CN111833840B - Noise reduction method, noise reduction device, noise reduction system, electronic equipment and storage medium - Google Patents
Noise reduction method, noise reduction device, noise reduction system, electronic equipment and storage medium Download PDFInfo
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
- G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
- G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
- G10K11/1787—General system configurations
- G10K11/17879—General system configurations using both a reference signal and an error signal
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
- G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
- G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
- G10K11/1781—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions
- G10K11/17821—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions characterised by the analysis of the input signals only
- G10K11/17823—Reference signals, e.g. ambient acoustic environment
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- G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
- G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
- G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
- G10K11/1781—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions
- G10K11/17821—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions characterised by the analysis of the input signals only
- G10K11/17825—Error signals
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- G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
- G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
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Abstract
The embodiment of the disclosure discloses a noise reduction method, a noise reduction device, a noise reduction system, electronic equipment and a storage medium, wherein the method comprises the following steps: determining a main noise signal corresponding to a current driving state of the vehicle; determining an anti-noise signal for denoising the main noise signal based on the main noise signal; based on the anti-noise signal and the main noise signal, a denoised residual signal is obtained, and the main noise is denoised, so that the noise is reduced in a targeted manner, a variable noise source which cannot be tracked by the existing noise reduction technology can be processed, the whole noise reduction process is more stable, and the average noise reduction amount is higher; and the calculation amount of the denoising process is reduced.
Description
Technical Field
The present disclosure relates to speech technology, and in particular, to a noise reduction method and apparatus, a system, an electronic device, and a storage medium.
Background
With the popularization of vehicles, the harm of automobile noise is important, and the harm of automobile noise to human health is that various noises act on the central nervous system of a human body, so that the excitation and inhibition balance of cerebral cortex is unbalanced, the conditioned reflex is abnormal, and the cerebral vascular tension is damaged. These physiological changes can be restored in early stages, but for a long time, they can cause pathological changes, which cause symptoms such as headache, cerebral swelling, tinnitus, insomnia, memory deterioration, general fatigue and weakness.
Aiming at the denoising of automobile noise, the existing in-car noise reduction technology has the defects that the self-adaptive noise reduction system is difficult to update rapidly and the noise reduction effect is poor under the condition of multiple noise sources in an actual road.
Disclosure of Invention
The present disclosure has been made in order to solve the above technical problems. The embodiment of the disclosure provides a noise reduction method, a noise reduction device, a noise reduction system, electronic equipment and a storage medium.
According to an aspect of the embodiments of the present disclosure, there is provided a noise reduction method, including:
determining a main noise signal corresponding to a current driving state of the vehicle;
determining an anti-noise signal for denoising the main noise signal based on the main noise signal;
And obtaining a denoised residual signal based on the anti-noise signal and the main noise signal.
According to another aspect of the embodiments of the present disclosure, there is provided a noise reduction apparatus including:
A main noise signal determining module for determining a main noise signal corresponding to a current running state of the vehicle;
an anti-noise signal determination module configured to determine an anti-noise signal for denoising the main noise signal based on the main noise signal determined by the main noise signal determination module;
And the denoising module is used for obtaining a denoised residual signal based on the anti-noise signal obtained by the anti-noise signal determining module and the main noise signal.
According to still another aspect of the embodiments of the present disclosure, there is provided a noise reduction system including: at least one information acquisition module arranged inside and outside the vehicle, a sound source output module arranged inside the vehicle and the noise reduction device in the embodiment;
The information acquisition module is used for acquiring the running related information of the vehicle;
the noise reduction device is used for determining a main noise signal based on the driving related information acquired by the information acquisition module and determining an anti-noise signal based on the main noise signal; obtaining a denoised residual signal based on the anti-noise signal and the main noise signal;
The sound source output module is used for outputting the anti-noise signal obtained by the noise reduction device.
According to still another aspect of the embodiments of the present disclosure, there is provided an electronic device including:
A processor;
A memory for storing the processor-executable instructions;
The processor is configured to execute the noise reduction method described in the foregoing embodiment.
According to still another aspect of the embodiments of the present disclosure, there is provided a computer-readable storage medium storing a computer program for executing the noise reduction method described in the above embodiments.
Based on the noise reduction method, the device, the system, the electronic equipment and the storage medium provided by the embodiment of the disclosure, determining a main noise signal corresponding to the current running state of the vehicle; determining an anti-noise signal for denoising the main noise signal based on the main noise signal; based on the anti-noise signal and the main noise signal, a denoised residual signal is obtained, and the main noise is denoised, so that the noise is reduced in a targeted manner, a variable noise source which cannot be tracked by the existing noise reduction technology can be processed, the whole noise reduction process is more stable, and the average noise reduction amount is higher; and the calculation amount of the denoising process is reduced.
The technical scheme of the present disclosure is described in further detail below through the accompanying drawings and examples.
Drawings
The above and other objects, features and advantages of the present disclosure will become more apparent by describing embodiments thereof in more detail with reference to the accompanying drawings. The accompanying drawings are included to provide a further understanding of embodiments of the disclosure, and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure, without limitation to the disclosure. In the drawings, like reference numerals generally refer to like parts or steps.
Fig. 1 is a schematic structural diagram of a denoising system according to an exemplary embodiment of the present disclosure.
Fig. 2 is a flow chart of a denoising method according to an exemplary embodiment of the present disclosure.
Fig. 3 is a flow chart illustrating step 201 in the embodiment shown in fig. 2 of the present disclosure.
Fig. 4 is a flow chart illustrating step 2013 in the embodiment of fig. 3 of the present disclosure.
Fig. 5 is a flow chart illustrating step 202 in the embodiment of fig. 2 of the present disclosure.
Fig. 6 is a partial flow diagram in a denoising method according to another exemplary embodiment of the present disclosure.
Fig. 7 is a schematic structural diagram of a denoising apparatus according to an exemplary embodiment of the present disclosure.
Fig. 8 is a schematic structural view of a denoising apparatus provided in another exemplary embodiment of the present disclosure.
Fig. 9 is a block diagram of an electronic device provided in an exemplary embodiment of the present disclosure.
Detailed Description
Hereinafter, example embodiments according to the present disclosure will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present disclosure and not all of the embodiments of the present disclosure, and that the present disclosure is not limited by the example embodiments described herein.
It should be noted that: the relative arrangement of the components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless it is specifically stated otherwise.
It will be appreciated by those of skill in the art that the terms "first," "second," etc. in embodiments of the present disclosure are used merely to distinguish between different steps, devices or modules, etc., and do not represent any particular technical meaning nor necessarily logical order between them.
It should also be understood that in embodiments of the present disclosure, "plurality" may refer to two or more, and "at least one" may refer to one, two or more.
It should also be appreciated that any component, data, or structure referred to in the presently disclosed embodiments may be generally understood as one or more without explicit limitation or the contrary in the context.
In addition, the term "and/or" in this disclosure is merely an association relationship describing an association object, and indicates that three relationships may exist, for example, a and/or B may indicate: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" in the present disclosure generally indicates that the front and rear association objects are an or relationship.
It should also be understood that the description of the various embodiments of the present disclosure emphasizes the differences between the various embodiments, and that the same or similar features may be referred to each other, and for brevity, will not be described in detail.
Meanwhile, it should be understood that the sizes of the respective parts shown in the drawings are not drawn in actual scale for convenience of description.
The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses.
Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail, but are intended to be part of the specification where appropriate.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further discussion thereof is necessary in subsequent figures.
Embodiments of the present disclosure may be applicable to electronic devices such as terminal devices, computer systems, servers, etc., which may operate with numerous other general purpose or special purpose computing system environments or configurations. Examples of well known terminal devices, computing systems, environments, and/or configurations that may be suitable for use with the terminal device, computer system, server, or other electronic device include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, minicomputer systems, mainframe computer systems, and distributed cloud computing technology environments that include any of the above systems, and the like.
Electronic devices such as terminal devices, computer systems, servers, etc. may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, etc., that perform particular tasks or implement particular abstract data types. The computer system/server may be implemented in a distributed cloud computing environment in which tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computing system storage media including memory storage devices.
Summary of the application
In the process of implementing the present disclosure, the inventors found that, in the case of multiple noise sources in an actual road, a plurality of noises are included in a vehicle, besides wind noises and tire noises, there are often burst noises caused by other vehicles passing, that is, at least the following problems exist: the existing active noise reduction technology in the automobile is difficult to realize multiple noises simultaneously, and an ideal noise reduction effect is realized.
Exemplary System
Fig. 1 is a schematic diagram of a noise reduction system according to an exemplary embodiment of the present disclosure. Comprising the following steps: at least one information acquisition module 101 provided inside and outside the vehicle, a sound source output module 102 provided inside the vehicle, and a noise reduction device 103;
The information acquisition module 101 is used for acquiring the driving related information of the vehicle.
Alternatively, the information acquisition module 101 may include a variety of sensors, including, for example, at least one of: vehicle-mounted microphones, image capture devices, infrared sensors, etc., may also receive information transmitted by the vehicle control system (e.g., engine information, air conditioning operation information, etc.).
Scene recognition can be achieved through the information acquisition module, and the current driving situation of the vehicle, such as whether the vehicle is running, whether window opening or air conditioning is performed, how the vehicle speed is, the road surface type and the surrounding environment of the vehicle, is analyzed. By analyzing the travel-related information of the vehicle acquired by the information acquisition module 101, the travel state of the vehicle at this time can be determined.
A noise reduction device 103, configured to determine a main noise signal based on the traveling related information acquired by the information acquisition module, and determine an anti-noise signal based on the main noise signal; the denoised residual signal is obtained based on the anti-noise signal and the main noise signal.
The source of the main noise (for example, engine noise, tire noise during driving, wind noise caused by high-speed driving, noise caused by other vehicles passing nearby, etc.) is determined by identifying the main noise source. After the primary noise source is determined, active noise reduction can be performed on the primary noise signal generated by the primary noise source. The main noise signal can be obtained by installing reference microphones near an engine, a tire and a vehicle window, and selecting a proper reference microphone according to the source of a main noise source, so that the problem that the simultaneous input of multichannel microphone signals brings huge operation pressure to a processor is avoided. For example, if the nearby vehicle is a main noise source, the speed, type and distance of the nearby vehicle are determined according to the analysis of the multiple sensors, the radiation noise of the type of vehicle under the condition of the speed is queried through a cloud database, the noise intensity of the nearby vehicle at the moment can be obtained, the noise reaching the interior of the vehicle is calculated by combining the vehicle distance and the opposite speed analysis, and the calculation result can be used as a main noise signal.
The sound source output module 102 is configured to output an anti-noise signal obtained by the noise reduction device.
Optionally, the sound source output module 102 may include, but is not limited to, a vehicle speaker, and performs noise suppression on the main noise signal through the anti-noise signal that is played, so as to implement active control on the main noise source, so that the sound field in the vehicle after control is stable, and abrupt noise during driving can be well suppressed, so as to implement a good noise reduction effect.
Exemplary method
Fig. 2 is a flow chart illustrating a noise reduction method according to an exemplary embodiment of the present disclosure. The embodiment can be applied to an electronic device, as shown in fig. 2, and includes the following steps:
step 201, determining a main noise signal corresponding to a current running state of the vehicle.
Wherein the current running state of the vehicle can be determined by acquiring information such as an image of the vehicle, information output by a vehicle control system, and the like. The different running states of the vehicle may correspond to different main noise sources, and optionally, the main noise source corresponding to the current running state is subjected to signal acquisition by the sound acquisition device to obtain a main noise signal.
Step 202, an anti-noise signal for denoising the main noise signal is determined based on the main noise signal.
In an embodiment, the anti-noise signal is calculated based on the main noise signal for de-noising the main noise signal.
In step 203, a denoised residual signal is obtained based on the anti-noise signal and the main noise signal.
In an embodiment, when the main noise signal and the anti-noise signal are played at the same time, denoising of the main noise signal can be achieved, and a denoised residual signal is obtained, so that an in-vehicle sound field is stable. Alternatively, the residual signal is obtained by using an LMS algorithm, which is an active noise reduction algorithm commonly used at present, and provides a basic flow of active noise reduction. In this embodiment, obtaining the residual signal by the LMS algorithm may be implemented as formula (1):
e (n) =d (n) -y (n) formula (1)
Where n denotes a current time, e (n) denotes a residual signal of the current time, d (n) denotes a main noise signal of the current time, and y (n) =f (d (n)) denotes an anti-noise signal of the current time calculated based on the main noise signal.
Based on the noise reduction method provided by the embodiment of the disclosure, determining a main noise signal corresponding to the current running state of the vehicle; determining an anti-noise signal for denoising the main noise signal based on the main noise signal; based on the anti-noise signal and the main noise signal, a denoised residual signal is obtained, and the main noise is subjected to targeted denoising treatment, so that a variable noise source which cannot be tracked by the existing denoising technology can be treated, the whole denoising process is more stable, and the average denoising quantity is higher; since denoising is performed only for the main noise signal, the calculation amount of denoising processing is reduced.
As shown in fig. 3, on the basis of the embodiment shown in fig. 2, step 201 may include the following steps:
In step 2011, an information collection module corresponding to a current driving state of the vehicle is determined.
Alternatively, the information acquisition module may employ a microphone, a camera, or the like, which can acquire information on the current running state of the vehicle.
In step 2012, the control information collecting module collects driving related information corresponding to the current driving state.
Alternatively, the travel related information may include, but is not limited to, at least one of the following: the running state information of the vehicle, the opening and closing state of the window of the vehicle, the opening and closing state of the air conditioner of the vehicle, the vehicle type information, the vehicle speed information, the road surface type, the surrounding environment information of the vehicle, the type of the vehicle within a preset distance from the vehicle, the vehicle speed of the vehicle within a preset distance from the vehicle, and the like. The driving state information may include, for example, a parking state, a driving state, and the like; the opening and closing states of the window may include a window opening state and a window closing state; the on-off state of the air conditioner may include an air conditioner on state and an air conditioner off state; the road surface type may include, for example, gravel road, expressway, earth road, etc.; the surrounding information of the vehicle may include that there are no other vehicles around the vehicle, that there are other vehicles around the vehicle, and so on.
The speed of the vehicle within the preset distance from the vehicle may be a relative speed between the current vehicle and the vehicle within the preset distance, or a speed of the vehicle within the preset distance from the vehicle.
After the primary noise source is determined, active noise reduction may be performed for the primary noise source and the anti-noise signal may be switched. The reference microphones are arranged near the engine, the tyre and the car window, and according to the source of the main noise source, the proper reference microphone is selected as the reference signal input, so that the huge operation pressure of the processor caused by the simultaneous input of the multi-channel microphone signals is avoided. The acquisition of different travel related information may be performed by different information acquisition modules, or a plurality of travel related information may be acquired by one information acquisition module, for example, surrounding environment information of the vehicle may be acquired by a camera (a hardware form of the information acquisition module) provided around the vehicle, and travel state information of the vehicle, a switching state of a window of the vehicle, a switching state of an air conditioner of the vehicle, vehicle type information, and vehicle speed information may be obtained from information transmitted by, for example, a vehicle control system.
Step 2013, determining a main noise signal of the vehicle based on the driving related information.
The embodiment realizes scene recognition, the current running state of the vehicle can be analyzed through the running related information acquired by the information acquisition module, and the main noise source of the vehicle is determined through the analysis of the running related information of the vehicle, so that the main noise signal is obtained. For example, if in a park condition, the engine or air conditioner is the primary source of noise in the vehicle; if the vehicle is driven independently at a high speed, determining whether the main noise is tire noise, wind noise or engine noise through the main sources of noise under different vehicle speed conditions analyzed in a design stage; if the window is opened, the tire noise and wind noise become main noise sources, and the path of the main noise entering the vehicle can be determined according to different window opening positions of the vehicle window; in the case of a sandy road, noise generated by the friction of tires with sand will become a major source of noise. In addition to the driving condition of the vehicle, if a large vehicle or a vehicle passing at a high speed appears beside the vehicle during driving, when the vehicles are staggered, the tire noise of the opposite vehicle and the noise of the engine rotating at a high speed become main noise sources, and the model and the speed of the nearby vehicle can be judged through analysis of multiple sensors.
According to the embodiment, the main noise signal of the vehicle is determined through the acquired driving related information, so that the main noise source in the vehicle can be obtained under any scene condition, and further the main noise signal is obtained.
As shown in fig. 4, on the basis of the embodiment shown in fig. 3, step 2013 may include the following steps:
in step 20131, a main noise signal at the current time is determined based on the type of the nearby vehicle and the speed of the nearby vehicle.
Wherein the nearby vehicle is a vehicle within a preset distance from the vehicle.
Step 20132 predicts the main noise signal at the next time based on the main noise signal at the current time and the speed of the nearby vehicle.
For rapidly-changing noise sources such as high-speed overtaking of nearby vehicles, real-time convergence cannot be achieved by means of simple iterative updating of the filter. In this embodiment, the position of the nearby vehicle after a short time is predicted by the vehicle speed and the relative position of the vehicle, the main noise signal at the next time is predicted, the optimal filter coefficient at the next time is calculated, the filter coefficient at the next time is updated by the result, and the filter coefficient at the next time is dynamically calculated according to the actual arrival position of the nearby vehicle and the vehicle speed change, so that a faster filter iteration update process is realized without being limited by the iteration step of the filter.
Optionally, step 202 includes: an anti-noise signal that is denoised for the main noise information at the next time is determined based on the main noise signal at the next time.
In this embodiment, since the main noise signal belongs to a suddenly appearing noise signal, if an iterative method is adopted to determine the noise signal, the noise reduction is not performed, and the noise reduction speed is increased while the noise reduction effect is improved by predicting the noise signal at the next moment through the noise signal at the current moment and reducing the noise of the main noise signal at the next moment through the predicted noise signal.
In an alternative embodiment, in addition to any of the above embodiments, the anti-noise method further includes:
And uploading the main noise signal and/or the anti-noise signal to a cloud server for storage.
Wherein each main noise signal and/or anti-noise signal corresponds to different driving related information.
Alternatively, for the same vehicle information (e.g., model, vehicle speed, etc.), there is a case where after the main noise source is determined, its main noise signal is fixed, for example, the engine noise is the same in the case where the vehicle speeds are the same for the same vehicle; for the situation that the main noise signal is fixed, the main noise signal is stored in the cloud server, so that the corresponding main noise signal can be directly obtained from the cloud server under the same situation next time, the obtaining speed of the main noise signal is increased, and the anti-noise efficiency is improved; for example, optionally, step 201 includes: determining a current running state of the vehicle; and acquiring a main noise signal of the vehicle from the cloud server based on the current running state.
Meanwhile, because the anti-noise signal is obtained based on the main noise signal calculation, the anti-noise signal or the main noise signal and the anti-noise signal thereof can be stored in the cloud server, after the main noise source is determined after the anti-noise signal is stored, the corresponding anti-noise signal can be obtained through searching, the process of calculating the anti-noise signal based on the main noise signal is further reduced, and the anti-noise efficiency is improved. For example, optionally, step 202 includes: and reading an anti-noise signal corresponding to the running related information of the current vehicle from the cloud server based on the main noise signal.
As shown in fig. 5, step 202 may include the following steps, based on the embodiment shown in fig. 2, described above:
Step 2021, determining a path for the main noise signal to reach a location for emitting the anti-noise signal.
Step 2022, based on the path, determines the anti-noise signal.
The sound signals transmitted to different positions by different paths are different, and the main noise signal is received at the position where the anti-noise signal (for example, the vehicle-mounted loudspeaker) is transmitted, so that the path from the main noise source to the position where the anti-noise signal is transmitted is taken as the transmission path of the main noise signal; the magnitude of the received main noise signal may be determined based on the propagation path, at which time an anti-noise signal is calculated based on the main noise signal that may cancel the main noise signal at that location.
As shown in fig. 6, on the basis of the embodiment shown in any one of fig. 2 to 5, after performing step 203 to obtain the denoised residual signal, the method further includes:
Step 601, adjusting the anti-noise signal based on the residual signal, and obtaining an adjusted anti-noise signal.
Step 602, obtaining a denoised residual signal based on the adjusted anti-noise signal and the main noise signal.
Step 603, detecting whether the residual signal meets a preset condition, and if so, executing step 604; if the preset condition is not satisfied, executing step 601;
Step 604, outputting a residual signal.
The embodiment realizes that for the known stable main noise signal, the control filter coefficient required by calculating the anti-noise signal can be calculated in an iterative updating mode, so that the noise control with better effect is realized; the process can comprise the following steps: transmitting the residual signal back to a control unit for calculating the residual signal, realizing the adjustment of the anti-noise signal based on the residual signal, iteratively updating the residual signal by the control unit, and outputting the obtained denoised residual signal after multiple iterations until a preset condition is met, wherein the preset condition can comprise: the residual signal is stable, namely, the transformation amplitude of the residual signal in the two iterative processes is smaller than a certain value; and obtaining a stable residual signal, so that stable noise reduction can be realized.
The active noise reduction technology is applied in the vehicle, and mainly adopts the multichannel feedforward self-adaptive active noise reduction technology to obtain a stable noise reduction area. It is necessary to use devices such as a reference microphone, an error microphone, and a control unit for controlling a sound source, and to provide sufficient computing power. The reference microphone is used for acquiring signals of internal and external (such as the inside and the outside of the vehicle) noise sources, the acquired signals are reference signals (such as noise signals), after the control unit acquires the reference signals, the noise resistant signals are calculated and output through the sound source output module, and the error microphone receives the radiation noise of the noise sources and the noise resistant signals output by the sound source output module at the same time to obtain error signals. In order to achieve a better denoising effect, the obtained error signal can be transmitted back to the control unit, and the control unit iteratively updates the anti-noise signal. After multiple iterations, the error microphone will obtain a stable residual signal, thereby achieving stable noise reduction. In practical use, a plurality of references, error microphones and a plurality of sound source output modules are used to realize regional noise reduction in the whole vehicle, and the use of multiple channels also brings about a great increase in calculation amount. If a better noise reduction result is to be obtained, a higher sampling rate may be used in addition to adding more channels, making the iterative updating of the control unit more frequent.
Any of the noise reduction methods provided by the embodiments of the present disclosure may be performed by any suitable device having data processing capabilities, including, but not limited to: terminal equipment, servers, etc. Or any of the noise reduction methods provided by the embodiments of the present disclosure may be executed by a processor, such as the processor executing any of the noise reduction methods mentioned by the embodiments of the present disclosure by invoking corresponding instructions stored in a memory. And will not be described in detail below.
Exemplary apparatus
Fig. 7 is a schematic structural diagram of a denoising apparatus according to an exemplary embodiment of the present disclosure. The apparatus of this embodiment may be used to implement the method embodiments of the present disclosure described above. As shown in fig. 7, includes:
the main noise signal determination module 71 is configured to determine a main noise signal corresponding to a current running state of the vehicle.
An anti-noise signal determination module 72 for determining an anti-noise signal for denoising the main noise signal based on the main noise signal determined by the main noise signal determination module.
The denoising module 73 is configured to obtain a denoised residual signal based on the anti-noise signal obtained by the anti-noise signal determining module and the main noise signal.
The noise reduction device provided by the embodiment of the disclosure determines a main noise signal corresponding to a current running state of a vehicle; determining an anti-noise signal for denoising the main noise signal based on the main noise signal; based on the anti-noise signal and the main noise signal, a denoised residual signal is obtained, and the main noise is denoised, so that the noise is reduced in a targeted manner, a variable noise source which cannot be tracked by the existing noise reduction technology can be processed, the whole noise reduction process is more stable, and the average noise reduction amount is higher; and the calculation amount of the denoising process is reduced.
FIG. 8 is a schematic structural view of an anti-noise device provided by another exemplary embodiment of the present disclosure. On the basis of the embodiment shown in fig. 7 described above, the main noise signal determining module 71 includes:
An information collection determining unit 711 for determining an information collection module corresponding to a current running state of the vehicle.
And the state information acquisition unit 712 is configured to control the information acquisition module to acquire driving related information corresponding to the current driving state.
A signal determination unit 713 for determining a main noise signal of the vehicle based on the travel related information.
Optionally, the driving related information includes at least one of the following information: the driving state information of the vehicle, the opening and closing state of the window of the vehicle, the opening and closing state of the air conditioner of the vehicle, the vehicle type information, the vehicle speed information, the road surface type, the surrounding environment information of the vehicle, the type of the vehicle within a preset distance from the vehicle, and the vehicle speed of the vehicle within a preset distance from the vehicle.
A signal determination unit 713 for determining a main noise signal at the present time based on the type of the nearby vehicle, which is a vehicle within a preset distance from the vehicle, and the speed of the nearby vehicle; based on the main noise signal at the present time and the speed of the nearby vehicle, the main noise signal at the next time is predicted.
Optionally, the anti-noise signal determination module 72 is configured to determine an anti-noise signal denoised for the main noise information at the next time based on the main noise signal at the next time.
Optionally, the apparatus of this embodiment further includes:
The signal storage module 74 is configured to upload the main noise signal and/or the anti-noise signal to the cloud server for saving.
Wherein each main noise signal and/or anti-noise signal corresponds to different driving related information.
Optionally, the main noise signal determining module 71 is specifically configured to determine a current running state of the vehicle; and acquiring a main noise signal of the vehicle from the cloud server based on the current running state.
Optionally, the anti-noise signal determining module 72 is specifically configured to read, from the cloud server, an anti-noise signal corresponding to the driving related information of the current vehicle based on the main noise signal.
Optionally, the anti-noise signal determination module 72 includes:
A path determination unit 721 for determining a path of the main noise signal to a position for emitting the anti-noise signal.
The signal acquisition unit 722 is configured to determine the anti-noise signal based on the path.
Optionally, the apparatus of this embodiment further includes:
An iteration adjustment module 75 for adjusting the anti-noise signal based on the residual signal to obtain an adjusted anti-noise signal; obtaining a denoised residual signal based on the adjusted anti-noise signal and the main noise signal; and when the residual signal is detected to meet the preset condition, obtaining the residual signal.
Exemplary electronic device
Next, an electronic device according to an embodiment of the present disclosure is described with reference to fig. 9. The electronic device may be either or both of the first device 100 and the second device 200, or a stand-alone device independent thereof, which may communicate with the first device and the second device to receive the acquired input signals therefrom.
Fig. 9 illustrates a block diagram of an electronic device according to an embodiment of the disclosure.
As shown in fig. 9, the electronic device 90 includes one or more processors 901 and memory 902.
Processor 901 may be a Central Processing Unit (CPU) or other form of processing unit having data processing and/or instruction execution capabilities and may control other components in electronic device 90 to perform desired functions.
The memory 902 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, random Access Memory (RAM) and/or cache memory (cache), and the like. The non-volatile memory may include, for example, read Only Memory (ROM), hard disk, flash memory, and the like. One or more computer program instructions may be stored on the computer readable storage medium that can be executed by the processor 901 to implement the denoising methods of the various embodiments of the present disclosure described above and/or other desired functions. Various contents such as an input signal, a signal component, a noise component, and the like may also be stored in the computer-readable storage medium.
In one example, the electronic device 90 may further include: an input device 903 and an output device 904, which are interconnected by a bus system and/or other forms of connection mechanisms (not shown).
For example, when the electronic device is the first device 100 or the second device 200, the input means 903 may be a microphone or a microphone array as described above for capturing an input signal of a sound source. When the electronic device is a stand-alone device, the input means 903 may be a communication network connector for receiving the acquired input signals from the first device 100 and the second device 200.
In addition, the input device 903 may also include, for example, a keyboard, a mouse, and the like.
The output device 904 may output various information to the outside, including the determined distance information, direction information, and the like. The output means 904 may include, for example, a display, speakers, a printer, and a communication network and remote output devices connected thereto, etc.
Of course, only some of the components of the electronic device 9 relevant to the present disclosure are shown in fig. 9 for simplicity, components such as buses, input/output interfaces, and the like being omitted. In addition, the electronic device 90 may include any other suitable components depending on the particular application.
Exemplary computer program product and computer readable storage Medium
In addition to the methods and apparatus described above, embodiments of the present disclosure may also be a computer program product comprising computer program instructions which, when executed by a processor, cause the processor to perform steps in a denoising method according to various embodiments of the present disclosure described in the above "exemplary methods" section of the present specification.
The computer program product may write program code for performing the operations of embodiments of the present disclosure in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server.
Furthermore, embodiments of the present disclosure may also be a computer-readable storage medium, having stored thereon computer program instructions, which when executed by a processor, cause the processor to perform steps in a denoising method according to various embodiments of the present disclosure described in the above section of the "exemplary method" of the present description.
The computer readable storage medium may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may include, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The basic principles of the present disclosure have been described above in connection with specific embodiments, but it should be noted that the advantages, benefits, effects, etc. mentioned in the present disclosure are merely examples and not limiting, and these advantages, benefits, effects, etc. are not to be considered as necessarily possessed by the various embodiments of the present disclosure. Furthermore, the specific details disclosed herein are for purposes of illustration and understanding only, and are not intended to be limiting, since the disclosure is not necessarily limited to practice with the specific details described.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different manner from other embodiments, so that the same or similar parts between the embodiments are mutually referred to. For system embodiments, the description is relatively simple as it essentially corresponds to method embodiments, and reference should be made to the description of method embodiments for relevant points.
The block diagrams of the devices, apparatuses, devices, systems referred to in this disclosure are merely illustrative examples and are not intended to require or imply that the connections, arrangements, configurations must be made in the manner shown in the block diagrams. As will be appreciated by one of skill in the art, the devices, apparatuses, devices, systems may be connected, arranged, configured in any manner. Words such as "including," "comprising," "having," and the like are words of openness and mean "including but not limited to," and are used interchangeably therewith. The terms "or" and "as used herein refer to and are used interchangeably with the term" and/or "unless the context clearly indicates otherwise. The term "such as" as used herein refers to, and is used interchangeably with, the phrase "such as, but not limited to.
The methods and apparatus of the present disclosure may be implemented in a number of ways. For example, the methods and apparatus of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, firmware. The above-described sequence of steps for the method is for illustration only, and the steps of the method of the present disclosure are not limited to the sequence specifically described above unless specifically stated otherwise. Furthermore, in some embodiments, the present disclosure may also be implemented as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present disclosure. Thus, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.
It is also noted that in the apparatus, devices and methods of the present disclosure, components or steps may be disassembled and/or assembled. Such decomposition and/or recombination should be considered equivalent to the present disclosure.
The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the disclosure. Thus, the present disclosure is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The foregoing description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of the disclosure to the form disclosed herein. Although a number of example aspects and embodiments have been discussed above, a person of ordinary skill in the art will recognize certain variations, modifications, alterations, additions, and subcombinations thereof.
Claims (13)
1. A method of noise reduction, comprising:
Determining a main noise signal corresponding to a current driving state of the vehicle; the determination of the primary noise includes: determining a main noise signal at a current moment based on a type of a nearby vehicle and a speed of the nearby vehicle, the nearby vehicle being a vehicle within a preset distance from the vehicle; predicting a main noise signal at a next time based on the main noise signal at the current time and a speed of the nearby vehicle;
determining an anti-noise signal for denoising the main noise signal based on the main noise signal; the determining an anti-noise signal for denoising the main noise signal based on the main noise signal, comprising:
determining a path for the main noise signal to a location for emitting the anti-noise signal;
Determining the anti-noise signal based on the path; determining a magnitude of the received main noise signal based on the path, calculating an anti-noise signal based on the main noise signal to cancel the main noise signal at the location;
And obtaining a denoised residual signal based on the anti-noise signal and the main noise signal.
2. The method of claim 1, wherein the determining a primary noise signal corresponding to a current driving state of the vehicle comprises:
determining an information acquisition module corresponding to a current driving state of the vehicle;
Controlling the information acquisition module to acquire driving related information corresponding to the current driving state;
A main noise signal of the vehicle is determined based on the travel related information.
3. The method of claim 2, wherein the travel related information includes at least one of: the vehicle control system comprises running state information of a vehicle, opening and closing states of windows of the vehicle, opening and closing states of air conditioners of the vehicle, vehicle type information, vehicle speed information, road surface type information, surrounding environment information of the vehicle, type of the vehicle within a preset distance from the vehicle, and vehicle speed of the vehicle within the preset distance from the vehicle.
4. The method of claim 1, wherein the determining an anti-noise signal for denoising the main noise signal based on the main noise signal comprises:
And determining the main noise signal based on the next moment as an anti-noise signal for denoising the main noise signal of the next moment.
5. A method according to claim 2 or 3, wherein the method further comprises:
Uploading the main noise signals and/or the anti-noise signals to a cloud server for storage, wherein each main noise signal and/or each anti-noise signal corresponds to different driving related information.
6. The method of claim 5, wherein the determining a primary noise signal corresponding to a current driving state of the vehicle comprises:
Determining a current running state of the vehicle;
and acquiring a main noise signal of the vehicle from the cloud server based on the current running state.
7. The method of claim 5, wherein the determining an anti-noise signal for denoising the main noise signal based on the main noise signal comprises:
and reading the anti-noise signal corresponding to the running related information of the current vehicle from the cloud server based on the main noise signal.
8. The method of claim 1, wherein the method further comprises:
adjusting the anti-noise signal based on the residual signal to obtain an adjusted anti-noise signal;
obtaining a denoised residual signal based on the adjusted anti-noise signal and the main noise signal;
and when the residual signal is detected to meet the preset condition, obtaining the residual signal.
9. A noise reduction device, comprising:
A main noise signal determining module for determining a main noise signal corresponding to a current running state of the vehicle; the main noise signal determining module comprises a signal determining unit, wherein the signal determining unit is used for determining a main noise signal at the current moment based on the type of a nearby vehicle and the speed of the nearby vehicle, and the nearby vehicle is a vehicle within a preset distance from the vehicle; predicting a main noise signal at a next time based on the main noise signal at the current time and a speed of the nearby vehicle;
An anti-noise signal determination module configured to determine an anti-noise signal for denoising the main noise signal based on the main noise signal determined by the main noise signal determination module; the anti-noise signal determination module includes: a path determining unit configured to determine a path by which the main noise signal reaches a position for emitting the anti-noise signal;
A signal acquisition unit for determining the anti-noise signal based on the path; determining a magnitude of the received main noise signal based on the path, calculating an anti-noise signal based on the main noise signal to cancel the main noise signal at the location;
And the denoising module is used for obtaining a denoised residual signal based on the anti-noise signal obtained by the anti-noise signal determining module and the main noise signal.
10. A noise reduction system, comprising: at least one information acquisition module provided inside and outside the vehicle, a sound source output module provided inside the vehicle, and the noise reduction device according to claim 9;
The information acquisition module is used for acquiring the running related information of the vehicle;
the noise reduction device is used for determining a main noise signal based on the driving related information acquired by the information acquisition module and determining an anti-noise signal based on the main noise signal; obtaining a denoised residual signal based on the anti-noise signal and the main noise signal;
The sound source output module is used for outputting the anti-noise signal obtained by the noise reduction device.
11. The system of claim 10, wherein the information acquisition module comprises at least one of: vehicle microphone, image acquisition equipment, infrared sensor.
12. An electronic device, the electronic device comprising:
A processor;
A memory for storing the processor-executable instructions;
the processor is configured to perform the noise reduction method according to any of the preceding claims 1-8.
13. A computer readable storage medium storing a computer program for performing the noise reduction method of any of the preceding claims 1-8.
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| CN114756565B (en) * | 2022-06-16 | 2022-09-20 | 中关村科学城城市大脑股份有限公司 | Map updating method and device, electronic equipment and computer readable medium |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH03203497A (en) * | 1989-12-29 | 1991-09-05 | Nissan Motor Co Ltd | Active type noise controller |
| EP1531605A1 (en) * | 2003-11-12 | 2005-05-18 | Harman/Becker Automotive Systems GmbH | Method and system for noise reduction of a sound signal |
| JP2007011124A (en) * | 2005-07-01 | 2007-01-18 | Yamaha Corp | Noise-removing device and program thereof |
| JP2009231928A (en) * | 2008-03-19 | 2009-10-08 | Alpine Electronics Inc | Sound improving device and sound improving method |
| CN104835490A (en) * | 2014-02-12 | 2015-08-12 | 本田技研工业株式会社 | Vehicle vibration and noise reduction device |
| CN106128449A (en) * | 2016-08-16 | 2016-11-16 | 青岛歌尔声学科技有限公司 | A kind of automobile active denoising method |
| CN206282607U (en) * | 2016-08-16 | 2017-06-27 | 青岛歌尔声学科技有限公司 | A kind of automobile active noise reduction system |
| CN107195294A (en) * | 2017-04-07 | 2017-09-22 | 吉利汽车研究院（宁波）有限公司 | A kind of active denoising method and device for vehicle |
| CN107218846A (en) * | 2017-06-30 | 2017-09-29 | 邢优胜 | A kind of driving of a tank room noise Active Control Method and system |
| CN107230472A (en) * | 2017-06-30 | 2017-10-03 | 邢优胜 | Noise initiative control method and system in a kind of helicopter cockpit |
| CN107240392A (en) * | 2017-06-30 | 2017-10-10 | 邢优胜 | A kind of armored vehicle cabin room noise Active Control Method and system |
| KR101814977B1 (en) * | 2016-09-06 | 2018-01-05 | 현대자동차주식회사 | Vehicle and controlling method thereof |
| WO2018158288A1 (en) * | 2017-03-02 | 2018-09-07 | Jaguar Land Rover Limited | System and method for noise cancellation |
| CN108711434A (en) * | 2018-04-04 | 2018-10-26 | 北京小米移动软件有限公司 | Vehicle noise-reduction method and device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP6001248B2 (en) * | 2011-09-20 | 2016-10-05 | トヨタ自動車株式会社 | Sound source detection device |
-
2019
- 2019-04-17 CN CN201910311716.6A patent/CN111833840B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH03203497A (en) * | 1989-12-29 | 1991-09-05 | Nissan Motor Co Ltd | Active type noise controller |
| EP1531605A1 (en) * | 2003-11-12 | 2005-05-18 | Harman/Becker Automotive Systems GmbH | Method and system for noise reduction of a sound signal |
| JP2007011124A (en) * | 2005-07-01 | 2007-01-18 | Yamaha Corp | Noise-removing device and program thereof |
| JP2009231928A (en) * | 2008-03-19 | 2009-10-08 | Alpine Electronics Inc | Sound improving device and sound improving method |
| CN104835490A (en) * | 2014-02-12 | 2015-08-12 | 本田技研工业株式会社 | Vehicle vibration and noise reduction device |
| CN206282607U (en) * | 2016-08-16 | 2017-06-27 | 青岛歌尔声学科技有限公司 | A kind of automobile active noise reduction system |
| CN106128449A (en) * | 2016-08-16 | 2016-11-16 | 青岛歌尔声学科技有限公司 | A kind of automobile active denoising method |
| KR101814977B1 (en) * | 2016-09-06 | 2018-01-05 | 현대자동차주식회사 | Vehicle and controlling method thereof |
| WO2018158288A1 (en) * | 2017-03-02 | 2018-09-07 | Jaguar Land Rover Limited | System and method for noise cancellation |
| CN107195294A (en) * | 2017-04-07 | 2017-09-22 | 吉利汽车研究院（宁波）有限公司 | A kind of active denoising method and device for vehicle |
| CN107218846A (en) * | 2017-06-30 | 2017-09-29 | 邢优胜 | A kind of driving of a tank room noise Active Control Method and system |
| CN107230472A (en) * | 2017-06-30 | 2017-10-03 | 邢优胜 | Noise initiative control method and system in a kind of helicopter cockpit |
| CN107240392A (en) * | 2017-06-30 | 2017-10-10 | 邢优胜 | A kind of armored vehicle cabin room noise Active Control Method and system |
| CN108711434A (en) * | 2018-04-04 | 2018-10-26 | 北京小米移动软件有限公司 | Vehicle noise-reduction method and device |
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|---|---|
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