Real-time Coal Quality Detection Device and Method for Intermediate Storage Pulverizing Systems

Abstract

This invention relates to the field of coal quality testing equipment technology, and particularly to a real-time coal quality testing device and method suitable for intermediate storage pulverizing systems. The device comprises a belt sampling module, a primary grinding module, a primary reduction module, a secondary grinding module, a secondary reduction module, a moisture detection module, a tertiary grinding module, a briquette pressing module, a LIBS analysis module, and a communication interface, arranged sequentially. The invention incorporates a moisture detection and drying process to eliminate the influence of sample moisture. The moisture detection module features two weighing operations to effectively control the amount of coal sampled for briquette pressing. Multiple measurements are taken at various locations on the briquette to obtain N sample spectra, effectively reducing the impact of environmental factors and briquette uniformity on the test results. Compensation is provided for the 6-8 hour delay from the conveyor belt to the coal entering the furnace, reducing the impact of this time uncertainty and improving the real-time accuracy of the coal quality measurement.

Description

Technical Field

[0001] This invention relates to the field of coal quality testing equipment technology, and in particular to a real-time coal quality testing device and method suitable for intermediate storage pulverizing systems. Background Technology

[0002] Currently, most coal-fired power units use offline sampling and laboratory analysis for coal quality testing. Existing methods are complex, time-consuming, and have poor sample representativeness, making it difficult to provide timely feedback on the various components of the coal. Each power plant's laboratory analysis typically generates only one or two sets of data per day, with data on coal calorific value and composition delayed by 8-24 hours, making it difficult to reflect real-time coal quality conditions.

[0003] In recent years, laser-induced plasma spectroscopy (LIBS) has emerged as a novel laser analysis technology due to its advantages such as high sensitivity, multi-element measurement, and rapid measurement, showing great potential for application in online coal quality detection. Existing related patent applications, such as Chinese invention patent publication number CN109557278A, describe a LIBS online intelligent rapid coal quality detection system comprising eight modules: a sampling system, a sample delivery system, a drying system, a crushing system, a material suction and pressing system, a cake delivery system, a LIBS detection system, and a packaging and coding system. The sampling system acquires a full-moisture coal sample and delivers it to the sample delivery system, which then transports the sample to the drying system, controlling the moisture content of the coal sample within a certain range. The crushing system grinds the dried coal sample to obtain coal powder. The pressing system compresses the coal cake, and the cake delivery system delivers two compressed coal cakes to the LIBS detection system and the packaging and coding system, respectively. The LIBS detection system detects one of the coal cakes. The packaging and coding system automatically packages and codes the two coal cakes.

[0004] However, this method has the following problems:

[0005] 1. The coal quality calculation has a large delay. The LIBS online coal quality monitoring system usually samples the coal entering the plant or the coal conveyor belt. There is still a 6-8 hour delay from the coal conveyor belt to the coal entering the furnace. Especially for intermediate storage pulverizing systems, there is a powder silo after the coal mill outlet. When sampling is taken from the coal feeder outlet, the measured coal quality data is still significantly different from the coal entering the furnace.

[0006] 2. The elemental analysis results of the LIBS online coal quality monitoring system are greatly affected by the moisture content of the sample. If the moisture content of the sample fluctuates greatly, the accuracy of the LIBS elemental analysis results will be greatly reduced.

[0007] 3. Due to problems such as belt misalignment and uneven coal distribution, the coal cake samples pressed out by the LIBS online coal quality monitoring system may be incomplete, resulting in laser misalignment and inaccurate coal quality test results. Summary of the Invention

[0008] To address the aforementioned problems in the existing technology, a real-time coal quality detection device and method suitable for intermediate storage pulverizing systems are proposed.

[0009] To achieve the above-mentioned technical effects, the technical solution protected in this application is as follows:

[0010] A device for real-time detection of coal quality entering the furnace in an intermediate storage pulverizing system includes a belt sampling module, a primary grinding module, a primary reduction module, a secondary grinding module, a secondary reduction module, a moisture detection module, a tertiary grinding module, a cake pressing module, a LIBS analysis module, and a communication interface, arranged sequentially.

[0011] The belt sampling module samples the coal in the belt before the pulverizing system inlet;

[0012] The primary grinding module grinds the raw coal, and the particle size becomes less than 13mm after passing through the primary grinding module;

[0013] The primary reduction module extracts 5%–20% of the coal sample output from the previous stage.

[0014] The secondary grinding module grinds the coal sample from the primary reduction module to within 3mm.

[0015] The secondary reduction module extracts 30%–60% of the coal sample output from the previous stage;

[0016] The moisture detection module performs moisture calculations and coal sampling drying.

[0017] The three-stage grinding module grinds the sampled coal output by the moisture detection module to within 0.2mm;

[0018] The briquetting module presses the sampled coal output from the three grinding modules into uniformly shaped briquettes;

[0019] The communication interface transmits real-time coal quality monitoring results to the power plant's information system.

[0020] Furthermore, the belt sampling module includes an electric guide plate and a weighing device. The electric guide plate is installed on the coal conveyor belt, and the weighing device is installed at the end of the electric guide plate. The electric guide plate can be configured as two guide plates arranged side by side at intervals at the end of the belt, and a limiting plate for adjusting the position is provided between the two guide plates and the outlet of the grinding mill.

[0021] Furthermore, the primary grinding module, secondary grinding module, and tertiary grinding module are coal powder pulverizers. The primary grinding module is installed at the outlet of the belt sampling module to grind the raw coal. The secondary grinding module is installed at the outlet of the primary reduction module to grind the coal sample. The tertiary grinding module is installed at the outlet of the moisture detection module. The cake pressing device is an electric cake pressing machine.

[0022] Furthermore, the primary grinding module includes a forward and reverse belt, a guide plate, and a rotary separator; the forward and reverse belt is located at the outlet of the primary grinding module and is equipped with a frame for determining the direction of coal powder transmission; the guide plate is located at the end of the forward and reverse belt, and the rotary separator is located at the end of the guide plate.

[0023] Furthermore, the secondary reduction module includes a 3mm round hole sieve and a divider, allowing the coal powder from the secondary grinding module outlet to pass through the 3mm round hole sieve at a uniform speed; then the divider is used to directly reduce the coal powder to 30%-60% for sample preparation.

[0024] Furthermore, the moisture detection module includes a sample receiving and spreading device, a weighing mechanism, and a drying oven; the spreading device spreads the sampled coal output from the secondary reduction module, the weighing mechanism weighs the sampled coal, and then sends it to the drying oven for drying and weighing again.

[0025] Furthermore, the LIBS analysis module includes a sample rotating stage, an Nd:YAG solid-state laser, a lens, a light receiver, an optical fiber, a spectrometer, a detector, and an industrial control computer. The coal cake is placed on the sample rotating stage, and the Nd:YAG solid-state laser emits laser light, which is projected onto the coal cake through the lens to generate plasma. The light receiver is placed next to the sample rotating stage to collect the light signals emitted by the plasma during cooling and attenuation, and transmits them to the spectrometer and detector through the optical fiber. The processed spectral information is then transmitted to the industrial control computer. The communication interface on the industrial control computer communicates with the information platform for data transmission.

[0026] Preferably, the communication interface can be a wireless transmission communication module.

[0027] A method for real-time coal quality detection applicable to intermediate storage pulverizing systems includes the following steps:

[0028] Step 1. Use a belt sampling module to extract raw coal from the coal conveyor belt of a coal-fired power plant.

[0029] Step 2. Use the primary grinding module to grind the sampled coal output from the belt sampling module to a particle size of less than 13mm;

[0030] Step 3. The first reduction module extracts the sampled coal output from the first grinding module. The mass of the extracted sampled coal is a part of the mass of the sampled coal output from the first grinding module.

[0031] Step 4. The secondary grinding module grinds the sampled coal output from the primary reduction module to within 3mm;

[0032] Step 5. The secondary reduction module extracts the sampled coal output from the secondary grinding module. The mass of the extracted sampled coal is a portion of the mass of the sampled coal output from the secondary grinding module.

[0033] Step 6. The moisture detection module flattens, weighs, and sends the sampled coal output from the secondary reduction module into the drying box, and then weighs it again; the drying method is multi-layer rapid air drying, the heating time is 2 min to 10 min, and the heating temperature is 105℃ to 110℃;

[0034] Furthermore, the formula for calculating moisture in step 6 is as follows:

[0035]

[0036] In the formula:

[0037] M t —Total moisture content of the test coal sample, expressed as a mass fraction, %

[0038] m — the mass of the sample taken, in grams;

[0039] m0 — Mass of the empty tray of the sample receiving and leveling device, in grams;

[0040] m1—Hot mass of the sample and sample leveling device under drying conditions, in grams;

[0041] m f — Buoyancy effect value of the sample and the sample leveling device under dry conditions, in g.

[0042] Step 7. The three-stage grinding module grinds the sampled coal output by the moisture detection module to within 0.2mm;

[0043] Step 8. The briquetting module presses the sampled coal output from the three grinding modules into briquettes;

[0044] Step 9. The Nd:YAG solid-state laser in the LIBS analysis module emits a laser beam, which is focused by a lens and strikes the surface of the rotating coal cake, generating plasma. The receiver collects the light signals emitted by the plasma during cooling and attenuation, transmits them to the spectrometer and detector via optical fiber, and transmits the processed spectral information to the industrial control computer. Preferably, to reduce the influence of the environment and the uniformity of the coal cake, multiple measurements are taken at multiple different locations on the coal cake to obtain N sample spectra.

[0045] Step 10. Average and normalize the spectra of N samples to obtain the average spectrum;

[0046] Step 11. Calculate the peak area integral of the spectral line, and use the spectral correction method of local spectral normalization and plasma temperature compensation to calculate the spectral line intensity of the element to be measured; substitute the spectral line intensity of the element to be measured into the calibration curve equation, and then calculate the concentration of the element to be measured;

[0047] Step 12. Calculate the time delay from the belt sampling point to the furnace in the intermediate storage pulverizing system, which is used for time compensation by the information system to accurately obtain the current coal quality.

[0048] Furthermore, the delay calculation method is as follows:

[0049] Step 1: Extract 5-10 days of operational data from the historical database;

[0050] The data extraction parameters include the opening degree of the left / right capacity damper of the coal mill, the instantaneous coal feed rate of the coal feeder, the primary air pressure at the inlet of the coal mill, and the material level of the coal mill;

[0051] Step II: The data needs to be preprocessed, including removing outliers and extracting data under stable conditions;

[0052] Outlier removal is performed according to the sampling order. Multiple sampling periods after a step change in parameters are considered as a transition process. After filtering the sampled data using a low-pass filter, the relative deviation accuracy of each parameter is set according to the actual parameter range. Values ​​with deviations greater than the specified accuracy are deleted, and operating data under stable conditions are extracted.

[0053] Step III: Use the k-Means clustering algorithm with Euclidean distance as the criterion to group data that are close in distance into the same category;

[0054] Based on the actual working conditions of each data set, set the number of data sets and the initial centroid of each dataset. Assign all data to the set with the closest distance, and then recalculate the centroid of the set using the mean method. If the new centroid of the set is consistent with the original centroid, the clustering is complete. Otherwise, set the number of data sets and the initial centroid of each dataset again and recalculate until the new centroid of the set is consistent with the original centroid.

[0055] Step IV: Based on the fitting results of Step III, construct a dynamic characteristic model that is closely related to the coal powder flow rate of the coal mill and the instantaneous coal feed rate of the coal feeder, the opening of the capacity damper, the primary air pressure, and the material level.

[0056] The model formula is:

[0057]

[0058]

[0059] In the formula, Q n(t) represents the pulverized coal flow rate of the nth coal mill at time t, in t / h; Q n_in (t) represents the instantaneous coal feed rate of the coal feeder, in t / h; f n,1 (X n,1 Let L(t) represent the coal powder flow characteristic function corresponding to the capacity damper opening of the nth coal mill, where L(t) is the capacity damper opening at time t, in %; n,2 (X n,2 ) represents the characteristic function of pulverized coal flow rate corresponding to the inlet primary air pressure of the nth coal mill, where P(t) is the inlet primary air pressure of the coal mill at time t, in kPa; f n,3 (X n,3 Let represent the coal powder flow rate characteristic function corresponding to the material level of the nth coal mill, and H(t) be the coal mill material level at time t, in Pa. total (t) represents the total amount of coal in the coal mill at time t, and N is the number of coal mills.

[0060] Step V: Substitute the real-time measured data of the left / right capacity damper opening of the coal mill, the instantaneous coal feed rate of the coal feeder, the primary air pressure at the coal mill inlet, and the actual coal mill material level into the model formula constructed in Step IV to obtain the real-time total coal feed rate of the boiler.

[0061] Step VI: Calculate the initial time delay from the belt sampling point to the furnace inlet of the intermediate storage pulverizing system. The calculation formula is as follows:

[0062]

[0063] In the formula, T0 represents the current time; Q total (T0) represents the total amount of coal in the pulverizer at the current moment; T delay_T0 This represents the initial calculated time delay from the belt sampling point to the furnace entry point in the intermediate storage pulverizing system.

[0064] Step VII: Calculate the distance from the current time T delay_T0 The total integral coal quantity Q between time point A and the current time point B N_cal .

[0065]

[0066] In the formula, Q total (t) represents the total amount of coal in the pulverizer calculated at time t;

[0067] Step VIII: Integrate the total coal quantity Q N_cal With the rated capacity Q of the intermediate storage pulverizing system N In comparison, if Q N_cal Q N If the value is small, increase the calculated delay value T. delay_T0 If QN_cal Q N If the value is large, then reduce the calculated delay value T. delay_T0 Recalculate Q N_cal Until Q N_cal With Q N The same; thus, the calculated time T from the belt sampling point to the furnace entry point of the intermediate storage pulverizing system is finally obtained. delay .

[0068] Step 13. Combine the coal quality data obtained in Step 11 and the delay calculation value T obtained in Step 12. delay Transmitted to the power plant's SIS system or other information systems.

[0069] The advantages of this application are:

[0070] 1. This invention provides a real-time coal quality detection device and method, which includes a moisture detection and drying process to eliminate the influence of sample moisture and improve the accuracy of LIBS elemental analysis results.

[0071] 2. The present invention provides a real-time coal quality detection device and method. The belt sampling module is equipped with a limit plate and a weighing device to effectively control the amount of coal sampled. The moisture detection module is equipped with two weighings, which can effectively control the amount of coal sampled for pressing coal cakes and avoid incomplete coal cake samples.

[0072] 3. The real-time coal quality detection method provided by this invention measures the coal cake at multiple different locations multiple times to obtain N sample spectra, which can effectively reduce the influence of the environment and coal cake uniformity on the detection results.

[0073] 4. This invention provides a method for calculating the time delay from the belt sampling point to the furnace in an intermediate storage pulverizing system. It compensates for the 6-8 hour delay from the coal conveyor belt to the coal entering the furnace, reduces the impact of the uncertainty of the time delay from the coal conveyor belt to the coal entering the furnace, and improves the real-time accuracy of coal quality measurement. Attached Figure Description

[0074] Figure 1 This is a structural diagram of a real-time coal quality monitoring device suitable for intermediate storage pulverizing systems.

[0075] Figure 2 This is a structural diagram of the LIBS analysis module.

[0076] Figure 3 This is a flowchart of a method for real-time detection of coal quality entering the furnace, applicable to intermediate storage pulverizing systems.

[0077] Figure 4 A flow chart for calculating the time delay from the belt sampling point to the furnace in an intermediate storage pulverizing system.

[0078] Figures 5-7To fit the obtained characteristic curve of the coal mill in the intermediate storage pulverizing system. Detailed Implementation

[0079] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0080] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0081] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0082] In the description of this application, it should be noted that the terms "upper," "vertical," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product is in use, or the orientation or positional relationship commonly understood by those skilled in the art. They are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this application. In addition, the terms "first," "second," etc., are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0083] In the description of this application, it should also be noted that, unless otherwise expressly specified and limited, the terms "set," "install," and "connect" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0084] Example 1

[0085] like Figure 1As shown, a device for real-time detection of coal quality entering the furnace in an intermediate storage pulverizing system includes a belt sampling module, a primary grinding module, a primary reduction module, a secondary grinding module, a secondary reduction module, a moisture detection module, a tertiary grinding module, a cake pressing module, a LIBS analysis module, and a communication interface, arranged sequentially. The belt sampling module samples the coal in the belt before it enters the pulverizing system.

[0086] The primary grinding module grinds the raw coal, which typically has a particle size of 30-100mm. After passing through the primary grinding module, the particle size is reduced to within 13mm.

[0087] The primary reduction module reduces the sample mass to the level required for analytical testing, typically extracting 5%–20% of the coal sample output from the previous stage.

[0088] The secondary grinding module grinds the coal sample from the outlet of the primary reduction module, reducing the 13mm particle size of the coal to within 3mm.

[0089] The function of the secondary reduction module is to reduce the sample mass to the level required for analytical testing, typically extracting 30%–60% of the coal sample output from the previous stage.

[0090] The moisture detection module performs moisture calculation and coal sampling drying. Firstly, moisture calculation is an essential part of coal quality testing (coal chemical composition analysis includes moisture, ash, carbon, hydrogen, oxygen, nitrogen, and sulfur). Secondly, drying the sampled coal is necessary because moisture affects the accuracy of element detection by the LIBS module, and drying improves the accuracy of the LIBS detection module.

[0091] The three-stage grinding module grinds the sampled coal output from the moisture detection module to within 0.2mm, in order to facilitate subsequent LIBS analysis.

[0092] The briquetting module presses the sampled coal output from the three grinding modules into uniformly shaped briquettes for subsequent LIBS analysis.

[0093] The communication interface transmits real-time coal quality monitoring results to the power plant's information system.

[0094] The belt sampling module includes an electric guide plate and a weighing device. The electric guide plate is installed on the coal conveyor belt, and the weighing device is installed at the end of the electric guide plate. The electric guide plate can be configured as two guide plates arranged side by side at intervals at the end of the belt, and a limiting plate for adjusting the position is provided between the two guide plates and the outlet of the grinding mill, thereby effectively controlling the amount of coal sampled and improving the sample preparation accuracy.

[0095] The primary grinding module, secondary grinding module, and tertiary grinding module are coal powder pulverizers. The primary grinding module is installed at the outlet of the belt sampling module to grind the raw coal. The secondary grinding module is installed at the outlet of the primary reduction module to grind the coal sample. The tertiary grinding module is installed at the outlet of the moisture detection module. The pressing device is an electric pressing machine.

[0096] The primary grinding module includes a forward and reverse belt, a guide plate, and a rotary separator; the forward and reverse belt is located at the outlet of the primary grinding module and is equipped with a frame for determining the direction of coal powder transmission; the guide plate is located at the end of the forward and reverse belt and the rotary separator is located at the end of the guide plate.

[0097] The secondary reduction module includes a 3mm round hole sieve and a divider, which allows the coal powder from the secondary grinding module to pass through the 3mm round hole sieve at a uniform speed to ensure that the particle size of the coal powder in the secondary reduction is less than 3mm; then the divider is used to directly reduce the coal powder to 30%-60% for sample preparation.

[0098] The moisture detection module includes a sample receiving and leveling device, a weighing mechanism, and a drying oven. The leveling device flattens the sampled coal output from the secondary reduction module, the weighing mechanism weighs the sampled coal, and it is then sent to the drying oven for drying and weighed again. In this application, the moisture detection and drying processes are combined into one step, saving costs.

[0099] like Figure 2 As shown, the LIBS analysis module includes a sample rotating stage, an Nd:YAG solid-state laser, a lens, a receiver, an optical fiber, a spectrometer, a detector, and an industrial control computer. A coal cake is placed on the sample rotating stage. The Nd:YAG solid-state laser emits laser light, which is projected onto the coal cake through the lens, generating plasma. The receiver, placed beside the sample rotating stage, collects the light signals emitted by the plasma during cooling and attenuation. This data is transmitted via optical fiber to the spectrometer and detector, and the processed spectral information is transmitted to the industrial control computer. The communication interface on the industrial control computer communicates with the power plant's SIS system or other information platforms for data transmission. The communication interface can employ a wireless transmission communication module.

[0100] Example 2

[0101] like Figure 3 As shown, a method for real-time coal quality detection suitable for intermediate storage pulverizing systems includes the following steps:

[0102] Step 1. Use the belt sampling module to extract raw coal from the coal conveyor belt of the coal-fired power plant. Use a weighing device and a limit plate to control the quality of the sampled raw coal, which is usually 300g to 1000g (can be set freely).

[0103] Step 2. Use the primary grinding module to grind the sampled coal output from the belt sampling module (usually the raw coal particle size of the belt is 25mm to 30mm) to a particle size of less than 13mm;

[0104] Step 3. The first reduction module extracts the sampled coal output from the first grinding module. The mass of the extracted sampled coal is a portion of the mass of the sampled coal output from the first grinding module, for example, 5%-20% (can be set freely).

[0105] Step 4. The secondary grinding module grinds the sampled coal (particle size within 13mm) output from the primary reduction module to within 3mm;

[0106] Step 5. The secondary reduction module extracts the sampled coal output from the secondary grinding module. The mass of the extracted sampled coal is a portion of the mass of the sampled coal output from the secondary grinding module, for example, 30%-60% (can be set freely).

[0107] Step 6. The moisture detection module flattens, weighs, and sends the sampled coal output from the secondary reduction module into the drying box for weighing again; the drying method is multi-layer rapid air drying, the heating time is 2min-10min (can be set freely), and the heating temperature is 105℃-110℃ (can be set freely).

[0108] The formula for calculating moisture content is:

[0109]

[0110] In the formula:

[0111] M t —Total moisture content of the test coal sample, expressed as a mass fraction, %

[0112] m — the mass of the sample taken, in grams;

[0113] m0 — Mass of the empty tray of the sample receiving and leveling device, in grams;

[0114] m1—Hot mass of the sample and sample leveling device under drying conditions, in grams;

[0115] m f — Buoyancy effect value of the sample and the sample leveling device under dry conditions, in g.

[0116] Moisture calculation is an essential part of coal quality testing. Coal chemical composition analysis includes: moisture, ash, carbon, hydrogen, oxygen, nitrogen, and sulfur. The moisture calculation module not only calculates moisture content but also dries the sampled coal, as moisture affects the accuracy of element detection by the LIBS module; drying improves the accuracy of the LIBS detection module.

[0117] Step 7. The three-stage grinding module grinds the sampled coal output by the moisture detection module to within 0.2mm;

[0118] Step 8. The briquetting module presses the sampled coal output from the three-stage grinding module into briquettes with a diameter of 10mm-50mm (which can be freely set);

[0119] Step 9. The Nd:YAG solid-state laser in the LIBS analysis module emits a laser beam, which is focused by a lens and strikes the surface of the rotating coal cake, generating plasma. The receiver collects the light signals emitted by the plasma during cooling and attenuation, transmits them to the spectrometer and detector via optical fiber, and transmits the processed spectral information to the industrial control computer. Preferably, to reduce the influence of the environment and the uniformity of the coal cake, multiple measurements are taken at 4-8 different locations on the coal cake to obtain N sample spectra.

[0120] Step 10. Average and normalize the spectra of N samples to obtain the average spectrum;

[0121] Step 11. Calculate the peak area integral of the spectral line, and use the spectral correction method of local spectral normalization and plasma temperature compensation to calculate the spectral line intensity of the element to be measured; substitute the spectral line intensity of the element to be measured into the calibration curve equation, and then calculate the concentration of the element to be measured; the method used in this step is the prior art, and will not be described in detail in this patent.

[0122] Step 12. Calculate the time delay from the belt sampling point to the furnace in the intermediate storage pulverizing system. This time delay is used for time compensation by the SIS (Supervisory Information System for thermal power plants) or other information systems to accurately obtain the current coal quality.

[0123] Furthermore, the delay calculation method is as follows:

[0124] Step 1: Extract 5-10 days of operational data from the SIS historical database;

[0125] The data extraction parameters include the opening degree of the left / right capacity damper of the coal mill, the instantaneous coal feed rate of the coal feeder, the primary air pressure at the inlet of the coal mill, and the material level of the coal mill;

[0126] Step II: The SIS data needs to be preprocessed, including removing outliers and extracting data under various stable conditions;

[0127] Outlier removal is performed according to the SIS sampling order. The 3-5 sampling periods after a step change in parameters are a transition process. After filtering the sampled data using a low-pass filter, the relative deviation accuracy of each parameter is set according to the actual parameter range. Values ​​with deviations greater than the specified accuracy are deleted, and the operating data under each stable condition is extracted.

[0128] Step III: Use the k-Means clustering algorithm with Euclidean distance as the criterion to group data that are close in distance into the same category;

[0129] Based on the actual working conditions of each data set, set the number of data sets and the initial centroid of each dataset. Assign all data to the set with the closest distance, and then recalculate the centroid of the set using the mean method. If the new centroid of the set is consistent with the original centroid, the clustering is complete. Otherwise, set the number of data sets and the initial centroid of each dataset again and recalculate until the new centroid of the set is consistent with the original centroid.

[0130] Step IV: Based on the fitting results of Step III, construct a dynamic characteristic model that is closely related to the coal powder flow rate of the coal mill and the instantaneous coal feed rate of the coal feeder, the opening of the capacity damper, the primary air pressure, and the material level.

[0131] The model formula is:

[0132]

[0133]

[0134] In the formula, Q n (t) represents the pulverized coal flow rate of the nth coal mill at time t, in t / h; Q n_in (t) represents the instantaneous coal feed rate of the coal feeder, in t / h; f n,1 (X n,1 Let L(t) represent the coal powder flow characteristic function corresponding to the capacity damper opening of the nth coal mill, where L(t) is the capacity damper opening at time t, in %; n,2 (X n,2 ) represents the characteristic function of pulverized coal flow rate corresponding to the inlet primary air pressure of the nth coal mill, where P(t) is the inlet primary air pressure of the coal mill at time t, in kPa; f n,3 (X n,3 H(t) represents the coal flow rate characteristic function corresponding to the material level of the nth coal mill, where H(t) is the coal mill material level at time t, in Pa; Q total (t) represents the total amount of coal in the coal mill at time t, and N is the number of coal mills.

[0135] Step V: Substitute the real-time measured data of the left / right capacity damper opening of the coal mill, the instantaneous coal feed rate of the coal feeder, the primary air pressure at the coal mill inlet, and the actual coal mill material level into the model formula constructed in Step IV to obtain the real-time total coal feed rate of the boiler.

[0136] Step VI: Calculate the initial time delay from the belt sampling point to the furnace inlet of the intermediate storage pulverizing system. The calculation formula is as follows:

[0137]

[0138] In the formula, T0 represents the current time; Q total (T0) represents the total amount of coal in the pulverizer at the current moment; T delay_T0 This represents the initial calculated time delay from the belt sampling point to the furnace entry point in the intermediate storage pulverizing system.

[0139] Step VII: Calculate the distance from the current time T delay_T0 The total integral coal quantity Q between time point A and the current time point B N_cal .

[0140]

[0141] In the formula, Q total (t) represents the total amount of coal in the pulverizer calculated at time t;

[0142] Step VIII: Integrate the total coal quantity Q N_cal With the rated capacity Q of the intermediate storage pulverizing system N In comparison, if Q N_cal Q N If the value is small, increase the calculated delay value T. delay_T0 If Q N_cal Q N If the value is large, then reduce the calculated delay value T. delay_T0 Recalculate Q N_cal until Q N_cal With Q N The same; thus, the calculated time T from the belt sampling point to the furnace entry point of the intermediate storage pulverizing system is finally obtained. delay .

[0143] Step 13. Combine the coal quality data obtained in Step 11 and the delay calculation value T obtained in Step 12. delay Transmitted to the power plant's SIS system or other information systems.

[0144] Example 3

[0145] like Figure 1 As shown, a real-time coal quality detection device suitable for intermediate storage pulverizing systems includes the following components: a belt sampling module, a primary grinding module, a primary sizing module, a secondary grinding module, a secondary sizing module, a moisture detection module, a tertiary grinding module, a cake pressing module, a LIBS analysis module, and a communication interface.

[0146] The belt sampling module includes an electric guide plate and a weighing device. The electric guide plate is installed on the coal conveyor belt, and the weighing device is installed at the end of the electric guide plate. The electric guide plate is configured as two guide plates arranged side by side at intervals at the end of the belt, and a limiting plate for adjusting the position is provided between the two guide plates and the outlet of the grinding mill, thereby effectively controlling the amount of coal sampled and improving the sample preparation accuracy.

[0147] The primary grinding module includes a reversible belt, a guide plate, and a rotary separator. The reversible belt is located at the outlet of the primary grinding module and is equipped with a frame for determining the direction of coal powder transport; the guide plate is located at the end of the reversible belt; and the rotary separator is located at the end of the guide plate.

[0148] The secondary reduction module includes a 3mm round hole sieve and a divider.

[0149] The moisture detection module includes a sample receiving and spreading device, a weighing mechanism, and a drying oven.

[0150] like Figure 2 As shown, the LIBS analysis module includes a sample rotary stage, an Nd:YAG solid-state laser, a lens, a receiver, an optical fiber, a spectrometer, a detector, and an industrial control computer.

[0151] The communication interface can communicate with the power plant's SIS system or other information platforms to transmit data. In this embodiment, the communication interface uses a wireless digital signal transmission device and a wireless analog signal transmission device.

[0152] like Figure 3 As shown, the method for real-time detection of coal quality entering the furnace in an intermediate storage pulverizing system includes the following steps:

[0153] (1) Raw coal was extracted from the coal conveyor belt of the coal-fired power plant using a belt sampling module. The mass of the sampled raw coal was controlled to be 1000g using a weighing device and a limit plate.

[0154] (2) The sampled coal output by the belt sampling module is ground to a particle size of less than 13mm using the primary grinding module.

[0155] (3) The first reduction module extracts the sampled coal from each segment. The mass of the extracted sampled coal is 10% of the mass of the sampled coal output by the first grinding module, i.e., 100g.

[0156] (4) The secondary grinding module grinds the sampled coal (within 13mm particle size) output by the primary reduction module to within 3mm.

[0157] (5) The secondary reduction module extracts the sampled coal from each segment. The mass of the extracted sampled coal is 20% of the mass of the sampled coal output by the secondary grinding module, i.e., 20g.

[0158] (6) The moisture detection module flattens, weighs, and sends the sampled coal output from the secondary reduction module into the drying chamber, where it is weighed again. The drying method is multi-layer rapid air drying, with a heating time of 8 minutes and a heating temperature of 105℃. The moisture calculation formula is:

[0159]

[0160] In the formula:

[0161] M t —Total moisture content of the test coal sample, expressed as a mass fraction, %

[0162] m — the mass of the sample taken, in grams;

[0163] m0 — Mass of the empty tray of the sample receiving and leveling device, in grams;

[0164] m1—Hot mass of the sample and sample leveling device under drying conditions, in g;

[0165] m f —Buoyancy effect value of the sample and sample leveling device under drying conditions, in g;

[0166] The sample was found to have a total moisture content of 28%, and its mass after removing moisture was 14.4g.

[0167] (7) The three-stage grinding module grinds the sampled coal output by the moisture detection module to within 0.2 mm.

[0168] (8) The pressing module presses the sampled coal output from the three grinding modules into coal cakes with a diameter of 30 mm. To ensure the compactness of the sample, the pressing pressure is set to 30 MPa.

[0169] (9) The Nd:YAG solid-state laser of the LIBS analysis module emits a laser beam that is focused by a lens and strikes the surface of the rotating coal cake to generate plasma. The energy of the solid-state laser is set to 50 mJ / pulse, the pulse frequency is 1-10 Hz, and the wavelengths are 532 nm and 355 nm. The receiver collects the light signals emitted by the plasma during cooling and decay, transmits them to the spectrometer and detector through optical fiber, and transmits the processed spectral information to the industrial control computer. To reduce the influence of the environment and the uniformity of the coal cake, the rotation speed of the rotating stage is set to 3 rpm, and 8 measurements are randomly selected to obtain 8 sample spectra; the measurement height is 3 mm below the surface of the coal cake. The specific elements measured include C, H, O, N, and S.

[0170] (10) The spectral data of the 8 samples were averaged and normalized to obtain the average spectral data.

[0171] (11) The peak area integral of each spectral line was calculated using a self-developed program. The spectral intensity of the element to be measured was calculated using a spectral correction method with local spectral normalization and plasma temperature compensation. The spectral intensity of the element to be measured was substituted into the calibration curve equation to calculate the concentration of the element to be measured. Si was selected as the internal standard element. The measurement results of C, H, O, N and S were calculated.

[0172] (12) such as Figure 4 As shown, the time delay from the belt sampling point to the furnace in an intermediate storage pulverizing system is calculated. This is used for time compensation in SIS systems or other information systems to accurately obtain the current coal quality. The calculation method is as follows:

[0173] Step 1: Extract operational data from the SIS historical database for the period from May 16th to May 26th, 2022. This includes the opening of the left / right capacity dampers for the six coal mills, the instantaneous coal feed rate of the feeders, the primary air pressure at the mill inlet, and the coal mill material level, totaling 144,000 data points. The calculation process for other coal mills is the same, using mill A as an example.

[0174] Step II: Preprocessing of the SIS data is required. Preprocessing includes removing outliers and extracting operational data under stable conditions. A total of 24,000 data points were collected for mill A. During preprocessing, the deviation accuracy for the average opening of the capacity damper, the instantaneous coal feed rate of the feeder, the mill material level, and the primary air pressure at the mill inlet were set to 0.02, 0.02, 0.09, and 0.05, respectively. After removing outliers, the data volume was reduced by 45%, leaving 13,200 valid data points.

[0175] Step III: Using the k-Means clustering algorithm with Euclidean distance as the criterion, data with similar distances are grouped into the same category. The stable values ​​of the average opening of the capacity damper of the coal mill, the coal mill material level, and the primary air pressure at the coal mill inlet are set to 1%, 390 Pa, and 6.3 kPa, respectively. The stability threshold is set to 1% of the rated value for each. The characteristic function f is then extracted. n,1 (X n,1 ), f n,2 (X n,2 ) and f n,3 (X n,3 The data under steady-state conditions are 851, 623, and 425 respectively. The fitted characteristic curves are shown below. Figures 5-7 As shown.

[0176] Step IV: Based on the fitting results of Step III, construct a dynamic characteristic model of the pulverized coal flow rate, capacity damper opening, primary air pressure, and material level of the coal mill. The model formula is:

[0177]

[0178]

[0179] Step V: Substitute the real-time measured data of the left / right capacity damper opening of the coal mill, the instantaneous coal feed rate of the coal feeder, the primary air pressure at the coal mill inlet, and the actual coal mill material level into the model formula constructed in Step IV to obtain the real-time total coal feed rate of the boiler, which is 473t / h.

[0180] Step VI: Calculate the initial time delay from the belt sampling point to the furnace inlet of the intermediate storage pulverizing system. The calculation formula is as follows:

[0181]

[0182] In the formula, Q represents the rated capacity of the intermediate storage milling system. N If the value is 1660t, then the initial calculated value of the delay from the belt sampling point to the furnace entry point of the intermediate storage pulverizing system is 3.5h.

[0183] Step VII: Calculate the total integrated coal quantity Q from 3.5 hours ago to the current time. N_cal .

[0184]

[0185] Calculations show that Q N_cal It is 1520t.

[0186] Step VIII: Set the delay value to 4h and calculate Q again. N_cal It is 1600t, with a rated capacity Q N The error is 3.6%, which meets the error range. Therefore, the calculated delay from the belt sampling point to the furnace entry point of the current intermediate storage pulverizing system is 4 hours.

[0187] (13) Combine the coal quality data obtained in step (11) and the delay calculation value T obtained in step (12). delay Transmitted to the power plant's SIS system or other information platforms.

Claims

1. A method for real-time coal quality detection suitable for intermediate storage pulverizing systems, characterized in that: Includes the following steps: Step 1. Use a belt sampling module to extract raw coal from the coal conveyor belt of a coal-fired power plant; Step 2. Use the primary grinding module to grind the sampled coal output from the belt sampling module to a particle size of less than 13mm; Step 3. The first reduction module extracts the sampled coal output from the first grinding module. The mass of the extracted sampled coal is a part of the mass of the sampled coal output from the first grinding module. Step 4. The secondary grinding module grinds the sampled coal output from the primary reduction module to within 3mm; Step 5. The secondary reduction module extracts the sampled coal output from the secondary grinding module. The mass of the extracted sampled coal is a portion of the mass of the sampled coal output from the secondary grinding module. Step 6. The moisture detection module flattens, weighs, and sends the sampled coal output from the secondary reduction module into the drying box, where it is weighed again; the drying method is multi-layer rapid air drying. Step 7. The three-stage grinding module grinds the sampled coal output by the moisture detection module to within 0.2mm; Step 8. The briquetting module presses the sampled coal output from the three grinding modules into briquettes; Step 9. The Nd:YAG solid-state laser in the LIBS analysis module emits a laser beam that is focused by a lens and strikes the surface of a rotating coal cake, generating plasma. The receiver collects the light signals emitted by the plasma during cooling and decay, transmits them to the spectrometer and detector through optical fiber, and transmits the processed spectral information to the industrial control computer. To reduce the impact of the environment and the uniformity of the coal cake, multiple measurements are taken at multiple different locations on the coal cake to obtain N sample spectra. Step 10. Average and normalize the spectra of N samples to obtain the average spectrum; Step 11. Calculate the peak area integral of the spectral line, and use the spectral correction method of local spectral normalization and plasma temperature compensation to calculate the spectral line intensity of the element to be measured; substitute the spectral line intensity of the element to be measured into the calibration curve equation, and then calculate the concentration of the element to be measured; Step 12. Calculate the time delay from the belt sampling point to the furnace in the intermediate storage pulverizing system, which is used by the information system for time compensation to accurately obtain the current coal quality; Step 13. Combine the coal quality data obtained in Step 11 and the delay calculation value T obtained in Step 12. delay Transmitted to the power plant's information system; The delay calculation method in step 12 is as follows: Step 1: Extract operational data for several days from the historical database; The data extraction parameters include the opening degree of the left / right capacity damper of the coal mill, the instantaneous coal feed rate of the coal feeder, the primary air pressure at the inlet of the coal mill, and the material level of the coal mill; Step II: The data needs to be preprocessed, including removing outliers and extracting data under stable conditions; Outlier removal is performed according to the sampling order. Multiple sampling periods after a step change in parameters are considered as a transition process. After filtering the sampled data using a low-pass filter, the relative deviation accuracy of each parameter is set according to the actual parameter range. Values ​​with deviations greater than the specified accuracy are deleted, and the operating data under each stable condition is extracted. Step III: Use the k-Means clustering algorithm with Euclidean distance as the criterion to group data that are close in distance into the same category; Based on the actual working conditions of each data set, set the number of data sets and the initial centroid of each dataset. Assign all data to the set that is closest to it, and then recalculate the centroid of the set using the mean method. If the new centroid of the set is consistent with the original centroid, the clustering is complete. Otherwise, set the number of data sets and the initial centroid of each dataset again and recalculate until the new centroid of the set is consistent with the original centroid. Step IV: Based on the fitting results of Step III, construct a dynamic characteristic model that is closely related to the coal powder flow rate of the coal mill and the instantaneous coal feed rate of the coal feeder, the opening of the capacity damper, the primary air pressure, and the material level. The model formula is: In the formula, Q n (t) represents the pulverized coal flow rate of the nth coal mill at time t, in t / h; Q n_in (t) represents the instantaneous coal feed rate of the coal feeder, in t / h; f n,1 (X n,1 Let L(t) represent the coal powder flow characteristic function corresponding to the capacity damper opening of the nth coal mill, where L(t) is the capacity damper opening at time t, in %; n,2 (X n,2 ) represents the characteristic function of pulverized coal flow rate corresponding to the inlet primary air pressure of the nth coal mill, where P(t) is the inlet primary air pressure of the coal mill at time t, in kPa; f n,3 (X n,3 H(t) represents the coal flow rate characteristic function corresponding to the material level of the nth coal mill, where H(t) is the coal mill material level at time t, in Pa; Q total (t) represents the total amount of coal produced by the coal mill at time t, and N is the number of coal mills; Step V: Substitute the real-time measured data of the opening of the left / right capacity damper of the coal mill, the instantaneous coal feed rate of the coal feeder, the primary air pressure at the inlet of the coal mill, and the actual material level of the coal mill into the model formula constructed in Step IV to obtain the real-time total coal feed rate of the boiler. Step VI: Calculate the initial time delay from the belt sampling point to the furnace inlet of the intermediate storage pulverizing system. The calculation formula is as follows: In the formula, T0 represents the current time; Q total (T0) represents the total amount of coal in the pulverizer at the current moment; T delay_T0 Q represents the initial calculated time delay from the belt sampling point to the furnace in an intermediate storage pulverizing system. N Rated capacity; Step VII: Calculate the distance from the current time T delay_T0 The total integral coal quantity Q between time point A and the current time point B N_cal : In the formula, Q total (t) represents the total amount of coal in the pulverizer calculated at time t; Step VIII: Integrate the total coal quantity Q N_cal With the rated capacity Q of the intermediate storage pulverizing system N In comparison, if Q N_cal Q N If the value is small, increase the calculated delay value T. delay_T0 If Q N_cal Q N If the value is large, then reduce the calculated delay value T. delay_T0 Recalculate Q N_cal Until Q N_cal With Q N The same; thus, the calculated time T from the belt sampling point to the furnace entry point of the intermediate storage pulverizing system is finally obtained. delay .

2. The method for real-time coal quality detection applicable to intermediate storage pulverizing systems according to claim 1, characterized in that: The formula for calculating moisture in step 6 is: In the formula: M t —Total moisture content of the test coal sample, expressed as a mass fraction, % m — the mass of the sample taken, in grams; m0 — Mass of the empty tray of the sample receiving and leveling device, in grams; m1—Hot mass of the sample and sample leveling device under drying conditions, in grams; m f — Buoyancy effect value of the sample and the sample leveling device under dry conditions, in g.

3. A method for real-time coal quality detection suitable for intermediate storage pulverizing systems according to claim 1 or 2, characterized in that: The equipment used in this method is a device for real-time detection of coal quality entering the furnace in an intermediate storage pulverizing system. The device includes a belt sampling module, a primary grinding module, a primary reduction module, a secondary grinding module, a secondary reduction module, a moisture detection module, a tertiary grinding module, a cake pressing module, a LIBS analysis module, and a communication interface, which are arranged in sequence. The belt sampling module samples the coal in the belt before the pulverizing system inlet; The primary grinding module grinds the raw coal, and the particle size becomes less than 13mm after passing through the primary grinding module; The primary reduction module extracts a portion of the coal sample output from the previous stage. The secondary grinding module grinds the coal sample from the primary reduction module to within 3mm. The secondary reduction module extracts a portion of the coal sample output from the previous stage. The moisture detection module performs moisture calculations and coal sampling drying. The three-stage grinding module grinds the sampled coal output by the moisture detection module to within 0.2mm; The briquetting module presses the sampled coal output from the three grinding modules into uniformly shaped briquettes; The communication interface transmits real-time coal quality monitoring results to the power plant's information system.

4. The method for real-time coal quality detection in an intermediate storage pulverizing system according to claim 3, characterized in that: The belt sampling module includes an electric guide plate and a weighing device. The electric guide plate is installed on the coal conveyor belt, and the weighing device is installed at the end of the electric guide plate. The electric guide plate can be configured as two guide plates arranged side by side at intervals at the end of the belt, and a limiting plate for adjusting the position is provided between the two guide plates and the outlet of the grinding mill.

5. The method for real-time coal quality detection in an intermediate storage pulverizing system according to claim 3, characterized in that: The primary grinding module, secondary grinding module, and tertiary grinding module are coal powder pulverizers. The primary grinding module is installed at the outlet of the belt sampling module to grind the raw coal. The secondary grinding module is installed at the outlet of the primary reduction module to grind the coal sample. The tertiary grinding module is installed at the outlet of the moisture detection module. The cake pressing module is an electric cake pressing machine.

6. The method for real-time coal quality detection applicable to intermediate storage pulverizing systems according to claim 3, characterized in that: The primary grinding module includes a forward and reverse belt, a guide plate, and a rotary separator; the forward and reverse belt is located at the outlet of the primary grinding module and is equipped with a frame for determining the direction of coal powder transmission; the guide plate is located at the end of the forward and reverse belt and the rotary separator is located at the end of the guide plate.

7. The method for real-time coal quality detection in an intermediate storage pulverizing system according to claim 3, characterized in that: The secondary reduction module includes a 3mm round hole sieve and a divider, which allows the coal powder from the secondary grinding module to pass through the 3mm round hole sieve at a uniform speed, and then the divider directly reduces the coal powder to 30%-60% for sample preparation. The moisture detection module includes a sample receiving and spreading device, a weighing mechanism, and a drying oven. The spreading device spreads the sampled coal output from the secondary reduction module, the weighing mechanism weighs the sampled coal, and it is sent to the drying oven for drying and then weighed again.

8. The method for real-time coal quality detection applicable to intermediate storage pulverizing systems according to claim 3, characterized in that: The LIBS analysis module includes a sample rotating stage, an Nd:YAG solid-state laser, a lens, a light receiver, an optical fiber, a spectrometer, a detector, and an industrial control computer. A coal cake is placed on the sample rotating stage. The Nd:YAG solid-state laser emits laser light, which is projected onto the coal cake through the lens, generating plasma. The light receiver, placed next to the sample rotating stage, collects the light signals emitted by the plasma during cooling and attenuation. This data is transmitted via the optical fiber to the spectrometer and detector, and the processed spectral information is transmitted to the industrial control computer. The communication interface on the industrial control computer communicates with the information platform for data transmission.

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