CN104390936A - Novel method for rapidly detecting volatile in coal samples - Google Patents
Novel method for rapidly detecting volatile in coal samples Download PDFInfo
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Abstract
The invention discloses a novel method for rapidly detecting volatile in coal samples. The novel method comprises the following steps: S1, collecting and preparing multiple coal samples, and adopting a conventional method to detect the volatile content of each coal sample; S2, adopting an NIRS analysis meter to scan and collect spectroscopic data and curves of the coal samples; S3, processing the spectroscopic data of the coal samples obtained in the S2, obtaining the calibration equation of the volatile content through regression calculation, correcting and verifying the volatile content calibration equation, and establishing detection models; S4, sequentially and directly filling a sample injector of an NIR instrument with the to-be-detect coal samples, starting the scanning key to automatically record and store spectrums of the coal samples by the NIR instrument, determining the affiliation spectrogram type of the coal samples, and selecting a corresponding detection model to obtain the detection result. According to the invention, the accuracy of the method for detecting the volatile content in the coal samples meets the requirements of the reproducibility tolerance of the current standard method, the operation is simple and fast, and the scan and detection of a sample can be completed within about 50 seconds including data output. During the entire operation process, the samples are not required to be weighed, no chemical reagent is added, and the characteristics of high speediness and convenience as well as zero pollution are realized.
Description
Technical field
The present invention relates to coal analysis detection technique field, more specifically, relate to the novel method for quick of volatile matter in a kind of coal sample.
Background technology
Coal resources are the first energy of China, are the basic energy resource materials needed for industrial development.Coal resources in China is very abundant, accounts for about 70% of China's total energy.
According to the coal examination criteria of the world, coal needs to detect the quality projects such as fixed carbon usually.Need by China's national regulation and trade, coal need detect the index such as Nei Shui, full sulphur, volatile matter, ash content, thermal value, fixed carbon, flammable body usually, current standard methods is mainly: interior water has GB/T212, ISO11722, ASTMD3173, ash content has GB/T212, ISO1171, ASTMD3174, volatile matter have GB/T212,
ISO562, ASTMD3175, full sulphur has GB/T214, ISO351, ASTMD4239, and thermal value has GB/T213, ISO1928, ASTMD5865, and fixed carbon and flammable body carry out with reference to the requirement in the Industry Analysis Method of coal.
The chemical method in the classics that above-mentioned standard method generally adopts or modern times and physical-chemical process: volatile matter, volatile matter, volatile matter, fixed carbon, flammable body are all classical gravimetric method, relate to the equipment such as balance, baking oven, high temperature furnace, carbonization, ashing, constant weight, weighing, calculating are the steps often needing to carry out, quite loaded down with trivial details time-consuming; Even if use more advanced instrument at present, a technician completes these projects and also obtains 5 ~ 6 days, and the work such as operation, maintenance, demarcation, verification of modern physical chemistry instrument is also very heavy simultaneously.The traditional detection method of coal is numerous and diverse owing to working, and cost cost compare is high, and spended time is long.The classification of coal is sold, the quick demand etc. of the export trade and power plant, and traditional coal round of visits is oversize, is unfavorable for the sale of coal, needs the proving time shortening coal for this reason, needs to find the new method of inspection.
NIRS is the english abbreviation of near infrared spectrum.NIRS technology is one of high-new analytical technology with the fastest developing speed nearly ten years.NIRS analytical technology application of spectral section wavelength coverage is approximately 3 ~ 0.70mm, belong to dry infrared range of spectrum, the same with visible ray, be all an electromagnetic ingredient, the general characteristic shown when having electromagnetic wave and object effect, as transmission, diffuse reflection, absorption etc.In addition, frequency multiplication and the sum of fundamental frequencies uptake zone of its most outstanding feature to be this SPECTRAL REGION be hydric group (OH, SH, CH, NH).The near infrared spectrum of material is the frequency multiplication of wherein each group vibration and the comprehensive absorption performance of combination frequency.
NIRS develops rapidly nearly ten years, China is mainly used in the attributional analysis of agricultural product from the eighties in last century, now be applied to every field, expand to the field such as petrochemical complex and basic organic chemical industry, macromolecule chemical industry, pharmacy and clinical medicine, biochemical industry, environmental science, textile industry and food industry from traditional agricultural byproducts analysis.But the research report of current NIRS technology in coal seldom.
Data shows, the existence that external report utilizes NIRS technology to detect coal is much difficult, domestic have employing Fourier transform near infrared spectrum method to set up coal volatile matter, determination of moisture model, but do not propose the concrete technical scheme adopting NIRS technology quantitative test Coal ' moisture, volatile matter.The applicant is through long-term large quantifier elimination, it is feasible for summing up the correlation merit project method for quick utilizing NIR technology to set up coal, but the technical matters that following emphasis will solve effectively is solved always: (1) finds the suitable mathematics transition form of coal NIRS spectroscopic data; (2) NIRS finding suitable mathematical conversion detects reliable funtcional relationship between data and the detection data of coal quality composition conventional method; (3) gained funtcional relationship revised further and verify.Have no the technology report utilizing NIR technology to set up the method for quick of the volatile matter of coal.
Summary of the invention
The technical problem to be solved in the present invention is the detection for coal volatile matter, the suitable mathematics transition form of concrete NIRS spectroscopic data is provided, sums up reliable funtcional relationship between the NIRS detection data of suitable mathematical conversion and the detection data of coal quality composition conventional method, and gained funtcional relationship is revised further and verifies, the novel method for quick of volatile matter in a kind of coal sample is provided.
Object of the present invention is achieved by the following technical programs:
The novel method for quick of volatile matter in a kind of coal sample is provided, comprises the following steps:
S1. collect and prepare several coal samples, conventional method measures the volatile content of each sample respectively;
S2. spectroscopic data and the curve of described coal sample is collected with the scanning of NIRS analyser;
S3. the spectroscopic data of S2 gained sample is processed, through returning the calibration equation calculating and obtain volatile matter, revising and checking volatile matter calibration equation, setting up detection model;
S4. coal sample to be measured is directly filled successively the injector (not needing to sample) of NIR instrument, start scanning key, NIR instrument records storage sample spectra automatically.Determine sample ownership spectrogram type, select corresponding detection model, obtain testing result.
Scanning with NIRS analyser the spectroscopic data collecting described sample described in S2 is by sample (not needing to sample), directly fills the injector of NIR instrument successively, adopts digital raster system to scan, is automatically recorded and store sample spectra by NIRS instrument.Classified by its different variation tendency by the sample original spectrum collected, the collection of illustrative plates identical or close with variation tendency according to peak type is combined, and sorts out, and obtains Y type original spectrum, W type original spectrum, P type original spectrum and X-type original spectrum respectively.
Carrying out mathematics manipulation to the spectroscopic data of S2 gained sample described in S3 is adopt WinISI software carry out spectral analysis and set up detection model, the spectroscopic data of S2 gained sample is imported NIR instrument, determines detection model, print testing result.Pretreated spectra adopts one or more of the methods such as the correction of trend converter technique, standard normal variable transformation approach, Multivariate Discrete, anti-phase Multivariate Discrete correction respectively, in conjunction with coal sample specificity analysis, finally determines optimization process method; Regression correction method adopts Stepwise Regression Method (SMLR), principal component analysis (PCA) (PCA) and minimal error analytical method (PLS), by Data Dimensionality Reduction, to eliminate message part overlapped in numerous information co-exist and finally to accomplish the quantification to spectrum.
Utilize detection model to detect volatile content in the sample of one group of unknown component content to be measured, then the detected value of NIR method gained and Typical physical chemical method detected value are compared and evaluate.The comparative result of two kinds of methods is with predicting that 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 value is analyzed, and described GH value is greater than the sample rejecting of 3.0, sets up calibration (detection) model of respective type spectrogram by the sample sets that GH value is less than 3.0 respectively;
S32. by calculating SEC value and the RSQ value of calibration (detection) model described in S31;
S33. evaluation experimental determination optimum detection model is carried out to detection model.The present invention adopts validation-cross error (Standard Error of cross validation, SECV) and the validation-cross coefficient of determination (1minus thevariance ratio, 1-VR) or coefficient R v to weigh detection model.Can the prediction accuracy of Efficient Evaluation detection model by this two indices.Adopt and there is low SECV value and high (1-VR) or the Rv value good detection model of evaluation and all detection models carry out validation-cross test, select the detection model of minimum SECV value and the highest (1-VR) or Rv value, be defined as optimum detection model.
Beneficial effect of the present invention is 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 method, relate to the equipment such as balance, baking oven, high temperature furnace, carbonization, ashing, constant weight, weighing, calculating are the steps often needing to carry out, quite loaded down with trivial details time-consuming; Thermal value, full sulphur, state-of-the-art is at present adopt High Temperature High Pressure combustion method, but the operation of modern physical chemistry instrument, maintenance, demarcation are also very heavy.
For a long time, near-infrared spectrum technique is only used for analyzing pure organism.Because the wave number of near infrared spectrum is at 4000cm
-1above (i.e. below 2500nm), therefore, vibration frequency is only had at 2000cm
-1above vibration, just may produce one-level frequency multiplication in near-infrared region, and can at 2000cm
-1what more than produce fundamental vibration mainly contains hydrogen functional group, as the stretching vibration of C-H, N-H, S-H and O-H.Almost the information of all hydric groups in organism, can be reflected near infrared spectrum.
Coal is a kind of flammable rock.Near-infrared spectrum technique is applied to this compounding substances system be made up of most of organic substance and part mineral matter and moisture of coal by the present invention first, and successfully set up the assay method of volatile content, thus prove that near-infrared spectrum technique can be applied to analysis dead matter, overcomes prior art prejudice to a certain extent.
The present invention establishes the near infrared detection method of coal volatile matter, fill up prior art blank, and solve a following focus technology difficult problem: sum up the mathematics transition form that coal NIRS spectroscopic data is suitable, the NIRS providing suitable mathematical conversion detects reliable funtcional relationship between data and the detection data of coal quality composition conventional method, provides practical, reliable and stable correction and verification method to gained funtcional relationship.
Based on the inventive method, obtain 4 detection models of volatile content in coal, and foundation can be applied to new detection method in daily practice examining work.The volatile content that the present invention detects in coal sample needs a few minutes, and without the need to sampling, without the need to using the test condition such as chemical reagent or high temperature, high pressure, big current, chemistry, biology or electromagnetic pollution can not be produced, harmful effect can not be caused to operating personnel and environment, continuous detecting can be realized, to mass detection task, its superiority is more outstanding.
The present invention is compared with existing high temperature oven process: it is 0.27% that the original spectrogram of Y type calibrates standard deviation, and calibration related coefficient is 0.9922; Validation-cross standard deviation 0.29%, validation-cross related coefficient 0.9911; The standard deviation of Preliminary Applications is 0.37%, and related coefficient is 0.986.W type original spectrogram calibration standard deviation is 0.22%, and calibration related coefficient is 0.9618; Validation-cross standard deviation 0.24%, validation-cross related coefficient 0.9521; The standard deviation of Preliminary Applications is 0.25%, and related coefficient is 0.928.P type original spectrogram calibration standard deviation is 0.93%, and calibration related coefficient is 0.9889; Validation-cross standard deviation 1.05%, validation-cross related coefficient 0.9858; The standard deviation of Preliminary Applications is 0.89%, and related coefficient is 0.975.X-type original spectrogram calibration standard deviation is 0.59%, and calibration related coefficient is 0.9991; Validation-cross standard deviation 0.65%, validation-cross related coefficient 0.9989; The standard deviation of Preliminary Applications is 1.61%, and related coefficient is 0.994.
The present invention only needs employing near-infrared spectrometers, just can replace that prior art is multiple, multiple stage analytical instrument, only need grind away equipment, not Water demand balance, usually people's operation is only needed, and within a few minutes, by gathering the spectrum of primary measured sample, just can complete the mensuration of volatile content simultaneously.In spectra collection process except consumption electric energy, do not need to consume any reagent and standard substance, the purchasing of a large amount of instrument and equipment can be saved like this, operate, the expense such as maintenance, save a large amount of time and manpower, greatly reduce analysis cost, significantly improve the efficiency of testing.
Accompanying drawing explanation
The near-infrared diffuse reflectance DDS original spectrum of Fig. 1 509 anthracite samples is always schemed.
The near-infrared diffuse reflectance DDS original spectrum of Fig. 2 134 bituminous coal samples is always schemed.
The near-infrared diffuse reflectance DDS original spectrum of Fig. 3 155 steam coal samples is always schemed.
The near-infrared diffuse reflectance DDS original spectrum of Fig. 4 60 meager lean coal samples is always schemed.
The near-infrared diffuse reflectance DDS original spectrum of Fig. 5 134 steam coal samples is always schemed.
The near-infrared diffuse reflectance DDS original spectrum of Fig. 6 179 samples clearly do not divided into groups always is schemed.
The near-infrared diffuse reflectance DDS original spectrum of Fig. 7 202 anthracite samples is always schemed (sample in 2008).
The near-infrared diffuse reflectance DDS original spectrum of Fig. 8 235 samples clearly do not divided into groups always is schemed (sample in 2008).
The original spectrogram of Fig. 9 standard specimen (be above 103f stone coal, lower is 101L bituminous coal).
The original spectrogram of Figure 10 certified reference coal.
Figure 11 stone coals 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 stone coals in 2008 and standard specimen stone coal original spectrum are through (NONE+0011) process figure.
Figure 14 stone coals in 2008 and standard specimen stone coal original spectrum are through (NONE+1441) process figure.
Figure 15 stone coals in 2008 and standard specimen stone coal original spectrum are through (D+1441) process figure.
Figure 16 stone coals in 2008 and standard specimen stone coal original spectrum are through (D+1441) process figure.
The original spectrum of Figure 17 2005-2008 bituminous coal and standard specimen bituminous coal is through (NONE+0011) process figure.
The original spectrum of Figure 18 2005-2008 bituminous coal and standard specimen bituminous coal is through (D+1441) process figure.
The original spectrum of Figure 19 2005-2008 bituminous coal and standard specimen bituminous coal is through (D+0011) process figure.
Figure 20 509 anthracite sample original spectrums are through (NONE+1441) process figure.
Figure 21 509 anthracite sample original spectrums are through (NONE+0011) process figure.
Figure 22 509 anthracite sample original spectrums are through (D+1441) process figure.
Figure 23 Y type (374) primary light spectrogram.
Figure 24 W type (1367) primary light spectrogram.
Figure 25 P type (436) original spectrogram.
Figure 26 X-type (52) original spectrum.
The GH Distribution value figure of the original spectrogram of Figure 27 Y type.
The GH Distribution value figure of the original spectrogram of Figure 28 W type.
The GH Distribution value figure of the original spectrogram of Figure 29 P type.
The GH Distribution value figure of the original spectrogram of Figure 30 X-type.
Figure 31 is through Y type original spectrum volatile matter detection model (MPLS+NONE+1441) of validation-cross.
Figure 32 is through W type original spectrum volatile matter detection model (MPLS+NONE+0011) of validation-cross.
Figure 33 is through P type original spectrum volatile matter detection model (PLS+SNVD+1441) of validation-cross.
Figure 34 is through X-type original spectrum volatile matter detection model (PLS+NONE+0011) of validation-cross.
Embodiment
The present invention is further illustrated below in conjunction with the drawings and specific embodiments.The equipment of embodiment of the present invention employing can refer to listed equipment and reagent in " the standard sample method that high temperature process furnances combustion method analyzes sulfur content in coal and coke analysis sample " (ASTMD-4239-2010e1), " proximate analysis of coal " (GB/T212-2008), " heat output determining method of coal " (GB/T213-2008).Other unless stated otherwise, the embodiment of the present invention adopt reagent and equipment be this area routine use reagent and equipment.
Embodiment 1
The present embodiment provides the novel method for quick of volatile matter in a kind of coal sample, comprises the following steps:
S1. collect and prepare several coal samples, conventional method measures the volatile content of each sample respectively;
S2. spectroscopic data and the curve of described coal sample is collected with the scanning of NIRS analyser;
S3. the spectroscopic data of S2 gained sample is processed, through returning the calibration equation calculating and produce volatile matter, revising and checking volatile matter calibration equation, setting up detection model;
S4. coal sample to be measured is directly filled successively the injector (not needing to sample) of NIR instrument, start scanning key, NIR instrument records storage sample spectra automatically.After judgement sample ownership spectrogram type, click corresponding detection model, obtain testing result.
Wherein, to collect described in S1 and the method for preparing coal sample is carried out with reference to the requirement in " sample for commercial coal takes method " (GB475-2008) and " preparation method of coal sample " (GB474-2008).The method of the volatile content of described conventional method working sample is undertaken by " proximate analysis of coal " (GB/T212-2008).
Scanning with NIRS analyser the spectroscopic data collecting described sample described in S2 is by sample (not needing to sample), directly fills the injector of NIR instrument successively, adopts digital raster system to scan, is automatically recorded and store sample spectra by NIRS instrument.
The SY-3650-2 type near-infrared analyzer that the present embodiment adopts FOSS ANALYTICAL A/S company of Denmark to produce, monochromator: the holographic digital raster of single beam, wavelength coverage 1100 ~ 2500nm; Light source: tungsten lamp; Detecting device: PBS, mobile conveying multipoint positioning detects automatically, and check point is greater than 32; Operating temperature: 15 ~ 32 DEG C; Analysis time: continuous spectrum per minute scans more than 32 subsamples and completes its spectral analysis; System noise: noise signal value is less than 2 × 10
-5aU; Report the test: show the sample that result and display " surmount correcting range " on a terminal screen, is reported the result by printer simultaneously, is also connected by RS-232C interface and external electrical computing machine.
Method of operating: carefully stir coal sample, dress gets appropriate sample in the sample cell of quartz, thickness of sample must be made even, cover little cardboard, press gently, make sample tight distribution in filling process.After filling, observe the sample situation on sample cell surface, if find that there is gap or sample has loosening phenomenon, again should load sample.The sample cell filled is placed on sample introduction track, click " scanning ", by the input mode pumped, complete Scanning Detction and according to output.In the process of whole detection operation, without the need to sampling, without the need to adding any chemical reagent.
First, digital raster system (Digital Dispersive System, DDS) is adopted to carry out scanning collection sample spectra.The present invention scientifically classifies, and is divided into groups respectively by coal sample according to stone coal, bituminous coal, steam coal, meager lean coal, steam coal, is then classified as separately one group to the sample of not concrete classification.Coal sample does not need to sample, and directly fills the injector of NIR instrument successively, then the sample of the injector that overfills is scalped, and near-infrared analyzer records the DDS spectrum storing sample automatically, obtains original spectrogram, sees shown in accompanying drawing 1 to accompanying drawing 8.From primary light spectrogram shown in accompanying drawing 1 to accompanying drawing 8, the variation tendency of the near-infrared diffuse reflectance DDS original spectrum of the meager lean coal sample that drawings attached 4 shows relatively or unanimously, the variation tendency of obvious difference all appears in the original spectrogram of other coals as stone coal, bituminous coal, steam coal, steam coal.Due to the spectrogram that accompanying drawing 1 to Fig. 6 is nearly three months concentrated collection, consider the impact analyzed Sample Storage time and environment and exist its original spectrum, the present invention collects coal sample in 2008 and gathers spectrogram in time, obtain Fig. 7 to Fig. 8, can see, Fig. 7 and Fig. 1 is basically identical, and the near-infrared diffuse reflectance DDS original spectrum of the various coal sample of Fig. 8 covers the variation tendency of original spectrogram of aforementioned stone coal, bituminous coal, steam coal, steam coal substantially.This illustrates that our storage of samples conditioned disjunction Spectral acquisition times is not obvious on original spectrum impact, can meet the present invention and study needs.For better investigating coal original spectrum, we adopt the same manner to gather original spectrum to coal standard model, obtain Fig. 9 to Figure 10.And the original spectrogram of gained standard model original spectrum and corresponding coal is combined observes, obtain Figure 11 to Figure 12.Can see that spectrum change trend is basically identical to aforementioned corresponding coal by Figure 11 and Figure 12.
Then, the present invention carries out Pretreated spectra respectively to Figure 11 to Figure 12, obtains Figure 13 to Figure 19.Pretreated spectra mode is respectively: NONE+0011, NONE+1441, D+1441, D+1441, NONE+0011, D+1441, D+0011 are (wherein, NONE represents and does not carry out Pretreated spectra, be original spectrogram, D represents trend converter technique, 1441 represent with every 4 spectrum points for the mathematics manipulation of first order derivative is made at interval, and 0011 represents and do not make any derivative processing.Such as, D+1441 is after carrying out the pre-service of trend converter technique to primary light spectrogram, then with every 4 spectrum points for carrying out mathematics manipulation as first order derivative in interval).Can see that spectrogram variation tendency after pretreatment is more obvious, clear by Figure 13 to Figure 19, but the various Different treatments income effects equal ubiquity visibly different peak type of same coal and change.Totally it seems, Pretreated spectra also fails to obtain more consistent spectrogram.Pre-service is carried out to the aforementioned various coal original spectrums collected, gained situation is substantially identical, for 509 anthracite sample original spectrums through (NONE+1441) process figure, result is asked for an interview shown in accompanying drawing 20 to accompanying drawing 22, and other sample pretreatments figure does not repeat (figure slightly) one by one at this.
The sample original spectrum collected is classified by its different variation tendency by S2, and the collection of illustrative plates identical or close with variation tendency according to peak type is combined, and sorts out, and obtains Y type original spectrum, W type original spectrum, P type original spectrum and X-type original spectrum respectively.The aforementioned original spectrum collected divides into groups by its different variation tendency by the present invention, then peak type is identical with variation tendency or relatively collection of illustrative plates is combined, and sorts out, obtains spectrogram 23 to Figure 26.The spectrogram of Figure 23 is labeled as Y type original spectrum, represents most steam coal and the coal such as part bituminous coal, partial power coal, has 374 samples.Figure 24 is marked as W type original spectrum, represents the coals such as most stone coal, part bituminous coal, partial power coal, has 1367 samples.Figure 25 is marked as P type original spectrum, represents the coals such as most meager lean coal, part bituminous coal, partial power coal, has 436 samples.Figure 26 is marked as X-type original spectrum, represents non-common coal, has 195 samples.
Carrying out mathematics manipulation to the spectroscopic data of S2 gained sample described in S3 is adopt WinISI software carry out spectral analysis and set up detection model, the spectroscopic data of S2 gained sample is imported NIR instrument, determines detection model, print testing result.Pretreated spectra adopts one or more of the methods such as the correction of trend converter technique, standard normal variable transformation approach, Multivariate Discrete, anti-phase Multivariate Discrete correction respectively, in conjunction with coal sample specificity analysis, finally determines optimization process method; Regression correction method adopts Stepwise Regression Method (SMLR), principal component analysis (PCA) (PCA) and minimal error analytical method (PLS), by Data Dimensionality Reduction, to eliminate message part overlapped in numerous information co-exist and finally to accomplish the quantification to spectrum.
Utilize detection model to detect volatile content in the sample of one group of unknown component content to be measured, then the detected value of NIR method gained and Typical physical chemical method detected value are compared and evaluate.The comparative result of two kinds of methods is with predicting that 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 value is analyzed: GH value and mahalanobis distance are in the score three-dimensional plot of spectroscopic data regression correction, the distance of each sample distance center sample spot.GH value is usually set to 3.0 near infrared spectrum data analysis, and implication is 3 times of standard variation unit, is namely exactly 2.84 times that are similar to standard deviation (SD), this means the GH value of the sample having about 10% to be greater than 3.0.If the GH value of which sample is greater than 3.0, this sample needs to reject, and separately performs an analysis.The present invention adopts principal component analysis (PCA) (PCR) to carry out cluster analysis respectively to Y type original spectrum, W type original spectrum, P type original spectrum and X-type original spectrum; The results are shown in 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 3.0, the sample that Y type is greater than 3.0 has 8, the sample that W type is greater than 3.0 has 10, the sample that P type is greater than 3.0 has 13, the sample that X is greater than 3.0 has 9, after described GH value is greater than the sample rejecting of 3.0 by the present invention, calibration (detection) model of respective type spectrogram is set up respectively, wherein 366, Y type, 1357, W type by the sample sets that GH value is less than 3.0,423, P type, X-type 186.
S32. by calculating SEC value and the RSQ value of calibration (detection) model described in S31;
Spectral manipulation and regression correction method in WinISI software is utilized to carry out spectral manipulation and data analysis to above-mentioned four class original spectrums.Pretreated spectra adopts one or more of the methods such as the correction of trend converter technique, standard normal variable transformation approach, Multivariate Discrete, anti-phase Multivariate Discrete correction respectively, in conjunction with coal sample specificity analysis, finally determines optimization process method; Mathematics manipulation adopts and makes first order derivative (1441) or second derivative (2441) method with the interval (Gap) of every 4 spectrum points, and any derivative processing is not done in (0011) expression.Regression correction method adopts Stepwise Regression Method (Stepwise Mutiple Linear Regression, SMLR), principal component analysis (PCA) (Principal Component Analysis, PCR), minimal error analytical method (Partial LeastSquares Regression, PLS) and inclined minimal error analytical method (Modified Partial Least SquaresRegression, MPLS) calculate SEC value and the RSQ value of described calibration (detection) model.
SEC is calibration standard deviation (Standard Error of Calibration, SEC), referring to that the calibration model by setting up predicts obtained near-infrared analysis value and the standard deviation of conventional chemical methods assay value to calibration sample collection, is the mark returning reading and actual read number degree of agreement.SEC is lower, illustrate near-infrared analysis result and traditional analysis result more identical, confidence level is higher.RSQ (R squared) is the calibration coefficient of determination, be related coefficient (Rc) square, refer to that calibration model make a variation the percent that can describe out to calibration sample collection, expression near-infrared analysis value and the close degree of conventional method assay value linear relationship.A good detection model requires low SEC and high RSQ (Rc).According to the existing common practise in this area, in theory, the model possessing minimum SEC value and the highest RSQ value should be just best detection model.But the present invention finds through experimental summary long-term in a large number, and the model of not least SEC value and the highest RSQ value is exactly the detection model of the best, but finally can be decided to be optimum detection model necessarily there is lower SEC value and higher RSQ value.The present invention carries out evaluation test one by one to the whole detection models set up for this reason.For the original spectrogram of Y type, other can refer to Y type and carry out experimental summary, do not repeat one by one.Volatile matter spectral manipulation and the regression correction result of coal sample are shown in Table 1 (the original spectrogram of Y type) respectively:
The table original spectrogram spectral manipulation of 1Y type and regression correction effect (volatile matter)
The validation-cross result (volatile matter) of table 2Y type detection model
S33. evaluation experimental determination optimum detection model is carried out to detection model.As can be seen from table 1 and table 2, no matter the coal spectrum of which kind of type, the detection model of each coal index, SEC value, the RSQ value of the eigenwert of its validation-cross result--SECV value, (1-VR) value and corresponding model are all different, SECV value is all slightly larger than SEC value, and (1-VR) value is all slightly less than RSQ value.SECV value, (1-VR) value more can reflect detection model in the future for predicting the accuracy of unknown sample than SEC value, RSQ value, this is because SEC value, RSQ value reflect to be detection model predict to calibration sample collection the degree that the standard deviation of obtained near-infrared analysis value and conventional chemical methods assay value, near-infrared analysis value and conventional method assay value linear relationship are close; And the reflection of SECV value, (1-VR) value is when validation-cross calculates, detection model predicts to the sample not participating in calibration modeling the degree that the standard deviation of obtained near-infrared analysis value and conventional chemical methods assay value, the sample near-infrared analysis value of not participating in calibration modeling and conventional method assay value linear relationship are close.As can be seen here, a good detection model not only requires low SEC and high RSQ (Rc), more requires low SECV value and high (1-VR) or Rv value.
No matter the coal spectrum of which kind of type, the detection model of each coal index, a detection model having minimum SECV value and the highest (1-VR) or a Rv value, necessarily has lower SEC value and higher RSQ value.The present invention is based on the knot of summing up in more kinds of sample detection research except coal sample consistent with result of study of the present invention, the detection model that each coal index of the present invention's four kinds of spectrum types has minimum SECV value and the highest (1-VR) value is judged to be optimum detection model, and by main information analysis and summary in table 3.
The main characteristic parameters of table 3 optimum detection model and validation-cross result thereof
From table 3, utilize the near-infrared diffuse reflectance original spectrum of WinISI software to coal to carry out multiple spectrum process and regression correction, result to adopt standard normal variable to change (SNV), trend conversion (D), without scattering (NONE) process and smoothing (0011), make first order derivative (1441) with the interval (Gap) of 4 spectrum points, second derivative (2441) processes and combined effect the best of MPLS, PLS regression correction.The principal character value of gained optimum detection model and corresponding homing method, spectral manipulation mode refer to listed by table 3.The optimum N IR detection model of each coal index has 692 parameters, wherein comprises a constant term, refers to table 4 to table 7, and equation curve (detection model) is as shown in Figure 31 to Figure 34, and the parameter of other detection model and equation curve figure are slightly.
Table 4Y type original spectrum detection model parameter (volatile matter %)
Table 5W type original spectrum detection model parameter (volatile matter %)
Table 6P type original spectrum detection model parameter (volatile matter %)
Table 7X type original spectrum detection model parameter (volatile matter %)
Embodiment 2 applicating evaluating is tested
The detection model that the present embodiment utilizes embodiment to establish detects volatile content in the coal sample of one group of unknown component content to be measured, then the detected value of NIR method gained and Typical physical chemical method detected value are compared and evaluated.The comparative result of two kinds of methods is with predicting that standard deviation (SEP, Standard Error of Prediction) and the corresponding coefficient of determination (RSQp) or coefficient R p are weighed.
Select some coal samples at random, do not need to sample, directly fill the injector of NIR instrument successively, start scanning key, NIR instrument records storage sample spectra automatically.After judgement sample ownership spectrogram type, click corresponding detection model, just can print testing result, complete the testing of the volatile matter index of quality of coal sample fast.The scan values (average and standard deviation) that the experiment value (average and standard deviation) that the sample number that this application test Y, W, P, X Four types adopts, conventional method obtain, Near-Infrared Absorption Method obtain, SEP and corresponding RSQp, Rp value are shown in Table 8 respectively.
The various coal the inventive method of table 8 analyzes testing result
From table 8, the prediction standard deviation of volatile content detection method in coal of the present invention, the index such as the coefficient of determination and related coefficient are all close with the result with corresponding calibration.The repeatability limit difference of concrete conventional method Physical Chemistry Experiment value, NIR method scan values and both differences, current standard methods is in table 9 to table 12, and the every project of every type only lists the result of 10 samples, and other abundant experimental results do not repeat one by one at this.
Table 9Y type detection model testing result-volatile matter (%)
Table 10W type detection model Preliminary Applications result-volatile matter (%)
Table 11P type detection model Preliminary Applications result-volatile matter (%)
Table 12X type detection model Preliminary Applications result-volatile matter (%)
From above-mentioned table 9 to table 12, in the coal that the present invention sets up, the accuracy of volatile matter detection method conforms to current standards the requirement of method repeatability limit difference.Operate very fast easy, within about 50 seconds, just can complete the Scanning Detction of a sample, comprise the output of data.In the process of whole detection operation, without the need to sampling, without the need to adding any chemical reagent, there is quick, convenient, free of contamination feature.
Claims (5)
1. the novel method for quick of volatile matter in coal sample, is characterized in that, comprise the following steps:
S1. collect and prepare several coal samples, conventional method measures the volatile content of each sample respectively;
S2. spectroscopic data and the curve of described coal sample is collected with the scanning of NIRS analyser;
S3. the spectroscopic data of S2 gained sample is processed, through returning the calibration equation calculating and obtain volatile matter, revising and checking volatile matter calibration equation, setting up detection model;
S4. coal sample to be measured is directly filled successively the injector of NIR instrument, start scanning key, NIR instrument records storage sample spectra automatically, determines sample ownership spectrogram type, selects corresponding detection model, obtain testing result.
2. the novel method for quick of volatile matter in coal sample according to claim 1, it is characterized in that, the method for building up of described detection model comprises the following steps:
S31. GH value is analyzed, and described GH value is greater than the sample rejecting of 3.0, sets up the detection model of respective type spectrogram by the sample sets that GH value is less than 3.0 respectively;
S32. by calculating SEC value and the RSQ value of detection model described in S31;
S33. evaluation experimental determination optimum detection model is carried out to detection model.
3. the novel method for quick of volatile matter in coal sample according to claim 2, is characterized in that, determine that optimum detection model adopts validation-cross error and the validation-cross coefficient of determination or related coefficient to weigh detection model described in S33.
4. the novel method for quick of volatile matter in coal sample according to claim 3, it is characterized in that, that employing has the good detection model of low validation-cross error amount and the high validation-cross coefficient of determination or correlation coefficient value evaluation and all detection models carry out validation-cross test, select the detection model of minimum validation-cross error amount and the highest validation-cross coefficient of determination or correlation coefficient value, be defined as optimum detection model.
5. the novel method for quick of volatile matter in coal sample according to claim 1, it is characterized in that, S2 also comprises and being combined according to the collection of illustrative plates that peak type is identical or close with variation tendency by the sample original spectrum collected, sort out, obtain Y type original spectrum, W type original spectrum, P type original spectrum and X-type original spectrum respectively.
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Inventor after: Su Caizhu Inventor after: Yu Fang Inventor after: Li Peishen Inventor after: Zheng Jianguo Inventor after: Li Guowei Inventor after: Ruan Xiongjie Inventor after: Qiu Minmin Inventor after: Zheng Shuyun Inventor after: Zhang Weimin Inventor after: Xie Wenxi Inventor after: Ma Lina Inventor before: Su Caizhu Inventor before: Zheng Jianguo Inventor before: Li Guowei Inventor before: Qiu Minmin Inventor before: Zheng Shuyun Inventor before: Cai Yingjun Inventor before: Yao Baihui |
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