Method and device for determining noise order, electronic device, and storage medium
By performing human ear correction on the reference noise time domain data of engine noise, obtaining the noise audio domain data and determining the hit frequency matrix, the problem of low noise positioning efficiency in the prior art is solved, and a higher noise positioning accuracy is achieved.
Patent Information
- Application Number
- CN202410116120.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-01-26
- Publication Date
- 2025-05-06
- Estimated Expiration
- 2044-01-26
AI Technical Summary
In the prior art, it is less efficient to distinguish the source of noise through the human ear, and it is difficult to accurately locate the parts that generate noise, which affects the user's experience of use.
By obtaining the reference noise time domain data of engine noise, performing human ear correction, obtaining human ear time domain noise data, and then obtaining the strike frequency matrix based on the human ear noise audio domain data, and finally determining the noise order.
It improves the accuracy of engine noise positioning, can more accurately determine the parts that produce noise, and reduces the inefficiency of the human ear to distinguish the noise source.
Smart Images
Figure CN118067402B_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of automobile noise processing, and in particular to a method and device, electronic equipment, and storage medium for determining noise order. Background Art
[0002] At present, due to the working characteristics of the fuel engine, that is, the operation of the fuel engine will make the parts related to the work of the fuel engine, such as ignition, fuel injection, valves and camshafts, run at angles proportional to the angle of rotation of the fuel engine. For example, when the fuel engine is a 4-cylinder engine, the fuel engine runs 360 degrees in one circle, and the camshaft runs 0.5 circles and 180 degrees. Therefore, during the operation of the engine, a rhythmic clapping noise that can be perceived in the car will be generated, and the clapping noise is composed of one or more noises of different orders. Since the clapping noise can be perceived by the human ear, it will affect the user's experience. Therefore, it is necessary to locate the parts that generate noise in order to facilitate the maintenance of the vehicle and reduce the generation of clapping noise.
[0003] Currently, related technologies all use human ears to identify the source of noise, which is inefficient. Summary of the invention
[0004] To solve the above technical problems, the embodiments of the present application provide a method and device, an electronic device, and a storage medium for determining noise order, so as to improve the accuracy of engine noise positioning.
[0005] According to one aspect of an embodiment of the present application, a method for determining a noise order is provided, including: obtaining reference noise time domain data of engine noise; performing human ear correction on the reference noise time domain data to obtain human ear time domain noise data; obtaining human ear noise frequency domain data corresponding to the engine noise based on the human ear time domain noise data; obtaining a clap frequency matrix corresponding to the frequency of the engine noise based on the human ear noise frequency domain data; and obtaining a noise order corresponding to the engine noise based on the clap frequency matrix.
[0006] According to one aspect of an embodiment of the present application, a device for determining a noise order is provided, comprising: a reference noise time domain data acquisition module, configured to acquire reference noise time domain data of an engine noise; a human ear time domain noise data acquisition module, configured to perform human ear correction on the reference noise time domain data to obtain human ear time domain noise data; a frequency domain data acquisition module, configured to acquire human ear noise frequency domain data corresponding to the engine noise based on the human ear time domain noise data; a matrix acquisition module, configured to acquire a clap frequency matrix corresponding to the frequency of the engine noise based on the human ear noise frequency domain data; and an order acquisition module, configured to acquire the noise order corresponding to the engine noise based on the clap frequency matrix.
[0007] According to one aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the electronic device implements the method for determining noise order as described above.
[0008] According to one aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which computer-readable instructions are stored. When the computer-readable instructions are executed by a processor of a computer, the computer executes the method for determining noise order as described above.
[0009] In the technical solution provided in the embodiment of the present application, the reference noise time domain data of the engine noise is obtained; the reference noise time domain data is corrected for human ears to obtain the human ear time domain noise data; then the human ear noise frequency domain data corresponding to the engine noise is obtained based on the human ear time domain noise data, the clapping frequency matrix corresponding to the frequency of the engine noise is obtained based on the human ear noise frequency domain data, and finally the noise order corresponding to the engine noise is obtained based on the clapping frequency matrix. In this way, by correcting the reference noise time domain data of the engine noise for human ears, the human ear time domain noise data can accurately simulate the noise of the engine heard by the human ear, and then the clapping frequency matrix corresponding to the frequency of the engine noise is obtained through the human ear time domain noise data, and the noise order corresponding to the engine noise is accurately obtained based on the clapping frequency matrix, so as to determine the parts that generate the noise based on the noise order, which improves the accuracy of locating the engine noise compared to determining the source of the noise through the human ear.
[0010] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS
[0011] The drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:
[0012] Figure 1 is a schematic diagram of an implementation environment shown in an exemplary embodiment of the present application;
[0013] Figure 2 is a flow chart of a method for determining noise order shown in an exemplary embodiment of the present application;
[0014] Figure 3 yes Figure 2 Step S210 in the illustrated embodiment is a flow chart in an exemplary embodiment;
[0015] Figure 4 yes Figure 3 Step S350 in the illustrated embodiment is a flow chart in an exemplary embodiment;
[0016] Figure 5 yes Figure 2 Step S220 in the illustrated embodiment is a flow chart in an exemplary embodiment;
[0017] Figure 6 yes Figure 2 Step S230 in the illustrated embodiment is a flow chart in an exemplary embodiment;
[0018] Figure 7 yes Figure 2 Step S240 in the illustrated embodiment is a flow chart in an exemplary embodiment;
[0019] Figure 8 yes Figure 2 Step S250 in the illustrated embodiment is a flow chart in an exemplary embodiment;
[0020] Fig. 9 is a block diagram of an apparatus for determining a noise order according to an exemplary embodiment of the present application;
[0021] Fig.10 is a schematic diagram of an electronic device shown in an exemplary embodiment of the present application;
[0022] Fig.11 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown. DETAILED DESCRIPTION
[0023] Here, exemplary embodiments will be described in detail, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are only examples of devices and methods consistent with some aspects of the present application as detailed in the attached claims.
[0024] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.
[0025] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.
[0026] The term "multiple" as used in this application refers to two or more than two. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the related objects are in an "or" relationship.
[0027] Please refer to Figure 1 , Figure 1 1 is a schematic diagram of an implementation environment involved in the present application, which includes a vehicle 100, an electronic device 200, and a recording device 300, wherein the recording device 300 communicates with the electronic device 200 via a wired or wireless network.
[0028] The recording device 300 is placed in the vehicle 100 and is used to record the engine noise generated by the engine to obtain recording data.
[0029] The electronic device 200 can determine the noise order of the engine noise. It can be placed in the vehicle 100 or can be independent of the vehicle 100, and the present application does not make any specific limitation on it.
[0030] Exemplarily, the electronic device 200 obtains reference noise time domain data of engine noise; performs human ear correction on the reference noise time domain data to obtain human ear time domain noise data; obtains human ear noise frequency domain data corresponding to the engine noise based on the human ear time domain noise data; obtains a clap frequency matrix corresponding to the frequency of the engine noise based on the human ear noise frequency domain data; and obtains the noise order corresponding to the engine noise based on the clap frequency matrix.
[0031] The vehicle 100 is a car powered by a fuel engine, including but not limited to a conventional fuel vehicle, a hybrid vehicle, a plug-in hybrid vehicle, etc., which are not limited herein. The electronic device 200 is a control device of the vehicle, such as a vehicle console, a computer, a vehicle controller, etc., which are not limited herein.
[0032] See also Figure 2 , Figure 2 is a flowchart of a method for determining noise order shown in an exemplary embodiment of the present application. The method can be applied to Figure 1The implementation environment shown is specifically executed by the electronic device 200 in the implementation environment. It should be understood that the method can also be applied to other exemplary implementation environments and be specifically executed by devices in other implementation environments, and this embodiment does not limit the implementation environment to which the method is applicable.
[0033] like Figure 2 As shown, in an exemplary embodiment, the method for determining the noise order includes at least steps S210 to S250, which are described in detail as follows:
[0034] Step S210, obtaining reference noise time domain data of engine noise.
[0035] Among them, engine noise refers to the noise generated by the engine.
[0036] Figure 3 yes Figure 2 Step S210 in the illustrated embodiment is a flow chart of an exemplary embodiment. Figure 3 As shown, the process of obtaining the reference noise time domain data of the engine noise may include steps S310 to S350, which are described in detail as follows:
[0037] Step S310, obtaining recording data of engine noise.
[0038] It should be noted that the process of recording the engine noise generated by the engine by the recording equipment is actually the process of sampling the engine noise generated by the engine.
[0039] The recording data is obtained by recording the engine noise generated by the engine through a recording device according to a preset sampling frequency. The preset sampling frequency is the sampling frequency set by the recording device, which complies with the Nyquist sampling theorem. The recording data includes multiple voice data points of the engine noise. The voice data points in the recording data represent the noise amplitude value of the engine noise at the time of sampling.
[0040] Step S320: obtaining first candidate noise time domain data according to the recording data.
[0041] Further, obtaining the first candidate noise time domain data according to the recording data includes: obtaining the sampling frequency of the recording data; when the sampling frequency of the recording data is the same as the preset target sampling frequency, determining the recording data as the first candidate noise time domain data; and / or, when the sampling frequency of the recording data is different from the preset target sampling frequency, resampling the recording data to obtain the first candidate noise time domain data; the sampling frequency of the first candidate noise time domain data is the preset target sampling frequency. Among them, the sampling frequency of the recording data is the sampling frequency set by the recording device, that is, the preset sampling frequency; the preset target sampling frequency includes 48000Hz; the first candidate noise time domain data includes multiple voice data points of engine noise.
[0042] In some embodiments, the recorded data is resampled to obtain first alternative noise time domain data, that is, when the sampling frequency of the recorded data is less than a preset target sampling frequency, the recorded data is interpolated to obtain first alternative noise time domain data; and / or, when the sampling frequency of the recorded data is less than a preset target sampling frequency, the recorded data is extracted to obtain first alternative noise time domain data.
[0043] Step S330: performing equal loudness processing on the first candidate noise time domain data to obtain second candidate noise time domain data.
[0044] It should be noted that the frequency of sound and noise that human ears can hear is between 20Hz and 20kHz, but human ears cannot really hear the size of each frequency signal. For example, for the frequency band of 3kHz to 4kHz, which is the most sensitive to human ears, human ears can hear it as long as the loudness is -10dB, but if it is a low-frequency signal of 20Hz, it requires a loudness of more than 60dB for human ears to hear it. It can be seen that although the intensity of 60dB 20Hz sound and -10dB 3kHz sound is very different, they are the same to human ears. This is the equal loudness effect of human ears, and the equal loudness effect of human ears will decrease as the volume increases. The role of equal loudness processing is to increase the volume of high-frequency and low-frequency components of engine noise at low volume, so that the loudness ratio of low, medium and high parts remains the same as the loudness ratio at high volume.
[0045] Further, performing equal loudness processing on the first candidate noise time domain data to obtain the second candidate noise time domain data includes: obtaining the first equal loudness coefficient by calculating spl_c=10^(b / 20)×2e-5; wherein spl_c is the first equal loudness coefficient, b is the second equal loudness coefficient, for example, b is 94db; obtaining the second candidate noise time domain data by calculating data_P=data_org×spl_c. wherein data_P is the second candidate noise time domain data; and data_org is the first candidate noise time domain data.
[0046] Step S340, obtaining the data length of the second candidate noise time domain data.
[0047] The first candidate noise time domain data includes a plurality of speech data points of the engine noise. The speech data points in the first candidate noise time domain data represent the noise amplitude value of the engine noise after equal loudness processing. The data length of the second candidate noise time domain data is the number of speech data points included in the second candidate noise time domain data.
[0048] Step S350: Acquire reference noise time domain data according to the data length and the second candidate noise time domain data.
[0049] The reference noise time domain data is the noise time domain data after the second candidate noise time domain is length-processed.
[0050] Figure 4 yes Figure 3 Step S350 in the illustrated embodiment is a flow chart of an exemplary embodiment. Figure 4 As shown, the process of obtaining reference noise time domain data according to the data length and the second candidate noise time domain data may include steps S410 to S420, which are described in detail as follows:
[0051] Step S410, determining whether the data length is an even number.
[0052] Further, determining whether the data length is an even number includes: obtaining a remainder between the data length and a preset parity coefficient; when the remainder is a preset first value, determining that the data length is an even number; and / or, when the remainder is a preset second value, determining that the data length is an odd number. The preset parity coefficient is 2; the preset first value is 0; and the preset second value is 1.
[0053] Step S420, when the data length is an even number, determine the second candidate noise time domain data as the reference noise time domain data; and / or, when the data length is an odd number, delete one data in the second candidate noise time domain data to obtain the reference noise time domain data.
[0054] It should be noted that this can ensure that the number of speech data points of the reference noise time domain data is an even number, so that the reference noise time domain data can be successfully fast Fourier transformed.
[0055] Step S220, performing human ear correction on the reference noise time domain data to obtain human ear time domain noise data.
[0056] It should be noted that the reference noise time domain data includes sound data that can be heard by human ears and sound data that cannot be heard by human ears. Human ear correction is performed on the reference noise time domain data, that is, the sound data that can be heard by human ears in the reference noise time domain data is restored.
[0057] Figure 5 yes Figure 2 Step S220 in the illustrated embodiment is a flow chart of an exemplary embodiment. Figure 5 As shown, the process of performing human ear correction on the reference noise time domain data to obtain human ear time domain noise data may include steps S510 to S530, which are described in detail as follows:
[0058] Step S510, performing fast Fourier transform on the reference noise time domain data to obtain first reference noise frequency domain data.
[0059] In the embodiment of the present application, a fast Fourier transform (FFT) is performed on the reference noise time domain data to obtain the first reference noise frequency domain data, that is, the reference noise time domain data is converted from the time domain to the frequency domain. The reference noise time domain data is the sound data of the engine noise in the time domain; the first reference noise frequency domain data is the sound data of the engine noise in the frequency domain.
[0060] Step S520: performing weighted calculation on the first reference noise frequency domain data to obtain second reference noise frequency domain data audible to human ears.
[0061] In the embodiment of the present application, the first reference noise frequency domain data is weighted, that is, the first reference noise frequency domain data is A-weighted. A-weighted is a standard weighting method for noise measurement, and the A-weighted calculation can be used to reflect the response characteristics of the human ear, so that the second reference noise frequency domain data only includes sound data that can be heard by the human ear, and the first reference noise frequency domain data is filtered, so that the second reference noise frequency domain data can accurately simulate the engine noise heard by the human ear.
[0062] Step S530: Perform an inverse fast Fourier transform on the second reference noise frequency domain data to obtain human ear time domain noise data.
[0063] In the embodiment of the present application, the second reference noise frequency domain data is subjected to an inverse fast Fourier transform to obtain the human ear time domain noise data, that is, the second reference noise frequency domain data is converted from the frequency domain back to the time domain. The second reference noise frequency domain data is the sound data of the engine noise in the frequency domain; the human ear time domain noise data is the sound data of the engine noise in the time domain. In this way, the human ear time domain noise data can accurately restore the engine noise heard by the human ear.
[0064] Step S230, obtaining human ear noise frequency domain data corresponding to the engine noise according to the human ear time domain noise data.
[0065] The human ear time domain noise data includes a plurality of speech data points of the engine noise after human ear correction. The speech data points in the human ear time domain noise data represent the noise amplitude value of the engine noise after human ear correction.
[0066] Figure 6 yes Figure 2 Step S230 in the illustrated embodiment is a flow chart of an exemplary embodiment. Figure 6 As shown, the process of obtaining human ear noise frequency domain data corresponding to engine noise according to human ear time domain noise data may include steps S610 to S630, which are described in detail as follows:
[0067] Step S610, slicing and reorganizing the human ear time domain noise data according to a preset overlap rate and a preset number of slicing points to obtain a time slice matrix.
[0068] Among them, the preset overlap rate represents the probability of the nth slice overlapping with the n-1th slice, and the preset number of slice points is a power of 2, for example: 256, 512, etc.; the preset number of slice points represents the number of speech data points that do not overlap between the nth slice and the n-1th slice.
[0069] In the embodiment of the present application, the preset overlap rate is 50%, and the preset number of slice points is 256. The human ear time domain noise data includes 480,000 voice data points. Then, the human ear time domain noise data is sliced to obtain slice 1: {d1, d2, ..., d512}, slice 2 {d257, d258, ..., d768}, slice 3 {d513, d514, ..., d1024}, ..., until the human ear time domain noise data is sliced, and the last slice is obtained, slice 1874 {d479489, d479490, ..., d480000}; wherein d1 is the first voice data point in the human ear time domain noise data; d2 is the second voice data point in the human ear time domain noise data; d512 is the 512th voice data point in the human ear time domain noise data; d257 is the 257th voice data point in the human ear time domain noise data speech data point; d258 is the 258th speech data point in the human ear time domain noise data; d768 is the 768th speech data point in the human ear time domain noise data; d513 is the 513th speech data point in the human ear time domain noise data; d514 is the 514th speech data point in the human ear time domain noise data; d1024 is the 1024th speech data point in the human ear time domain noise data; d479489 is the 479489th speech data point in the human ear time domain noise data; d479490 is the 479490th speech data point in the human ear time domain noise data; d480000 is the 480000th speech data point in the human ear time domain noise data.
[0070] Reorganization is to arrange the slices to obtain the time slice matrix Right now
[0071] During the slicing process, you can choose not to complete the slicing of all human ear time domain noise data, and confirm the completion of slicing when the preset number of slices is reached. The preset number is a multiple of the number of slicing points. For example: the preset number is the number of slicing points.
[0072] Step S620, performing fast Fourier transform on the time slice matrix to obtain candidate human ear noise frequency domain data.
[0073] Further, the time slice matrix is subjected to a fast Fourier transform to obtain candidate human ear noise frequency domain data, including: using a preset window function to perform a fast Fourier transform on the time slice matrix to obtain candidate human ear noise frequency domain data. The window function includes: a rectangular window, a triangular window, a Hanning window, a Hamming window, and a Gaussian window. In this way, the time slice matrix can better meet the periodicity requirements of the fast Fourier transform and reduce signal leakage.
[0074] The candidate human ear noise frequency domain data is matrix type data.
[0075] Step S630, transposing the candidate human ear noise frequency domain data to obtain human ear noise frequency domain data.
[0076] It should be noted that the human ear noise frequency domain data is matrix type data. The candidate human ear noise frequency domain data is transposed, that is, the rows and columns of the candidate human ear noise frequency domain data are swapped to obtain the human ear noise frequency domain data; the human ear noise frequency domain data is the transposed matrix of the candidate human ear noise frequency domain data.
[0077] It should be noted that, since the overlap rate of the slices is 50% before the fast Fourier transform, that is, there is 50% invalid data in the human ear noise frequency domain data, that is, the data information contained in the invalid data is repeated. The invalid data in the human ear noise frequency domain data is filtered out to update the human ear noise frequency domain data. For example: the matrix dimension of the human ear noise frequency domain data before the update is spline rows and spline columns; the matrix dimension of the human ear noise frequency domain data after the update is spline / 2 rows and spline columns. Among them, spline is the preset number of slice points.
[0078] Step S240, obtaining a clap frequency matrix corresponding to the frequency of the engine noise according to the human ear noise frequency domain data.
[0079] Figure 7 yes Figure 2 Step S240 in the illustrated embodiment is a flow chart in an exemplary embodiment. Figure 7 As shown, the process of obtaining the clapping frequency matrix corresponding to the frequency of the engine noise according to the human ear noise frequency domain data may include steps S710 to S730, which are described in detail as follows:
[0080] Step S710, frequency slicing is performed on the human ear noise frequency domain data to obtain human ear noise frequency domain vectors corresponding to multiple frequencies.
[0081] It should be noted that in the human ear noise frequency domain data, each row represents a speech data point corresponding to a frequency that can be heard by the human ear in the engine noise. The human ear noise frequency domain data is frequency sliced, that is, the human ear noise frequency domain data is sliced according to the row to obtain the human ear noise frequency domain vector corresponding to a frequency. Where a is the number of rows of the human ear noise frequency domain data.
[0082] Step S720, performing fast Fourier transform on each human ear noise frequency domain vector to obtain the clapping frequency vector corresponding to each frequency.
[0083] Step S730, obtaining a tapping frequency matrix according to the tapping frequency vectors corresponding to each frequency.
[0084] In the embodiment of the present application, the slap frequency matrix is obtained according to the slap frequency vectors corresponding to each frequency, that is, the slap frequency vectors corresponding to each frequency are reorganized to obtain the slap frequency matrix. For example, the slap frequency vectors corresponding to each frequency include: the slap frequency vector Ha corresponding to frequency a, the slap frequency vector Hb corresponding to frequency b, the slap frequency vector Hc corresponding to frequency c, the slap frequency vector Hd corresponding to frequency d, and the slap frequency vector He corresponding to frequency e. Then, the slap frequency vectors corresponding to each frequency are reorganized to obtain the slap frequency matrix:
[0085] Step S250, obtaining the noise order corresponding to the engine noise according to the slap frequency matrix.
[0086] It should be noted that the noise order here is relative to the basic frequency of the engine speed.
[0087] Figure 8 yes Figure 2 Step S250 in the illustrated embodiment is a flow chart of an exemplary embodiment. Figure 8 As shown, the process of obtaining the noise order corresponding to the engine noise according to the slap frequency matrix may include steps S810 to S850, which are described in detail as follows:
[0088] Step S810, performing response frequency restoration on the frequencies of the tapping frequency matrix to obtain a frequency characteristic matrix.
[0089] Further, the response frequency restoration is performed on the frequency of the slap frequency matrix to obtain a frequency feature matrix, including: obtaining a first frequency interval of the reference noise time domain data; determining the first frequency interval as the second frequency interval of each voice data point in the slap frequency matrix; multiplying the slap frequency matrix by the second frequency interval to obtain a frequency feature matrix. The rows of the frequency feature matrix represent the slap frequencies, and the columns represent the characteristic response frequencies.
[0090] Step S820, obtaining the tapping frequency vector corresponding to each response frequency in the frequency characteristic matrix.
[0091] In an embodiment of the present application, a clapping frequency vector corresponding to each response frequency is obtained in the frequency characteristic matrix, that is, multiple row vectors, that is, the clapping frequency vector corresponding to each response frequency, are obtained in the frequency characteristic matrix according to the rows of the matrix.
[0092] Step S830, obtaining the basic frequency of the engine speed.
[0093] Further, obtaining the engine speed base frequency includes: obtaining the engine speed of the engine; obtaining the engine speed base frequency by calculating F0=m / 60; wherein F0 is the engine speed base frequency, m is the engine speed of the engine; and 60 is a unit conversion coefficient, which represents that 1 minute is equal to 60 seconds.
[0094] Step S840, obtaining a reference noise order corresponding to each response frequency according to each slap frequency vector and the rotation speed basic frequency.
[0095] Furthermore, a reference noise order corresponding to each response frequency is obtained according to each clap frequency vector and the rotation speed base frequency, including: dividing each clap frequency vector by the rotation speed base frequency to obtain a reference noise order corresponding to each response frequency.
[0096] Step S850: determining the reference noise order as the noise order corresponding to the engine noise.
[0097] Fig. 9 is a block diagram of an apparatus for determining noise order shown in an exemplary embodiment of the present application. The apparatus can be applied to Figure 1 The implementation environment shown in the figure is specifically configured in the electronic device 200. The device can also be applied to other exemplary implementation environments and specifically configured in other devices. This embodiment does not limit the implementation environment to which the device is applied.
[0098] like Fig. 9 As shown, the exemplary apparatus for determining the noise order includes:
[0099] A reference noise time domain data acquisition module 901 is configured to acquire reference noise time domain data of engine noise;
[0100] The human ear time domain noise data acquisition module 902 is configured to perform human ear correction on the reference noise time domain data to obtain human ear time domain noise data;
[0101] The frequency domain data acquisition module 903 is configured to acquire human ear noise frequency domain data corresponding to the engine noise according to the human ear time domain noise data;
[0102] The matrix acquisition module 904 is configured to acquire a beat frequency matrix corresponding to the frequency of the engine noise according to the human ear noise frequency domain data;
[0103] The order acquisition module 905 is configured to acquire the noise order corresponding to the engine noise according to the slap frequency matrix.
[0104] In an exemplary embodiment, the reference noise time domain data acquisition module 901 includes:
[0105] A recording data acquisition module configured to acquire recording data of engine noise;
[0106] A first candidate noise time domain data acquisition module, configured to acquire first candidate noise time domain data according to the recording data;
[0107] an equal loudness processing module, configured to perform equal loudness processing on the first candidate noise time domain data to obtain second candidate noise time domain data;
[0108] A data length acquisition module, configured to acquire the data length of the second candidate noise time domain data;
[0109] The first reference noise time domain data acquisition module is configured to acquire reference noise time domain data according to the data length and the second candidate noise time domain data.
[0110] In an exemplary embodiment, the first reference noise time domain data acquisition module includes:
[0111] a parity determination module configured to determine whether the data length is an even number;
[0112] The second reference noise time domain data module is configured to determine the second candidate noise time domain data as the reference noise time domain data when the data length is an even number; and / or, when the data length is an odd number, delete one data in the second candidate noise time domain data to obtain the reference noise time domain data.
[0113] In an exemplary embodiment, the human ear time domain noise data acquisition module 902 includes:
[0114] A fast Fourier transform module is configured to perform a fast Fourier transform on the reference noise time domain data to obtain first reference noise frequency domain data;
[0115] A weighting module configured to perform weighted calculation on the first reference noise frequency domain data to obtain second reference noise frequency domain data audible to human ears;
[0116] The inverse fast Fourier transform module is configured to perform an inverse fast Fourier transform on the second reference noise frequency domain data to obtain human ear time domain noise data.
[0117] In an exemplary embodiment, the frequency domain data acquisition module 903 includes:
[0118] A time slice matrix acquisition module is configured to slice and reorganize the human ear time domain noise data according to a preset overlap rate and a preset number of slice points to obtain a time slice matrix;
[0119] A candidate human ear noise frequency domain data acquisition module is configured to perform a fast Fourier transform on the time slice matrix to obtain candidate human ear noise frequency domain data;
[0120] The transposition module is configured to transpose the candidate human ear noise frequency domain data to obtain the human ear noise frequency domain data.
[0121] In an exemplary embodiment, the matrix acquisition module 904 includes:
[0122] A frequency slicing module is configured to perform frequency slicing on the frequency domain data of human ear noise to obtain frequency domain vectors of human ear noise corresponding to multiple frequencies;
[0123] A slap frequency vector acquisition module is configured to perform fast Fourier transform on each human ear noise frequency domain vector respectively to obtain a slap frequency vector corresponding to each frequency;
[0124] The clap frequency matrix acquisition module is configured to acquire the clap frequency matrix according to the clap frequency vectors corresponding to each frequency.
[0125] In an exemplary embodiment, the order acquisition module 905 includes:
[0126] A response frequency recovery module is configured to perform response frequency recovery on the frequencies of the slap frequency matrix to obtain a frequency characteristic matrix;
[0127] A slap frequency vector acquisition module, configured to obtain a slap frequency vector corresponding to each response frequency in a frequency characteristic matrix;
[0128] A rotation speed basic frequency acquisition module, configured to acquire the rotation speed basic frequency of the engine;
[0129] A reference noise order acquisition module is configured to obtain a reference noise order corresponding to each response frequency according to each slap frequency vector and a rotation speed base frequency;
[0130] The order determination module is configured to determine the reference noise order as the noise order corresponding to the engine noise.
[0131] It should be noted that the device for determining the noise order provided in the above embodiment and the method for determining the noise order provided in the above embodiment belong to the same concept, wherein the specific manner in which each module and unit performs the operation has been described in detail in the method embodiment, and will not be repeated here. In practical applications, the device for adjusting the outlet air temperature provided in the above embodiment can allocate the above functions to different functional modules as needed, that is, divide the internal structure of the device into different functional modules to complete all or part of the functions described above, and this is not limited here.
[0132] An embodiment of the present application also provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the electronic device implements the method for adjusting the air outlet temperature provided in the above-mentioned embodiments.
[0133] Fig.10 FIG. 1 is a schematic diagram of an electronic device in one embodiment of the present application. Fig.10 As shown, the electronic device 200 in the embodiment of the present application is placed in a car. The electronic device 200 includes: one or more processors 1001; a storage device 1002, which is used to store one or more programs. When the one or more programs are executed by the one or more processors, the electronic device implements the method for adjusting the air outlet temperature provided in the above-mentioned various embodiments.
[0134] The processor 1001 may include one or more processing cores. The processor 1001 uses various interfaces and lines to connect various parts of the entire car, and executes various functions of the car and processes data by running or executing instructions, programs, code sets or instruction sets stored in the storage device 1002, and calling data stored in the storage device 1002. Optionally, the processor 1001 can be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), and programmable logic array (PLA). The processor 1001 can integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. Among them, the CPU mainly processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing display content; and the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 1001, but may be implemented separately through a communication chip.
[0135] The storage device 1002 may include a random access memory (RAM) or a read-only memory (ROM). The storage device 1002 may be used to store instructions, programs, codes, code sets or instruction sets. The storage device 1002 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function, instructions for implementing the above-mentioned various method embodiments, etc. The data storage area may also store data created by the hybrid vehicle during use.
[0136] Fig.11 The structure diagram of the computer system suitable for implementing the electronic device of the embodiment of the present application is shown. It should be noted that: Fig.11 The computer system 1100 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.
[0137] like Fig.11 As shown, the computer system 1100 includes a central processing unit (CPU) 1101, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 1102 or the program loaded from the storage part 1108 to the random access memory (RAM) 1103, such as executing the method described in the above embodiment. In the RAM 1103, various programs and data required for system operation are also stored. The CPU 1101, the ROM 1102 and the RAM 1103 are connected to each other through the bus 1104. The input / output (I / O) interface 1105 is also connected to the bus 1104.
[0138] The following components are connected to the I / O interface 1105: an input section 1106 including a keyboard, a mouse, etc.; an output section 1107 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 1108 including a hard disk, etc.; and a communication section 1109 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 1109 performs communication processing via a network such as the Internet. A drive 1110 is also connected to the I / O interface 1105 as needed. A removable medium 1111, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1110 as needed so that a computer program read therefrom is installed into the storage section 1108 as needed.
[0139] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 1109, and / or installed from a removable medium 1111. When the computer program is executed by a central processing unit (CPU) 1101, various functions defined in the system of the present application are executed.
[0140] It should be noted that the computer-readable medium shown in the embodiment of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. This propagated data signal can take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. A computer program contained on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.
[0141] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.
[0142] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.
[0143] Another aspect of the present application also provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the road condition refreshing method as described above is implemented. The computer-readable storage medium may be included in the electronic device described in the above embodiment, or may exist independently without being assembled into the electronic device.
[0144] Another aspect of the present application also provides a computer program product or a computer program, which includes a computer instruction stored in a computer-readable storage medium. A processor of a computer device reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the road condition refreshing method provided in each of the above embodiments.
[0145] The above content is only a preferred exemplary embodiment of the present application and is not intended to limit the implementation scheme of the present application. A person skilled in the art can easily make corresponding changes or modifications based on the main concept and spirit of the present application. Therefore, the scope of protection of the present application shall be based on the scope of protection required by the claims.
Claims
1. A method for determining a noise order, characterized in that include: Obtain reference noise time domain data of engine noise; Performing human ear correction on the reference noise time domain data to obtain human ear time domain noise data; Acquire human ear noise frequency domain data corresponding to the engine noise according to the human ear time domain noise data; Acquire a clap frequency matrix corresponding to the frequency of the engine noise according to the human ear noise frequency domain data; Acquire the noise order corresponding to the engine noise according to the slap frequency matrix; The step of obtaining the clapping frequency matrix corresponding to the frequency of the engine noise according to the human ear noise frequency domain data comprises: performing frequency slicing on the human ear noise frequency domain data to obtain human ear noise frequency domain vectors corresponding to a plurality of frequencies; Perform fast Fourier transform on each human ear noise frequency domain vector respectively to obtain the slap frequency vector corresponding to each frequency; and obtain the slap frequency matrix according to the slap frequency vector corresponding to each frequency.
2. The method according to claim 1, characterized in that The step of obtaining reference noise time domain data of engine noise includes: Acquiring recording data of the engine noise; Acquire first candidate noise time domain data according to the recording data; Performing equal loudness processing on the first candidate noise time domain data to obtain second candidate noise time domain data; Obtaining the data length of the second candidate noise time domain data; The reference noise time domain data is acquired according to the data length and the second candidate noise time domain data.
3. The method according to claim 2, characterized in that Acquiring the reference noise time domain data according to the data length and the second candidate noise time domain data includes: Determining whether the data length is an even number; When the data length is an even number, the second candidate noise time domain data is determined as the reference noise time domain data; and / or, when the data length is an odd number, one data in the second candidate noise time domain data is deleted to obtain the reference noise time domain data.
4. The method according to claim 1, characterized in that: Performing human ear correction on the reference noise time domain data to obtain human ear time domain noise data includes: Performing a fast Fourier transform on the reference noise time domain data to obtain first reference noise frequency domain data; Performing weighted calculation on the first reference noise frequency domain data to obtain second reference noise frequency domain data audible to human ears; Perform an inverse fast Fourier transform on the second reference noise frequency domain data to obtain the human ear time domain noise data.
5. The method according to claim 1, characterized in that Acquiring human ear noise frequency domain data corresponding to the engine noise according to the human ear time domain noise data, including: Slicing and reorganizing the human ear time domain noise data according to a preset overlap rate and a preset number of slice points to obtain a time slice matrix; Performing a fast Fourier transform on the time slice matrix to obtain candidate human ear noise frequency domain data; The candidate human ear noise frequency domain data is transposed to obtain the human ear noise frequency domain data.
6. The method according to claim 1, characterized in that Obtaining the noise order corresponding to the engine noise according to the slap frequency matrix includes: Performing response frequency restoration on the frequencies of the slapping frequency matrix to obtain a frequency characteristic matrix; Obtaining the clapping frequency vector corresponding to each response frequency in the frequency characteristic matrix; Get the basic frequency of engine speed; Obtaining a reference noise order corresponding to each response frequency according to each of the slap frequency vectors and the rotation speed basic frequency; The reference noise order is determined as the noise order corresponding to the engine noise.
7. A device for determining a noise order, characterized in that include: A reference noise time domain data acquisition module is configured to acquire reference noise time domain data of engine noise; A human ear time domain noise data acquisition module is configured to perform human ear correction on the reference noise time domain data to obtain human ear time domain noise data; A frequency domain data acquisition module is configured to acquire human ear noise frequency domain data corresponding to the engine noise according to the human ear time domain noise data; A matrix acquisition module, configured to acquire a clap frequency matrix corresponding to the frequency of the engine noise according to the human ear noise frequency domain data; An order acquisition module, configured to acquire a noise order corresponding to the engine noise according to the slap frequency matrix; The step of obtaining the clapping frequency matrix corresponding to the frequency of the engine noise according to the human ear noise frequency domain data comprises: performing frequency slicing on the human ear noise frequency domain data to obtain human ear noise frequency domain vectors corresponding to a plurality of frequencies; Perform fast Fourier transform on each human ear noise frequency domain vector respectively to obtain the slap frequency vector corresponding to each frequency; and obtain the slap frequency matrix according to the slap frequency vector corresponding to each frequency.
8. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the electronic device to implement the method for determining the noise order as described in any one of claims 1 to 6.
9. A computer-readable storage medium, characterized in that: Computer readable instructions are stored thereon, and when the computer readable instructions are executed by a processor of a computer, the computer is caused to execute the method for determining noise order according to any one of claims 1 to 6.