CN104515749B - The quick determination method of water in coal sample - Google Patents

The quick determination method of water in coal sample Download PDF

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CN104515749B
CN104515749B CN201410579762.1A CN201410579762A CN104515749B CN 104515749 B CN104515749 B CN 104515749B CN 201410579762 A CN201410579762 A CN 201410579762A CN 104515749 B CN104515749 B CN 104515749B
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sample
coal
detection model
spectrum
values
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CN104515749A (en
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苏彩珠
刘二龙
李国伟
郑建国
郑淑云
邱敏敏
蔡英俊
姚柏辉
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HUANGPU ENTRY-EXIT INSPECTION AND QUARANINE
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Abstract

The invention discloses a kind of quick determination method of interior water in coal sample.It the described method comprises the following steps:S1. several coal samples are collected and prepare, conventional method determines the interior water content of each sample respectively;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, the calibration equation for obtaining interior water is calculated through returning, water calibration equation in amendment and checking sets up detection model;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 NIRS instrument determines that sample belongs to spectrogram type, selects corresponding detection model, obtains testing result.The degree of accuracy of water detection method 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, can just complete within 50 seconds or so the Scanning Detction of a sample, 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

The quick determination method of water in coal sample
Technical field
The present invention relates to coal analysis detection technique field, more particularly, in a kind of coal sample water it is quick Detection 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 Row standard method is mainly:Interior water has GB/T 212, ISO 11722, an ASTMD 3173, ash content have GB/T 212, ISO 1171, ASTMD 3174, volatile matter have GB/T 212,
ISO 562, ASTMD 3175, full sulphur have GB/T 214, ISO 351, ASTMD 4239, and caloric value has GB/T 213rd, the requirement in the Industry Analysis Method of ISO 1928, ASTMD 5865, fixed carbon and flammable body reference coal is carried out.
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 the quick detection for the interior water that coal is set up using NIR technology The technology report of method.
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 detection data and coal quality composition conventional method detection data Between reliable functional relation, and further amendment and there is provided water in a kind of coal sample is verified to gained functional relation New quick determination method.
The purpose of the present invention is achieved by the following technical programs:
A kind of new quick determination method of water in coal sample is provided, comprised the following steps:
S1. several coal samples are collected and prepare, conventional method determines the interior water content of each sample respectively;
S2. the spectroscopic data and curve of the coal sample are collected with the scanning of NIRS analyzers;
S3. Mathematical treatment is carried out to the spectroscopic data of sample obtained by S2, the calibration equation of water in acquisition is calculated through returning, is repaiied Just with water calibration equation in checking, detection model is set up;
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 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 NIRS instrument, detection model is determined, testing result is printed.Light Trend converter technique, standard normal variable transformation approach, Multivariate Discrete correction, the correction of anti-phase Multivariate Discrete etc. is respectively adopted in spectrum pretreatment The one or more of method, it is final to determine optimization process method;Regression correction method is using Stepwise Regression Method (SMLR), master Componential analysis (PCA) and minimal error analytical method (PLS), it is overlapped in numerous information co-exists to eliminate by Data Dimensionality Reduction Message part and finally accomplish 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 NIRS 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 (1minus 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 only 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 the assay method of interior water content is successfully established, from And prove that near-infrared spectrum technique can apply to analyze inorganic substances, overcome prior art prejudice to a certain extent.
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, 4 detection models of water content in coal are obtained, and foundation can be applied to day New detection method in normal practice examining work.Interior water content in present invention detection coal sample needs a few minutes, and without claiming Sample, without using the test condition such as chemical reagent or high temperature, high pressure, high current, chemistry, biological or electromagnetic pollution will not be produced, Operating personnel and environment will not be had undesirable effect, continuous detection can be achieved, to mass detection task, its superiority is more It is prominent.
It is of the invention compared with existing Oven Method:The original spectrogram calibration standard deviation of Y types is 0.14%, and calibration coefficient correlation is 0.9969;Validation-cross standard deviation 0.15%, validation-cross coefficient correlation 0.9965;Standard deviation in 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;Standard deviation in is 0.23%, and coefficient correlation 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%, is handed over Coefficient correlation 0.9746 is mutually verified, the standard deviation in is 0.83%, and coefficient correlation is 0.944, the original spectrogram calibration of X-type Standard deviation is 0.12%, and calibration coefficient correlation is 0.9981;Validation-cross standard deviation 0.31%, validation-cross coefficient correlation 0.9874, the standard deviation in is 0.13%, and coefficient correlation is 0.997.
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 interior water content.During spectra collection in addition to electric energy is consumed, no Any reagent and standard substance need to be consumed, can so save a large amount of instrument and equipments the expense such as purchases, operates, repairing, and saves 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 new quick determination method of water in coal sample, comprises the following steps:
S1. several coal samples are collected and prepare, conventional method determines the interior water content of each sample respectively;
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, through return calculate produce in water calibration equation, amendment and Water calibration equation, sets up detection model 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.After judgement sample ownership spectrogram type, corresponding detection model is clicked on, detection knot is obtained Really.
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.
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 (interior water)
The validation-cross result (interior water) 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 knot summarized in sample detection research in addition to coal sample is consistent with result of study of the present invention, four kinds of spectrum types of the invention Each coal index there is the detection model of minimum SECV values and highest (1-VR) value to be determined as optimum detection model, and will be main Information summary is wanted to analyze 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 Constant term, refers to table 4 to table 7, equation curve (detection model) is as shown in Figure 31 to Figure 34, the parameter of other detection models and side Journey curve map is 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 detection work of the interior water index of quality of coal sample is rapidly completed.This application tests the species of Y, W, P, X tetra- Scan values that sample number that type is used, conventional method obtained experiment value (average and standard deviation), Near-Infrared Absorption Method are obtained (average and Standard deviation), SEP and corresponding RSQp, Rp value are shown in Table 8 respectively.
The various coals of table 8 present invention analysis testing result
Prediction standard deviation, the coefficient of determination and the phase relation of water content detection method in table 8, coal of the present invention The indexs such as number are close with corresponding calibration and the result.Specific conventional method Physical Chemistry Experiment value, NIR methods scan values and two Difference, the repeatability of the current standard methods limit difference of person is shown in Table 9 to table 12, only lists the knot of 10 samples per project per type Really, 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 degree of accuracy of water detection method meets existing mark in the coal set up from above-mentioned table 9 to table 12, the present invention The requirement of quasi- method repeatability limit difference.Operation is very easy to be quick, can just complete the Scanning Detction of a sample within 50 seconds or so, Output including data.During whole detection operation, without claiming sample, without adding any chemical reagent, with quickly, just Prompt, free of contamination feature.

Claims (3)

1. the quick determination method of water in a kind of coal sample, it is characterised in that comprise the following steps:
S1. several coal samples are collected and prepare, conventional method determines the interior water content of each sample respectively;
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 S2 is handled, the calibration equation of water in obtaining, amendment and checking is calculated through recurrence Interior water calibration equation, sets up detection model;
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 testing result;
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;
Determine that optimum detection model is weighed using validation-cross error and the validation-cross coefficient of determination or coefficient correlation described in S33 Measure detection model.
2. according to claim 1 in coal sample in water quick determination method, it is characterised in that be use have it is low Validation-cross error amount and the high validation-cross coefficient of determination or correlation coefficient value evaluate good detection model and all detections Model interacts checking test, selects minimum validation-cross error amount and the highest validation-cross coefficient of determination or coefficient correlation The detection model of value, is defined as optimum detection model.
3. according to claim 1 in coal sample in water quick determination method, it is characterised in that step S2 also include will The sample original spectrum being collected into is combined according to the peak type collection of illustrative plates identical or close with variation tendency, is 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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