A method, apparatus and electronic equipment for analyzing the fineness of pulverized coal

Abstract

This invention discloses a method, apparatus, and electronic equipment for analyzing the fineness of pulverized coal. The method includes: acquiring data on the target coal mill model and the wind speed, pulverized coal concentration, and audio data from multiple audio probes within a preset time range; selecting audio feature values ​​of pulverized coal of different particle sizes impacting the pulverized coal pipe from a preset audio database, corresponding to the wind speed and pulverized coal concentration data; analyzing the audio data based on the audio feature values ​​to obtain the proportion of pulverized coal of different particle sizes at each audio probe within the preset time range; and calculating the average fineness of the pulverized coal in the pulverized coal pipe based on the proportion of pulverized coal of different particle sizes at each audio probe. This invention calculates the fineness of pulverized coal by statistically analyzing the audio data of pulverized coal of different particle sizes impacting the pulverized coal pipe within a preset time range to obtain the quantity of pulverized coal of different particle sizes. It is applicable to various types of coal mills and offers fast analysis speed and high accuracy.

Description

Technical Field

[0001] This invention relates to the field of thermal power generation technology, specifically to a method, apparatus, and electronic equipment for analyzing the fineness of pulverized coal. Background Technology

[0002] A coal mill is a key piece of equipment for further pulverizing materials after they have been crushed. Since burning pulverized coal improves combustion efficiency, most thermal power plants use coal mills to process raw coal into pulverized coal, ensuring complete combustion. The main function of a coal mill in a thermal power plant is to first feed raw coal from the coal hopper into the mill and grind it into pulverized coal. Then, the pulverized coal is blown into the exhaust fan by hot air via a conveyor belt and enters the boiler furnace for combustion. The fineness of the pulverized coal grinding during operation directly affects the quality of combustion in the power plant. After grinding, the pulverized coal is blown into the boiler by hot air. The hot flue gas generated after the pulverized coal is fully combusted in the boiler releases heat as it flows along the boiler, followed by ash separation. Higher grinding efficiency and finer grinding in the coal mill facilitate more complete combustion of the pulverized coal in the boiler, thereby improving coal utilization and reducing the potential for environmental pollution caused by incomplete combustion.

[0003] In existing technologies, the mill outlet air velocity and coal powder concentration in thermal power plants have been measured online in real time. However, the existing method of obtaining coal powder fineness by measuring the audio characteristics at a specific time point and then referring to a corresponding relationship table cannot be applied to different models of equipment. Each model of equipment requires testing to obtain the corresponding relationship table, which increases the amount of calculation and the difficulty of application. If multiple models of equipment use the same relationship table, there may be differences in the influencing factors between the relationship table and different equipment, resulting in errors between the coal powder fineness matched by the relationship table and the actual situation. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a method for analyzing the fineness of pulverized coal to solve the problem of poor accuracy in the fineness analysis of pulverized coal in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] This invention provides a method for analyzing the fineness of pulverized coal, comprising:

[0007] Acquire data on the target coal mill model and the wind speed inside the pulverized coal pipe, pulverized coal concentration, and audio data from multiple audio probes within a preset time range;

[0008] Based on the target coal mill model, select audio characteristic values ​​of coal powder of different particle sizes impacting the coal powder pipe from a preset audio database, corresponding to the wind speed data and the coal powder concentration data;

[0009] Based on the audio feature values, the audio data is analyzed to obtain the proportion of coal powder at different particle size ranges at each audio probe within the preset time range;

[0010] The average fineness of the coal powder in the coal powder tube is calculated based on the proportion of coal powder in different particle size ranges at each audio probe.

[0011] Optionally, the step of analyzing the audio data based on the audio feature values ​​to obtain the proportion of coal powder at different particle size ranges at each audio probe within the preset time range includes:

[0012] Feature extraction is performed on the audio data to obtain the impact feature value of each coal powder particle impact within the preset time range;

[0013] The impact feature value is compared with the audio feature value to obtain the particle size information of coal powder at each audio probe.

[0014] The particle size information is analyzed to obtain the proportion of coal powder in different particle size ranges at each audio probe.

[0015] Optionally, comparing the impact feature value with the audio feature value to obtain the particle size information of coal powder at each audio probe includes:

[0016] Cluster analysis is performed on the impact feature values ​​to obtain multiple sets of impact feature categories;

[0017] Based on the preset particle size range and the audio feature values ​​corresponding to the coal powder impacting the coal powder tube within different particle size ranges, the audio feature range corresponding to different particle size ranges is obtained.

[0018] Calculate the feature mean of each impact feature set based on the impact feature values ​​within the impact feature set;

[0019] The average value of the features is compared with the range of the audio features to obtain the granularity range of each impact feature set;

[0020] Granularity information is obtained by statistically analyzing the granularity range of multiple impact feature sets.

[0021] Optionally, the step of analyzing the particle size information to obtain the proportion of coal powder in different particle size ranges at each audio probe includes:

[0022] The total number of coal powder particles is obtained by counting the number of impact characteristic values.

[0023] The particle value of coal powder within each particle size range is obtained by counting the number of impact feature values ​​in each impact feature set.

[0024] The proportion of coal powder in different particle size ranges is calculated based on the particle size of coal powder within each particle size range and the total number of coal powder particles.

[0025] Optionally, the calculation of the average fineness of the coal powder in the coal powder tube based on the proportion of coal powder in different particle size ranges at each audio probe includes:

[0026] The fineness of the coal powder at each audio probe is calculated based on the proportion of coal powder with different particle size ranges at each audio probe.

[0027] The average fineness of the coal powder at each audio probe is calculated by averaging the fineness of the coal powder in the coal powder tube.

[0028] Optionally, before averaging the coal powder fineness at each audio probe, the method further includes:

[0029] The fineness of the coal powder at each audio probe is corrected according to a preset correction factor.

[0030] Optionally, the method further includes:

[0031] The first set of coal powder fineness was obtained by measuring the coal powder fineness at each audio probe under the same wind speed and different coal powder concentration conditions.

[0032] By determining the fineness of coal powder through coal powder testing at various audio probes under the same coal powder concentration but different wind speeds, a second set of coal powder fineness was obtained.

[0033] The coal powder fineness data in the first coal powder fineness set and the second coal powder fineness set are compared with the corresponding determined coal powder fineness to obtain the correction coefficient of each audio probe under different wind speed and coal powder concentration conditions.

[0034] This invention also provides a coal powder fineness analysis device, comprising:

[0035] The acquisition module is used to acquire data on the target coal mill model and the wind speed inside the coal powder pipe, coal powder concentration data, and audio data from multiple audio probes within a preset time range;

[0036] The extraction module is used to select audio feature values ​​of coal powder of different particle sizes impacting the coal powder tube from a preset audio database according to the target coal mill model;

[0037] The analysis module is used to analyze the audio data based on the audio feature values ​​to obtain the proportion of coal powder at different particle size ranges at each audio probe within the preset time range;

[0038] The calculation module is used to calculate the average fineness of the coal powder in the coal powder tube based on the proportion of coal powder in different particle size ranges at each audio probe.

[0039] This invention also provides an electronic device, comprising:

[0040] The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes these computer instructions to perform the coal powder fineness analysis method provided in this embodiment of the invention.

[0041] This invention also provides a computer-readable storage medium storing computer instructions for causing a computer to execute the coal powder fineness analysis method provided in this invention.

[0042] The technical solution of this invention has the following advantages:

[0043] This invention provides a method for analyzing the fineness of pulverized coal. It involves acquiring data on the target coal mill model, wind speed within the pulverized coal tube, pulverized coal concentration, and audio data from multiple audio probes within a preset time range. Based on the target coal mill model, it selects audio characteristic values ​​from a preset audio database corresponding to the wind speed and pulverized coal concentration data, representing the impact of pulverized coal of different particle sizes onto the pulverized coal tube. The audio data is then analyzed based on these audio characteristic values ​​to obtain the proportion of pulverized coal of different particle sizes at each audio probe within the preset time range. Finally, the average fineness of the pulverized coal in the pulverized coal tube is calculated based on the proportion of pulverized coal of different particle sizes at each audio probe. Since the audio characteristics of pulverized coal of different particle sizes impacting the pulverized coal tube differ, this invention calculates the fineness of the pulverized coal by statistically analyzing the audio data of pulverized coal of different particle sizes impacting the pulverized coal tube within a preset time range to obtain the quantity of pulverized coal of different particle sizes. This method is applicable to various types of coal mills and offers fast analysis speed and high accuracy. Attached Figure Description

[0044] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0045] Figure 1 This is a flowchart of the coal powder fineness analysis method in an embodiment of the present invention;

[0046] Figure 2 This is a schematic diagram showing the distribution of audio probe positions in an embodiment of the present invention;

[0047] Figure 3 This is a flowchart illustrating the analysis of the proportion of coal powder in different particle size ranges according to an embodiment of the present invention;

[0048] Figure 4 This is a flowchart illustrating the analysis of coal powder particle size information at each audio probe according to an embodiment of the present invention;

[0049] Figure 5 This is a flowchart illustrating the process of analyzing the proportion of coal powder at different particle size ranges at each audio probe according to an embodiment of the present invention.

[0050] Figure 6 This is a flowchart for calculating the average fineness of pulverized coal in a pulverized coal pipe according to an embodiment of the present invention;

[0051] Figure 7 A flowchart illustrating the process of obtaining the correction coefficients for each audio probe under different wind speeds and coal dust concentrations according to an embodiment of the present invention;

[0052] Figure 8 This is a schematic diagram of the coal powder fineness analysis device in an embodiment of the present invention;

[0053] Figure 9 This is a schematic diagram of the structure of an electronic device in an embodiment of the present invention. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0055] According to an embodiment of the present invention, a method for analyzing the fineness of pulverized coal is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0056] This embodiment provides a method for analyzing the fineness of pulverized coal, which can be used in the aforementioned terminal devices, such as computers, etc. Figure 1 As shown, the method for analyzing the fineness of pulverized coal includes the following steps:

[0057] Step S1: Obtain the target coal mill model and the wind speed data, coal powder concentration data, and audio data from multiple audio probes 2 within a preset time range in the coal powder pipe 1.

[0058] Specifically, the audio data is obtained by collecting audio vibration signals from the impact of pulverized coal at the bend of the pulverized coal pipe 1 at the outlet of the coal mill within a certain time range during the operation of the pipe. The audio probe 2 is installed on the outer wall of the bend of the pulverized coal pipe 1, away from the center of the bend. The bend of the pulverized coal pipe 1 refers to the curved pulverized coal pipe 1 at the outlet of the coal mill in the thermal power plant; it can be a 90-degree bend or other bending angles. Figure 2 As shown, the distribution positions of the audio probes 2 are determined according to the following rules:

[0059] ①For example Figure 2 As shown, a plane is defined by O and the arc of the elbow center, which is the center plane (XOY) of the elbow. Audio probes 2 are symmetrically distributed around this center plane.

[0060] ②The audio probe 2 is located at the intersection of an arc centered at O ​​and a plane that forms a fixed angle with 0X and is perpendicular to the central plane (XOY).

[0061] ③ The number of audio probes 2 can be adjusted according to the measurement accuracy requirements. The higher the accuracy requirement, the greater the density of the audio probes 2 arranged outside the elbow, resulting in more collected and representative audio signals. Among them, the density of probes on the outer ring surface of the elbow has the greatest impact on measurement accuracy.

[0062] Step S2: Based on the target coal mill model, select audio feature values ​​of coal powder impacting the coal powder tube 1 with different particle sizes corresponding to the wind speed data and coal powder concentration data from a preset audio database. Specifically, since the coal powder tube 1 of different coal mill models may have different materials and wall thicknesses, it will affect the vibration emitted by the coal powder impacting the coal powder tube 1, thereby affecting the audio data collected by the audio probe 2; therefore, a database is established in advance to store the audio feature values ​​of coal powder impacting the coal powder tube 1 of various coal mill models under different wind speeds and coal powder concentrations. When needed, the audio feature values ​​of coal powder impacting the coal powder tube 1 with different particle sizes under the current wind speed and coal powder concentration conditions can be directly extracted according to the model of the target coal mill coal powder tube 1.

[0063] Step S3: Analyze the audio data based on audio feature values ​​to obtain the proportion of coal dust at each audio probe 2 with different particle size ranges within a preset time range. Specifically, since coal dust of different particle sizes will generate audio signals with specific frequency characteristics when colliding with the bend of the coal dust pipe 1 at different wind speeds, the particle size of each coal dust that makes an impact can be obtained by comparison. Dividing the particle size range can group coal dust within a certain particle size range into the same category, thereby reducing the amount of calculation and improving the calculation efficiency of real-time monitoring of coal dust fineness.

[0064] Step S4: Calculate the average fineness of the coal powder in coal powder pipe 1 based on the proportion of coal powder with different particle size ranges at each audio probe 2. Specifically, the analysis process of this scheme does not focus on the mixed vibration signal of all coal powder impacting the pipe after mixing. Instead, by statistically analyzing the number of coal powder particles with different characteristic particle sizes impacting coal powder pipe 1 over a period of time, the percentage of coal powder with various finenesses can be calculated, and thus the average fineness of the coal powder can be calculated, which has high accuracy.

[0065] Since the audio characteristics of coal powder with different particle sizes impacting the coal powder tube 1 are different, according to the above steps S1 to S4, the coal powder fineness analysis method provided in this embodiment of the invention obtains the quantity of coal powder with different particle sizes by statistically analyzing the audio data of coal powder with different particle size ranges impacting the coal powder tube 1 within a preset time range, thereby calculating the coal powder fineness. It can be applied to a variety of different types of coal mills, and the analysis speed is fast and the accuracy is high.

[0066] Specifically, in one embodiment, step S3 described above is as follows: Figure 3 As shown, the specific steps include the following:

[0067] Step S31: Extract features from the audio data to obtain the impact feature value of each coal powder particle impact within a preset time range. Specifically, since coal powder of different particle sizes will generate audio signals with specific frequency characteristics when colliding with the bend of coal powder pipe 1 under different wind speeds and coal powder concentrations, the impact feature value of each coal powder particle impact can be obtained by analyzing the audio data.

[0068] Step S32: Compare the impact feature value with the audio feature value to obtain the particle size information of coal powder at each audio probe. Specifically, by comparing the audio feature value of coal powder impacting different particle sizes in the database, the particle size information of coal powder at each audio probe can be accurately obtained.

[0069] Step S33: Analyze the particle size information to obtain the proportion of coal dust in different particle size ranges at each audio probe 2. Specifically, since coal dust of different particle sizes will generate audio signals with specific frequency characteristics when colliding with the bend of the coal dust pipe 1 at different wind speeds, the particle size of each coal dust that makes an impact can be obtained by comparison. Dividing the particle size range can group coal dust within a certain particle size range into the same category, thereby reducing the amount of calculation and improving the calculation efficiency of real-time monitoring of coal dust fineness.

[0070] Specifically, in one embodiment, step S32 described above is as follows: Figure 4 As shown, the specific steps include the following:

[0071] Step S321: Perform cluster analysis on the impact feature values ​​to obtain multiple sets of impact feature categories. Specifically, cluster analysis can be performed on the pile diameter feature values ​​based on the median aperture of a standard sieve. For example, standard sieve apertures include 200, 120, 90, 75, and 65 micrometers. Impact feature values ​​can be clustered using 160, 105, 82.5, and 70 micrometers to obtain multiple sets of impact feature values. The impact feature values ​​within each set tend to be related to the median aperture, facilitating subsequent classification.

[0072] Step S322: Based on the preset particle size range and the audio characteristic values ​​corresponding to the impact of coal powder on the coal powder pipe 1 within different particle size ranges, the audio characteristic range corresponding to different particle size ranges is obtained. Specifically, for example, the audio characteristic values ​​can be divided into 6 preset particle size ranges, with the aperture of a standard sieve as the boundary: above 200, 120-200, 90-120, 75-90, 65-75, and below 65.

[0073] Step S323: Calculate the mean value of each impact feature set based on the impact feature values ​​within the impact feature set. Specifically, calculating the mean value facilitates subsequent comparisons and reveals the granularity of each set.

[0074] Step S324: Compare the mean value of the features with the range of the audio features to obtain the particle size range of each impact feature set. Specifically, by comparison, the mean particle size of coal powder within each impact feature set can be obtained.

[0075] Step S325: Statistically analyze the particle size ranges of multiple impact feature sets to obtain particle size information. Specifically, the particle size information includes the average particle size of coal powder within each impact feature set. By using cluster analysis and then comparing the average values, it is unnecessary to compare the impact feature values ​​of each coal powder particle, greatly reducing the computational load and improving the analysis speed.

[0076] Specifically, in one embodiment, step S33 described above is as follows: Figure 5 As shown, the specific steps include the following:

[0077] Step S331: Count the number of impact feature values ​​to obtain the total number of coal powder particles.

[0078] Step S332: Count the number of impact feature values ​​in each impact feature set to obtain the particle value of coal powder in each particle size range.

[0079] Step S333: Calculate the proportion of coal powder in different particle size ranges based on the particle size value of coal powder and the total number of coal powder particles in each particle size range.

[0080] Specifically, statistical analysis was used to obtain the proportion of coal powder at different particle size ranges at each of the two audio probes, which facilitates subsequent analysis and calculation of the average fineness of coal powder in the coal powder tube 1.

[0081] Specifically, in one embodiment, step S4 described above is as follows: Figure 6 As shown, the specific steps include the following:

[0082] Step S41: Calculate the fineness of the coal powder at each audio probe 2 based on the proportion of coal powder in different particle size ranges at each audio probe 2.

[0083] Step S42: Average the coal powder fineness at each audio probe 2 to obtain the average coal powder fineness of coal powder tube 1.

[0084] Specifically, the calculation method for average coal powder fineness is as follows:

[0085] Assuming audio probe 2 is numbered N, analyze different granularities (X) N1 -X NN The percentage is a. N1 -a NN The average fineness of pulverized coal is:

[0086] Y N =a N1 *X N1 +a N2 *X N2 +…+a NN *X NN .

[0087] By statistically analyzing the number of coal powder particles of different sizes impacting the coal powder tube 1, the percentage of coal powder of various finenesses can be calculated, and then the average coal powder fineness can be calculated with high accuracy.

[0088] Specifically, in one embodiment, before step S42 described above, the following steps are further included:

[0089] The fineness of the coal powder at each audio probe 2 is corrected according to a preset correction coefficient. Specifically, when the wind speed is constant, the percentage of different audio signals measured at the same audio probe 2 will change with the coal powder concentration for the same fineness. Similarly, when the coal powder concentration is constant, the percentage of different audio signals measured at the same audio probe 2 will also change with the wind speed for the same fineness. Correcting each probe effectively improves the final calculation accuracy. Correction is performed using a weighted calculation method. For example, assuming the average fineness of the coal powder in coal powder pipe 1 is Y, and the average fineness values ​​obtained from each audio probe 2 are Y1-YN, with correction coefficients §1-§N for each probe, then the weighted value for the average fineness Y of coal powder in coal powder pipe 1 is:

[0090] Y=(§1·Y1+§2·Y2+…+§N·YN) / N.

[0091] Specifically, in one embodiment, the aforementioned preset correction coefficient, such as Figure 7 As shown, it is obtained through the following steps:

[0092] Step S401: By determining the coal powder fineness at each audio probe 2 under the same wind speed and different coal powder concentration conditions, the first coal powder fineness set is obtained.

[0093] Step S402: By determining the coal powder fineness at each audio probe 2 under the same coal powder concentration but different wind speed conditions, a second coal powder fineness set is obtained.

[0094] Step S403: Compare the coal powder fineness data in the first coal powder fineness set and the second coal powder fineness set with the corresponding determined coal powder fineness to obtain the correction coefficient of each audio probe 2 under different wind speed and coal powder concentration conditions.

[0095] Specifically, the correction coefficients §1-§N at each probe were obtained experimentally, and the method of obtaining them is as follows:

[0096] First, given a fixed coal powder fineness, select K groups of wind velocities V1-V K Then determine the coal powder concentration M1-M in group L. L By measuring the average coal powder fineness at each probe at every combination of wind speed and coal powder concentration, the correction coefficient § at each point under different wind speeds and coal powder concentrations at the current coal powder fineness can be calculated. The calculation formula is § = Y / Y N Where Y represents the actual dust fineness, Y NThe average fineness of the coal powder is obtained through audio analysis of the selected probes. N sets of probes can yield N sets of coefficient comparison tables. As the fineness of the coal powder changes, each fineness corresponds to N sets of comparison tables. Assuming there are Q sets of typical coal powder fineness, each probe will have Q sets of comparison tables.

[0097] The comparison table is shown in Table 1:

[0098] Table 1

[0099] <![CDATA[V1]]> <![CDATA[V2]]> … <![CDATA[V K ]]> <![CDATA[M1]]> <![CDATA[§ 11 ]]> <![CDATA[§ 12 ]]> … <![CDATA[§ 1K ]]> <![CDATA[M2]]> <![CDATA[§ 21 ]]> <![CDATA[§ 22 ]]> … <![CDATA[§ 2K ]]> … … … … … <![CDATA[M L ]]> <![CDATA[§ L1 ]]> <![CDATA[§ L2 ]]> … <![CDATA[§ LK ]]>

[0100] A total of N*Q sets of data can be obtained, with Q sets of data for each probe.

[0101] In the actual measurement process, after determining the average concentration measured at a specific probe, the correction factor is looked up in the reference table of the closest average concentration for that probe. If the actual wind speed and pulverized coal concentration fall between two wind speeds and pulverized coal concentrations in the reference table, the correction factor is determined using the closest wind speed and pulverized coal concentration. The correction factors for all probes are determined in this way, thereby obtaining the average pulverized coal fineness of the entire pulverized coal pipe 1.

[0102] This embodiment also provides a coal powder fineness analysis device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0103] This embodiment provides a coal powder fineness analysis device, such as... Figure 8 As shown, it includes:

[0104] The acquisition module 101 is used to acquire wind speed data, coal powder concentration data, and audio data from multiple audio probes 2 within a preset time range in the coal powder pipe 1 of the target coal mill. For details, please refer to the relevant description of step S1 in the above method embodiment, which will not be repeated here.

[0105] The extraction module 102 is used to select audio feature values ​​of coal powder of different particle sizes impacting the coal powder pipe 1 from a preset audio database according to the target coal mill model and the wind speed data and coal powder concentration data. For details, please refer to the relevant description of step S2 in the above method embodiment, which will not be repeated here.

[0106] Analysis module 103 is used to analyze audio data based on audio feature values ​​to obtain the proportion of coal powder at two different particle size ranges at each audio probe within a preset time range. For details, please refer to the relevant description of step S3 in the above method embodiment, which will not be repeated here.

[0107] The calculation module 104 is used to calculate the average fineness of the coal powder in the coal powder tube 1 based on the proportion of coal powder in different particle size ranges at each audio probe 2. For details, please refer to the relevant description of step S4 in the above method embodiment, which will not be repeated here.

[0108] In this embodiment, the coal powder fineness analysis device is presented in the form of a functional unit. Here, a unit refers to an ASIC circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0109] Further functional descriptions of the above modules are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0110] According to embodiments of the present invention, an electronic device is also provided, such as... Figure 9 As shown, the electronic device may include a processor 901 and a memory 902, wherein the processor 901 and the memory 902 may be connected via a bus or other means. Figure 9 Taking the example of a connection between China and Israel via a bus.

[0111] Processor 901 can be a Central Processing Unit (CPU). Processor 901 can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations of the above types of chips.

[0112] The memory 902, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the methods in the method embodiments of the present invention. The processor 901 executes various functional applications and data processing of the processor by running the non-transitory software programs, instructions, and modules stored in the memory 902, thereby implementing the methods in the above method embodiments.

[0113] The memory 902 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created by the processor 901, etc. Furthermore, the memory 902 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 902 may optionally include memory remotely located relative to the processor 901, and these remote memories may be connected to the processor 901 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0114] One or more modules are stored in memory 902 and, when executed by processor 901, perform the methods described in the above method embodiments.

[0115] The specific details of the aforementioned electronic device can be understood by referring to the relevant descriptions and effects in the above method embodiments, and will not be repeated here.

[0116] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium can also include combinations of the above types of memory.

[0117] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for analyzing the fineness of pulverized coal, characterized in that, include: Acquire data on the target coal mill model and the wind speed inside the pulverized coal pipe, pulverized coal concentration, and audio data from multiple audio probes within a preset time range; Based on the target coal mill model, select audio characteristic values ​​of coal powder of different particle sizes impacting the coal powder pipe from a preset audio database, corresponding to the wind speed data and the coal powder concentration data; Based on the audio feature values, the audio data is analyzed to obtain the proportion of coal powder at different particle size ranges at each audio probe within the preset time range; The average fineness of the coal powder in the coal powder tube is calculated based on the proportion of coal powder in different particle size ranges at each audio probe. The step of analyzing the audio data based on the audio feature values ​​to obtain the proportion of coal powder at different particle size ranges at each audio probe within the preset time range includes: Feature extraction is performed on the audio data to obtain the impact feature value of each coal powder particle impact within the preset time range; The impact feature value is compared with the audio feature value to obtain the particle size information of coal powder at each audio probe. The particle size information was analyzed to obtain the proportion of coal powder in different particle size ranges at each audio probe. The step of comparing the impact feature value with the audio feature value to obtain the particle size information of coal powder at each audio probe includes: Cluster analysis is performed on the impact feature values ​​to obtain multiple sets of impact feature categories; Based on the preset particle size range and the audio feature values ​​corresponding to the coal powder impacting the coal powder tube within different particle size ranges, the audio feature range corresponding to different particle size ranges is obtained. Calculate the feature mean of each impact feature set based on the impact feature values ​​within the impact feature set; The average value of the features is compared with the range of the audio features to obtain the granularity range of each impact feature set; Granularity information is obtained by statistically analyzing the granularity range of multiple impact feature sets.

2. The method for analyzing the fineness of pulverized coal according to claim 1, characterized in that, The step of analyzing the particle size information to obtain the proportion of coal powder in different particle size ranges at each audio probe includes: The total number of coal powder particles is obtained by counting the number of impact characteristic values. The particle value of coal powder within each particle size range is obtained by counting the number of impact feature values ​​in each impact feature set. The proportion of coal powder in different particle size ranges is calculated based on the particle size of coal powder within each particle size range and the total number of coal powder particles.

3. The method for analyzing the fineness of pulverized coal according to claim 1, characterized in that, The calculation of the average fineness of the coal powder in the coal powder tube based on the proportion of coal powder in different particle size ranges at each audio probe includes: The fineness of the coal powder at each audio probe is calculated based on the proportion of coal powder with different particle size ranges at each audio probe. The average fineness of the coal powder at each audio probe is calculated by averaging the fineness of the coal powder in the coal powder tube.

4. The method for analyzing the fineness of pulverized coal according to claim 3, characterized in that, Before averaging the coal powder fineness at each audio probe, the method further includes: The fineness of the coal powder at each audio probe is corrected according to a preset correction factor.

5. The method for analyzing the fineness of pulverized coal according to claim 4, characterized in that, The method further includes: The first set of coal powder fineness was obtained by measuring the coal powder fineness at each audio probe under the same wind speed and different coal powder concentration conditions. By determining the fineness of coal powder through coal powder testing at various audio probes under the same coal powder concentration but different wind speeds, a second set of coal powder fineness was obtained. The coal powder fineness data in the first coal powder fineness set and the second coal powder fineness set are compared with the corresponding determined coal powder fineness to obtain the correction coefficient of each audio probe under different wind speed and coal powder concentration conditions.

6. A coal powder fineness analysis device, characterized in that, include: The acquisition module is used to acquire data on the target coal mill model and the wind speed inside the coal powder pipe, coal powder concentration data, and audio data from multiple audio probes within a preset time range; The extraction module is used to select audio feature values ​​of coal powder of different particle sizes impacting the coal powder tube from a preset audio database according to the target coal mill model; The analysis module is used to analyze the audio data based on the audio feature values ​​to obtain the proportion of coal powder at different particle size ranges at each audio probe within the preset time range; The calculation module is used to calculate the average fineness of the coal powder in the coal powder tube based on the proportion of coal powder in different particle size ranges at each audio probe. Specifically, the analysis module is used to: extract features from the audio data to obtain impact feature values ​​of each coal powder particle impact within the preset time range; compare the impact feature values ​​with the audio feature values ​​to obtain the particle size information of coal powder at each audio probe; and analyze the particle size information to obtain the proportion of coal powder in different particle size ranges at each audio probe. The analysis module is further configured to: perform cluster analysis on the impact feature values ​​to obtain multiple impact feature sets; obtain audio feature ranges corresponding to different particle size ranges based on preset particle size ranges and audio feature values ​​corresponding to coal powder impacting coal powder pipes within different particle size ranges; calculate the feature mean of each impact feature set based on the impact feature values ​​within the impact feature sets; compare the feature mean with the audio feature ranges to obtain the particle size range of each impact feature set; and statistically analyze the particle size ranges of multiple impact feature sets to obtain particle size information.

7. An electronic device, characterized in that, include: A memory and a processor are interconnected, the memory storing computer instructions, and the processor executing the computer instructions to perform the coal powder fineness analysis method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the coal powder fineness analysis method according to any one of claims 1-5.

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