Noise elimination method and device, vehicle, electronic equipment and storage medium

Abstract

The invention provides a noise elimination method and device, a vehicle, electronic equipment and a storage medium, and relates to the technical field of sound processing, and the main technical scheme comprises the steps of obtaining working condition information of a target vehicle; matching from a preset filter library according to the working condition information to obtain a corresponding target noise reduction filter; wherein the preset filter library comprises noise reduction filters corresponding to different working condition information; and noise generated when the target vehicle is in the vehicle state corresponding to the working condition information is eliminated through the target noise reduction filter. Compared with the prior art, the embodiment of the invention has the advantages that the working condition information of the target vehicle is acquired, and the most suitable noise reduction filter under the working condition information is selected in real time based on the working condition information to perform active road noise elimination work, so that the noise reduction performance is ensured not to be lost, the computing power requirement of a digital signal processing chip is reduced, and the computing power resource is saved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of sound processing, and in particular to a noise elimination method and device, a vehicle, an electronic device, and a storage medium. Background Art

[0002] Currently, the main vehicle-mounted active road noise cancellation (RNC) solution adopts a feedforward active noise control (ANC) system solution. The feedforward ANC system directly obtains a noise reference signal by placing a reference microphone or non-acoustic sensor at the target noise location, and obtains the residual noise signal of the target noise through an error sensor. Both the residual noise signal and the noise reference signal are used as inputs to the controller, which generates and drives the speaker to emit a canceling sound source to cancel the noise and achieve road noise cancellation.

[0003] However, the active road noise cancellation method in the existing technology needs to use an adaptive algorithm to calculate the corresponding canceling sound source of each noise during the road noise cancellation process. The calculation amount is large and the computing power requirements of the digital signal processing chip are high, resulting in a waste of computing resources. Summary of the Invention

[0004] This disclosure provides a noise cancellation method and apparatus, vehicle, electronic device, and storage medium. Its primary purpose is to address the problem of existing active road noise cancellation methods, which require adaptive algorithms to calculate the corresponding canceling sound source for each noise. This computationally intensive process requires high computing power from digital signal processing chips, leading to a waste of computing resources.

[0005] According to a first aspect of the present disclosure, a noise cancellation method is provided, comprising:

[0006] Obtaining the operating condition information of the target vehicle;

[0007] According to the working condition information, matching is performed from a preset filter library to obtain a corresponding target noise reduction filter; wherein the preset filter library contains noise reduction filters corresponding to different working condition information;

[0008] The target noise reduction filter is used to eliminate noise generated when the target vehicle is in a vehicle state corresponding to the operating condition information.

[0009] Optionally, before obtaining the operating condition information of the target vehicle, the following steps are also included:

[0010] Acquiring a preset number of preset operating condition information, and acquiring noise information and acceleration signals generated when the target vehicle is in a vehicle state corresponding to each of the preset operating condition information, wherein the preset operating condition information is any custom-set operating condition information;

[0011] Obtaining a transfer function between each speaker in the target vehicle and each preset sound receiving device, wherein the preset sound receiving device is a device in the target vehicle for obtaining the noise information;

[0012] According to the transfer function, the noise information and the acceleration signal, a noise reduction filter corresponding to each preset working condition information is calculated, and the preset filter library is constructed according to the preset number of noise reduction filters.

[0013] Optionally, calculating the noise reduction filter corresponding to each preset operating condition information according to the transfer function, the noise information, and the acceleration signal includes:

[0014] Multiplying the acceleration signal by the transfer function to obtain a filtered reference signal;

[0015] Calculating an autocorrelation matrix of the filtered reference signal using a preset autocorrelation algorithm, and calculating a cross-correlation matrix between the filtered reference signal and the noise information using a preset cross-correlation algorithm;

[0016] The inverse matrix of the autocorrelation matrix is ​​multiplied by the cross-correlation matrix to obtain the noise reduction filter.

[0017] Optionally, matching from a preset filter library according to the operating condition information to obtain a corresponding target noise reduction filter includes:

[0018] Matching the operating condition information with the preset operating condition information from the preset filter library;

[0019] If the preset operating condition information including the operating condition information is matched, the noise reduction filter corresponding to the preset operating condition information including the operating condition information is used as the target noise reduction filter.

[0020] Optionally, obtaining the operating condition information of the target vehicle includes:

[0021] Acquire the road surface information of the target vehicle through a preset image acquisition device;

[0022] Obtaining the speed information of the target vehicle through a preset speed acquisition device;

[0023] The road surface information and the vehicle speed information are combined and processed to obtain the operating condition information.

[0024] Optionally, the acquiring of noise information and acceleration signals generated when the target vehicle is in a vehicle state corresponding to each of the preset operating condition information includes:

[0025] Acquiring, by the preset sound receiving device, noise information generated when the target vehicle is in a vehicle state corresponding to each of the preset operating condition information;

[0026] The acceleration signal generated when the target vehicle is in the vehicle state corresponding to each of the preset working condition information is obtained through the preset sensor equipment.

[0027] According to a second aspect of the present disclosure, there is provided a noise cancellation device, comprising:

[0028] A first acquiring unit, configured to acquire operating condition information of a target vehicle;

[0029] a matching unit, configured to perform matching from a preset filter library according to the operating condition information to obtain a corresponding target noise reduction filter; wherein the preset filter library contains noise reduction filters corresponding to different operating condition information;

[0030] The elimination unit is configured to eliminate noise generated when the target vehicle is in a vehicle state corresponding to the operating condition information by using the target noise reduction filter.

[0031] Optionally, the device further includes:

[0032] a second acquisition unit, configured to acquire a preset number of preset operating condition information, and acquire noise information and acceleration signals generated when the target vehicle is in a vehicle state corresponding to each of the preset operating condition information, wherein the preset operating condition information is any custom-set operating condition information;

[0033] The second acquisition unit is further configured to acquire a transfer function between each speaker in the target vehicle and each preset sound receiving device, wherein the preset sound receiving device is a device in the target vehicle for acquiring the noise information;

[0034] a calculation unit, configured to calculate a noise reduction filter corresponding to each of the preset operating condition information according to the transfer function, the noise information, and the acceleration signal;

[0035] A construction unit is configured to construct the preset filter library according to the preset number of noise reduction filters.

[0036] Optionally, the computing unit is further configured to:

[0037] Multiplying the acceleration signal by the transfer function to obtain a filtered reference signal;

[0038] Calculating an autocorrelation matrix of the filtered reference signal using a preset autocorrelation algorithm, and calculating a cross-correlation matrix between the filtered reference signal and the noise information using a preset cross-correlation algorithm;

[0039] The inverse matrix of the autocorrelation matrix is ​​multiplied by the cross-correlation matrix to obtain the noise reduction filter.

[0040] Optionally, the matching unit is further configured to:

[0041] Matching the operating condition information with the preset operating condition information from the preset filter library;

[0042] When the preset operating condition information including the operating condition information is matched, the noise reduction filter corresponding to the preset operating condition information including the operating condition information is used as the target noise reduction filter.

[0043] Optionally, the first acquiring unit includes:

[0044] An acquisition module, configured to acquire road surface information on which the target vehicle is located through a preset image acquisition device;

[0045] The acquisition module is further configured to acquire the speed information of the target vehicle through a preset speed acquisition device;

[0046] The merging module is used to merge the road surface information and the vehicle speed information to obtain the working condition information.

[0047] Optionally, the second acquiring unit is further configured to:

[0048] Acquiring, by the preset sound receiving device, noise information generated when the target vehicle is in a vehicle state corresponding to each of the preset operating condition information;

[0049] The acceleration signal generated when the target vehicle is in the vehicle state corresponding to each of the preset working condition information is obtained through the preset sensor equipment.

[0050] According to a third aspect of the present disclosure, a vehicle is provided, wherein the vehicle includes the noise elimination device according to the second aspect of the present disclosure.

[0051] According to a fourth aspect of the present disclosure, there is provided an electronic device, including:

[0052] at least one processor; and

[0053] a memory communicatively connected to the at least one processor; wherein,

[0054] The memory stores instructions that can be executed by the at least one processor. The instructions are executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect.

[0055] According to a fifth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0056] According to a sixth aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method as described in the first aspect above.

[0057] The present disclosure provides a noise cancellation method and apparatus, vehicle, electronic device, and storage medium. The method obtains operating condition information of a target vehicle; matches a preset filter library based on the operating condition information to obtain a corresponding target noise reduction filter; wherein the preset filter library contains noise reduction filters corresponding to different operating condition information; and uses the target noise reduction filter to eliminate noise generated when the target vehicle is in the vehicle state corresponding to the operating condition information. Compared to related technologies, the present disclosure embodiment obtains the operating condition information of the target vehicle and, based on the operating condition information, selects the most appropriate noise reduction filter for this operating condition in real time to perform active road noise cancellation. This ensures that noise reduction performance is not compromised while reducing the computing power requirements of the digital signal processing chip, thus conserving computing resources.

[0058] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] The accompanying drawings are provided to facilitate a better understanding of the present invention and do not constitute a limitation of the present disclosure.

[0060] Figure 1 A flowchart of a noise elimination method provided by an embodiment of the present disclosure;

[0061] Figure 2 A schematic diagram of the principle of a noise elimination method provided by an embodiment of the present disclosure;

[0062] Figure 3 A schematic flow chart of a method for constructing a preset filter library provided in an embodiment of the present disclosure;

[0063] Figure 4 A schematic diagram of the calculation principle of a noise reduction filter provided in an embodiment of the present disclosure;

[0064] Figure 5 A schematic structural diagram of a noise elimination device provided by an embodiment of the present disclosure;

[0065] Figure 6 A schematic structural diagram of another noise elimination device provided by an embodiment of the present disclosure;

[0066] Figure 7 A schematic block diagram of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0067] The following description of exemplary embodiments of the present disclosure is made in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding. These details should be considered as merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0068] The following describes a method and apparatus for noise cancellation, a vehicle, an electronic device, and a storage medium according to embodiments of the present disclosure with reference to the accompanying drawings.

[0069] Figure 1 A flowchart of a noise elimination method provided by an embodiment of the present disclosure is provided.

[0070] like Figure 1 As shown, the method comprises the following steps:

[0071] Step 101: Obtain operating condition information of a target vehicle.

[0072] In the embodiment of the present disclosure, the operating condition information includes but is not limited to: road surface information on which the target vehicle is located, vehicle speed information of the target vehicle, etc. The road surface information includes but is not limited to: cement road, asphalt road, etc. The method of obtaining the road surface information includes but is not limited to: obtaining it by using an external camera for recognition, etc. Specifically, the embodiment of the present disclosure does not impose any restrictions.

[0073] The working condition information can be obtained by adding the road surface information to the vehicle speed information. For example, the working condition information is: cement road + vehicle speed is 70km / h, etc. Specifically, the embodiment of the present disclosure does not limit the format of the working condition information.

[0074] Step 102 : Matching is performed from a preset filter library according to the operating condition information to obtain a corresponding target noise reduction filter; wherein the preset filter library contains noise reduction filters corresponding to different operating condition information.

[0075] In the embodiment of the present disclosure, the preset filter library is a pre-configured database containing noise reduction filters corresponding to a variety of different operating conditions. The noise reduction filter is a digital signal processing technology used to reduce or eliminate noise signals, thereby improving the quality of the original signal. The noise reduction filter corresponding to the operating condition information, namely the target noise reduction filter, can better eliminate the noise generated when the target vehicle is in the operating condition information.

[0076] Step 103 : Eliminate noise generated when the target vehicle is in a vehicle state corresponding to the operating condition information by using the target noise reduction filter.

[0077] In the embodiment of the present disclosure, the noise generated by the target vehicle can be effectively eliminated by using a noise reduction algorithm in the target noise reduction filter. The types of the target noise reduction filter include, but are not limited to, mean filtering, median filtering, Gaussian filtering, and Wiener filtering. Specifically, the embodiment of the present disclosure does not limit the type of the target noise reduction filter.

[0078] In order to facilitate understanding of the implementation process of the embodiment of the present disclosure, the embodiment of the present disclosure provides a principle schematic diagram of a noise elimination method, as shown in FIG. Figure 2 As shown, Figure 2 The working condition 1 filter W ... working condition N filter W are noise reduction filters stored in the preset filter library; Figure 2 The filter selector according to the real-time parking space road condition + vehicle speed is used to match from the preset filter library according to the working condition information to obtain the corresponding target noise reduction filter; Figure 2 The filter W in the RNC system is the target noise reduction filter.

[0079] The noise cancellation method provided by the present disclosure obtains operating condition information of a target vehicle; matches a preset filter library based on the operating condition information to obtain a corresponding target noise reduction filter; wherein the preset filter library contains noise reduction filters corresponding to different operating condition information; and uses the target noise reduction filter to eliminate noise generated when the target vehicle is in the vehicle state corresponding to the operating condition information. Compared with related technologies, the present embodiment obtains the operating condition information of the target vehicle and, based on the operating condition information, selects the most appropriate noise reduction filter for this operating condition in real time to perform active road noise cancellation. This ensures that noise reduction performance is not compromised while reducing the computing power requirements of the digital signal processing chip, thus saving computing resources.

[0080] In one possible implementation of the embodiment of the present disclosure, in order to obtain the target noise reduction filter to eliminate the noise generated by the target vehicle, it is necessary to calculate a preset number of noise reduction filters in advance according to the different working condition information of the target vehicle, and construct the preset filter library. Therefore, in order to obtain the target noise reduction filter to eliminate the noise generated when the target vehicle is in the working condition information state, the embodiment of the present disclosure provides a flow chart of a method for constructing a preset filter library, as shown in FIG. Figure 3 As shown, including:

[0081] Step 301: Obtain a preset number of preset operating condition information, and obtain noise information and acceleration signals generated when the target vehicle is in the vehicle state corresponding to each preset operating condition information. The preset operating condition information is any custom set operating condition information.

[0082] In an embodiment of the present disclosure, the preset number is a number value of a custom setting, for example: 100, 200, etc., and the preset operating condition information is any operating condition information of a custom setting, wherein the vehicle speed information in the preset operating condition information is interval information, for example: cement road + vehicle speed is 70-80km / h, asphalt road + vehicle speed is 90-100km / h, etc. Specifically, the embodiment of the present disclosure does not limit the preset number and the preset operating condition information.

[0083] The noise information and the acceleration signal are obtained by recording through the sound receiving equipment and sensors pre-configured in the target vehicle. For example, when the target vehicle is in any preset working condition information state, the noise d(1), ..., d(M) is recorded by the M microphones configured in the target vehicle, and the acceleration signals r(1), ..., r(R) are recorded by the R acceleration sensors configured in the target vehicle. Specifically, the number of noises and acceleration signals obtained when the target vehicle is in each preset working condition information state depends on actual conditions and is not limited in the embodiments of the present disclosure.

[0084] Step 302 : Acquire a transfer function between each speaker in the target vehicle and each preset sound receiving device, where the preset sound receiving device is a device in the target vehicle used to acquire the noise information.

[0085] In the embodiment of the present disclosure, since the noise is canceled by playing the sound source through the speaker, when calculating the noise reduction filter, it is necessary to determine the transfer function between the speaker and the preset sound receiving device to accurately calculate the noise reduction filter, wherein the preset sound receiving device is a custom-set device, such as a microphone, etc. The position of the preset sound receiving device in the target vehicle can be custom-configured, and the embodiment of the present disclosure does not limit it.

[0086] It should be noted that the transfer function is a transfer function between each speaker in the target vehicle and each preset radio device. For example, if there are S speakers and M preset radio devices in the target vehicle, the transfer function is Sec(M,S).

[0087] Step 303 : Calculate the noise reduction filter corresponding to each of the preset working condition information according to the transfer function, the noise information, and the acceleration signal, and construct the preset filter library according to the preset number of the noise reduction filters.

[0088] In the embodiment of the present disclosure, when calculating the noise reduction filter, the noise reduction filter corresponding to the target vehicle when it is in each of the preset operating condition information states is calculated to obtain the preset number of noise reduction filters. The preset number of noise reduction filters are grouped together to construct the preset filter library.

[0089] In one possible implementation of the embodiment of the present disclosure, as a refinement of the above-mentioned step 303, when calculating the noise reduction filter corresponding to each of the preset operating condition information, it can also be implemented by, but not limited to, the following method: multiplying the acceleration signal by the transfer function to obtain a filter reference signal; calculating the autocorrelation matrix of the filter reference signal by a preset autocorrelation algorithm, and calculating the cross-correlation matrix between the filter reference signal and the noise information by a preset cross-correlation algorithm; multiplying the inverse matrix of the autocorrelation matrix by the cross-correlation matrix to obtain the noise reduction filter.

[0090] In the embodiment of the present disclosure, the preset autocorrelation algorithm and the preset cross-correlation algorithm are custom-set algorithms, which can generate corresponding autocorrelation matrices and cross-correlation matrices. Specifically, the embodiment of the present disclosure does not limit the preset autocorrelation algorithm and the preset cross-correlation algorithm.

[0091] Regarding the calculation process of the noise reduction filter, the embodiment of the present disclosure provides a schematic diagram of the calculation principle of the noise reduction filter, such as Figure 4 shown.

[0092] At the same time, in order to facilitate understanding of the implementation process of the embodiment of the present disclosure, an example is provided for illustration: taking the target vehicle in any preset working condition information state as an example, if the transfer function between each speaker and each microphone in the target vehicle is Sec(M, S), the noise d(1), ..., d(M) recorded by the M microphones configured in the target vehicle, and the acceleration signals r(1), ..., r(R) recorded by the R acceleration sensors configured in the target vehicle, then when calculating the filtered reference signal, the following formula (1) may be used for calculation:

[0093]

[0094] Among them, x is the filtering reference signal, sec is the transfer function, and r is the acceleration signal. When calculating the filtering reference signal, R acceleration signals are merged and then calculated with the transfer function to obtain the filtering reference signal.

[0095] When calculating the autocorrelation matrix, the following formula (2) may be used but is not limited thereto:

[0096]

[0097] Among them, R xx is the autocorrelation matrix.

[0098] When calculating the cross-correlation matrix, the following formula (3) may be used but is not limited thereto:

[0099]

[0100] Among them, R dx is the mutual correlation matrix, x is the filtered reference signal, and d is the noise information. When calculating the mutual correlation matrix, M noise information will be calculated simultaneously with the filtered reference signal to obtain the mutual correlation matrix.

[0101] When calculating the noise reduction filter, the calculation may be performed using, but not limited to, formula (4):

[0102]

[0103] Wherein, w is the noise reduction filter, is the inverse matrix of the autocorrelation matrix.

[0104] In one possible implementation method of the embodiment of the present disclosure, in order to accurately match the corresponding target noise reduction filter according to the operating condition information, it can also be implemented by but not limited to the following method: matching the operating condition information with the preset operating condition information from the preset filter library; if the preset operating condition information containing the operating condition information is matched, the noise reduction filter corresponding to the preset operating condition information containing the operating condition information is used as the target noise reduction filter.

[0105] In the embodiment of the present disclosure, since the vehicle speed information in the preset operating condition information is interval information, the corresponding target noise reduction filter can be determined by matching the preset operating condition information containing the operating condition information. For example, the operating condition information is cement road + vehicle speed is 70 km / h. When the preset operating condition information with the content of cement road + vehicle speed of 70-80 km / h is matched, the noise reduction filter corresponding to the preset operating condition information with the content of cement road + vehicle speed of 70-80 km / h can be used as the target noise reduction filter.

[0106] In one possible implementation of the embodiment of the present disclosure, since the operating condition information is mainly determined by the road surface information (cement road, asphalt road, etc.) on which the target vehicle is traveling and the vehicle speed information, when obtaining the operating condition information, it can also be implemented by, but not limited to, the following methods: obtaining the road surface information on which the target vehicle is located through a preset image acquisition device; obtaining the vehicle speed information of the target vehicle through a preset speed acquisition device; and merging the road surface information and the vehicle speed information to obtain the operating condition information.

[0107] In the embodiment of the present disclosure, the preset image acquisition device is a custom-selected device, such as an external vehicle camera, etc., and the preset speed acquisition device is a custom-selected device, such as a vehicle's own speed sensor, etc. Specifically, the embodiment of the present disclosure does not limit the preset image acquisition device and the preset speed acquisition device.

[0108] In one possible implementation of the embodiment of the present disclosure, when acquiring noise information and acceleration signals, in order to obtain accurate and sufficient noise information and acceleration signals, the following method may also be adopted but is not limited to: obtaining, through the preset sound receiving device, the noise information generated when the target vehicle is in the vehicle state corresponding to each of the preset operating condition information; and obtaining, through the preset sensor device, the acceleration signal generated when the target vehicle is in the vehicle state corresponding to each of the preset operating condition information.

[0109] In an embodiment of the present disclosure, when the target vehicle is in a vehicle state corresponding to each of the preset operating condition information, multiple noise information will be obtained through multiple preset sound receiving devices, that is, each vehicle state corresponds to multiple noise information, wherein the number of noise information corresponding to each vehicle state is the same as the number of the preset sound receiving devices. Similarly, when the target vehicle is in a vehicle state corresponding to each of the preset operating condition information, multiple acceleration signals will be obtained through multiple preset sensor devices, that is, each vehicle state corresponds to multiple acceleration signals, wherein the number of acceleration signals corresponding to each vehicle state is the same as the number of the preset sensor devices.

[0110] In summary, the embodiments of the present disclosure can achieve the following effects:

[0111] The disclosed embodiment obtains the operating condition information of the target vehicle and, based on the operating condition information, selects in real time the most appropriate noise reduction filter under this operating condition information to perform active road noise cancellation. This not only ensures that the noise reduction performance is not lost, but also reduces the computing power requirements of the digital signal processing chip, thereby saving computing power resources.

[0112] Corresponding to the above-mentioned noise elimination method, the present invention also provides a noise elimination device. Since the device embodiment of the present invention corresponds to the above-mentioned method embodiment, details not disclosed in the device embodiment can be referred to the above-mentioned method embodiment and will not be repeated in this invention.

[0113] Figure 5 A schematic diagram of a noise elimination device according to an embodiment of the present disclosure is shown in FIG. Figure 5 As shown, including:

[0114] A first acquiring unit 51 is configured to acquire operating condition information of a target vehicle;

[0115] a matching unit 52 for matching a preset filter library according to the operating condition information to obtain a corresponding target noise reduction filter; wherein the preset filter library contains noise reduction filters corresponding to different operating condition information;

[0116] The elimination unit 53 is configured to eliminate the noise generated when the target vehicle is in the vehicle state corresponding to the operating condition information by using the target noise reduction filter.

[0117] The noise cancellation device provided in the present disclosure obtains operating condition information of a target vehicle; matches the operating condition information from a preset filter library to obtain a corresponding target noise reduction filter; wherein the preset filter library contains noise reduction filters corresponding to different operating condition information; and uses the target noise reduction filter to eliminate noise generated when the target vehicle is in the vehicle state corresponding to the operating condition information. Compared with related technologies, the embodiments of the present disclosure obtain the operating condition information of the target vehicle and, based on the operating condition information, select the most appropriate noise reduction filter for this operating condition in real time to perform active road noise cancellation. This ensures that noise reduction performance is not compromised while reducing the computing power requirements of the digital signal processing chip, thus saving computing resources.

[0118] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 6 As shown, the device also includes:

[0119] A second acquisition unit 54 is configured to acquire a preset number of preset operating condition information, and acquire noise information and acceleration signals generated when the target vehicle is in a vehicle state corresponding to each of the preset operating condition information, wherein the preset operating condition information is any custom-set operating condition information;

[0120] The second acquisition unit 54 is further configured to acquire a transfer function between each speaker in the target vehicle and each preset sound receiving device, where the preset sound receiving device is a device in the target vehicle used to acquire the noise information;

[0121] a calculation unit 55, configured to calculate a noise reduction filter corresponding to each of the preset operating condition information according to the transfer function, the noise information, and the acceleration signal;

[0122] The constructing unit 56 is configured to construct the preset filter library according to the preset number of noise reduction filters.

[0123] Furthermore, in a possible implementation of the embodiment of the present disclosure, the calculation unit 55 is further configured to:

[0124] Multiplying the acceleration signal by the transfer function to obtain a filtered reference signal;

[0125] Calculating an autocorrelation matrix of the filtered reference signal using a preset autocorrelation algorithm, and calculating a cross-correlation matrix between the filtered reference signal and the noise information using a preset cross-correlation algorithm;

[0126] The inverse matrix of the autocorrelation matrix is ​​multiplied by the cross-correlation matrix to obtain the noise reduction filter.

[0127] Furthermore, in a possible implementation of the embodiment of the present disclosure, the matching unit 52 is further configured to:

[0128] Matching the operating condition information with the preset operating condition information from the preset filter library;

[0129] When the preset operating condition information including the operating condition information is matched, the noise reduction filter corresponding to the preset operating condition information including the operating condition information is used as the target noise reduction filter.

[0130] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 6 As shown, the first acquiring unit 51 includes:

[0131] An acquisition module 511 is configured to acquire road surface information on which the target vehicle is located through a preset image acquisition device;

[0132] The acquisition module 511 is further configured to acquire the speed information of the target vehicle through a preset speed acquisition device;

[0133] The merging module 512 is configured to merge the road surface information and the vehicle speed information to obtain the operating condition information.

[0134] Furthermore, in a possible implementation of the embodiment of the present disclosure, the second acquiring unit 54 is further configured to:

[0135] Acquiring, by the preset sound receiving device, noise information generated when the target vehicle is in a vehicle state corresponding to each of the preset operating condition information;

[0136] The acceleration signal generated when the target vehicle is in the vehicle state corresponding to each of the preset working condition information is obtained through the preset sensor equipment.

[0137] In an embodiment of the present disclosure, a vehicle is further provided, wherein the vehicle is equipped with a noise cancellation device.

[0138] It should be noted that the above explanation of the method embodiment is also applicable to the device of the embodiment of the present disclosure, and the principles are the same, which is no longer limited in the embodiment of the present disclosure.

[0139] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0140] Figure 7A schematic block diagram of an example electronic device 700 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0141] like Figure 7 As shown, the device 700 includes a computing unit 701, which can perform various appropriate actions and processes according to a computer program stored in a ROM (Read-Only Memory) 702 or a computer program loaded from a storage unit 708 into a RAM (Random Access Memory) 703. Various programs and data required for the operation of the device 700 can also be stored in the RAM 703. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An I / O (Input / Output) interface 705 is also connected to the bus 704.

[0142] Various components in device 700 are connected to I / O interface 705, including an input unit 706, such as a keyboard, mouse, etc.; an output unit 707, such as various types of displays, speakers, etc.; a storage unit 708, such as a magnetic disk, optical disk, etc.; and a communication unit 709, such as a network card, modem, wireless communication transceiver, etc. The communication unit 709 allows device 700 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0143] The computing unit 701 can be various general-purpose and / or specialized processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a CPU (Central Processing Unit), a GPU (Graphic Processing Unit), various specialized AI (Artificial Intelligence) computing chips, various computing units that run machine learning model algorithms, a DSP (Digital Signal Processor), and any suitable processor, controller, microcontroller, etc. The computing unit 701 performs the various methods and processes described above, such as the noise cancellation method. For example, in some embodiments, the noise cancellation method can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 708. In some embodiments, part or all of the computer program can be loaded and / or installed on the device 700 via the ROM 702 and / or the communication unit 709. When the computer program is loaded into the RAM 703 and executed by the computing unit 701, one or more steps of the method described above can be performed. Alternatively, in other embodiments, the computing unit 701 may be configured to perform the aforementioned noise elimination method in any other appropriate manner (for example, by means of firmware).

[0144] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application Specific Standard Products), SOCs (System on Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0145] The program code for implementing the method of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0146] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, RAM, ROM, EPROM (Electrically Programmable Read-Only-Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0147] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: 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 can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the 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 acoustic input, voice input, or tactile input).

[0148] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: LAN (Local Area Network), WAN (Wide Area Network), the Internet, and blockchain networks.

[0149] A computer system may include a client and a server. The client and server are generally remote from each other and typically interact via a communication network. This client-server relationship is established by computer programs running on the respective computers, establishing a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host, a host product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosts and VPS services ("Virtual Private Servers" or simply "VPS"). The server may also be a server in a distributed system or a server integrated with blockchain.

[0150] It's important to note that artificial intelligence (AI) is the study of how computers can simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). This encompasses both hardware and software technologies. AI hardware technologies generally include sensors, specialized AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily encompass computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graphs.

[0151] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved. This is not limited herein.

[0152] The above specific embodiments do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the scope of protection of this disclosure.

Claims

1. A noise elimination method, characterized in that: include: Obtaining the operating condition information of the target vehicle; According to the working condition information, matching is performed from a preset filter library to obtain a corresponding target noise reduction filter; wherein the preset filter library contains noise reduction filters corresponding to different working condition information; The target noise reduction filter is used to eliminate noise generated when the target vehicle is in a vehicle state corresponding to the operating condition information.

2. The method according to claim 1, characterized in that Before obtaining the operating condition information of the target vehicle, the following steps are also included: Acquiring a preset number of preset operating condition information, and acquiring noise information and acceleration signals generated when the target vehicle is in a vehicle state corresponding to each of the preset operating condition information, wherein the preset operating condition information is any custom-set operating condition information; Obtaining a transfer function between each speaker in the target vehicle and each preset sound receiving device, wherein the preset sound receiving device is a device in the target vehicle for obtaining the noise information; According to the transfer function, the noise information and the acceleration signal, a noise reduction filter corresponding to each preset working condition information is calculated, and the preset filter library is constructed according to the preset number of noise reduction filters.

3. The method according to claim 2, characterized in that Calculating the noise reduction filter corresponding to each preset working condition information according to the transfer function, the noise information, and the acceleration signal includes: Multiplying the acceleration signal by the transfer function to obtain a filtered reference signal; Calculating an autocorrelation matrix of the filtered reference signal using a preset autocorrelation algorithm, and calculating a cross-correlation matrix between the filtered reference signal and the noise information using a preset cross-correlation algorithm; The inverse matrix of the autocorrelation matrix is ​​multiplied by the cross-correlation matrix to obtain the noise reduction filter.

4. The method according to claim 2, characterized in that The matching from a preset filter library according to the working condition information to obtain a corresponding target noise reduction filter includes: Matching the operating condition information with the preset operating condition information from the preset filter library; If the preset operating condition information including the operating condition information is matched, the noise reduction filter corresponding to the preset operating condition information including the operating condition information is used as the target noise reduction filter.

5. The method according to claim 1, wherein The obtaining of the operating condition information of the target vehicle includes: Acquire the road surface information of the target vehicle through a preset image acquisition device; Obtaining the speed information of the target vehicle through a preset speed acquisition device; The road surface information and the vehicle speed information are combined and processed to obtain the operating condition information.

6. The method according to claim 2, characterized in that The acquiring of the noise information and acceleration signal generated when the target vehicle is in the vehicle state corresponding to each of the preset working condition information comprises: Acquiring, by the preset sound receiving device, noise information generated when the target vehicle is in a vehicle state corresponding to each of the preset operating condition information; The acceleration signal generated when the target vehicle is in the vehicle state corresponding to each of the preset working condition information is obtained through the preset sensor equipment.

7. A noise elimination device, characterized in that: include: A first acquiring unit, configured to acquire operating condition information of a target vehicle; a matching unit, configured to perform matching from a preset filter library according to the operating condition information to obtain a corresponding target noise reduction filter; wherein the preset filter library contains noise reduction filters corresponding to different operating condition information; The elimination unit is configured to eliminate noise generated when the target vehicle is in a vehicle state corresponding to the operating condition information by using the target noise reduction filter.

8. A vehicle, characterized in that: The vehicle includes the noise cancellation device according to claim 7.

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 instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 6.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 6.

Images