A method and system for intelligent detection of carbon, hydrogen and nitrogen in coal for coal quality detection

Abstract

The present application provides a kind of carbon hydrogen nitrogen intelligent detection method and system for coal quality detection in coal, comprising: respectively to each to-be-tested coal sample combustion detection, determine the corresponding coal quality data of each to-be-tested coal sample, according to coal quality data, the carbon hydrogen nitrogen content ratio corresponding to each to-be-tested coal sample is evaluated, corresponding spectrum irradiation scheme is retrieved, according to the light emission task of spectrum irradiation scheme, after the to-be-tested coal sample is combusted, infrared absorption analysis is carried out, the element concentration corresponding to different elements in each to-be-tested coal sample is obtained, the element composition list is constructed, the coal quality report corresponding to each to-be-tested coal sample is generated according to the coal quality data and element composition list corresponding to each to-be-tested coal sample, by sampling coal, then by the means of combustion and spectrum to detect the content of each element in coal, so that the eligibility of coal can be determined quickly, effectively avoid unqualified coal into market.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of coal energy detection, and particularly relates to a coal carbon hydrogen nitrogen intelligent detection method and system for coal quality detection. BACKGROUND

[0002] Coal is a mineral formed from plant debris through geological processes over millions of years. It is an organic substance with high carbon content and rich heat value, widely used in industrial production and energy production. Coal plays an important role in the energy field. It is widely used in power generation, steel production, chemical industry, etc. However, over time, people gradually realize the impact of pollution and greenhouse gases produced by coal combustion on the environment and human health. Therefore, there is a demand for clean energy worldwide to reduce dependence on fossil fuels such as coal. Despite this, coal remains one of the main sources of energy in some countries. In these regions, the demand for coal is still great, but also faces challenges such as environmental and climate change. Therefore, how to allow qualified coal to enter the market to balance the relationship between the use of coal and environmental protection has become an important issue

[0003] Therefore, the present application provides a coal carbon hydrogen nitrogen intelligent detection method and system for coal quality detection. SUMMARY

[0004] The present application provides a coal carbon hydrogen nitrogen intelligent detection method and system for coal quality detection, which can quickly determine the qualification of coal by sampling coal and detecting the content of each element in coal through combustion and spectral means, effectively avoiding unqualified coal flowing into the market.

[0005] The present application provides a coal carbon hydrogen nitrogen intelligent detection method for coal quality detection, comprising:

[0006] Step 1: respectively burning each coal sample to be tested, and determining the coal quality data corresponding to each coal sample to be tested according to the combustion detection results;

[0007] Step 2: evaluating the carbon hydrogen nitrogen content ratio corresponding to each coal sample to be tested according to the coal quality data, and retrieving the corresponding spectral irradiation scheme according to the carbon hydrogen nitrogen content ratio;

[0008] Step 3: performing the light emission task according to the spectral irradiation scheme, and performing infrared absorption analysis on the coal sample to be tested after combustion to obtain the element concentration corresponding to different elements in each coal sample to be tested, and constructing an element composition list;

[0009] Step 4: generating a coal quality report corresponding to each coal sample to be tested according to the coal quality data and the element composition list corresponding to each coal sample to be tested.

[0010] In an implementable mode,

[0011] The step 1 comprises:

[0012] Step 11: sampling the coal to be tested to obtain a plurality of coal samples to be tested, and recording the sampling information corresponding to each of the coal samples to be tested respectively;

[0013] Step 12: respectively detecting the combustion of each of the coal samples to be tested, and respectively determining the low calorific value and the high calorific value of each of the coal samples to be tested during the combustion process to obtain the low calorific value and the high calorific value corresponding to each of the coal samples to be tested;

[0014] Step 13: respectively analyzing the ash content of each of the coal samples to be tested after the combustion is completed to obtain the ash content and the ash melting amount corresponding to each of the coal samples to be tested;

[0015] Step 14: establishing the coal quality data of the corresponding coal sample to be tested according to the sampling information, the low calorific value, the high calorific value, the ash content and the ash melting amount corresponding to each of the coal samples to be tested.

[0016] In an implementable mode,

[0017] The step 2 comprises:

[0018] Step 21: obtaining the combustion environment information corresponding to the combustion detection, combining the coal quality data to establish the combustion characteristics of each of the coal samples to be tested under different combustion temperatures, obtaining the coal combustion curve corresponding to each of the coal samples to be tested, and determining the coal residue information of each of the coal samples to be tested;

[0019] Step 22: determining the combustion amount of the corresponding coal sample to be tested according to the coal residue information, determining the coal quality of the corresponding coal sample to be tested according to the combustion amount, positioning the curve point corresponding to the preset sufficient combustion temperature in each of the coal combustion curves, taking the curve point as a mapping starting point, and respectively mapping each of the coal combustion curves into the same display space;

[0020] Step 23: obtaining the curve difference information between each of the different coal combustion curves in the display space, constructing the sample accidental characteristics of the corresponding coal sample to be tested according to the curve difference information, adjusting the corresponding coal combustion curve by using the sample accidental characteristics, and counting a plurality of adjustment positions corresponding to each of the coal combustion curves and the adjustment amount corresponding to each of the adjustment positions;

[0021] Step 24: establishing the carbon-hydrogen-nitrogen content ratio of the corresponding coal sample to be tested according to the oxygen consumption corresponding to each of the adjustment positions and the adjustment amount corresponding to each of the adjustment positions, adjusting the emission rule of the preset spectrum according to the carbon-hydrogen-nitrogen content ratio, and generating a spectrum irradiation scheme.

[0022] In an implementable mode,

[0023] The step 3 comprises:

[0024] Step 31: controlling the corresponding emission device to perform the emission light task according to the spectral irradiation scheme, and determining a plurality of emission lights contained in the emission light task according to the spectral irradiation scheme, and respectively acquiring a detection direction corresponding to each emission light;

[0025] Step 32: respectively acquiring a corresponding presentation feature of each burned coal sample under different detection directions, and determining the carbon element concentration contained in each coal sample according to the presentation feature;

[0026] Step 33: determining the hydrogen element concentration range value and the nitrogen element concentration range value in each coal sample according to the carbon-hydrogen-nitrogen content ratio, and performing numerical correction on the corresponding presentation feature, the corresponding element concentration range value and the nitrogen element concentration range value of each coal sample to obtain the hydrogen element concentration and the nitrogen element concentration contained in the corresponding coal sample;

[0027] Step 34: if the carbon element concentration error value, the nitrogen element concentration error value and the hydrogen element concentration error value between different coal samples are within the standard error value range, generating an element composition list.

[0028] In an implementable mode,

[0029] Further comprising:

[0030] If one or more of the carbon element concentration error value, the nitrogen element concentration error value and the hydrogen element concentration error value between different coal samples are not within the standard error value range, an abnormal concentration error value corresponding to the coal sample is acquired;

[0031] The abnormal element concentration corresponding to the abnormal concentration error is subjected to normal distribution analysis to obtain an abnormal coal sample with the highest dispersion degree;

[0032] Acquiring the sampling information corresponding to the coal sample, and determining the sampling position of the coal sample;

[0033] Supplementarily sampling the sampling position, and analyzing the obtained supplementarily sampled coal sample.

[0034] In an implementable mode,

[0035] Further comprising:

[0036] Before the combustion detection, an image of each coal sample corresponding to the coal sample is acquired;

[0037] Respectively, the texture analysis is performed on each of the coal sample images to obtain granularity information and color formation information corresponding to each of the to-be-tested coal samples;

[0038] After the combustion of the to-be-tested coal samples, the granularity information and the color formation information are supplemented into the sampling information.

[0039] In an implementable mode,

[0040] Further comprising:

[0041] Before the combustion detection, the corresponding grinding mode is called according to the granularity information;

[0042] The corresponding to-be-tested coal sample is ground and pretreated by using the grinding mode.

[0043] In an implementable mode,

[0044] The step 4 comprises:

[0045] Step 41: constructing a coal structure of each to-be-tested coal sample according to coal quality data and an element composition list corresponding to the to-be-tested coal sample;

[0046] Step 42: constructing a coal quality report according to the coal structure and combining with to-be-tested coal source information.

[0047] The present application provides a coal hydrogen and carbon nitrogen intelligent detection system for coal quality detection, comprising:

[0048] A combustion detection module is used for respectively performing combustion detection on each to-be-tested coal sample, and determining coal quality data corresponding to each of the to-be-tested coal samples according to the combustion detection result;

[0049] A light analysis module is used for evaluating carbon, hydrogen and nitrogen content ratios corresponding to each of the to-be-tested coal samples according to the coal quality data, and calling a corresponding spectrum irradiation scheme according to the carbon, hydrogen and nitrogen content ratios;

[0050] An element analysis module is used for performing an emission light task according to the spectrum irradiation scheme, performing infrared absorption analysis on the to-be-tested coal sample after combustion, obtaining element concentrations corresponding to different elements in each of the to-be-tested coal samples, and constructing an element composition list;

[0051] A report generation module is used for generating a coal quality report corresponding to each of the to-be-tested coal samples according to coal quality data and an element composition list corresponding to each of the to-be-tested coal samples.

[0052] In an implementable mode,

[0053] The combustion detection module comprises:

[0054] The first combustion detection unit is used for sampling the to-be-tested coal to obtain a plurality of to-be-tested coal samples, and sampling information corresponding to each to-be-tested coal sample is recorded respectively;

[0055] The second combustion detection unit is used for respectively performing combustion detection on each to-be-tested coal sample, performing calorific value determination on each to-be-tested coal sample in a combustion process, and obtaining low calorific value and high calorific value corresponding to each to-be-tested coal sample;

[0056] The third combustion detection unit is used for respectively performing ash content analysis on each to-be-tested coal sample after combustion, and obtaining impurity content and ash melting amount corresponding to each to-be-tested coal sample;

[0057] The fourth combustion detection unit is used for establishing coal quality data of the corresponding to-be-tested coal sample according to the sampling information, the low calorific value, the high calorific value, the impurity content and the ash melting amount corresponding to each to-be-tested coal sample

[0058] The beneficial effects that can be achieved by the present application are as follows: in order to analyze the to-be-tested coal, combustion detection is first performed on a plurality of to-be-tested coal samples, a plurality of coal quality data can be obtained, and then the carbon, hydrogen and nitrogen content ratio of each to-be-tested coal sample is evaluated according to the coal quality data, so that the corresponding spectral irradiation scheme is retrieved, so that different quality coals can be analyzed in detail, and the randomness of analysis is effectively reduced, then the spectral irradiation scheme is used to irradiate the coal residue after combustion, the element concentration of different elements in the to-be-tested coal sample is determined according to the absorption of the coal residue to different light, and an element composition list is constructed, and finally a coal quality report is generated, the coal quality detection is completed, and the user can judge whether the coal is qualified according to the report, and can timely process the unqualified coal.

[0059] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the present application. The objects and other advantages of the present application can be realized and achieved by the structure particularly pointed out in the written description, claims, and accompanying drawings.

[0060] The technical solutions of the present application will be further described in detail below with the help of the accompanying drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0061] The accompanying drawings are used to provide a further understanding of the present application, and constitute a part of the specification, together with the embodiments of the present application, to explain the present application, and do not constitute a limitation on the present application. In the drawings:

[0062] Figure 1 It is a work flow schematic diagram of a coal carbon hydrogen nitrogen intelligent detection method for coal quality detection in the embodiments of the present application;

[0063] Figure 2 Figure 1 is a schematic diagram of a coal carbon hydrogen nitrogen intelligent detection system for coal quality detection according to an embodiment of the present application. DETAILED DESCRIPTION

[0064] The preferred embodiments of the present application will be described herein below with reference to the accompanying drawings, in which it is understood that the preferred embodiments described herein are merely intended to illustrate and explain the present application, and are not intended to limit the present application.

[0065] Embodiment 1

[0066] The present embodiment provides a coal carbon hydrogen nitrogen intelligent detection system for coal quality detection, as shown in Figure 1, comprising: Figure 1

[0067] Step 1: respectively burning each coal sample to be tested, and determining the coal quality data corresponding to each coal sample to be tested according to the burning detection results;

[0068] Step 2: evaluating the carbon hydrogen nitrogen content ratio corresponding to each coal sample to be tested according to the coal quality data, and retrieving the corresponding spectrum irradiation scheme according to the carbon hydrogen nitrogen content ratio;

[0069] Step 3: performing the light emission task according to the spectrum irradiation scheme, and performing infrared absorption analysis on the coal sample to be tested after burning to obtain the element concentration corresponding to each element in each coal sample to be tested, and constructing an element composition list;

[0070] Step 4: generating a coal quality report corresponding to each coal sample to be tested according to the coal quality data and the element composition list corresponding to each coal sample to be tested.

[0071] In this example, the spectrum irradiation scheme represents the process of irradiating the coal sample to be tested with red light of different frequencies;

[0072] In this example, the coal quality data represents the quality of coal with specific data;

[0073] In this example, the carbon hydrogen nitrogen content ratio represents the content ratio between carbon, hydrogen and nitrogen elements contained in the coal sample to be tested;

[0074] In this example, the element concentration represents the content of each element in a coal sample to be tested.

[0075] ​The working principle and beneficial effects of the above technical solutions are as follows: in order to analyze the to-be-tested coal, a plurality of to-be-tested coal samples are subjected to combustion detection, a plurality of coal quality data can be obtained, and then the carbon-hydrogen-nitrogen content ratio of each to-be-tested coal sample is evaluated according to the coal quality data, so that the corresponding spectral irradiation scheme is retrieved, so that different quality coals can be analyzed in detail, and the randomness of analysis is effectively reduced, then the spectral irradiation scheme is used to irradiate the coal residue after combustion, the element concentration of different elements in the to-be-tested coal sample is determined according to the absorption of different light rays by the coal residue, so that an element composition list is constructed, and finally a coal quality report is generated, the coal quality detection is completed, and the user can judge whether the coal is qualified according to the report, and can timely process the unqualified coal.

[0076] Embodiment 2

[0077] Based on the embodiment 1, the step 1 comprises:

[0078] Step 11: sampling the to-be-tested coal to obtain a plurality of to-be-tested coal samples, and recording the sampling information corresponding to each to-be-tested coal sample;

[0079] Step 12: respectively detecting each to-be-tested coal sample, and respectively determining the calorific value of each to-be-tested coal sample in the combustion process to obtain the low calorific value and the high calorific value corresponding to each to-be-tested coal sample;

[0080] Step 13: respectively analyzing the ash content of each to-be-tested coal sample after combustion to obtain the impurity content and the ash melting amount corresponding to each to-be-tested coal sample;

[0081] Step 14: establishing the coal quality data of the corresponding to-be-tested coal sample according to the sampling information, the low calorific value, the high calorific value, the impurity content and the ash melting amount corresponding to each to-be-tested coal sample.

[0082] In this example, the low calorific value represents the heat released by the to-be-tested coal sample when completely combusted without considering the condensation heat of water vapor;

[0083] In this example, the high calorific value is usually greater than the low calorific value, and represents the heat released by the to-be-tested coal sample when completely combusted considering the condensation heat of water vapor;

[0084] In this example, the ash content represents the coal residue after combustion of the to-be-tested coal sample;

[0085] In this example, the impurity content represents the non-combustible components contained in the to-be-tested coal sample;

[0086] In this example, the ash fusion quantity represents the ash in the solid fuel, and the product deforms after reaching a certain temperature.

[0087] The working principle and beneficial effects of the above technical solution are as follows: in order to preliminarily understand the to-be-tested coal sample, the calorific value of the to-be-tested coal sample is determined when combustion detection is performed, the low calorific value and the high calorific value of the to-be-tested coal sample are obtained, and ash analysis is performed after combustion is completed, so that the impurity content and the ash fusion quantity of the to-be-tested coal sample are obtained, and the coal quality data of the to-be-tested coal sample is constructed according to the above data, the to-be-tested coal sample is analyzed from multiple angles and in all directions, and the coal quality data is more persuasive.

[0088] Embodiment 3

[0089] On the basis of embodiment 1, the step 2 of the method for intelligently detecting carbon, hydrogen and nitrogen in coal for coal quality detection comprises the following steps.

[0090] Step 21: Obtain combustion environment information corresponding to combustion detection, establish combustion characteristics of each to-be-tested coal sample at different combustion temperatures in combination with the coal quality data, obtain a coal combustion curve corresponding to each to-be-tested coal sample, and determine coal residue information of each to-be-tested coal sample.

[0091] Step 22: Determine the combustion quantity of the corresponding to-be-tested coal sample according to the coal residue information, determine the coal quality of the corresponding to-be-tested coal sample according to the combustion quantity, locate a curve point corresponding to a preset sufficient combustion temperature in each coal combustion curve, and map each coal combustion curve to the same display space with the curve point as a mapping starting point.

[0092] Step 23: Obtain curve difference information between each different coal combustion curve in the display space, construct sample accidental characteristics of the corresponding to-be-tested coal sample according to the curve difference information, adjust the corresponding coal combustion curve by using the sample accidental characteristics, and count a plurality of adjustment positions corresponding to each coal combustion curve and an adjustment amount corresponding to each adjustment position.

[0093] Step 24: Establish the carbon, hydrogen and nitrogen content ratio of the corresponding to-be-tested coal sample according to the oxygen consumption amount corresponding to each adjustment position and the adjustment amount corresponding to each adjustment position, adjust the emission rule of the preset spectrum according to the carbon, hydrogen and nitrogen content ratio, and generate a spectrum irradiation scheme.

[0094] In this example, the combustion environment information represents the environment in which combustion detection is performed.

[0095] In this example, the to-be-tested coal sample will exhibit different combustion characteristics at different combustion temperatures.

[0096] In this example, the mapping starting point represents the first mapping position when mapping is performed.

[0097] In this example, the preset sufficient combustion temperature is 135℃±0.1℃.

[0098] In this example, the sample accidental feature represents the error caused by the difference of the combustion environment to the combustion work.

[0099] The working principle and beneficial effects of the above technical solution are as follows: in order to reduce the accident and avoid the influence of the external environment on the detection result, when the combustion detection is carried out, the combustion characteristics of the sample at different combustion temperatures are established according to the environmental information, so as to draw the coal combustion curve at different combustion temperatures, and further determine the information difference between the to-be-detected coal samples by mapping, so as to determine the corresponding sample accidental characteristics, and then adjust the coal combustion curve, thereby determining the carbon, hydrogen and nitrogen content ratio of the to-be-detected coal sample, and then adjusting the emission rule of the preset spectrum according to the carbon, hydrogen and nitrogen content ratio, generating a spectrum irradiation scheme that is mutually matched and adapted to the to-be-detected coal sample, thereby effectively improving the accuracy of spectrum irradiation.

[0100] Embodiment 4

[0101] On the basis of embodiment 1, the coal carbon, hydrogen and nitrogen intelligent detection method for coal quality detection, the step 3 comprises:

[0102] Step 31: controlling the corresponding emission device to perform the emission light task according to the spectrum irradiation scheme, and determining a plurality of emission lights contained in the emission light task according to the spectrum irradiation scheme, and respectively acquiring the detection direction corresponding to each emission light;

[0103] Step 32: respectively acquiring the corresponding presented features of each to-be-detected coal sample after combustion in different detection directions, and determining the carbon element concentration contained in each to-be-detected coal sample according to the presented features;

[0104] Step 33: determining the hydrogen element concentration range value and the nitrogen element concentration range value in each to-be-detected coal sample according to the carbon, hydrogen and nitrogen content ratio, and performing numerical correction on the presented features corresponding to each to-be-detected coal sample and the corresponding element concentration range value and nitrogen element concentration range value, to obtain the hydrogen element concentration and nitrogen element concentration contained in the corresponding to-be-detected coal sample.

[0105] Step 34: if the carbon element concentration error value, nitrogen element concentration error value and hydrogen element concentration error value between different to-be-detected coal samples are within the standard error value range, an element composition list is generated.

[0106] In this example, the detection direction comprises a hydrogen element detection direction, a hydrogen element detection direction and a nitrogen element detection direction.

[0107] The working principle and beneficial effects of the technical solution are as follows: in order to accurately analyze the content of each element in the coal sample to be measured, the coal sample to be measured is irradiated according to the spectrum irradiation scheme, and then a plurality of characteristic features of the coal sample to be measured are determined, so as to determine the carbon element concentration, and the hydrogen element concentration and the nitrogen element concentration in the coal sample to be measured are corrected in combination with the carbon-hydrogen-nitrogen content ratio, and finally the error analysis of each element content is performed, and the composition list is generated after the analysis. In the test process, the accidental nature is eliminated by setting the spectrum irradiation scheme, and the second check is performed through numerical correction, thereby effectively improving the accuracy of the detection result.

[0108] Embodiment 5

[0109] Based on embodiment 4, the intelligent coal carbon-hydrogen-nitrogen detection method for coal quality detection further comprises:

[0110] If one or more of the carbon element concentration error value, the nitrogen element concentration error value and the hydrogen element concentration error value between different coal samples to be measured are not within the standard error value range, the corresponding abnormal concentration error value is obtained;

[0111] The abnormal element concentration corresponding to the abnormal concentration error is subjected to normal distribution analysis, and the abnormal coal sample to be measured with the highest dispersion degree is obtained;

[0112] The sampling information corresponding to the coal sample to be measured is obtained, and the sampling position of the coal sample to be measured is determined;

[0113] The sampling position is supplemented with sampling, and the supplemented coal sample to be measured is analyzed.

[0114] The working principle and beneficial effects of the technical solution are as follows: since black stones may be mixed in the coal, in order to avoid the influence of the stones on the detection result, when the element concentration is abnormal, the sampling position is resampled and corresponding detection is performed, more accurate data is provided for the coal detection, and the persuasiveness is improved.

[0115] Embodiment 6

[0116] Based on embodiment 2, the intelligent coal carbon-hydrogen-nitrogen detection method for coal quality detection further comprises:

[0117] Before the combustion detection, the coal sample image corresponding to each coal sample to be measured is obtained;

[0118] The texture analysis is performed on each coal sample image to obtain the granularity information and the color formation information corresponding to each coal sample to be measured;

[0119] After the coal sample to be measured is combusted, the granularity information and the color formation information are supplemented into the sampling information.

[0120] The working principle and beneficial effects of the above technical solution are that the appearance of the coal sample to be measured is analyzed through image analysis, realizing multi-angle and all-around analysis.

[0121] Embodiment 7

[0122] Based on embodiment 6, the intelligent detection method for carbon, hydrogen and nitrogen in coal for coal quality detection further comprises:

[0123] Before the combustion detection, the corresponding grinding mode is retrieved according to the granularity information;

[0124] The corresponding coal sample to be measured is ground and pretreated by using the grinding mode.

[0125] The working principle and beneficial effects of the above technical solution are that in order to make the coal sample to be measured fully burn, the coal sample to be measured is ground before combustion, avoiding the influence on the detection result caused by insufficient combustion.

[0126] Embodiment 8

[0127] Based on embodiment 1, the intelligent detection method for carbon, hydrogen and nitrogen in coal for coal quality detection, the step 4 comprises:

[0128] Step 41: constructing the coal structure of the corresponding coal sample to be measured according to the coal quality data and the element composition list corresponding to each coal sample to be measured;

[0129] Step 42: constructing the coal quality report according to the coal structure and combining the source information of the coal sample to be measured.

[0130] The working principle and beneficial effects of the above technical solution are that the coal quality report is constructed by combining the coal structure with the coal quality data and the element composition list of the coal sample to be measured, providing technical reference for users.

[0131] Embodiment 9

[0132] The present example provides an intelligent detection system for carbon, hydrogen and nitrogen in coal for coal quality detection, as shown in Figure 2 The intelligent detection system for carbon, hydrogen and nitrogen in coal for coal quality detection comprises:

[0133] A combustion detection module is configured to perform combustion detection on each coal sample to be measured respectively, and determine the coal quality data corresponding to each coal sample to be measured according to the combustion detection result;

[0134] A light analysis module is configured to evaluate the carbon, hydrogen and nitrogen content ratio corresponding to each coal sample to be measured according to the coal quality data, and retrieve the corresponding spectrum irradiation scheme according to the carbon, hydrogen and nitrogen content ratio;

[0135] an element analysis module configured to perform an emission light task according to the spectral irradiation scheme, to perform infrared absorption analysis on the combusted coal sample to be tested, and to obtain element concentrations of different elements in each coal sample to be tested, and to construct an element composition list;

[0136] a report generation module configured to generate a coal quality report corresponding to each coal sample to be tested according to the coal quality data and the element composition list corresponding to each coal sample to be tested.

[0137] In this example, the spectral irradiation scheme represents a process of irradiating the coal sample to be tested with red light of different frequencies.

[0138] In this example, the coal quality data represent the quality of coal in specific data.

[0139] In this example, the carbon-hydrogen-nitrogen content ratio represents the content ratio among carbon, hydrogen, and nitrogen elements contained in the coal sample to be tested.

[0140] In this example, the element concentration represents the content of each element in a coal sample to be tested.

[0141] The working principle and beneficial effects of the above technical solution are as follows: In order to analyze the coal to be tested, a plurality of coal samples to be tested are detected by combustion, a plurality of coal quality data are obtained, the carbon-hydrogen-nitrogen content ratio of each coal sample to be tested is evaluated according to the coal quality data, and the corresponding spectral irradiation scheme is retrieved. In this way, different quality coals can be analyzed in detail, and the randomness of analysis is effectively reduced. Then, the coal residue after combustion is irradiated by using the spectral irradiation scheme, the element concentrations of different elements in the coal sample to be tested are determined according to the absorption of different light by the coal residue, and an element composition list is constructed. Finally, a coal quality report is generated, the coal quality detection is completed, the user can determine whether the coal is qualified according to the report, and the unqualified coal can be processed in a timely manner.

[0142] Embodiment 10

[0143] Based on the embodiment 9, the coal carbon-hydrogen-nitrogen intelligent detection system for coal quality detection, the combustion detection module comprises:

[0144] a first combustion detection unit configured to sample the coal to be tested to obtain a plurality of coal samples to be tested, and to record sampling information corresponding to each coal sample to be tested;

[0145] a second combustion detection unit configured to perform combustion detection on each coal sample to be tested respectively, to perform calorific value determination on each coal sample to be tested during the combustion process, to obtain low calorific value and high calorific value corresponding to each coal sample to be tested;

[0146] A third combustion detection unit is configured to complete ash analysis on each of the coal samples to be detected after combustion, and obtain the ash content and ash melting amount corresponding to each of the coal samples to be detected;

[0147] A fourth combustion detection unit is configured to establish coal quality data of each of the coal samples to be detected according to the sampling information, low calorific value, high calorific value, ash content and ash melting amount corresponding to each of the coal samples to be detected.

[0148] In this example, the combustion environment information indicates the environment in which the combustion detection is performed;

[0149] In this example, the coal samples to be detected have different combustion characteristics at different combustion temperatures;

[0150] In this example, the mapping starting point indicates the first mapping position when the mapping is performed;

[0151] In this example, the preset sufficient combustion temperature is 135℃±0.1℃;

[0152] In this example, the sample accidental characteristic indicates the error caused by the different combustion environments to the combustion work.

[0153] The working principle and beneficial effects of the above technical solution are as follows: in order to reduce the accident and avoid the influence of the external environment on the detection result, when the combustion detection is performed, the combustion characteristics of the coal samples to be detected at different combustion temperatures are established according to the environment information, so as to draw the coal combustion curve of the coal samples to be detected at different combustion temperatures, and further determine the information difference between the coal samples to be detected by the mapping, so as to determine the corresponding sample accidental characteristics, and then adjust the coal combustion curve, thereby determining the carbon-hydrogen-nitrogen content ratio of the coal samples to be detected, and then adjusting the emission rule of the preset spectrum according to the carbon-hydrogen-nitrogen content ratio, generating a spectrum irradiation scheme that is matched and adapted to the coal samples to be detected, and effectively improving the accuracy of the spectrum irradiation.

[0154] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the claims of the present application and their equivalents, the present application also intends to include these modifications and variations.

Claims

1. A method for intelligent detection of carbon, hydrogen and nitrogen in coal for coal quality detection, characterized in that, The application relates to a coal quality data evaluation method and device. Step 1: respectively detecting each to-be-tested coal sample, and determining the coal quality data corresponding to each to-be-tested coal sample according to the detection result; Step 2: evaluating the carbon-hydrogen-nitrogen content ratio corresponding to each to-be-tested coal sample according to the coal quality data, and adjusting the corresponding spectrum irradiation scheme according to the carbon-hydrogen-nitrogen content ratio; Step 3: performing the light emission task according to the spectrum irradiation scheme, and performing infrared absorption analysis on the to-be-tested coal sample after combustion to obtain the element concentration corresponding to different elements in each to-be-tested coal sample, and constructing an element composition list; Step 4: generating the coal quality report corresponding to each to-be-tested coal sample according to the coal quality data and the element composition list corresponding to each to-be-tested coal sample. The step 2 comprises the following steps. Step 21: obtaining the combustion environment information corresponding to the combustion detection, combining the coal quality data to establish the combustion characteristics of each to-be-tested coal sample under different combustion temperatures, obtaining the coal combustion curve corresponding to each to-be-tested coal sample, and determining the coal residue information of each to-be-tested coal sample; Step 22: determining the combustion amount of the corresponding to-be-tested coal sample according to the coal residue information, determining the coal quality of the corresponding to-be-tested coal sample according to the combustion amount, locating the curve point corresponding to the preset sufficient combustion temperature in each coal combustion curve, and respectively mapping each coal combustion curve to the same display space with the curve point as the mapping starting point; Step 23: obtaining the curve difference information between each different coal combustion curve in the display space, constructing the sample accidental characteristics of the corresponding to-be-tested coal sample according to the curve difference information, adjusting the corresponding coal combustion curve by using the sample accidental characteristics, and counting the adjustment positions corresponding to each coal combustion curve and the adjustment amount corresponding to each adjustment position; Step 24: establishing the carbon-hydrogen-nitrogen content ratio of the corresponding to-be-tested coal sample according to the oxygen consumption amount corresponding to each adjustment position and the adjustment amount, adjusting the emission rule of the preset spectrum according to the carbon-hydrogen-nitrogen content ratio, and generating the spectrum irradiation scheme.

2. The intelligent detection method for carbon, hydrogen and nitrogen in coal for coal quality detection according to claim 1, characterized in that, The step 1 comprises the following steps. Step 11: sampling the to-be-tested coal to obtain a plurality of to-be-tested coal samples, and recording the sampling information corresponding to each to-be-tested coal sample; Step 12: respectively detecting each to-be-tested coal sample, and respectively determining the low calorific value and the high calorific value of each to-be-tested coal sample in the combustion process; Step 13: respectively analyzing the ash content of each to-be-tested coal sample after combustion, and obtaining the impurity quality and the ash melting amount corresponding to each to-be-tested coal sample; Step 14: establishing the coal quality data of the corresponding to-be-tested coal sample according to the sampling information, the low calorific value, the high calorific value, the impurity quality and the ash melting amount corresponding to each to-be-tested coal sample.

3. The intelligent method for detecting carbon, hydrogen and nitrogen in coal for coal quality detection according to claim 1, characterized in that, The step 3 comprises the following steps. Step 31: controlling the corresponding emission device to perform the light emission task according to the spectrum irradiation scheme, and determining a plurality of emission lights contained in the light emission task according to the spectrum irradiation scheme, and respectively obtaining the detection direction corresponding to each emission light. Step 32: Obtain the corresponding characteristic of each burned coal sample in different detection directions respectively, and determine the carbon element concentration contained in each coal sample according to the characteristic; Step 33: Determine the hydrogen element concentration range value and nitrogen element concentration range value in each coal sample according to the carbon-hydrogen-nitrogen content ratio, and perform numerical correction on the corresponding characteristic, element concentration range value and nitrogen element concentration range value of each coal sample to obtain the hydrogen element concentration and nitrogen element concentration contained in the corresponding coal sample; Step 34: If the carbon element concentration error value, nitrogen element concentration error value and hydrogen element concentration error value between different coal samples are within the standard error value range, generate an element composition list.

4. The intelligent detection method for carbon, hydrogen and nitrogen in coal for coal quality detection according to claim 3, characterized in that, Also includes: If one or more of the carbon element concentration error value, nitrogen element concentration error value and hydrogen element concentration error value between different coal samples are not within the standard error value range, obtain the corresponding abnormal concentration error value; Perform normal distribution analysis on the abnormal element concentration corresponding to the abnormal concentration error to obtain the abnormal coal sample with the highest dispersion degree; Obtain the sampling information corresponding to the coal sample to determine the sampling position of the coal sample; Supplement sampling to the sampling position and analyze the obtained supplement coal sample.

5. The intelligent method for detecting carbon, hydrogen and nitrogen in coal for coal quality detection according to claim 2, characterized in that, Also includes: Before the combustion detection, obtain the corresponding coal sample image of each coal sample respectively; Perform texture analysis on each coal sample image to obtain the granularity information and color information corresponding to each coal sample respectively; After the combustion of the coal sample, supplement the granularity information and color information to the sampling information.

6. The intelligent detection method for carbon, hydrogen and nitrogen in coal for coal quality detection according to claim 5, characterized in that, Also includes: Before the combustion detection, retrieve the corresponding grinding method according to the granularity information; Grind the corresponding coal sample for pretreatment using the grinding method.

7. The intelligent method for detecting carbon, hydrogen and nitrogen in coal for coal quality detection according to claim 1, characterized in that, The step 4 includes: Step 41: Construct the coal structure of each coal sample according to the coal quality data and element composition list corresponding to each coal sample; Step 42: Construct a coal quality report according to the coal structure and the source information of the coal sample.

8. A coal hydrocarbon nitrogen intelligent detection system for coal quality detection, characterized in that, Includes: A combustion detection module for detecting each coal sample respectively, and determining the coal quality data corresponding to each coal sample according to the combustion detection result; An illumination analysis module for evaluating the carbon-hydrogen-nitrogen content ratio of each coal sample according to the coal quality data, and retrieving the corresponding spectral illumination scheme according to the carbon-hydrogen-nitrogen content ratio; An element analysis module for performing an emission light task according to the spectral illumination scheme, performing infrared absorption analysis on the burned coal sample, obtaining the element concentration of different elements in each coal sample, and constructing an element composition list; A report generation module for generating a coal quality report corresponding to each coal sample according to the coal quality data and element composition list corresponding to each coal sample; The process of the illumination analysis module for evaluating the carbon-hydrogen-nitrogen content ratio of each coal sample according to the coal quality data, and retrieving the corresponding spectral illumination scheme, includes: Obtaining combustion environment information corresponding to combustion detection, combining the coal quality data to establish the corresponding combustion characteristics of each of the to-be-tested coal samples at different combustion temperatures, obtaining the coal combustion curve corresponding to each of the to-be-tested coal samples, and determining the coal residue information of each of the to-be-tested coal samples; According to the coal residue information, the combustion amount of the corresponding to-be-tested coal sample is determined, the coal quality of the corresponding to-be-tested coal sample is determined according to the combustion amount, and the curve point corresponding to the preset sufficient combustion temperature is located in each of the coal combustion curves. The curve point is used as the mapping starting point, and each of the coal combustion curves is mapped into the same display space; Obtaining the curve difference information between each different coal combustion curve in the display space, constructing the sample accidental characteristics of the corresponding to-be-tested coal sample according to the curve difference information, adjusting the corresponding coal combustion curve by using the sample accidental characteristics, and statistically analyzing a plurality of adjustment positions corresponding to each of the coal combustion curves and an adjustment amount corresponding to each of the adjustment positions; According to the oxygen consumption corresponding to each of the adjustment positions and the adjustment amount, the carbon-hydrogen-nitrogen content ratio of the corresponding to-be-tested coal sample is established, the emission rule of the preset spectrum is adjusted according to the carbon-hydrogen-nitrogen content ratio, and a spectrum irradiation scheme is generated.

9. The intelligent system for detecting carbon, hydrogen and nitrogen in coal for coal quality detection according to claim 8, wherein, The combustion detection module comprises: A first combustion detection unit is configured to sample the to-be-tested coal to obtain a plurality of to-be-tested coal samples, and record the sampling information corresponding to each of the to-be-tested coal samples; A second combustion detection unit is configured to perform combustion detection on each of the to-be-tested coal samples, respectively, and to determine the calorific value of each of the to-be-tested coal samples during the combustion process, to obtain the low calorific value and the high calorific value corresponding to each of the to-be-tested coal samples; A third combustion detection unit is configured to perform ash analysis on each of the to-be-tested coal samples after combustion, to obtain the impurity content and the ash melting amount corresponding to each of the to-be-tested coal samples; A fourth combustion detection unit is configured to establish the coal quality data of the corresponding to-be-tested coal sample according to the sampling information, the low calorific value, the high calorific value, the impurity content, and the ash melting amount corresponding to each of the to-be-tested coal samples.

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