Abnormal sound evaluation method, system, device and computer-readable storage medium

Abstract

A method, system, device, and computer-readable storage medium for evaluating abnormal noises relate to the technical field of abnormal noise testing. Specifically, when an abnormal noise is detected by a target vehicle on a target road surface, the method comprises obtaining a target abnormal noise level coefficient corresponding to the abnormal noise and a road surface roughness corresponding to the target road surface, and determining a target road surface coefficient based on the road surface roughness; determining a target abnormal noise frequency weight coefficient corresponding to the abnormal noise based on a target reproducible probability of the abnormal noise and a mapping relationship between the reproducible probability and the abnormal noise frequency weight coefficient, wherein the reproducible probability of the abnormal noise is determined based on component clearance and surface wear; and determining an abnormal noise score based on the target abnormal noise frequency weight coefficient, the target abnormal noise level coefficient, and the target road surface coefficient. This application provides a universal abnormal noise evaluation method that addresses the technical problem of poor universality of vehicle abnormal noise level assessment methods in the prior art.

Description

Technical Field

[0001] The present application relates to the technical field of abnormal sound testing, and in particular to an abnormal sound evaluation method, system, device, and computer-readable storage medium. Background Art

[0002] With the increasing popularity of new energy vehicles, abnormal vehicle noise is a growing concern. This noise not only affects the user experience but can also indicate potential quality issues, making it a key research area for manufacturers and R&D institutions.

[0003] Current methods and technologies for assessing vehicle noise levels are diverse and challenging. Different testing conditions and environments significantly impact noise, complicating accurate assessment. Existing methods for quantifying vehicle noise levels vary. While some methods may be suitable for specific types of noise, they are difficult to apply universally or ensure consistent results in practical applications. This leads to limited universality in vehicle noise level assessment methods. Therefore, developing a universal noise evaluation method is an urgent issue. Summary of the Invention

[0004] The present application provides a method, system, device and computer-readable storage medium for evaluating abnormal noise, which can solve the technical problem of poor versatility of vehicle abnormal noise level evaluation methods in the prior art.

[0005] In a first aspect, an embodiment of the present application provides a method for evaluating abnormal noise, the method comprising:

[0006] When an abnormal sound is generated by the target vehicle on the target road surface, a target abnormal sound level coefficient corresponding to the abnormal sound and a road surface roughness corresponding to the target road surface are obtained, and a target road surface coefficient is determined based on the road surface roughness;

[0007] Determining a target abnormal sound frequency weight coefficient corresponding to the abnormal sound based on a target reproducible probability of the abnormal sound and a mapping relationship between the reproducible probability and the abnormal sound frequency weight coefficient, wherein the reproducible probability of the abnormal sound is determined based on component clearance and surface wear;

[0008] An abnormal sound score is determined according to the target abnormal sound frequency weight coefficient, the target abnormal sound level coefficient, and the target road surface coefficient.

[0009] In combination with the first aspect, in one embodiment, determining the target road surface coefficient based on the road surface roughness includes:

[0010] Determine the power spectrum density of road surface roughness according to road surface roughness;

[0011] Determine the target road surface roughness coefficient according to the road surface roughness power spectrum density;

[0012] Determining a target road surface grade corresponding to the target road surface roughness coefficient based on a mapping relationship between the target road surface roughness coefficient and the road surface grade;

[0013] A target road surface coefficient corresponding to the target road surface grade is determined based on a mapping relationship between the target road surface grade and the road surface coefficient.

[0014] In combination with the first aspect, in one embodiment, obtaining a target abnormal sound level coefficient corresponding to the abnormal sound includes:

[0015] Acquiring target parameters corresponding to the abnormal sound, the parameters including acoustic parameters loudness, sharpness, and roughness;

[0016] Determine the abnormal sound level based on the magnitude relationship between the target parameter and the preset target parameter threshold range;

[0017] A target abnormal noise level coefficient corresponding to the abnormal noise is determined based on a mapping relationship between the abnormal noise level and the abnormal noise level coefficient.

[0018] In combination with the first aspect, in one embodiment, determining the abnormal sound score according to the target abnormal sound frequency weight coefficient, the target abnormal sound level coefficient, and the target road surface coefficient includes:

[0019] Substitute the target abnormal sound frequency weight coefficient, the target abnormal sound level coefficient, and the target road surface coefficient into the first calculation formula to obtain the abnormal sound score. The first calculation formula is as follows:

[0020]

[0021] Where R I is the target road surface coefficient; G I is the target abnormal sound level coefficient; F I is the target abnormal sound frequency weight coefficient; S I is the abnormal noise score, and i is the number of abnormal noise problems.

[0022] In a second aspect, an embodiment of the present application provides an abnormal sound evaluation system, the abnormal sound evaluation system comprising:

[0023] a first processing module configured to, when an abnormal sound is generated by a target vehicle on a target road surface, obtain a target abnormal sound level coefficient corresponding to the abnormal sound and a road surface roughness corresponding to the target road surface, and determine a target road surface coefficient based on the road surface roughness;

[0024] a second processing module, configured to determine a target abnormal sound frequency weight coefficient corresponding to the abnormal sound based on a target reproducible probability of the abnormal sound and a mapping relationship between the reproducible probability and the abnormal sound frequency weight coefficient, wherein the reproducible probability of the abnormal sound is determined based on component clearance and surface wear;

[0025] The third processing module is used to determine an abnormal sound score according to the target abnormal sound frequency weight coefficient, the target abnormal sound level coefficient and the target road surface coefficient.

[0026] In conjunction with the second aspect, in one embodiment, the first processing module is specifically configured to:

[0027] Determine the power spectrum density of road surface roughness according to road surface roughness;

[0028] Determine the target road surface roughness coefficient according to the road surface roughness power spectrum density;

[0029] Determining a target road surface grade corresponding to the target road surface roughness coefficient based on a mapping relationship between the target road surface roughness coefficient and the road surface grade;

[0030] A target road surface coefficient corresponding to the target road surface grade is determined based on a mapping relationship between the target road surface grade and the road surface coefficient.

[0031] In conjunction with the second aspect, in one embodiment, the first processing module is further configured to:

[0032] Acquiring target parameters corresponding to the abnormal sound, the parameters including acoustic parameters loudness, sharpness, and roughness;

[0033] Determine the abnormal sound level based on the magnitude relationship between the target parameter and the preset target parameter threshold range;

[0034] A target abnormal noise level coefficient corresponding to the abnormal noise is determined based on a mapping relationship between the abnormal noise level and the abnormal noise level coefficient.

[0035] In conjunction with the second aspect, in one embodiment, the third processing module is specifically configured to:

[0036] Substitute the target abnormal sound frequency weight coefficient, the target abnormal sound level coefficient, and the target road surface coefficient into the first calculation formula to obtain the abnormal sound score. The first calculation formula is as follows:

[0037]

[0038] Where R I is the target road surface coefficient; G I is the target abnormal sound level coefficient; F I is the target abnormal sound frequency weight coefficient; S I is the abnormal noise score, and i is the number of abnormal noise problems.

[0039] In a third aspect, an embodiment of the present application provides an abnormal sound evaluation device, which includes a processor, a memory, and an abnormal sound evaluation program stored in the memory and executable by the processor. When the abnormal sound evaluation program is executed by the processor, the steps of the abnormal sound evaluation method described in any of the above items are implemented.

[0040] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which an abnormal sound evaluation program is stored. When the abnormal sound evaluation program is executed by a processor, the steps of the abnormal sound evaluation method as described in any of the above items are implemented.

[0041] The beneficial effects of the technical solutions provided in the embodiments of the present application include:

[0042] When an abnormal noise occurs on a target vehicle on a target road surface, the road surface unevenness corresponding to the target road surface and the abnormal noise level coefficient corresponding to the abnormal noise are obtained, and a road surface coefficient is determined based on the road surface unevenness; the target abnormal noise frequency weight coefficient corresponding to the abnormal noise is determined according to the target reproducible probability of the abnormal noise and the mapping relationship between the reproducible probability and the abnormal noise frequency weight coefficient; the road surface coefficient, the abnormal noise level coefficient and the abnormal noise frequency weight coefficient are comprehensively considered to determine the abnormal noise score of the whole vehicle or component. Regardless of the test bench or road, the whole vehicle or component makes an abnormal noise through the stimulation of the road surface or equipment. Therefore, the abnormal noise evaluation method in this application is not only suitable for abnormal noise road evaluation and test bench evaluation, but can also be used for the evaluation and comparative analysis of single problems, which significantly improves the versatility and practicality of the abnormal noise evaluation method. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a flow chart of an embodiment of the abnormal noise evaluation method of the present application;

[0044] Figure 2 For this application Figure 1 Detailed flow chart of step S10;

[0045] Figure 3 A schematic diagram of a road surface power spectrum density curve according to an embodiment of the abnormal noise evaluation method of this application;

[0046] Figure 4 This is a schematic diagram of the architecture of an embodiment of the abnormal sound evaluation system of the present application;

[0047] Figure 5 This is a schematic diagram of the hardware structure of the abnormal sound evaluation device involved in the embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention 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 this application.

[0049] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0050] In a first aspect, an embodiment of the present application provides a method for evaluating abnormal noise.

[0051] In one embodiment, referring to Figure 1 , Figure 1 This is a flow chart of an embodiment of the abnormal noise evaluation method of the present application.

[0052] like Figure 1 As shown in Figure 2, the abnormal noise evaluation method includes:

[0053] Step S10: When an abnormal sound occurs on a target road surface when the target vehicle is traveling on the target road surface, a target abnormal sound level coefficient corresponding to the abnormal sound and a road surface roughness corresponding to the target road surface are obtained, and a target road surface coefficient is determined based on the road surface roughness.

[0054] For example, in the embodiment of the present application, the road surface roughness is the change in the height q of the road surface relative to the reference plane along the road length I (i.e., q(I)). The roughness data can be obtained by a level or a special road surface meter. In the embodiment of the present application, the road surface roughness corresponding to the target road surface can be collected according to the established road surface and vehicle speed information; the abnormal noise level coefficient can usually be determined based on characteristics such as the type, frequency, and intensity of the abnormal noise to quantify and describe the severity of the abnormal noise, and can help evaluate the impact of the abnormal noise on vehicle performance and driving comfort, thereby guiding subsequent maintenance or improvement measures.

[0055] Specifically, when a target vehicle experiences an abnormal noise on a target road surface, the system obtains a target abnormal noise level coefficient and a road surface roughness corresponding to the abnormal noise. After obtaining the road surface roughness, the target road surface coefficient is determined based on the road surface roughness. The abnormal noise level coefficient and road surface roughness coefficient not only help diagnose and resolve abnormal noise issues, but also provide important reference for improving vehicle design and optimizing road surface maintenance, thereby enhancing vehicle safety, comfort, and performance.

[0056] Step S20: Determine a target abnormal sound frequency weight coefficient corresponding to the abnormal sound according to the target reproducible probability of the abnormal sound and the mapping relationship between the reproducible probability and the abnormal sound frequency weight coefficient, wherein the reproducible probability of the abnormal sound is determined based on the component clearance and surface wear.

[0057] For example, in this embodiment, the reproducibility probability of an abnormal noise refers to the frequency with which the abnormal noise occurs during multiple tests or actual use. This probability depends on the clearances between components and the wear on the component surfaces. Larger clearances or wear may lead to more frequent abnormal noise. The abnormal noise frequency weighting coefficient is used to quantify the contribution of the abnormal noise frequency to the overall abnormal noise assessment. It reflects the importance of the frequency of the abnormal noise to the overall abnormal noise level. Abnormal noises with higher frequencies may have a greater impact on driving comfort and vehicle reliability, and therefore their weighting coefficient should be relatively high.

[0058] Table 1 Mapping relationship between the reproducible probability of abnormal sound and the weight coefficient of abnormal sound frequency

[0059] Frequency Weight Frequency weight coefficient describe high 1 The probability of recurrence of abnormal noise is more than 2 / 3 middle 0.8 The probability of recurrence of abnormal noise is between 1 / 3 and 2 / 3 Low 0.6 The probability of recurrence of abnormal noise is less than 1 / 3

[0060] Specifically, the target frequency weighting factor for abnormal noise can typically be mapped to the reproducibility probability based on experimental data or empirical rules. Specifically, the frequency of abnormal noise can be statistically analyzed based on the degree of impact of abnormal noise on driver perception at different frequencies, and the weighting factor can be set based on the statistical analysis results. As shown in Table 1, when the reproducibility probability of an abnormal noise is greater than 2 / 3, the corresponding frequency weighting factor is 1; when the reproducibility probability of an abnormal noise is between 1 / 3 and 2 / 3, the corresponding frequency weighting factor is 0.8; and when the reproducibility probability of an abnormal noise is less than 1 / 3, the corresponding frequency weighting factor is 0.6. Therefore, the target frequency weighting factor for abnormal noise can be determined based on the target reproducibility probability of the abnormal noise and the mapping relationship between the reproducibility probability and the frequency weighting factor as recorded in Table 1.

[0061] It should be noted that the mapping relationship between the reproducible probability of abnormal noise and the abnormal noise frequency weight coefficient is set to quantify the frequency and importance of abnormal noise, so as to more accurately evaluate its impact on vehicle performance and driving experience.

[0062] Step S30: Determine an abnormal sound score based on the target abnormal sound frequency weight coefficient, the target abnormal sound level coefficient, and the target road surface coefficient.

[0063] For example, in the embodiment of the present application, the target abnormal noise frequency weight coefficient, the target abnormal noise level coefficient and the target road surface coefficient are substituted into the abnormal noise score calculation formula to determine the abnormal noise score. The abnormal noise score calculated by combining the above three factors can not only be used to quantify and describe the overall impact or severity of the abnormal noise of the vehicle on different road surfaces, but also can be used to compare the abnormal noise conditions under different conditions so as to take appropriate maintenance or improvement measures, thereby improving the driving experience and vehicle quality.

[0064] This application obtains the road surface roughness corresponding to the target road surface and the abnormal noise level coefficient corresponding to the abnormal noise when an abnormal noise occurs on a target vehicle on a target road surface, and determines the road surface coefficient based on the road surface roughness; then determines the target abnormal noise frequency weight coefficient corresponding to the abnormal noise according to the target reproducible probability of the abnormal noise and the mapping relationship between the reproducible probability and the abnormal noise frequency weight coefficient; comprehensively considers the road surface coefficient, the abnormal noise level coefficient and the abnormal noise frequency weight coefficient to determine the abnormal noise score of the whole vehicle or component. Regardless of the test bench or road, the whole vehicle or component emits abnormal noise through the stimulation of the road surface or equipment. Therefore, the abnormal noise evaluation method in this application is not only suitable for abnormal noise road evaluation and test bench evaluation, but can also be used for the evaluation and comparative analysis of single problems, which significantly improves the versatility and practicality of the abnormal noise evaluation method.

[0065] Furthermore, in one embodiment, referring to Figure 2 As shown, the target road surface coefficient is determined based on the road surface roughness, including:

[0066] Step S101: determining the road surface roughness power spectrum density according to the road surface roughness;

[0067] Step S102: determining a target road surface roughness coefficient according to the road surface roughness power spectrum density;

[0068] Step S103: determining a target road surface grade corresponding to the target road surface roughness coefficient based on a mapping relationship between the target road surface roughness coefficient and the road surface grade;

[0069] Step S104: Determine a target road surface coefficient corresponding to the target road surface grade based on the mapping relationship between the target road surface grade and the road surface coefficient.

[0070] Exemplarily, in an embodiment of the present application, the power spectral density (PSD) of the road surface is determined based on its roughness; the target road surface roughness coefficient is calculated based on the power spectral density; the grade of the target road surface is determined using the mapping relationship between the target road surface roughness coefficient and the road surface grade; and the target road surface coefficient corresponding to the target road surface grade is determined based on the mapping relationship between the target road surface grade and the road surface coefficient.

[0071] Specifically, the measured road roughness data is subjected to Fast Fourier Transform (FFT) to calculate the road power spectrum density, and then the double logarithmic coordinate graph is plotted as follows: Figure 3 The pavement power spectrum density curve is shown; the target pavement roughness coefficient can be determined by substituting the pavement power spectrum density into the fitting formula between the pavement power spectrum density and the pavement roughness coefficient. The fitting formula between the pavement power spectrum density and the pavement roughness coefficient is as follows:

[0072]

[0073] Where n is the spatial frequency, which is the reciprocal of the wavelength, and the unit is m -1 ; n0 is the reference spatial frequency, where n0 = 0.1m -1 ; G q (n0) is the road surface power spectrum density value at the reference spatial frequency (i.e., the target road surface roughness coefficient), in m 3 ; G q (n) is the power spectrum density of the road surface; W is the frequency index, which is the slope of the oblique line on the double logarithmic coordinate. Currently, the road surface grade is generally set to 8 in the industry, and it can be preferably set to 2, that is, W=2.

[0074] It should be noted that the geometric mean values ​​of various road roughness coefficients and their mapping relationships with road surface grades are shown in Table 2.

[0075] Table 2 Geometric mean of road roughness coefficient and its mapping relationship with road surface grade

[0076]

[0077] Referring to Table 2, it can be understood that when the geometric mean of the road surface roughness coefficient is 16, the corresponding road surface grade is A; when the geometric mean of the road surface roughness coefficient is 64, the corresponding road surface grade is B; and when the geometric mean of the road surface roughness coefficient is 256, the corresponding road surface grade is C.

[0078] Table 3 Relationship between pavement grade and pavement coefficient

[0079] Road surface grade A B C D E F G H <![CDATA[Road surface coefficient R I > <![CDATA[R A =1]]> <![CDATA[R B =0.9]]> <![CDATA[R C =0.8]]> <![CDATA[R D =0.7]]> <![CDATA[R E =0.6]]> <![CDATA[R F =0.5]]> <![CDATA[R G =0.3]]> <![CDATA[R H =0.1]]>

[0080] It should be noted that in this embodiment, higher road surface grades correspond to higher road surface coefficients to suit customer usage scenarios. For example, as shown in Table 3, road surface grade A corresponds to a road surface coefficient of 1; road surface grade B corresponds to a road surface coefficient of 0.9; and road surface grade C corresponds to a road surface coefficient of 0.8.

[0081] Furthermore, in one embodiment, obtaining a target abnormal sound level coefficient corresponding to the abnormal sound includes:

[0082] Acquiring target parameters corresponding to the abnormal sound, the parameters including acoustic parameters loudness, sharpness, and roughness;

[0083] Determine the abnormal sound level based on the magnitude relationship between the target parameter and the preset target parameter threshold range;

[0084] A target abnormal noise level coefficient corresponding to the abnormal noise is determined based on a mapping relationship between the abnormal noise level and the abnormal noise level coefficient.

[0085] For example, in the embodiment of the present application, the preset target parameter threshold range can be determined according to actual needs and is not limited here. Specifically, the process of realizing abnormal noise target parameter analysis includes measuring acoustic parameters (loudness, sharpness, roughness) and setting the target parameter threshold range, and determining the abnormal noise level based on the measured values, and finally mapping the level to the corresponding abnormal noise level coefficient to help evaluate and improve the acoustic quality and user experience of the product. It should be noted that since the abnormal noise in the car is the superposition of multiple sound sources, the objective evaluation is to quantify the total sound source, and it is difficult to quantify a single sound source; and the abnormal noise may be broadband, low or sharp, and it is difficult to completely replace it with an objective indicator, so different actual situations may have different evaluation results. In other words, this embodiment is not limited to evaluating the abnormal noise level based only on loudness, sharpness, and roughness.

[0086] Specifically, we'll use the three parameters of loudness, sharpness, and roughness as examples. Assume the loudness threshold range a = [1, 30]; the sharpness threshold range b = [0.1, 3]; and the roughness threshold range c = [0.3, 0.7]. Assume the noise level is categorized as follows: Level 1 means all target parameters are met; Level 2 means one or more parameters slightly deviate from the target range; and Level 3 means one or more parameters significantly deviate from the target range. Assume the noise level coefficient for Level 1 is 0.5; the noise level coefficient for Level 2 is 0.75; and the noise level coefficient for Level 1 is 1.

[0087] It can be understood that, assuming the measured loudness is 20 and is within range a, thus meeting the requirements; the sharpness is 1.4 and is within range b, thus meeting the requirements; and the roughness is 0.5 and is within range c, thus meeting the requirements. These measurement results are within the preset target parameter ranges, so the abnormal sound level is 1 and the abnormal sound level coefficient is 1.

[0088] It should be noted that the target abnormal noise level coefficient can also be determined through subjective evaluation. Specifically, the level of the abnormal noise problem can be determined by using a grade scoring method. The abnormal noise problem can be divided into three levels for judgment by referring to the table below.

[0089] Table 4 Relationship between abnormal noise level and abnormal noise level coefficient

[0090]

[0091]

[0092] Specifically, when the abnormal noise level is described as being clearly audible to the evaluator in any normal sitting position, causing discomfort or even uneasiness, the corresponding abnormal noise level coefficient is 1; when the abnormal noise level is described as being barely audible to the evaluator in any normal sitting position, the corresponding abnormal noise level coefficient is 0.3; when the abnormal noise level is described as being barely audible to the evaluator in abnormal sitting positions such as leaning forward, the corresponding abnormal noise level coefficient is 0.1.

[0093] Furthermore, in one embodiment, determining the abnormal sound score according to the target abnormal sound frequency weight coefficient, the target abnormal sound level coefficient, and the target road surface coefficient includes:

[0094] Substitute the target abnormal sound frequency weight coefficient, the target abnormal sound level coefficient, and the target road surface coefficient into the first calculation formula to obtain the abnormal sound score. The first calculation formula is as follows:

[0095]

[0096] Where R I is the target road surface coefficient; G I is the target abnormal sound level coefficient; F I is the target abnormal sound frequency weight coefficient; S I is the abnormal noise score, and i is the number of abnormal noise problems.

[0097] For example, in the embodiment of the present application, the target road surface coefficient R I , Target abnormal noise level coefficient G I , target abnormal sound frequency weight coefficient F I Substitute the following calculation formula to obtain the abnormal sound score S I , the calculation formula is as follows:

[0098]

[0099] In a second aspect, an embodiment of the present application also provides an abnormal sound evaluation system.

[0100] In one embodiment, referring to Figure 4 , Figure 4This is a functional module diagram of an embodiment of the abnormal sound evaluation system of this application. Figure 4 As shown in the figure, the abnormal sound evaluation system includes:

[0101] a first processing module configured to, when an abnormal sound is generated by a target vehicle on a target road surface, obtain a target abnormal sound level coefficient corresponding to the abnormal sound and a road surface roughness corresponding to the target road surface, and determine a target road surface coefficient based on the road surface roughness;

[0102] a second processing module, configured to determine a target abnormal sound frequency weight coefficient corresponding to the abnormal sound based on a target reproducible probability of the abnormal sound and a mapping relationship between the reproducible probability and the abnormal sound frequency weight coefficient, wherein the reproducible probability of the abnormal sound is determined based on component clearance and surface wear;

[0103] The third processing module is used to determine an abnormal sound score according to the target abnormal sound frequency weight coefficient, the target abnormal sound level coefficient and the target road surface coefficient.

[0104] Furthermore, in one embodiment, the first processing module is specifically configured to:

[0105] Determine the power spectrum density of road surface roughness according to road surface roughness;

[0106] Determine the target road surface roughness coefficient according to the road surface roughness power spectrum density;

[0107] Determining a target road surface grade corresponding to the target road surface roughness coefficient based on a mapping relationship between the target road surface roughness coefficient and the road surface grade;

[0108] A target road surface coefficient corresponding to the target road surface grade is determined based on a mapping relationship between the target road surface grade and the road surface coefficient.

[0109] Furthermore, in one embodiment, the first processing module is further configured to:

[0110] Acquiring target parameters corresponding to the abnormal sound, the parameters including acoustic parameters loudness, sharpness, and roughness;

[0111] Determine the abnormal sound level based on the magnitude relationship between the target parameter and the preset target parameter threshold range;

[0112] A target abnormal noise level coefficient corresponding to the abnormal noise is determined based on a mapping relationship between the abnormal noise level and the abnormal noise level coefficient.

[0113] Furthermore, in one embodiment, the third processing module is specifically configured to:

[0114] Substitute the target abnormal sound frequency weight coefficient, the target abnormal sound level coefficient, and the target road surface coefficient into the first calculation formula to obtain the abnormal sound score. The first calculation formula is as follows:

[0115]

[0116] Where R I is the target road surface coefficient; G I is the target abnormal sound level coefficient; F I is the target abnormal sound frequency weight coefficient; S I is the abnormal noise score, and i is the number of abnormal noise problems.

[0117] This application obtains the road surface roughness corresponding to the target road surface and the abnormal noise level coefficient corresponding to the abnormal noise when an abnormal noise occurs on a target vehicle on a target road surface, and determines the road surface coefficient based on the road surface roughness; then determines the target abnormal noise frequency weight coefficient corresponding to the abnormal noise according to the target reproducible probability of the abnormal noise and the mapping relationship between the reproducible probability and the abnormal noise frequency weight coefficient; comprehensively considers the road surface coefficient, the abnormal noise level coefficient and the abnormal noise frequency weight coefficient to determine the abnormal noise score of the whole vehicle or component. Regardless of the test bench or road, the whole vehicle or component emits abnormal noise through the stimulation of the road surface or equipment. Therefore, the abnormal noise evaluation method in this application is not only suitable for abnormal noise road evaluation and test bench evaluation, but can also be used for the evaluation and comparative analysis of single problems, which significantly improves the versatility and practicality of the abnormal noise evaluation method.

[0118] Among them, the functional implementation of each module in the above-mentioned abnormal sound evaluation system corresponds to each step in the above-mentioned abnormal sound evaluation method embodiment, and its functions and implementation processes are not repeated here one by one.

[0119] In a third aspect, an embodiment of the present application provides an abnormal sound evaluation device, which may be a device with data processing capabilities, such as a personal computer (PC), a laptop computer, or a server.

[0120] Reference Figure 5 , Figure 5 Schematic diagram of the hardware structure of the abnormal sound evaluation device involved in the embodiment of the present application. In the embodiment of the present application, the abnormal sound evaluation device may include a processor, a memory, a communication interface and a communication bus.

[0121] The communication bus may be of any type and is used to interconnect the processor, memory, and communication interface.

[0122] Communication interfaces include input / output (I / O) interfaces, physical interfaces, and logical interfaces, which are used to interconnect components within the abnormal sound evaluation device, as well as interfaces used to interconnect the abnormal sound evaluation device with other devices (such as other computing devices or user devices). Physical interfaces can be Ethernet, fiber optic, or ATM interfaces; user devices can be displays, keyboards, and other devices.

[0123] The memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0124] The processor can be a general-purpose processor that can call the abnormal sound evaluation program stored in the memory and execute the abnormal sound evaluation method provided in the embodiments of this application. For example, the general-purpose processor can be a central processing unit (CPU). The method executed when the abnormal sound evaluation program is called can be referred to in the various embodiments of the abnormal sound evaluation method of this application and will not be further described here.

[0125] Those skilled in the art will understand that Figure 5 The hardware structure shown in the figure does not constitute a limitation to the present application and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0126] In a fourth aspect, an embodiment of the present application also provides a readable storage medium.

[0127] The readable storage medium of the present application stores an abnormal sound evaluation program, wherein when the abnormal sound evaluation program is executed by the processor, the steps of the abnormal sound evaluation method as described above are implemented.

[0128] Among them, the method implemented when the abnormal sound evaluation program is executed can refer to the various embodiments of the abnormal sound evaluation method of this application, and will not be repeated here.

[0129] The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices. The terms "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit the "first", "second" and "third" to different types.

[0130] In the description of the embodiments of this application, the words "exemplary," "for example," or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary," "for example," or "for example" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary," "for example," or "for example" is intended to present the relevant concepts in a concrete manner.

[0131] In the description of the embodiments of the present application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; “and / or” in the text is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, “multiple” refers to two or more than two.

[0132] In some processes described in the embodiments of the present application, multiple operations or steps are included that appear in a specific order. However, it should be understood that these operations or steps may not be performed in the order in which they appear in the embodiments of the present application or may be performed in parallel. The sequence numbers of the operations are only used to distinguish between different operations, and the sequence numbers themselves do not represent any order of execution. In addition, these processes may include more or fewer operations, and these operations or steps may be performed in sequence or in parallel, and these operations or steps may be combined.

[0133] It should be noted that the serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0134] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for enabling a terminal device to execute the methods described in each embodiment of the present application.

[0135] The above are only preferred embodiments of the present application and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method for evaluating abnormal noise, characterized in that: The abnormal noise evaluation method includes: When an abnormal sound is generated by the target vehicle on the target road surface, a target abnormal sound level coefficient corresponding to the abnormal sound and a road surface roughness corresponding to the target road surface are obtained, and a target road surface coefficient is determined based on the road surface roughness; Determining a target abnormal sound frequency weight coefficient corresponding to the abnormal sound based on a target reproducible probability of the abnormal sound and a mapping relationship between the reproducible probability and the abnormal sound frequency weight coefficient, wherein the reproducible probability of the abnormal sound is determined based on component clearance and surface wear; An abnormal sound score is determined according to the target abnormal sound frequency weight coefficient, the target abnormal sound level coefficient, and the target road surface coefficient.

2. The abnormal noise evaluation method according to claim 1, wherein: Determining a target road surface coefficient based on the road surface roughness includes: Determine the power spectrum density of road surface roughness according to road surface roughness; Determine the target road surface roughness coefficient according to the road surface roughness power spectrum density; Determining a target road surface grade corresponding to the target road surface roughness coefficient based on a mapping relationship between the target road surface roughness coefficient and the road surface grade; A target road surface coefficient corresponding to the target road surface grade is determined based on a mapping relationship between the target road surface grade and the road surface coefficient.

3. The abnormal noise evaluation method according to claim 1, wherein: The obtaining of a target abnormal sound level coefficient corresponding to the abnormal sound includes: Acquiring target parameters corresponding to the abnormal sound, the parameters including acoustic parameters loudness, sharpness, and roughness; Determine the abnormal sound level based on the magnitude relationship between the target parameter and the preset target parameter threshold range; A target abnormal noise level coefficient corresponding to the abnormal noise is determined based on a mapping relationship between the abnormal noise level and the abnormal noise level coefficient.

4. The abnormal noise evaluation method according to claim 1, wherein: Determining the abnormal sound score according to the target abnormal sound frequency weight coefficient, the target abnormal sound level coefficient, and the target road surface coefficient includes: Substitute the target abnormal sound frequency weight coefficient, the target abnormal sound level coefficient, and the target road surface coefficient into the first calculation formula to obtain the abnormal sound score. The first calculation formula is as follows: Where R I is the target road surface coefficient; G I is the target abnormal sound level coefficient; F I is the target abnormal sound frequency weight coefficient; S I is the abnormal noise score, and i is the number of abnormal noise problems.

5. An abnormal sound evaluation system, characterized in that: The abnormal sound evaluation system includes: a first processing module configured to, when an abnormal sound is generated by a target vehicle on a target road surface, obtain a target abnormal sound level coefficient corresponding to the abnormal sound and a road surface roughness corresponding to the target road surface, and determine a target road surface coefficient based on the road surface roughness; a second processing module, configured to determine a target abnormal sound frequency weight coefficient corresponding to the abnormal sound based on a target reproducible probability of the abnormal sound and a mapping relationship between the reproducible probability and the abnormal sound frequency weight coefficient, wherein the reproducible probability of the abnormal sound is determined based on component clearance and surface wear; The third processing module is used to determine an abnormal sound score according to the target abnormal sound frequency weight coefficient, the target abnormal sound level coefficient and the target road surface coefficient.

6. The abnormal noise evaluation system according to claim 5, wherein: The first processing module is specifically configured to: Determine the power spectrum density of road surface roughness according to road surface roughness; Determine the target road surface roughness coefficient according to the road surface roughness power spectrum density; Determining a target road surface grade corresponding to the target road surface roughness coefficient based on a mapping relationship between the target road surface roughness coefficient and the road surface grade; A target road surface coefficient corresponding to the target road surface grade is determined based on a mapping relationship between the target road surface grade and the road surface coefficient.

7. The abnormal noise evaluation system according to claim 5, wherein: The first processing module is further configured to: Acquiring target parameters corresponding to the abnormal sound, the parameters including acoustic parameters loudness, sharpness, and roughness; Determine the abnormal sound level based on the magnitude relationship between the target parameter and the preset target parameter threshold range; A target abnormal noise level coefficient corresponding to the abnormal noise is determined based on a mapping relationship between the abnormal noise level and the abnormal noise level coefficient.

8. The abnormal noise evaluation system according to claim 5, wherein: The third processing module is specifically configured to: Substitute the target abnormal sound frequency weight coefficient, the target abnormal sound level coefficient, and the target road surface coefficient into the first calculation formula to obtain the abnormal sound score. The first calculation formula is as follows: Where R I is the target road surface coefficient; G I is the target abnormal sound level coefficient; F I is the target abnormal sound frequency weight coefficient; S I is the abnormal noise score, and i is the number of abnormal noise problems.

9. An abnormal sound evaluation device, characterized in that: The abnormal sound evaluation device includes a processor, a memory, and an abnormal sound evaluation program stored in the memory and executable by the processor, wherein when the abnormal sound evaluation program is executed by the processor, the steps of the abnormal sound evaluation method according to any one of claims 1 to 4 are implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores an abnormal sound evaluation program, wherein when the abnormal sound evaluation program is executed by the processor, the steps of the abnormal sound evaluation method according to any one of claims 1 to 4 are implemented.

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