CN110095429A - A kind of product oil method for quickly detecting quality - Google Patents
A kind of product oil method for quickly detecting quality Download PDFInfo
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- CN110095429A CN110095429A CN201910358718.0A CN201910358718A CN110095429A CN 110095429 A CN110095429 A CN 110095429A CN 201910358718 A CN201910358718 A CN 201910358718A CN 110095429 A CN110095429 A CN 110095429A
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- 238000000034 method Methods 0.000 title claims abstract description 31
- 238000005259 measurement Methods 0.000 claims abstract description 23
- 230000003595 spectral effect Effects 0.000 claims abstract description 14
- 238000001228 spectrum Methods 0.000 claims abstract description 11
- 238000001514 detection method Methods 0.000 claims abstract description 9
- 238000004611 spectroscopical analysis Methods 0.000 claims abstract description 7
- 238000000862 absorption spectrum Methods 0.000 claims abstract description 5
- 239000011521 glass Substances 0.000 claims abstract description 4
- LFQSCWFLJHTTHZ-UHFFFAOYSA-N Ethanol Chemical compound CCO LFQSCWFLJHTTHZ-UHFFFAOYSA-N 0.000 claims description 4
- 238000012937 correction Methods 0.000 claims description 4
- 229960000935 dehydrated alcohol Drugs 0.000 claims description 4
- 239000000126 substance Substances 0.000 claims description 4
- 238000010521 absorption reaction Methods 0.000 claims description 3
- 238000002512 chemotherapy Methods 0.000 claims description 3
- 239000000446 fuel Substances 0.000 claims description 3
- 238000002347 injection Methods 0.000 claims description 3
- 239000007924 injection Substances 0.000 claims description 3
- 230000002452 interceptive effect Effects 0.000 claims description 3
- 239000000463 material Substances 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 claims description 3
- 239000000203 mixture Substances 0.000 claims description 3
- 239000010453 quartz Substances 0.000 claims description 3
- 238000007430 reference method Methods 0.000 claims description 3
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N silicon dioxide Inorganic materials O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 claims description 3
- 238000012353 t test Methods 0.000 claims description 3
- 238000010998 test method Methods 0.000 claims description 3
- 238000004821 distillation Methods 0.000 description 3
- RTZKZFJDLAIYFH-UHFFFAOYSA-N Diethyl ether Chemical compound CCOCC RTZKZFJDLAIYFH-UHFFFAOYSA-N 0.000 description 2
- 238000004140 cleaning Methods 0.000 description 2
- 239000002283 diesel fuel Substances 0.000 description 2
- 238000013210 evaluation model Methods 0.000 description 2
- 239000003502 gasoline Substances 0.000 description 2
- 238000007689 inspection Methods 0.000 description 2
- 239000007788 liquid Substances 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 238000004497 NIR spectroscopy Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 239000000356 contaminant Substances 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000001035 drying Methods 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 230000002650 habitual effect Effects 0.000 description 1
- 125000004435 hydrogen atom Chemical group [H]* 0.000 description 1
- 238000002329 infrared spectrum Methods 0.000 description 1
- 239000003921 oil Substances 0.000 description 1
- 230000010355 oscillation Effects 0.000 description 1
- 239000003208 petroleum Substances 0.000 description 1
- 238000000513 principal component analysis Methods 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 239000000243 solution Substances 0.000 description 1
- 238000002604 ultrasonography Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N1/00—Sampling; Preparing specimens for investigation
- G01N1/28—Preparing specimens for investigation including physical details of (bio-)chemical methods covered elsewhere, e.g. G01N33/50, C12Q
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3577—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing liquids, e.g. polluted water
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- Physics & Mathematics (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
The invention discloses a kind of product oil method for quickly detecting quality, relate generally to detection technique field, near infrared spectrometer absorption spectrum is set, near infrared spectrometer is put into sample cell, using air as reference, acquire background spectrum, with in glass dropper pipette samples merging sample cell, measure the spectrum of sample, using PLS method, establish the calibration model of every quality index and spectroscopic data relationship, spectroscopic data using sample and the calibration model established, measure the mahalanobis distance and items quality index of sample and calibration set sample, and report measurement result, it will be compared specified in product oil items quality index and product standard, this detection method is suitable for the field of circulation and the product oil of storage location quickly detects, and it realizes and utilizes quick measurement of the spectral information to a variety of quality index of sample to be tested.
Description
Technical field
The invention mainly relates to detection technique field, specifically a kind of product oil method for quickly detecting quality.
Background technique
After oil plant produces finished industrial product diesel oil, gasoline, oil product can constantly circulate, and can just sell away, and circulate process
Including transfers processes such as pipeline transportation, oil product storage, vehicle transport, ship transportations.Although oil product has stringent inspection when dispatching from the factory
Program, but during these transfers, it might have introduced contaminants or foreign matter be mixed into oil product, therefore, sale responsible organizations at different levels
It needs to test to oil product, just can guarantee the quality of sale oil product.Conventional oil product check system is exactly to sample, steamed
Evaporate, using the end point of distillation of gasoline and 95% recovery point of diesel oil as index, measurement when oil product is substantially all distill when, oil product distillation
The maximum temperature that temperature reaches.In existing oil product checked operation device, each sections such as sampling, distillation, temperature data acquisition are point
From, for the linking between each section completely by artificial control, whole operation process compares time and effort consuming, the inspection from standard, science
Testing operating process still has certain gap；In addition, temperature data is measured using mercurial thermometer, read by human eye, then artificial note
Record acquisition, measurement result are influenced by many subjective factors such as habitual posture, the responds of people, and accuracy of data acquisition is caused to compare
It is low.
Summary of the invention
In view of the deficiencies in the prior art and defect, the present invention provides a kind of quick sides of detection of finished product oil quality
Method.
In order to solve the above-mentioned technical problem, the present invention adopts the following technical scheme:
A kind of product oil method for quickly detecting quality, it is characterised in that: including,
Step 1: the measurement pattern that the spectral measurement of near infrared spectrometer is arranged is absorption spectrum, and spectral region is
4400cm-1~8800cm-1, spectral resolution 2cm-1, wave number repeatability 0.05cm-1,
Step 2: being put into sample cell near infrared spectrometer, using air as reference, acquires background spectrum,
Step 3: being placed in sample cell with glass dropper pipette samples, and ensures three molecules two and nothing full of sample cell
Bubble exists, and sample injection rate should not be less than 1mL, measures the spectrum of sample,
Step 4: using PLS method, using chemo metric software, establishes every quality index and spectroscopic data relationship
Calibration model needs to detect and delete two classes out-of-bounds point in calibration model establishment process,
The first kind, which is out-of-bounds put, refers to that the sample has extreme chemical composition, to model performance compared with remaining sample of calibration set
It seriously affects, such, which is out-of-bounds put, can be differentiated and be rejected by mahalanobis distance (MD), deleted mahalanobis distance (D2) and be greater than 3k/
The sample of n, wherein n is correcting sample number, and k is PLS number of main factor,
Wherein tiThe principal component scores of i sample are concentrated for calibration samples,For the average vector of principal component scores T,
TcentFor the mean value centralization matrix of principal component scores T, MDiFor the mahalanobis distance of calibration set sample i,
Second class, which is out-of-bounds put, refers between the reference data of sample and model predication value there is statistical significance difference, can pass through
Raw (t) is examined, and deleting t is more than regulation freedom degree (n-k, if mean value centralization is handled, for the sample of the t theoretical value of n-k-1)
Product,
In formula: tiFor the t test value of calibration set sample i, eiThe predicted value of-calibration set sample i and the difference of reference data
Value,
Step 5: using SEC (calibration standard error) come evaluation model performance,
yiI-th of samples Reference method measured value of-calibration set is surveyed according to test method as defined in finished oil product standard
Every quality index of fixed all kinds of fuel correction collection and verifying collection sample；
The index predicted value of i-th of sample of-calibration set；
N-correcting sample number；
Step 5: using spectroscopic data and the calibration model established of sample, the horse of sample and calibration set sample is measured
Family name's distance and every quality index.If sample mahalanobis distance has been more than the range of model, which belongs to the first kind out-of-bounds
Point, measurement result cannot use, and need to measure using with reference to method.If sample mahalanobis distance is in model scope, this matter
Figureofmerit can use, and report measurement result.
Step 6: it will be compared specified in product oil items quality index and product standard.
As a further improvement of the present invention, to obtain good signal-to-noise ratio, the scanning times of near infrared spectrometer are many
In 32 times, scanning speed is no less than 5 times/second.
As a further improvement of the present invention, near infrared spectrometer, which is equipped with, has the dynamic of plane mirror electromagnetic drive interference function
State collimates interferometer, eliminates temperature and vibration bring measurement error.
As a further improvement of the present invention, it is absorption cell that the sample cell, which selects quartz material 5mm light path sample feeding pipe, is
It prevents sample room from interfering, needs to change new sample feeding pipe after the completion of detection every time, used sample feeding pipe, which can be put into dehydrated alcohol, to be soaked
Bubble, and cleaned in time to reuse.
As a further improvement of the present invention, sample before detection should be constant at 15 DEG C~27 DEG C of room temperature.
Compared with prior art, the device have the advantages that are as follows: this detection method be suitable for the field of circulation and storage
The product oil in place quickly detects, and realizes and utilize quick measurement of the spectral information to a variety of quality index of sample to be tested.
Specific embodiment
In order to which technical solution of the present invention and beneficial effect are more clearly understood, combined with specific embodiments below to the present invention
It is described in further detail, it should be understood that the specific embodiments described herein are only used for understanding the present invention, and do not have to
Of the invention, the every other implementation obtained by those of ordinary skill in the art without making creative efforts in limiting
Example, shall fall within the protection scope of the present invention.
Near infrared spectroscopy is the frequency multiplication using the stretching vibration containing hydrogen group (X-H, X are as follows: C, O, N etc.) chemical bond
And sum of fundamental frequencies, the absorption spectrum near infrared region is obtained in a manner of transmission or reflection, by principal component analysis, Partial Least Squares with
And the Modern Chemometrics method such as artificial neural network, establish the linearly or nonlinearly relationship between spectrum and quality index
(calibration model), to realize the quick measurement using spectral information to a variety of quality index of sample to be tested.
Near infrared spectrometer is ft-nir spectrometer, and the near infrared spectrometer of selection should meet GB/T
21186 require.The effective wavelength section of near infrared spectrum includes 12800-3800cm-1, and spectral resolution is better than 2cm-1, wave number
Accuracy is better than ± 0.03cm-1, and wave number repeatability is better than 0.05cm-1, and scanning speed is better than 5 times/second.
Spectroscopic system is equipped with the dynamic collimation interferometer with plane mirror electromagnetic drive interference function, can eliminate temperature and shake
Dynamic bring measurement error, realizes vehicle-mounted stability and accuracy.
Sample cell: it is absorption cell that quartz material 5mm light path sample feeding pipe, which may be selected,；To prevent sample room from interfering, detect every time
New sample feeding pipe is needed to change after the completion, and used sample feeding pipe, which can be put into dehydrated alcohol, to be impregnated, and is cleaned in time to reuse.
Sample feeding pipe cleaning method: first by sample feeding pipe immerse dehydrated alcohol in, in ultrasonic oscillator ultrasound 15 minutes with
On, clamp sample feeding pipe using tweezers later, liquid in pipe poured out, then invades in petroleum ether, using sonic oscillation 15 minutes with
On, liquid in pipe is controlled out, the sample feeding pipe after cleaning is laid in double-layer filter paper, is placed in 50 DEG C of baking ovens 20 minutes, to complete
It takes out to be cooled to room temperature after drying and be fitted into sample introduction box.
It should be constant at 15 DEG C~27 DEG C of room temperature before sample analysis.
Spectral measurement: setting instrument spectral measure measurement pattern be absorption spectrum, spectral region be 4400cm-1~
8800cm-1, spectral resolution 2cm-1, wave number repeatability 0.05cm-1, to obtain good signal-to-noise ratio, it is proposed that the scanning of spectrum
Number is no less than 32 times.It is put into sample cell, using air as reference, acquires background spectrum, is placed in sample with glass dropper pipette samples
In product pond, and ensure three molecules two full of sample cell and bubble-free presence, sample injection rate should not be less than 1mL, measure sample
Spectrum.
Calibration model is established
This standard establishes calibration model using PLS method.Using chemo metric software, every quality index and spectrum are established
The calibration model of data relationship.Using SEC (calibration standard error) come evaluation model performance, formula (1) is shown in SEC calculating.
In formula:
yiI-th of samples Reference method measured value of-calibration set is surveyed according to test method as defined in finished oil product standard
Every quality index of fixed all kinds of fuel correction collection and verifying collection sample；
The index predicted value of i-th of sample of-calibration set；
N-correcting sample number；
Need to detect and delete two classes out-of-bounds point in calibration model establishment process.
The first kind, which is out-of-bounds put, refers to that the sample has extreme chemical composition, to model performance compared with remaining sample of calibration set
It seriously affects.Such, which is out-of-bounds put, can be differentiated and be rejected by mahalanobis distance (MD).It deletes mahalanobis distance (D2) and is greater than 3k/
The sample of n, wherein n is correcting sample number, and k is PLS number of main factor.Formula (2) are shown in mahalanobis distance calculating
Wherein tiThe principal component of i sample is concentrated for calibration samples
Score,For the average vector of principal component scores T, TcentFor the mean value centralization matrix of principal component scores T,
MDiFor the mahalanobis distance of calibration set sample i.
Second class, which is out-of-bounds put, refers between the reference data of sample and model predication value there is statistical significance difference.It can pass through
Raw (t) is examined, and deleting t is more than regulation freedom degree (n-k, if mean value centralization is handled, for the sample of the t theoretical value of n-k-1)
Formula (3) are shown in product, t calculating.
In formula: tiFor the t test value of calibration set sample i, ei- calibration set sample i
Predicted value and reference data difference.
Measure sample
The mahalanobis distance of spectroscopic data using sample and the calibration model established, measurement sample and calibration set sample and
Every quality index.If sample mahalanobis distance has been more than the range of model, which belongs to the first kind out-of-bounds point, measurement knot
Fruit cannot use, and need to measure using with reference to method.If sample mahalanobis distance, in model scope, this quality index can be with
Using, and report measurement result.
As a result it reports
It is consistent specified in the report and product standard of product oil items quality index.
Claims (8)
1. a kind of product oil method for quickly detecting quality, it is characterised in that: including,
Step 1: the measurement pattern that the spectral measurement of near infrared spectrometer is arranged is absorption spectrum, spectral region 4400cm-1
~8800cm-1, spectral resolution 2cm-1, wave number repeatability 0.05cm-1,
Step 2: being put into sample cell near infrared spectrometer, using air as reference, acquires background spectrum,
Step 3: being placed in sample cell with glass dropper pipette samples, and ensures three molecules two and bubble-free full of sample cell
In the presence of, sample injection rate should not be less than 1mL, the spectrum of sample is measured,
Step 4: using PLS method, using chemo metric software, establishes the correction of every quality index and spectroscopic data relationship
Model needs to detect and delete two classes out-of-bounds point (first kind out-of-bounds point, the second class out-of-bounds point) in calibration model establishment process,
Step 5: the geneva of the spectroscopic data using sample and the calibration model established, measurement sample and calibration set sample away from
From with every quality index.If sample mahalanobis distance has been more than the range of model, which belongs to the first kind out-of-bounds point, surveys
Determining result cannot use, and need to measure using with reference to method.If sample mahalanobis distance is in model scope, this quality index
It can use, and report measurement result.
Step 6: it will be compared specified in product oil items quality index and product standard.
2. a kind of product oil method for quickly detecting quality according to claim 1, it is characterised in that: the first kind is out-of-bounds
Point refers to that compared with remaining sample of calibration set, the sample has extreme chemical composition, seriously affects to model performance, such is out-of-bounds
Point can be differentiated and be rejected by mahalanobis distance (MD), delete the sample that mahalanobis distance (D2) is greater than 3k/n, and wherein n is correction
Sample number, k are PLS number of main factor,
Wherein tiThe principal component scores of i sample are concentrated for calibration samples,For the average vector of principal component scores T, TcentFor
The mean value centralization matrix of principal component scores T, MDiFor the mahalanobis distance of calibration set sample i.
3. a kind of product oil method for quickly detecting quality according to claim 1, it is characterised in that: second class is out-of-bounds
Point refers between the reference data of sample and model predication value there is statistical significance difference, can be examined by student (t), and it is super to delete t
Cross regulation freedom degree (n-k, if mean value centralization is handled, for the sample of the t theoretical value of n-k-1),
In formula: tiFor the t test value of calibration set sample i, eiThe predicted value of-calibration set sample i and the difference of reference data.
4. a kind of product oil method for quickly detecting quality according to claim 1, it is characterised in that: described
yiI-th of samples Reference method measured value of-calibration set, according to test method as defined in finished oil product standard, measurement is each
Every quality index of class A fuel A calibration set and verifying collection sample；
The index predicted value of i-th of sample of-calibration set；
N-correcting sample number.
5. a kind of product oil method for quickly detecting quality according to claim 1, it is characterised in that: to obtain good letter
It makes an uproar and compares, the scanning times of near infrared spectrometer are no less than 32 times, and scanning speed is no less than 5 times/second.
6. a kind of product oil method for quickly detecting quality according to claim 1, it is characterised in that: near infrared spectrometer is matched
The standby dynamic collimation interferometer with plane mirror electromagnetic drive interference function eliminates temperature and vibration bring measurement error.
7. a kind of product oil method for quickly detecting quality according to claim 1, it is characterised in that: the sample cell selection
Quartz material 5mm light path sample feeding pipe is absorption cell, to prevent sample room from interfering, needs to change new sample feeding pipe after the completion of detection every time,
Used sample feeding pipe, which can be put into dehydrated alcohol, to be impregnated, and is cleaned in time to reuse.
8. a kind of product oil method for quickly detecting quality according to claim 1, it is characterised in that: sample is answered before detection
It is constant at 15 DEG C~27 DEG C of room temperature.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110927099A (en) * | 2019-12-11 | 2020-03-27 | 山东省产品质量检验研究院 | Rapid detection method for nitrogen oxide reducing agent of diesel engine |
| CN110987862A (en) * | 2019-11-06 | 2020-04-10 | 汉谷云智(武汉)科技有限公司 | Diesel oil on-line blending method |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101893561B (en) * | 2010-07-13 | 2012-04-25 | 中国人民解放军总后勤部油料研究所 | Near infrared spectrum quick test method of new oil quality of lubricating oil |
| CN103115973A (en) * | 2013-01-25 | 2013-05-22 | 山东大学 | Method for judging consistency of traditional Chinese medicine batches |
| CN106338526A (en) * | 2016-08-15 | 2017-01-18 | 上海创和亿电子科技发展有限公司 | Correction model based on microwave moisture analyzer and detection method thereof |
| CN106841100A (en) * | 2016-12-28 | 2017-06-13 | 北京医药集团有限责任公司 | Active pharmaceutical ingredient rapid assay methods in a kind of small dimension oral solid formulation based on near-infrared spectrum technique |
| CN107036999A (en) * | 2016-11-15 | 2017-08-11 | 天津工业大学 | A kind of five yuan of ready-mixed oil quantitative analysis methods based near infrared spectrum and Chemical Measurement |
| CN109060711A (en) * | 2018-08-28 | 2018-12-21 | 中蓝晨光成都检测技术有限公司 | A method of calculating white oil content in white oil-doped organosilicon product |
-
2019
- 2019-04-30 CN CN201910358718.0A patent/CN110095429A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101893561B (en) * | 2010-07-13 | 2012-04-25 | 中国人民解放军总后勤部油料研究所 | Near infrared spectrum quick test method of new oil quality of lubricating oil |
| CN103115973A (en) * | 2013-01-25 | 2013-05-22 | 山东大学 | Method for judging consistency of traditional Chinese medicine batches |
| CN106338526A (en) * | 2016-08-15 | 2017-01-18 | 上海创和亿电子科技发展有限公司 | Correction model based on microwave moisture analyzer and detection method thereof |
| CN107036999A (en) * | 2016-11-15 | 2017-08-11 | 天津工业大学 | A kind of five yuan of ready-mixed oil quantitative analysis methods based near infrared spectrum and Chemical Measurement |
| CN106841100A (en) * | 2016-12-28 | 2017-06-13 | 北京医药集团有限责任公司 | Active pharmaceutical ingredient rapid assay methods in a kind of small dimension oral solid formulation based on near-infrared spectrum technique |
| CN109060711A (en) * | 2018-08-28 | 2018-12-21 | 中蓝晨光成都检测技术有限公司 | A method of calculating white oil content in white oil-doped organosilicon product |
Non-Patent Citations (8)
| Title |
|---|
| 刘翠玲 等: "直接标准化算法在食用油酸值和过氧化值上的近红外光谱模型转移的研究", 《光谱学与光谱分析》 * |
| 尚廷义 等: "《基于光谱技术的寒地水稻稻瘟病害分析及机理研究》", 30 June 2016, 哈尔滨工程大学出版社 * |
| 尹宝全 等: "近红外多组分分析中异常样本识别方法", 《农业机械学报》 * |
| 张福东 等: "基于最小二乘支持向量机的油页岩含油率近红外光谱分析", 《高等学校化学学报》 * |
| 段敏伟: "生物柴油检测技术研究与评价体系的建立", 《中国优秀硕士学位论文全文数据库工程科技Ⅰ辑》 * |
| 蔡立晶 等: "基于近红外透射光谱及神经网络的大豆油质量分析", 《湖北农业科学》 * |
| 邹贤勇 等: "PCA结合马氏距离法剔除近红外异常样品", 《江苏大学学报(自然科学版)》 * |
| 陈斌 等: "基于浓度外扰的二维相关近红外光谱快速鉴别4种食用植物油", 《应用化工》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110987862A (en) * | 2019-11-06 | 2020-04-10 | 汉谷云智(武汉)科技有限公司 | Diesel oil on-line blending method |
| CN110927099A (en) * | 2019-12-11 | 2020-03-27 | 山东省产品质量检验研究院 | Rapid detection method for nitrogen oxide reducing agent of diesel engine |
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