CN109211835A - A kind of rubbish from cooking rapid identification method based on spectral technique - Google Patents
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- 238000010411 cooking Methods 0.000 title claims abstract description 65
- 238000000034 method Methods 0.000 title claims abstract description 55
- 230000003595 spectral effect Effects 0.000 title claims abstract description 25
- 239000002699 waste material Substances 0.000 claims abstract description 6
- 239000000523 sample Substances 0.000 claims description 63
- 238000002329 infrared spectrum Methods 0.000 claims description 25
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- 238000004846 x-ray emission Methods 0.000 claims description 4
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- 108010000912 Egg Proteins Proteins 0.000 claims description 3
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Classifications
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- 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
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
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- Biochemistry (AREA)
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Abstract
The rubbish from cooking rapid identification method based on spectral technique that the invention discloses a kind of is related to technical field of waste treatment, including collects sample, establish near-infrared qualitative discrimination model, establish 3, X-ray data library step.This method provides technical support for rubbish from cooking classification accuracy judgement, realizes that wisdom environmental sanitation provides a kind of quick, lossless, accurate, environmentally friendly new method for environmental sanitation mechanism.
Description
Technical field
The present invention relates to technical field of waste treatment, in particular to a kind of rubbish from cooking Rapid identifications based on spectral technique
Method.
Background technique
Rubbish from cooking is the general designation for the remaining food that the eating and drinking establishments such as family, hotel, restaurant are abandoned.Countries in the world are exhausted at present
About 40% is rubbish from cooking in most cities rubbish, mainly includes rice and flours food residues, vegetables, vegetable oil, animal
Oil, meat bone, fishbone etc..Its chemical composition is mainly starch, cellulose, protein, lipid and inorganic salts etc..Rubbish from cooking just like
Lower feature: first is that the content of organics such as crude protein and crude fibre are higher (respectively to account for 16.73% He of rubbish from cooking dried object
2.52%), value of exploiting and utilizing is larger, but perishable and generate stench；Second is that moisture content is high (mass fraction of water is greater than 80%),
Transport is collected in inconvenience, and calorific value is low, deals with improperly and is easy to produce the secondary pollutions such as Leachate site；Third is that (crude fat accounts for food waste to oils
The 28.82% of drying garbage object) and the more other house refuses height of salts substances (NaCl content is up to 1.239%) content, to money
Source product quality is affected, and needs to deal carefully with.
Infrared spectroscopy is electromagnetic wave of the wave-length coverage in 780~2526nm, belongs to molecular spectrum, main in the wave-length coverage
If sum of fundamental frequencies and frequency multiplication that hydric group (X-H, X C, O, N, S etc.) generates absorb.Because of all organic compounds and big absolutely
Part inorganic compound all at least contains a hydric group, so they, which can absorb near infrared light, generates specific absorb
Spectrogram.Currently, near infrared spectroscopy (NIRS) is excellent because of its quick, easy, low cost, non-destructive and simultaneous determination of multiponents etc.
Point is valued by people, and is widely used in agricultural, food, petroleum, medicine and other fields, but near-infrared spectrum technique is in measurement kitchen
The research of remaining component of refuse rare report at home.Chinese patent disclose " rubbish from cooking disposition monitoring method " (application number:
CN201810143498.5), spectral analysis technique is used, provides the specific method of soil property sampling, and according to spectrum point
The characteristics of analysis, proposes a kind of data processing method of synthesis so that for soil property organic matter and total nitrogen content and soil property metal at
Divide the prediction effect of content basicly stable good, but it needs to separate rubbish from cooking solid-state and liquid, and to rubbish from cooking
Detection is confined in element state level.
X-ray is the transition due to the electronics in atom between two energy levels that energy differs greatly and the particle generated
Stream, is electromagnetic wave of the wavelength between ultraviolet light and gamma-rays.Its wavelength is very short about between 0.01~100 angstrom.X-ray
With very high penetrating power, many substances opaque to visible light, such as black paper, timber can be penetrated.This naked eyes are seen not
The ray seen can make many solid materials that visible fluorescence occur, and keep photographic negative photosensitive and the effects such as air ionization.X is penetrated
Line is used primarily for medical imaging diagnosis and X-ray crystallography, is now also widely used in safe examination system, but it is detected in rubbish from cooking
Aspect has not been reported.
Summary of the invention
The technical problem to be solved by the present invention is to overcome the above technological deficiencies, provide a kind of food waste rubbish based on spectral technique
Rubbish rapid identification method provides technical support for rubbish from cooking classification accuracy judgement；Realize that wisdom environmental sanitation mentions for environmental sanitation mechanism
For a kind of quick, lossless, accurate, environmentally friendly new method.
In order to achieve the above object of the invention, a kind of the technical solution adopted by the present invention are as follows: food waste rubbish based on spectral technique
Rubbish rapid identification method, near-infrared qualitative discrimination model and X-ray detection database including establishing rubbish from cooking main component,
The following steps are included:
(1) collect sample: acquisition 10 kinds of usual ingredients of rubbish from cooking, 1. staple food (rice, meal, steamed bun, noodles), 2. vegetables,
3. fruit, 4. meat, 5. eggshell, 6. fishes and shrimps, 7. tealeaves spent coffee, 8. bean product, 9. leftovers, 10. waste grease, often
Kind acquires 40 parts of samples as modeling collection sample respectively, and 10 parts of samples are as calibration set sample；
(2) it establishes near-infrared qualitative discrimination model: preparing near infrared spectrometer and near-infrared fibre-optical probe, to step (1)
10 kinds of modelings collection sample of acquisition carries out laboratory infrared analysis respectively, and the analysis of Binding experiment room as a result, determine modeling respectively
Collect the optimal acquisition condition of near infrared spectrum of sample, and by Pretreated spectra and data compression, establish 10 kinds of rubbish from cooking at
Divide qualitative discrimination model, and singular point is rejected to model, the atlas of near infrared spectra of calibration set sample is used under the same terms, is called
Qualitative discrimination model carries out qualitative analysis to calibration set sample to be corrected to model；
(3) X-ray data library is established: being prepared X-ray emission source and detector, is collected to 10 kinds of modelings of step (1) acquisition
Sample utilizes the standby inspection article of low dose of x-ray bombardment, and the ray thrown is analyzed using computer, is penetrated and is penetrated according to each ingredient
10 kinds of ingredients of rubbish from cooking are established color, shape and database and are subject to by the properties of samples that the mutation analysis of line is pierced
It distinguishes.
Further, the modeling collection sample and lab analysis sample are that collected 10 kinds of rubbish from cooking usual ingredients are appointed
The aggregate sample for one or more of anticipating.
Further, the modeling collection sample and lab analysis sample are solid-liquid mixing samples and without any
Pretreatment measure, and sample volume is no more than 1dm3。
Further, the near infrared spectra collection condition includes detector, white light source, gain, index glass speed, scanning model
It encloses, scanning times, resolution ratio index.
Further, the near infrared spectrum data is the absorbance obtained in such a way that near infrared spectrometer is using diffusing reflection
Value.
Further, the near infrared spectrum pretreatment refers to the modeling collection sample near infrared spectrum that will be acquired in step (1)
Data pass through the machine learning such as smoothing processing, the correction of removal trend, multiplicative scatter correction (MSC) and vector normalization (SNV)
Algorithm finally obtains the optimal conditions of Pretreated spectra and wave-length coverage.
Further, the near infrared spectrum data compression, which refers to, will pass through the spectral translation for all modeling collection samples located in advance
For data matrix, Data Dimensionality Reduction is carried out to all spectroscopic datas using principal component analysis (PCA) method, extracts the number of principal component.
Further, the rubbish from cooking near infrared spectrum qualitative discrimination model returns (PLS) using Partial Least Squares and builds
It is vertical.
Further, the fibre-optical probe of the spectrometer is placed in away from 10~50cm above rubbish from cooking sample surfaces, kitchen
Remaining rubbish is placed in rotation specimen cup, is rotated 360 °, rotation speed 2r/s, the rubbish from cooking is examined in 40s
It surveys as a result, prediction related coefficient R2It is above 0.98, sample cup volumes are 5~8dm3。
Further, the rubbish from cooking can be scanned at least 64 times in 30s, and the spectrum after arithmetic mean is adopted as one
Sample spectrum.
Further, the spectral detection system has auto-alarm function to unreasonable ingredient.
The invention has the benefit that
(1) due to the complexity of rubbish from cooking, near-infrared spectral analysis technology combination detection method of X-ray be can be realized
The qualitative discrimination of each component of rubbish from cooking provides reference frame to be the Fast Evaluation of rubbish from cooking；
(2) rubbish from cooking on-line monitoring may be implemented by near-infrared spectrum technique and X-ray spectrum technology, can be used for house
Front yard rubbish from cooking is rationally collected, it can also be used to which rubbish from cooking classification recycling in community's provides for rubbish from cooking classification accuracy judgement
Technical support increases the diversity of testing result purposes；
(3) two class spectral technique comprehensive analysis, for environmental sanitation mechanism realize categorized consumer waste provide it is a kind of it is quick, lossless,
Accurately, environmentally friendly new method.
Detailed description of the invention
Fig. 1 is a kind of structural schematic diagram of the rubbish from cooking rapid identification method based on spectral technique of the present invention.
Specific embodiment
It is noted that following detailed description is all illustrative, it is intended to provide further instruction to the application.Unless another
It indicates, all technologies used herein and technics have usually to be managed with the application person of an ordinary skill in the technical field
The identical meanings of solution.It should be noted that term used herein above is merely to describe specific embodiment, and be not intended to limit
Make the illustrative embodiments according to the application.As used herein, unless the context clearly indicates otherwise, otherwise singular
Form be also intended to include plural form, additionally, it should be understood that, when in the present specification use term "comprising" and/or
When " comprising ", existing characteristics, step, operation, device, component and/or their combination are indicated.
A kind of rubbish from cooking rapid identification method based on spectral technique carries out specific steps explanation in conjunction with Fig. 1:
(1) collect sample: the modeling collection sample of this method acquires 10 kinds of usual ingredients of rubbish from cooking respectively, 1. staple food (rice,
Meal, steamed bun, noodles), 2. vegetables, 3. fruit, 4. meat, 5. eggshell, 6. fishes and shrimps, 7. tealeaves spent coffee, 8. bean product, 9. residual
Custard leftovers, 10. waste grease, every kind acquires 40 parts, and totally 400 parts of samples are as modeling collection sample, and 10 parts of samples are as calibration set sample
Product.Modeling collection sample and lab analysis sample are any one or a few mixed of collected 10 kinds of rubbish from cooking usual ingredients
Close sample.
(2) instrument and equipment: near infrared spectrometer, near-infrared fibre-optical probe, X-ray emission source, detector, desktop computer,
And instrument and desktop computer are carried out using preceding correction.
(3) acquisition of sample near infrared spectrum: mensuration mode: diffusing reflection, measurement range: 400nm~2450nm；Scanning speed
Degree: 10 times/second, spectral resolution: 6nm.Measuring method: infrared detection sample is mixed without the solid-liquid of any pretreatment measure
Close aspect product；The fibre-optical probe of spectrometer is placed in away from rubbish from cooking sample surfaces 10~50cm of top；Rubbish from cooking is placed in rotation
Turn in specimen cup, rotate 360 °, rotation speed 2r/s, sample cup volumes are 0.5~0.8dm3；Rubbish from cooking is in 30s
Interior to be scanned at least 64 times, the spectrum after arithmetic mean is as a sampling spectrum.
(4) near infrared spectrum pre-processes: the sample near infrared spectrum data that will be acquired in step (1), by smoothing processing,
The machine learning algorithms such as the correction of removal trend, multiplicative scatter correction (MSC) and vector normalization (SNV), finally obtain spectrum
The optimal conditions of pretreatment and wave-length coverage.
(5) near infrared spectrum data is compressed: being data square by the spectral translation of all samples of acquisition process in step (4)
Battle array carries out Data Dimensionality Reduction to all spectroscopic datas using principal component analysis (PCA) method, extracts the number of principal component.
(6) rubbish from cooking near infrared spectrum qualitative discrimination model is established: in determining wavelength band, using step (4)
The principal component number that obtained preprocessing procedures and step (5) obtain returns (PLS) with Partial Least Squares and establishes food waste
The qualitative discrimination model of each ingredient of rubbish.
(7) rubbish from cooking near infrared spectrum qualitative discrimination model rejects singular point: by rubbish from cooking obtained in step (6)
Each ingredient qualitative discrimination model rejects singular point, determines the number for needing to reject singular point, simultaneously using successive optimization diagnostic method
Determine that Partial Least Squares returns qualitative discrimination model.
(8) X-ray data library is established: being prepared X-ray emission source and detector, is collected to 10 kinds of modelings of step (1) acquisition
Sample utilizes the standby inspection article of low dose of x-ray bombardment, and the ray thrown is analyzed using computer, is penetrated and is penetrated according to each ingredient
10 kinds of ingredients of rubbish from cooking are established color, shape and database and are subject to by the properties of samples that the mutation analysis of line is pierced
It distinguishes.
(9) model corrects: the atlas of near infrared spectra of acquisition correction collection sample under the same terms calls qualitative discrimination model pair
Calibration set sample carries out qualitative analysis；Simultaneously to rubbish from cooking X-ray data library using calibration set sample correct, improve model with
The precision of prediction of database obtains reliable accurately analysis result.
(10) rubbish from cooking intelligent measurement: rubbish from cooking is when by airtight passage, respectively by near-infrared fibre-optical probe and X
Ray scanning, fibre-optical probe are transferred to computer by optical fiber by sample product near infrared light spectrum information for what scanning obtained, passed through
It is matched with model in database, intelligent distinguishing rubbish from cooking ingredient；It is penetrated simultaneously by control unit triggering x-ray source transmitting X
Line, X-ray form very narrow fan-ray beam after collimator, penetrate and are fallen on detector by sample product, detector handle
The X-ray received becomes electric signal, these very weak current signals quantify after being amplified, and is transmitted to by universal serial bus
Computer for further processing, it is built in the image and database for obtaining high quality after complicated operation and imaging
Vertical color, shape carry out matching and obtain composition information, and when being not belonging to rubbish from cooking by sample product, system has automatic report
Alert function.Two kinds of testing result comprehensive considerations obtain the testing result of high-accuracy, and testing result is obtained in 40s, and prediction is related
Coefficients R2It is above 0.98.
The present invention and its embodiments have been described above, this description is no restricted, shown in the drawings
Only one of embodiments of the present invention, actual structure is not limited to this.All in all if the ordinary skill of this field
Personnel are enlightened by it, without departing from the spirit of the invention, are not inventively designed and the technical solution phase
As frame mode and embodiment, be within the scope of protection of the invention.
Claims (10)
1. a kind of rubbish from cooking rapid identification method based on spectral technique, it is characterised in that: main including establishing rubbish from cooking
The near-infrared qualitative discrimination model and X-ray detection database of component, comprising the following steps:
(1) it collects sample: acquiring 10 kinds of usual ingredients of rubbish from cooking, 1. staple food (rice, meal, steamed bun, noodles), 2. vegetables, 3. water
Fruit, 4. meat, 5. eggshell, 6. fishes and shrimps, 7. tealeaves spent coffee, 8. bean product, 9. leftovers, 10. waste grease, every kind point
Not Cai Ji 40 parts of samples as modeling collection samples, 10 parts of samples are as calibration set sample；
(2) it establishes near-infrared qualitative discrimination model: preparing near infrared spectrometer and near-infrared fibre-optical probe, step (1) is acquired
10 kinds of modelings collection sample carry out laboratory infrared analysis respectively, and the analysis of Binding experiment room as a result, determine modeling collection sample respectively
The optimal acquisition condition of the near infrared spectrum of product, and by Pretreated spectra and data compression, it is fixed to establish 10 kinds of ingredients of rubbish from cooking
Property discrimination model, and singular point is rejected to model, the atlas of near infrared spectra of calibration set sample is used under the same terms, is called qualitative
Discrimination model carries out qualitative analysis to calibration set sample to be corrected to model；
(3) X-ray data library is established: being prepared X-ray emission source and detector, is collected sample to 10 kinds of modelings of step (1) acquisition
Using the standby inspection article of low dose of x-ray bombardment, the ray thrown is analyzed using computer, according to each ingredient through ray
10 kinds of ingredients of rubbish from cooking are established color, shape and database and are distinguish by the properties of samples that mutation analysis is pierced.
2. a kind of rubbish from cooking rapid identification method based on spectral technique according to claim 1, it is characterised in that: institute
It states modeling collection sample and lab analysis sample is any one or a few mixed of collected 10 kinds of rubbish from cooking usual ingredients
Close sample.
3. a kind of rubbish from cooking rapid identification method based on spectral technique according to claim 1, it is characterised in that: institute
The modeling collection sample and lab analysis sample stated are solid-liquid mixing samples and without any pretreatment measure, and sample
Volume is no more than 1dm3。
4. a kind of rubbish from cooking rapid identification method based on spectral technique according to claim 1, it is characterised in that: institute
Stating near infrared spectra collection condition includes detector, white light source, gain, index glass speed, scanning range, scanning times, resolution
Rate index.
5. a kind of rubbish from cooking rapid identification method based on spectral technique according to claim 1, it is characterised in that: institute
Stating near infrared spectrum data is the absorbance value obtained in such a way that near infrared spectrometer is using diffusing reflection.
6. a kind of rubbish from cooking rapid identification method based on spectral technique according to claim 1, it is characterised in that: institute
State near infrared spectrum pretreatment and refer to the modeling collection sample near infrared spectrum data that will be acquired in step (1), by smoothing processing,
The machine learning algorithms such as the correction of removal trend, multiplicative scatter correction (MSC) and vector normalization (SNV), finally obtain spectrum
The optimal conditions of pretreatment and wave-length coverage.
7. a kind of rubbish from cooking rapid identification method based on spectral technique according to claim 1, it is characterised in that: institute
It states near infrared spectrum data compression and refers to and will integrate the spectral translation of sample as data matrix, using master by all modelings located in advance
Constituent analysis (PCA) method carries out Data Dimensionality Reduction to all spectroscopic datas, extracts the number of principal component.
8. a kind of rubbish from cooking rapid identification method based on spectral technique according to claim 1, it is characterised in that: institute
It states rubbish from cooking near infrared spectrum qualitative discrimination model and (PLS) foundation is returned using Partial Least Squares.
9. a kind of rubbish from cooking rapid identification method based on spectral technique according to claim 1, it is characterised in that: institute
The fibre-optical probe for the spectrometer stated is placed in away from 10~50cm, rubbish from cooking is placed in rotation sample above rubbish from cooking sample surfaces
In cup, rotate 360 °, rotation speed 2r/s, the rubbish from cooking obtains testing result, prediction related coefficient in 40s
R2It is above 0.98, sample cup volumes are 5~8dm3。
10. a kind of rubbish from cooking rapid identification method based on spectral technique according to claim 1, it is characterised in that:
The spectral detection system has auto-alarm function to unreasonable ingredient.
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| CN110775467A (en) * | 2019-10-31 | 2020-02-11 | 哈尔滨工业大学（深圳） | Garbage storage system and method based on intelligent recognition and voice prompt |
| WO2021046854A1 (en) * | 2019-09-14 | 2021-03-18 | 南京大学（溧水）生态环境研究院 | Big data-based kitchen waste classification method |
| WO2021046851A1 (en) * | 2019-09-14 | 2021-03-18 | 南京大学（溧水）生态环境研究院 | Method for identification and classification of kitchen waste |
| CN112613413A (en) * | 2020-12-25 | 2021-04-06 | 平安国际智慧城市科技股份有限公司 | Perishable garbage classification quality determination method and device and computer readable storage medium |
| CN113051963A (en) * | 2019-12-26 | 2021-06-29 | 中移(上海)信息通信科技有限公司 | Garbage detection method and device, electronic equipment and computer storage medium |
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