Boiler secondary air bellow additionally-installed ash removal device and method thereof

Abstract

The invention relates to the technical field of secondary air bellow ash removal devices, in particular to a boiler secondary air bellow additionally-installed ash removal device and a method thereof.The boiler secondary air bellow additionally-installed ash removal device comprises a nozzle pipe and a branch pipe arranged in the nozzle pipe, two baffle rings are fixed in the nozzle pipe, and a plurality of through holes are formed in the middles of the two baffle rings; branch pipes are fixed between the through holes in the upper end and the lower end; the branch pipes are obliquely arranged between the baffle rings, and six groups of through holes are arranged in an equidistant array; the bottom ends of the nozzle pipes are connected with the air guide pipes, the outer sides of the air guide pipes are communicated with the primary air mother pipe, and the primary air mother pipe is communicated with an external high-pressure air source and is aligned with accumulated dust at the dead corners of the box body for blowing. 6-8 special nozzles are arranged on each air guide pipe between the two main pipes and are downwards aligned to the lower part for blowing, the nozzles are mainly used for enabling sprayed airflow to rotate to a certain degree, accumulated dust at the bottom of a secondary air bellow can be better driven, and the accumulated dust can be taken away and removed again along with secondary air after being blown up.

Description

Technical Field

[0001] The present invention relates to the technical field of secondary air box ash cleaning devices, and particularly relates to an ash cleaning device installed on a boiler secondary air box and a method thereof. Background Art

[0002] Most of the existing secondary air boxes in steam turbine units have ash accumulation problems. The reasons are as follows: During operation, the secondary air from the air preheater will carry dust in the flue gas. Due to the large flow area and low wind speed of the secondary air, the dust-carrying capacity of the secondary air decreases, and some dust will deposit at the bottom of the secondary air box. As the boiler operates for a long time, the amount of dust accumulated at the bottom of the secondary air box will increase, resulting in the blockage of the bottom channel of the secondary air box, increasing the resistance of the secondary air box, causing uneven air volume distribution of the burners at the bottom of the front and rear walls, and large operating resistance, etc., leading to a decrease in the burner efficiency, seriously affecting the safe operation of the boiler unit, and also having a negative impact on the combustion efficiency, nitrogen oxide emissions, etc. The secondary air will exchange heat with the flue gas in the air preheater before entering the large air boxes of each layer of burners, and the flue gas carries about 90% of the coal ash in the coal. Due to ash accumulation on the heating surface of the air preheater, the secondary air passing through the air preheater will carry some coal ash.

[0003] To ensure that each burner receives basically the same air volume, the air distribution of each burner is uniform, and the flames inside the furnace are uniform. After the secondary air enters each layer of air boxes, the designed internal wind speed of the air box is relatively low, generally about 10 m / s, which can be regarded as a static pressure air box. Therefore, the coal ash carried by the secondary air will gradually deposit and accumulate at the bottom of the air box at a low wind speed. As the ash accumulation increases, the reduction of the flow area in the air box and the increase of the wind speed, the coal ash it carries will no longer deposit and reach a balance.

[0004] The ash accumulation in this air box is a common phenomenon, but a large amount of ash accumulation affects the air distribution of the burners, the stability of the flame detectors, the operation, the load-bearing of the air box, and the maintenance inside the air box after the boiler is shut down. It is necessary to clean the ash during the operation of the unit.

[0005] Due to the large amount of work for ash cleaning during boiler shutdown and the pollution of dust to the environment and construction personnel, technical measures for ash cleaning during operation are adopted to reduce ash accumulation and the amount of ash cleaning work;

[0006] To ensure the safety of the unit, achieve the goals of energy conservation, environmental protection, and improve the economic benefits of thermal power plants, and at the same time meet the requirements of the national dual-carbon goal, it is very necessary to retrofit the secondary air box system (6 layers) to prevent ash accumulation. Summary of the Invention

[0007] Technical Problems to be Solved

[0008] In view of the above-mentioned disadvantages of the prior art, the present invention provides a soot cleaning device and method for adding to a boiler secondary air box, which can effectively solve the problem of anti-ash accumulation transformation of the secondary air box system (6 layers) in the prior art.

[0009] Technical solution

[0010] To achieve the above objectives, the present invention is realized through the following technical solutions:

[0011] The present invention provides a soot cleaning device for adding to a boiler secondary air box, including a nozzle pipe and a branch pipe arranged inside the nozzle pipe. Two groups of retaining rings are fixed inside the nozzle pipe, and multiple groups of through holes are opened in the middle of the two groups of retaining rings. Branch pipes are fixed between the through holes at the upper and lower ends.

[0012] Further, the branch pipes are inclined between the retaining rings, and six groups of through holes are arranged in an equidistant array.

[0013] Further, the bottom end of the nozzle pipe is connected to a gas guide pipe. The outside of the gas guide pipe is in communication with the primary air main pipe, and the primary air main pipe is in communication with an external high-pressure air source. The nozzle pipe and the external gas guide pipe are arranged in an inclined manner.

[0014] Further, solenoid valve structures are arranged inside both the gas guide pipe and the primary air main pipe.

[0015] A method for adding a soot cleaning device to a boiler secondary air box, including a soot cleaning device for adding to a boiler secondary air box, and the steps are as follows:

[0016] Step 1: Divide the air box into multiple detection areas according to different distribution positions, and obtain the ash accumulation data of each detection area. The ash accumulation data includes historical ash thickness data and ash accumulation time data in a day. The time interval in the time data is 1 h;

[0017] Step 2: Analyze based on the ash accumulation state in each detection area, mark the results as areas prone to ash accumulation and areas not prone to ash accumulation. According to the time information, mark the watermark as a picture, and merge it into a picture set of areas prone to ash accumulation and a picture set of areas not prone to ash accumulation, and calculate the proportion sp of the ash accumulation area in the detection area;

[0018] Step 3: In the picture set of areas prone to ash accumulation, extract the gray values of this area and the historical ash accumulation area image set, and perform conversion to convert the color image into a gray image to form two groups of gray value pixel matrix sets. Then, perform a comparison and gray-level co-occurrence matrix (GLCM) model analysis, extract texture features, output two groups of P(i,j) values, and draw a time (h)-gray (g) line chart of the two groups of picture sets in chronological order;

[0019] Step 4: Fuse according to the two sequence values of the output P(i,j) value and the time information data to obtain the deviation coefficient S, and construct a standard deviation function.

[0020]

[0021] Among them, S represents the standard deviation (%), n represents the total number of data or the number of measurements. Generally, the number of n is not less than 40, and i represents each measured value. Obtain S_easy: the standard deviation value of the easy-to-accumulate ash area and S_history: the standard deviation value of the historical ash-accumulation area. Perform time-domain aggregation analysis on S_easy and S_history respectively. Taking S_easy as an example: obtain the first easy-to-accumulate ash reference interval and the second easy-to-accumulate ash reference interval of S_easy. The two are adjacent time zones. If the loss values of the first easy-to-accumulate ash reference interval and the second easy-to-accumulate ash reference interval are not greater than the standard deviation value, then merge the first easy-to-accumulate ash reference interval and the second easy-to-accumulate ash reference interval into an aggregated ash-accumulation interval, and repeat the loop analysis. Stop the aggregation when S_easy of any adjacent time zones is greater than the standard deviation ash-accumulation threshold, and output the S_easy time-series information. Similarly, obtain the S_history time-series information.

[0022] Step 5: Perform data analysis on the S_easy time-series information and the S_history time-series information, calculate the time ratio of the aggregated ash-accumulation interval and each combined ash-accumulation reference time zone respectively, and set it as the time zone weight value. Perform weighted mean analysis on each aggregated ash-accumulation interval to obtain the temperature ash-accumulation value within the aggregated time zone group. Similarly, obtain the aggregated time zone ash-accumulation time-series information, and compare it with the deviation threshold according to the aggregated time zone ash-accumulation time-series information. If it is not less than the deviation threshold, it means that the blowing power needs to be increased at this position during this time period. If it is less than the deviation threshold, it means that there is no need to increase the power at this position during this time.

[0023] Further, in Step 3, the gray value conversion method for converting a color image to a gray image adopts the weighted average method, Y = 0.299R + 0.587G + 0.114R (where R, G, and B are the values of the red, green, and blue channels of the color image respectively, and Y is the gray value). The texture features include contrast, correlation, energy, and entropy.

[0024] Further, in the gray-level co-occurrence matrix model in Step 3, the side length of the two groups of gray value pixel matrix sets is Ng. Mark the picture set of the easy-to-accumulate ash area as t, and the image set of the historical ash-accumulation area as T. P(i,j) = #{(x1,y1),(x2,y2)∈M×N|f(x1,y1)=i,f(x2,y2)=j};

[0025] Let #(x) denote the number of elements in set x. Obviously, P is an Ng×Ng matrix. If the distance between (x1, y1) and (x2, y2) is d, and the angles between them and the horizontal axis of the coordinate are θ, then the gray-level co-occurrence matrix P(i, j, d, θ) for various spacings and angles can be obtained. If the gray levels of the image are defined as N levels, then the co-occurrence matrix is an N×N matrix, which can be expressed as M(Δx, Δy)(h, k). The meaning is that the value mhk of the element located at (h, k) represents the number of occurrences of a pair of pixels with a distance of (Δx, Δy) and gray levels of h and k respectively. Analyzing the result P value, for the area of coarse texture, the mhk values of its gray-level co-occurrence matrix are more concentrated near the main diagonal. For coarse texture, pixel pairs tend to have the same gray level. For the area of fine texture, the mhk values in its gray-level co-occurrence matrix are scattered everywhere.

[0026] Advantageous Effects

[0027] The technical solution provided by the present invention has the following advantageous effects compared with the known public technology:

[0028] In the present invention, special nozzles are added at the positions where each secondary air box is prone to ash accumulation. The main pipes at both ends in the box body with special nozzles are designed to have 40 - 60 nozzles per row. The special nozzles (tilted at 45°) are aimed at the ash accumulation at the dead corners of the box body for purging. 6 - 8 special nozzles are arranged on each air duct between the two main pipes, aiming downward at the bottom for purging. The main function of the nozzles is to make the ejected air flow have a certain rotation, which can better drive the ash accumulation at the bottom of the secondary air box. After the ash is blown up, it can be taken away and removed along with the secondary air again.

[0029] In the ash cleaning method of this device, the area is divided, and watermarks are marked through detection time points. First, gray-scale conversion is performed to form a set of gray-scale value pixel matrices, then gray-level co-occurrence matrix model analysis is carried out to extract texture values, and two groups of P values are obtained. They are fused with time data, marked as the deviation coefficient S, and the standard deviation value is calculated through the standard deviation function. Finally, according to the time interval, time-domain aggregation analysis is carried out and analyzed with the deviation threshold. According to the deviation magnitude of the data, the output power of the fan within this time is adjusted to achieve the effect of increasing the fan output at a specific time and reducing the problem of dust accumulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0031] Figure 1 Schematic structural diagram of the nozzle of the present invention;

[0032] Figure 2 Structural sectional view of the nozzle of the present invention;

[0033] Figure 3 Schematic structural diagram of the soot blowing pipeline system of the large air box in the present invention;

[0034] Figure 4 Structural sectional view of the layout of the purging device in the present invention;

[0035] Figure 5 Layout diagram of the on - line soot cleaning pipeline in the secondary air box in the present invention;

[0036] Figure 6 CFD simulation calculation diagram of the secondary air box in the present invention;

[0037] Figure 7 Flow chart of the steps in the present invention.

[0038] The reference numerals in the figure respectively represent: 1, nozzle pipe; 2, retaining ring; 3, branch pipe; 4, air guide pipe; 5, primary air main pipe. Specific implementation mode

[0039] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0040] The present invention will be further described below with reference to the embodiments.

[0041] Embodiment 1: A soot cleaning device and method for retrofitting a boiler secondary air box, referring to the attached Figure 1 - attached Figure 4, including a nozzle pipe 1 and a branch pipe 3 arranged inside the nozzle pipe 1. Two groups of retaining rings 2 are fixed inside the nozzle pipe 1. A plurality of through holes are formed in the middle of each of the two groups of retaining rings 2, and a branch pipe 3 is fixed between the through holes at the upper and lower ends; the branch pipe 3 is inclined between the retaining rings 2, and six groups of through holes are arranged in an equidistant array. The bottom end of the nozzle pipe 1 is connected to a gas guide pipe 4. The outside of the gas guide pipe 4 is in communication with a primary air main pipe 5, and the primary air main pipe 5 is in communication with an external high-pressure air source. The nozzle pipe 1 and the external gas guide pipe 4 are arranged in an inclined manner; solenoid valve structures are arranged in both the gas guide pipe and the primary air main pipe; by adding a special nozzle pipe 1 at each position where ash is likely to accumulate in each secondary air box, the primary air main pipes 5 at both ends inside the box body with the special nozzle pipe 1 are designed to have 40 - 60 each row. The special nozzle pipe 1 (inclined at 45°) is aimed at the ash accumulation at the dead corners of the box body for purging. 6 - 8 special nozzle pipes 1 are arranged on each gas guide pipe 4 between the two primary air main pipes 5, aiming downward at the bottom for purging. The main function of the nozzle pipe 1 is to make the ejected air flow have a certain rotation, which can better drive the ash accumulation at the bottom of the secondary air box. After the ash is blown up, it can be taken away and removed again along with the secondary air.

[0042] Embodiment 2: Refer to the appendix Figure 5 - appendix Figure 7 , a method for adding ash cleaning to the secondary air box of a boiler, including an ash cleaning device for adding to the secondary air box of a boiler in Embodiment 1,

[0043] Step 1: Divide the air box into multiple detection areas according to different distribution positions, and obtain the ash accumulation data of each detection area. The ash accumulation data includes historical ash accumulation thickness data and ash accumulation time data in a day. The time interval in the time data is 1h;

[0044] Step 2: Analyze based on the ash accumulation state in each detection area, mark the results as easy - ash - accumulation areas and non - easy - ash - accumulation areas. According to the time information, mark it as a picture watermark, and merge it into an easy - ash - accumulation area picture set and a non - easy - ash - accumulation area picture set, and calculate the proportion sp of the ash - accumulation area in the detection area.

[0045] Step 3: In the easy - ash - accumulation area picture set, extract the gray - scale values of this area and the historical ash - accumulation area image set, and perform conversion to convert the color image into a gray - scale image, forming two groups of gray - scale value pixel matrix sets. Then, perform comparison and gray - level co - occurrence matrix (GLCM) model analysis, extract texture features, output two groups of P(i,j) values, and draw a time (h) - gray - scale (g) line chart of the two picture sets in chronological order.

[0046] Step 4: And fuse according to the two sequence values of the output P(i,j) value and the time information data to obtain a deviation coefficient S, and construct a standard deviation function.

[0047]

[0048] Among them, S represents the standard deviation (%), n represents the total number of data or the number of measurements. Generally, the number of n is not less than 40, and i represents each measured value; it is easy to obtain S_yi: the standard deviation value of the easy-to-accumulate ash area and S_li: the standard deviation value of the historical ash-accumulation area. Perform time-domain aggregation analysis on S_yi and S_li respectively. Taking S_yi as an example: obtain the first easy-to-accumulate ash reference interval and the second easy-to-accumulate ash reference interval of S_yi. The two are adjacent time zones. If the loss values of the first easy-to-accumulate ash reference interval and the second easy-to-accumulate ash reference interval are not greater than the standard deviation value, then merge the first easy-to-accumulate ash reference interval and the second easy-to-accumulate ash reference interval into an aggregated ash-accumulation interval, and repeat the loop analysis. Stop the aggregation when S_yi of any adjacent time zones is greater than the standard deviation ash-accumulation threshold, and output the S_yi time-series information. Similarly, obtain the S_li time-series information.

[0049] Step Five: Perform data analysis on the S_yi time-series information and the S_li time-series information, and calculate the time ratio of the aggregated ash-accumulation interval and each combined ash-accumulation reference time zone respectively, and set it as the time zone weight value. Perform weighted mean analysis on each of the aggregated ash-accumulation intervals to obtain the temperature ash-accumulation value within the aggregated time zone group. Similarly, obtain the aggregated time zone ash-accumulation time-series information, and compare it with the deviation threshold. If it is not less than the deviation threshold, it means that the blowing power needs to be increased at this position during this time period. If it is less than the deviation threshold, it means that there is no need to increase the power at this position during this time.

[0050] Embodiment Three: The gray value conversion method for converting a color image into a gray image adopts the weighted average method, Y = 0.299R + 0.587G + 0.114R (where R, G, and B are the values of the red, green, and blue channels of the color image respectively, and Y is the gray value). The texture features include contrast, correlation, energy, and entropy.

[0051] In the gray-level co-occurrence matrix model in Step Three, the side length of the two groups of gray value pixel matrix sets is Ng. Mark the picture set of the easy-to-accumulate ash area as t, and the image set of the historical ash-accumulation area as T.

[0052] P(i, j) = #{(x1, y1), (x2, y2) ∈ M × N|f(x1, y1) = i, f(x2, y2) = j};

[0053] Where #(x) represents the number of elements in set x. Obviously, P is a matrix of Ng×Ng. If the distance between (x1, y1) and (x2, y2) is d, and the angles between them and the horizontal axis of coordinates are θ, then the gray-level co-occurrence matrix P(i, j, d, θ) for various spacings and angles can be obtained. If the gray levels of the image are defined as N levels, then the co-occurrence matrix is an N×N matrix, which can be expressed as M(Δx, Δy)(h, k). The meaning is that the value of the element mhk at (h, k) represents the number of occurrences of a pixel pair with a gray level of h and another gray level of k and a distance of (Δx, Δy). Analyze the result P value. For the area of coarse texture, the mhk values of its gray-level co-occurrence matrix are more concentrated near the main diagonal. For coarse texture, the pixel pairs tend to have the same gray level. For the area of fine texture, the mhk values in its gray-level co-occurrence matrix are scattered everywhere; the ash cleaning method divides the area therein and marks the watermark through the detection time point. First, perform gray conversion to form a set of gray-value pixel matrices, then perform gray-level co-occurrence matrix model analysis, extract the texture values, obtain two groups of P values, fuse them with time data, mark them as the deviation coefficient S, calculate the standard deviation value through the standard deviation function, and finally, according to the time interval, perform time-domain aggregation analysis and analyze it with the deviation threshold. Adjust the output power of the fan within this time according to the deviation size of the data to achieve the effect of increasing the fan output at a specific time and reducing the problem of dust accumulation.

[0054] In actual operation, the single soot blowing device has a single soot blowing time of about 2 minutes (adjusted according to the ash accumulation situation and the soot blowing effect), and the recommended soot blowing cycle is once a week (adjusted according to the ash accumulation situation and the soot blowing effect).

[0055] To reduce the impact on combustion stability during soot blowing, etc., it is recommended to operate at medium and high loads; to smoothly implement this project during class maintenance, after the unit is shut down, the construction personnel need to clean the ash accumulation at the bottom of the wind box before implementation. The present invention cooperates with the structure of the inclined nozzle pipe 1 to improve the combustion effect of the boiler burner, save energy and improve efficiency, reduce ash dust during soot blowing, protect the environment, meet the requirements of national energy conservation and emission reduction, and promote the sustainable development of the ecological environment.

[0056] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the protection scope of the technical solutions of the embodiments of the present invention.

Claims

1. A boiler secondary wind box equipped with a dust cleaning device, characterized in that: It comprises a nozzle tube (1) and a branch tube (3) arranged in the nozzle tube (1), wherein two groups of retaining rings (2) are fixed inside the nozzle tube (1), a plurality of through holes are provided in the middle of the two groups of retaining rings (2), and a branch tube (3) is fixed between the through holes at the upper and lower ends.

2. A boiler secondary air box equipped with a dust cleaning device according to claim 1, characterized in that: The branch pipe (3) is arranged obliquely between the retaining rings (2), and six groups of through holes are arranged in an equidistant array.

3. A boiler secondary air box equipped with a dust cleaning device according to claim 1, characterized in that: The bottom end of the nozzle pipe (1) is connected to the air guide pipe (4), the outer side of the air guide pipe (4) is connected to the primary air main pipe (5), and the primary air main pipe (5) is connected to an external high-pressure air source, and the nozzle pipe (1) and the external air guide pipe (4) are arranged in an inclined manner.

4. A boiler secondary air box equipped with a dust cleaning device according to claim 1, characterized in that: The air guide pipe and the primary air main pipe are both provided with electromagnetic valve structures.

5. A method for installing a cleaning device for a boiler secondary wind box, comprising the method for installing a cleaning device for a boiler secondary wind box according to any one of claims 1 to 4, characterized in that: Step 1: Divide the wind box into multiple detection areas according to different distribution positions, and obtain the dust accumulation data of each detection area, where the dust accumulation data includes historical dust accumulation thickness data and dust accumulation time data of a day, and the time interval in the time data is 1 hour; Step 2: Analyze the dust accumulation status in each detection area, mark the result as easy dust accumulation area and difficult dust accumulation area, use time information as image watermark, and merge them into easy dust accumulation area image set and difficult dust accumulation area image set, and calculate the proportion of dust accumulation area in the detection area as sp, Step 3: In the image set of dust-prone areas, the grayscale values ​​of the area and the image set of historical dust accumulation areas are extracted and converted to form two sets of grayscale value pixel matrix sets. Then, the gray level co-occurrence matrix (GLCM) model analysis is compared to extract texture features and output two sets of P (i, j) values. In chronological order, a time (h)-grayscale (g) line chart is drawn for the two sets of image sets. Step 4: Fusion the output P(i,j) value and the time information data into two sequence values, which is the deviation coefficient S, and construct the standard deviation function. Among them, S represents the standard deviation (%), n represents the total number of data or the number of measurements, generally the number of n is not less than 40, and i represents the value of each measurement; obtain Syi: the standard deviation value of the dust-prone area and Sli: the standard deviation value of the historical dust accumulation area, and perform time domain aggregation analysis on Syi and Sli respectively. Take Syi as an example: obtain the first dust-prone benchmark interval and the first dust-prone benchmark interval of Syi, which are adjacent time zones. If the loss value of the first dust-prone benchmark interval and the second dust-prone benchmark interval is not greater than the standard deviation value, then the first dust-prone benchmark interval and the second dust-prone benchmark interval are merged into an aggregated dust accumulation interval, and the cyclic analysis is repeated. When Syi in any adjacent time zone is greater than the standard deviation dust accumulation threshold, the aggregation is stopped, and the Syi time series information is output. In the same way, the Sli time series information is obtained. Step 5: Perform data analysis on the S easy time series information and the S history time series information, and calculate the time ratio of the aggregated dust accumulation interval and each combined dust accumulation benchmark time zone respectively, and set it as the time zone weight value, perform weighted mean analysis on each aggregated dust accumulation interval, and obtain the temperature dust accumulation value within the aggregated time zone group. Similarly, obtain the aggregated time zone dust accumulation timing information, and compare the aggregated time zone dust accumulation timing information with the deviation threshold. If it is not less than the deviation threshold, it means that the location needs to increase the blowing power within the time period. If it is less than the deviation threshold, it means that the location does not need to increase the power within the time.

6. A method for adding dust removal to a boiler secondary wind box according to claim 5, characterized in that: In step three, the grayscale value conversion method for converting the color image into the grayscale image adopts the weighted average method, Y=0.299R+0.587G+0.114R (where R, G, B are the values ​​of the red, green, and blue channels of the color image, respectively, and Y is the grayscale value), and the texture features include contrast, correlation, energy, and entropy.

7. A method for adding dust removal to a boiler secondary wind box according to claim 6, characterized in that: In the gray-level co-occurrence matrix model in step three, the side length of the two gray-value pixel matrix sets is Ng, the image set of the marked dust-prone area is t, and the image set of the historical dust-prone area is T. P(i,j)=#{(x1,y1),(x2,y2)∈M×N|f(x1,y1)=i,f(x2,y2)=j}; Where #(x) represents the number of elements in the set x. Obviously, P is a matrix of Ng×Ng. If the distance between (x1, y1) and (x2, y2) is d, and the angle between the two and the horizontal axis of the coordinate is θ, then the grayscale co-occurrence matrix P(i, j, d, θ) of various spacings and angles can be obtained. If the grayscale level of the image is set to N, the co-occurrence matrix is ​​an N×N matrix, which can be expressed as M(Δx, Δy)(h, k), which means: the value of the element mhk located at (h, k) represents the number of times two pixel pairs with a distance of (Δx, Δy) and a grayscale of h and a grayscale of k appear. The resulting P value is analyzed. For coarse texture areas, the mhk values ​​of the grayscale co-occurrence matrix are more concentrated near the main diagonal. For coarse textures, the pixel pairs tend to have the same grayscale. For fine texture areas, the mhk values ​​in the grayscale co-occurrence matrix are scattered everywhere.

Images