CN104568821B - It is a kind of to detect that 7 refer to calibration method in coal sample simultaneously - Google Patents
It is a kind of to detect that 7 refer to calibration method in coal sample simultaneously Download PDFInfo
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Abstract
Detect that 7 refer to calibration method in coal sample simultaneously the invention discloses a kind of.It the described method comprises the following steps：S1. several coal samples are collected and prepare, conventional method determines 7 indexs of content and caloric value of interior water, ash content, volatile matter, full sulphur, fixed carbon and the flammable body of each sample respectively；S2. the spectroscopic data and curve of described 7 indexs of coal sample are collected with the scanning of NIRS analyzers；S3. the spectroscopic data of sample obtained by S2 is handled, calculates the calibration equation for obtaining 7 indexs through returning, detection model is set up after amendment and checking；S4., coal sample to be measured is directly filled to the injector of NIRS instrument successively, starts scanning key, the automatic record storage sample spectra of NIR instrument determines that sample belongs to spectrogram type, selects corresponding detection model, obtains testing result.The degree of accuracy of 7 crucial index detection methods conforms to current standards the requirement of method repeatability limit difference in the coal that the present invention is set up, and operation is very easy to be quick, and a few minutes can just complete the scanning of sample and the detection of 7 indexs, include the output of data.During whole detection operation, without claiming sample, without adding any chemical reagent, with quick, convenient, free of contamination feature.
Description
Technical field
The present invention relates to coal analysis detection technique field, 7 are detected in coal sample simultaneously more particularly, to a kind of
Refer to calibration method.
Background technology
Coal resources are the first big energy of China, are the basic energy resource materials needed for industrial development.Coal resources in China
Enrich very much, account for 70% or so of China's total energy.
According to international coal examination criteria, coal usually requires to detect the quality project such as interior water.By China's national regulation
Needed with trade, coal need to generally detect the indexs such as caloric value, full sulphur, interior water, volatile matter, ash content, fixed carbon, flammable body, it is existing
The standard method of row detection 7 indexs is mainly：Interior water has GB/T 212, ISO 11722, ASTMD 3173, and ash content has
GB/T 212, ISO 1171, ASTMD 3174, volatile matter have GB/T 212, ISO 562, ASTMD 3175, and full sulphur has GB/T
214th, ISO 351, ASTMD 4239, caloric value have GB/T 213, ISO 1928, ASTMD 5865, fixed carbon and flammable body ginseng
Carried out according to the requirement in the Industry Analysis Method of coal.
The classical or modern chemical method and physical-chemical process that above-mentioned standard method is generally used：Interior water, volatile matter, ash
Divide, fixed carbon, flammable body are all classical gravimetric methods, be related to the equipment such as balance, baking oven, high temperature furnace, carbonization, ashing, perseverance
Weight, weigh, calculate be frequently necessary to carry out the step of, it is quite cumbersome time-consuming；Even if using more advanced instrument, one at present
Technical staff completes these projects and also obtained 5~6 days, while the operation of the physical chemistry instrument of modernization, maintenance, demarcation, verification
It is also very heavy Deng work.The traditional detection method of coal is numerous and diverse due to working, and spends cost higher, spends the time long.
Quick demand of the classification sale of coal, the export trade and power plant etc., traditional coal round of visits is oversize, is unfavorable for coal
Sale, the Check-Out Time for shortening coal is needed for this, it is necessary to find the new method of inspection.
NIRS is the english abbreviation of near infrared spectrum.NIRS technologies are high-new analysis skills with the fastest developing speed nearly ten years
One of art.NIRS analytical technology application spectrum section wave-length coverages are about 3~0.70mm, the dry infrared range of spectrum of category, and can
See that light is the same, be all a part of electromagnetic wave, the general characteristic shown when being acted on electromagnetic wave and object, such as thoroughly
Penetrate, diffusing reflection, absorption etc..In addition, the characteristics of it is most prominent be this SPECTRAL REGION for hydric group (OH, SH, CH, NH) times
Frequency and sum of fundamental frequencies uptake zone.The near infrared spectrum of material is the frequency multiplication of wherein each group vibration and the synthesis absorption table of combination frequency
It is existing.
NIRS is quickly grown nearly ten years, and China is mainly used in the quality point of agricultural product since the eighties in last century
Analysis, through being applied to every field, expands to petrochemical industry and basic organic chemical industry, height from traditional agricultural byproducts analysis
The field such as molecule chemical industry, pharmacy and clinical medicine, biochemical industry, environmental science, textile industry and food industry.But, at present
Research report of the NIRS technologies in terms of coal is seldom.
Data shows that the presence that foreign countries' report is detected using NIRS technologies to coal is much difficult, and there is use the country
Fourier transform near infrared spectrum method sets up coal volatile matter, determination of moisture model, but does not propose to determine using NIRS technologies
Amount analysis Coal ' moisture, the concrete technical scheme of volatile matter.The applicant is summed up using near red by long-term substantial amounts of research
The correlation merit project quick determination method that outer analysis technology sets up coal be it is feasible, still, the following emphasis skill to be solved
Art problem is not solved effectively always：(1) the suitable mathematics transition form of coal NIRS spectroscopic datas is found；(2) find and close
Reliable functional relation between the NIRS detection data of suitable mathematics conversion and the detection data of coal quality composition conventional method；(3)
To further amendment and the checking of gained functional relation.Have no and set up using NIR technology while detecting coal sample 7
The technology report of the quick determination method of index.
The content of the invention
The technical problem to be solved in the present invention is that there is provided specific NIRS spectroscopic datas are suitable for the detection of water in coal
Mathematics transition form, sum up suitable mathematical conversion NIRS detect 7 quality component conventional methods of data and coal detection
Reliable functional relation between data, and further amendment and checking detect coal simultaneously there is provided a kind of to gained functional relation
7 refer to calibration method in sample.
The purpose of the present invention is achieved by the following technical programs：
There is provided a kind of while detecting that 7 refer to calibration method in coal sample, comprise the following steps：
S1. several coal samples are collected and prepare, conventional method determines the interior water, ash content, volatilization of each sample respectively
Point, 7 indexs of content and caloric value of full sulphur, fixed carbon and flammable body；
S2. the spectroscopic data and curve of the coal sample are collected with the scanning of NIRS analyzers；
S3. the spectroscopic data of sample obtained by S2 is handled, calculates the calibration equation for obtaining 7 indexs through returning, repair
Just detection model is set up with after water in checking；
S4., coal sample to be measured is directly filled to the injector (being not required to claim sample) of NIRS instrument successively, starts scanning key, NIR
The automatic record storage sample spectra of instrument.Determine that sample belongs to spectrogram type, select corresponding detection model, obtain testing result.
Scan with NIRS analyzers that to collect the spectroscopic data of the sample be by sample (being not required to claim sample), successively directly described in S2
The injector of the full NIRS instrument of tipping, is scanned using digital raster system, is recorded automatically by NIRS instrument and storage sample light
Spectrum.The sample original spectrum being collected into is classified by its different variation tendency, it is identical or close with variation tendency according to peak type
Collection of illustrative plates is combined, and is sorted out, and respectively obtains Y types original spectrum, W types original spectrum, p-type original spectrum and X-type primary light
Spectrum.
It is that spectrum analysis is carried out using WinISI softwares and built to the spectroscopic data progress processing of sample obtained by S2 described in S3
Vertical detection model, NIRS instrument is imported by the spectroscopic data of sample obtained by S2, determines detection model, prints testing result.Spectrum is pre-
The methods such as trend converter technique, standard normal variable transformation approach, Multivariate Discrete correction, the correction of anti-phase Multivariate Discrete are respectively adopted in processing
One or more, it is final to determine optimization process method；Regression correction method uses Stepwise Regression Method (SMLR), principal component
Analytic approach (PCA) and minimal error analytical method (PLS), by Data Dimensionality Reduction, to eliminate letter overlapped in numerous information co-exists
Cease partly and finally accomplish the quantization to spectrum.
Water content in the sample of one group of unknown component content to be measured is detected using detection model, then by obtained by NIR methods
Detected value is compared and evaluated with Typical physical chemical method detected value.The comparative result of two methods prediction standard deviation
(SEP, Standard Error of Prediction) and the corresponding coefficient of determination (RSQp) or coefficient R p are weighed.
The method for building up of described detection model comprises the following steps：
S31.GH values are analyzed, and the sample that the GH values are more than 3.0 are rejected, the sample sets for being less than 3.0 with GH values are built respectively
Calibration (detection) model of vertical respective type spectrogram；
S32. the SEC values and RSQ values of (detection) model are calibrated described in S31 by calculating；
S33. evaluation experimental is carried out to detection model and determines optimum detection model.The present invention uses validation-cross error
(Standard Error of cross validation, SECV) and the validation-cross coefficient of determination (1 minus the
Variance ratio, 1-VR) or coefficient R v weigh detection model.Detection can be effectively assessed by the two indexs
The prediction accuracy of model.Good detection model is evaluated with owning using with low SECV values and high (1-VR) or Rv values
Detection model interacts checking test, selects the detection model of minimum SECV values and highest (1-VR) or Rv values, is defined as most
Good detection model.
Beneficial effects of the present invention are as follows：
The principle of the existing examination criteria of coal is all classical or modern chemical method and physical-chemical process：Interior water, volatile matter,
Ash content, fixed carbon, flammable body are all classical gravimetric methods, are related to the equipment such as balance, baking oven, high temperature furnace, be carbonized, be ashed,
Constant weight, weighing, calculate be frequently necessary to carry out the step of, it is quite cumbersome time-consuming；Caloric value, full sulphur, state-of-the-art at present is to adopt
Use HTHP combustion method, but the operation of the physical chemistry instrument of modernization, maintenances, demarcation are also very heavy.
For a long time, near-infrared spectrum technique is used for analyzing pure organic matter.Because the wave number of near infrared spectrum exists
4000cm-1Above (i.e. below 2500nm), therefore, only vibration frequency is in 2000cm-1Vibration above, is only possible near red
One-level frequency multiplication is produced in outskirt, and can be in 2000cm-1Produce fundamental vibration above mainly contains hydrogen functional group, such as C-H, N-
H, S-H and O-H stretching vibration.Almost in organic matter all hydric groups information, can be able near infrared spectrum anti-
Reflect.
Coal is a kind of flammable rock.It is this by major part that near-infrared spectrum technique is applied to coal by the present invention first
The compounding substances system of organic substance and part mineral matter and moisture composition, and it is successfully established 7 key indexs in coal sample
The method of detection, so as to prove that near-infrared spectrum technique can apply to analyze inorganic substances to a certain extent, overcomes simultaneously
Prior art prejudice.
The present invention establishes the near infrared detection method of water in coal, has filled up prior art blank, and solve following
Focus technology problem：Sum up what the suitable mathematics transition form of coal NIRS spectroscopic datas was changed there is provided suitable mathematical
NIRS detects reliable functional relation between data and the detection data of coal quality composition conventional method, and gained functional relation is carried
Practical, reliable and stable amendment and verification method are supplied.
Based on the inventive method, water in coal, ash content, volatile matter, full sulphur, fixed carbon and flammable body are obtained respectively
4 detection models of each index in 7 indexs of content and caloric value, and foundation can be applied to daily practice examining work
In new detection method.7 indexs in present invention detection coal sample only need a few minutes, and need not claim sample, without using changing
The test condition such as reagent or high temperature, high pressure, high current is learned, chemistry, biological or electromagnetic pollution will not be produced, will not be to operating personnel
Had undesirable effect with environment, continuous detection can be achieved, to mass detection task, its superiority is more protruded.
The present invention is compared with current methods, with significant superiority.(1) lacking a kind of ground simple and easy to apply at present can be once
Property analysis simultaneously obtain the detection methods of 7 key indexs, the present invention can successfully solve this technical barrier.The present invention is provided
New method detection obtain 7 key components in coal sample and only need a few minutes, and sample need not be claimed, without using chemical reagent
Or the test condition such as high temperature, high pressure, high current, chemistry, biological or electromagnetic pollution will not be produced, will not be to operating personnel and environment
Have undesirable effect.(2) for the single Indexes Comparison of each single item：
The detection of moisture, compared with existing Oven Method：The original spectrogram calibration standard deviation of Y types is 0.14%, and calibration is related
Coefficient is 0.9969；Validation-cross standard deviation 0.15%, validation-cross coefficient correlation 0.9965；The standard deviation of Preliminary Applications is
0.17%, coefficient correlation is 0.995.The original spectrogram calibration standard deviation of W types is 0.25%, and calibration coefficient correlation is 0.9021；
Validation-cross standard deviation 0.28%, validation-cross coefficient correlation 0.8756；The standard deviation of Preliminary Applications is 0.23%, phase relation
Number is 0.875.The original spectrogram calibration standard deviation of p-type is 0.41%, and calibration coefficient correlation is 0.9814；Validation-cross standard deviation
0.47%, validation-cross coefficient correlation 0.9746；The standard deviation of Preliminary Applications is 0.83%, and coefficient correlation is 0.944.X-type
Original spectrogram calibration standard deviation is 0.12%, and calibration coefficient correlation is 0.9981；Validation-cross standard deviation 0.31%, interaction is tested
Demonstrate,prove coefficient correlation 0.9874；The standard deviation of Preliminary Applications is 0.13%, and coefficient correlation is 0.997.
The detection of ash content, compared with existing high temperature oven process：The original spectrogram calibration standard deviation of Y types is 0.34%, calibrates phase
Relation number is 0.9955；Validation-cross standard deviation 0.35%, validation-cross coefficient correlation 0.9954；The standard deviation of Preliminary Applications
For 0.77%, coefficient correlation is 0.980.The original spectrogram calibration standard deviation of W types is 0.51%, and calibration coefficient correlation is
0.9851；Validation-cross standard deviation 0.74%, validation-cross coefficient correlation 0.9687；The standard deviation of Preliminary Applications is
0.57%, coefficient correlation is 0.982.The original spectrogram calibration standard deviation of p-type is 1.29%, and calibration coefficient correlation is 0.9785；
Validation-cross standard deviation 1.62%, validation-cross coefficient correlation 0.9659；The standard deviation of Preliminary Applications is 1.32%, phase relation
Number is 0.970.The original spectrogram calibration standard deviation of X-type is 1.48%, and calibration coefficient correlation is 0.9879；Validation-cross standard deviation
2.05%, validation-cross coefficient correlation 0.9763；The standard deviation of Preliminary Applications is 3.88%, and coefficient correlation is 0.926.
Volatile matter is detected, compared with existing high temperature oven process：The original spectrogram calibration standard deviation of Y types is 0.27%, calibrates phase
Relation number is 0.9922；Validation-cross standard deviation 0.29%, validation-cross coefficient correlation 0.9911；The standard deviation of Preliminary Applications
For 0.37%, coefficient correlation is 0.986.The original spectrogram calibration standard deviation of W types is 0.22%, and calibration coefficient correlation is
0.9618；Validation-cross standard deviation 0.24%, validation-cross coefficient correlation 0.9521；The standard deviation of Preliminary Applications is
0.25%, coefficient correlation is 0.928.The original spectrogram calibration standard deviation of p-type is 0.93%, and calibration coefficient correlation is 0.9889；
Validation-cross standard deviation 1.05%, validation-cross coefficient correlation 0.9858；The standard deviation of Preliminary Applications is 0.89%, phase relation
Number is 0.975.The original spectrogram calibration standard deviation of X-type is 0.59%, and calibration coefficient correlation is 0.9991；Validation-cross standard deviation
0.65%, validation-cross coefficient correlation 0.9989；The standard deviation of Preliminary Applications is 1.61%, and coefficient correlation is 0.994.
The detection of full sulphur, compared with high-temp combustion infrared absorption method：The original spectrogram calibration standard deviation of Y types is 0.06%,
It is 0.9838 to calibrate coefficient correlation；Validation-cross standard deviation 0.07%, validation-cross coefficient correlation 0.9822；The mark of Preliminary Applications
Quasi- deviation is 0.08%, and coefficient correlation is 0.976.The original spectrogram calibration standard deviation of W types is 0.04%, and calibration coefficient correlation is
0.9496；Validation-cross standard deviation 0.05%, validation-cross coefficient correlation 0.9379；The standard deviation of Preliminary Applications is
0.05%, coefficient correlation is 0.917.The original spectrogram calibration standard deviation of p-type is 0.17%, and calibration coefficient correlation is 0.9572；
Validation-cross standard deviation 0.21%, validation-cross coefficient correlation 0.9330；The standard deviation of Preliminary Applications is 0.22%, phase relation
Number is 0.927.The original spectrogram calibration standard deviation of X-type is 0.11%, and calibration coefficient correlation is 0.8988；Validation-cross standard deviation
0.16%, validation-cross coefficient correlation 0.7412；The standard deviation of Preliminary Applications is 0.12%, and coefficient correlation is 0.849.
The detection of caloric value, compared with existing oxygen bomb combustion：The original spectrogram calibration standard deviation of Y types is 0.12MJ/Kg,
It is 0.9960 to calibrate coefficient correlation；Validation-cross standard deviation 0.14MJ/Kg, validation-cross coefficient correlation 0.9951；Preliminary Applications
Standard deviation be 0.26MJ/Kg, coefficient correlation is 0.983.The original spectrogram calibration standard deviation of W types is 0.22MJ/Kg, calibration
Coefficient correlation is 0.9815；Validation-cross standard deviation 0.31MJ/Kg, validation-cross coefficient correlation 0.9610；The mark of Preliminary Applications
Quasi- deviation is 0.27MJ/Kg, and coefficient correlation is 0.972.The original spectrogram calibration standard deviation of p-type is 0.48MJ/Kg, and calibration is related
Coefficient is 0.9734；Validation-cross standard deviation 0.60MJ/Kg, validation-cross coefficient correlation 0.9594；The standard deviation of Preliminary Applications
Difference is 0.88MJ/Kg, and coefficient correlation is 0.971.The original spectrogram calibration standard deviation of X-type is 0.45%, and calibration coefficient correlation is
0.9830；Validation-cross standard deviation 0.72MJ/Kg, validation-cross coefficient correlation 0.9582；The standard deviation of Preliminary Applications is
1.20MJ/Kg, coefficient correlation is 0.901.
The detection of fixed carbon, compared with existing baking oven, high temperature oven process：The original spectrogram calibration standard deviation of Y types is 0.29%,
It is 0.9948 to calibrate coefficient correlation；Validation-cross standard deviation 0.30%, validation-cross coefficient correlation 0.9931；The mark of Preliminary Applications
Quasi- deviation is 0.43%, and coefficient correlation is 0.986.The original spectrogram calibration standard deviation of W types is 2.20%, and calibration coefficient correlation is
0.8499；Validation-cross standard deviation 2.49%, validation-cross coefficient correlation 0.8036；The standard deviation of Preliminary Applications is
2.11%, coefficient correlation is 0.835.The original spectrogram calibration standard deviation of p-type is 1.34%, and calibration coefficient correlation is 0.9731；
Validation-cross standard deviation 1.65%, validation-cross coefficient correlation 0.9587；The standard deviation of Preliminary Applications is 3.10%, phase relation
Number is 0.941.The original spectrogram calibration standard deviation of X-type is 1.66%, and calibration coefficient correlation is 0.9883；Validation-cross standard deviation
2.16%, validation-cross coefficient correlation 0.9802, the standard deviation of Preliminary Applications is 2.64%, and coefficient correlation is 0.972.
The detection of flammable body, compared with existing baking oven, high temperature oven process：The original spectrogram calibration standard deviation of Y types is 0.34%,
It is 0.9954 to calibrate coefficient correlation；Validation-cross standard deviation 0.37%, validation-cross coefficient correlation 0.9948；The mark of Preliminary Applications
Quasi- deviation is 0.60%, and coefficient correlation is 0.988.The original spectrogram calibration standard deviation of W types is 2.35%, and calibration coefficient correlation is
0.8414；Validation-cross standard deviation 2.62%, validation-cross coefficient correlation 0.7981；The standard deviation of Preliminary Applications is
2.19%, coefficient correlation is 0.819.The original spectrogram calibration standard deviation of p-type is 1.32%, and calibration coefficient correlation is 0.9685；
Validation-cross standard deviation 1.51%, validation-cross coefficient correlation 0.9586；The standard deviation of Preliminary Applications is 4.67%, phase relation
Number is 0.867.The original spectrogram calibration standard deviation of X-type is 1.34%, and calibration coefficient correlation is 0.9874；Validation-cross standard deviation
1.92%, validation-cross coefficient correlation 0.9738；The standard deviation of Preliminary Applications is 3.32%, and coefficient correlation is 0.930.
Present invention only requires using near-infrared spectrometers, it is possible to instead of prior art is a variety of, many analyses
Instrument, it is only necessary to grind away equipment, it is not necessary to assay balance, generally only needs people's operation, and within a few minutes, pass through collection one
The spectrum of secondary sample, it is possible to while completing the measure of 7 indexs of coal sample.Except consumption electricity during spectra collection
Can be outer, consumption any reagent and standard substance are not required to, can so save a large amount of instrument and equipments the expense such as purchases, operates, repairing
With saving substantial amounts of time and manpower greatly reduce analysis cost, significantly improve the efficiency of detection work.
Brief description of the drawings
The near-infrared diffusing reflection DDS original spectrum total figures of 509 anthracite samples of Fig. 1.
The near-infrared diffusing reflection DDS original spectrum total figures of 134 bituminous coal samples of Fig. 2.
The near-infrared diffusing reflection DDS original spectrum total figures of 155 steam coal samples of Fig. 3.
The near-infrared diffusing reflection DDS original spectrum total figures of 60 meager lean coal samples of Fig. 4.
The near-infrared diffusing reflection DDS original spectrum total figures of 134 power coal samples of Fig. 5.
The near-infrared diffusing reflection DDS original spectrum total figures for the sample that packet is not known in Fig. 6 179.
The near-infrared diffusing reflection DDS original spectrums total figure (sample in 2008) of 202 anthracite samples of Fig. 7.
The near-infrared diffusing reflection DDS original spectrums total figure (sample in 2008) for the sample that packet is not known in Fig. 8 235.
The original spectrogram of Fig. 9 standard specimens (being above 103f anthracites, lower is 101L bituminous coal).
The original spectrogram of Figure 10 certified reference coals.
Figure 11 anthracites in 2008 and the anthracitic original spectrogram of standard specimen.
The original spectrogram of Figure 12 2005-2008 bituminous coal and standard specimen bituminous coal.
Figure 13 anthracites in 2008 and standard specimen anthracite original spectrum handle figure through (NONE+0011).
Figure 14 anthracites in 2008 and standard specimen anthracite original spectrum handle figure through (NONE+1441).
Figure 15 anthracites in 2008 and standard specimen anthracite original spectrum handle figure through (D+1441).
Figure 16 anthracites in 2008 and standard specimen anthracite original spectrum handle figure through (D+1441).
The original spectrum of Figure 17 2005-2008 bituminous coal and standard specimen bituminous coal handles figure through (NONE+0011).
The original spectrum of Figure 18 2005-2008 bituminous coal and standard specimen bituminous coal handles figure through (D+1441).
The original spectrum of Figure 19 2005-2008 bituminous coal and standard specimen bituminous coal handles figure through (D+0011).
509 anthracite sample original spectrums of Figure 20 handle figure through (NONE+1441).
509 anthracite sample original spectrums of Figure 21 handle figure through (NONE+0011).
509 anthracite sample original spectrums of Figure 22 handle figure through (D+1441).
Figure 23 Y types (374) primary light spectrogram.
Figure 24 W types (1367) primary light spectrogram.
Figure 25 p-types (436) original spectrogram.
Figure 26 X-types (52) original spectrum.
The GH Distribution value figures of the original spectrogram of Figure 27 Y types.
The GH Distribution value figures of the original spectrogram of Figure 28 W types.
The GH Distribution value figures of the original spectrogram of Figure 29 p-types.
The GH Distribution value figures of the original spectrogram of Figure 30 X-types.
Water detection model (MPLS+D+1441) in Y type original spectrums of the Figure 31 through validation-cross.
Water surveys model (PLS+D+0011) in W types original spectrum inspections of the Figure 32 through validation-cross.
Water detection model (MPLS+D+0011) in p-type original spectrums of the Figure 33 through validation-cross.
Water surveys model (MPLS+NONE+2441) in X-type original spectrum inspections of the Figure 34 through validation-cross.
Embodiment
Below in conjunction with the accompanying drawings the present invention is further illustrated with specific embodiment.The equipment that the embodiment of the present invention is used can refer to
《High temperature process furnances combustion method analyzes the standard specimen method of sulfur content in coal and coke analysis sample》(ASTMD-4239-
2010e1)、《Proximate analysis of coal》(GB/T212-2008)、《The heat output determining method of coal》(GB/T213-2008) in
Listed equipment and reagent.Other unless stated otherwise, the reagent and equipment that the embodiment of the present invention is used is commonly used in the art
Reagent and equipment.
Embodiment 1
The present embodiment provides a kind of while detecting that 7 refer to calibration method in coal sample, comprise the following steps：
S1. several coal samples are collected and prepare, conventional method determines the interior water, ash content, volatilization of each sample respectively
Point, 7 indexs of content and caloric value of full sulphur, fixed carbon and flammable body；
S2. the spectroscopic data and curve of the coal sample are collected with the scanning of NIRS analyzers；
S3. the spectroscopic data of sample obtained by S2 is handled, calculates the calibration equation for obtaining 7 indexs through returning, repair
Just detection model is set up with after water in checking；
S4., coal sample to be measured is directly filled to the injector (being not required to claim sample) of NIRS instrument successively, starts scanning key, NIRS
The automatic record storage sample spectra of instrument.Determine that sample belongs to spectrogram type, select corresponding detection model, obtain testing result.
Wherein, the method for coal sample being collected and preparing described in S1 is reference《Sample for commercial coal takes method》(GB475-
2008) and《The preparation method of coal sample》(GB474-2008) requirement in is carried out.The interior water of the conventional method determination sample contains
The method of amount be by《Proximate analysis of coal》(GB/T212-2008) carry out, the conventional method determination sample caloric value
Method be by《The heat output determining method of coal》(GB/T213-2008) requirement in is carried out, in the conventional method determination sample
Fixed carbon method be by《Proximate analysis of coal》(GB/T212-2008) requirement in is carried out, and the conventional method is surveyed
The method of the content of ashes of random sample product be by《Proximate analysis of coal》(GB/T212-2008) carry out, the conventional method is surveyed
The method of the volatile matter content of random sample product be by《Proximate analysis of coal》(GB/T212-2008) carry out, the conventional method
The method of flammable body in determination sample is flammable body reference《Proximate analysis of coal》(GB/T212-2008) requirement in
Carry out, the method for the total sulphur content of the conventional method determination sample be by《High temperature process furnances combustion method analyzes coal and coke point
Analyse the standard specimen method of sulfur content in sample》(ASTMD-4239-2010e1) carry out.
Scan with NIRS analyzers that to collect the spectroscopic data of the sample be by sample (being not required to claim sample), successively directly described in S2
The injector of the full NIRS instrument of tipping, is scanned using digital raster system, is recorded automatically by NIRS instrument and storage sample light
Spectrum.
The present embodiment uses the SY-3650-2 type near-infrared analysis that FOSS ANALYTICAL A/S companies of Denmark produce
Instrument, monochromator：Single beam holography digital raster, 1100~2500nm of wave-length coverage；Light source：Tengsten lamp；Detector：PBS, automatically
Mobile conveying multipoint positioning detection, test point is more than 32；Operation temperature：15~32 DEG C；Analysis time：It is per minute to use continuous light
Spectrum scans more than 32 subsamples and completes its spectrum analysis；System noise：Noise signal value is less than 2 × 10-5AU；As a result report
Accuse：The sample of result and display " having surmounted correcting range " is shown on a terminal screen, while reporting result by printer, also may be used
It is connected by RS-232C interfaces with external electrical computer.
Operating method：Carefully stirring coal sample, fills and takes appropriate sample in the sample cell of quartz system, must during filling
Make thickness of sample uniform, cover small cardboard, press lightly on, make sample tight distribution.After filling is finished, observation sample rooved face
Sample situation, if it find that having gap or sample to have the phenomenon of loosening, should recharge sample.The sample cell filled is placed in
On sample introduction track, click on " scanning ", by the input mode pumped, completion Scanning Detction and according to output.Entirely
During detection operation, without claiming sample, without adding any chemical reagent.
First, collection sample is scanned using digital raster system (Digital Dispersive System, DDS)
Spectrum.The present invention is scientifically classified, by coal sample respectively according to anthracite, bituminous coal, steam coal, meager lean coal, thermal coal
It is grouped, one group is then individually classified as to the sample do not classified specifically.Coal sample need not claim sample, and NIRS instrument is directly filled successively
Injector, then the sample for the injector that overfills is scalped, the DDS spectrum of the automatic record storage sample of near-infrared analyzer are obtained
Original spectrogram, as shown in accompanying drawing 1 to accompanying drawing 8.The display of the primary light spectrogram shown in accompanying drawing 1 to accompanying drawing 8, only accompanying drawing 4
The variation tendency of the near-infrared diffusing reflection DDS original spectrums of meager lean coal sample relatively or unanimously, other coals such as anthracite,
All there is the variation tendency of obvious difference in bituminous coal, steam coal, the original spectrogram of thermal coal.Because accompanying drawing 1 to Fig. 6 is nearly three
The spectrogram of individual month concentrated collection, considers the influence that analysis Sample Storage time and environment exist to its original spectrum, this hair
Bright collection coal sample in 2008 gathers spectrogram in time, obtains Fig. 7 to Fig. 8, it can be seen that Fig. 7 is basically identical with Fig. 1, the various coals of Fig. 8
The near-infrared diffusing reflection DDS original spectrums of sample cover foregoing anthracite, bituminous coal, steam coal, the original spectrum of thermal coal substantially
The variation tendency of figure.This illustrates that our storage of samples condition or Spectral acquisition times influences unobvious to original spectrum, can be with
Meet present invention research needs.More preferably to investigate coal original spectrum, we are gathered to coal standard sample using the same manner
Original spectrum, obtains Fig. 9 to Figure 10.And the original spectrogram of gained standard sample original spectrum and corresponding coal is combined progress
Observation, obtains Figure 11 to Figure 12.Spectrum change trend can see by Figure 11 and Figure 12 and foregoing corresponding coal is basically identical.
Then, the present invention carries out Pretreated spectra respectively to Figure 11 to Figure 12, obtains Figure 13 to Figure 19.Pretreated spectra mode
Respectively：NONE+0011, NONE+1441, D+1441, D+1441, NONE+0011, D+1441, D+0011 (wherein, NONE tables
Show and do not carry out Pretreated spectra, as original spectrogram, D represents trend converter technique, 1441 represent to make by interval of every 4 spectrum point
The Mathematical treatment of first derivative, 0011 represents not making any derivative processing.For example, D+1441 is to carry out trend to primary light spectrogram
After converter technique pretreatment, then make by interval of every 4 spectrum point first derivative progress Mathematical treatment).Can be with by Figure 13 to Figure 19
See that spectrogram variation tendency after pretreatment is more obvious, clear, but imitated obtained by the various Different treatments of same coal
The fruit visibly different peak type of generally existing and change.Totally apparently, Pretreated spectra fails to obtain than more consistent spectrogram.
The foregoing various coal original spectrums collected are pre-processed, gained situation is essentially identical, original with 509 anthracite samples
Exemplified by spectrum is through (NONE+1441) processing figure, result is see shown in accompanying drawing 20 to accompanying drawing 22, and other sample pretreatment figures exist
This is not repeated (figure is omited) one by one.
S2 is that the sample original spectrum that will be collected into is classified by its different variation tendency, identical with variation tendency according to peak type
Or close collection of illustrative plates is combined, and is sorted out, Y types original spectrum, W types original spectrum, p-type original spectrum and X are respectively obtained
Type original spectrum.The foregoing original spectrum collected is grouped by the present invention by its different variation tendency, then peak type and change are become
Gesture is identical or collection of illustrative plates of relatively is combined, and is sorted out, obtains spectrogram 23 to Figure 26.Figure 23 spectrogram is former labeled as Y types
Beginning spectrum, represents the coal such as most steam coal and part bituminous coal, partial power coal, has 374 samples.Figure 24 is labeled
For W type original spectrums, the coals such as most anthracite, part bituminous coal, partial power coal are represented, 1367 samples are had.Figure
25 are marked as p-type original spectrum, represent the coals such as most meager lean coal, part bituminous coal, partial power coal, have 436
Sample.Figure 26 is marked as X-type original spectrum, represents non-common coal, has 195 samples.
It is that spectrum analysis is carried out using WinISI softwares to the spectroscopic data progress Mathematical treatment of sample obtained by S2 described in S3
With set up detection model, the spectroscopic data of sample obtained by S2 is imported into NIR instrument, detection model is determined, testing result is printed.Spectrum
The sides such as trend converter technique, standard normal variable transformation approach, Multivariate Discrete correction, the correction of anti-phase Multivariate Discrete are respectively adopted in pretreatment
The one or more of method, it is final to determine optimization process method with reference to coal sample specificity analysis；Regression correction method is using progressively
Regression analysis (SMLR), PCA (PCA) and minimal error analytical method (PLS) are numerous to eliminate by Data Dimensionality Reduction
Overlapped message part and quantization to spectrum is finally accomplished in information co-exist.
Water content in the sample of one group of unknown component content to be measured is detected using detection model, then by obtained by NIR methods
Detected value is compared and evaluated with Typical physical chemical method detected value.The comparative result of two methods prediction standard deviation
(SEP, Standard Error of Prediction) and the corresponding coefficient of determination (RSQp) or coefficient R p are weighed.
The method for building up of described detection model comprises the following steps：
S31.GH values are analyzed：GH values are mahalanobis distance, be spectroscopic data regression correction score graphics in, each sample
The distance of distance center sample spot.GH values are generally set to 3.0 near infrared spectrum data analysis, are meant that standard makes a variation
3 times of unit, that is, be exactly be similar to standard deviation (SD) 2.84 times, it means that can be big by the GH values for the sample for having about 10%
In 3.0.If the GH values of which sample are more than 3.0, the sample needs to reject, and separately performs an analysis.The present invention uses PCA
(PCR) clustering is carried out respectively to Y types original spectrum, W types original spectrum, p-type original spectrum and X-type original spectrum；As a result
As shown in accompanying drawing 27 to accompanying drawing 30, analyzed from accompanying drawing 27 to 30, the GH value overwhelming majority of the original spectrogram of four types is less than
The sample that 3.0, Y types are more than 3.0 has 8, and the sample that W types are more than 3.0 has 10, and the sample that p-type is more than 3.0 has 13, and X is more than
3.0 sample has 9, and the GH values are more than after the rejecting of 3.0 sample by the present invention, and 3.0 sample sets point are less than with GH values
Calibration (detection) model of respective type spectrogram, wherein 366, Y types, 1357, W types, p-type 423, X-type 186 are not set up.
S32. the SEC values and RSQ values of (detection) model are calibrated described in S31 by calculating；
Spectral manipulation is carried out to above-mentioned four classes original spectrum using spectral manipulation in WinISI softwares and regression correction method
And data analysis.Pretreated spectra be respectively adopted trend converter technique, standard normal variable transformation approach, Multivariate Discrete correction, it is anti-phase
The one or more of the methods such as Multivariate Discrete correction, it is final to determine optimization process method with reference to coal sample specificity analysis；Mathematics
Processing is used makees first derivative (1441) or second dervative (2441) method, (0011) table with the interval (Gap) of every 4 spectrum point
Show and do not do any derivative processing.Regression correction method uses Stepwise Regression Method (Stepwise Mutiple Linear
Regression, SMLR), PCA (Principal Component Analysis, PCR), minimum deflection analysis
Method (Partial Least Squares Regression, PLS) and inclined minimal error analytical method (Modified Partial
Least Squares Regression, MPLS) calculate the SEC values and RSQ values for calibrating (detection) model.
SEC is calibration standard deviation (Standard Error of Calibration, SEC), refers to the calibration by foundation
Model calibration sample collection is predicted obtained by near-infrared analysis value and conventional chemical methods assay value standard deviation, be back
Return the mark of reading and actual read number degree of agreement.SEC is lower, illustrates that near-infrared analysis result is more kissed with traditional analysis result
Close, confidence level is higher.RSQ (R squared) is the calibration coefficient of determination, is coefficient correlation (Rc) square, refers to calibration model pair
The percentage that the variation of calibration sample collection can be depicted, represents that near-infrared analysis value and conventional method assay value linear relationship are close
Degree.One good detection model requirement has low SEC and high RSQ (Rc).It is theoretical according to the existing common knowledge in this area
On, the model for possessing minimum SEC values and highest RSQ values should be just optimal detection model.But the present invention is by a large amount of long
The experimental summary of phase is found, and the model of not least SEC values and highest RSQ values is exactly optimal detection model, but finally can quilt
Be set to optimum detection model necessarily has relatively low SEC values and higher RSQ values.The whole of foundation is detected for this present invention
Model carries out evaluation test one by one.By taking the original spectrogram of Y types as an example, other can refer to Y types and carry out experimental summary, not repeat one by one.
The interior water spectral manipulation and regression correction result of coal sample are shown in Table 1 (the original spectrogram of Y types) respectively：
The original spectrogram spectral manipulation of the Y types of table 1 and regression correction effect
The validation-cross result of the Y type detection models of table 2
S33. evaluation experimental is carried out to detection model and determines optimum detection model.Though it can be seen from Tables 1 and 2 which
The coal spectrum of type, the detection model of each coal index, the characteristic value of its validation-cross result -- SECV values, (1-
VR) the SEC values of value and corresponding model, RSQ values are all different, and SECV values are all slightly larger than SEC values, and (1-VR) value is all slightly less than
RSQ values.SECV values, (1-VR) value can more reflect that detection model is used to predict the accurate of unknown sample in the future than SEC values, RSQ values
Degree, because the reflection of SEC values, RSQ values is that detection model is predicted resulting near-infrared analysis to calibration sample collection
Standard deviation, near-infrared analysis value and the close journey of conventional method assay value linear relationship of value and conventional chemical methods assay value
Degree；And the reflection of SECV values, (1-VR) value is that, when validation-cross is calculated, detection model is not to participating in the sample that calibration is modeled
The standard deviation of near-infrared analysis value and conventional chemical methods assay value obtained by being predicted, the sample for not participating in calibration modeling
Product near-infrared analysis value and the close degree of conventional method assay value linear relationship.As can be seen here, a good detection model is not
But it is required that there is low SEC and high RSQ (Rc), more require there is low SECV values and high (1-VR) or Rv values.
No matter which type of coal spectrum, the detection model of each coal index, one possess minimum SECV values and
The detection model of highest (1-VR) or Rv values, necessarily with relatively low SEC values and higher RSQ values.The present invention is based on more kinds of
The result summarized in sample detection research in addition to coal sample is consistent with result of study of the present invention, four kinds of spectral classes of the invention
There is each coal index of type the detection model of minimum SECV values and highest (1-VR) value to be determined as optimum detection model, and will
Main information analysis and summary are in table 3.
The main characteristic parameters and its validation-cross result of the optimum detection model of table 3
From table 3, multiple spectrum processing is carried out to the near-infrared diffusing reflection original spectrum of coal using WinISI softwares
And regression correction, as a result with using standard normal variable conversion (SNV), trend conversion (D), without scattering (NONE) processing and once
Smoothing (0011), made with the interval (Gap) of 4 spectrum points first derivative (1441), second dervative (2441) processing and
The combined effect of MPLS, PLS regression correction is optimal.The principal character value and corresponding homing method of gained optimum detection model,
Spectral manipulation mode is referred to listed by table 3.The optimum N IR detection models of each coal index have 692 parameters, wherein including one
Within constant term, the present embodiment exemplified by water, the parameter and equation curve of detection model refer to table 4 to table 7, equation curve (detection
Model) as shown in Figure 31 to Figure 34, the parameter and equation curve figure of other detection models are omited.
The Y type original spectrum detection model parameters (interior water %) of table 4
The W type original spectrum detection model parameters (interior water %) of table 5
The p-type original spectrum detection model parameter (interior water %) of table 6
The X-type original spectrum detection model parameter (interior water %) of table 7
The applicating evaluating of embodiment 2 is tested
The detection model that the present embodiment is established using embodiment is detected in the coal sample of one group of unknown component content to be measured
Interior water content, then the detected value obtained by NIRS methods is compared and evaluated with Typical physical chemical method detected value.Two methods
Comparative result prediction standard deviation (SEP, Standard Error of Prediction) and the corresponding coefficient of determination
Or coefficient R p is weighed (RSQp).
Some coal samples are selected at random, is not required to claim sample, the injector of NIRS instrument is directly filled successively, start scanning key,
The automatic record storage sample spectra of NIRS instrument.After judgement sample ownership spectrogram type, corresponding detection model is clicked on, it is possible to
Testing result is printed, the content and hair of interior water, ash content, volatile matter, full sulphur, fixed carbon and the flammable body of coal sample is rapidly completed
The detection work of 7 indexs of heat.The experiment that sample number, the conventional method that this application experiment Y, W, P, X tetra- type is used are obtained
The scan values (average and standard deviation) that value (average and standard deviation), Near-Infrared Absorption Method are obtained, SEP and corresponding RSQp, Rp value
It is shown in Table 8 respectively.
The various coals of table 8 analyze testing result using the inventive method
The content and hair of water, ash content, volatile matter, full sulphur, fixed carbon and flammable body in table 8, coal of the present invention
The indexs such as the prediction standard deviation, the coefficient of determination and coefficient correlation of 7 index detection methods of heat are calibrated and tested with corresponding
Demonstrate,prove result close.Specific conventional method Physical Chemistry Experiment value, NIR methods scan values and both differences, current standard methods are again
Existing property limit difference is shown in Table 9 to table 12, only lists the result of 10 samples per project per type, within water, caloric value, fixed carbon be
Example, other abundant experimental results can not be repeated one by one herein.
The Y type detection models testing result of table 9-interior water (%)
The W type detection model Preliminary Applications result of table 10-interior water (%)
The p-type detection model Preliminary Applications result of table 11 -- interior water (%)
The X-type detection model Preliminary Applications result of table 12-interior water (%)
The Y type detection model Preliminary Applications result of table 13-caloric value (MJ/Kg)
The W type detection model Preliminary Applications result of table 14-caloric value (MJ/Kg)
The p-type detection model Preliminary Applications result of table 15-caloric value (MJ/Kg)
The X-type detection model Preliminary Applications result of table 16-caloric value (MJ/Kg)
The Y type detection model Preliminary Applications result of table 17-fixed carbon (%)
The W type detection model Preliminary Applications result of table 18-fixed carbon (%)
The p-type detection model Preliminary Applications result of table 19-fixed carbon (%)
The X-type detection model Preliminary Applications result of table 20-fixed carbon (%)
The degree of accuracy symbol of index detection method in the coal set up from above-mentioned representational table 9 to table 20, the present invention
Close the requirement of current standard methods repeatability limit difference.Operation is very easy to be quick, can just complete within 50 seconds or so sample
Scanning and 7 Indexs measures of content and caloric value of interior water, ash content, volatile matter, full sulphur, fixed carbon and flammable body, including data
Output.During whole detection operation, without claiming sample, without adding any chemical reagent, with it is quick, convenient, without dirt
The characteristics of dye.
Claims (3)
1. it is a kind of at the same in quick detection coal multiple quality projects near-infrared method, it is characterised in that comprise the following steps：
S1. collect and prepare several coal samples, conventional method determines the interior water of each sample respectively, ash content, volatile matter, complete
Sulphur, 7 indexs of the content of fixed carbon and flammable body and caloric value；
S2. the spectrum for collecting the coal sample is scanned using digital raster system with digital raster near-infrared diffusing reflection instrument
Data and curve；
S3. the spectroscopic data of sample obtained by step S2 is handled, calculates the calibration equation for obtaining 7 indexs through returning, repair
Just with set up detection model after checking；
S4., coal sample to be measured is directly filled to the injector of digital raster near-infrared diffusing reflection instrument successively, starts scanning key, number
The automatic record storage sample spectra of word grating near-infrared diffusing reflection instrument, determines that sample belongs to spectrogram type, the corresponding detection of selection
Model, obtains the testing result of 7 indexs；
Wherein, the spectroscopic data for scanning the collection coal sample described in step S2 with NIRS analyzers is to distinguish coal sample
It is grouped according to anthracite, bituminous coal, steam coal, meager lean coal, thermal coal, one is then individually classified as to the sample do not classified specifically
Group, original spectrum is gathered to coal standard sample using the same manner；By the sample original spectrum being collected into according to peak type and change
The identical or close collection of illustrative plates of change trend is combined, and is sorted out；
It is that spectrum analysis is carried out using WinISI softwares and built to the spectroscopic data progress processing of sample obtained by S2 described in step S3
Vertical detection model, imports NIRS instrument by the spectroscopic data of sample obtained by S2, sets up detection model；
The method for building up of described detection model comprises the following steps：
S31.GH values are analyzed, and the sample that the GH values are more than 3.0 are rejected, the sample sets for being less than 3.0 with GH values set up phase respectively
Answer the detection model of type spectrogram；
S32. the SEC values and RSQ values of detection model described in calculation procedure S31 are passed through；
S33. evaluation experimental is carried out to detection model and determines optimum detection model；
It is to use validation-cross error and the validation-cross coefficient of determination or coefficient correlation that optimum detection model is determined described in step S33
To weigh detection model.
2. according to claim 1 simultaneously in quick detection coal multiple quality projects near-infrared method, it is characterised in that
It is to use to evaluate good detection with low validation-cross error amount and the high validation-cross coefficient of determination or correlation coefficient value
Model interacts checking test with all detection models, selects minimum validation-cross error amount and highest validation-cross is determined
The detection model of coefficient or correlation coefficient value, is defined as optimum detection model.
3. according to claim 1 simultaneously in quick detection coal multiple quality projects near-infrared method, it is characterised in that
Step S2 also includes the sample original spectrum being collected into being combined according to the peak type collection of illustrative plates identical or close with variation tendency,
Sorted out, respectively obtain Y types original spectrum, W types original spectrum, p-type original spectrum and X-type original spectrum.
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