CN113588819A - Quantitative evaluation method for odor of automobile interior part - Google Patents
Quantitative evaluation method for odor of automobile interior part Download PDFInfo
- Publication number
- CN113588819A CN113588819A CN202110849504.0A CN202110849504A CN113588819A CN 113588819 A CN113588819 A CN 113588819A CN 202110849504 A CN202110849504 A CN 202110849504A CN 113588819 A CN113588819 A CN 113588819A
- Authority
- CN
- China
- Prior art keywords
- odor
- typical
- grade
- substances
- level
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 25
- 238000011158 quantitative evaluation Methods 0.000 title claims description 8
- 239000000126 substance Substances 0.000 claims abstract description 85
- 238000011156 evaluation Methods 0.000 claims abstract description 28
- 238000002290 gas chromatography-mass spectrometry Methods 0.000 claims abstract description 10
- 230000002159 abnormal effect Effects 0.000 claims abstract description 9
- 238000004445 quantitative analysis Methods 0.000 claims abstract description 4
- 239000003205 fragrance Substances 0.000 claims description 24
- YXFVVABEGXRONW-UHFFFAOYSA-N Toluene Chemical compound CC1=CC=CC=C1 YXFVVABEGXRONW-UHFFFAOYSA-N 0.000 claims description 15
- 239000007789 gas Substances 0.000 claims description 7
- 238000005070 sampling Methods 0.000 claims description 7
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 6
- 238000010586 diagram Methods 0.000 claims description 5
- 238000007789 sealing Methods 0.000 claims description 5
- 238000012360 testing method Methods 0.000 claims description 5
- 238000003795 desorption Methods 0.000 claims description 4
- 238000013210 evaluation model Methods 0.000 claims description 4
- 238000012544 monitoring process Methods 0.000 claims description 3
- 229910052757 nitrogen Inorganic materials 0.000 claims description 3
- 238000002360 preparation method Methods 0.000 claims description 3
- 238000011002 quantification Methods 0.000 claims description 3
- 238000005457 optimization Methods 0.000 claims description 2
- 238000005086 pumping Methods 0.000 claims description 2
- 230000001502 supplementing effect Effects 0.000 claims description 2
- 230000007794 irritation Effects 0.000 description 4
- 238000001514 detection method Methods 0.000 description 3
- 206010028813 Nausea Diseases 0.000 description 2
- 239000002033 PVDF binder Substances 0.000 description 2
- 239000010985 leather Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000008693 nausea Effects 0.000 description 2
- 229920002981 polyvinylidene fluoride Polymers 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000004817 gas chromatography Methods 0.000 description 1
- 238000001871 ion mobility spectroscopy Methods 0.000 description 1
- 238000004949 mass spectrometry Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012821 model calculation Methods 0.000 description 1
- 230000009965 odorless effect Effects 0.000 description 1
- 230000008447 perception Effects 0.000 description 1
- 229920002620 polyvinyl fluoride Polymers 0.000 description 1
- 238000004451 qualitative analysis Methods 0.000 description 1
- 238000012113 quantitative test Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012764 semi-quantitative analysis Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/62—Detectors specially adapted therefor
- G01N30/72—Mass spectrometers
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0001—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00 by organoleptic means
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
Landscapes
- Chemical & Material Sciences (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Engineering & Computer Science (AREA)
- Food Science & Technology (AREA)
- Medicinal Chemistry (AREA)
- Sampling And Sample Adjustment (AREA)
Abstract
The invention provides a method for quantitatively evaluating the odor of an automotive interior part, which comprises the steps of accurately locking a typical odor substance of a specific part by utilizing GC-O, then quantitatively analyzing the locked odor substance by utilizing GC/MS, fitting a quantitative analysis result of the odor substance and subjective odor rating by comprehensively applying GC-O and GC/MS to establish a model relation, quantitatively and accurately calculating the odor grade of the part by utilizing the typical odor substance of the specific part, solving the problem that the odor evaluation result is influenced by subjective factors of evaluators, improving the accuracy of an odor model, helping to effectively and quickly lock abnormal odor substances, being particularly suitable for improving the odor consistency control evaluation efficiency of the automotive interior part and further improving the quality of the automotive interior part.
Description
Technical Field
The invention belongs to the technical field of odor detection, and particularly relates to an odor detection technology of automobile parts.
Background
With the rapid development of economic society, besides meeting the basic travel requirements, automobiles have higher requirements on driving comfort, particularly on the health quality of air in the automobiles. The smell in the car is the most intuitive health feeling of the customer and is greatly concerned, and a large amount of manpower and material resources are invested in various large car enterprises to carry out related researches so as to ensure that the smell in the car is in an acceptable state. The smell in the car mainly comes from various smell type substances emitted by interior parts.
Chinese patent document CN109212059A discloses a method for detecting odor components in automobile leather, which utilizes a gas chromatograph-mass spectrometry technique to identify the obtained volatile substance samples, so as to obtain qualitative and semi-quantitative data of the volatile substances in the automobile leather samples. The method is only suitable for qualitative and semi-quantitative analysis of volatile substances, cannot identify the types of odor substances, and cannot be associated with odor evaluation grades.
Chinese patent CN107796890A discloses a method for evaluating the source of peculiar smell in an automobile, which comprises the steps of collecting volatile substance samples in the whole automobile and volatile substance samples of various parts after the whole automobile is disassembled, identifying main odor substances by combining a smell and identification tester, and determining the source of peculiar smell and the peculiar smell substances in the automobile by comparison. The method is suitable for tracing the peculiar smell source of specific vehicles and parts, cannot establish an objective quantitative model suitable for the smell of the parts in each vehicle and a smell substance library of each part, cannot be used for fast and accurately identifying the smell of mass-produced parts, cannot be applied to consistency quantitative management and control evaluation, and has limitations.
Chinese patent CN111007176A discloses an in-vehicle odor grade evaluation method based on gas chromatography and ion mobility spectrometry. A set of in-vehicle odor grade evaluation system is formed by combining the subjective odor evaluation grade of personnel with a GC-IMS spectrogram, correspondingly forming a data set by subjective evaluation data and GC-IMS detection data, and performing data iterative training. The data base established by the odor grade system comprises all volatile substances in the collection range, the principle is similar to that of an electronic nose array sensor, the odor grade of the odor grade system is greatly interfered by the content of volatile components (if the content of odorless volatile odor substances is large, the odor grade precision can be influenced), and the method is not based on accurate identification of the odor substances and matching modeling based on the content of the odor substances.
Disclosure of Invention
Aiming at the existing problems, the invention provides a quantitative evaluation method for the odor of the interior parts of the automobile, which solves the problem that the odor evaluation result is influenced by subjective factors of evaluators, improves the accuracy of an odor model, effectively and quickly locks abnormal odor substances, improves the odor consistency control evaluation efficiency of the interior parts of the automobile, and further improves the quality of the interior parts of the automobile.
The technical scheme of the invention is as follows:
the invention provides a quantitative evaluation method for the odor of automobile interior parts, which comprises the following steps:
s01: preparation of part odor samples of different odor grades:
s02: collecting an odor sample: extracting the odor sample from the odor bag through the collection tube to make the substance adsorbed in the collection tube;
s03: performing subjective odor rating on the odor sample of the part by an odor evaluator to obtain the subjective odor grade of the sample;
s04: identifying typical odorants: placing the sample collection tube on a GC-O thermal desorption device, and identifying typical odor substances of the parts by at least 3 professional odor evaluators through the olfactory identification of an olfactory discrimination tester; meanwhile, respectively quantifying typical odor substances based on a toluene quantitative standard curve;
S05: establishing a typical odor substance and odor grade fitting model: carrying out curve fitting on the quantitative relation of the typical odor substances and the subjective evaluation grade of the odor, and establishing a fitting model;
s06: optimizing the fitting model: the method comprises the steps of calculating objective odor grade results of newly added samples through an odor fitting model by increasing the number of similar samples, comparing the objective odor grade results with actual subjective odor evaluation results of the newly added samples to obtain fitting model accuracy, and continuously supplementing a data optimization model until the accuracy reaches a set standard;
s07: and quantitatively testing the smell of the parts in the vehicle.
Further, the step S01 is specifically: and (3) putting the same type of parts into a smell bag, pumping out redundant air in the bag, filling high-purity nitrogen into the smell bag, sealing and carrying out constant temperature treatment, and obtaining part smell samples with different smell grades by adjusting constant temperature, standing time and the like.
Further, the step S02 is specifically: extracting the odor sample from the odor bag through the collection tube to make the substance adsorbed in the collection tube;
further, the step S03 is specifically: after the odor sample is collected, the gas in the bag is subjectively graded by at least 3 professional odor raters in a blind grading mode to obtain the subjective odor grade of the sample.
Further, in step S04, the odorant intensity evaluation of the olfactory recognition tester is divided into 4 levels, which are 1 level, 2 level, 3 level and 4 level in sequence from weak to strong according to the odorant intensity of the olfactory recognition tester, and the evaluators evaluate all the odorant with the odorant intensity of 2 level and above as the typical odorant of the component as the basis of subsequent modeling, wherein the odorant level of the olfactory recognition link is set according to the odorant intensity of subjective perception during olfactory recognition, and the odorant level of 1 level to 4 level are weak odorant, easily perceivable odorant, clearly perceivable odorant and strong odorant in sequence.
Further, the step S05 is specifically: the typical odor substances identified at S04 were quantitatively calculated separately based on a standard curve for toluene quantification, the amount of each substance being calculated as xnMeasuring, quantifying x for each typical odor substancenAnd performing curve fitting with the subjective odor grade (y) evaluated in the S03, selecting a model to establish a fitting relation, and obtaining the fitting relation to be used as a quantitative odor evaluation model.
Further, the step S06 is: and in addition, selecting a plurality of similar parts to operate according to S01, S02 and S05 respectively, substituting the obtained content of typical odor substances in S05 into an S05 odor quantitative evaluation model to calculate, taking the closest 0.5 grade as a final result of the calculated odor grade result, comparing and verifying the odor grade with the S03 subjective evaluation result, if the accuracy of the fitting calculation of the selected parts reaches a set standard, successfully establishing the model, if the accuracy of the fitting calculation of the selected parts does not reach the set standard, continuing increasing the sample size, repeating S01-S05, and improving the accuracy of the model until the accuracy reaches the standard.
Further, the step S07 is specifically: according to the parts to be evaluated, an established odor quantitative evaluation model of the parts is selected, and the odor grade is calculated through sampling and quantitative analysis and the content of various typical odor substances and is applied to daily odor consistency monitoring tests.
According to the scheme, the typical odor substances of the specific parts are accurately locked by using the GC-O, then the locked odor substances are quantitatively analyzed by using the GC-MS, the GC-O and the GC-MS are comprehensively applied to fit the quantitative analysis results of the odor substances and the subjective odor rating to establish a model relation, so that the odor grade of the parts is quantitatively and accurately calculated through the typical odor substances of the specific parts, the problem that the odor evaluation results are affected by subjective factors of evaluators can be solved, the accuracy of the odor model is improved, meanwhile, the abnormal odor substances can be effectively and quickly locked, and the method is particularly suitable for improving the odor consistency control evaluation efficiency of the parts in the automobile and further improving the quality of the parts in the automobile.
Drawings
FIG. 1 is a flow chart of a method for quantitatively evaluating odor of parts in a vehicle
FIG. 2 exemplary odorant determination schematic
FIG. 3 is a graph showing the content range of typical odorants in the corresponding odor classes
Detailed Description
In order to make the technical problems, technical solutions and advantages of the present invention more apparent, the following detailed description is given with reference to the accompanying drawings and specific embodiments. In the following description, specific details such as specific configurations and components are provided only to help the full understanding of the embodiments of the present invention. Thus, it will be apparent to those skilled in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the invention. In addition, descriptions of well-known functions and constructions are omitted for clarity and conciseness.
As shown in fig. 1, the present embodiment provides a method for quantitatively evaluating odor of an automotive interior part, including the following steps:
s01: preparation of part odor samples of different odor grades:
the same type of interior parts (such as a single seat) are selected, the sample amount of each part is not less than 10, the parts are not required to be packaged and coated without pollution, and the state composition is consistent with the actual state.
Respectively placing the parts into corresponding odor bags containing polyvinylidene fluoride (PVF), if a 500L sampling bag is placed in a single seat, sealing the bag by using a special sealing strip, extracting redundant air in the bag, filling high-purity nitrogen with the volume of about 60%, placing the bag into a constant temperature box, and carrying out constant temperature treatment;
Different odor grade gradients of the same parts are established by adjusting different temperature gradients (room temperature, 40 ℃, 60 ℃ and 80 ℃) and time gradients (1h, 2h and 4h) (for example, the parts are kept for 1h in a sealed manner under the condition of room temperature, 1h in a sealed manner under the condition of 40 ℃, 2h in a sealed manner under the condition of 60 ℃, 4h in a sealed manner under the condition of 60 ℃, 2h in a sealed manner under the condition of 80 ℃, 4h in a sealed manner under the condition of 80 ℃ and the like, so that the odor grade of the sample covers 2.0-4.0 grades according to the difference of 0.5 grade of subjective evaluation, and part of parts with higher odor grade (such as sealing strips and the like) covers 3.0-5.0 grades.
S02: collecting a smell sample;
at least 3 gas outlet valves on the odor bag are respectively led out by a polyvinyl fluoride catheter, the odor bag is sequentially connected with an odor sample collection pipe and an atmosphere sampling pump, the 3 atmosphere sampling pumps are simultaneously started to collect gas with a fixed volume at a certain speed (for example, the gas is collected at the flow rate of 400ml/min for 30min, and the total sampling volume is 12L), the odor sample is extracted from the odor bag, and volatile substances are adsorbed in the collection pipe, so that at least 3 sample collection pipes adsorbing the odor substances are obtained;
s03: the odor evaluator subjectively rates the odor of the part sample:
after the odor sample is collected, the odor bag is taken out of the incubator, at least 3 professional odor evaluators subjectively rate the gas in the bag in a blind evaluation mode, the mode of evaluation results is used as the subjective odor grade of the sample, and the evaluation rules are as follows:
| Strength grade | Description of the |
| 1 | No smell is sensed and no smell is produced |
| 1.5 | The odor is barely sensed and the odor type is difficult to distinguish |
| 2 | The presence of odor can be sensed |
| 2.5 | Can obviously sense smell without |
| 3 | Can be used for the treatment of odor and slight irritation |
| 3.5 | Can obviously sense the smell and has |
| 4 | Obvious unpleasant odor and irritation |
| 4.5 | Strong pungent odor |
| 5 | Strong pungent odor, nausea |
| 5.5 | Strong thornsPungent odor, |
| 6 | Cannot tolerate |
S04: identifying a typical odorant;
firstly, carrying out olfactory discrimination analysis on 3 sample collection tubes of samples with the highest subjective rating of odor samples in S03, placing the sampling tubes on a GC-O thermal desorption device, desorbing odor substances into GC/MS (gas chromatography/mass spectrometry) through thermal desorption, and subjectively identifying and determining typical odor substances of the parts through an olfactory discrimination tester of GC-0 by 3 professional odor evaluators respectively.
The odor substance strength evaluation of the olfactory discrimination tester is divided into 4 grades, the grades are 1 grade, 2 grade, 3 grade and 4 grade according to the odor intensity from weak to strong, and the evaluators evaluate all the substances with the odor intensity of 2 grade and above as the typical odor substance of the part as the subsequent modeling basis, such as: when 10 kinds of odor substances are identified in a certain part of a certain vehicle through olfactory discrimination and evaluation, wherein 5 kinds of substances with 2 grades and above are selected, and the rest 5 kinds are 1 grades with lower odor intensity, the front 5 kinds are selected as typical odor substances of the part (as shown in figure 2). The remaining sample odorants having a lower subjective rating for the odorant sample in S03 were also modeled using the 5 representative odorants.
S05: establishing a typical odor substance and odor grade fitting model:
the typical odor substances identified at S04 were quantitatively calculated separately based on a standard curve for toluene quantification (amount of each substance in x)nMeter), each typical odorant was quantified x using a tool such as MatlabnPerforming curve fitting with the subjective grade (y) of the odor evaluated in the S03, and selecting a proper model to establish a fitting relation to obtain the fitting relation, wherein the fitting relation is as follows and is used as a quantitative odor evaluation model (taking 5 typical odor substances as examples):
ax1+bx2+cx3+dx4+ex5＝y
xn: quantitative value of each typical odor substance;
y: odor rating.
S06: optimizing the fitting model:
and selecting at least 5 similar parts to operate according to S01, S02 and S04 respectively, substituting the obtained typical odor substance content in S05 into an S05 fitting formula to calculate, taking the nearest 0.5 grade as a final result (for example, if the odor grade y is calculated to be 2.12, the odor grade is 2.0 grade, and the odor grade y is calculated to be 2.42, the odor grade is 2.5 grade), comparing and verifying the odor grade with the S03 subjective evaluation result, if the fitting calculation accuracy of at least 5 selected parts reaches 90% or more, successfully establishing the model, if the fitting calculation accuracy of the parts is not enough, continuing to increase the sample amount, and repeating S01-S05 to improve the model accuracy until the accuracy reaches 90% or more.
Meanwhile, a content range diagram of each typical odor substance of the part at different odor levels is established, and the range diagram shows the content range of each odor level, the number of the typical odor substances of a certain part, and the lowest value and the highest value range of each substance. For example: at odor level 3.0, there are 5 typical odor substances for a part, each substance having a minimum and maximum range of values, respectively, see fig. 3.
S07: the odor quantitative test application of the parts in the vehicle comprises the following steps:
selecting an established quantitative odor evaluation model according to the parts to be evaluated, directly identifying the contents of various typical substances by a GC/MS (gas chromatography/mass spectrometry) of the odor acquisition sample tube, substituting the contents into the model to calculate the odor grade (taking the closest 0.5 grade as a final result), and applying the odor grade to daily odor quality monitoring tests; if the odor level is abnormal, such as exceeding the standard, the abnormal substance can be quickly identified by analyzing the deviation of the typical odor substance content in a certain odor level by using the graph 3 in S06, and the abnormal substance can be locked as the abnormal substance beyond the maximum range of the certain odor typical substance in the certain odor level. For example: the odor grade of a certain part is 3.0 grade, and the grade is 3.5 grade through model calculation, so that the overproof substances can be quickly locked through the content range diagram of each substance with the odor of the part of 3.0 grade.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. A method for quantitatively evaluating the odor of an automobile interior part is characterized by comprising the following steps:
s01: preparation of part odor samples of different odor grades:
s02: collecting an odor sample: extracting the odor sample from the odor bag through the collection tube to make the substance adsorbed in the collection tube;
s03: performing subjective odor rating on the odor sample of the part by an odor evaluator to obtain the subjective odor grade of the sample;
s04: identifying typical odorants: placing the sample collection tube on a GC-O thermal desorption device, and identifying typical odor substances of the parts by at least 3 professional odor evaluators through the olfactory identification of an olfactory discrimination tester; simultaneously, respectively quantifying typical odor substances by utilizing GC/MS based on a toluene quantitative standard curve;
s05: establishing a typical odor substance and odor grade fitting model: carrying out curve fitting on the quantitative relation of the typical odor substances and the subjective evaluation grade of the odor, and establishing a fitting model;
S06: optimizing the fitting model: by increasing the number of similar samples, calculating objective odor grade results of the newly added samples through an odor fitting model, comparing the objective odor grade results with actual subjective odor evaluation results of the newly added samples, obtaining fitting model accuracy through calculating a proportion with completely consistent grades, and continuously supplementing a data optimization model until the accuracy reaches a set standard;
s07: and quantitatively testing the smell of the parts in the vehicle.
2. The method for quantitatively evaluating the odor of an automobile interior part according to claim 1, wherein the step S01 is specifically: and (3) putting the same type of parts into a smell bag, pumping out redundant air in the bag, filling high-purity nitrogen into the smell bag, sealing and carrying out constant temperature treatment, and obtaining part smell samples with different smell grades by adjusting constant temperature, standing time and the like.
3. The method for quantitatively evaluating the odor of an automobile interior part according to claim 1, wherein the step S02 is specifically: the odor sample is drawn from the odor bag through the collection tube, causing the substance to be adsorbed within the collection tube.
4. The method for quantitatively evaluating the odor of an automobile interior part according to claim 1, wherein the step S03 is specifically: after the odor sample is collected, the gas in the bag is subjectively graded by at least 3 professional odor raters in a blind grading mode to obtain the subjective odor grade y of the sample.
5. The method for quantitatively evaluating the odor of an automobile interior part according to claim 1, wherein in step S04, the odorant intensity evaluation of the olfactory tester is divided into 4 levels, the odorant intensity evaluation is sequentially 1 level, 2 level, 3 level and 4 level from weak to strong, and all substances with odor intensity of 2 level or more are evaluated by an evaluator as a typical odorant of the part as a basis for subsequent modeling, wherein the odor level of the olfactory tester is set according to the odor intensity subjectively sensed during olfactory discrimination, and the odor level of 1 level to 4 level is sequentially weak odor, easily perceived odor, clearly perceived odor and strong odor.
6. The method for quantitatively evaluating the odor of an automobile interior part according to claim 1, wherein the step S05 is specifically: the typical odor substances identified at S04 were individually quantified based on a standard curve for GC/MS toluene quantification, each substance in amounts of xnMeasuring, quantifying x for each typical odor substancenAnd performing curve fitting with the subjective odor grade y evaluated in the S03, selecting a model to establish a fitting relation, and obtaining the fitting relation to be used as a quantitative odor evaluation model.
7. The method for quantitatively evaluating the odor of an automobile interior part according to claim 1, wherein the step S06 is: and in addition, selecting a plurality of similar parts to operate according to S01, S02 and S05 respectively, substituting the obtained content of typical odor substances in S05 into an odor quantitative evaluation model fitted by S05 to calculate, taking the closest 0.5 grade as a final result of the calculated objective odor grade result, comparing and verifying the objective odor grade with the S03 subjective evaluation result, if the accuracy of the fitting calculation of the selected parts reaches a set standard, successfully establishing the model, if the accuracy of the fitting calculation of the selected parts does not reach the set standard, continuing increasing the sample size, repeating the S01-S05, and increasing the accuracy of the model until the accuracy reaches the standard.
8. The method for quantitatively evaluating the odor of an automobile interior part as claimed in claim 1, wherein the step S06 further comprises establishing a content range diagram of each typical odor substance of the part at different odor levels, wherein the range diagram shows the number of the typical odor substances of a certain part at each odor level, and the lowest value and highest value ranges of each substance.
9. The method for quantitatively evaluating the odor of an automobile interior part according to claim 1, wherein the step S07 is specifically: according to the parts to be evaluated, an established odor quantitative evaluation model of the parts is selected, and the odor grade is calculated through sampling and quantitative analysis and the content of various typical odor substances and is applied to daily odor consistency monitoring tests.
10. The method for quantitatively evaluating the odor of an automobile interior part according to claim 7 or 8, wherein the step S07 further comprises, when the odor level is detected to be abnormal, using the content range map of typical odor substances of the part at different odor levels established in S06, by analyzing the deviation of the content of the typical odor substances at a certain odor level, the odor substances beyond the maximum range of the certain odor typical substances at the certain odor level can be locked as abnormal substances.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110849504.0A CN113588819A (en) | 2021-07-27 | 2021-07-27 | Quantitative evaluation method for odor of automobile interior part |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110849504.0A CN113588819A (en) | 2021-07-27 | 2021-07-27 | Quantitative evaluation method for odor of automobile interior part |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113588819A true CN113588819A (en) | 2021-11-02 |
Family
ID=78250296
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110849504.0A Pending CN113588819A (en) | 2021-07-27 | 2021-07-27 | Quantitative evaluation method for odor of automobile interior part |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113588819A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114235537A (en) * | 2022-02-25 | 2022-03-25 | 中汽研汽车零部件检验中心(宁波)有限公司 | Method for simulating typical odor substance of automobile material |
| CN114324781A (en) * | 2022-03-11 | 2022-04-12 | 中汽研汽车零部件检验中心(宁波)有限公司 | Intelligent sniffing method and system |
| CN114487223A (en) * | 2022-01-19 | 2022-05-13 | 青岛科大新橡塑检测服务有限公司 | Method for measuring VOC content in EPS foam |
| CN115290784A (en) * | 2022-08-03 | 2022-11-04 | 南京中车浦镇城轨车辆有限责任公司 | Method for determining unpleasant odor substances in vehicle |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130219991A1 (en) * | 2012-02-14 | 2013-08-29 | The Regents Of The University Of California | Gas chromatography recomposition-olfactometry for characterization of aroma mixtures |
| CN104297434A (en) * | 2014-10-29 | 2015-01-21 | 重庆长安汽车股份有限公司 | Odor evaluation method for automotive interior parts |
| CN107796890A (en) * | 2017-10-23 | 2018-03-13 | 奇瑞汽车股份有限公司 | Peculiar smell source appraisal procedure in a kind of Automobile of man-computer cooperation |
| JP2018063232A (en) * | 2016-02-05 | 2018-04-19 | 株式会社カネカテクノリサーチ | Method of manufacturing imitated-odor composition |
| CN109212059A (en) * | 2018-08-30 | 2019-01-15 | 上海应用技术大学 | A kind of detection method of automobile leather odour component |
| CN110531018A (en) * | 2019-09-20 | 2019-12-03 | 通标标准技术服务(上海)有限公司 | A kind of pocket type method direct injected GC-O/MS test macro and its test method |
| CN111007176A (en) * | 2019-12-26 | 2020-04-14 | 冲之智能科技(天津)有限公司 | In-vehicle odor grade evaluation method based on gas chromatography and ion mobility spectrometry |
| CN111241458A (en) * | 2019-12-25 | 2020-06-05 | 中汽研汽车检验中心（天津）有限公司 | Method for tracing odor in vehicle through multi-factor coupling analysis |
| CN111693649A (en) * | 2020-06-08 | 2020-09-22 | 中汽研汽车零部件检验中心(宁波)有限公司 | Odor evaluation method for automobile part material by threshold method |
| CN111724868A (en) * | 2020-05-06 | 2020-09-29 | 嘉兴汇智诚电子科技有限公司 | VOC (volatile organic compound) odor rating model and optimization method |
| CN112285296A (en) * | 2020-11-11 | 2021-01-29 | 重庆长安汽车股份有限公司 | Automobile interior part smell evaluation method based on electronic nose |
-
2021
- 2021-07-27 CN CN202110849504.0A patent/CN113588819A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130219991A1 (en) * | 2012-02-14 | 2013-08-29 | The Regents Of The University Of California | Gas chromatography recomposition-olfactometry for characterization of aroma mixtures |
| CN104297434A (en) * | 2014-10-29 | 2015-01-21 | 重庆长安汽车股份有限公司 | Odor evaluation method for automotive interior parts |
| JP2018063232A (en) * | 2016-02-05 | 2018-04-19 | 株式会社カネカテクノリサーチ | Method of manufacturing imitated-odor composition |
| CN107796890A (en) * | 2017-10-23 | 2018-03-13 | 奇瑞汽车股份有限公司 | Peculiar smell source appraisal procedure in a kind of Automobile of man-computer cooperation |
| CN109212059A (en) * | 2018-08-30 | 2019-01-15 | 上海应用技术大学 | A kind of detection method of automobile leather odour component |
| CN110531018A (en) * | 2019-09-20 | 2019-12-03 | 通标标准技术服务(上海)有限公司 | A kind of pocket type method direct injected GC-O/MS test macro and its test method |
| CN111241458A (en) * | 2019-12-25 | 2020-06-05 | 中汽研汽车检验中心（天津）有限公司 | Method for tracing odor in vehicle through multi-factor coupling analysis |
| CN111007176A (en) * | 2019-12-26 | 2020-04-14 | 冲之智能科技(天津)有限公司 | In-vehicle odor grade evaluation method based on gas chromatography and ion mobility spectrometry |
| CN111724868A (en) * | 2020-05-06 | 2020-09-29 | 嘉兴汇智诚电子科技有限公司 | VOC (volatile organic compound) odor rating model and optimization method |
| CN111693649A (en) * | 2020-06-08 | 2020-09-22 | 中汽研汽车零部件检验中心(宁波)有限公司 | Odor evaluation method for automobile part material by threshold method |
| CN112285296A (en) * | 2020-11-11 | 2021-01-29 | 重庆长安汽车股份有限公司 | Automobile interior part smell evaluation method based on electronic nose |
Non-Patent Citations (5)
| Title |
|---|
| 张云娟等: "前壁板隔音件气味提升研究", 《汽车工艺与材料》 * |
| 王焰孟等: "PP类材料气味改善提升方法研究", 《天津科技》 * |
| 王焰孟等: "成分分析及GC-O耦合联用对座椅坐垫材料气味评价与改善的实验探索", 《天津科技》 * |
| 王鑫等: "基于GC-O和OAV方法的前壁板隔音垫气味物质研究", 《汽车零部件》 * |
| 许双英等: "气相色谱-质谱/嗅辩在整车气味溯源中的应用研究", 《汽车工艺与材料》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114487223A (en) * | 2022-01-19 | 2022-05-13 | 青岛科大新橡塑检测服务有限公司 | Method for measuring VOC content in EPS foam |
| CN114235537A (en) * | 2022-02-25 | 2022-03-25 | 中汽研汽车零部件检验中心(宁波)有限公司 | Method for simulating typical odor substance of automobile material |
| CN114235537B (en) * | 2022-02-25 | 2022-08-09 | 中汽研汽车零部件检验中心(宁波)有限公司 | Method for simulating typical odor substance of automobile material |
| CN114324781A (en) * | 2022-03-11 | 2022-04-12 | 中汽研汽车零部件检验中心(宁波)有限公司 | Intelligent sniffing method and system |
| CN114324781B (en) * | 2022-03-11 | 2022-12-02 | 中汽研汽车零部件检验中心(宁波)有限公司 | Intelligent sniffing method and system |
| CN115290784A (en) * | 2022-08-03 | 2022-11-04 | 南京中车浦镇城轨车辆有限责任公司 | Method for determining unpleasant odor substances in vehicle |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113588819A (en) | Quantitative evaluation method for odor of automobile interior part | |
| CN108918691B (en) | Method for determining odor substances in vehicle and method for tracing odor substances in vehicle | |
| CN103134850B (en) | A kind of tea leaf quality method for quick based on characteristic perfume | |
| CN111007176A (en) | In-vehicle odor grade evaluation method based on gas chromatography and ion mobility spectrometry | |
| CN110441423A (en) | A kind of method and its system measuring grain fragrance component | |
| CN110763775A (en) | Method for calculating odor concentration of composite gas | |
| CN108760913B (en) | Atmospheric odor pollution traceability system and application | |
| CN109521127B (en) | Qualitative and quantitative analysis method for evaluating odor of single odor substance | |
| CN101470121A (en) | Built-in bionic smell recognition method and device | |
| CN109959748A (en) | It is a kind of car emphasis odoring substance and the high-risk components of smell determine method | |
| CN105469224A (en) | Odor pollution source key odor causing substance recognition method | |
| CN111766328A (en) | Method for detecting odor source in vehicle | |
| CN109637143B (en) | Improved travel time reliability analysis method | |
| CN111781292A (en) | Urine proteomics spectrogram data analysis system based on deep learning model | |
| CN109297534B (en) | Environmental parameter weight determination method and system for evaluating indoor environmental quality | |
| JP3707010B2 (en) | General-purpose multicomponent simultaneous identification and quantification method in chromatograph / mass spectrometer | |
| CN113899823A (en) | Rail vehicle product pleasure degree evaluation and prediction method | |
| CN113340943B (en) | Method for analyzing odor type and odor intensity in water body based on fingerprint | |
| CN108533254A (en) | Reservoir hydrocarbons water layer logging parameters Dominated Factors weight analysis method | |
| Bax et al. | Real-time monitoring of odour concentration at a landfill fenceline: performance verification in the field | |
| CN111241458A (en) | Method for tracing odor in vehicle through multi-factor coupling analysis | |
| CN110836941A (en) | Method for tracing odor in rail transit vehicle | |
| CN112285296A (en) | Automobile interior part smell evaluation method based on electronic nose | |
| CN211877911U (en) | Portable electronic nose system for evaluating odor grade of automotive interior material | |
| CN101021495A (en) | Method for distinguishing petroleum products variety |
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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20211102 |