Noise active control methods, devices, electronic equipment, media and products
By combining discrete Fourier transform and acoustic transfer function dictionary, the problem of high computational complexity in traditional NANC systems is solved, achieving improved noise reduction efficiency and reduced hardware costs. It is suitable for low-frequency line spectrum narrowband noise control in equipment such as automotive range extenders and engines.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-25
- Publication Date
- 2026-05-26
AI Technical Summary
Traditional NANC systems have high computational complexity when processing multiple reference signals and multiple channels, making it difficult to meet real-time noise reduction requirements, and increasing hardware costs and power consumption.
The coefficients of the Discrete Fourier Transform are used for scalar dot product operations to replace the traditional filter vector convolution calculation. The acoustic transfer function dictionary is combined to perform offline calculation and real-time update of filter parameters, thereby reducing system complexity.
It effectively reduces the computational complexity of the NANC system, improves noise reduction efficiency, reduces hardware resource requirements and power consumption, and adapts to multi-channel and multi-order noise control in vehicles.
Smart Images
Figure CN122090812A_ABST
Abstract
Description
Technical Field
[0001] The embodiments of the present invention relate to the field of signal processing technology, and in particular to a method, apparatus, electronic device, medium and product for active noise control. Background Technology
[0002] Active Noise Cancellation (ANC) is a technology that neutralizes ambient noise by generating inverse sound waves. This technology is widely used in various environments such as headphones, automobiles, and airplanes. In an ANC system, a reference microphone captures ambient noise signals, a processing chip analyzes this noise and generates corresponding inverse sound waves, secondary speakers are used to generate these inverse sound waves, and an error microphone is used to detect the difference between the actual generated inverse sound waves and the noise for further adjustment. Narrowband Active Noise Cancellation (NANC) mainly refers to generating a cancellation signal with the same amplitude but opposite phase to the noise based on a reference signal. This cancellation signal is then played through a speaker, thereby reducing narrowband linespectral noise.
[0003] Currently, in-vehicle NANC systems typically employ adaptive filtering-based schemes to control harmonic noise at different locations within the vehicle. The noise signal from the range extender is usually treated as multiple distinct reference signals, and these reference signals are denoised using adaptive algorithms. In traditional methods, the secondary path (representing the transfer function between the secondary speaker and the error microphone) is typically modeled as a Finite Impulse Response (FIR) filter vector. In this approach, the output signal of the secondary source is calculated by convolving it with the reference signals. These signals drive the door speakers, thus interfering with the original noise, ultimately resulting in residual noise at the error microphone.
[0004] Traditional methods suffer from the following drawbacks: Vector convolution calculations for filters are extremely time-consuming, especially in systems with multiple reference signals and multiple channels, where the computational load increases significantly. Furthermore, due to the high computational complexity, it is difficult to meet the requirements for fast response in real-time systems, particularly when range extender noise has multiple orders, further exacerbating the computational burden. Moreover, the large number of speakers and error channels places a significant computational load on the system, leading to increased hardware costs and power consumption. Therefore, reducing the complexity of NANC and improving noise reduction efficiency has become an urgent problem to be solved. Summary of the Invention
[0005] This invention provides a method, apparatus, electronic device, medium, and product for active noise control, in order to reduce the complexity of noise reduction and improve noise reduction efficiency.
[0006] In a first aspect, embodiments of this application provide an active noise control method, including:
[0007] For each channel, determine the coefficients of the corresponding Discrete Fourier Transform (DFT) for that channel, where each channel corresponds to a reference signal, a secondary loudspeaker, and an error microphone, the reference signal being a rotating component noise signal of a certain frequency, and the coefficients of the Discrete Fourier Transform being in the form of scalar dot products.
[0008] The filter parameters for each combination are determined based on the coefficients of the discrete Fourier transform of each channel, and each combination corresponds to a reference signal and a secondary loudspeaker, respectively.
[0009] Based on the filter parameters and the sine and cosine components of each reference signal, the output signal corresponding to each secondary loudspeaker is determined, and the output signal is used to control the operation of the corresponding secondary loudspeaker.
[0010] Secondly, embodiments of this application also provide an active noise control device, comprising:
[0011] The coefficient determination module is used to determine the coefficients of the corresponding discrete Fourier transform for each channel, wherein each channel corresponds to a reference signal, a secondary loudspeaker, and an error microphone, the reference signal is a rotating component noise signal of a certain frequency, and the coefficients of the discrete Fourier transform are in the form of scalar dot product.
[0012] The parameter determination module is used to determine the filter parameters corresponding to each combination based on the coefficients of the discrete Fourier transform of each channel. Each combination corresponds to a reference signal and a secondary loudspeaker, respectively.
[0013] The control module is used to determine the output signal corresponding to each of the secondary loudspeakers based on the parameters of each filter and the sine and cosine components of each reference signal. The output signal is used to control the operation of the corresponding secondary loudspeaker.
[0014] Thirdly, embodiments of this application provide an electronic device, including:
[0015] One or more processors;
[0016] Storage device for storing one or more programs;
[0017] When the one or more programs are executed by the one or more processors, the one or more processors implement the active noise control method as described in the first aspect.
[0018] Fourthly, embodiments of this application also provide a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the active noise control method as described in the first aspect.
[0019] Fifthly, embodiments of this application also provide a computer program product, including a computer program and / or instructions, which, when executed by a processor, implement the active noise control method as described in any of the above embodiments.
[0020] This application provides a method, apparatus, electronic device, medium, and product for active noise control. The active noise control method includes: for each channel, determining the coefficients of the corresponding Discrete Fourier Transform (DFT) for that channel, wherein each channel corresponds to a reference signal, a secondary loudspeaker, and an error microphone; the reference signal is a rotating component noise signal of a certain frequency; and the DFT coefficients are in the form of scalar dot products. Based on the DFT coefficients of each channel, determining filter parameters for each combination, each combination corresponding to a reference signal and a secondary loudspeaker. Based on the filter parameters and the sine and cosine components of each reference signal, determining the output signal corresponding to each secondary loudspeaker, the output signal being used to compensate for the rotating component noise signal. This technical solution uses DFT coefficients in the process of determining filter parameters, employing scalar dot products to avoid vector convolution calculations in the filter. Based on this, the output signal corresponding to the stimulation loudspeaker is determined according to the filter coefficients, controlling the corresponding secondary loudspeaker to operate, thereby compensating for the rotating component noise. This reduces the complexity of active noise control (NANC) and improves noise reduction efficiency. Attached Figure Description
[0021] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.
[0022] Figure 1 A schematic diagram illustrating an active noise control method provided in an embodiment of this application;
[0023] Figure 2 A flowchart of an active noise control method provided in an embodiment of this application;
[0024] Figure 3 A schematic diagram of a NANC process provided in an embodiment of this application;
[0025] Figure 4This is a schematic diagram of the structure of an active noise control device provided in an embodiment of this application;
[0026] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation
[0027] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the application and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present application, not the entire structure.
[0028] Before discussing the exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the steps as sequential processes, many of these steps can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the steps can be rearranged. The process can be terminated when its operation is complete, but may also have additional steps not included in the figures. The process can correspond to a method, function, procedure, subroutine, subroutine, etc.
[0029] It should be noted that the concepts of "first" and "second" mentioned in the embodiments of this application are only used to distinguish different devices, modules, units or other objects, and are not used to limit the order of functions performed by these devices, modules, units or other objects or their interdependencies.
[0030] Furthermore, the embodiments and features described in this application may be combined with each other, unless otherwise specified.
[0031] Figure 1 This is a schematic diagram illustrating an active noise control method provided in an embodiment of this application. Figure 1 As shown, a noise field to be controlled is called the primary sound field, its sound source is the primary noise source, the generated noise is the primary noise or primary sound wave, and the acoustic path of the primary noise is the primary path. The subsequently generated reverse sound wave used to cancel the primary noise can be called the secondary noise or secondary sound wave, forming a sound field called the secondary sound field, and the acoustic path of the secondary noise is the secondary path. The reverse sound wave can be played by a secondary loudspeaker, and an error microphone can be used to monitor the error between the primary and secondary sound waves and collect residual noise. Noise reduction can be achieved by utilizing the destructive interference of the primary and secondary sound waves.
[0032] Figure 2This is a flowchart illustrating an active noise control method provided in an embodiment of this application. This embodiment is applicable to handling noise from rotating components. Specifically, the active noise control method can be executed by an active noise control device, which can be implemented through software and / or hardware and integrated into an electronic device. Specifically, it can be integrated into an Electronic Control Unit (ECU), computing device, chip, host computer, ANC system processing chip or controller, or a controller inside a vehicle, etc.
[0033] like Figure 1 As shown, the method specifically includes the following steps:
[0034] S110. For each channel, determine the coefficients of the corresponding discrete Fourier transform of the channel, wherein each channel corresponds to a reference signal, a secondary loudspeaker, and an error microphone, the reference signal being a rotating component noise signal of a certain frequency, and the coefficients of the discrete Fourier transform being in the form of scalar dot products.
[0035] In this embodiment, a channel can be understood as a processing object consisting of a secondary speaker and an error microphone when processing a reference signal of a certain frequency. The reference signal can be understood as a rotating component noise signal. The rotating component can refer to electric vehicle parts and machinery that operate in a rotating manner, mainly referring to the range extender, but also to air conditioning units, fans, engines, or generators, etc. The noise of the rotating component is mainly due to the sound generated by the vibration and electromagnetic radiation of the internal electronic components. For example, if there are R reference signals, S secondary speakers, and M error microphones, then there are a total of R*S*M channels. Here, R can represent all possible frequencies, such as obtaining a frequency every 0.5Hz in the frequency range of 20Hz-130Hz.
[0036] Each channel corresponds to a coefficient of the Discrete Fourier Transform (DFT). Based on the DFT coefficients, the spectral components of the reference signal can be analyzed, and filters can be designed. In this embodiment, the DFT coefficients are in the form of scalar dot products, and NANC is performed using DFT coefficient expansion. This method abandons the traditional approach of calculating secondary paths based on vector convolution operations, thus resulting in lower computational complexity.
[0037] S120. Determine the filter parameters corresponding to each combination based on the coefficients of the discrete Fourier transform of each channel. Each combination corresponds to a reference signal and a secondary loudspeaker, respectively.
[0038] The filter is used to filter the reference signal to obtain the output signal of the secondary loudspeaker. The output signal can be used to cancel or compensate the R reference signals. The filter parameters for each secondary loudspeaker are determined based on the coefficients of the discrete Fourier transform of that secondary loudspeaker.
[0039] For example, with R reference signals, S secondary loudspeakers, and M error microphones, there are a total of R*S*M channels, each corresponding to one of the coefficients of an R*S*M discrete Fourier transform, resulting in R*S combinations. For each secondary loudspeaker, a corresponding output signal needs to be calculated using R filters (the filtering results of the R filters are accumulated along the dimension of the number of microphones (M)), resulting in a total of R*S filters and S output signals. Each output signal can be used to compensate for the R reference signals at the corresponding secondary loudspeaker.
[0040] S130. Based on the parameters of each filter and the sine and cosine components of each reference signal, determine the output signal corresponding to each secondary loudspeaker. The output signal is used to control the operation of the corresponding secondary loudspeaker.
[0041] For each secondary speaker, using the above filter parameters, R corresponding filters can be used to calculate a corresponding output signal by combining the sine and cosine components of each reference signal.
[0042] For example, for the s-th secondary speaker, the corresponding output signal y j (n) can be represented as:
[0043]
[0044] Where, x sin，r (n) represents the sinusoidal component of the r-th reference signal at time n, x cos，r (n) represents the cosine component of the r-th reference signal at time n, w cos，rs (n) and w sin，rs (n) represent the filter parameters, which can be determined based on the coefficients of the discrete Fourier transform.
[0045] Figure 3 This is a schematic diagram of a NANC process provided as an embodiment. (As shown...) Figure 3 As shown, for the channel corresponding to the s-th secondary speaker, the r-th reference signal, and the m-th error microphone, P represents the actual secondary path in the environment. sm (l) indicates the method adopted in the embodiments of this application, namely, the secondary path estimated by using DFT coefficient expansion, representing the sine and cosine components of the reference signal, respectively. cos，rs(n) and w sin，ts (n) represent the filter parameters. In this embodiment, the filter parameters are updated by combining the estimated secondary path with the truth component and cosine component of the reference signal and using the Least Mean Squares Algorithm (LMS). m (n) represents the residual error signal of the error microphone, d m (z) represents the raw noise signal at the error microphone, i.e., the raw noise that has not been processed by the algorithm.
[0046] The active noise control method of this embodiment can be widely used in automobile range extenders, engines, or large rotating equipment for active control of low-frequency line spectrum narrowband noise. Since the discrete Fourier transform coefficient expansion is used instead of traditional convolution calculation in the process of determining filter parameters, and the output signal corresponding to the secondary speaker is determined according to the filter coefficients to compensate for the noise of the range extender, the complexity of NANC is reduced and the noise reduction efficiency is improved.
[0047] In one embodiment, determining the coefficients of the corresponding discrete Fourier transform for each channel includes:
[0048] For each channel, the coefficients of the corresponding discrete Fourier transform are determined based on the angular frequency of the reference signal corresponding to that channel, and the cosine and sine responses of the secondary path corresponding to that channel relative to the reference signal.
[0049] In this embodiment, for the channels corresponding to the s-th secondary speaker, the r-th reference signal, and the m-th error microphone, the DFT coefficients can be determined by multiplying the sine and cosine function values of the angular frequency of the reference signal with the sine and cosine responses of the reference signal. Thus, the DFT expansion can be used to approximate the cosine and sine responses of the secondary path, reducing the complexity of NANC.
[0050] In one embodiment, the coefficients of the discrete Fourier transform corresponding to each channel include a first coefficient and a second coefficient;
[0051] For a channel, the first coefficient is the sum of the following two: the cosine component of the angular frequency of the reference signal corresponding to the channel and the cosine response of the secondary path corresponding to the channel at the corresponding frequency; the sine component of the angular frequency of the reference signal corresponding to the channel and the sine response of the secondary path corresponding to the channel at the corresponding frequency.
[0052] The second coefficient is the sum of the following two: the inverse of the cosine component of the angular frequency of the reference signal corresponding to the channel and the product of the sinusoidal response of the secondary path corresponding to the channel at the corresponding frequency; and the product of the sinusoidal component of the angular frequency of the reference signal corresponding to the channel and the cosine response of the secondary path corresponding to the channel at the corresponding frequency.
[0053] For example, for the channel corresponding to the s-th secondary speaker, the r-th reference signal, and the m-th error microphone, the first coefficient (denoted as h) cos，rsm (n) and the second coefficient (represented as h) sin，rsm (n) are respectively represented as:
[0054]
[0055]
[0056] Where, ω r Indicates the angular frequency of the reference signal. and Let cos(ω) represent the cosine and sine responses of the reference signal, respectively. r n) represents the cosine component of the angular frequency, -cos(ω r n) represents the negative of the cosine component of the angular frequency, sin(ω) r n) represents the sinusoidal component of the angular frequency, l represents the filter length or order of the secondary path, and P represents the secondary path. sm (l) was originally a vector with a length of L. In this embodiment, convolution operations are avoided when solving for the cosine and sine responses of the reference signal, effectively reducing the complexity of NANC.
[0057] Based on the above, the coefficients of the discrete Fourier transform are the result of scalar multiplication between the secondary path and the cosine and sine responses. Thus, in the real-time NANC process, the complexity of vector multiplication can be reduced to scalar dot product, thereby improving computational efficiency.
[0058] In one embodiment, before determining the coefficients of the corresponding discrete Fourier transform for the channel, the method further includes:
[0059] For each channel, calculate the cosine and sine responses of the secondary path corresponding to that channel relative to the reference signal; save the corresponding cosine and sine responses of each channel to the acoustic transfer function dictionary.
[0060] In this embodiment, the Acoustics Transfer Function Dictionary (ATFD) can be used to store the pre-calculated cosine and sine responses of different reference signals, or it can store the coefficients of the corresponding discrete Fourier transforms of different reference signals. Specifically, considering that the response of the secondary path at different frequencies is actually very stable, this part of the calculation can be performed offline. Therefore, an Acoustics Transfer Function Dictionary is constructed, that is, the cosine components of the secondary path at different frequencies are calculated offline in advance. Sine component α rsm and β rsm Save the data to a dictionary of transfer functions. Based on this, when cosine and sine responses are needed during real-time NANC, the pre-calculated and saved results can be directly read, avoiding redundant calculations.
[0061] In one embodiment, determining the coefficients of the corresponding discrete Fourier transform of a channel includes:
[0062] Read the corresponding cosine and sine responses for this channel from the acoustic transfer function dictionary;
[0063] The coefficients of the discrete Fourier transform of the corresponding channel are calculated based on the angular frequency of the reference signal corresponding to the channel, and the cosine and sine responses of the secondary path corresponding to the channel relative to the reference signal.
[0064] In this embodiment, when determining the DFT coefficients, the corresponding cosine and sine responses for each channel can be directly read from the ATFD, and the DFT coefficients for the corresponding channel can be calculated accordingly. That is, the read cosine and sine responses are substituted into the solution to obtain the DFT coefficients (h). cos，rsm (n) and h sin，rsm The formula (n) is used to quickly obtain the DFT coefficients. Based on this, redundant calculations can be avoided during real-time NANC, improving the real-time performance of the system and effectively reducing the complexity of the NANC system.
[0065] In one embodiment, the cosine and sinusoidal responses of different reference signals can be pre-calculated, and the DFT coefficients can be calculated by combining them with the angular frequency and stored in the acoustic transfer function dictionary. When actually using the coefficients of the discrete Fourier transform, they can be directly read from the ATFD. This can further reduce the computational load of the NANC process and improve the real-time performance of the system.
[0066] In one embodiment, filter parameters for each combination are determined based on the coefficients of the discrete Fourier transform of each channel, each combination corresponding to a reference signal and a secondary loudspeaker, including:
[0067] Based on the filter parameters from the previous time step, the residual error signals of each error microphone from the previous time step, and the coefficients of the discrete Fourier transform of each channel, determine the filter parameters corresponding to each combination at the current time step.
[0068] In this embodiment, the filter parameters can be updated using the residual error signals of each error microphone at historical time points and the coefficients of the discrete Fourier transform.
[0069] For example, for the s-th secondary loudspeaker, the r-th reference signal, and the m-th error microphone, the filter parameters at the current time include w cos，rs (n) and w sin，rs (n), the filter parameters at the current time include w cos，rs (n+1) and w sin，rs (n+1)
[0070] Based on the iterative formula of the adaptive filtering LMS algorithm, the update formula for the filter parameters can be obtained as follows:
[0071]
[0072]
[0073] Where, k cos，rsm (n) and h sin，rsm (n) are the coefficients of the discrete Fourier transform, This represents the residual error signal of the m-th error microphone at the previous moment. It is the residual error signal obtained after the sound wave acts on the m-th error microphone after passing through the secondary path and is superimposed with the original noise. μ is the update step size, which can be flexibly set according to actual needs.
[0074] In one embodiment, it further includes:
[0075] Engine speed information is obtained via the controller area network bus;
[0076] The base frequency is determined based on the engine speed information;
[0077] Each frequency of the range extender noise signal is determined based on the aforementioned base frequency.
[0078] In this embodiment, engine speed (Revolutions per Minute, RPM) information can be obtained through the Controller Area Network (CAN) bus, and the engine speed can be converted into the corresponding base frequency, denoted as F. In the case where it is necessary to control the noise of multiple orders of the range extender, the frequencies of multiple reference signals can be set according to the base frequency, such as F, 2F, 3F, etc.
[0079] The method described in this application addresses the problems of high computational complexity, insufficient real-time performance, and excessive system computational burden in NANC (Near-Nearest Noise Control). Targeting the narrowband noise characteristics of range extenders, a secondary path generation method based on Discrete Fourier Transform (DFT) is employed, where the DFT coefficients are in the form of scalar dot products. This avoids convolution operations in traditional methods, effectively reducing system complexity. Furthermore, by introducing an acoustic transfer function dictionary, the cosine and sine responses of the secondary path relative to the reference signal can be calculated offline and pre-stored in the dictionary. When solving for the DFT coefficients, each cosine and sine response can be directly read from the dictionary, eliminating the need for online real-time calculations. This further reduces the computational load of the NANC process, improving the system's real-time response capability while maintaining control effectiveness, and reducing hardware requirements and power consumption. This method is adaptable to the control requirements of multi-channel and multi-order noise within vehicles. In addition, this method reduces hardware resource requirements and lowers the power consumption of NANC, making it more suitable for active control of low-frequency line spectrum narrowband noise in automotive range extenders, engines, and large equipment.
[0080] Figure 4 This is a schematic diagram of a noise active control device provided in an embodiment of this application. The noise active control device provided in this embodiment includes:
[0081] The coefficient determination module 210 is used to determine the coefficients of the corresponding discrete Fourier transform for each channel, wherein each channel corresponds to a reference signal, a secondary speaker and an error microphone, the reference signal is a range extender noise signal of a certain frequency, and the coefficients of the discrete Fourier transform are in the form of scalar dot product.
[0082] The parameter determination module 220 is used to determine the filter parameters corresponding to each combination based on the coefficients of the discrete Fourier transform of each channel. Each combination corresponds to a reference signal and a secondary loudspeaker.
[0083] The control module 230 is used to determine the output signal corresponding to each of the secondary loudspeakers based on the parameters of each filter and the sine and cosine components of each reference signal. The output signal is used to control the operation of the corresponding secondary loudspeaker.
[0084] In one embodiment, the coefficient determination module 210 is specifically used for:
[0085] The coefficients of the discrete Fourier transform of the channel are determined based on the angular frequency of the reference signal corresponding to the channel, and the cosine and sine responses of the secondary path corresponding to the channel relative to the reference signal.
[0086] The secondary path is the acoustic transmission path between the secondary speaker and the error microphone corresponding to the channel.
[0087] In one embodiment, before determining the coefficients of the corresponding discrete Fourier transform of the channel, the device further includes:
[0088] The calculation module is used to calculate, for each of the channels, the cosine response and sine response of the secondary path corresponding to the channel relative to the reference signal;
[0089] Save the cosine and sine responses corresponding to each channel to the acoustic transfer function dictionary.
[0090] In one embodiment, the coefficient determination module 210 is specifically used for:
[0091] For each channel, the corresponding cosine and sine responses for that channel are read from the acoustic transfer function dictionary;
[0092] The coefficients of the discrete Fourier transform of the channel are calculated based on the angular frequency of the reference signal corresponding to the channel, as well as the cosine and sine responses corresponding to the channel.
[0093] In one embodiment, the parameter determination module 220 is specifically used to: determine the filter parameters corresponding to each combination at the current time based on the filter parameters of the previous time, the residual error signal of each error microphone at the previous time, and the coefficients of the discrete Fourier transform of each channel.
[0094] In one embodiment, the coefficients of the discrete Fourier transform corresponding to each channel include a first coefficient and a second coefficient;
[0095] The first coefficient is the sum of the following two: the cosine component of the angular frequency of the reference signal corresponding to the channel and the cosine response of the secondary path corresponding to the channel at the corresponding frequency; the sine component of the angular frequency of the reference signal corresponding to the channel and the sine response of the secondary path corresponding to the channel at the corresponding frequency.
[0096] The second coefficient is the sum of the following two: the negative of the cosine component of the angular frequency of the reference signal corresponding to the channel and the product of the sinusoidal response of the secondary path corresponding to the channel at the corresponding frequency; and the product of the sinusoidal component of the angular frequency of the reference signal corresponding to the channel and the cosine response of the secondary path corresponding to the channel at the corresponding frequency.
[0097] In one embodiment, the device further includes a frequency determination module, configured to:
[0098] Engine speed information is obtained via the controller area network bus;
[0099] The base frequency is determined based on the engine speed information;
[0100] Each frequency of the range extender noise signal is determined based on the aforementioned base frequency.
[0101] The noise active control device provided in this application embodiment can be used to execute the noise active control method provided in any of the above embodiments, and has corresponding functions and beneficial effects.
[0102] Figure 5 A schematic diagram of an electronic device 10 that can be used to implement embodiments of this application is shown. The electronic device 10 may be an ECU, a computing device, a chip, a host computer, a controller in a vehicle, or other devices that can be used to implement the active noise control method provided in any of the above embodiments.
[0103] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.
[0104] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks and wireless networks.
[0105] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above.
[0106] In some embodiments, the methods described above can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the methods described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the methods of any of the embodiments described above by any other suitable means (e.g., by means of firmware).
[0107] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or channels thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.
[0108] Computer programs used to implement the methods of this application may be written in any channel of one or more programming languages. These computer programs may be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.
[0109] In the context of this application, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable channel thereof. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable channel thereof.
[0110] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device 10, which includes: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device 10. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).
[0111] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any computing system that includes such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.
[0112] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.
[0113] This application also provides a computer program product, including a computer program and / or instructions, which, when executed by a processor, implement the active noise control method as described in any of the above embodiments.
[0114] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this application can be achieved, and this is not limited herein.
[0115] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, channels, sub-channels, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.
Claims
1. A noise signal control method, characterized in that, include: For each channel, the coefficients of the corresponding Discrete Fourier Transform are determined, wherein each channel corresponds to a reference signal, a secondary loudspeaker, and an error microphone, the reference signal being a rotating component noise signal of a certain frequency, and the coefficients of the Discrete Fourier Transform being in the form of scalar dot products; The filter parameters for each combination are determined based on the coefficients of the discrete Fourier transform of each channel, and each combination corresponds to a reference signal and a secondary loudspeaker, respectively. Based on the filter parameters and the sine and cosine components of each reference signal, the output signal corresponding to each secondary loudspeaker is determined, and the output signal is used to control the operation of the corresponding secondary loudspeaker.
2. The method according to claim 1, characterized in that, Determining the coefficients of the corresponding discrete Fourier transform of the channel includes: The coefficients of the discrete Fourier transform of the channel are determined based on the angular frequency of the reference signal corresponding to the channel, and the cosine and sine responses of the secondary path corresponding to the channel relative to the reference signal. The secondary path is the acoustic transmission path between the secondary speaker and the error microphone corresponding to the channel.
3. The method according to claim 1, characterized in that, Before determining the coefficients of the corresponding discrete Fourier transform of the channel, the process also includes: For each of the channels, calculate the cosine and sine responses of the secondary path corresponding to the channel relative to the reference signal; Save the corresponding cosine and sine responses of each channel to the acoustic transfer function dictionary.
4. The method according to claim 1, characterized in that, Determining the coefficients of the corresponding discrete Fourier transform of the channel includes: Read the corresponding cosine and sine responses of the channel from the acoustic transfer function dictionary; The coefficients of the discrete Fourier transform of the channel are calculated based on the angular frequency of the reference signal corresponding to the channel, as well as the cosine and sine responses of the channel.
5. The method according to claim 1, characterized in that, The filter parameters for each combination are determined based on the coefficients of the discrete Fourier transform of each channel, including: Based on the filter parameters of the previous time step, the residual error signals of each error microphone of the previous time step, and the coefficients of the discrete Fourier transform of each channel, determine the filter parameters corresponding to each combination at the current time step.
6. The method according to claim 1, characterized in that, The coefficients of the discrete Fourier transform corresponding to each channel include the first coefficient and the second coefficient; The first coefficient is the sum of the following two: the cosine component of the angular frequency of the reference signal corresponding to the channel and the cosine response of the secondary path corresponding to the channel at the corresponding frequency; the sine component of the angular frequency of the reference signal corresponding to the channel and the sine response of the secondary path corresponding to the channel at the corresponding frequency. The second coefficient is the sum of the following two: the negative of the cosine component of the angular frequency of the reference signal corresponding to the channel and the product of the sinusoidal response of the secondary path corresponding to the channel at the corresponding frequency; and the product of the sinusoidal component of the angular frequency of the reference signal corresponding to the channel and the cosine response of the secondary path corresponding to the channel at the corresponding frequency.
7. The method according to any one of claims 1-6, characterized in that, Also includes: Engine speed information is obtained via the controller area network bus; The base frequency is determined based on the engine speed information; Each frequency of the rotating component noise signal is determined based on the fundamental frequency.
8. A noise control device, characterized in that, include: The coefficient determination module is used to determine the coefficients of the corresponding discrete Fourier transform for each channel, wherein each channel corresponds to a reference signal, a secondary loudspeaker, and an error microphone, the reference signal is a rotating component noise signal of a certain frequency, and the coefficients of the discrete Fourier transform are in the form of scalar dot product. The parameter determination module is used to determine the filter parameters corresponding to each combination based on the coefficients of the discrete Fourier transform of each channel. Each combination corresponds to a reference signal and a secondary loudspeaker, respectively. The control module is used to determine the output signal corresponding to each of the secondary loudspeakers based on the parameters of each filter and the sine and cosine components of each reference signal. The output signal is used to control the operation of the corresponding secondary loudspeaker.
9. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor to enable the at least one processor to perform the noise control method as described in any one of claims 1-6.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the noise control method as described in any one of claims 1-7.
11. A computer program product, characterized in that, Includes a computer program / instruction that, when executed by a processor, implements the noise control method as described in any one of claims 1-7.