CN118335050A

CN118335050A - Method and system for quick offline modeling by using sound recording file and active noise reduction method

Info

Publication number: CN118335050A
Application number: CN202410437518.5A
Authority: CN
Inventors: 宁远贵; 刘亚敏
Original assignee: Shenzhen Bailing Acoustics Co ltd
Current assignee: Shenzhen Bailing Acoustics Co ltd
Priority date: 2024-04-11
Filing date: 2024-04-11
Publication date: 2024-07-12

Abstract

The application is suitable for the technical field of active noise reduction of automobiles, and provides a method and a system for rapid offline modeling by using a recording file and an active noise reduction method, wherein the method comprises the following steps: determining a reference vehicle according to the target new vehicle; determining an acoustic path within the reference vehicle; the acoustic path includes a primary path and a secondary path; recording files on the main path and the secondary path of the engine of the reference vehicle under different working states are respectively acquired, and noise data of the engine are acquired; training a preset noise reduction model according to the sound record file on the main path, the sound record file on the secondary path and the noise data of the engine to obtain a trained preset noise reduction model; the application is beneficial to improving the development efficiency of the active noise reduction system in the target new vehicle.

Description

Method and system for quick offline modeling by using sound recording file and active noise reduction method

Technical Field

The application belongs to the technical field of active noise reduction of automobiles, and particularly relates to a method and a system for rapid offline modeling by using a recording file and an active noise reduction method.

Background

Active noise reduction (Active Noise Control, ANC) of automobiles is a technique that reduces or eliminates noise by generating sound waves opposite to the noise. In the field of automobiles, the technology mainly controls and generates sound waves opposite to noise through a noise reduction algorithm model so as to reduce the noise level in the automobile and improve the comfort of passengers.

In the development process of a new vehicle, a noise reduction algorithm model in a noise reduction product carried by the vehicle can be obtained after pre-training and verification. After a new car is acquired, an acoustic path is determined for the new car, and then a sound recording file of the new car is acquired according to the acoustic path, so that a noise reduction algorithm model is trained and verified. However, the method can train the model only after the actual vehicle is produced, thereby being unfavorable for the development efficiency of the active noise reduction system of the new vehicle.

Disclosure of Invention

The embodiment of the application provides a method and a system for quick offline modeling by using a sound recording file and an active noise reduction method, which are beneficial to improving the development efficiency of an active noise reduction system of a new vehicle.

In a first aspect, an embodiment of the present application provides a method for fast offline modeling using a sound recording file, including:

Determining a reference vehicle according to the target new vehicle;

Determining an acoustic path within the reference vehicle; the acoustic path includes a primary path and a secondary path;

recording files on the main path and the secondary path of the engine of the reference vehicle under different working states are respectively acquired, and noise data of the engine are acquired;

And training a preset noise reduction model according to the sound record file on the main path, the sound record file on the secondary path and the noise data of the engine to obtain the trained preset noise reduction model.

In a possible implementation manner of the first aspect, the determining a reference vehicle according to the target new vehicle includes:

at least one vehicle is randomly selected as a reference vehicle from vehicles which are developed based on the same platform and have the same noise reduction system as the target new vehicle.

In a possible implementation manner of the first aspect, the acquiring audio records on the primary path and the secondary path of the engine of the reference vehicle under different working states respectively includes:

Collecting recording files of the engine of the reference vehicle on the main path under idle working conditions and different running states; the running states include constant speed running, acceleration running, and deceleration running.

and collecting sound records of the engine of the reference vehicle on the main path under different speeds and different engine speeds.

and collecting sound records on the secondary path when the engine of the reference vehicle is not started.

In a possible implementation manner of the first aspect, the collecting a sound file on the secondary path when the engine of the reference vehicle is in an inactive state includes:

and controlling a loudspeaker in the reference vehicle to emit white noise signals, and collecting acoustic data received by a microphone.

In a possible implementation manner of the first aspect, the speaker is provided at a bottom of each door of the reference vehicle, and the microphone is provided at an in-vehicle top of the reference vehicle.

In a possible implementation manner of the first aspect, before the determining the acoustic path in the reference vehicle, the method includes:

Determining an acoustic resonance region of the reference vehicle interior;

determining a mounting position of the loudspeaker according to the acoustic resonance region, and mounting the loudspeaker based on the mounting position; wherein the mounting location avoids the acoustic resonance region.

In a second aspect, an embodiment of the present application provides a system for rapid offline modeling using sound recordings, including:

The reference vehicle determining module is used for determining a reference vehicle according to the target new vehicle;

a reference vehicle acoustic path determination module that determines an acoustic path within the reference vehicle; the acoustic path includes a primary path and a secondary path;

The reference vehicle recording file acquisition module is used for respectively acquiring recording files on the main path and the secondary path of the engine of the reference vehicle in different working states and acquiring noise data of the engine;

The preset noise reduction model generation module trains the preset noise reduction model according to the sound record file on the main path, the sound record file on the secondary path and the noise data of the engine to obtain the trained preset noise reduction model.

In a third aspect, an embodiment of the present application provides an active noise reduction method for an automobile, including:

Acquiring acoustic data in a new target vehicle;

Verifying the trained preset noise reduction model based on the acoustic data of the target new vehicle, and determining model parameters; the trained preset noise reduction model is generated based on the method using the audio file for rapid offline modeling according to any one of claims 1-8;

Determining a target noise reduction model according to the model parameters and the preset noise reduction model;

And generating sound waves with opposite phases to noise according to the target noise reduction model and the loudspeaker in the target new vehicle so as to realize active noise reduction.

In a fourth aspect, an embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the method for fast offline modeling using sound files according to any one of the first aspects above when executing the computer program.

In a fifth aspect, embodiments of the present application provide a computer readable storage medium storing a computer program which, when executed by a processor, implements a method of using a sound recording file for fast offline modeling according to any one of the first aspects above.

Compared with the prior art, the embodiment of the application has the beneficial effects that:

According to the embodiment of the application, the reference vehicle is determined according to the target new vehicle, then the recording file on the acoustic path of the reference vehicle is acquired, and the pre-set noise reduction model is pre-trained according to the recording file of the reference vehicle, so that training and verification of the pre-set noise reduction model can be performed without waiting for the production of the target new vehicle, verification is performed on the target new vehicle based on the trained model on other vehicles, namely, the model is finely adjusted based on the acoustic data of the target new vehicle, and a final noise reduction system can be obtained, thereby improving the development efficiency of the active noise reduction system of the new vehicle and having lower cost.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a method for rapid offline modeling using sound recordings provided by an embodiment of the present application;

FIG. 2 is a flow chart of a method for rapid offline modeling using sound files according to another embodiment of the present application;

FIG. 3 is a flow chart of a method for fast offline modeling using sound recordings according to another embodiment of the application;

FIG. 4 is a flow chart of a method for rapid offline modeling using sound files according to another embodiment of the present application;

FIG. 5 is a schematic diagram of a system for rapid offline modeling using sound recordings according to an embodiment of the present application;

fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It should also be understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.

As used in the present description and the appended claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]".

Furthermore, the terms "first," "second," "third," and the like in the description of the present specification and in the appended claims, are used for distinguishing between descriptions and not necessarily for indicating or implying a relative importance.

Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.

As shown in FIG. 1, one embodiment of the present invention discloses a method for rapid offline modeling using sound recordings. The method is used for constructing and training the automobile noise reduction model. The automobile noise reduction model is applied to an active noise reduction system of a target new automobile. In active noise reduction systems, an automobile noise reduction model is used to analyze and process noise signals to generate inverted sound waves. Specifically, the collected noise signal is input into a noise reduction model of the automobile, which analyzes the spectral characteristics of the noise signal based on acoustic signal processing techniques such as fourier transform, wavelet transform, etc., to calculate optimal inverted acoustic parameters, which are then used to drive a speaker to generate inverted acoustic waves. In active noise reduction systems, the car noise reduction model needs to work in real time in order to respond quickly to noise changes.

In this embodiment, the method for rapid offline modeling using a sound recording file includes the steps of:

s110, determining a reference vehicle according to the target new vehicle. For example, the reference vehicle may be determined according to the in-vehicle size and classification type of the target new vehicle. The classification type may be a car or an SUV.

As an example and not by way of limitation, a vehicle that belongs to the same classification type as the target new vehicle and has a height difference in the vehicle that is less than a first preset threshold value is taken as a reference vehicle. For example, the first preset threshold may be, for example, 2cm, which is not limited to the present application.

S120, determining an acoustic path in the reference vehicle. The acoustic path includes a primary path and a secondary path.

Specifically, in the field of automotive active noise reduction (ANC), the primary Path (PRIMARY PATH) and the Secondary Path (Secondary Path) are two different acoustic paths that describe the propagation of an acoustic signal from a noise source to a receiving point (such as a microphone). The primary path refers to an acoustic path that propagates directly from a source of noise (e.g., an engine, an exhaust system, a tire to road contact point, etc.) to a receiving point (typically a microphone in a vehicle or an ear of a passenger). The acoustic properties of this path include all attenuation, reflection, refraction, interference, etc. effects of sound waves from noise sources as they propagate through the vehicle structure and air medium. The main path is a key factor in noise control because it directly determines the noise level perceived by the occupants of the vehicle.

The secondary path refers to an acoustic path that propagates from a noise source to a receiving point through a speaker in the active noise reduction system (as a secondary sound source). The acoustic properties of the secondary path also include the propagation effects of sound waves in the vehicle structure and air medium, but the secondary path is primarily a propagation process from the speaker to the receiving point.

In this embodiment, the microphone may be disposed at the top of the cabin of the reference vehicle, near the engine, and the plurality of speakers may be disposed at the door of the vehicle, so that destructive interference with the original noise may be more effectively performed than when the speakers are disposed on the inner wall of the front portion of the cabin, and the destructive interference effect with the original noise may be maximized, that is, the active noise reduction effect in the cabin may be improved.

In some alternative embodiments, the number of cabin top microphones and the number of cabin interior speakers are equal.

S130, recording files on a main path and a secondary path of an engine of the reference vehicle under different working states are respectively acquired, and noise data of the engine are acquired. That is, the audio files on the main path and the secondary path of the engine of the reference vehicle under different working states are respectively collected to form the audio files on the main path and the secondary path.

In this embodiment, a microphone disposed near the engine is used to collect noise data of the engine. The microphone may be mounted inside the engine compartment, at the junction between the engine and the body, on the firewall of the vehicle or near the Engine Control Unit (ECU). The engine noise can be captured when the engine noise passes through the vehicle body structure by being arranged at the joint between the engine and the vehicle body or on the fireproof wall of the vehicle. According to the embodiment, the sound recording files on the main path and the secondary path are comprehensively adopted, and the noise data of the engine are collected and input into the automobile noise reduction model for calculation, so that the calculation accuracy of the inverted sound wave parameters is improved, and the noise reduction effect in the automobile is improved.

In this embodiment, the steps include: recording files on a main path of an engine of a reference vehicle under idle working conditions and different running states are collected. And/or collecting sound recordings of the engine of the reference vehicle on the main path at different speeds and different engine speeds. Wherein, the running state comprises uniform running, acceleration running and deceleration running. The recording file is the recording data. In the implementation, multiple groups of recording data can be recorded under each working condition.

And S140, training the preset noise reduction model according to the sound record file on the main path, the sound record file on the secondary path and the noise data of the engine to obtain the trained preset noise reduction model. In this embodiment, the obtained trained preset noise reduction model is the above-mentioned noise reduction model of the automobile. The preset noise reduction model adopts a least mean square (LEAST MEAN square, LMS) algorithm, but the application is not limited thereto. The LMS algorithm is an adaptive filtering algorithm that adjusts the filter weights by minimizing the mean square value of the error signal to produce an anti-noise signal that is opposite in phase to the original noise.

Another embodiment of the invention discloses another method for rapid offline modeling using sound files. As shown in fig. 2, this embodiment is based on the corresponding embodiment of fig. 1 described above, and step S110 is replaced by step S111:

At least one vehicle is randomly selected as a reference vehicle from vehicles which are developed based on the same platform and have the same noise reduction system as the target new vehicle. The same noise reduction system specifically has the same number of microphones and adopts the same secondary path transfer function, so that the calculation accuracy of the inverted sound wave parameters in the automobile noise reduction model applied to the target new automobile is improved, and the in-automobile noise reduction effect is improved.

The transfer function describes the acoustic path characteristics from the noise source to the receiving point, where the loudspeaker can be used to generate a test signal of known frequency for actual measurement, and the response measured at the receiving point (e.g. microphone position) to obtain the transfer function, i.e. the acoustic characteristics of the secondary path.

Another embodiment of the invention discloses another method for rapid offline modeling using sound files. As shown in fig. 3, this embodiment, on the basis of the corresponding embodiment of fig. 1, includes the steps of:

S150, determining an acoustic resonance area of the interior of the reference vehicle.

S160, determining the installation position of the loudspeaker according to the acoustic resonance area, and installing the loudspeaker based on the installation position. Wherein the mounting location avoids the acoustic resonance region.

Step S120 is replaced with step S121: and determining an acoustic path in the reference vehicle according to the installed loudspeaker.

Thus, unnecessary noise enhancement can be reduced, interference to sound waves collected by the microphone is avoided, noise collection accuracy is improved, and accordingly noise reduction effect in the vehicle is guaranteed.

In some alternative embodiments, the step S130 further includes: a sound recording file on a secondary path of an engine of a reference vehicle in an unactuated state is acquired. Specifically, during the recording file collection of the secondary path, a loudspeaker in the reference vehicle can be controlled to emit a white noise signal, and acoustic data received by a microphone is collected.

In a preferred embodiment, the speakers are provided at the bottoms of the respective doors of the reference vehicle, so that the generated anti-noise sound waves cover more space inside the vehicle cabin than if the speakers were mounted on the inner wall of the front portion of the vehicle cabin, to maximize the destructive interference effect with the original noise, thereby facilitating the improvement of the noise reduction effect in the vehicle. In another preferred embodiment, the emitting direction of the speaker is toward the middle of the vehicle cabin so that sound waves can be uniformly propagated to the inside of the vehicle cabin, covering a wider area to maximize the destructive interference effect with the original noise, thereby facilitating the improvement of the noise reduction effect in the vehicle.

Another embodiment of the invention discloses an active noise reduction method for an automobile. As shown in fig. 4, the method comprises the steps of:

S210, acquiring acoustic data in the new target vehicle.

S220, verifying the trained preset noise reduction model based on the acoustic data of the target new vehicle, and determining model parameters. The trained preset noise reduction model is generated based on the method using the audio file for rapid offline modeling disclosed in any embodiment.

S230, determining a target noise reduction model according to the model parameters and a preset noise reduction model.

S240, generating sound waves with opposite phases to noise according to the target noise reduction model and a loudspeaker in the new target vehicle so as to realize active noise reduction. Namely, the target noise reduction model is utilized to drive the loudspeaker to generate the opposite-phase sound wave, so that the influence of noise is eliminated, and noise reduction is realized.

In this embodiment, the reference vehicle is mounted with a reference microphone, an error microphone, and an auxiliary reference microphone. The reference microphone is mounted on the front of the vehicle roof and near the engine, near the noise source, for capturing the raw noise signal. The reference microphone is not installed in a location that may be directly affected by the secondary sound source (speaker) to ensure that an undisturbed noise signal is captured. An error microphone is provided on the center of the roof for capturing residual noise after noise reduction, the position of which can represent the position of the ears of the passenger, so as to evaluate the noise reduction effect more accurately. An auxiliary reference microphone may be provided at the rear of the roof for auxiliary capturing of noise signals.

In this embodiment, the noise signal collected by the auxiliary reference microphone facilitates determining two parameters, namely the step size factor and the filter length in the LMS algorithm. The step factor is a key parameter for controlling the convergence rate of the algorithm, and determines the amplitude of weight update in each iteration, so that the stability and the rapid convergence of the algorithm are affected. The filter length determines the order of the adaptive filter, i.e. the number of weights in the filter.

Meanwhile, in the embodiment, only the reference microphone and the error microphone are required to be arranged on the target new vehicle, and an auxiliary reference microphone is not required to be arranged. Because the preset noise reduction model is trained based on the sound record file acquired by the reference vehicle, the target new vehicle and the reference vehicle have determined relevance, and the same preset noise reduction model is adopted, the auxiliary reference microphone is not required to be arranged on the subsequent target new vehicle, the step size factor and the value of the filter length obtained based on the reference vehicle are directly utilized, the manufacturing complexity and the cost of the target new vehicle can be effectively reduced, and the development efficiency of the active noise reduction system on the target new vehicle is improved.

On the other hand, the setting positions of the reference microphone, the error microphone and the loudspeaker on the target new vehicle are the same as the setting positions and the number of the microphone and the loudspeaker on the reference vehicle, so that the active noise reduction effect of the target new vehicle can be ensured. In other embodiments, the positions and numbers of the reference microphone, the error microphone and the speaker on the new target vehicle may be different from those of the reference microphone and the speaker on the new target vehicle, which is not limited by the present invention.

It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present application.

It should be noted that, the above embodiments of the method disclosed by the application can be freely combined, and the technical scheme obtained after the free combination is also within the protection scope of the application.

Corresponding to the method for rapid offline modeling using a sound recording file described in the above embodiments, fig. 5 shows a block diagram of a system for rapid offline modeling using a sound recording file according to an embodiment of the present application, and for convenience of explanation, only the portions related to the embodiments of the present application are shown. The system is used for constructing and training the automobile noise reduction model. The automobile noise reduction model is applied to an active noise reduction system of a target new automobile. The active noise reduction system comprises the system for quick offline modeling by using the sound recording file.

Referring to fig. 5, the system for fast offline modeling using sound recordings includes:

The reference vehicle determination module 51 determines a reference vehicle based on the target new vehicle.

A reference vehicle acoustic path determination module 52 determines an acoustic path within the reference vehicle. The acoustic path includes a primary path and a secondary path.

The reference vehicle audio file collection module 53 respectively obtains audio files on the main path and the secondary path of the engine of the reference vehicle under different working states, and collects noise data of the engine.

The preset noise reduction model generating module 54 trains the preset noise reduction model according to the sound record file on the main path, the sound record file on the secondary path and the noise data of the engine to obtain the trained preset noise reduction model.

In some alternative embodiments, the reference vehicle determining module 51 is configured to randomly select at least one reference vehicle from vehicles developed on the same platform and having the same noise reduction system as the target new vehicle.

In some alternative embodiments, the reference vehicle audio file collection module 53 is configured to collect audio files on the main path of the engine of the reference vehicle under idle conditions and different driving states; the running states include constant speed running, acceleration running, and deceleration running.

In some alternative embodiments, the reference vehicle profile collection module 53 is configured to collect profiles of the engine of the reference vehicle on the main path at different vehicle speeds and different engine speeds.

In some alternative embodiments, the reference vehicle profile collection module 53 is configured to collect profiles of the engine of the reference vehicle on the secondary path in an inactive state.

In some alternative embodiments, the reference vehicle audio file collection module 53 is configured to control a speaker inside the reference vehicle to emit a white noise signal, and collect acoustic data received by a microphone.

In some alternative embodiments, the speakers are provided at the bottom of each door of the reference vehicle, and the microphones are provided at the roof of the reference vehicle.

In some alternative embodiments, the system further comprises:

an acoustic resonance region determination module determines an acoustic resonance region of the reference vehicle interior.

An installation position determining module for determining an installation position of the speaker according to the acoustic resonance region and installing the speaker based on the installation position; wherein the mounting location avoids the acoustic resonance region.

It should be noted that, because the content of information interaction and execution process between the above systems/units is based on the same concept as the method embodiment of the present application, specific functions and technical effects thereof may be referred to in the method embodiment section, and will not be described herein.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the system is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.

The embodiment of the present application also provides an electronic device, as shown in fig. 6, the electronic device 60 includes: at least one processor 601, a memory 602 and a computer program 603 stored in the memory and executable on the at least one processor, which processor implements the steps of any of the various method embodiments described above when it executes the computer program.

Embodiments of the present application also provide a computer readable storage medium storing a computer program which, when executed by a processor, implements steps for implementing the various method embodiments described above.

Embodiments of the present application provide a computer program product which, when run on a mobile terminal, causes the mobile terminal to perform steps that enable the implementation of the method embodiments described above.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiments, and may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a camera device/electronic apparatus, a recording medium, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, and a software distribution medium. Such as a U-disk, removable hard disk, magnetic or optical disk, etc. In some jurisdictions, computer readable media may not be electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiments provided in the present application, it should be understood that the disclosed system/network device and method may be implemented in other manners. For example, the system/network device embodiments described above are merely illustrative, e.g., the division of the modules or elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, systems or units, which may be in electrical, mechanical or other forms.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

The above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.

Claims

1. A method for rapid offline modeling using sound recordings, comprising:

Determining a reference vehicle according to the target new vehicle;

2. The method for rapid offline modeling using audio files of claim 1, wherein determining a reference vehicle from a target new vehicle comprises:

3. A method of rapid offline modeling using audio files as defined in claim 1 wherein said separately obtaining audio files on said primary path and said secondary path for said reference vehicle's engine under different operating conditions comprises:

4. A method of rapid offline modeling using audio files as defined in claim 1 wherein said separately obtaining audio files on said primary path and said secondary path for said reference vehicle's engine under different operating conditions comprises:

5. A method of rapid offline modeling using audio files as defined in claim 1 wherein said separately obtaining audio files on said primary path and said secondary path for said reference vehicle's engine under different operating conditions comprises:

6. A method of rapid offline modeling using sound recordings as defined in claim 5, wherein said capturing sound recordings on said secondary path of said reference vehicle's engine in an inactive state comprises:

7. A method of rapid offline modeling using audio files as defined in claim 6 wherein the speakers are located at the bottom of each door of the reference vehicle and the microphones are located at the roof of the reference vehicle.

8. A method of rapid offline modeling using sound recordings as defined in claim 1, wherein prior to said determining an acoustic path within said reference vehicle, said method comprises:

Determining an acoustic resonance region of the reference vehicle interior;

9. An active noise reduction method for an automobile, comprising:

Acquiring acoustic data in a new target vehicle;

10. A system for rapid offline modeling using sound recordings, comprising: