NL2030689B1 - Analysis method for online monitoring of biomass blended-combustion ratio based on stable carbon isotopes - Google Patents

Analysis method for online monitoring of biomass blended-combustion ratio based on stable carbon isotopes Download PDF

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NL2030689B1
NL2030689B1 NL2030689A NL2030689A NL2030689B1 NL 2030689 B1 NL2030689 B1 NL 2030689B1 NL 2030689 A NL2030689 A NL 2030689A NL 2030689 A NL2030689 A NL 2030689A NL 2030689 B1 NL2030689 B1 NL 2030689B1
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Feng Xiangyu
Zhu Di
Shi Zhe
Wang Shuyuan
Guan Haibin
Peng Yu
Xu Dan
Baofeng Zhao
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Energy Res Inst Shandong Academy Sciences
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Abstract

A system and an analysis method for on-line monitoring of biomass blended-combustion ratio based on stable carbon isotopes, wherein flue gas is taken from the flue of the co-combustion boiler of coal and biomass for cooling and dust removal, and then mid-infrared laser detection apparatus based on stable carbon isotopes is adopted to measure the stable carbon isotope ratio SBC of the blended flue gas, the test error of the apparatus is only i0.025%o and is not interfered by moisture, and the apparatus cost is far lower than 14C online analysis apparatus, so it is economically competitive. An online analysis method is established, the linear regression equation obtained after correction by using carbon content or correction by using calorific value has a goodness-of—flt of R2>0.99, and the error for determining biomass blended-combustion ratio is controlled within 2.0% and can be used for monitoring changes in biomass blended-combustion ratios in real time. The present disclosure can accurately monitor biomass blended-combustion ratios in real time, and thus can technically support formulation and implementation of biomass application subsidy policies, and can be used in carbon emission monitoring and carbon trading markets.

Description

ANALYSIS METHOD FOR ONLINE MONITORING OF BIOMASS
BLENDED-COMBUSTION RATIO BASED ON STABLE CARBON
ISOTOPES
Technical Field
The present disclosure relates to the establishment of a real-time online detection method for monitoring 8!*C value in the co-combustion flue gas of coal and biomass in real time by using stable carbon isotope mid-infrared laser apparatus, so as to determine the biomass blended-combustion ratio, and belongs to the field of isotope detection and boiler combustion technology detection.
Background
Biomass energy is clean and renewable. In recent years, biomass power generation has gradually emerged, and the adoption of biomass, instead of fossil fuels, for power generation can effectively reduce emissions of CO: and SO2. Power generation by co-combustion of biomass and coal has been included in the national industrial planning, and electricity price subsidies will be provided for the biomass power generation part, which involves the metering of biomass electricity. However, scientific and fair online detection of biomass is still the biggest problem faced by existing technologies of coal-biomass coupled power generation. According to collection and detection locations, the ratio detection of biomass fuel can be divided into front-end detection and back-end detection. Great progress has been made in co-combustion power generation in the EU, but current methods mostly use front-end detection, which requires a large quantity of tests, calculations, reports and labors. At present, the relatively advanced back-end detection methods mainly include SO; concentration detection method and #*C content detection method. Biomass contains some alkali metals, which will react with S and affect the monitoring results of SO: concentration; the over low natural abundance of !*C requires extremely high apparatus accuracy, so the accuracy and reliability of the *C content detection method is still in the exploratory stage; moreover, !*C technology mostly uses flue gas side sampling for laboratory analysis, and the analysis apparatus used is mostly expensive, such as nuclear magnetic precise instrument, mass spectrometry precise instrument and so on, as a result,
the promotion and application of the back-end detection technology for biomass are limited. It is reported in an open master’s thesis (Study on Biomass Blended-combustion ratio Measurement and Particulate Matter Abatement in Co-firing Plants, Mei Kaiyuan, Tsinghua University, 2015) that the error for the laboratory accelerated mass spectrometer (AMS) to determine the biomass blended-combustion ratio by means of *C concentration offline test is 10% to 16%. Therefore, the research and development of apparatus, which is suitable for popularization in the industry and is capable of rapidly and accurately detecting application amount of biomass, can technically support the implementation of government subsidy policies.
At present, it is urgent to solve the problems existing in the back-end detection of biomass application amount, such as real-time detection, expensive apparatus and so on. The technology of mid-infrared laser isotope detection can realize fast and real-time detection of stable carbon isotope ratio $C (3CO2/2CO:}). Since the §°C values of biomass are significantly different from those of coal, the blending ratio of coal and biomass can be detected according to the differences in their §°C values. In addition, the mid-infrared laser isotope detection apparatus is low in cost, and has been successfully applied to exploration of oil and gas fields. Based on the continuously maturing and developing quantum cascade lasers, a set of multichannel optical detection core devices has been designed and developed for existing carbon isotope mid-infrared laser detection apparatus, wherein the detection error of the apparatus is only +0.025%0, which can meet the demand for accurate measurement of biomass application amount; besides, the difficulty in installing and maintaining mid- and far-infrared laser detection apparatus has been greatly decreased, and laser detectors can be rapidly replaced to meet the needs of instruments with different wavelengths, so mass spectrometry and other expensive apparatuses can be replaced, but there is yet no corresponding measurement method at home and abroad. Therefore, it is very important to establish a real-time online detection and analysis method for monitoring the biomass blended-combustion ratio by means of stable carbon isotope mid-infrared laser detection apparatus. This method can technically support the implementation of government subsidy policies, and also can be applied to carbon inspection and carbon trading markets, thereby promoting healthy and orderly development of clean energy.
Summary of the Invention
The present disclosure provides a system and an analysis method for on-line monitoring of biomass blended-combustion ratio based on stable carbon isotopes, so as to realize real-time online detection of biomass blended-combustion ratio with an error controlled within 2.0%.
The technical solution of the present disclosure is as follows: a system and an analysis method for real-time online monitoring of biomass blended-combustion ratio based on stable carbon isotopes, wherein the system comprises a flue gas online sampling channel, a condenser, a filter, a back pressure valve, and a carbon isotope mid-infrared laser detection apparatus.
The carbon isotope mid-infrared laser detector mainly comprises a quantum cascade laser, a hollow waveguide and a mid-infrared laser detector, the hollow waveguide comprising a multichannel optical path, a laser inlet, and a gas inlet/outlet. The blended flue gas enters the multichannel optical path system in the hollow waveguide through the gas inlet, the quantum cascade laser emits mid-infrared laser in the spectrum, and the mid-infrared laser passes through the hollow waveguide and interacts with the carbon dioxide gas molecules therein, wherein the infrared laser is absorbed by carbon dioxide gas molecules according to Lambert Beer’s law, and the absorption spectrum receives signals via the detector, thereby measuring the absorption value of the carbon isotopes. The carbon isotope mid-infrared laser detector can measure multiple spectral absorption peaks by measuring the absorption spectrum, and the two main absorption peaks are the CO: absorption peak on the left and the '2CO, absorption peak on the right. When the isotope ratio 38°C (C/C) contained in the carbon dioxide gas is obtained from the absorption peak area, the isotope value can be given in real time. The carbon isotope mid-infrared laser detection apparatus is an analyzer that accurately measures the carbon element content and stable isotope values (**C/**C) in various carbon-containing components. The carbon isotope analyzer creatively uses advanced optical measurement technologies, namely, mid-infrared quantum cascade laser (QCL) and hollow waveguide (HWG), to achieve high-precision laser measurement of carbon isotopes. QCL is a unipolar semiconductor laser based on the electronic transition between sub-bands of semiconductor coupled quantum wells, and the working principle thereof is completely different from that of conventional semiconductor lasers. It breaks the electron-hole recombination stimulated radiation mechanism of traditional p-n junction semiconductor lasers, and realizes single electron injection and multi-photon output by using the population inversion between the separated electronic states caused by the quantum confinement effect in the thin layer of the semiconductor heterojunction.
QCL has the advantages of small size, simple operation, low price, and low environmental sensitivity.
Also in the present disclosure, a back pressure valve is installed ahead of the carbon isotope mid-infrared laser detection apparatus to realize continuous sample feeding; the carbon isotope mid-infrared laser detector can simultaneously detect CO: and “CO; stable carbon isotope values.
The present disclosure provides a system and an analysis method for on-line monitoring of biomass blended-combustion ratio based on stable carbon isotopes, wherein: the flue gas taken online from a coal and biomass co-combustion boiler is a blended gas of CO: and CO, and is introduced into the carbon isotope mid-infrared laser detection apparatus for stable carbon isotope analysis, the stable carbon isotope mid-infrared laser detection apparatus being capable of directly testing the carbon isotope ratio §*C (**C/'2C) of the blended flue gas.
The carbon isotope ratio °C (#3C/!2C) detected by the carbon isotope mid-infrared laser detection apparatus is defined according to the formula below: 55C = [(Rp/Rs-1)]x1000 in the formula, Rp is the abundance ratio (*Cp/*2Cp) of heavy and light isotopes of carbon element in the sample, and Rs is the abundance ratio (*Cs/'2Cs) of heavy and light isotopes in internationally universal reference substances.
The stable carbon isotope mid-infrared laser detection apparatus can directly test the carbon isotope ratio 8!°C of the blended flue gas, and §C values of different coal samples are significantly different from that of different biomass. According to the differences in §"°C values, a linear regression equation is obtained after correction by using carbon content of coal and biomass, and can be used to calculate the biomass blended-combustion ratio in the co-combustion substances: v=ax+b (1)
Erg) Kerr (2)
In formula (1), v is the ô7C value displayed by the carbon isotope laser detection apparatus, and x is the biomass blended-combustion ratio corrected by using carbon content, wherein the influences of moisture, ash, volatile matter and other interference factors can be excluded after correction by using carbon content, a is the slope of the linear regression equation obtained by co-combustion of different types of coal with different biomass ratios, and b is the 3'*C value of a coal sample; in formula (2), 7 is the biomass blended-combustion ratio without correction by using carbon content, ('c is the carbon content of the coal sample, and Cz is the biomass carbon content.
The stable carbon isotope mid-infrared laser detection apparatus can directly test the carbon 5 isotope ratio '°C of the blended flue gas, and significant differences exist in the §'°C values of different coal samples and different biomass. According to the differences in ôC values, a linear regression equation is obtained after correction by using calorific values of coal and biomass, and can be used to determine the biomass blended-combustion ratio in the co-combustion substances: y=ax;+b (3) r = VEA ir gaNsitgs (4)
In formula (3), y is the ô1°C value displayed by the carbon isotope laser detection apparatus, and x; is the biomass blended-combustion ratio corrected by using calorific value, a; is the slope of the linear regression equation obtained by co-combustion of different types of coal with different biomass ratios, and 5 is the 3C value of a coal sample, wherein the influences of moisture, ash, volatile matter and other interference factors can be excluded after correction by using calorific value; in formula (4), 7; is the biomass blended-combustion ratio without correction by using calorific value, Oc is the calorific value of the coal sample, and (3 is the biomass calorific value.
As for the above method of the present disclosure, the error of the stable carbon isotope online detection apparatus is only +£0.025%o, the linear regression equation y=ax+b has a goodness-of-fit of R2>0.99, and the test error range for biomass blended-combustion ratio (e.g. 20%) is controlled to be within 2.0%.
The present disclosure has the following advantages and outstanding effects: (1) the test error of the stable carbon isotope mid-infrared laser detection apparatus is only +0.025%o, the obtained carbon isotope ratio &°C is not interfered by moisture, ash, volatile matter, etc., and the apparatus cost is far lower than !*C online analysis apparatus, and is simple, practical and portable, so it is economically competitive; (2) an online analysis method is established to monitor the biomass blended-combustion ratio in real time, and the linear regression equation v=ax+b or y=ax,+b obtained after correction by using carbon content or correction by using calorific value has a goodness-of-fit of R2>0.99, and the error range for determining biomass blended-combustion ratio (e.g. 20%) is controlled within 2.0%, showing a high accuracy; (3) the online analysis method provided in the present disclosure is applicable for the co-combustion detection of a variety of coal and biomass, and is less restricted by the types of raw materials; at the same time, the analytical method based on correction by using carbon content can be used in carbon emission monitoring and carbon trading markets; (4) the linear regression equation v=a;x;+b obtained after correction by using calorific value can provide important reference data for the power generation generated by co-combustion of biomass in power plants; and (5) in case of a significant difference between the actual biomass blended-combustion ratio obtained according to the analysis method and the provided ratio, it can be inferred that the water content in the biomass is too high or there is adulteration.
Description of Drawings
Fig. 1 is a diagram showing the connection of a sampling test system according to the embodiment of the present disclosure. Fig. 2 is a multichannel coupling optical path system of a mid-infrared laser. Fig. 3 is a measuring schematic diagram of the carbon isotope measuring instrument used in the present disclosure. Fig. 4 is a fitted linear relation obtained in Example 3 of the present disclosure corrected by using carbon content. Fig. 5 is a fitted linear relation obtained in Example 3 of the present disclosure corrected by using calorific value. Fig. 6 is a fitted linear relation obtained in Example 5 of the present disclosure corrected by using carbon content. Fig. 7 is a fitted linear relation obtained in Example 5 of the present disclosure corrected by using calorific value. Fig. 8 is a fitted linear relation obtained in Example 7 of the present disclosure corrected by using carbon content. Fig. 9 is a fitted linear relation obtained in
Example 7 of the present disclosure corrected by using calorific value.
Fig. 10 is a fitted linear relation obtained in Example 8 of the present disclosure corrected by using carbon content. Fig. 11 is a fitted linear relation obtained in Example 8 of the present disclosure corrected by using calorific value. Fig. 12 is a linear relation obtained in Example 9 of the present disclosure. Fig. 13 is a fitted linear relation obtained in Example 12 of the present disclosure corrected by using carbon content. Fig. 14 is a fitted linear relation obtained in
Example 12 of the present disclosure corrected by using calorific value. Fig. 15 is a fitted linear relation obtained in Example 13 of the present disclosure corrected by using carbon content. Fig. 16 is a fitted linear relation obtained in Example 13 of the present disclosure corrected by using calorific value.
In the drawings: 1-Boiler; 2-Flue gas channel; 3-Sampling channel; 4-Condenser; 5-Filter; 6-Back pressure valve; 7-Carbon isotope mid-infrared laser detection apparatus.
Embodiments
In order to make the monitoring system, the real-time online analysis method and advantages of the present disclosure clearer, the present disclosure will be further elaborated below with reference to specific examples and the drawings.
The present disclosure discloses a system and an analysis method for real-time monitoring of biomass blended-combustion ratio based on stable carbon isotopes. Fig. 1 is a structure diagram of a system device for monitoring biomass blended-combustion ratio according to the present disclosure, wherein the system comprises a boiler 1, a flue gas channel 2, a sampling channel 3, a condenser 4, a filter 5, a back pressure valve 6, and a carbon isotope mid-infrared laser detector 7. After the flue gas generated by the co-combustion of coal and biomass in the boiler passes through the condenser, the filter and the back pressure valve in sequence via the flue sampling channel into the carbon isotope laser detection apparatus, the ô7C value (13C02/2CO>) is obtained by the carbon isotope mid-infrared laser detector 7 and is then plugged into the calculation formula (1) and (3) to get the biomass blended-combustion ratio.
The carbon isotope mid-infrared laser detector mainly comprises a quantum cascade laser (AdTech, USA), a hollow waveguide and a mid-infrared laser detector (THORLABS,
DET10A/M), wherein the hollow waveguide contains a multichannel optical path, a laser inlet, and a gas inlet/outlet, as shown in Fig. 2.
The process of detecting the flue gas carbon isotope ratio by using the carbon isotope measuring instrument is as below: the blended flue gas enters the multichannel optical path system in the hollow waveguide through the gas inlet, the quantum cascade laser emits mid-infrared laser in the spectrum, and the mid-infrared laser passes through the hollow waveguide and interacts with the carbon dioxide gas molecules therein, wherein the infrared
Jager is absorbed by carbon dioxide gas molecules according to Lambert Beer’s law, and the absorption spectrum receives signals via the detector, thereby measuring the absorption value of the carbon isotopes. The measurement diagram of the carbon isotope measuring instrument is shown in Fig. 3, wherein the carbon isotope mid-infrared laser detector can measure multiple spectral absorption peaks by measuring the absorption spectrum, and the two main absorption peaks are the *CO; absorption peak on the left and the !2CO: absorption peak on the right. When 3 the isotope ratio 53C (!*C/2C) contained in the carbon dioxide gas is obtained from the absorption peak area, the isotope value can be given in real time.
Table 1 shows industrial analyses, element analyses and calorific value determination of seven samples, including Shanxi coal, Inner Mongolia coal, Guizhou coal, com stalks, cotton stalks, sawdust, and rice husks. The real-time online analysis method of the present disclosure will be further explained by the co-combustion of different coal samples (Shanxi coal, Inner
Mongolia coal, Guizhou coal) and different types of biomass (corn stalks, cotton stalks, sawdust, rice husks), but the present disclosure is not limited to these examples.
Example 1: Method for online detection of the 5C value of a coal sample by means of a carbon isotope mid-infrared laser detector
Pure Shanxi coal was added to a boiler for full combustion, then the flue gas was obtained from the sampling pipe of the flue in real time during the combustion process and passed through the condenser, the filter and the back pressure valve in sequence, and finally the spectral absorption peak areas of CO; and "CO; contained in the blended gas were measured by the carbon isotope mid-infrared laser detection apparatus. Based on the comparison of the isotope peak area difference between CO and "*CO,, the carbon isotope 8!°C value of Shanxi coal was obtained, and the "°C value of Shanxi coal obtained after correction by using the standard CO: carbon isotope 8!°C value was -20.61.
Example 2: Method for online detection of the 8!3C value of biomass by means of a carbon isotope mid-infrared laser detector
Pure com stalks were added to a boiler for full combustion, then the flue gas was obtained from the sampling pipe of the flue in real time during the combustion process and passed through the condenser, the filter and the back pressure valve in sequence, and finally the spectral absorption peak areas of 3CO: and !2CO2 contained in the blended gas were measured by the carbon isotope mid-infrared laser detection apparatus. Based on the comparison of the isotope peak area difference between !3CO2 and *CO,, the carbon isotope 8'°C value of corn stalks was obtained, and the 85C value of corn stalks obtained after correction by using the standard CO: carbon isotope °C value was -11.91.
Example 3: Method for on-line monitoring of biomass blended-combustion ratio by means of a carbon isotope mid-infrared laser detector
Together with different blending ratios of corn stalks, Shanxi coal was added into a boiler for full combustion, the blending ratios of com stalks being 2.5%, 5%, 7.5%, 10%, 15%, 20%, 25%, and 30%, then the flue gases were obtained from the sampling pipe of the flue in real time during the combustion process and passed through the condenser, the filter and the back pressure valve in sequence, and finally the spectral absorption peak areas of CO, and !?CO: contained in the blended gas were measured by the carbon isotope mid-infrared laser detection apparatus.
Based on the comparison of the isotope peak area difference between CO» and CO, the carbon isotope 8'*C values of different com stalk blending ratios were obtained after correction by using the standard CO: carbon isotope 85C value, i.e. -21.4, -21.224, -21.09, -20.91, -20.68, -20.32, -19.95, and -19.56. The biomass blending ratios corrected by using carbon content were: 1.41%, 2.86%, 4.33%, 5.84%, 8.97%, 12.25%, 15.69%, and 19.31%. These blending ratios were taken as the abscissas, and obtained corresponding 57C values were taken as ordinates for plotting, and a linear equation was obtained after linear fitting. As shown in Fig. 4, the obtained fitted linear relation of Shanxi coal and different blending ratios of corn stalks was y=0.1x-21.55 (wherein x is the biomass blended-combustion ratio corrected by using carbon content, y is the carbon isotope §°C value), and the goodness-of-fit was R?=0.997, indicating that the linear relationship is good. This relation was used for error analysis for the combustion ratio of Shanxi coal and corn stalks. When the blended-combustion ratio of corn stalks was 20%, the error range was 2.0%.
In addition, the biomass blending ratio can also be determined via correction by using calorific value. The biomass blending ratios corrected by using calorific value were: 1.44%, 2.91%, 4.41%, 5.95%, 9.13%, 12.46%, 15.95%, and 19.61%. These blending ratios were taken as the abscissas, and obtained corresponding 8'°C values were taken as ordinates for plotting, and a linear equation was obtained after linear fitting. As shown in Fig. 5, the obtained fitted linear relation of Shanxi coal and different blending ratios of corn stalks was y=0.1x-21.55 (wherein x is the biomass blended-combustion ratio corrected by using calorific value, y is the carbon isotope °C value), and the goodness-of-fit was R?=0.9973, indicating that the linear relationship is good. This relation was used for error analysis for the combustion ratio of Shanxi coal and corn stalks. When the blended-combustion ratio of corn stalks was 20%, the error range was 1.9%.
Based on the comparison of the linear equations obtained after correction by using carbon content with that obtained after correction by using calorific value, the two correction methods can both obtain the true functional relation between biomass blending ratio and carbon isotope ratio, and the error analyses are similar.
Example 4: Method for on-line monitoring of biomass blended-combustion ratio by means of a carbon isotope mid-infrared laser detector
Pure cotton stalks were added to a boiler for full combustion, then the flue gas was obtained from the sampling pipe of the flue in real time during the combustion process and passed through the condenser, the filter and the back pressure valve in sequence, and finally the spectral absorption peak areas of CO; and "CO; contained in the blended gas were measured by the carbon isotope mid-infrared laser detection apparatus. Based on the comparison of the isotope peak area difference between “CO, and '*CO,, the carbon isotope §'*C value of cotton stalks was obtained, and the §'*C value of cotton stalks obtained after correction by using the standard
CO: carbon isotope 8'°C value was -26.09.
Example 5: Method for on-line monitoring of biomass blended-combustion ratio by means of a carbon isotope mid-infrared laser detector
Together with different blending ratios of cotton stalks, Shanxi coal was added into a boiler for full combustion, the blending ratios of cotton stalks being 5%, 10%, 20%, and 30%; similar steps as those in Example 3 will not be repeated here, and the differences are as follows: the §!*C values of different cotton stalk blending ratios were obtained after correction by using carbon content, i.e. -21.88, -22.14, -22.60, and -23.25, and the blending ratios corrected by using carbon content were: 3.09%, 6.31%, 13.16%, and 20.62%, these blending ratios were taken as the abscissas, and obtained corresponding 8"C values were taken as ordinates for plotting, and a linear equation was obtained after linear fitting; as shown in Fig. 6, the obtained fitted linear relation of Shanxi coal and different blended-combustion ratios of cotton stalks was y=-0.0781x-21.62, and the goodness-of-fit was R?=0.996, indicating that the linear relationship is good. This relation was used for error analysis for the combustion ratio of Shanxi coal and cotton stalks. When the blended-combustion ratio of corn stalks was 20%, the error range was 1.0%. At the same time, the blending ratios corrected by using calorific value were: 3.12%,
il 6.36%, 13.26%, and 20.76%; the linear fitting equation obtained after plotting was y=-0.0777x-21.61, see Fig. 7, and the goodness-of-fit was R?=0.996, indicating that the linear relationship is good. This relation was used for error analysis for the combustion ratio of Shanxi coal and cotton stalks. When the blended-combustion ratio of corn stalks was 20%, the error range was 0.8%. The linear equation obtained after correction by using carbon content is similar to that obtained after correction by using calorific value, wherein the two correction methods can both obtain the true functional relation between biomass blending ratio and carbon isotope ratio, and the error analyses are similar.
Example 6: Method for online detection of the 8C value of biomass by means of a carbon isotope mid-infrared laser detector
Pure sawdust were added to a boiler for full combustion, then the flue gas was obtained from the sampling pipe of the flue in real time during the combustion process and passed through the condenser, the filter and the back pressure valve in sequence, and finally the spectral absorption peak areas of CO: and !2CO2 contained in the blended gas were measured by the carbon isotope mid-infrared laser detection apparatus. Based on the comparison of the isotope peak area difference between CO; and '2CO,, the carbon isotope §'°C value of sawdust was obtained, and the §'*C value of sawdust obtained after correction by using the standard CO: carbon isotope 8!3C value was -26.99.
Example 7: Method for on-line monitoring of biomass blended-combustion ratio by means of a carbon isotope mid-infrared laser detector
Together with different blending ratios of sawdust, Shanxi coal was added into a boiler for full combustion, the blending ratios of sawdust being 5%, 10%, 20%, and 30%; similar steps as those in Example 3 will not be repeated here, and the differences are as follows: the §'*C values of different sawdust blending ratios were obtained, 1.e. -21.84, -22.16, -22.60, and -23.20, and blending ratios corrected by using carbon content were: 3.14%, 6.40%, 13.34%, and 20.88%; these blending ratios were taken as the abscissas, and obtained corresponding $C values were taken as ordinates for plotting, and a linear equation was obtained after linear fitting; as shown in
Fig. 8, the obtained fitted linear relation of Shanxi coal and different blended-combustion ratios of sawdust was y=-0.077x-21.62, and the goodness-of-fit was R?=0.995, indicating that the linear relationship is good. This relation was used for error analysis for the combustion ratio of
Shanxi coal and sawdust. When the blended-combustion ratio of sawdust was 20%, the error range was 1.0%. At the same time, the blending ratios corrected by using calorific value were: 3.20%, 6.52%, 13.57%, and 21.21%, the linear fitting equation obtained after plotting was y=-0.0762x-21.62, see Fig. 9, and the goodness-of-fit was R?=0.995, indicating that the linear relationship is good. This relation was used for error analysis for the combustion ratio of Shanxi coal and sawdust. When the blended-combustion ratio of sawdust was 20%, the error range was 1.0%. Based on comparison, the linear equation obtained after correction by using carbon content is similar to that obtained after correction by using calorific value, wherein the two correction methods can both obtain the true functional relation between biomass blending ratio and carbon isotope ratio, and the error analyses are similar.
Example 8: Method for on-line monitoring of biomass blended-combustion ratio by means of a carbon isotope mid-infrared laser detector
Together with cotton stalks and sawdust, Shanxi coal was added into a boiler for full combustion, the common blending ratios of cotton stalks and sawdust being 5%, 10%, 20%, and 30% (the blending ratio is equally shared by the cotton stalks and the sawdust); similar steps as those in Example 3 will not be repeated here, and the differences are as follows: the §'°C values of different sawdust blending ratios were obtained, i.e. -21.85, -22.08, -22.6, and -23.15, and blending ratios corrected by using carbon content were: 3.11%, 6.36%, 13.25%, and 20.75%; these blended-combustion ratios were taken as the abscissas, and obtained corresponding §*C values were taken as ordinates for plotting; as shown in Fig. 10, the obtained fitted linear relation of Shanxi coal and different blending ratios of biomass (cotton stalks, sawdust) was y=-0.0744x-21.62, and the goodness-of-fit was R?=0.998, indicating that the linear relationship is good. This relation was used for error analysis for the combustion ratio of Shanxi coal and sawdust. When the biomass blended-combustion ratio was 20%, the error range was 2.0%. At the same time, the blending ratios corrected by using calorific value were: 3.16%, 0.44%, 13.41%, and 20.99%; the linear fitting equation obtained after plotting was y=-0.07365x-21.6, see Fig. 11, and the goodness-of-fit was R?=0.999, indicating that the linear relationship is good. This relation was used for error analysis for the combustion ratio of Shanxi coal and sawdust. When the biomass blended-combustion ratio was 20%, the error range was 1.9%. Based on comparison, the linear equation obtained after correction by using carbon content is similar to that obtained after correction by using calorific value, wherein the two correction methods can both obtain the true functional relation between biomass blending ratio and carbon isotope ratio, and the error analyses are similar.
Example 9: Method for on-line monitoring of biomass blended-combustion ratio by means of a carbon isotope mid-infrared laser detector
Together with cotton stalks and sawdust having a blending ratio of 20%, Shanxi coal was added into a boiler for full combustion, the blending ratios of cotton stalks and sawdust being: 0% of sawdust+20% of cotton stalks, 5% of sawdust+15% of cotton stalks, 10% of sawdust+10% of cotton stalks, and 15% of sawdust+5% of cotton stalks; similar steps as those in
Example 3 will not be repeated here, and the differences are as follows: the 3"*C values of different sawdust blending ratios were obtained, i.e. -22.5, -22.6, -22.6, and -22.6, and these blending ratios were taken as the abscissas, and obtained corresponding §'*C values were taken as ordinates for plotting; as shown in Fig. 12, the obtained fitted linear relation of Shanxi coal, and different blending ratios of cotton stalks and sawdust was almost a straight line, indicating that the coal can be used in co-combustion with multiple biomass and that the carbon isotope 55C value of the blended gas is irrelevant to the ratio changes of multiple biomass. Error analysis was performed. When the biomass blended-combustion ratio was 20%, the error range was 1.8%. Based on further analyses, the system for monitoring biomass blended-combustion ratio based on carbon isotope, and the analysis method thereof can be applied to co-combustion of coal sample with different biomass ratios in the present disclosure and the obtained total biomass blending ratio is barely influenced by the two types of biomass blending ratio variation.
Example 10: Method for online detection of the §'>C value of biomass by means of a carbon isotope mid-infrared laser detector
Pure Guizhou coal was added to a boiler for full combustion, then the flue gas was obtained from the sampling pipe of the flue in real time during the combustion process and passed through the condenser, the filter and the back pressure valve in sequence, and finally the spectral absorption peak areas of CO; and "CO; contained in the blended gas were measured by the carbon isotope mid-infrared laser detection apparatus. Based on the comparison of the isotope peak area difference between “CO; and !2CO>, the carbon isotope 85C value of Guizhou coal was obtained, and the §°C value of Guizhou coal obtained after correction by using the standard
CO: carbon isotope §'*C value was -21.01.
Example 11: Method for online detection of the 8!°C value of biomass by means of a carbon isotope mid-infrared laser detector
Pure Inner Mongolia coal was added to a boiler for full combustion, then the flue gas was obtained from the sampling pipe of the flue in real time during the combustion process and passed through the condenser, the filter and the back pressure valve in sequence, and finally the spectral absorption peak areas of 13CO2 and !?CO2 contained in the blended gas were measured by the carbon isotope mid-infrared laser detection apparatus. Based on the comparison of the isotope peak area difference between “CO: and '2CO», the carbon isotope 8'°C value of Inner
Mongolia coal was obtained, and the 5!°C value of Inner Mongolia coal obtained after correction by using the standard CO: carbon isotope 5!?C value was -21.91.
Example 12: Method for on-line monitoring of biomass blended-combustion ratio by means of a carbon isotope mid-infrared laser detector
Together with different blending ratios of corn stalks, Guizhou coal was added into a boiler for full combustion, the blending ratios of corn stalks being 5%, 10%, 20%, and 30%; similar steps as those in Example 3 will not be repeated here, and the differences are as follows: the °C values of different corn stalk blending ratios were obtained, i.e. -20.77, -20.38, -19.78, and -19.05, and blending ratios corrected by using carbon content were: 3.17%, 6.47%, 13.47%, and 21.06%; these blended-combustion ratios were taken as the abscissas, and obtained corresponding 8!5C values were taken as ordinates for plotting; as shown in Fig. 13, the obtained fitted linear relation of Guizhou coal and different blending ratios of corn stalks was y=0.095x-21.0, and the goodness-of-fit was R°=0.998, indicating that the linear relationship is good. This relation was used for error analysis for the combustion ratio of Guizhou coal and corn stalks. When the blended-combustion ratio of corn stalks was 20%, the error range was 0.5%. At the same time, the blending ratios corrected by using calorific value were: 3.19%, 6.50%, 13.52%, and 21.14%; the linear fitting equation obtained after plotting was y=0.095x-21.05, see
Fig. 14, and the goodness-of-fit was R2=0.998, indicating that the linear relationship is good.
This relation was used for error analysis for the combustion ratio of Guizhou coal and corn stalks.
When the blended-combustion ratio of corn stalks was 20%, the error range was 0.7%. Based on comparison, the linear equation obtained after correction by using carbon content is similar to that obtained after correction by using calorific value, wherein the two correction methods can both obtain the true functional relation between biomass blending ratio and carbon isotope ratio, and the error analyses are similar.
Example 13: Method for on-line monitoring of biomass blended-combustion ratio by means of a carbon isotope mid-infrared laser detector
Together with different blending ratios of corn stalks, Inner Mongolia coal was added into a boiler for full combustion, the blending ratios of corn stalks being 5%, 10%, 20%, and 30%; similar steps as those in Example 3 will not be repeated here, and the differences are as follows: the 83°C values of different corn stalk blending ratios were obtained, i.e. -21.65, -21.36, 20.81, and -20.14, and blending ratios corrected by using carbon content were: 3.17%, 6.47%, 13.47%, and 21.06%; these blending ratios were taken as the abscissas, and obtained corresponding §'*C values were taken as ordinates for plotting; as shown in Fig. 15, the obtained fitted linear relation of Inner Mongolia coal and different blending ratios of corn stalks was y=0.9048x-21.905, and the goodness-of-fit was R*=0.999, indicating that the linear relationship is good. This relation was used for error analysis for the combustion ratio of Inner Mongolia coal and corn stalks.
When the blended-combustion ratio of corn stalks was 20%, the error range was 0.5%. At the same time, the blending ratios corrected by using calorific value were: 2.84%, 5.81%, 12.19%, and 19.23%; the linear fitting equation obtained after plotting was y=0.912x-21.904, see Fig. 16, and the goodness-of-fit was R?=0.999, indicating that the linear relationship is good. This relation was used for error analysis for the combustion ratio of Inner Mongolia coal and corn stalks. When the blended-combustion ratio of corn stalks was 20%, the error range was 0.2%.
Based on comparison, the linear equation obtained after correction by using carbon content is similar to that obtained after correction by using calorific value, wherein the two correction methods can both obtain the true functional relation between biomass blending ratio and carbon isotope ratio, and the error of the biomass blending ratio corrected by using calorific value is smaller.
Examples 3, 5 and 7 of the present disclosure relate to co-combustion of Shanxi coal respectively with a single biomass involving three types of biomass, such as corn stalks, cotton stalks and sawdust; then the carbon isotope $'°C value of the blended flue gas is obtained by means of carbon isotope laser detection apparatus, and, with the biomass blended-combustion ratios (0 to 30%) taken as the abscissas and carbon isotope 8!°C values taken as ordinates, a linear regression equation was obtained after fitting corrected by using carbon contents or calorific values of Shanxin coal and different biomass, wherein the goodness-of-fit was R*>0.99, indicating that their linear relationship is good. When the biomass blending ratio is 20%, the error the biomass blended-combustion ratio is determined to be within a range of 2.0%, which is a great enhancement relative to the accuracy of prior art. Therefore, the accuracy of biomass blended-combustion ratio determination by means of the real-time online detection and analysis method involved in the present disclosure based on stable carbon isotope is high.
Examples 8 and 9 of the present disclosure relate to co-combustion of Shanxi coal simultaneously blended with two types of biomass including cotton stalks and sawdust; by modulating the blended-combustion ratio (0 to 30%, equally shared by the two types of biomass, abscissas) of the two types of biomass, the carbon isotope °C value (ordinates) of the blended flue gas is obtained by means of carbon isotope laser detection apparatus, thereby obtaining the goodness-of-fit of the linear regression equation, namely, R*>0.99; the total blended-combustion ratio of cotton stalks and sawdust was controlled to be 20%, the fitted linear relation obtained by modulating different ratios of the two was almost a straight line, and the error analysis was within 2.0%, indicating that the carbon isotope 3!?C value (ordinates) of the blended flue gas is relevant to the total blending amount of the multiple (two or more) types of biomass, and 1s irrelevant to the blended-combustion ratio of each type of biomass.
Examples 12 and 13 of the present disclosure relate to co-combustion of different blended-combustion ratios of corn stalks respectively with different coal samples (Guizhou coal,
Inner Mongolia coal), the obtained goodness-of-fit of the linear relationship was R*>0.99, indicating that this real-time online monitoring system and the analysis method thereof are applicable to the co-combustion of a single biomass and different coal samples. Based on these examples, the present disclosure is applicable to the co-combustion detection of multiple types of coal and multiple types of biomass, and is limited little by the type of raw materials. Table 1 is a physical and chemical parameter table of coal and biomass.
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EMBODIMENTS
1. A system for online monitoring of biomass blended-combustion ratio based on stable carbon isotopes, comprising: a flue gas online sampling channel, a condenser, a filter, a back pressure valve, and a carbon isotope mid-infrared laser detector. 2. The system for online monitoring of biomass blended-combustion ratio based on stable carbon isotopes according to claim 1, wherein: the carbon isotope mid-infrared laser detector mainly comprises a quantum cascade laser, a hollow waveguide and a mid-infrared laser detector, the hollow waveguide comprising a multichannel optical path, a laser inlet, and a gas inlet/outlet; the blended flue gas enters the multichannel optical path system in the hollow waveguide through the gas inlet, the quantum cascade laser emits mid-infrared laser in the spectrum, and the mid-infrared laser passes through the hollow waveguide and interacts with the carbon dioxide gas molecules therein, wherein the infrared laser is absorbed by carbon dioxide gas molecules according to Lambert Beer’s law, and the absorption spectrum receives signals via the detector, thereby measuring the absorption value of the carbon isotopes; the carbon isotope mid-infrared laser detector can measure multiple spectral absorption peaks by measuring the absorption spectrum, and the two main absorption peaks are the CO: absorption peak on the left and the 12C0; absorption peak on the right; when the isotope ratio §*C (3C/2C} contained in the carbon dioxide gas is obtained from the absorption peak area, the isotope value can be given in real time; the carbon isotope mid-infrared laser detector is an analyzer that accurately measures the carbon element content and stable isotope values (C/C) in various carbon-containing components, and can simultaneously detect CO: and CO: stable carbon isotope values, the detection error of this apparatus being only ++0.025%0. 3. A biomass blended-combustion ratio online monitoring method based on stable carbon isotopes by using the system according to claim 1 or 2, wherein: (1) the flue gas taken online from a coal and biomass co-combustion boiler is a blended gas of CO; and CO, and is introduced into the carbon isotope mid-infrared laser detector for stable carbon isotope analysis, the stable carbon isotope mid-infrared laser detector being capable of directly testing the carbon isotope ratio 8C (1*C/!*C) of the blended flue gas, and 8'*C values of different coal samples are significantly different from that of different biomass; and (2) according to the differences in °C values, a linear regression equation is obtained after correction by using carbon content of coal and biomass, and can be used to calculate the biomass blended-combustion ratio in the co-combustion substances: y=ax+b (1) } {Cr—Caixe ts 2): in formula (1), y is the 8!°C value displayed by the carbon isotope laser detection apparatus, and x is the biomass blended-combustion ratio corrected by using carbon content, wherein the influences of moisture, ash, volatile matter and other interference factors can be excluded after correction by using carbon content, « is the slope of the linear regression equation obtained by co-combustion of different types of coal with different biomass ratios, and #4 is the §!°C value of a coal sample; in formula (2), » is the biomass blended-combustion ratio without correction by using carbon content, Cc is the carbon content of the coal sample, and Cs is the biomass carbon content. 4. The biomass blended-combustion ratio online monitoring method based on stable carbon isotopes according to claim 3, wherein: the stable carbon isotope mid-infrared laser detection apparatus can directly test the carbon isotope ratio ô5C of the blended flue gas, 8/°C values of different coal samples are significantly different from that of different biomass, and a linear regression equation can be obtained after correction by using calorific values of coal and biomass, so as to be used to determine the biomass blended-combustion ratio: yv=a;x;+b (3) fi == mss
To @o-feiner+Qn (4); in formula (3), y is the "°C value displayed by the carbon isotope laser detection apparatus, xy is the biomass blended-combustion ratio corrected by using calorific value, a; is the slope of the linear regression equation obtained by co-combustion of different types of coal with different biomass ratios, and & is the 85C value of a coal sample, wherein the influences of moisture, ash, volatile matter and other interference factors can be excluded after correction by using calorific value; in formula (4), #; is the biomass blended-combustion ratio without correction by using calorific value, (Jc is the calorific value of the coal sample, and Oz is the biomass calorific value. 5. The biomass blended-combustion ratio online monitoring method based on stable carbon isotopes according to claim 4, wherein: the error of the stable carbon isotope online detection apparatus is only £0.025%, the linear regression equation has a goodness-of-fit of R2>0.99, and the test error range for biomass blended-combustion ratio is controlled to be within 2.0%.

Claims (5)

ConclusiesConclusions 1. Een systeem voor het online bewaken van biomassa gemengde verbrandingsverhouding voor stabiele koolstofisotopen, omvattende: een rookgas onlinebemonsteringskanaal, een condensor, een filter, een terugdrukklep, en een koolstofisotoop mid-infrarood laserdetector.A system for on-line monitoring of biomass mixed combustion ratio for stable carbon isotopes, comprising: a flue gas on-line sampling channel, a condenser, a filter, a check valve, and a carbon isotope mid-infrared laser detector. 2. Het systeem voor het online bewaken van biomassa gemengde verbrandingsverhouding voor stabiele koolstofisotopen volgens conclusie 1, waarbij: de koolstofisotoop mid-infrarood laserdetector hoofdzakelijk een kwantum cascade laser, een holle golfgeleider en een mid- infrarood lasterdetector omvat, waarbij de holle golfgeleider een multi-kanaal optisch pad, een laserinlaat, en een gasinlaat/uitlaat omvat; het gemengde rookgas komt binnen in het multi-kanaal optisch padsysteem in de holle golfgeleider door de gasinlaat, de kwantum cascade laser zendt mid-infrarood laser uit in het spectrum, en de mid-infrarood laser gaat door de holle golfgeleider heen en reageert met de koolstofdioxidegasmoleculen daarin, waarbij de infrarood laster geabsorbeerd wordt door koolstofdioxidegasmoleculen volgens de wet van Lambert Beer, en het absorptiespectrum signalen ontvangt via de detector, op die manier de absorptiewaarde van de koolstofisotopen metend; de koolstofisotoop mid-infrarood laser detector kan meerdere spectrale absorptiepieken meten door het absorptiespectrum te meten, en de twee grootste absorptiepieken zijn de CO; absorptiepiek links en de *CO» absorptiepiek rechts; wanneer de isotoopverhouding 87°C (13C/12C) omvat in het koolstofdioxidegas verkregen is uit het absorptiepiekgebied, kan de isotoopwaarde in real time weergegeven worden; de koolstofisotoop mid-infrarood laser detector is een analyzer die de inhoud van het koolstofelement en stabiele isotoopwaarden (12C/!3C) in verschillende koolstof bevattende componenten accuraat meet, en kan tegelijkertijd 2CO2 en CO: stabiele koolstofisotoopwaarden detecteren, waarbij de detectiefoutenmarge van dit apparaat enkel +0,025%0 is.The system for online monitoring of biomass mixed combustion ratio for stable carbon isotopes according to claim 1, wherein: the carbon isotope mid-infrared laser detector mainly comprises a quantum cascade laser, a hollow waveguide, and a mid-infrared laser detector, wherein the hollow waveguide is a multi channel includes optical path, a laser inlet, and a gas inlet/outlet; the mixed flue gas enters the multi-channel optical path system in the hollow waveguide through the gas inlet, the quantum cascade laser emits mid-infrared laser in the spectrum, and the mid-infrared laser passes through the hollow waveguide and reacts with the carbon dioxide gas molecules therein, wherein the infrared laser is absorbed by carbon dioxide gas molecules according to Lambert Beer's law, and the absorption spectrum receives signals through the detector, thus measuring the absorption value of the carbon isotopes; the carbon isotope mid-infrared laser detector can measure multiple spectral absorption peaks by measuring the absorption spectrum, and the two largest absorption peaks are the CO; absorption peak on the left and the *CO» absorption peak on the right; when the isotope ratio includes 87°C (13C/12C) in the carbon dioxide gas obtained from the absorption peak region, the isotope value can be displayed in real time; The carbon isotope mid-infrared laser detector is an analyzer that accurately measures the carbon element content and stable isotope values (12C/!3C) in various carbon-containing components, and can detect 2CO2 and CO: stable carbon isotope values at the same time, with the detection error margin of this device is only +0.025%0. 3. Een onlinebewakingswerkwijze voor biomassa gemengde verbrandingsverhouding gebaseerd op stabiele koolstofisotopen door het systeem volgens conclusie 1 of 2 te gebruiken, waarbij: (1) het rookgas online genomen van een kool en biomassa verbrandingsboiler een gemengd gas is van !2CO: en !3CO2, en geïntroduceerd is in de koolstofisotoop mid-infrarood laser detector voor stabiele koolstofisotoopanalyse, de stabiele koolstofisotoop mid-infrarood laser detector in staat zijnde om de koolstofisotoopverhouding 313C (**C/"C) van het gemengde rookgas direct te testen, en 6'°C waarden van verschillende koolmonsters significant verschillen van die van andere biomassa; en (2) volgens de verschillen in §'°C waarden, een lineaire regressievergelijking verkregen na correctie door de koolstofinhoud van kool en biomassa, en gebruikt kan worden om de biomassa gemengde verbrandingsverhouding in de co- verbrandingsmaterialen te berekenen: v=ax+b (1) LLC TLEISNSTLE (2): in formule (1) is y de 8!*C waarde getoond door het koolstofisotoop laster detectieapparaat, en is x de biomassa gemengde verbrandingsverhouding gecorrigeerd door de koolstofinhoud te gebruiken, waarbij de invloeden van vochtigheid, as, volatiele materialen en andere interfererende factoren uitgezonderd kunnen worden na correctie door koolstofinhoud te gebruiken, is a de helling van de lineaire regressievergelijking verkregen door co-verbranding van verschillende types kool met verschillende biomassaverhoudingen, en is b de 3!C waarde van een koolmonster; in formule (2) is » de biomassa gemengde verbrandingsverhouding zonder correctie door koolstofinhoud te gebruiken, is Cc de koolstofinhoud van het koolmonster, en is Cz de biomassa koolstofinhoud.A biomass mixed combustion ratio online monitoring method based on stable carbon isotopes by using the system of claim 1 or 2, wherein: (1) the flue gas taken online from a coal and biomass combustion boiler is a mixed gas of !2CO: and !3CO2, and introduced in the carbon isotope mid-infrared laser detector for stable carbon isotope analysis, the stable carbon isotope mid-infrared laser detector capable of directly testing the carbon isotope ratio 313C (**C/"C) of the mixed flue gas, and 6'° C values of different coal samples are significantly different from those of other biomass; and (2) according to the differences in §'°C values, a linear regression equation obtained after correction by the carbon content of coal and biomass, and can be used to determine the biomass mixed combustion ratio in the co-combustion materials to be calculated: v=ax+b (1) LLC TLEISNSTLE (2): In formula (1), y is the 8!*C value shown by the carbon isotope slander detection device, and x is the biomass mixed combustion ratio corrected using the carbon content, excluding the influences of humidity, ash, volatile materials and other interfering factors after correction by using carbon content, a is the slope of the linear regression equation obtained by co-burning different types of coal with different biomass ratios , and b is the 3!C value of a carbon sample; in formula (2) » is the biomass mixed combustion ratio without correction by using carbon content, Cc is the carbon content of the sample coal, and Cz is the biomass carbon content. 4. De onlinebewakingswerkwijze voor biomassa gemengde verbrandingsverhouding gebaseerd op stabiele koolstofisotopen volgens conclusie 3, waarbij: het stabiele koolstofisotoop mid-infrarood laser detectieapparaat de koolstofisotoopverhouding $C van het gemengde rookgas direct kan detecteren, 8!3C waardes van verschillende koolmonsters significant anders zijn van die van andere biomassa, en een lineaire regressievergelijking kan worden verkregen na correctie door de calorische waarden van kool en biomassa te gebruiken, zodat die gebruikt kunnen worden om de biomassa gemengde verbrandingsverhouding te bepalen: yv=apx;+b (3) in formule (3) is y de §"*C waarde getoond door het koolstofisotoop laser detectieapparaat, is x; de biomassa gemengde verbrandingsverhouding gecorrigeerd door calorische waarde te 60 gebruiken, is a; de helling van de lineaire regressievergelijking verkregen door co-verbranding van verschillende types kool met andere biomassaverhoudingen, en is ó de §°C waarde van een koolmonster, waarbij de invloeden van vochtigheid, as, volatiele materialen en andere interfererende factoren uitgezonderd kunnen worden na correctie door de calorische waarde te gebruiken; in formule (4) is r; de biomassa gemengde verbrandingsverhouding zonder correctie 65 door calorische waarde te gebruiken, is Oc de calorische waarde van het koolmonster, en is Os de biomassa calorische waarde.The on-line monitoring method for biomass mixed combustion ratio based on stable carbon isotopes according to claim 3, wherein: the stable carbon isotope mid-infrared laser detecting device can directly detect the carbon isotope ratio σC of the mixed flue gas, 8·3C values of different carbon samples are significantly different from those from other biomass, and a linear regression equation can be obtained after correction by using the calorific values of coal and biomass so that they can be used to determine the biomass mixed combustion ratio: yv=apx;+b (3) in formula (3 ) y is the §"*C value shown by the carbon isotope laser detection device, is x; the biomass mixed combustion ratio corrected by using calorific value 60, is a; the slope of the linear regression equation obtained by co-combustion of different types of coal with other biomass ratios, and ó is the §°C value of a coal sample, where the influences of humidity, ash, volatile materials and other interfering factors can be excluded after correction by using the calorific value; in formula (4) r is; the biomass mixed combustion ratio without correction 65 by using calorific value, Oc is the calorific value of the coal sample, and Os is the biomass calorific value. 5. De onlinebewakingswerkwijze voor biomassa gemengde verbrandingsverhouding gebaseerd op stabiele koolstofisotopen volgens conclusie 4, waarbij: de foutenmarge van het 70 stabiele koolstofisotoop online detectieapparaat enkel +0,025% is, de lineaire regressievergelijking een goodness-of-fit van R?>0,99 heeft, en de testfoutenmarge voor biomassa gemengde verbrandingsverhouding gecontroleerd wordt zodat die binnen 2,0% blijft.The biomass mixed combustion ratio online monitoring method based on stable carbon isotopes according to claim 4, wherein: the error rate of the 70 stable carbon isotope online detection device is only +0.025%, the linear regression equation has a goodness-of-fit of R?>0.99 , and the test error rate for biomass mixed combustion ratio is controlled to remain within 2.0%.
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