CN111798109B - Material friction abnormal sound matching method - Google Patents
Material friction abnormal sound matching method Download PDFInfo
- Publication number
- CN111798109B CN111798109B CN202010572262.0A CN202010572262A CN111798109B CN 111798109 B CN111798109 B CN 111798109B CN 202010572262 A CN202010572262 A CN 202010572262A CN 111798109 B CN111798109 B CN 111798109B
- Authority
- CN
- China
- Prior art keywords
- abnormal sound
- risk
- loudness
- test
- friction
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000002159 abnormal effect Effects 0.000 title claims abstract description 102
- 239000000463 material Substances 0.000 title claims abstract description 52
- 238000000034 method Methods 0.000 title claims abstract description 41
- 238000012360 testing method Methods 0.000 claims abstract description 61
- 238000004458 analytical method Methods 0.000 claims abstract description 20
- 238000004364 calculation method Methods 0.000 claims abstract description 20
- 238000012502 risk assessment Methods 0.000 claims description 11
- 230000005856 abnormality Effects 0.000 claims description 6
- 238000012216 screening Methods 0.000 claims description 6
- 208000006011 Stroke Diseases 0.000 claims description 4
- 238000012545 processing Methods 0.000 claims description 4
- 239000003344 environmental pollutant Substances 0.000 claims description 3
- 231100000719 pollutant Toxicity 0.000 claims description 3
- 239000012925 reference material Substances 0.000 claims description 3
- 238000004140 cleaning Methods 0.000 claims description 2
- 230000007613 environmental effect Effects 0.000 claims description 2
- 230000005284 excitation Effects 0.000 claims description 2
- 238000011156 evaluation Methods 0.000 abstract description 10
- 238000011161 development Methods 0.000 abstract description 5
- 238000007619 statistical method Methods 0.000 abstract description 5
- 238000012795 verification Methods 0.000 abstract description 3
- 239000007769 metal material Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000010998 test method Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 230000001953 sensory effect Effects 0.000 description 1
- 230000035943 smell Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Development Economics (AREA)
- Marketing (AREA)
- Educational Administration (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
Abstract
The invention discloses a material friction abnormal sound matching method, which belongs to the technical field of automobile materials, and comprises the steps of obtaining friction abnormal sound noise data through test, analyzing and calculating the data, fitting, grading and calculating a loudness curve obtained through calculation, obtaining material friction abnormal sound matching analysis key parameters according to a weight calculation and evaluation formula, and forming a method for accurately judging the risk of abnormal sound generation of two parts. According to the method, the matching degree of the friction abnormal sound of the materials under different conditions can be judged through hierarchical division, statistical analysis and weighting evaluation, and a material matching database can be accurately and effectively formed by applying the method disclosed by the invention, so that early data support is provided for the development of the abnormal sound performance of the whole vehicle. In addition, the method can judge and analyze the friction abnormal sound problem of the real vehicle, is convenient for problem cause analysis and subsequent scheme verification, and provides important support for improving the abnormal sound performance of the whole vehicle.
Description
Technical Field
The invention belongs to the technical field of automobile materials, and particularly relates to a material friction abnormal sound matching method.
Background
The perceived quality of an automobile refers to the sensory quality that can be directly experienced by human vision, touch, smell and hearing. And hearing belongs to NVH range, mainly refers to sound perceived by drivers and passengers in normal driving and operating processes of the vehicle, and audible sound can be pleasant to people, and annoying abnormal sound causes complaints of users. In recent years, statistics find that the performance of the whole vehicle is gradually improved, and complaints of members on abnormal sound problems in the vehicle are gradually increased, and the friction abnormal sound between parts is a high-frequency problem and a heavy disaster area complaint by users.
The invention discloses a non-metallic material abnormal sound evaluation method and application thereof, and relates to the technical field of materials, in particular to an evaluation method and application of abnormal sound generated by relative motion between non-metallic materials, mainly rubber plastic materials and products thereof, for example, publication No. CN 109856044A. However, the whole test process and normalization are not restricted in detail, and the judgment method of the friction abnormal sound is to analyze through friction coefficients and whether the friction sliding motion is generated or not, judge whether the abnormal sound is generated or not through friction performance parameters, and judge that the risk degree of the abnormal sound generated by friction of the material cannot be effectively expressed through no-level division of the judgment method.
For another example, CN108009360a discloses a method and a device for analyzing abnormal noise of an automobile, and the disclosed method for predicting abnormal noise of friction predicts abnormal noise of friction during early development by CAE means, and does not introduce an actual measurement test method and abnormal noise judgment standard. The publication No. CN209961494U discloses a motion platform device of an abnormal sound friction test bed. The device is a motion platform device, interference can be avoided through the device, and a friction abnormal sound test method and a judgment standard are not involved.
Disclosure of Invention
In order to solve the problems of poor directness, unclear grading and unstable accuracy of friction abnormal sound risk analysis in the prior art, the invention aims to provide a material friction abnormal sound matching method, which comprises the steps of obtaining friction abnormal sound noise data through test, analyzing and calculating the data, fitting, grading and calculating a loudness curve obtained through calculation, obtaining material friction abnormal sound matching analysis key parameters according to a weight analysis evaluation formula, and forming a method for accurately judging abnormal sound risk of two components. According to the method, the matching degree of the friction abnormal sound of the materials under different conditions can be judged through hierarchical division, statistical analysis and weighting evaluation, and a material matching database can be accurately and effectively formed by applying the method disclosed by the invention, so that early data support is provided for the development of the abnormal sound performance of the whole vehicle. In addition, the method can judge and analyze the friction abnormal sound problem of the real vehicle, is convenient for problem cause analysis and subsequent scheme verification, and provides important support for improving the abnormal sound performance of the whole vehicle.
The invention is realized by the following technical scheme:
the material friction abnormal sound matching method specifically comprises the following steps as shown in fig. 1. :
S1, material friction abnormal sound test: noise data are obtained by carrying out friction abnormal sound test on the test sample pairs, and a test system for the test is an MCTS material matching test bed of MB company;
s2, abnormal sound risk analysis: the friction risk grade parameter is obtained through loudness analysis on noise data and calculation of risk grading statistics;
s3, friction abnormal sound matching degree analysis: and comparing the obtained grade parameter R value with a risk grade table to determine the friction abnormal sound matching property of the material.
Preferably, the friction abnormal sound test of the material in the step S1 specifically includes the following steps:
Step m1, preparing a sample for friction abnormal sound of a material, cutting the sample into standard sizes according to test requirements, cleaning the surface of the sample to prevent interference of pollutants other than the material, and fixing the sample on a test table after the sample preparation is finished;
Step m2, setting test conditions, namely setting temperature and humidity conditions and recording the temperature and humidity conditions in a test due to the fact that the friction abnormal sound of the material is related to the environmental temperature and humidity, and setting vertical load and excitation conditions according to test requirements;
Step m3, pre-testing, wherein after the test conditions are determined, the temperature and humidity environment is required to be invalid for more than 2 hours, and the pre-testing is carried out;
And m4, collecting data, namely collecting friction abnormal sound data after the pre-test is passed, wherein no external interference noise is ensured during sound collection, and the background noise of the test system is lower than 30dBA.
Preferably, the abnormal sound risk analysis in step S2 specifically includes the following steps:
step m5, analyzing the loudness of the data processing, namely analyzing the loudness value of the collected sound data through a loudness calculation formula to form a time loudness curve;
step m6, screening and storing loudness results, and primarily screening the loudness of the test results, if obvious interference noise exists, eliminating the loudness, and repeating m3, m4 and m5 until no abnormality exists, wherein three groups of non-abnormal constant data are required to be obtained under the same test condition;
Step m7, calculating a risk classification statistical value Si (i=0, 1 and 2), performing curve fitting on time-loudness data, setting a risk level 3, namely 0.5 tone, 1.0 tone and 1.5 tone, respectively performing integral statistics on loudness data in 3 level ranges of 0.5-1.0 tone, 1.0-1.5 tone and 1.5 tone, and integrating loudness curves in different areas to obtain friction abnormal sound risk classification statistical values S0, S1 and S2; the loudness curve classification and Si calculation are shown in fig. 2.
Step m8, analyzing and evaluating Rj (j=1.2.3) values, wherein Rj represents friction abnormal sound risk grade parameters under different loudness interval grading statistics;
and m9, judging a delta value of the Rj value obtained in m8, wherein the delta value is a difference value of Rj obtained by testing under the same working condition, if delta is more than or equal to 1.0, eliminating the data abnormality, and returning to the step m4 to acquire the data again.
Preferably, the loudness calculation formula described in step m 5:
St＝Sm+F(∑S-Sm)
Wherein:
st is the overall loudness;
Sm is the maximum loudness index;
sigma S is the sum of all band loudness indices; the S value is checked by looking up an ISO532 loudness index table;
F is the coefficient: the calculation band selection octave f=0.3.
Preferably, rj in the step m8 is obtained by empirical fitting of the values of S0, S1, S2 by the formula r=a×s0+b×s1+c×s2+d, A, B, C, D is a constant coefficient, and the results R1, R2, R3 are output.
Preferably, the friction abnormal sound matching degree analysis in the step S3 specifically includes the following steps:
Step m10, calculating an AR value, namely, AR= (R1+R2+R3)/3, performing risk analysis on the obtained AR value reference material friction abnormal sound matching risk level, wherein the score is 0-3.0, and the low risk matching can be used; scores of 3.0 to 4.0 are stroke risk matching, and conditional use is performed; scores of 4.0 to 5.0 are medium-high risk matching, and the method is limited in use; a score of 5.0 or more is a high risk match and cannot be used.
Compared with the prior art, the invention has the following advantages:
1. According to the material friction abnormal sound matching method, friction abnormal sound is analyzed through noise data acquisition and loudness processing, friction abnormal sound risk grades are calculated through grading statistics and weighting analysis, and matching suggestions are provided according to the grades;
2. According to the friction abnormal sound risk classification statistical value method, the loudness data is subjected to risk classification, and the classified data is subjected to statistical analysis to obtain a key statistical parameter Si
3. The risk grade of friction abnormal sound is evaluated to obtain Rj value, and risk grade parameter value is calculated by fitting formula R=A, S0+B, S1+C, S2+D.
4. The friction abnormal sound risk level classification method provided by the invention carries out risk analysis on the obtained AR value.
5. According to the method, friction abnormal sound noise data are obtained through test, the data are analyzed and calculated, fitting, grading and risk statistics are calculated on the loudness curve obtained through calculation, and the material friction abnormal sound matching analysis key parameters are obtained according to a weight analysis and evaluation formula, so that a method for accurately judging abnormal sound risks of two parts is formed. According to the method, the matching degree of the friction abnormal sound of the materials under different conditions can be judged through hierarchical division, statistical analysis and weighting evaluation, and a material matching database can be accurately and effectively formed by applying the method disclosed by the invention, so that early data support is provided for the development of the abnormal sound performance of the whole vehicle. In addition, the method can judge and analyze the friction abnormal sound problem of the real vehicle, is convenient for problem cause analysis and subsequent scheme verification, and provides important support for improving the abnormal sound performance of the whole vehicle.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. Like elements or portions are generally identified by like reference numerals throughout the several figures. In the drawings, elements or portions thereof are not necessarily drawn to scale.
FIG. 1 is a flow chart of a method of friction abnormal sound matching of the material of the present invention;
FIG. 2 is an exemplary loudness curve classification and Si calculation of the present invention;
FIG. 3 is a typical low risk loudness curve of the present invention and R values;
FIG. 4 is a graph of risk loudness curves and R values typical of the present invention;
FIG. 5 is a typical high risk loudness curve of the present invention and R values;
Detailed Description
The following embodiments of the present invention will be described in detail with reference to the accompanying drawings, which are only used to more clearly illustrate the technical solution of the present invention, and therefore are only used as examples, and are not to be construed as limiting the scope of the present invention.
It is noted that unless otherwise indicated, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this application belongs.
Example 1
The invention relates to a material friction abnormal sound matching method, which mainly comprises three parts: and (3) carrying out friction abnormal sound test on the material, and carrying out risk analysis and matching degree analysis of the abnormal sound, as shown in figure 1. Examples samples a and B were used for material friction matching.
And the first part of material friction abnormal sound test is used for obtaining noise data by carrying out friction abnormal sound test on the test sample piece pair, and the noise data comprises four steps of processes of m1, m2, m3 and m 4. The test system for testing was an MCTS material matching test stand from MB company.
Step m1, preparing a sample for friction abnormal sound of a material, wherein the sample is required to be cut into standard sizes according to test requirements: sample a25 x 60mm and sample B25 x 25mm, or other prescribed shape dimensions. The surface of the sample is cleaned to prevent the interference of pollutants of non-materials, and the sample is fixed on a test table after preparation.
In the step m2, test conditions are set, temperature and humidity conditions are set to be 23 ℃ and 40% RH, and the vertical load is selected from F1=1N, F2=10N and F3=15N.
And m3, pre-testing, wherein after the test conditions are determined, the temperature and humidity environment is required to be invalid for more than 2 hours, and the pre-testing is carried out.
And m4, collecting data, namely collecting friction abnormal sound data after the pre-test is passed, wherein no external interference noise is ensured during sound collection, and the background noise of the test system is lower than 30dBA.
And carrying out risk analysis on the friction abnormal sound of the second part of material, and calculating a risk classification statistical value to obtain friction risk grade parameters by carrying out loudness analysis on noise data, wherein the friction risk grade parameters comprise five steps of flow of m5, m6, m7, m8 and m 9.
And m5, analyzing the loudness of the data processing, and analyzing the loudness value of the collected sound data to form a time loudness curve.
Loudness calculation formula: the overall loudness is calculated based on octaves (for other methods see ISO 532 for calculation of acoustic loudness level)
St＝Sm+F(∑S-Sm)
Wherein:
st is the overall loudness
Sm is the maximum loudness index
Sigma S is the sum of all band loudness indices; the S value is looked up by looking up an ISO532 loudness index table.
F is the coefficient: the calculation band selection octave f=0.3.
And m6, screening and storing loudness results, and primarily screening the loudness of the test results, if obvious interference noise exists, eliminating the loudness, and repeating m3, m4 and m5 until no abnormality exists, wherein three groups of abnormality-free data are required to be obtained under the same test condition.
And m7, performing curve fitting on the time-loudness data by using the risk classification statistical value Si (i= 0.1.2), setting a risk level 3 (0.5 tone, 1.0 tone and 1.5 tone), and performing integral statistics on the loudness data in the range of 3 levels above 0.5-1.0 tone, 1.0-1.5 tone and 1.5 tone respectively. And integrating the loudness curves of different regions to obtain risk classification statistical values S0, S1 and S2 of the friction abnormal noise, and obtaining the loudness curves and the risk classification statistical values of different vertical forces as shown in figures 3, 4 and 5.
In step m8, the Rj (j=1.2.3) value is analyzed and evaluated, rj represents the risk grade parameter of the abnormal friction noise under the grading statistics of different loudness intervals, rj is obtained by using S0, S1 and S2 values through empirical fitting formula r=a×s0+b×s1+c×s2+d, A, B, C, D is a constant coefficient, and the output results r1=1.0, r2=3.5 and r3=7.0.
And (3) m9, determining the delta (delta is the Rj difference value obtained by the same working condition test) of the Rj value obtained in m8 according to the AR value, if the delta is more than or equal to 1.0, eliminating the data abnormality, returning to m4, and re-obtaining the data, wherein AR= (R1+R2+R3)/3.
And thirdly, analyzing the matching degree of the friction abnormal sound, and comparing the obtained grade parameter R value with a risk grade table to determine the matching degree of the friction abnormal sound of the material, wherein the matching degree comprises an m10 one-step process.
Step m10, performing risk analysis on the risk level of the friction abnormal sound matching of the obtained AR value reference material, wherein the score is 0-3.0 and is divided into low risk matching, and the low risk matching can be used; scores 3.0-4.0 are stroke risk matching, conditional use; scores 4.0-5.0 are medium-high risk matches, limiting use; a score of 5.0 or more is a high risk match and cannot be used. When the force f1=1n according to the calculation result, r1=1.0 belongs to the low risk class and can be used; when the force f2=10n, r2=3.5 belongs to the stroke risk class, and is used conditionally; when the force f3=15n, r3=7.0 belongs to the high risk class and cannot be used.
The friction abnormal sound matching risk grades of the materials are shown in table 1.
Table 1 the friction abnormal sound matching risk level table of the material of the present invention
According to the material friction abnormal sound matching method, friction abnormal sound noise data are obtained through test, analysis and calculation are carried out on the data, fitting, grading and risk statistics calculation are carried out on loudness curves obtained through calculation, key parameters of material friction abnormal sound matching analysis are obtained according to a weight calculation analysis and evaluation formula, and the method for accurately judging abnormal sound risk of two parts is formed. According to the method, the friction abnormal sound matching risk degree of the materials under different conditions can be judged through hierarchical division, statistical analysis and weighting evaluation, and a material matching database can be effectively formed by applying the method disclosed by the invention, so that early data support is provided for the development of the abnormal sound performance of the whole vehicle.
The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the present invention is not limited to the specific details of the above embodiments, and various simple modifications can be made to the technical solution of the present invention within the scope of the technical concept of the present invention, and all the simple modifications belong to the protection scope of the present invention.
In addition, the specific features described in the above embodiments may be combined in any suitable manner, and in order to avoid unnecessary repetition, various possible combinations are not described further.
Moreover, any combination of the various embodiments of the invention can be made without departing from the spirit of the invention, which should also be considered as disclosed herein.
Claims (2)
1. The material friction abnormal sound matching method is characterized by comprising the following steps of:
s1, material friction abnormal sound test: noise data are obtained through friction abnormal sound tests on the test sample;
s2, abnormal sound risk analysis: the friction risk grade parameter is obtained through loudness analysis on noise data and calculation of risk grading statistics;
s3, friction abnormal sound matching degree analysis: comparing the obtained grade parameter R value with a risk grade table to determine the friction abnormal sound matching property of the material;
the abnormal sound risk analysis in step S2 specifically includes the following steps:
step m5, analyzing the loudness of the data processing, namely analyzing the loudness value of the collected sound data through a loudness calculation formula to form a time loudness curve;
step m6, screening and storing loudness results, and primarily screening the loudness of the test results, if obvious interference noise exists, eliminating the loudness, and repeating m3, m4 and m5 until no abnormality exists, wherein three groups of non-abnormal constant data are required to be obtained under the same test condition;
Step m7, calculating a risk classification statistical value Si (i=0, 1 and 2), performing curve fitting on time-loudness data, setting a risk level 3, namely 0.5 tone, 1.0 tone and 1.5 tone, respectively performing integral statistics on loudness data in 3 level ranges of 0.5-1.0 tone, 1.0-1.5 tone and 1.5 tone, and integrating loudness curves in different areas to obtain friction abnormal sound risk classification statistical values S0, S1 and S2;
Step m8, analyzing and evaluating Rj (j=1, 2, 3) values, wherein Rj represents friction abnormal sound risk grade parameters under different loudness interval grading statistics;
step m9, judging the father value of the Rj value obtained in the step m8, wherein the father value is the difference value of Rj obtained by the same working condition test, if the father value is more than or equal to 1.0, the data abnormality is removed and the step m4 is returned to carry out data acquisition again;
The friction abnormal sound matching degree analysis in the step S3 specifically comprises the following steps:
Step m10, calculating an AR value, namely, AR= (R1+R2+R3)/3, performing risk analysis on the obtained AR value reference material friction abnormal sound matching risk level, wherein the score of 0-3.0 is divided into low risk matching, and the low risk matching can be used; scores of 3.0-4.0 are stroke risk matching, and conditional use is performed; scores of 4.0-5.0 are medium-high risk matching, and the method is limited to use; a score of 5.0 or more is high risk matching, and can not be used;
The Rj in the step m8 is obtained by empirical fitting of the values of S0, S1, S2 with the formula r=a×s0+b×s1+c×s2+d, A, B, C, D is a constant coefficient, and the results R1, R2, R3 are output.
2. A material friction abnormal sound matching method as defined in claim 1, wherein,
The friction abnormal sound test of the material in the step S1 specifically comprises the following steps:
Step m1, preparing a material sample with abnormal friction sound, cutting the sample into standard sizes according to test requirements, cleaning the surface of the sample to prevent interference of pollutants other than the material, and fixing the sample on a test table after the sample preparation is finished;
Step m2, setting test conditions, namely setting temperature and humidity conditions and recording the temperature and humidity conditions in a test due to the fact that the friction abnormal sound of the material is related to the environmental temperature and humidity, and setting vertical load and excitation conditions according to test requirements;
Step m3, pre-testing, wherein after the test conditions are determined, the temperature and humidity environment is required to be invalid for more than 2 hours, and the pre-testing is carried out;
And m4, collecting data, namely collecting friction abnormal sound data after the pre-test is passed, wherein no external interference noise is ensured during sound collection, and the background noise of the test system is lower than 30dBA.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010572262.0A CN111798109B (en) | 2020-06-22 | 2020-06-22 | Material friction abnormal sound matching method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010572262.0A CN111798109B (en) | 2020-06-22 | 2020-06-22 | Material friction abnormal sound matching method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111798109A CN111798109A (en) | 2020-10-20 |
| CN111798109B true CN111798109B (en) | 2024-05-07 |
Family
ID=72804607
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010572262.0A Active CN111798109B (en) | 2020-06-22 | 2020-06-22 | Material friction abnormal sound matching method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111798109B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111581743B (en) * | 2020-04-30 | 2022-05-17 | 重庆长安汽车股份有限公司 | Defect risk assessment method based on casting simulation software |
| CN114880301B (en) * | 2022-04-24 | 2024-06-11 | 中国第一汽车股份有限公司 | Abnormal sound database construction method and system for abnormal sound target determination and failure mode accumulation |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1983327A2 (en) * | 2007-04-17 | 2008-10-22 | Kurashiki Kako Co., Ltd. | Abnormal noise inspection method for anti-vibration device for vehicle use |
| CN108507793A (en) * | 2017-02-27 | 2018-09-07 | 华晨汽车集团控股有限公司 | A kind of test and evaluation method of vehicle different sound performance |
| CN109856044A (en) * | 2019-01-21 | 2019-06-07 | 江铃重型汽车有限公司 | A kind of nonmetallic materials abnormal sound evaluation method and its application |
| CN110375995A (en) * | 2019-08-02 | 2019-10-25 | 中国汽车工程研究院股份有限公司 | A kind of scaling method based on friction abnormal sound testing stand horizontal direction exciting |
| CN209961494U (en) * | 2019-07-19 | 2020-01-17 | 中国汽车工程研究院股份有限公司 | Abnormal sound friction test platform motion platform device |
-
2020
- 2020-06-22 CN CN202010572262.0A patent/CN111798109B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1983327A2 (en) * | 2007-04-17 | 2008-10-22 | Kurashiki Kako Co., Ltd. | Abnormal noise inspection method for anti-vibration device for vehicle use |
| CN108507793A (en) * | 2017-02-27 | 2018-09-07 | 华晨汽车集团控股有限公司 | A kind of test and evaluation method of vehicle different sound performance |
| CN109856044A (en) * | 2019-01-21 | 2019-06-07 | 江铃重型汽车有限公司 | A kind of nonmetallic materials abnormal sound evaluation method and its application |
| CN209961494U (en) * | 2019-07-19 | 2020-01-17 | 中国汽车工程研究院股份有限公司 | Abnormal sound friction test platform motion platform device |
| CN110375995A (en) * | 2019-08-02 | 2019-10-25 | 中国汽车工程研究院股份有限公司 | A kind of scaling method based on friction abnormal sound testing stand horizontal direction exciting |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111798109A (en) | 2020-10-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101672690A (en) | Method for objectively and quantifiably evaluating noise fret degree in vehicle based on auditory model | |
| US9058816B2 (en) | Emotional and/or psychiatric state detection | |
| CN111798109B (en) | Material friction abnormal sound matching method | |
| US7437274B2 (en) | Method and apparatus for objective measurement of noise | |
| CN111985788A (en) | Sound quality test and evaluation method for automobile electric device | |
| CN110567575B (en) | Automobile door lock joint sound quality evaluation method | |
| CN112067117A (en) | Method for evaluating automobile wind noise performance | |
| CN110196098B (en) | Heart rate change-based vehicle sound quality evaluation method | |
| Kim et al. | Sound quality evaluation of the impact noise induced by road courses having an impact bar and speed bumps in a passenger car | |
| CN115307721A (en) | Method, device and equipment for evaluating quality of automobile acceleration sound and storage medium | |
| CN111272875A (en) | Apple brittleness nondestructive testing method based on vibration sound signals | |
| Al-Dhahebi et al. | A computational approach for optimizing vehicles’ interior noise and vibration | |
| CN115683318A (en) | Method for evaluating sound quality and determining limit value of driving motor system | |
| CN111855125B (en) | Quantitative evaluation method for automobile door lock closing sound tremor degree | |
| CN114861392A (en) | Method for establishing evaluation model of noise quality of electronic equipment and feedback device | |
| CN113313397A (en) | Sound quality satisfaction degree grading and limit value determining method | |
| KR100354969B1 (en) | Method for assessing sound quality of automobile interior noise | |
| CN113567146A (en) | Method for evaluating road noise based on masking effect | |
| CN113486448A (en) | Method for evaluating transmission squeal based on masking effect | |
| Al-Dhahebi et al. | Genetic and random search algorithms for optimising vehicle interior noise and vibration | |
| Bayani et al. | Analysis of sound characteristics to design an annoyance metric for rattle sounds in the automotive industry | |
| CN113901576A (en) | Objective quantification method for subjective evaluation of warning performance of automobile warning tone | |
| CN118092004B (en) | Impact resistance test method and system for outer screen board of reinforced liquid crystal display | |
| CN114880301B (en) | Abnormal sound database construction method and system for abnormal sound target determination and failure mode accumulation | |
| Wang et al. | Subjective Evaluation of Vehicle Sound Quality |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |