CN104880422B - A kind of characterization method of visualized array sensor - Google Patents
A kind of characterization method of visualized array sensor Download PDFInfo
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- CN104880422B CN104880422B CN201510227959.3A CN201510227959A CN104880422B CN 104880422 B CN104880422 B CN 104880422B CN 201510227959 A CN201510227959 A CN 201510227959A CN 104880422 B CN104880422 B CN 104880422B
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Abstract
The invention discloses a kind of characterization method of visualized array sensor, the full spectral information of visualized array sensor is obtained using high light spectrum image-forming technology, and the spectral differences therefrom extracted under characteristic wavelength are used for the characterization of visualized array sensor.The present invention improves the accuracy of detection and stability of visualized array sensor, can be applied to the fields such as detection of gas with multiple constituents, Food Inspection.
Description
Technical field
The present invention relates to a kind of characterization method of visualized array sensor, refer in particular to a kind of using high light spectrum image-forming skill
Art carries out characterization, and then the method for improving its Detection results to visualized array sensor.
Background technology
Visualized array sensing technology is a kind of New Sensing Technology developed in recent years, and it has one using various
Determine the chemo-responsive dyes such as porphyrin, metalloporphyrin, the pH indicator of specific recognition ability and gas reaction produces characteristic response letter
Number, the characteristic spectrum of testing sample is obtained by signal processing system, and then carry out qualitative or quantitative analysis.
Can be sent out as the chemo-responsive dyes and the front and rear color of detected object effect of visualized array sensor sensing unit
Changing, its general principle is that detected gas occur the effect such as Molecular Adsorption, Hydrogenbond, covalent bond with developer, is drawn
Color developer molecules structure change is played so as to the absorption to special wavelength light changes.
Generally, this change can be characterized by two methods, i.e., ultraviolet-visible light spectral technology and three primary colors are imaged
Technology.The spectral information of more horn of plenty can be obtained due to ultraviolet-visible light spectral technology, therefore with larger application potential.
But ultraviolet-visible light spectral technology needs to gather spectral information one by one to the sensing unit in sensor array, to using sensing unit
More sensor array is time-consuming when being detected, laborious, or even is difficult to carry out, and operating error is larger.Additionally, ultraviolet-visible
Spectral technique is generally only applicable to liquid sensor array, helpless for solid-state sensor array and gas detection.Relative to purple
Outward-visible spectrum technology, three primary colors imaging technique then can be with the color change of the whole sensor array of quick obtaining.However, its generation
Valency is that three primary colors imaging technique can only obtain three variate-values of red, green, blue, and information content is less.Additionally, for three primary colors imaging
The sensitivity spectrum of three kinds of imaging units of equipment such as camera, scanner intersect, cause three variables of red, green, blue
Comprising more redundancy.In sum, there is a problem of cannot be while take into account precision and operation convenience for prior art.
High light spectrum image-forming technology can also obtain its spatial information while detected object spectral information is obtained, and
The advantage of ultraviolet-spectral technique and three primary colors imaging technique is turned round and look at.Additionally, high light spectrum image-forming technology can also pass visualized array
The spectra collection scope of sensor is expanded to infrared range.Therefore, high light spectrum image-forming technology is applied to visualized array sensing skill
Art, it is contemplated that the accuracy of detection and stability of visualized array sensor can be improved, and it is easy to operate, it is time saving and energy saving.In addition, its
Liquid sensor array is applicable not only to, the solid sensor array with nontransparent substrate is also applied for.
The content of the invention
It is an object of the invention to provide a kind of characterization method of visualized array sensor, to improve model prediction
The stability and precision of result.
In order to solve the above technical problems, the present invention carries out letter using high light spectrum image-forming technology to visualized array sensor
Number characterize, concrete technical scheme is as follows：
A kind of characterization method of visualized array sensor, it is characterised in that comprise the following steps：
Step one, is reacted, and obtained using Hyperspectral imager using visualized array sensor and detected object
High spectrum image I before visualized array sensor and detected object reactionbWith reacted high spectrum image Ia；
Step 2, by high spectrum image IbAnd IaExtract the original spectrum of xth sensing unit one by one respectively, S is designated as respectivelyb-x
And Sa-x；Standard is carried out to original spectrum, and just too change of variable and rolling average are pre-processed, so that before obtaining pretreated reaction
Spectrum Sb-x-pWith spectrum S after reactiona-x-p；X is the sensing unit sum on visible sensor, 1≤x≤X；
Step 3, to spectrum S before the reaction of xth sensing unitb-x-pWith anti-rear spectrum Sa-x-pSpectrum is poor, obtains xth sensing
The difference spectrum S of unitd-x=Sa-x-p–Sb-x-p；
Step 4, according to the coefficient correlation between spectral differences and detected object actual concentrations, selects xth sensing unit
Take the preceding n characteristic wavelength λ with detected object correlation maximumx-1, λx-2..., λx-n；1≤n≤6；
Step 5, with the characteristic wavelength λ for preferably going outx-1, λx-2..., λx-(n-1), λx-nUnder spectral differences Rx-1,
Rx-2..., Rx-(n-1), Rx-nCharacterize the color signal change of xth sensing unit；To the color signal changing value of all sensing units
Ri-1, Ri-2..., Ri-nAfter carrying out principal component analysis, m principal component PC before choosing1, PC2..., PCmCharacterize whole sensor array
Color signal changes；M=1,2 ..., 7；
Step 6, by the principal component PC corresponding to various concentrations object to be detected1, PC2..., PCmIt is dense as input variable
Angle value sets up the Quantitative Prediction Model Y=F (PC of object to be detected as output variable1, PC2..., PCm)；Sample is surveyed
Regularly, gained Principal component will be processed by above step and will substitute into above-mentioned model realization quantitative forecast.I=1,2 ..., X；M=1,
2 ..., 7.
The present invention has beneficial effect.
1. the present invention utilizes high light spectrum image-forming technology, and energy is quick, easily obtain the complete of whole visualized array sensor
Spectral information, is remarkably improved the detection stability and precision of visualized array sensor.
2. in high-spectral data block of the present invention enrich spectral information, can targetedly obtain each sensing unit with it is to be detected
Color signal change under the related characteristic wavelength of object, is that more practical and convenient multispectral equipment development lays the foundation.
3. by expanding spectra collection scope, the spectral information that can obtain sensor array near infrared region becomes the present invention
Change, information representation more horn of plenty, comprehensively.
Brief description of the drawings
Fig. 1 is Hyperspectral imager schematic diagram of the present invention for visualized array sensor detection.
Fig. 2 is visualized array sensor characterization flow chart of the present invention based on hyperspectral information.
Fig. 3 a are testing result of the present invention based on high spectrum image.
Fig. 3 b are the testing result based on three-primary-color image.
In figure：1 shell, 2 EO-1 hyperion cameras, 3 optical fiber, 4 line sources, 5 light sources, 6 reative cells, 7 electronic control translation stages, 8 gases
Entrance, 9 visualized array sensors, 10 high spectrum images, 11 computers, 12 gas vents.
Specific embodiment
To make the purpose, technical scheme and advantage of the embodiment of the present invention clearer, below in conjunction with the embodiment of the present invention
In accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is
A part of embodiment of the present invention, rather than whole embodiments, based on the embodiment in the present invention, those of ordinary skill in the art
The every other embodiment obtained on the premise of creative work is not made, belongs to the scope of protection of the invention.
The present embodiment is predicted, device therefor using 4 × 4 sensor arrays by taking ammonia detection as an example to ammonia concentration
As shown in figure 1, information process is as shown in Figure 2.The present invention is comprised the following steps：
(1) preferred porphyrin and pH indicator are made into the solution of 0.05mol/L using chloroform or ethanol, using capillary
Point sample method point after room temperature is dried, is sealed, kept in dark place, standby to 4 × 4 sensor arrays are made in reverse phase silica gel plate substrate；
(2) the EO-1 hyperion system boot preheating 30min, and blank and dark correction are carried out successively.By the visualization
It is the reative cell 6 of transparency silica glass that sensor array 9 is put into top, and pure nitrogen is passed through 20 minutes to clean by gas access
Whole air-channel system and sensor.
(3) after cleaning terminates, electronic control translation stage 7 is made to drive reative cell 6 to vertically move with the speed of 1.25mm/s, EO-1 hyperion
Linear array detector in camera 2 carries out transversal scanning along optics focal plane vertical direction, obtains each pixel of strip space in each ripple
The spectral information of strong point；As sensor array is longitudinally advanced, linear array detector can complete the collection of whole sensor array data.
Spectra collection is 430~960nm at intervals of 0.858nm, acquisition range, collects the image under 618 wavelength, is finally given
One size for 618 × 1628 × 618 the (I of high spectrum image 10b), and store to computer 11.
(4) required concentration ammonia is passed through by gas access 8, continues to make within 20 minutes the sensitive pigment in ammonia and sensor array
Fully reaction.Then the reacted high spectrum image I of visualized array sensor is obtained according to step (3)a.The ammonia concentration
0.5,1,2,3.5,5,7.5,10ppm totally 7 gradients, 12 sensor arrays of each concentration mensuration, totally 84 is set altogether.
(5)IbAnd IaAfter being corrected through black and white, the original spectrum S of xth sensing unit is extracted one by one using ENVI4.5b-xWith
Sa-x, average and standard normal variable preconditioning is moved to original spectrum, so as to obtain light before pretreated reaction
Spectrum Sb-x-pWith spectrum S after reactiona-x-p。
(6) it is poor to the spectrum before and after the reaction of xth sensing unit, obtain the difference spectrum S of xth sensing unitd-x=Sa-x-p-
Sb-x-p。
(7) composed using the difference under xth sensing unit various concentrations and calculate spectral differences and ammonia concentration under each wavelength respectively
Coefficient correlation C between valuex-λ.Choosing 3 has Ju portions great ∣ Cx-λWavelength (the λ of ∣x-1, λx-2, λx-3) as the sensing unit
Characteristic wavelength.With λx-1, λx-2, λx-3Corresponding spectral differences Rx-1, Rx-2, Rx-3The color signal for characterizing the sensing unit becomes
Change.
(8) to the color signal changing value R of all sensing units1-1, R1-2, R1-3, R2-1..., R16-3Carry out principal component point
After analysis, preceding 3 principal component PC are chosen1, PC2, PC3Characterize the color signal change of whole sensor array.
(9) by the principal component PC corresponding to various concentrations ammonia1, PC2, PC3Used as input variable, concentration value is used as output
Variable, sets up the Quantitative Prediction Model Y=F (PC of ammonia1, PC2, PC3)；By corresponding to sample when being analyzed to specific sample
PC1, PC2, PC3Substituting into above-mentioned model carries out quantitative forecast.Testing result such as Fig. 3 a institute of the present invention based on high spectrum image
Show；And the ammonia concentration of three-primary-color image predicts the outcome as shown in Figure 3 b.Compares figure 3a and Fig. 3 b are visible, based on high spectrum image
Model prediction result substantially improved, its stability and precision are improved significantly.
Claims (1)
1. a kind of characterization method of visualized array sensor, it is characterised in that comprise the following steps：
Step one, is reacted using visualized array sensor and detected object, and obtains visual using Hyperspectral imager
Change the high spectrum image I before sensor array reacts with detected objectbWith reacted high spectrum image Ia；
Step 2, by high spectrum image IbAnd IaExtract the original spectrum of xth sensing unit one by one respectively, S is designated as respectivelyb-xWith
Sa-x；Standard is carried out to original spectrum, and just too change of variable and rolling average are pre-processed, so as to obtain light before pretreated reaction
Spectrum Sb-x-pWith spectrum S after reactiona-x-p；X is the sensing unit sum on visible sensor, 1≤x≤X；
Step 3, to spectrum S before the reaction of xth sensing unitb-x-pWith anti-rear spectrum Sa-x-pSpectrum is poor, obtains xth sensing unit
Difference spectrum Sd-x=Sa-x-p–Sb-x-p；
Step 4, according to the coefficient correlation between spectral differences and detected object actual concentrations, before being chosen to xth sensing unit
The n characteristic wavelength λ with detected object correlation maximumx-1, λx-2..., λx-n；1≤n≤6；
Step 5, with the characteristic wavelength λ for preferably going outx-1, λx-2..., λx-(n-1), λx-nUnder spectral differences Rx-1, Rx-2...,
Rx-(n-1), Rx-nCharacterize the color signal change of xth sensing unit；To the color signal changing value R of all sensing unitsi-1,
Ri-2..., Ri-nAfter carrying out principal component analysis, m principal component PC before choosing1, PC2..., PCmCharacterize the color of whole sensor array
Signal intensity；M=1,2 ..., 7；
Step 6, by the principal component PC corresponding to various concentrations object to be detected1, PC2..., PCmAs input variable, concentration value
As output variable, the Quantitative Prediction Model Y=F (PC of object to be detected are set up1, PC2..., PCm)；Sample is measured
When, gained Principal component will be processed by above step and substitute into above-mentioned model realization quantitative forecast, i=1,2 ..., X；M=1,
2 ..., 7.
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| CN105675601B (en) * | 2016-03-04 | 2019-05-31 | 江苏大学 | The system and detection method of a kind of field quick detection catechol and its derivative |
| CN109883959B (en) * | 2019-02-26 | 2021-11-23 | 江苏大学 | Portable multispectral imaging device based on array sensor chip and application thereof |
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