Method and system for calculating carbon content based on intelligent coal quality parameters

Abstract

The invention discloses a carbon content calculation method and system based on intelligent coal quality parameters. The method comprises the following steps: acquiring batch coal samples from the same mining area or with stable coal quality characteristics; determining the air-dry-basis ash content and the air-dry-basis carbon content of a plurality of samples in the batch of coal samples by adopting a standard method; performing linear regression analysis on the measured data of the air-dry basis ash content and the air-dry basis carbon content, and establishing a linear relational expression between the air-dry basis carbon content and the air-dry basis ash content; determining the air-dry basis ash content of the similar coal samples to be detected; and substituting the measured air-dry basis ash content into the obtained linear relational expression, and calculating to obtain the air-dry basis carbon content of the coal sample to be measured. According to the method, the linear relation between the air dry basis ash content and the carbon content of the coal is established, so that the carbon content can be calculated only by measuring the ash content. The detection process is simplified, the cost and time for measuring the carbon content are remarkably reduced, and the technical problems in frequent detection and long-term carbon emission accounting are solved.

Description

Technical Field

[0001] This invention relates to the field of coal carbon content determination technology, and in particular to a method and system for calculating carbon content using intelligent coal quality parameters. Background Technology

[0002] Currently, instruments conforming to national and international standards can accurately determine the moisture, ash, and carbon content of coal. However, these methods require independent measurements and separate operations, resulting in low efficiency and high costs. Carbon content measurement is particularly frequent in coal quality testing and carbon emission calculations, necessitating the merging of multiple batches of coal samples into a monthly total sample for testing. This is not only time-consuming but also increases economic costs. Furthermore, the process of further refining and merging multiple batches of coal samples makes it difficult to accurately determine the sample quantities according to batch weight and combine them into a total sample to detect carbon content over monthly or longer periods. This carries the risk of sample distortion and fails to accurately reflect actual coal consumption. Therefore, there is an urgent need for a new technology to replace traditional measurement methods, simplifying the process and reducing costs. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the existing technology. To achieve the above objective, an intelligent coal quality parameter carbon content calculation method and system are adopted to solve the problems mentioned in the background technology.

[0004] A method for calculating carbon content from intelligent coal quality parameters includes the following steps: S1. Obtain batches of coal samples from the same mining area or with stable coal quality characteristics; S2. The air-dried basis moisture, air-dried basis ash and air-dried basis carbon content of multiple samples in the batch of coal samples are determined by standard methods, and the dry basis ash and dry basis carbon content are calculated by coal benchmark conversion formula. S3. Perform linear regression analysis on the multiple sets of air-dried basis ash or dry basis ash and air-dried basis carbon content or dry basis carbon content measured in step S2, and establish a linear relationship between air-dried basis carbon content or dry basis carbon content and air-dried basis ash or dry basis ash. S4. For the same type of coal sample to be tested, determine its air-dried ash content and air-dried moisture content, and calculate the dry-basis ash content. S5. Substitute the obtained air-dry basis ash content or dry basis ash content into the linear relationship obtained in step S3 to calculate the air-dry basis carbon content or dry basis carbon content of the coal sample to be tested.

[0005] As a further aspect of the present invention, the correlation coefficient of the linear relationship in step S3 is required to be no less than 0.95.

[0006] As a further aspect of the present invention: in step S5, the difference between the calculated air-dried carbon content and the air-dried carbon content measured by the standard method satisfies the reproducibility critical difference requirement for carbon content determination.

[0007] As a further aspect of the present invention, the reproducibility critical difference is less than 1.3%.

[0008] As a further aspect of the present invention: the determination of air-dried or received ash content in step S4 is performed online or offline using spectral analysis technology.

[0009] As a further aspect of the present invention: when the carbon content of coal samples from the same source is frequently tested, frequent carbon content data is obtained by frequently measuring and calculating the ash content.

[0010] As a further aspect of the present invention: when calculating the comprehensive carbon content over a specific time period, the specific steps include: Within the specified time period, coal samples were collected at time intervals and their air-dried basis ash content or received basis ash content, air-dried basis moisture content, and total moisture content were measured. The air-dried basis ash content or received basis ash content was calculated from the air-dried basis ash content or received basis ash content using the reference conversion formula. Dry basis ash content = Air-dry basis ash content 100 / (100 - air-dried basis moisture); Dry basis ash content = Ash content received on basis 100 / (100 - total water); The dry basis carbon content of each coal sample is calculated based on the linear relationship, and the received basis carbon content is calculated from the dry basis carbon content using the benchmark conversion formula. Received carbon content = Dry carbon content (100 - total water) / 100.

[0011] Based on the coal input corresponding to each time interval, the calculated carbon content of each received base is weighted and averaged to obtain the comprehensive carbon content for the specific time period.

[0012] As a further aspect of the present invention: the specific time period is a month, a quarter, or a year.

[0013] As a further aspect of the present invention: when verifying the accuracy of coal sample measurement results, if the difference between the air-dried carbon content measured by the standard method and the air-dried carbon content calculated by the linear relationship exceeds the allowable error range, the measurement result is judged to be abnormal.

[0014] The second aspect of the technical solution: A carbon emission accounting system that uses an intelligent coal quality parameter calculation method as described in any of the above claims to calculate carbon content, comprising: The data acquisition module is used to acquire batches of coal samples from the same mining area or with stable coal quality characteristics; The data processing and model management module is used to perform linear regression analysis on the data of air-dry basis ash or dry basis ash and air-dry basis carbon content or dry basis carbon content of multiple samples in the batch of coal samples using standard methods, and to establish a linear relationship between air-dry basis carbon content or dry basis carbon content and air-dry basis ash or dry basis ash content. The core calculation module is used to determine the air-dry basis ash content or dry basis ash content of the same type of coal sample to be tested; by substituting the measured air-dry basis ash content or dry basis ash content into the obtained linear relationship, the air-dry basis carbon content or dry basis carbon content of the coal sample to be tested is calculated.

[0015] Compared with the prior art, the present invention has the following technical advantages: By employing the above technical solution, multiple sets of air-dried basis ash and carbon content data are obtained through standard measurements of specific batches of coal samples. These data are then used to establish a quantitative relationship between ash and carbon content through linear regression analysis. For routine testing of coal samples from the same source, there is no need to directly measure carbon content using complex and expensive instruments. Only the air-dried basis ash (or received basis ash) and moisture content need to be measured. The corresponding air-dried basis carbon content (or dry basis carbon content) can then be quickly and accurately calculated using this pre-established relationship. This eliminates the need for separate carbon content measurement, significantly reducing reliance on and frequency of use of high-cost carbon content analysis instruments in the testing process. While greatly saving equipment, manpower, and time costs, it also improves testing efficiency and provides a feasible technical path for achieving rapid online carbon content detection and accurate long-term carbon emission accounting. Attached Figure Description

[0016] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings: Figure 1 This is a schematic diagram illustrating the steps of the calculation method according to an embodiment of this application. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Please refer to Figure 1 In this embodiment of the invention, a method for calculating carbon content using intelligent coal quality parameters includes the following steps: S1. Obtain batches of coal samples from the same mining area or with stable coal quality characteristics; S2. The air-dried basis moisture, air-dried basis ash and air-dried basis carbon content of multiple samples in the batch of coal samples are determined by standard methods, and the dry basis ash and dry basis carbon content are calculated by coal benchmark conversion formula. S3. Perform linear regression analysis on the multiple sets of air-dried basis ash or dry basis ash and air-dried basis carbon content or dry basis carbon content measured in step S2, and establish a linear relationship between air-dried basis carbon content or dry basis carbon content and air-dried basis ash or dry basis ash. The correlation coefficient of the linear relationship in step S3 must be no less than 0.95.

[0019] S4. For the same type of coal sample to be tested, determine its air-dried ash content and air-dried moisture content, and calculate the dry-basis ash content. S5. Substitute the obtained air-dry basis ash content or dry basis ash content into the linear relationship obtained in step S3 to calculate the air-dry basis carbon content or dry basis carbon content of the coal sample to be tested.

[0020] In this embodiment, in step S5, the difference between the calculated air-dried carbon content and the air-dried carbon content measured by the standard method meets the reproducibility critical difference requirement for carbon content determination.

[0021] In this embodiment, the reproducibility critical difference is less than 1.3%.

[0022] Specifically, the air-dry basis ash content or dry basis ash content and air-dry basis carbon content or dry basis carbon content of coal are determined by standard methods. After data processing, the theoretical calculation formula between the two can be established as: Y=AX+B. Where Y represents the air-dried basis carbon content (or dry basis carbon content), and X represents the air-dried basis ash content (or dry basis ash content). Based on this formula, the carbon content can be calculated from the measured ash content, and the reproducibility critical difference between the calculated result and the measured value meets the requirements of the standard method (carbon content reproducibility critical difference less than 1.3%).

[0023] In this embodiment, the determination of air-dried ash and moisture content or received ash and total water content in step S4 is performed online or offline using spectroscopic analysis technology.

[0024] In this embodiment, when the carbon content of coal samples from the same source is frequently tested, frequent carbon content data is obtained by frequently measuring ash content and calculating it.

[0025] In this embodiment, the specific steps for calculating the overall carbon content over a specific time period include: Within the specified time period, coal samples were collected at time intervals and their air-dried basis ash content or received basis ash content, air-dried basis moisture content, and total moisture content were measured. The air-dried basis ash content or received basis ash content was calculated from the air-dried basis ash content or received basis ash content using the reference conversion formula. Note: Dry basis ash content = Air basis ash content 100 / (100 - moisture content on dry basis), ash content on dry basis = ash content on received basis 100 / (100-total water).

[0026] The dry basis carbon content of each coal sample is calculated based on the linear relationship, and the received basis carbon content is calculated from the dry basis carbon content using the benchmark conversion formula. Note: Carbon content on received basis = Carbon content on dry basis (100 - total water) / 100.

[0027] Based on the coal input corresponding to each time interval, the calculated carbon content of each received base is weighted and averaged to obtain the comprehensive carbon content for the specific time period.

[0028] In this embodiment, the specific time period is a month, quarter, or year.

[0029] In this embodiment, when verifying the accuracy of the coal sample measurement results, if the difference between the air-dried carbon content measured by the standard method and the air-dried carbon content calculated by the linear relationship exceeds the allowable error range, the measurement result is judged to be abnormal.

[0030] Specifically, by using a linear relationship, within a certain range of ash or carbon content, the constants A and B of this calculation formula can be obtained after the ash and carbon content of coal are measured in advance. In daily testing, only one of the ash or carbon content needs to be measured by an instrument to calculate the other data, which greatly saves equipment, energy, manpower and time resources.

[0031] By utilizing linear relationships and combining rapid moisture optical wave determination and ash spectral analysis techniques for online moisture and ash content determination, online carbon content detection can be achieved.

[0032] In carbon emission calculation and verification, measuring the carbon content of coal used every shift is too costly; monthly carbon content measurement involves sample reduction and merging, making it difficult to obtain accurate results, distorting sample representativeness, and requiring excessive sample retention, while also introducing significant uncontrollability in sample retention verification testing. By utilizing a linear relationship, the carbon content can be calculated from the ash content of coal measured each shift. Then, by using the weight of the coal consumption per shift, the carbon content of coal used monthly, quarterly, or annually can be accurately calculated, making carbon emission calculation more scientific and effective.

[0033] Example 1 Linear regression analysis was performed on the air-dry basis carbon content and ash content of 200 chemical raw material coals and their multi-element blended coal samples to obtain the corresponding theoretical calculation formula: Y1 = 74.69 - 0.566X1, where Y1 is the air-dry basis carbon content and X1 is the air-dry basis ash content, with a correlation coefficient of 0.9653 between the carbon content and ash content data. Simultaneously, linear regression analysis was performed on the corresponding dry basis carbon content and ash content data to obtain the corresponding theoretical calculation formula: Y2 = 78.16 - 0.654X2, where Y2 is the dry basis carbon content and X2 is the dry basis ash content, with a correlation coefficient of 0.9634 between the carbon content and ash content data. The difference between the calculated and measured carbon content values ​​both meet the requirement that the reproducibility critical error of the carbon content determination method is less than 1.3%. The applicable range for coal sample carbon content values ​​is 59.00% to 72.95%, as shown in the table below.

[0034] Example 2 This laboratory obtained the theoretical calculation formula by linear regression analysis of the air-dry basis carbon content and ash content of 100 samples of coal delivered to the power plant and furnace, based on air-dry basis measurements and data processing: Y1 = 97.12 - 1.31X1, where Y1 is the air-dry basis carbon content and X1 is the air-dry basis ash content. The correlation coefficient between carbon content and ash content data was 0.9889. Simultaneously, the corresponding dry basis carbon content and dry basis ash content data were calculated and linearly regressed to obtain the theoretical calculation formula: Y2 = 98.33 - 1.31X2, where Y2 is the dry basis carbon content and X2 is the dry basis ash content. The correlation coefficient between carbon content and ash content data was 0.9780. The difference between the calculated and actual measured carbon content values ​​both met the requirement that the reproducibility critical error of the carbon content determination method be less than 1.3%, and the carbon content values ​​of the coal samples ranged from 50.00% to 62.00%. See the table below:

[0035] Example 3 The calculation of overall carbon content over a specific period is typically done monthly, quarterly, or annually. Here, we'll use a week as an example to calculate the weekly average carbon content, as shown in the table below:

[0036] The second aspect of the technical solution: A carbon emission accounting system that uses an intelligent coal quality parameter calculation method as described in any of the above claims to calculate carbon content, comprising: The data acquisition module is used to acquire batches of coal samples from the same mining area or with stable coal quality characteristics; The data processing and model management module is used to perform linear regression analysis on the data of air-dry basis ash or dry basis ash and air-dry basis carbon content or dry basis carbon content of multiple samples in the batch of coal samples using standard methods, and to establish a linear relationship between air-dry basis carbon content or dry basis carbon content and air-dry basis ash or dry basis ash content. The core calculation module is used to determine the air-dry basis ash content or dry basis ash content of the same type of coal sample to be tested; by substituting the measured air-dry basis ash content or dry basis ash content into the obtained linear relationship, the air-dry basis carbon content or dry basis carbon content of the coal sample to be tested is calculated.

[0037] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention. The scope of the invention is defined by the appended claims and their equivalents, all of which should be included within the scope of protection of the invention.

Claims

1. A method for calculating carbon content from intelligent coal quality parameters, characterized in that, Includes the following steps: S1. Obtain batches of coal samples from the same mining area or with stable coal quality characteristics; S2. The air-dried basis moisture, air-dried basis ash, and air-dried basis carbon content of multiple samples in the batch of coal samples were determined using standard methods. The dry basis ash and dry basis carbon content were calculated using the coal reference conversion formula. S3. Perform linear regression analysis on the multiple sets of air-dried basis ash or dry basis ash and air-dried basis carbon content or dry basis carbon content measured in step S2, and establish a linear relationship between air-dried basis carbon content or dry basis carbon content and air-dried basis ash or dry basis ash. S4. For the same type of coal sample to be tested, determine its air-dried ash content and air-dried moisture content, and calculate the dry-basis ash content. S5. Substitute the obtained air-dry basis ash content or dry basis ash content into the linear relationship obtained in step S3 to calculate the air-dry basis carbon content or dry basis carbon content of the coal sample to be tested.

2. The method for calculating carbon content using intelligent coal quality parameters according to claim 1, characterized in that, The correlation coefficient of the linear relationship in step S3 is required to be no less than 0.

95.

3. The method for calculating carbon content based on intelligent coal quality parameters according to claim 1, characterized in that, In step S5, the difference between the calculated air-dried carbon content and the air-dried carbon content measured using the standard method meets the reproducibility critical difference requirement for carbon content determination.

4. The method for calculating carbon content using intelligent coal quality parameters according to claim 3, characterized in that, The reproducibility critical difference is less than 1.3%.

5. The method for calculating carbon content using intelligent coal quality parameters according to claim 1, characterized in that, In step S4, the determination of air-dried or received ash content is performed online or offline using spectral analysis techniques.

6. The method for calculating carbon content based on intelligent coal quality parameters according to claim 1, characterized in that, When the carbon content of coal samples from the same source is frequently tested, frequent carbon content data are obtained by frequently measuring ash content and calculating it.

7. The method for calculating carbon content based on intelligent coal quality parameters according to claim 1, characterized in that, When calculating the overall carbon content over a specific time period, the specific steps include: Within the specified time period, coal samples were collected at time intervals and their air-dried basis ash content or received basis ash content, air-dried basis moisture content, and total moisture content were measured. The air-dried basis ash content or received basis ash content was calculated from the air-dried basis ash content or received basis ash content using the reference conversion formula. Dry basis ash content = Air-dry basis ash content 100 / (100 - air-dried basis moisture); Dry basis ash content = Ash content received on basis 100 / (100 - total water); The dry basis carbon content of each coal sample is calculated based on the linear relationship, and then the received basis carbon content is calculated from the dry basis carbon content using the benchmark conversion formula. Received carbon content = Dry carbon content (100 - total water) / 100; Based on the coal input corresponding to each time interval, the calculated carbon content of each received base is weighted and averaged to obtain the comprehensive carbon content for the specific time period.

8. The method for calculating carbon content using intelligent coal quality parameters according to claim 7, characterized in that, The specific time period is a month, quarter, or year.

9. The method for calculating carbon content using intelligent coal quality parameters according to claim 1, characterized in that, To verify the accuracy of coal sample test results, if the difference between the air-dried carbon content measured by the standard method and the air-dried carbon content calculated by the linear relationship exceeds the allowable error range, the test results are judged to be abnormal.

10. A carbon emission accounting system that uses a method for calculating carbon content based on intelligent coal quality parameters as described in any one of claims 1 to 9, characterized in that, include: The data acquisition module is used to acquire batches of coal samples from the same mining area or with stable coal quality characteristics; The data processing and model management module is used to perform linear regression analysis on the data of air-dry basis ash or dry basis ash and air-dry basis carbon content or dry basis carbon content of multiple samples in the batch of coal samples using standard methods, and to establish a linear relationship between air-dry basis carbon content or dry basis carbon content and air-dry basis ash or dry basis ash content. The core calculation module is used to determine the air-dry basis ash content or dry basis ash content of the same type of coal sample to be tested; by substituting the measured air-dry basis ash content or dry basis ash content into the obtained linear relationship, the air-dry basis carbon content or dry basis carbon content of the coal sample to be tested is calculated.

Images