0082] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When executed by a processor, the computer program implements the in-vehicle noise localization method described in the above embodiment, for example... Figure 1 Steps S101-S103 shown, or Figures 2 to 6 As shown, to avoid repetition, it will not be described again here. Alternatively, when the computer program is executed by the processor, it implements the functions of each module / unit in this embodiment of the in-vehicle noise localization system, for example... Figure 7 The functions of the in-vehicle noise localization system shown are not described again here to avoid repetition.

[0083] In this application, "multiple" refers to two or more.

[0084] The terms “first,” “second,” “third,” “fourth,” etc., in this application (if present) are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0085] In this application, the term "and / or" 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, or B existing alone. Additionally, in this application, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0086] Unless otherwise specified, all steps in this application may be performed sequentially or randomly. For example, if the method includes steps A and B, it means that the method may include steps A and B performed sequentially, or it may include steps B and A performed sequentially. For example, if the method may also include step C, it means that step C may be added to the method in any order. For example, the method may include steps A, B, and C, or it may include steps A, C, and B, or it may include steps C, A, and B, etc.

[0087] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method of locating in-vehicle noise, characterized by, include: Collect in-vehicle noise data from the passenger compartment; Feature extraction is performed on the in-vehicle noise to determine the target noise features corresponding to the in-vehicle noise; Using the localization strategy corresponding to the target noise features, the in-vehicle noise is located, and the location of the noise source corresponding to the in-vehicle noise is determined; When the target noise feature is an order noise feature, the step of extracting features from the in-vehicle noise and determining the target noise feature corresponding to the in-vehicle noise includes: The in-vehicle noise was subjected to spectral analysis to obtain the order noise characteristics; The step of using a localization strategy corresponding to the target noise features to locate the in-vehicle noise and determine the location of the noise source corresponding to the in-vehicle noise includes: Based on the order noise characteristics and a pre-set order noise mapping table, the component that generates the order noise characteristics is determined as the noise source location corresponding to the in-vehicle noise. When the target noise feature is impact noise, the in-vehicle noise includes first raw noise collected by at least three microphones. The step of feature extraction of the in-vehicle noise to determine the target noise feature corresponding to the in-vehicle noise includes: Perform time-domain analysis on each first original noise to obtain the noise peak characteristics of the corresponding first original noise, and determine the first data position where the noise peak characteristics appear in each first original noise; The step of using a localization strategy corresponding to the target noise features to locate the in-vehicle noise and determine the location of the noise source corresponding to the in-vehicle noise includes: Based on the first data location where the noise peak characteristics appear in each first original noise, and the installation location of each microphone in the passenger compartment, the noise source location corresponding to the in-vehicle noise is determined; The step of performing time-domain analysis on each first original noise to obtain the noise peak characteristics of the corresponding first original noise, and determining the first data position where the noise peak characteristics appear in each first original noise, includes: For any given first original noise, perform time-domain data analysis on the first original noise to obtain the time-sound pressure level relationship curve; The time-sound pressure level relationship curve is compared with a preset relationship curve without noise to obtain the peak value as the noise peak characteristic corresponding to the first original noise, and the position of the peak value is determined as the first data position in the first original noise.

2. The in-vehicle noise positioning method according to claim 1, characterized by, When the target noise feature is a resonant noise feature, the step of extracting features from the in-vehicle noise and determining the target noise feature corresponding to the in-vehicle noise includes: The resonant noise characteristics were obtained by performing spectral analysis on the in-vehicle noise. The step of using a localization strategy corresponding to the target noise features to locate the in-vehicle noise and determine the location of the noise source corresponding to the in-vehicle noise includes: Based on the resonant noise characteristics and a pre-set resonant noise mapping table, the component that generates the resonant noise characteristics is determined as the noise source location corresponding to the in-vehicle noise.

3. The in-vehicle noise localization method according to claim 1, characterized in that, When the target noise characteristic is frictional noise, the in-vehicle noise includes a second raw noise collected by at least three microphones; The step of extracting features from the in-vehicle noise and determining the target noise features corresponding to the in-vehicle noise includes: For each second original noise, the voiceprint is extracted to obtain the friction noise voiceprint features corresponding to the second original noise; The step of using a localization strategy corresponding to the target noise features to locate the in-vehicle noise and determine the location of the noise source corresponding to the in-vehicle noise includes: For any second original noise, the friction noise voiceprint features of the second original noise are compared with the voiceprints in the preset noise database to obtain the comparison results. Based on the comparison results, the second data location in which the friction noise acoustic signature appears in the second original noise is determined; Based on the second data location where the friction noise acoustic signature appears in each second original noise, and the installation location of each microphone in the passenger compartment, the noise source location corresponding to the in-vehicle noise is determined.

4. A vehicle interior noise localization system, characterized in that, include: The noise acquisition module is used to collect in-vehicle noise within the passenger compartment. The noise recognition module is used to extract features from the in-vehicle noise and determine the target noise features corresponding to the in-vehicle noise. The noise localization module is used to locate the in-vehicle noise using a localization strategy corresponding to the target noise characteristics, and to determine the location of the noise source corresponding to the in-vehicle noise. When the target noise feature is an order noise feature, the noise identification module includes: The order noise analysis unit is used to perform spectral analysis on the in-vehicle noise to obtain order noise characteristics; The noise localization module includes: The first positioning unit is used to determine the location of the component that generates the order noise feature as the noise source corresponding to the in-vehicle noise based on the order noise feature and a pre-set order noise mapping table. When the target noise characteristic is impact noise, the in-vehicle noise includes first raw noise collected by at least three microphones, and the noise recognition module includes: The impulse noise analysis unit is used to perform time-domain analysis on each first original noise, obtain the noise peak characteristics of the corresponding first original noise, and determine the first data position where the noise peak characteristics appear in each first original noise. The noise localization module includes: The third positioning unit is used to determine the noise source location corresponding to the in-vehicle noise based on the first data location where the noise peak characteristics appear in each first original noise and the installation location of each microphone in the passenger compartment. The impact noise analysis unit includes: The sound pressure level relationship curve subunit is used to perform time-domain data analysis on any first original noise to obtain a time sound pressure level relationship curve. The first data position determination subunit is used to compare the time sound pressure level relationship curve with a preset relationship curve without noise, obtain the peak value as the noise peak feature corresponding to the first original noise, and determine the position of the peak value as the first data position in the first original noise.

5. A control device, characterized in that, It includes a processor and memory, where the memory is used to store computer programs; A processor is configured to execute a program stored in the memory to implement the in-vehicle noise localization method as described in any one of claims 1 to 3.

6. A vehicle, characterized in that, Includes the control device as described in claim 5.

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