CN109975481A - Volatile organic component detection method, device, storage medium and terminal - Google Patents
Volatile organic component detection method, device, storage medium and terminal Download PDFInfo
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- 238000001514 detection method Methods 0.000 title claims abstract description 113
- 238000003860 storage Methods 0.000 title claims abstract description 15
- 239000000463 material Substances 0.000 claims abstract description 50
- 238000012800 visualization Methods 0.000 claims abstract description 6
- 238000000034 method Methods 0.000 claims description 33
- 238000012545 processing Methods 0.000 claims description 19
- 238000004422 calculation algorithm Methods 0.000 claims description 11
- 238000004590 computer program Methods 0.000 claims description 10
- 238000012360 testing method Methods 0.000 claims description 7
- 241001269238 Data Species 0.000 claims description 2
- 230000015572 biosynthetic process Effects 0.000 claims description 2
- 230000005055 memory storage Effects 0.000 claims description 2
- 238000003908 quality control method Methods 0.000 abstract description 30
- 238000004806 packaging method and process Methods 0.000 abstract description 6
- 238000005259 measurement Methods 0.000 abstract description 5
- 230000000007 visual effect Effects 0.000 abstract 1
- 239000012855 volatile organic compound Substances 0.000 description 41
- 238000010586 diagram Methods 0.000 description 12
- 238000007689 inspection Methods 0.000 description 11
- XEKOWRVHYACXOJ-UHFFFAOYSA-N Ethyl acetate Chemical compound CCOC(C)=O XEKOWRVHYACXOJ-UHFFFAOYSA-N 0.000 description 9
- 238000004891 communication Methods 0.000 description 7
- 238000004364 calculation method Methods 0.000 description 5
- ZWEHNKRNPOVVGH-UHFFFAOYSA-N 2-Butanone Chemical compound CCC(C)=O ZWEHNKRNPOVVGH-UHFFFAOYSA-N 0.000 description 4
- 230000008859 change Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 241000208125 Nicotiana Species 0.000 description 3
- 235000002637 Nicotiana tabacum Nutrition 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 3
- 239000000470 constituent Substances 0.000 description 3
- 239000004615 ingredient Substances 0.000 description 3
- 238000004519 manufacturing process Methods 0.000 description 3
- 239000000203 mixture Substances 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 239000003973 paint Substances 0.000 description 3
- 230000002093 peripheral effect Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 238000002485 combustion reaction Methods 0.000 description 2
- 239000002537 cosmetic Substances 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 235000013305 food Nutrition 0.000 description 2
- 239000003292 glue Substances 0.000 description 2
- 238000009776 industrial production Methods 0.000 description 2
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 2
- 239000005022 packaging material Substances 0.000 description 2
- 238000002360 preparation method Methods 0.000 description 2
- 238000007639 printing Methods 0.000 description 2
- 230000001953 sensory effect Effects 0.000 description 2
- 239000000126 substance Substances 0.000 description 2
- 239000004753 textile Substances 0.000 description 2
- 239000013598 vector Substances 0.000 description 2
- 239000000853 adhesive Substances 0.000 description 1
- 230000001070 adhesive effect Effects 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 239000011248 coating agent Substances 0.000 description 1
- 238000000576 coating method Methods 0.000 description 1
- 150000001875 compounds Chemical class 0.000 description 1
- 238000010411 cooking Methods 0.000 description 1
- 239000002989 correction material Substances 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000000151 deposition Methods 0.000 description 1
- 239000003599 detergent Substances 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 238000000802 evaporation-induced self-assembly Methods 0.000 description 1
- 239000004744 fabric Substances 0.000 description 1
- 239000000796 flavoring agent Substances 0.000 description 1
- 235000013355 food flavoring agent Nutrition 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 230000003694 hair properties Effects 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 239000003345 natural gas Substances 0.000 description 1
- 239000003960 organic solvent Substances 0.000 description 1
- 238000013450 outlier detection Methods 0.000 description 1
- 239000000779 smoke Substances 0.000 description 1
- 230000000391 smoking effect Effects 0.000 description 1
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- 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
- G01N33/0004—Gaseous mixtures, e.g. polluted air
- G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
- G01N33/0027—General constructional details of gas analysers, e.g. portable test equipment concerning the detector
- G01N33/0036—General constructional details of gas analysers, e.g. portable test equipment concerning the detector specially adapted to detect a particular component
- G01N33/0047—Organic compounds
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Abstract
The application provides volatile organic component detection method, device, storage medium and terminal comprising: the volatile component detection data of the multiple batches of sample of detected materials is obtained, forms the volatile component data acquisition system of the detected materials accordingly；The detection reference data of each batch sample of the detected materials is obtained according to the volatile component data acquisition system, and the similarity between the volatile component detection data of each batch sample and corresponding detection reference data is calculated separately, similarity upper limit threshold, central threshold and the lower threshold of the detected materials are determined accordingly；The comparison result information between the similarity and the upper limit threshold, central threshold and lower threshold of reference data of visualization output each batch sample.The application uses visual similarity Quality Control figure, calculates Quality Control figure bound and center limit, the quality stability of fast and effective evaluate packaging paper with similarity mean value and presupposition multiple Measurement of Similarity deviation or similarity limit value.
Description
Technical field
It is organic more particularly to volatility this application involves the quality stability detection technique field of volatile organic component
Component detection method, device, storage medium and terminal.
Background technique
In the industrial production, the preparation flow of package paper is complicated, since the application of printing technology will inevitably draw
Enter including the chemical constituent including volatile organic component (Volatile organic compounds, VOCs).Package paper
Middle VOCs too high levels will affect the sensory experience of user, for industries such as food, cosmetics, tobaccos, in packaging material
VOCs content height and its stability are always the key point of product Quality Control, but the quality stability of VOCs is assessed still at present
Lack comprehensively and effectively method.
Apply for content
In view of the foregoing deficiencies of prior art, the application is designed to provide volatile organic component detection side
Method, device, storage medium and terminal, for solving the problems of the prior art.
In order to achieve the above objects and other related objects, the first aspect of the application provides a kind of volatile organic component inspection
Survey method comprising: the volatile component detection data of the multiple batches of sample of detected materials is obtained, forms the detected materials accordingly
Volatile component data acquisition system；The inspection of each batch sample of the detected materials is obtained according to the volatile component data acquisition system
Reference data is surveyed, and is calculated separately between the volatile component detection data of each batch sample and corresponding detection reference data
Similarity determines the upper limit threshold, central threshold and lower threshold of the detected materials accordingly；Visualization output each batch sample
Comparison result information between the similarity of product and the upper limit threshold, central threshold and lower threshold.
In some embodiments of the first aspect of the application, in the method formation the detected materials volatility at
The mode of divided data set includes: to reject to peel off from the volatile component detection data of the multiple batches of sample of the detected materials
Data；According to the volatile component detection data after Outlier Data is eliminated, the volatile component number of the detected materials is established
According to library；Wherein the volatile component database includes that each volatile component detection of each batch sample of the detected materials refers to
Mark and detection data.
In some embodiments of the first aspect of the application, the detection base value of each batch sample of the detected materials
According to the mean value for the whole volatile component detection datas for including each batch sample.
In some embodiments of the first aspect of the application, waving for each batch sample is calculated using cosine similarity algorithm
Similarity between hair property composition detection data and the detection reference data.
In some embodiments of the first aspect of the application, which comprises according to the volatility of each batch sample
Similarity between composition detection data and the detection reference data, calculates the similarity mean value of those batch samples as institute
State central threshold.
In some embodiments of the first aspect of the application, which comprises pre- with the central threshold and first
If the difference of multiple standard deviation determines the lower threshold, but lower threshold is not less than 0.
In some embodiments of the first aspect of the application, which comprises pre- with the central threshold and second
If the sum of multiple standard deviation determines the upper limit threshold, but upper limit threshold is not higher than 1.
In order to achieve the above objects and other related objects, the second aspect of the application provides a kind of volatile organic component inspection
Survey device comprising: data acquisition module, the volatile component detection data of the multiple batches of sample for obtaining detected materials,
The volatile component data acquisition system of the detected materials is formed accordingly；Data processing module, for according to the volatile component number
The detection reference data of the detected materials is obtained according to set, and calculate separately the volatile component detection data of each batch sample with
Similarity between the detection reference data, determine accordingly the similarity upper limit thresholds of the detected materials, central threshold and
Lower threshold；Output module is visualized, for visualizing the similarity and the upper limit threshold, center of output each batch sample
Comparison result information between threshold value and lower threshold.
In order to achieve the above objects and other related objects, the third aspect of the application provides a kind of computer-readable storage medium
Matter, is stored thereon with computer program, and the computer program realizes the volatile organic component inspection when being executed by processor
Survey method.
In order to achieve the above objects and other related objects, the fourth aspect of the application provides a kind of electric terminal, comprising: place
Manage device and memory；The memory is used to execute the memory storage for storing computer program, the processor
Computer program, so that the terminal executes the volatile organic component detection method.
As described above, volatile organic component detection method, device, storage medium and the terminal of the application, have following
The utility model has the advantages that the application comments VOCs quality stability in package paper using similarity algorithm and the realization of monodrome Quality Control figure
Estimate, establishes all kinds of VOCs component basic databases in package paper using the value detection method that peels off, and with the detection of each VOCs component
On the basis of mean value, similarity between each batch sample and benchmark is calculated by similarity algorithm, with similarity mean value and presupposition multiple
Measurement of Similarity deviation or similarity limit value calculate Quality Control figure bound and center limit, draw similarity Quality Control figure, can quickly have
Imitate the quality stability of evaluate packaging paper.
Detailed description of the invention
Fig. 1 is shown as the flow diagram of volatile organic component detection method in one embodiment of the application.
Fig. 2 is shown as the schematic diagram of similarity Quality Control figure in one embodiment of the application.
Fig. 3 is shown as the schematic diagram of similarity Quality Control figure in one embodiment of the application.
Fig. 4 is shown as the schematic diagram of similarity Quality Control figure in one embodiment of the application.
Fig. 5 is shown as the schematic diagram of volatile organic component detection device in one embodiment of the application.
Fig. 6 is shown as detecting the structural schematic diagram of terminal in one embodiment of the application.
Specific embodiment
Illustrate presently filed embodiment below by way of specific specific example, those skilled in the art can be by this specification
Disclosed content understands other advantages and effect of the application easily.The application can also pass through in addition different specific realities
The mode of applying is embodied or practiced, the various details in this specification can also based on different viewpoints and application, without departing from
Various modifications or alterations are carried out under spirit herein.It should be noted that in the absence of conflict, following embodiment and implementation
Feature in example can be combined with each other.
It should be noted that with reference to attached drawing, attached drawing describes several embodiments of the application in described below.It should
Understand, other embodiments also can be used, and mechanical group can be carried out without departing substantially from spirit and scope
At, structure, electrical and operational change.Following detailed description should not be considered limiting, and the application
The range of embodiment only limited by the claims for the patent announced.Term used herein is merely to description is specific
Embodiment, and it is not intended to limit the application.The term of space correlation, for example, "upper", "lower", "left", "right", " following ", " under
Side ", " lower part ", " top ", " top " etc. can be used in the text in order to elements or features shown in explanatory diagram and another
The relationship of one elements or features.
In this application unless specifically defined or limited otherwise, term " installation ", " connected ", " connection ", " fixation ",
Terms such as " fixings " shall be understood in a broad sense, for example, it may be being fixedly connected, may be a detachable connection, or be integrally connected；
It can be mechanical connection, be also possible to be electrically connected；It can be directly connected, can also indirectly connected through an intermediary, it can be with
It is the connection inside two elements.For the ordinary skill in the art, above-mentioned art can be understood as the case may be
The concrete meaning of language in this application.
Furthermore as used in herein, singular " one ", "one" and "the" are intended to also include plural number shape
Formula, unless there is opposite instruction in context.It will be further understood that term "comprising", " comprising " show that there are the spies
Sign, operation, element, component, project, type, and/or group, but it is not excluded for one or more other features, operation, element, group
Presence, appearance or the addition of part, project, type, and/or group.Term "or" and "and/or" used herein are interpreted as including
Property, or mean any one or any combination.Therefore, " A, B or C " or " A, B and/or C " mean " it is following any one:
A；B；C；A and B；A and C；B and C；A, B and C ".Only when the combination of element, functions or operations is inherently mutual under certain modes
When repulsion, it just will appear the exception of this definition.
In the industrial production, the preparation flow of package paper is complicated, since the application of printing technology will inevitably draw
Enter including the chemical constituent including volatile organic component (Volatile organic compounds, VOCs).Package paper
Middle VOCs too high levels will affect the sensory experience of user, for industries such as food, cosmetics, tobaccos, in packaging material
VOCs content height and its stability are always the key point of product Quality Control, but the quality stability of VOCs is assessed still at present
Lack comprehensively and effectively method.
In view of variety of problems in the prior art, the application provides volatile organic component detection method, device, storage Jie
Matter and terminal, effectively to solve those technical problems.The main thought of the application, it is intended to use similarity algorithm and monodrome Quality Control
Figure realizes the assessment to VOCs quality stability in package paper, is established using the value detection method that peels off all kinds of in package paper
VOCs component basic database, and on the basis of each VOCs component detection mean value, pass through similarity algorithm and calculates each batch sample
The similarity between benchmark calculates Quality Control figure or more with similarity mean value and presupposition multiple Measurement of Similarity deviation or similarity limit value
Limit and center limit, draw similarity Quality Control figure, can fast and effective evaluate packaging paper quality stability.
It should be noted that technical solution provided by the present application cannot be only used for the VOC ingredient of detection package paper, may be used also
For detecting furniture upholstery, automobile parts material paint, textile fabrics, toy or at relatively high temperatures using Shi Huihui
Issue the VOC ingredient of electronic products of organic principle compound etc..It hereafter, will be in conjunction with specific embodiments to the skill of the application
Art scheme does detailed explanation.
As shown in Figure 1, showing the flow diagram of volatile organic component detection method in one embodiment of the application.
In some embodiments, the method can be applied to controller, such as: ARM controller, FPGA controller, SoC
Controller, dsp controller or MCU controller etc..In some embodiments, the method can also be applied to include depositing
Reservoir, storage control, one or more processing units (CPU), Peripheral Interface, RF circuit, voicefrequency circuit, loudspeaker, Mike
Wind, input/output (I/O) subsystem, display screen, other outputs or the computer for controlling the components such as equipment and outside port；
The computer includes but is not limited to such as desktop computer, laptop, tablet computer, smart phone, smart television, a number
The PCs such as word assistant (Personal Digital Assistant, abbreviation PDA).In other embodiments, described
Method applies also for server, and the server can be arranged in one or more real according to many factors such as function, loads
On body server, it can also be made of server cluster be distributed or concentration.
In this present embodiment, the volatile organic component detection method includes step S11, step S12, step S13.
In step s 11, the volatile component detection data of the multiple batches of sample of detected materials is obtained, being formed accordingly should be to
It measures and monitor the growth of standing timber the volatile component data acquisition system of material.
VOC is the english abbreviation of volatile organic compounds (Volatile organic compounds), outdoor main
From fuel combustion and communications and transportation, interior is mainly from combustion products, smoking, heating and the cookings such as coal-fired and natural gas etc.
Smog, the discharge etc. of building and ornament materials, furniture, household electrical appliance, detergent and human body itself.The volatile organic
Close object for example: ink, organic solvent of tobacco business etc., glue used in the footwear product of textile industry etc., toy industry
Correction fluid or flavouring agent etc., coating, paint or adhesive for being used in furniture upholstery etc., in automobile parts material
Glue or paint for using etc., cleaning solvent used in electric industry etc..
In one embodiment, the mode for forming the volatile component data acquisition system of the detected materials includes: from described to be measured
Outlier Data is rejected in the volatile component detection data of the multiple batches of sample of material；According to eliminating the volatilization after Outlier Data
Property composition detection data, establish the volatile component database of the detected materials；The wherein volatile component database packet
Include each volatile component Testing index and detection data of each batch sample of the detected materials.In the present embodiment, reject from
The mode of group's data can do data prediction to acquired volatile component detection data, prevent Outlier Data from detecting to VOC
Interference is generated, the accurate precision of detection is effectively promoted.
Specifically, detecting every part of volatile component detection data in each batch sample one by one using the Grubbs method of inspection
In whether there is Outlier Data, the Outlier Data that will test is rejected, and is not involved in the calculating of average value, and finally with the batch sample
The detection mean value of volatile component in product substitutes.Wherein, level of significance α can use the data such as 0.01 or 0.05, this reality
It applies example and this is not construed as limiting.
It should be noted that the detection method of Outlier Data includes but is not limited to the Grubbs method of inspection, other real
It applies in example, the outlier detection such as based on proximity, the detection based on density also can be selected and is based on clustering technique detection side
Method, the application are not construed as limiting this.
In step s 12, the inspection of each batch sample of the detected materials is obtained according to the volatile component data acquisition system
Reference data is surveyed, and is calculated separately between the volatile component detection data of each batch sample and corresponding detection reference data
Similarity determines the upper limit threshold, central threshold and lower threshold of the detected materials accordingly.
In one embodiment, the detection reference data of each batch sample of the detected materials includes the complete of each batch sample
The mean value of portion's volatile component detection data.It should be noted that the detection reference data of each batch sample includes but is not limited to
Median or root-mean-square value of detection data etc., the application also can be selected in other examples in the mean value of detection data
This is not construed as limiting.
In one embodiment, volatile component detection data and the institute of each batch sample are calculated using cosine similarity algorithm
State the similarity between detection reference data.Cosine similarity algorithm, which refers to, utilizes two vectorial angle cosines in vector space
Calculation method of the value as the size of two inter-individual differences of measurement, cosine value closer to 1, surface angle closer to 0 degree, namely
Two vectors are more similar, and the difference between two individuals is smaller.
For example, using formula 1 hereafter) carry out cosine similarity calculating:
Wherein, S indicates similarity, akFor k-th of volatile organic compounds component detected value of outturn a, bkFor paper
The smoke components k detected value of sample detection benchmark b is opened, n is the volatile organic compound ingredient sum of selection.
In one embodiment, according between the volatile component detection data of each batch sample and the detection reference data
Similarity, calculate the similarity mean value of those batch samples as the central threshold.That is, first calculating separately each batch sample
The similarity value of product, then the average value of those similarity values is calculated, the threshold value centered on the average value is specific using hereafter
Formula 2) calculated:
Wherein, CL indicates that central threshold, n indicate the lot count of the whole samples of the detected materials, SkIndicate kth batch
The similarity of secondary sample.
In one embodiment, the lower limit threshold is determined with the difference of the central threshold and the first presupposition multiple standard deviation
Value.For example, the lower threshold is determined with the difference of the central threshold and 3 multiple standard deviations, it is specific using public affairs hereafter
Formula 3) and formula 4) calculated:
LCL=CL-3 σ；Formula 3)
Wherein, LCL indicates that lower threshold, σ indicate that standard deviation, n indicate the batch of the whole samples of the detected materials
Sum, SkIndicate the similarity of kth batch sample,Indicate similarity mean value.
In one embodiment, the upper limit threshold is determined with the sum of the central threshold and the second presupposition multiple standard deviation
Value.Such as: the upper limit threshold is determined with the sum of the central threshold and 3 multiple standard deviations, it is specific using public affairs hereafter
Formula 5) it is calculated:
UCL=CL+3 σ；Formula 5)
Wherein, the calculation of UCL expression upper limit threshold, CL and σ are in above making an explanation, and so it will not be repeated.
It should be noted that the value of first presupposition multiple and the second presupposition multiple can be it is identical, such as all
3 times of value, it is also possible to different, the application is not construed as limiting this.
In step s 13, visualization output each batch sample similarity and the upper limit threshold, central threshold, with
And the comparison result information between lower threshold.
In one embodiment, exported in a manner of two-dimensional coordinate view the volatile component detection data of each batch sample with
Similarity between the detection reference data knot compared between the upper limit threshold, central threshold and lower threshold
Fruit information.
The testing result of each VOCs component should be with detection benchmark similarity in every batch of sample, and calculated result should be on time
Between sequence successively described point be drawn in set similarity Quality Control figure, to assess the whole wave of each VOCs component in every batch of sample
The sample quality stability of dynamic property and detected materials.
Preferably, the detection method of VOCs component, the VOCs component of detection and production technology are matched in subsequent every batch of sample
It is consistent with paper production parameter that Fang Yingyu establishes used detection method, similarity assessment parameter when detection benchmark.If above-mentioned
Either condition changes, and similarity Quality Control figure should be repainted and be assessed.
For ease of understanding, the similarity Quality Control figure illustrated in the present embodiment is further explained now in conjunction with Fig. 2.Fig. 2
Show the VOC detection data of 6 batch samples of certain detected materials, horizontal axis indicates that 6 batch sample, the longitudinal axis indicate similarity
Value, the present embodiment is using the range of similarity 0.6 to 1.0 as example.3 piece solid line degree of denoting like of the upper right under in figure
Upper limit threshold, central threshold and lower threshold.The similarity of every batch of sample is indicated using dot, by each batch sample
Similarity dot connects into broken line.
Therefore, visualization view provided in this embodiment can be by the similarity of each batch sample and upper limit threshold, center threshold
Comparison result between value and lower threshold is clear and is directly shown, convenient for analyzing and summing up.Such as: it can from Fig. 2
Know, the corresponding similarity of 4 sample of batch is lower than lower threshold LCL, therefore can intuitively know the quality stability of 4 sample of batch
Difference.
Those of ordinary skill in the art will appreciate that: realize that all or part of the steps of above-mentioned each method embodiment can lead to
The relevant hardware of computer program is crossed to complete.Computer program above-mentioned can store in a computer readable storage medium
In.When being executed, execution includes the steps that above-mentioned each method embodiment to the program；And storage medium above-mentioned include: ROM,
The various media that can store program code such as RAM, magnetic or disk.
As shown in figure 3, showing the schematic diagram of similarity Quality Control figure in one embodiment of the application.It is provided in this embodiment similar
The quality stability that Quality Control figure is used for evaluate packaging 30 batch samples of paper A1 is spent, is generated especially by following step process
Similarity Quality Control figure shown in Fig. 3.
Firstly, taking volatile component qualitative and quantitative detection data in 30 batch samples of package paper A1.Using Grubbs
It examines and outlier inspection is carried out to VOCs testing result in each batch sample, after excluding outlier, establish package paper A1's
VOCs basic database.
Secondly, calculating all VOCs component detection mean values in package paper A1 is detection a reference value, and similar using cosine
Degree algorithm successively calculates 30 batch sample VOCs detected values and detects the similarity between a reference value, and statisticallys analyze in similarity
Heart threshold value and standard deviation, the similarity mean value for measuring package paper A1 is 0.931, standard deviation 0.070, and wherein A1* is
Detect benchmark.In this present embodiment, the standard deviation calculation based on about 1 times obtains upper limit threshold 1.0, based on about 3 times of standard
Lower threshold 0.722 is calculated in deviation.Therefore, the Quality Control limit range of package paper A1 is [0.722,1], and central value is
0.931。
From the figure 3, it may be seen that package paper A1 all samples similarity value is distributed in the two sides up and down of central threshold, and exist
It is fluctuated within the scope of Quality Control, without transfiniting abnormal point, indicates that the sample quality homogeneity of package paper A1 is preferable, detection data is can
Control fluctuation in range.
As shown in figure 4, showing the schematic diagram of similarity Quality Control figure in another embodiment of the application.Phase provided in this embodiment
The quality stability of evaluate packaging 20 batch samples of paper B1 is used for like degree Quality Control figure, it is raw especially by following step process
At similarity Quality Control figure shown in Fig. 4.
Firstly, obtaining volatile component qualitative and quantitative detection data in 20 batch samples of package paper B1.Using
Grubbs, which is examined, carries out outlier inspection to VOCs testing result in each batch sample, after excluding outlier, establishes label paper
The VOCs basic database of B1.
Secondly, calculating all VOCs component detection mean values in package paper B1 is detection a reference value, and similar using cosine
Degree algorithm successively calculates 20 batch sample VOCs detected values and detects the similarity between a reference value, and statisticallys analyze in similarity
Heart threshold value and standard deviation, measuring package paper B1 similarity mean value is 0.891, standard deviation 0.113, and wherein B1* is inspection
Survey benchmark.In this present embodiment, the standard deviation calculation based on about 1 times obtains upper limit threshold 1.0, based on about 3 times of standard deviation
Lower threshold 0.552 is calculated in difference.Therefore, the Quality Control limit range of package paper A1 is [0.552,1], central value 0.891.
As shown in Figure 4, guarantee is distributed in the two sides up and down of central threshold with most of sample similarity value of paper B1, and
Fluctuated within the scope of Quality Control.But B1*-8 sample is 0.462 to similarity, is judged to abnormal point lower than Quality Control lower limit, traces back
8# sample each VOCs testing result in source is traced to the source the result shows that two kinds of volatile component butanone and ethyl acetate detected value in the sample
To organize interior minimum value, and substantially less than a reference value, wherein ethyl acetate is major volatile constituents in paper.It is indicated above that 8#
The reason of whole fluctuation of volatile component is larger in sample, generates fluctuation is mainly due to the detection of butanone and ethyl acetate
It is larger to measure deviation, this may produce change due to occurring formula in the abnormal or sample production process in outturn detection process
Change and cause the quality difference of sample room.
As shown in figure 5, showing the schematic diagram of volatile organic component detection device in one embodiment of the application.The detection
Device includes data acquisition module 51, data processing module 52 and visualization output module 52.
Data acquisition module 51 is used to obtain the volatile component detection data of the multiple batches of sample of detected materials, accordingly shape
At the volatile component data acquisition system of the detected materials.Data processing module 52 is used for according to the volatile component data acquisition system
The detection reference data of the detected materials is obtained, and calculates separately the volatile component detection data and the inspection of each batch sample
The similarity between reference data is surveyed, determines the upper limit threshold, central threshold and lower threshold of the detected materials accordingly.It can
Be used to visualize depending on changing output module 52 similarity and the upper limit threshold of output each batch sample, central threshold and
Comparison result information between lower threshold.
It should be noted that the embodiment of volatile organic component detection device provided in this embodiment, and above
The embodiment of the volatile organic component detection method of offer is similar, and so it will not be repeated.It is further to note that it should be understood that
The division of the modules of apparatus above is only a kind of division of logic function, can completely or partially be integrated in actual implementation
It, can also be physically separate onto a physical entity.And these modules can all be called with software by processing element
Form is realized；It can also all realize in the form of hardware；It can be in the form of part of module calls software by processing element
It realizes, part of module passes through formal implementation of hardware.For example, data processing module can be the processing element individually set up,
It can integrate and realized in some chip of above-mentioned apparatus, in addition it is also possible to be stored in above-mentioned dress in the form of program code
In the memory set, is called by some processing element of above-mentioned apparatus and execute the function of above data processing module.It is other
The realization of module is similar therewith.Furthermore these modules completely or partially can integrate together, can also independently realize.Here institute
The processing element stated can be a kind of integrated circuit, the processing capacity with signal.During realization, each step of the above method
The rapid or above modules can be complete by the integrated logic circuit of the hardware in processor elements or the instruction of software form
At.
For example, the above module can be arranged to implement one or more integrated circuits of above method, such as:
One or more specific integrated circuits (Application Specific Integrated Circuit, abbreviation ASIC), or,
One or more microprocessors (digital signal processor, abbreviation DSP), or, one or more scene can compile
Journey gate array (Field Programmable Gate Array, abbreviation FPGA) etc..For another example, when some above module passes through place
When managing the form realization of element scheduler program code, which can be general processor, such as central processing unit
(Central Processing Unit, abbreviation CPU) or it is other can be with the processor of caller code.For another example, these modules
It can integrate together, realized in the form of system on chip (system-on-a-chip, abbreviation SOC).
As shown in fig. 6, showing the structural schematic diagram for detecting terminal in one embodiment of the application.The detection that this example provides is whole
End, comprising: processor 61, memory 62, transceiver 63, communication interface 64 and system bus 65；Memory 62 and communication interface
64 connect with processor 61 and transceiver 63 and complete mutual communication by system bus 65, and memory 62 is based on storing
Calculation machine program, communication interface 64 and transceiver 63 are used for and other equipment are communicated, and processor 61 is for running computer journey
Sequence makes electric terminal execute each step of volatile organic component detection method as above.
System bus mentioned above can be Peripheral Component Interconnect standard (Peripheral Component
Interconnect, abbreviation PCI) bus or expanding the industrial standard structure (Extended Industry Standard
Architecture, abbreviation EISA) bus etc..The system bus can be divided into address bus, data/address bus, control bus etc..
Only to be indicated with a thick line in figure, it is not intended that an only bus or a type of bus convenient for indicating.Communication connects
Mouth is for realizing the communication between database access device and other equipment (such as client, read-write library and read-only library).Storage
Device may include random access memory (Random Access Memory, abbreviation RAM), it is also possible to further include non-volatile deposit
Reservoir (non-volatile memory), for example, at least a magnetic disk storage.
Above-mentioned processor can be general processor, including central processing unit (Central Processing Unit,
Abbreviation CPU), network processing unit (Network Processor, abbreviation NP) etc.；It can also be digital signal processor
(Digital Signal Processing, abbreviation DSP), specific integrated circuit (Application Specific
Integrated Circuit, abbreviation ASIC), field programmable gate array (Field-Programmable Gate Array,
Abbreviation FPGA) either other programmable logic device, discrete gate or transistor logic, discrete hardware components.
In conclusion the application provides volatile organic component detection method, device, storage medium and terminal, using phase
The assessment to VOCs quality stability in package paper is realized like degree algorithm and monodrome Quality Control figure, and using peeling off, value detection method is built
All kinds of VOCs component basic databases in vertical package paper, and on the basis of each VOCs component detection mean value, pass through similarity operator
Method calculates similarity between each batch sample and benchmark, is limited with similarity mean value and presupposition multiple Measurement of Similarity deviation or similarity
Value calculates Quality Control figure bound and center limit, draws similarity Quality Control figure, can the quality of fast and effective evaluate packaging paper stablize
Property.So the application effectively overcomes various shortcoming in the prior art and has high industrial utilization value.
The principles and effects of the application are only illustrated in above-described embodiment, not for limitation the application.It is any ripe
Know the personage of this technology all can without prejudice to spirit herein and under the scope of, carry out modifications and changes to above-described embodiment.Cause
This, those of ordinary skill in the art is complete without departing from spirit disclosed herein and institute under technical idea such as
At all equivalent modifications or change, should be covered by claims hereof.
Claims (10)
1. a kind of volatile organic component detection method characterized by comprising
The volatile component detection data for obtaining the multiple batches of sample of detected materials, formed accordingly the volatility of the detected materials at
Divided data set；
The detection reference data of each batch sample of the detected materials is obtained according to the volatile component data acquisition system, and respectively
The similarity between the volatile component detection data of each batch sample and corresponding detection reference data is calculated, determining accordingly should
Similarity upper limit threshold, central threshold and the lower threshold of detected materials；
Between the similarity and the upper limit threshold, central threshold and lower threshold of visualization output each batch sample
Comparison result information.
2. the method according to claim 1, wherein in the method formation the detected materials volatility at
The mode of divided data set includes:
Outlier Data is rejected from the volatile component detection data of the multiple batches of sample of the detected materials；
According to the volatile component detection data after Outlier Data is eliminated, the volatile component data of the detected materials are established
Library；Wherein the volatile component database includes each volatile component Testing index of each batch sample of the detected materials
And detection data.
3. the method according to claim 1, wherein the detection base value of each batch sample of the detected materials
According to the mean value for the whole volatile component detection datas for including each batch sample.
4. the method according to claim 1, wherein the described method includes: being calculated using cosine similarity algorithm
Similarity between the volatile component detection data of each batch sample and the detection reference data.
5. the method according to claim 1, wherein the described method includes:
According to the similarity between the volatile component detection data of each batch sample and the detection reference data, those are calculated
The similarity mean value of batch sample is as the central threshold.
6. method according to claim 1 or 5, which is characterized in that the described method includes: with the central threshold and first
The difference of presupposition multiple standard deviation determines the lower threshold, but lower threshold is not less than 0.
7. method according to claim 1 or 5, which is characterized in that the described method includes: with the central threshold and second
The sum of presupposition multiple standard deviation determines the upper limit threshold, but upper limit threshold is not higher than 1.
8. a kind of volatile organic component detection device characterized by comprising
Data acquisition module, the volatile component detection data of the multiple batches of sample for obtaining detected materials, being formed accordingly should
The volatile component data acquisition system of detected materials；
Data processing module, for obtaining the detection reference data of the detected materials according to the volatile component data acquisition system,
And the similarity between the volatile component detection data of each batch sample and the detection reference data is calculated separately, accordingly really
Upper limit threshold, central threshold and the lower threshold of the fixed detected materials；
Visualize output module, for visualize similarity and the upper limit threshold of output each batch sample, central threshold,
And the comparison result information between lower threshold.
9. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the computer program quilt
Processor realizes volatile organic component detection method described in any one of claims 1 to 7 when executing.
10. a kind of detection terminal characterized by comprising processor and memory；
The memory is for storing computer program；
The processor is used to execute the computer program of the memory storage, so that the terminal executes such as claim 1
To volatile organic component detection method described in any one of 7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111368432A (en) * | 2020-03-04 | 2020-07-03 | 广东石油化工学院 | Quality detection method, storage medium and equipment for centrifugal casting alloy furnace tube |
| CN114113466A (en) * | 2020-09-01 | 2022-03-01 | 中国石油化工股份有限公司 | Method and device for establishing fingerprint spectrum of volatile organic compound of production device |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106248850A (en) * | 2016-08-08 | 2016-12-21 | 云南中烟工业有限责任公司 | A kind of method of Fast Evaluation quality of flavoring essence for tobacco |
| CN107402547A (en) * | 2017-08-29 | 2017-11-28 | 北京易沃特科技有限公司 | Unit exception detection method and system based on the point analysis that peels off |
-
2019
- 2019-03-21 CN CN201910218123.5A patent/CN109975481A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106248850A (en) * | 2016-08-08 | 2016-12-21 | 云南中烟工业有限责任公司 | A kind of method of Fast Evaluation quality of flavoring essence for tobacco |
| CN107402547A (en) * | 2017-08-29 | 2017-11-28 | 北京易沃特科技有限公司 | Unit exception detection method and system based on the point analysis that peels off |
Non-Patent Citations (4)
| Title |
|---|
| 倪育才 编: "《实用测量不确定度评定》", 30 July 2016, 中国质检出版社、中国标准出版社 * |
| 戴晖等: "GC/MS法测定石油液化气残液中的挥发性有机化合物", 《贵州环保科技》 * |
| 赖燕华 等: "《卷烟质量稳定性综合评价》", 《中国烟草学报》 * |
| 郭伟清等: "《感器阵列结合化学计量学方法快速评估烟用包装材料中挥发性有机物》", 《分析化学研究报告》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111368432A (en) * | 2020-03-04 | 2020-07-03 | 广东石油化工学院 | Quality detection method, storage medium and equipment for centrifugal casting alloy furnace tube |
| CN111368432B (en) * | 2020-03-04 | 2023-05-30 | 广东石油化工学院 | Quality detection method, storage medium and equipment for centrifugally cast alloy furnace tube |
| CN114113466A (en) * | 2020-09-01 | 2022-03-01 | 中国石油化工股份有限公司 | Method and device for establishing fingerprint spectrum of volatile organic compound of production device |
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