A method, system, device and medium for establishing a benchmark for noise analysis

Abstract

The present invention discloses a method, system, device and medium for establishing a benchmark for noise analysis. The technical solution of the present invention places a loudspeaker sample on a fixture, performs logarithmic sine scanning on the loudspeaker sample to obtain acoustic test curve data and waveform data generated by the sound source of the loudspeaker sample, performs spectrum analysis on the waveform data of good products and the waveform data of defective products, and compares the waveform data of the defective products with the waveform data of good products to locate defects. Customized noise filter parameters are obtained by integrating the above contents to know the accurate setting range of the filter. The present invention also correspondingly proposes a system, device and medium for establishing a benchmark for noise analysis. The system, device and medium are used to implement the above method. The method of the present invention can eliminate environmental and product-specific factors through intuitive analysis, thereby creating suitable filter parameters, so as to ultimately accurately distinguish good products from defective products.

Description

Technical Field

[0001] The present invention relates to the technical field of loudspeakers, and in particular to a method, system, device and medium for establishing a reference for noise analysis. Background Art

[0002] Noise, or Rub & Buzz, mainly refers to high-order harmonic distortion. High-order harmonic distortion is an audio distortion phenomenon, which refers to the frequency components that appear in the audio signal with frequencies several times higher than the fundamental frequency. These frequency components are high-order harmonics. This distortion will cause the originally smooth sound to sound rustling, sharp or other obvious distortions, affecting the quality of the sound. Setting filters is an important technical means to improve the sound quality of speakers. By setting filters, defects can be located and abnormal parts can be filtered out. In the existing technology, the industry usually uses classic harmonic tracking high-pass filters, that is, through minimum analysis and high-order tracking filtering. The prior art is used to screen the loudspeaker production, while the classic harmonic tracking high-pass filter is not sufficient to separate good products from defective products due to its too single adjustment range, and thus it is impossible to obtain the detailed differences between good products and defective products. That is, in the process of defining the filter, the prior art cannot know whether the general noise source is the environmental factor, the characteristic factor of the product itself, or the production defect of the product itself. At the same time, the prior art is relatively complicated to create a custom filter, that is, the filter setting of the prior art cannot obtain a more accurate filter parameter setting by excluding environmental factors and product factors itself, and the creation process is relatively complicated, so that it is ultimately difficult to fully distinguish between good products and defective products on the production line. Summary of the invention

[0003] The main purpose of the present invention is to propose a benchmark creation method, system, device and medium for noise analysis, aiming to solve the technical problem that the filter setting in the prior art cannot obtain more accurate filter parameter settings by excluding environmental factors and product factors, and the creation process is relatively complicated, so that it is ultimately difficult to fully distinguish between good and defective products on the production line.

[0004] To achieve the above object, the present invention proposes a method for establishing a benchmark for noise analysis, comprising:

[0005] Acquire a speaker sample, and perform preprocessing on the speaker sample to obtain acoustic test curve data and waveform data corresponding to a sound source of the speaker sample;

[0006] Performing spectrum analysis on waveform data corresponding to the speaker sample sound source, wherein the waveform data includes waveform data of a standard speaker and waveform data of a defective speaker;

[0007] Obtain custom noise filter parameters, perform spectral analysis on the waveform data of the standard speaker and the waveform data of the defective speaker respectively to obtain corresponding spectral data, and obtain custom noise filter parameters by manually processing the spectral data. The custom noise filter parameters include customized high-pass filter settings and low-pass filter settings.

[0008] Furthermore, obtaining custom noise filter parameters by manually processing spectral data includes drawing at least high-pass filtering and low-pass filtering points according to the spectral data, obtaining a parameter curve formed by connecting continuous filtering points according to the filtering points, and obtaining custom noise filter parameters according to the parameter curve.

[0009] Furthermore, when the custom noise filter parameters are obtained, the custom noise filter parameters are specifically expressed in the form of a data matrix.

[0010] Further, the data matrix expression specifically includes forming an excitation frequency, forming a high pass filter harmonic order, and forming a low pass filter harmonic order.

[0011] Furthermore, in the process of manually processing the spectral data to obtain the custom noise filter parameters, the noise is evaluated in the form of artificial hearing to assist in creating the custom noise filter parameters.

[0012] Furthermore, the step of performing preprocessing according to the speaker samples includes performing logarithmic sine scanning on the speaker samples.

[0013] Furthermore, the specific step of performing spectral analysis on the waveform data includes performing short-time Fourier transform on the waveform data.

[0014] The present invention also provides a benchmark creation system for noise analysis, comprising:

[0015] The first acquisition module is used to acquire a speaker sample and obtain acoustic test curve data and waveform data corresponding to a sound source of the speaker sample;

[0016] A first processing module, used for performing spectrum analysis according to waveform data corresponding to a speaker sample sound source;

[0017] The second processing module is used to obtain custom noise filter parameters of customized high-pass filter settings and low-pass filter settings according to the acoustic test curve and waveform data.

[0018] The present invention also proposes a benchmark creation device for noise analysis, including a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the aforementioned method.

[0019] The present invention also provides a computer-readable storage medium, comprising a computer program for electronic data exchange, wherein the computer program enables a computer to execute the aforementioned method.

[0020] The technical solution of the present invention places a speaker sample on a fixture, performs a logarithmic sine scan on the speaker sample, obtains acoustic test curve data and waveform data generated by the sound source of the speaker sample, specifically, performs spectrum analysis on the waveform data of good products and the waveform data of defective products, distinguishes the waveform data of good products from the waveform data of defective products, and at the same time, compares the waveform data of defective products with the waveform data of good products to locate defects. Further, the custom noise filter parameters are obtained by integrating the above contents, and the corresponding spectrum data are obtained by performing spectrum analysis on the waveform data. The spectrum analysis includes short-time Fourier transform, and filter points are drawn according to the spectrum data to obtain a custom noise filter curve. The data matrix is ​​obtained through the filter curve, so as to know the accurate setting range of the filter. The custom noise filter includes customized high-pass filter settings and low-pass filter settings. The present invention also correspondingly proposes a benchmark creation system, device and medium for noise analysis. The system, device and medium are used to implement the above method. The method of the present invention can eliminate environmental and product factors through intuitive analysis, thereby creating suitable filter parameters, so as to accurately distinguish good products from defective products. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 A schematic diagram of a process flow of a method for establishing a reference for noise analysis provided by the present invention;

[0022] Figure 2 A schematic diagram of the process flow of a benchmark creation system for noise analysis provided by the present invention;

[0023] Figure 3 It is a schematic diagram of setting parameters of the custom noise filter of the present invention. DETAILED DESCRIPTION

[0024] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, top, bottom, inside, outside, vertical, horizontal, longitudinal, counterclockwise, clockwise, circumferential, radial, axial...), then the directional indication is only used to explain the relative position relationship, movement status, etc. between the components in a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0026] In addition, if there are descriptions involving "first" or "second" etc. in the embodiments of the present invention, the descriptions of "first" or "second" etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" or "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0027] The present invention provides a benchmark creation method for noise analysis.

[0028] In the embodiment of the present invention, Figures 1 to 3 As shown, the method includes steps 101 to 103, and the steps mainly include:

[0029] Step 101: obtaining a speaker sample, and performing preprocessing on the speaker sample to obtain acoustic test curve data and waveform data corresponding to a sound source of the speaker sample;

[0030] Step 102: performing spectrum analysis according to waveform data corresponding to the speaker sample sound source, wherein the waveform data includes waveform data of a standard speaker and waveform data of a defective speaker;

[0031] Step 103: Obtain custom noise filter parameters, perform spectral analysis on the waveform data of the standard speaker and the waveform data of the defective speaker respectively, obtain corresponding spectral data, and obtain custom noise filter parameters by manually processing the spectral data. The custom noise filter parameters include customized high-pass filter settings and low-pass filter settings.

[0032] In an embodiment of the present invention, before performing preprocessing on the loudspeaker sample to obtain the acoustic test curve data and the waveform data corresponding to the sound source of the loudspeaker sample, the loudspeaker sample is placed on a fixture to wait for preprocessing.

[0033] In an embodiment of the present invention, when performing spectrum analysis on the waveform data corresponding to the speaker sample sound source, a specific step further includes filling in sound pressure settings, which include start frequency, stop frequency and time settings.

[0034] In an embodiment of the present invention, obtaining the custom noise filter parameters by manually processing the spectral data includes drawing at least filtering points of high-pass filtering and low-pass filtering according to the spectral data, obtaining a parameter curve formed by connecting continuous filtering points according to the filtering points, and obtaining the custom noise filter parameters according to the parameter curve, such as Figure 3 As shown in the figure, several filtering points are marked, the filtering point located at the bottom is a high-pass filtering point, and the filtering point located at the top is a low-pass filtering point. The parameter curve is obtained by connecting the filtering point at the bottom with the filtering point at the top.

[0035] It should be noted that the specific drawing of the filtering points mentioned above depends on the comparison of spectral data, the range between the high-pass filtering point and the low-pass filtering point, that is, the spectral data generated by spectral analysis of the waveform data of the standard speaker and the waveform data of the defective speaker, and the position that needs to be filtered is obtained through the difference points of the spectral data, thereby excluding environmental factors and product factors themselves to obtain a better filtering range.

[0036] Specifically, when obtaining the custom noise filter parameters, the custom noise filter parameters are specifically expressed in the form of a data matrix.

[0037] More specifically, the data matrix expression specifically includes forming the excitation frequency, forming the high pass filter harmonic order, and forming the low pass filter harmonic order, such as Figure 3 As shown, the excitation frequency is the horizontal axis, and the high-pass filter harmonic order and the low-pass filter harmonic order correspond to the vertical axis. For example, in one embodiment of the present invention, the data matrix is ​​specifically expressed in the following form, wherein the first row of data indicates that the excitation frequency is 1, the high-pass filter harmonic order is 500, and the low-pass filter harmonic order is 20000; the second row of data indicates that the excitation frequency is 25, the high-pass filter harmonic order is 20, and the low-pass filter harmonic order is 800; and the subsequent data are deduced by analogy. In addition, taking the second row of data as an example, the high-pass frequency is 25*20Hz=500Hz, and the low-pass frequency is 25*800Hz=20000Hz. The data matrix is ​​subsequently imported into Klippel for specific use.

[0038]

[0039] Specifically, in the process of manually processing spectral data to obtain custom noise filter parameters, noise is evaluated in the form of artificial hearing, thereby assisting in obtaining the custom noise filter parameters.

[0040] Specifically, in the process of manually processing spectral data to obtain custom noise filter parameters, the noise can be evaluated by switching between a logarithmic view and a linear view, thereby assisting in obtaining the custom noise filter parameters.

[0041] In an embodiment of the present invention, the step of performing preprocessing according to the speaker samples comprises performing logarithmic sine scanning on the speaker samples.

[0042] Specifically, in the embodiments of the present invention, the logarithmic sine scan is usually based on 3 seconds and performs a scan starting from 20 Hz. The specific steps of the logarithmic sine scan are prior art and will not be described in detail here.

[0043] In an embodiment of the present invention, the specific step of performing spectral analysis on the waveform data includes performing short-time Fourier transform on the waveform data.

[0044] Specifically, the specific steps of performing spectral analysis on the waveform data include wavelet analysis and filter bank processing in addition to short-time Fourier transform. These methods can be implemented simultaneously or selectively, among which short-time Fourier transform is a preferred embodiment.

[0045] The present invention further provides a reference establishment system for noise analysis, comprising a first acquisition module 201 , a first processing module 202 and a second processing module 203 .

[0046] The first acquisition module 201 is used to acquire a speaker sample, obtain acoustic test curve data and waveform data corresponding to the speaker sample sound source;

[0047] The first processing module 202 is used to perform spectrum analysis according to the waveform data corresponding to the speaker sample sound source;

[0048] The second processing module 203 is used to obtain custom noise filter parameters of customized high-pass filter settings and low-pass filter settings according to the acoustic test curve and waveform data.

[0049] The present invention also proposes a benchmark creation device for noise analysis, including a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the aforementioned method.

[0050] The present invention also provides a computer-readable storage medium, comprising a computer program for electronic data exchange, wherein the computer program enables a computer to execute the aforementioned method.

[0051] It is worth noting that after executing the above method, the custom noise filter parameters can be imported into Klippel for use. Klippel is a speaker analysis tool produced in Germany in the prior art that can measure sound pressure level, frequency response, distortion and other parameters.

[0052] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for establishing a benchmark for noise analysis, characterized in that: include: Acquire a speaker sample, and perform preprocessing on the speaker sample to obtain acoustic test curve data and waveform data corresponding to a sound source of the speaker sample; Performing spectrum analysis on waveform data corresponding to the speaker sample sound source, wherein the waveform data includes waveform data of a standard speaker and waveform data of a defective speaker; Obtain custom noise filter parameters, perform spectral analysis on the waveform data of the standard speaker and the waveform data of the defective speaker respectively to obtain corresponding spectral data, and obtain custom noise filter parameters by manually processing the spectral data. The custom noise filter parameters include customized high-pass filter settings and low-pass filter settings.

2. The method for establishing a reference for noise analysis according to claim 1, characterized in that: The method of obtaining the custom noise filter parameters by manually processing the spectral data includes drawing at least high-pass filtering and low-pass filtering points according to the spectral data, obtaining a parameter curve formed by connecting continuous filtering points according to the filtering points, and obtaining the custom noise filter parameters according to the parameter curve.

3. The method for establishing a reference for noise analysis according to claim 2, characterized in that: When obtaining the custom noise filter parameters, the custom noise filter parameters are specifically expressed in the form of a data matrix.

4. The method for establishing a reference for noise analysis according to claim 3, characterized in that: The data matrix expression specifically includes forming an excitation frequency, forming a high-pass filter harmonic order, and forming a low-pass filter harmonic order.

5. The method for establishing a reference for noise analysis according to any one of claims 1 to 4, characterized in that: In the process of manually processing spectral data to obtain custom noise filter parameters, noise is evaluated in the form of artificial hearing to assist in creating custom noise filter parameters.

6. The method for establishing a reference for noise analysis according to claim 1, characterized in that: The step of preprocessing according to the speaker samples includes performing logarithmic sine scanning on the speaker samples.

7. The method for establishing a reference for noise analysis according to claim 1, characterized in that: The specific step of performing spectral analysis on the waveform data includes performing short-time Fourier transform on the waveform data.

8. A system for establishing a benchmark for noise analysis, characterized in that: include: The first acquisition module is used to acquire a speaker sample and obtain acoustic test curve data and waveform data corresponding to a sound source of the speaker sample; A first processing module, used for performing spectrum analysis according to waveform data corresponding to a speaker sample sound source; The second processing module is used to obtain custom noise filter parameters of customized high-pass filter settings and low-pass filter settings according to the acoustic test curve and waveform data.

9. A device for establishing a benchmark for noise analysis, characterized in that: The method comprises a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the programs include instructions for executing the steps in the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The method comprises storing a computer program for electronic data exchange, wherein the computer program causes a computer to execute the method according to any one of claims 1 to 7.

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