CN204255854U - A kind of system simultaneously detecting 7 indexs in coal sample - Google Patents
A kind of system simultaneously detecting 7 indexs in coal sample Download PDFInfo
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- CN204255854U CN204255854U CN201420623863.XU CN201420623863U CN204255854U CN 204255854 U CN204255854 U CN 204255854U CN 201420623863 U CN201420623863 U CN 201420623863U CN 204255854 U CN204255854 U CN 204255854U
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Abstract
The utility model discloses a kind of system simultaneously detecting 7 indexs in coal sample.Described system comprises charging hopper, sample introduction tank, sample introduction track, near-infrared analyzer, computing machine, display screen and printer, described charging hopper be arranged at sample introduction tank upper end and can within the scope of sample introduction tank reciprocal uniform motion, sample introduction tank enters near-infrared analyzer along sample introduction track, near-infrared analyzer connects computing machine and terminal display screen respectively, and computing machine and terminal display screen all can be connected printer.Based on system described in the utility model, filled by coal sample to be measured after sample introduction tank enters near-infrared analyzer, start scanning key, NIR instrument records storage sample spectra automatically, determines sample ownership spectrogram type, selects corresponding detection model, obtain testing result.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.
Description
Technical field
The utility model relates to coal analysis detection technique field, more specifically, relates to a kind of system simultaneously detecting 7 indexs in 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 interior water usually.Need by China's national regulation and trade, coal need detect thermal value usually, full sulphur, interior water, volatile matter, ash content, fixed carbon, the indexs such as flammable body, the standard method of described 7 indexs of existing detection is mainly: interior water has GB/T212, ISO11722, ASTMD3173, ash content has GB/T212, ISO1171, ASTMD3174, volatile matter has GB/T212, ISO562, ASTMD3175, full sulphur has GB/T214, ISO351, ASTMD4239, thermal value has GB/T213, ISO1928, ASTMD5865, 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: 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; 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 and the apparatus system that adopt NIRS technology quantitative test Coal ' moisture, volatile matter.
Utility model content
The technical problems to be solved in the utility model is the detection for coal 7 key indexs, provides a kind of system simultaneously detecting 7 indexs in coal sample.
The described system simultaneously detecting 7 indexs in coal sample comprises charging hopper, sample introduction tank, sample introduction track, near-infrared analyzer, computing machine, display screen and printer, described charging hopper be arranged at sample introduction tank upper end and can within the scope of sample introduction tank reciprocal uniform motion, sample introduction tank enters near-infrared analyzer along sample introduction track, near-infrared analyzer connects computing machine and terminal display screen respectively, and computing machine and terminal display screen all can be connected printer.
By the motion of charging hopper described in Serve Motor Control, it can be made at uniform motion reciprocal in sample introduction tank range of size, ensures cloth equably.
Preferably, described charging hopper is provided with stirring apparatus, carefully stirs coal sample, be layed in equably in sample cell by sample, thickness of sample must be made in filling process even by uniform motion reciprocal within the scope of sample introduction tank after coal sample being loaded.
Further preferably, described charging quarrel is provided with scalable flat board, and during filling sample, in dull and stereotyped retraction charging hopper, after filling sample, flat board leans out contact specimen surface from charging hopper, presses gently, make sample tight distribution to sample.Described flat board can adopt cardboard.
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.
Preferably, described near-infrared analyzer is the SY-3650-DDS type near-infrared analyzer of FOSS ANALYTICAL A/S company of Denmark; 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 computing machine.
Preferably, described sample introduction tank adopts quartz material.
By test sample, do not need to sample, directly fill the injector of NIR instrument successively, then the sample of the injector that overfills is scalped, adopt digital raster system to scan, NIR instrument records storage sample spectra automatically.
Based on the utility model, to detect in coal sample 7 when realizing as follows and refer to calibration method, said method comprising the steps of:
S1. collect and prepare several coal samples, being divided into two parts, a interior water, ash content, volatile matter, the content of full sulphur, fixed carbon and flammable body and thermal value 7 indexs adopting conventional method to measure each sample respectively;
S2. another part of coal sample NIRS analyser scanning is collected spectroscopic data and the curve of described coal sample;
S3. the spectroscopic data of S2 gained sample is processed, through returning the calibration equation calculating acquisition 7 indexs, revising and setting up detection model after water in checking;
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 process 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, 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 liquid water 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 utility model adopts validation-cross error (Standard Error of cross validation, SECV) and the validation-cross coefficient of determination (1minusthe variance ratio, 1-VR) or coefficient R v 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.
The beneficial effects of the utility model 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 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 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 utility model first, and successfully set up the system that in coal sample, 7 key indexs detect simultaneously, realize detecting while 7 key indexs in coal sample, thus prove that near-infrared spectrum technique can be applied to analysis dead matter, overcomes prior art prejudice to a certain extent.
The utility model system architecture is simple, be applied to 7 indexs detected in coal sample and only need 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, can realize continuous detecting, to mass detection task, its superiority is more outstanding.
The utility model only needs employing near-infrared spectrometers to combine computing machine and the printer of filling materials device and routine, just can replace that prior art is multiple, multiple stage analytical instrument, 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 coal sample 7 indexs 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.
The utility model is reasonable in design, by the design of charging hopper device and near-infrared analyzer combination of sciences, realize charging with the automation mechanized operation analyzed, overcoming the sample that hand charging may cause has gap or sample to have loosening phenomenon, for batch detection coal sample provides technical foundation.
Accompanying drawing explanation
Fig. 1 the utility model system architecture schematic diagram.
The near-infrared diffuse reflectance DDS original spectrum of Figure 25 09 anthracite sample is always schemed.
The near-infrared diffuse reflectance DDS original spectrum of Figure 31 34 bituminous coal samples is always schemed.
The near-infrared diffuse reflectance DDS original spectrum of Figure 41 55 steam coal samples is always schemed.
The near-infrared diffuse reflectance DDS original spectrum of Figure 56 0 meager lean coal sample is always schemed.
The near-infrared diffuse reflectance DDS original spectrum of Figure 61 34 steam coal samples is always schemed.
The near-infrared diffuse reflectance DDS original spectrum of Figure 71 79 samples clearly do not divided into groups always is schemed.
The near-infrared diffuse reflectance DDS original spectrum of Figure 82 02 anthracite sample is always schemed (sample in 2008).
The near-infrared diffuse reflectance DDS original spectrum of Figure 92 35 samples clearly do not divided into groups always is schemed (sample in 2008).
The original spectrogram of Figure 10 standard specimen (be above 103f stone coal, lower is 101L bituminous coal).
The original spectrogram of Figure 11 certified reference coal.
Figure 122 008 year stone coal and the anthracitic original spectrogram of standard specimen.
The original spectrogram of Figure 132 005-2008 bituminous coal and standard specimen bituminous coal.
Figure 142 008 year stone coal and standard specimen stone coal original spectrum are through (NONE+0011) process figure.
Figure 152 008 year stone coal and standard specimen stone coal original spectrum are through (NONE+1441) process figure.
Figure 162 008 year stone coal and standard specimen stone coal original spectrum are through (D+1441) process figure.
Figure 172 008 year stone coal and standard specimen stone coal original spectrum are through (D+1441) process figure.
The original spectrum of Figure 182 005-2008 bituminous coal and standard specimen bituminous coal is through (NONE+0011) process figure.
The original spectrum of Figure 192 005-2008 bituminous coal and standard specimen bituminous coal is through (D+1441) process figure.
The original spectrum of Figure 20 2005-2008 bituminous coal and standard specimen bituminous coal is through (D+0011) process figure.
Figure 21 509 anthracite sample original spectrums are through (NONE+1441) process figure.
Figure 22 509 anthracite sample original spectrums are through (NONE+0011) process figure.
Figure 23 509 anthracite sample original spectrums are through (D+1441) process figure.
Figure 24 Y type (374) primary light spectrogram.
Figure 25 W type (1367) primary light spectrogram.
Figure 26 P type (436) original spectrogram.
Figure 27 X-type (52) original spectrum.
The GH Distribution value figure of the original spectrogram of Figure 28 Y type.
The GH Distribution value figure of the original spectrogram of Figure 29 W type.
The GH Distribution value figure of the original spectrogram of Figure 30 P type.
The GH Distribution value figure of the original spectrogram of Figure 31 X-type.
Figure 32 water detection model (MPLS+D+1441) in the Y type original spectrum of validation-cross.
Figure 33 water in the W type original spectrum inspection of validation-cross surveys model (PLS+D+0011).
Figure 34 water detection model (MPLS+D+0011) in the P type original spectrum of validation-cross.
Figure 35 water in the X-type original spectrum inspection of validation-cross surveys model (MPLS+NONE+2441).
Embodiment
The utility model is further illustrated below in conjunction with the drawings and specific embodiments.The equipment of the utility model embodiment 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 utility model embodiment adopt reagent and equipment be this area routine use reagent and equipment.
Embodiment 1
A kind of system simultaneously detecting 7 indexs in coal sample is provided, comprise charging hopper 2, sample introduction tank 1, sample introduction track 7, near-infrared analyzer 3, computing machine 5, display screen 4 and printer 6, described charging hopper 2 be arranged at sample introduction tank 1 upper end and can in sample introduction tank 1 range of size reciprocal uniform motion, sample introduction tank 1 enters near-infrared analyzer 3 along sample introduction track 7, near-infrared analyzer 3 connects computing machine 5 and display screen 4 respectively, and computing machine 5 all can be connected printer 6 with display screen 4.
By the motion of charging hopper 2 described in Serve Motor Control, its reciprocal uniform motion in the range of size in sample introduction tank 1 can be made, ensures cloth equably.
Preferably, described charging hopper 2 is provided with stirring apparatus (not indicating in figure), carefully coal sample is stirred after coal sample being loaded charging hopper, by charging hopper reciprocal uniform motion in sample introduction tank range of size, sample is layed in sample cell equably, thickness of sample in filling process, must be made even.
Further preferably, described charging hopper 2 mouthfuls is provided with scalable flat board (not indicating in figure), during filling sample, in dull and stereotyped retraction charging hopper 2, after filling sample, flat board leans out from charging hopper 2, contact specimen surface, presses gently sample, makes sample tight distribution.Described flat board can adopt cardboard.
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.
Preferably, described near-infrared analysis 3 adopts the SY-3650-DDS type near-infrared analyzer of FOSS ANALYTICAL A/S company of Denmark; 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 computing machine.
Preferably, described sample introduction tank 1 adopts quartz material.
By test sample, do not need to sample, directly fill the injector of NIR instrument successively, then the sample of the injector that overfills is scalped, adopt digital raster system to scan, NIR instrument records storage sample spectra automatically.
Embodiment 2
The present embodiment, based on the system described in embodiment 1, provides one to detect in coal sample 7 simultaneously and refers to calibration method, comprise the following steps:
S1. collect and prepare several coal samples, being divided into duplicate, a interior water, ash content, volatile matter, the content of full sulphur, fixed carbon and flammable body and thermal value 7 indexs adopting conventional method to measure each sample respectively;
S2. another part of coal sample NIRS analyser scanning is collected spectroscopic data and the curve of described coal sample;
S3. the spectroscopic data of S2 gained sample is processed, through returning the calibration equation calculating acquisition 7 indexs, revising and setting up detection model after water in checking;
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.
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 interior liquid water content of described conventional method working sample is undertaken by " proximate analysis of coal " (GB/T212-2008), the method of described conventional method working sample thermal value is undertaken by the requirement in " heat output determining method of coal " (GB/T213-2008), the method of the fixed carbon in described conventional method working sample is undertaken by the requirement in " proximate analysis of coal " (GB/T212-2008), the method of the ash content of described conventional method working sample is undertaken by " proximate analysis of coal " (GB/T212-2008), the method of the volatile content of described conventional method working sample is undertaken by " proximate analysis of coal " (GB/T212-2008), the method of the flammable body in described conventional method working sample is that flammable body carries out with reference to the requirement in " proximate analysis of coal " (GB/T212-2008), the method of the total sulphur content of described conventional method working sample is undertaken by " high temperature process furnances combustion method analyzes the standard sample method of sulfur content in coal and coke analysis sample " (ASTMD-4239-2010e1).
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: coal sample is loaded on charging hopper, carefully stirs coal sample, lays appropriate sample in the sample cell 1 of quartz, thickness of sample must be made even, press gently, make sample tight distribution with cardboard 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 utility model is scientifically classified, 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 2 to accompanying drawing 9.From primary light spectrogram shown in accompanying drawing 2 to accompanying drawing 9, the variation tendency of the near-infrared diffuse reflectance DDS original spectrum of the meager lean coal sample that drawings attached 5 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 2 to Fig. 7 is nearly three months concentrated collection, consider the impact analyzed Sample Storage time and environment and exist its original spectrum, the utility model is collected coal sample in 2008 and is gathered spectrogram in time, obtain Fig. 8 to Fig. 9, can see, Fig. 8 and Fig. 2 is basically identical, and the near-infrared diffuse reflectance DDS original spectrum of the various coal sample of Fig. 9 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 utility model research needs.For better investigating coal original spectrum, we adopt the same manner to gather original spectrum to coal standard model, obtain Figure 10 to Figure 11.And the original spectrogram of gained standard model original spectrum and corresponding coal is combined observes, obtain Figure 12 to Figure 13.Can see that spectrum change trend is basically identical to aforementioned corresponding coal by Figure 12 and Figure 13.
Then, the utility model carries out Pretreated spectra respectively to Figure 12 to Figure 13, obtains Figure 14 to Figure 20.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 14 to Figure 20, 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 21 to accompanying drawing 23, 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 utility model, then peak type is identical with variation tendency or relatively collection of illustrative plates is combined, and sorts out, obtains spectrogram 24 to Figure 27.The spectrogram of Figure 24 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 25 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 26 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 27 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 liquid water 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 utility model 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 28 to accompanying drawing 31, analyzed from accompanying drawing 28 to 31, 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 utility model, 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 utility model 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 utility model 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.The interior water spectral manipulation of coal sample and regression correction result 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
The validation-cross result 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 utility model is consistent with the utility model result of study based on the result summed up in more kinds of sample detection research except coal sample, the detection model that each coal index of the utility model 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 comprise a constant term, within the present embodiment, water is example, the parameter of detection model and equation curve refer to table 4 to table 7, equation curve (detection model) is as shown in Figure 32 to Figure 35, and the parameter of other detection model and equation curve figure are slightly.
Table 4Y type original spectrum detection model parameter (interior water %)
Table 5W type original spectrum detection model parameter (interior water %)
Table 6P type original spectrum detection model parameter (interior water %)
Table 7X type original spectrum detection model parameter (interior water %)
Embodiment 2 applicating evaluating is tested
The detection model that the present embodiment utilizes embodiment to establish detects liquid water 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 interior water of coal sample, ash content, volatile matter, the full content of sulphur, fixed carbon and flammable body and the testing of thermal value 7 indexs 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 of table 8 adopts the utility model methods analyst testing result
From table 8, in the utility model coal, the index such as the prediction standard deviation of the content of water, ash content, volatile matter, full sulphur, fixed carbon and flammable body and thermal value 7 index detection method, the coefficient of determination and related coefficient is all close with the result with corresponding calibration.The repeatability of concrete conventional method Physical Chemistry Experiment value, NIR method scan values and both differences, current standard methods limits difference in table 9 to table 12, the every project of every type only lists the result of 10 samples, within water, thermal value, fixed carbon be example, other abundant experimental results can not repeat one by one at this.
Table 9Y type detection model testing result-interior water (%)
Table 10W type detection model Preliminary Applications result-interior water (%)
Table 11P type detection model Preliminary Applications result--interior water (%)
Table 12X type detection model Preliminary Applications result-interior water (%)
Table 13Y type detection model Preliminary Applications result-thermal value (MJ/Kg)
Table 14W type detection model Preliminary Applications result-thermal value (MJ/Kg)
Table 15P type detection model Preliminary Applications result-thermal value (MJ/Kg)
Table 16X type detection model Preliminary Applications result-thermal value (MJ/Kg)
Table 17Y type detection model Preliminary Applications result-fixed carbon (%)
Table 18W type detection model Preliminary Applications result-fixed carbon (%)
Table 19P type detection model Preliminary Applications result-fixed carbon (%)
Table 20X type detection model Preliminary Applications result-fixed carbon (%)
From above-mentioned representational table 9 to table 20, the utility model system be applied to coal middle finger target detect, its accuracy conform to current standards method repeatability limit difference requirement.Operate very fast easy, within about 50 seconds, just can complete the scanning of a sample and interior water, ash content, volatile matter, the content of full sulphur, fixed carbon and flammable body and thermal value 7 Indexs measure, 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.The new method provided based on the utility model detects and obtains 7 key components in coal sample and only need 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.With regard to the Indexes Comparison that each is single:
The detection of moisture, compared with existing Oven Method: it is 0.14% that the original spectrogram of Y type calibrates standard deviation, calibration related coefficient is 0.9969; Validation-cross standard deviation 0.15%, validation-cross related coefficient 0.9965; The standard deviation of Preliminary Applications is 0.17%, and related coefficient is 0.995.W type original spectrogram calibration standard deviation is 0.25%, and calibration related coefficient is 0.9021; Validation-cross standard deviation 0.28%, validation-cross related coefficient 0.8756; The standard deviation of Preliminary Applications is 0.23%, and related coefficient is 0.875.P type original spectrogram calibration standard deviation is 0.41%, and calibration related coefficient is 0.9814; Validation-cross standard deviation 0.47%, validation-cross related coefficient 0.9746; The standard deviation of Preliminary Applications is 0.83%, and related coefficient is 0.944.X-type original spectrogram calibration standard deviation is 0.12%, and calibration related coefficient is 0.9981; Validation-cross standard deviation 0.31%, validation-cross related coefficient 0.9874; The standard deviation of Preliminary Applications is 0.13%, and related coefficient is 0.997.
The detection of ash content, compared with existing high temperature oven process: it is 0.34% that the original spectrogram of Y type calibrates standard deviation, calibration related coefficient is 0.9955; Validation-cross standard deviation 0.35%, validation-cross related coefficient 0.9954; The standard deviation of Preliminary Applications is 0.77%, and related coefficient is 0.980.W type original spectrogram calibration standard deviation is 0.51%, and calibration related coefficient is 0.9851; Validation-cross standard deviation 0.74%, validation-cross related coefficient 0.9687; The standard deviation of Preliminary Applications is 0.57%, and related coefficient is 0.982.P type original spectrogram calibration standard deviation is 1.29%, and calibration related coefficient is 0.9785; Validation-cross standard deviation 1.62%, validation-cross related coefficient 0.9659; The standard deviation of Preliminary Applications is 1.32%, and related coefficient is 0.970.X-type original spectrogram calibration standard deviation is 1.48%, and calibration related coefficient is 0.9879; Validation-cross standard deviation 2.05%, validation-cross related coefficient 0.9763; The standard deviation of Preliminary Applications is 3.88%, and related coefficient is 0.926.
Volatile matter detects, and compared with existing high temperature oven process: it is 0.27% that the original spectrogram of Y type calibrates standard deviation, 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 detection of full sulphur, compared with high-temp combustion infrared absorption method: it is 0.06% that the original spectrogram of Y type calibrates standard deviation, calibration related coefficient is 0.9838; Validation-cross standard deviation 0.07%, validation-cross related coefficient 0.9822; The standard deviation of Preliminary Applications is 0.08%, and related coefficient is 0.976.W type original spectrogram calibration standard deviation is 0.04%, and calibration related coefficient is 0.9496; Validation-cross standard deviation 0.05%, validation-cross related coefficient 0.9379; The standard deviation of Preliminary Applications is 0.05%, and related coefficient is 0.917.P type original spectrogram calibration standard deviation is 0.17%, and calibration related coefficient is 0.9572; Validation-cross standard deviation 0.21%, validation-cross related coefficient 0.9330; The standard deviation of Preliminary Applications is 0.22%, and related coefficient is 0.927.X-type original spectrogram calibration standard deviation is 0.11%, and calibration related coefficient is 0.8988; Validation-cross standard deviation 0.16%, validation-cross related coefficient 0.7412; The standard deviation of Preliminary Applications is 0.12%, and related coefficient is 0.849.
The detection of thermal value, compared with existing oxygen bomb combustion: it is 0.12MJ/Kg that the original spectrogram of Y type calibrates standard deviation, calibration related coefficient is 0.9960; Validation-cross standard deviation 0.14MJ/Kg, validation-cross related coefficient 0.9951; The standard deviation of Preliminary Applications is 0.26MJ/Kg, and related coefficient is 0.983.W type original spectrogram calibration standard deviation is 0.22MJ/Kg, and calibration related coefficient is 0.9815; Validation-cross standard deviation 0.31MJ/Kg, validation-cross related coefficient 0.9610; The standard deviation of Preliminary Applications is 0.27MJ/Kg, and related coefficient is 0.972.P type original spectrogram calibration standard deviation is 0.48MJ/Kg, and calibration related coefficient is 0.9734; Validation-cross standard deviation 0.60MJ/Kg, validation-cross related coefficient 0.9594; The standard deviation of Preliminary Applications is 0.88MJ/Kg, and related coefficient is 0.971.X-type original spectrogram calibration standard deviation is 0.45%, and calibration related coefficient is 0.9830; Validation-cross standard deviation 0.72MJ/Kg, validation-cross related coefficient 0.9582; The standard deviation of Preliminary Applications is 1.20MJ/Kg, and related coefficient is 0.901.
The detection of fixed carbon, compared with existing baking oven, high temperature oven process: it is 0.29% that the original spectrogram of Y type calibrates standard deviation, calibration related coefficient is 0.9948; Validation-cross standard deviation 0.30%, validation-cross related coefficient 0.9931; The standard deviation of Preliminary Applications is 0.43%, and related coefficient is 0.986.W type original spectrogram calibration standard deviation is 2.20%, and calibration related coefficient is 0.8499; Validation-cross standard deviation 2.49%, validation-cross related coefficient 0.8036; The standard deviation of Preliminary Applications is 2.11%, and related coefficient is 0.835.P type original spectrogram calibration standard deviation is 1.34%, and calibration related coefficient is 0.9731; Validation-cross standard deviation 1.65%, validation-cross related coefficient 0.9587; The standard deviation of Preliminary Applications is 3.10%, and related coefficient is 0.941.X-type original spectrogram calibration standard deviation is 1.66%, and calibration related coefficient is 0.9883; Validation-cross standard deviation 2.16%, validation-cross related coefficient 0.9802, the standard deviation of Preliminary Applications is 2.64%, and related coefficient is 0.972.
The detection of flammable body, compared with existing baking oven, high temperature oven process: it is 0.34% that the original spectrogram of Y type calibrates standard deviation, calibration related coefficient is 0.9954; Validation-cross standard deviation 0.37%, validation-cross related coefficient 0.9948; The standard deviation of Preliminary Applications is 0.60%, and related coefficient is 0.988.W type original spectrogram calibration standard deviation is 2.35%, and calibration related coefficient is 0.8414; Validation-cross standard deviation 2.62%, validation-cross related coefficient 0.7981; The standard deviation of Preliminary Applications is 2.19%, and related coefficient is 0.819.P type original spectrogram calibration standard deviation is 1.32%, and calibration related coefficient is 0.9685; Validation-cross standard deviation 1.51%, validation-cross related coefficient 0.9586; The standard deviation of Preliminary Applications is 4.67%, and related coefficient is 0.867.X-type original spectrogram calibration standard deviation is 1.34%, and calibration related coefficient is 0.9874; Validation-cross standard deviation 1.92%, validation-cross related coefficient 0.9738; The standard deviation of Preliminary Applications is 3.32%, and related coefficient is 0.930.
Claims (7)
1. one kind is detected the system of 7 indexs in coal sample simultaneously, it is characterized in that, comprise charging hopper, sample introduction tank, sample introduction track, near-infrared analyzer, computing machine, display screen and printer, described charging hopper be arranged at sample introduction tank upper end and can in sample introduction tank range of size reciprocal uniform motion, sample introduction tank enters near-infrared analyzer along sample introduction track, near-infrared analyzer connects computing machine and display screen respectively, and computing machine is all connected printer with display screen.
2. detect the system of 7 indexs in coal sample according to claim 1, it is characterized in that, described near-infrared analyzer is the SY-3650-DDS type near-infrared analyzer of FOSS ANALYTICAL A/S company of Denmark simultaneously; 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.
3. according to claim 1 or 2, detect the system of 7 indexs in coal sample simultaneously, it is characterized in that, described near-infrared analyzer is connected by RS-232C interface and computing machine.
4. detect the system of 7 indexs in coal sample according to claim 1, it is characterized in that, described sample introduction tank is quartz material simultaneously.
5. detect the system of 7 indexs in coal sample according to claim 1, it is characterized in that, described charging hopper is provided with stirring apparatus simultaneously.
6. detect the system of 7 indexs in coal sample according to claim 1, it is characterized in that, described charging quarrel is provided with scalable flat board simultaneously.
7. detect the system of 7 indexs in coal sample according to claim 6, described flat board is cardboard simultaneously.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105445221A (en) * | 2015-12-31 | 2016-03-30 | 聚光科技(杭州)股份有限公司 | NIR (near infrared spectrum) analysis device and method for large-particle material |
| CN106053377A (en) * | 2016-08-12 | 2016-10-26 | 曹蕊 | Energy-saving apparatus used for detection of carbon content |
| CN111795912A (en) * | 2020-09-08 | 2020-10-20 | 天津美腾科技股份有限公司 | Ash content detection system and control method thereof |
| CN113522152A (en) * | 2021-09-17 | 2021-10-22 | 江西鼎峰智能装备有限公司 | Powder mixing system, control method and powder intensified mixing method |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105445221A (en) * | 2015-12-31 | 2016-03-30 | 聚光科技(杭州)股份有限公司 | NIR (near infrared spectrum) analysis device and method for large-particle material |
| CN106053377A (en) * | 2016-08-12 | 2016-10-26 | 曹蕊 | Energy-saving apparatus used for detection of carbon content |
| CN111795912A (en) * | 2020-09-08 | 2020-10-20 | 天津美腾科技股份有限公司 | Ash content detection system and control method thereof |
| CN111795912B (en) * | 2020-09-08 | 2020-12-15 | 天津美腾科技股份有限公司 | Ash content detection system and control method thereof |
| CN113522152A (en) * | 2021-09-17 | 2021-10-22 | 江西鼎峰智能装备有限公司 | Powder mixing system, control method and powder intensified mixing method |
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