Method for monitoring sealing of tuyere small sleeve

Abstract

The invention relates to the technical field of sealing monitoring, and particularly discloses a tuyere small sleeve sealing monitoring method which specifically comprises the following steps: step 1, in a monitoring period, acquiring pressure data of a tuyere small sleeve at each monitoring time point, and analyzing to acquire an abnormal monitoring time point; 2, acquiring abnormal data of the abnormal monitoring time point based on the acquired abnormal monitoring time point, analyzing the abnormal data, and calculating a pressure abnormal evaluation value; wherein the abnormal data comprises an abnormal monitoring time point number proportion and an abnormal pressure deviation value degree ratio total value. Therefore, abnormity can be detected before the sealing performance is obviously reduced, measures can be taken as early as possible, problem deterioration is reduced, a pressure abnormity evaluation value is calculated based on abnormal data of an abnormal monitoring point, the sealing performance of the tuyere small sleeve can be quantitatively evaluated, maintenance personnel can know the sealing condition of the tuyere small sleeve more visually, and the maintenance efficiency is improved. And the production efficiency and the product quality are improved.

Description

Technical Field

[0001] The invention relates to the technical field of sealing monitoring, and in particular to a method for monitoring the sealing of a tuyere sleeve. Background Art

[0002] Coal furnace, especially the tuyere sleeve in blast furnace, is a key component in blast furnace smelting process. It is usually installed in the tuyere area of ​​blast furnace to adjust and stabilize the blast furnace coal gas flow. It is responsible for sending the wind outside the furnace (usually hot wind or oxygen-enriched wind) into the blast furnace, and reacts with the coke in the charge to produce high-temperature reducing gas, which provides the necessary heat and reducing conditions for blast furnace smelting;

[0003] The tuyere sleeve is usually composed of an inner sleeve and an outer sleeve. The inner sleeve is a tube with a smaller inner diameter, which is used to adjust the detailed requirements of the gas flow, such as stroke, angle, height, etc., while the outer sleeve is a circular or polygonal structure with a larger cross-sectional area, which is used to adjust the overall flow and direction, as well as the separation of gas flow and solid material flow.

[0004] However, the design of the tuyere sleeve also needs to consider its sealing performance. The quality of the sealing performance directly affects the leakage of blast furnace gas and the stability of the pressure in the furnace. The existing monitoring method is usually that after the blast furnace has been running for a period of time, the maintenance personnel regularly inspect the tuyere sleeve and judge its sealing performance by observing its appearance, listening to the sound or measuring the temperature. However, this method has many shortcomings. First, it is difficult to achieve real-time monitoring through manual inspection, and it is impossible to detect abnormal changes in the sealing performance of the tuyere sleeve in time. Secondly, empirical judgment often relies on the personal skills and experience of the maintenance personnel, lacking objectivity and accuracy. In addition, even if an abnormality is found, it is impossible to accurately locate the fault point, and the time for troubleshooting and repair is often long, which can easily lead to the deterioration of the problem and affect the normal operation of the blast furnace.

[0005] In view of this, we propose a method for monitoring the sealing of tuyere sleeves. Summary of the invention

[0006] The object of the present invention is to provide a method for monitoring the sealing of a tuyere sleeve to solve the technical problems in the above background.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] The present invention provides a method for monitoring the sealing of an air vent sleeve, and the specific method comprises the following steps: step one: within a monitoring period, obtaining pressure data of the air vent sleeve at each monitoring time point, and analyzing to obtain abnormal monitoring time points; step two: based on the obtained abnormal monitoring time points, obtaining abnormal data of the abnormal monitoring time points, and analyzing to calculate a pressure anomaly assessment value; wherein the abnormal data comprises a proportion of the number of abnormal monitoring time points and a total value of the abnormal pressure deviation value degree ratio; step three: comparing the pressure anomaly assessment value with a pressure anomaly assessment threshold to evaluate the sealing performance of the air vent sleeve; step four: based on the result of evaluating the sealing performance of the air vent sleeve, analyzing the analysis points of the abnormal monitoring time points to obtain low-risk fault points and high-risk fault points.

[0009] As a further solution of the present invention: the process of obtaining the abnormal monitoring time point is:

[0010] Obtain the ratio of large pressure deviation values, and compare the ratio of large pressure deviation values ​​with the threshold of large pressure deviation ratio;

[0011] If the proportion of large pressure deviation values ​​is greater than the pressure deviation large value proportion threshold, a deviation abnormality signal is generated;

[0012] The monitoring time point corresponding to the generated deviation abnormal signal is obtained and marked as the abnormal monitoring time point.

[0013] As a further solution of the present invention: the process of obtaining the proportion of the large value of the pressure deviation is:

[0014] Obtaining a pressure deviation value, and comparing the pressure deviation value with a pressure deviation threshold;

[0015] If the pressure deviation value is greater than the pressure deviation threshold, a large pressure deviation signal is generated;

[0016] The number of generated large pressure deviation signals is obtained, and the number of generated large pressure deviation signals is ratioed with the number of analysis points to obtain the proportion of large pressure deviation values.

[0017] As a further solution of the present invention: the process of obtaining the pressure deviation value is:

[0018] The contact surface between the tuyere sleeve and the coal furnace is divided into several analysis points, a monitoring cycle is preset, and the monitoring cycle is divided into several monitoring time points;

[0019] At each monitoring time point, the pressure value of each analysis point is obtained, the pressure value of each analysis point is summed and averaged to obtain the pressure mean, the pressure value of each analysis point is calculated to be different from the pressure mean, the absolute value of the difference is taken to obtain the pressure deviation value.

[0020] As a further solution of the present invention: the process of obtaining the pressure abnormality assessment value is:

[0021] Obtain the percentage of abnormal monitoring time points and the total value of abnormal pressure deviation value ratio;

[0022] Substitute into the formula The pressure anomaly assessment value is calculated, where GS represents the ratio of the number of abnormal monitoring time points, CD represents the ratio of the abnormal pressure deviation value to the total value, and s1 and s2 are preset proportional coefficients.

[0023] As a further solution of the present invention: the process of obtaining the percentage of the number of abnormal monitoring time points is as follows:

[0024] Obtain the abnormal monitoring time point and the value of the abnormal monitoring time point within the monitoring period;

[0025] The ratio of the number of abnormal monitoring time points to the total number of monitoring time points is processed to obtain the proportion of the number of abnormal monitoring time points.

[0026] As a further solution of the present invention: the process of obtaining the abnormal pressure deviation value degree ratio total value is as follows:

[0027] At each abnormal monitoring time point, the pressure deviation value corresponding to the generated pressure deviation large signal is obtained, the pressure deviation values ​​are summed and averaged to obtain the abnormal pressure deviation mean, the difference between the abnormal pressure deviation mean and the pressure deviation threshold is calculated, and the difference is calculated to the pressure deviation threshold to obtain the abnormal pressure deviation value degree ratio;

[0028] The abnormal pressure deviation value degree ratios at all abnormal monitoring time points are summed up to obtain the total value of the abnormal pressure deviation value degree ratio.

[0029] As a further solution of the present invention: the process of evaluating the sealing performance of the tuyere sleeve is:

[0030] Obtaining a pressure anomaly assessment value, and comparing the pressure anomaly assessment value with a pressure anomaly assessment threshold;

[0031] If the pressure abnormality assessment value is less than or equal to the pressure abnormality assessment threshold, a normal sealing performance signal is generated;

[0032] If the pressure abnormality assessment value is greater than the pressure abnormality assessment threshold, a sealing performance abnormality signal is generated.

[0033] As a further solution of the present invention: the process of obtaining the low-risk fault points and the high-risk fault points is:

[0034] Obtain a value of the number of times the number to be analyzed is marked, and compare the value of the number of times the number to be analyzed is marked with a threshold value of the number of times the number to be analyzed is marked;

[0035] If the percentage of times the number to be analyzed is marked is equal to the threshold of times the number to be analyzed is marked, the analysis point is marked as a low-risk fault point;

[0036] If the percentage of times the number to be analyzed is marked is greater than the threshold of the percentage of times the number to be analyzed is marked, the analysis point is marked as a high-risk fault point.

[0037] As a further solution of the present invention: the process of obtaining the value of the percentage of times the number to be analyzed is marked is:

[0038] Number all analysis points from 1 to N;

[0039] At each abnormal monitoring time point, the analysis point corresponding to the generation of a large pressure deviation signal is obtained and marked as an abnormal analysis point, and the number of each abnormal analysis point is obtained and marked;

[0040] Among the numbers of all abnormal analysis points, different numbers are extracted and marked as numbers to be analyzed;

[0041] Obtain the number of times the number to be analyzed is marked, and perform ratio processing on the number of times the number to be analyzed is marked and the value of the abnormal monitoring time point to obtain the ratio of the number to be analyzed.

[0042] Beneficial effects of the present invention:

[0043] (1) The present invention divides the air vent sleeve into several analysis points, obtains the pressure value of each analysis, calculates the proportion of large pressure deviation values ​​at each monitoring time point in the monitoring period, determines the abnormal monitoring point, calculates the abnormal data of the abnormal monitoring point based on the acquired abnormal monitoring point, and calculates the pressure abnormality evaluation value based on the abnormal data, compares the pressure abnormality evaluation value with the pressure abnormality evaluation threshold, and determines the sealing performance of the air vent sleeve, so that the abnormality can be detected before the sealing performance is significantly reduced, which helps to take measures early and reduce the deterioration of the problem. The pressure abnormality evaluation value is calculated based on the abnormal data of the abnormal monitoring point, and the sealing performance of the air vent sleeve can be quantitatively evaluated, so that maintenance personnel can more intuitively understand the sealing status of the air vent sleeve and formulate corresponding maintenance plans, thereby improving production efficiency and product quality;

[0044] (2) The present invention is based on the generated sealing performance abnormal signal. By numbering all the analysis points, the abnormal analysis point corresponding to each abnormal monitoring time point is obtained. The different numbers in all the abnormal analysis points are obtained to obtain the number to be analyzed, and the proportion of the number to be analyzed is calculated. The value is compared with the threshold value of the proportion of the number to be analyzed. The low-risk fault point and the high-risk fault point are obtained, so that all the analysis points are numbered and the abnormal analysis point of each abnormal monitoring time point is obtained. The high-risk fault position can be accurately located, which helps to quickly locate the problem and reduce the troubleshooting time. According to the classification of low-risk and high-risk fault points, a more reasonable maintenance plan can be formulated. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The present invention will be further described below in conjunction with the accompanying drawings.

[0046] Figure 1 This is a flowchart of a method for monitoring the sealing of a tuyere sleeve of the present invention;

[0047] Figure 2 It is a flowchart of obtaining low-risk fault points and high-risk fault points in a tuyere sleeve sealing monitoring method of the present invention. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] Embodiment 1:

[0050] See also Figure 1 As shown, a method for monitoring the sealing of a tuyere sleeve according to an embodiment of the present invention comprises the following steps:

[0051] Step 1: During the monitoring period, obtain the pressure data of the tuyere sleeve at each monitoring time point, and analyze it to obtain the abnormal monitoring time point;

[0052] In some embodiments, the contact surface between the tuyere sleeve and the coal furnace is divided into several analysis points, a monitoring cycle is preset, and the monitoring cycle is divided into several monitoring time points, wherein the monitoring cycle is set by a person skilled in the art based on experience;

[0053] At each monitoring time point, the pressure value of each analysis point is obtained, the pressure value of each analysis point is summed and averaged to obtain the pressure mean value, the pressure value of each analysis point is calculated to be different from the pressure mean value, the absolute value of the difference is taken to obtain the pressure deviation value;

[0054] Compare the pressure deviation value with the pressure deviation threshold, wherein the pressure deviation threshold is a critical value used to determine the magnitude of the pressure deviation and is set by a person skilled in the art based on historical experimental data;

[0055] If the pressure deviation value is less than or equal to the pressure deviation threshold, it means that the deviation between the pressure value corresponding to the analysis point and the pressure mean is small, and a small pressure deviation signal is generated;

[0056] If the pressure deviation value is greater than the pressure deviation threshold, it means that the deviation between the pressure value corresponding to the analysis point and the pressure mean is large, and a large pressure deviation signal is generated;

[0057] Obtain the number of generated pressure deviation large signal values, perform ratio processing on the number of generated pressure deviation large signal values ​​and the number of analysis points, and obtain the ratio of the number of large pressure deviation values;

[0058] It should be explained that the meaning of the percentage of large pressure deviation values ​​is: the larger the percentage of large pressure deviation values, the more pressure values ​​of the analysis points of the tuyere sleeve at the monitoring time point deviate from the normal range, that is, there are more potential sealing problems or abnormalities;

[0059] The ratio of large pressure deviation values ​​is compared with the threshold of large pressure deviation ratio, wherein the threshold of large pressure deviation ratio is a critical value used to determine whether the pressure deviation at the monitoring time point is normal, and is summarized and set by technicians in this field based on historical experimental data;

[0060] If the proportion of large pressure deviation values ​​is less than or equal to the pressure deviation large value proportion threshold, it means that the pressure value deviation of the tuyere small set corresponding to the monitoring time point is relatively normal, and a normal deviation signal is generated;

[0061] If the proportion of large pressure deviation values ​​is greater than the pressure deviation large value proportion threshold, it means that the pressure value deviation of the tuyere small set corresponding to the monitoring time point is in an abnormal state, and a deviation abnormality signal is generated;

[0062] Obtain the monitoring time point corresponding to the generated deviation abnormal signal and mark it as the abnormal monitoring time point;

[0063] Step 2: Based on the acquired abnormal monitoring time point, obtain the abnormal data at the abnormal monitoring time point, analyze it, and calculate the pressure abnormality assessment value;

[0064] Among them, the abnormal data include the percentage of abnormal monitoring time points and the total value of abnormal pressure deviation value;

[0065] In some embodiments, an abnormal monitoring time point and a numerical value of the abnormal monitoring time point within a monitoring period are obtained;

[0066] The ratio of the number of abnormal monitoring time points to the total number of monitoring time points is processed to obtain the ratio of the number of abnormal monitoring time points;

[0067] At each abnormal monitoring time point, the pressure deviation value corresponding to the generated pressure deviation large signal is obtained, the pressure deviation values ​​are summed and averaged to obtain the abnormal pressure deviation mean, the difference between the abnormal pressure deviation mean and the pressure deviation threshold is calculated, and the difference is calculated to the pressure deviation threshold to obtain the abnormal pressure deviation value degree ratio;

[0068] The abnormal pressure deviation value degree ratios at all abnormal monitoring time points are summed up to obtain the total value of the abnormal pressure deviation value degree ratio;

[0069] Substitute into the formula The pressure anomaly assessment value is calculated, where GS represents the ratio of the number of abnormal monitoring time points, CD represents the ratio of the abnormal pressure deviation value to the total value, and s1 and s2 are preset proportional coefficients;

[0070] It needs to be explained that the meaning reflected by the pressure abnormality assessment value is: the pressure abnormality assessment value is calculated by the proportion of the number of abnormal monitoring time points and the abnormal pressure deviation value degree ratio to the total value, that is, the greater the proportion of the number of abnormal monitoring time points, the greater the pressure abnormality assessment value, and the more abnormal monitoring time is within the monitoring period, the more serious the abnormal sealing performance of the tuyere sleeve is, that is, the greater the abnormal pressure deviation value degree ratio to the total value, the greater the pressure abnormality assessment value, and the greater the deviation degree of the abnormal pressure deviation value at the abnormal monitoring time point within the monitoring period, the more serious the abnormal sealing performance of the tuyere sleeve is;

[0071] Step 3: Compare the pressure anomaly assessment value with the pressure anomaly assessment threshold to evaluate the sealing performance of the tuyere sleeve;

[0072] In some embodiments, a pressure anomaly assessment value is obtained, and the pressure anomaly assessment value is compared with a pressure anomaly assessment threshold, wherein the pressure anomaly assessment threshold is a critical value used to judge the sealing performance of the tuyere sleeve, and is summarized and set by a person skilled in the art based on historical multiple experimental data;

[0073] If the pressure abnormality assessment value is less than or equal to the pressure abnormality assessment threshold, it means that the sealing performance of the tuyere sleeve is in a normal state during the monitoring period, and a normal sealing performance signal is generated;

[0074] If the pressure abnormality assessment value is greater than the pressure abnormality assessment threshold, it means that the sealing performance of the tuyere sleeve is in an abnormal state during the monitoring period, and a sealing performance abnormality signal is generated;

[0075] The technical solution of the embodiment of the present invention is mainly as follows: by dividing the air vent sleeve into several analysis points, obtaining the pressure value of each analysis point, calculating the proportion of large pressure deviation values ​​at each monitoring time point within the monitoring period, judging the abnormal monitoring point, calculating the abnormal data of the abnormal monitoring point based on the acquired abnormal monitoring point, and calculating the pressure abnormality evaluation value based on the abnormal data, comparing the pressure abnormality evaluation value with the pressure abnormality evaluation threshold, judging the sealing performance of the air vent sleeve, so that the abnormality can be detected before the sealing performance is significantly reduced, which helps to take measures early and reduce the deterioration of the problem. The pressure abnormality evaluation value is calculated based on the abnormal data of the abnormal monitoring point, and the sealing performance of the air vent sleeve can be quantitatively evaluated, so that maintenance personnel can more intuitively understand the sealing condition of the air vent sleeve and formulate corresponding maintenance plans, thereby improving production efficiency and product quality.

[0076] Embodiment 2:

[0077] Based on Example 1, please refer to Figure 2 As shown, a method for monitoring the sealing of a tuyere sleeve according to an embodiment of the present invention further includes the following steps:

[0078] Step 4: Based on the generated sealing performance abnormality signal, analyze the analysis points of the abnormal monitoring time points to obtain low-risk fault points and high-risk fault points;

[0079] In some embodiments, based on the generated sealing performance abnormality signal, all analysis points are numbered sequentially from 1 to N;

[0080] At each abnormal monitoring time point, the analysis point corresponding to the generation of a large pressure deviation signal is obtained and marked as an abnormal analysis point, and the number of each abnormal analysis point is obtained and marked;

[0081] Among the numbers of all abnormal analysis points, different numbers are extracted and marked as numbers to be analyzed;

[0082] Obtain the number of times the number to be analyzed is marked, and perform ratio processing on the number of times the number to be analyzed is marked and the value of the abnormal monitoring time point to obtain the ratio of the number to be analyzed;

[0083] Compare the value of the number of times the number to be analyzed is marked with the threshold value of the number of times the number to be analyzed is marked, wherein the value of the number of times the number to be analyzed is summarized and set by a person skilled in the art based on historical experimental data;

[0084] If the value of the number to be analyzed marked times is equal to the threshold value of the number to be analyzed marked times, it means that the abnormal analysis point does not appear abnormally frequently during the monitoring period, and the analysis point is marked as a low-risk fault point;

[0085] Based on the marked low-risk fault points, continuous monitoring is carried out, and the regular monitoring time is shortened based on the original monitoring period (i.e. the interval between two adjacent monitoring time points), thereby reducing the performance degradation caused by long-term use;

[0086] If the value of the number of times the number to be analyzed is marked is greater than the threshold value of the number of times the number to be analyzed is marked, it means that the abnormal analysis point has frequent abnormalities during the monitoring period, and the analysis point is marked as a high-risk fault point;

[0087] Based on the marked high-risk fault points, the staff will immediately conduct investigations and repairs, and the equipment needs to be shut down for inspection to ensure the safe operation of the equipment;

[0088] The technical solution of the embodiment of the present invention is mainly as follows: based on the generated sealing performance abnormal signal, by numbering all analysis points, obtaining the abnormal analysis point corresponding to each abnormal monitoring time point, obtaining the number to be analyzed with different numbers in all abnormal analysis points, calculating the proportion of the number to be analyzed marked, and comparing with the proportion threshold of the number to be analyzed marked, obtaining low-risk fault points and high-risk fault points, thereby numbering all analysis points and obtaining the abnormal analysis point of each abnormal monitoring time point, which can accurately locate the high-risk fault position, help to quickly locate the problem, reduce the troubleshooting time, and formulate a more reasonable maintenance plan based on the classification of low-risk and high-risk fault points.

[0089] Embodiment 3:

[0090] On the basis of Example 1 and Example 2, a tuyere sleeve sealing monitoring system according to an embodiment of the present invention comprises:

[0091] Abnormal monitoring time point acquisition module: During the monitoring period, the pressure data of the tuyere sleeve at each monitoring time point is obtained, and analyzed to obtain the abnormal monitoring time point;

[0092] Pressure anomaly assessment value calculation module: based on the acquired abnormal monitoring time point, obtain the abnormal data at the abnormal monitoring time point, analyze it, and calculate the pressure anomaly assessment value;

[0093] Sealing performance judgment module: compares the pressure abnormality assessment value with the pressure abnormality assessment threshold to evaluate the sealing performance of the tuyere sleeve;

[0094] Fault point risk degree analysis module: Based on the generated sealing performance abnormality signal, the analysis points of the abnormal monitoring time points are analyzed to obtain low-risk fault points and high-risk fault points.

[0095] The size of the above threshold is set for the convenience of comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each group of sample data; for example: in the actual acquisition process, there are many groups of fluctuation degree coefficients and fluctuation uniformity coefficients. The proportion of the number of abnormal monitoring time points and the total value of the abnormal pressure deviation value degree ratio of many groups are processed to obtain the pressure anomaly assessment value of the corresponding group. The staff evaluates the sealing state of the air vent sleeve based on so many groups of pressure anomaly assessment values, thereby obtaining a corresponding relationship between a pressure anomaly assessment value and the sealing state of the air vent sleeve, and then derives and divides the threshold of the pressure anomaly assessment value according to the sealing state of the air vent sleeve, thereby obtaining the pressure anomaly assessment threshold, and compares the obtained pressure anomaly assessment value with the pressure anomaly assessment threshold, that is, completes the identification of the sealing state of the air vent sleeve corresponding to the pressure anomaly assessment value;

[0096] The above formulas are obtained by collecting a large amount of data and performing software simulation to select a formula close to the actual value. The factors in the formula are set by technicians in this field according to actual conditions; for example: Formula A technician in this field collects multiple groups of test data and sets a corresponding pressure anomaly assessment value for each group of test data (i.e., the ratio of the number of abnormal monitoring time points and the ratio of the degree of abnormal pressure deviation value to the total value); substitutes the set pressure anomaly assessment value and the acquired test data into the formula, any two formulas constitute a binary linear equation system, and the calculated factors are screened and averaged to obtain the values ​​of s1 and s2, which are 3.68 and 1.32 respectively;

[0097] The size of the factor is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the factor depends on the amount of detection data and the initial setting of the corresponding pressure anomaly assessment value for each set of detection data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the pressure anomaly assessment value is proportional to the proportion of the number of abnormal monitoring time points.

[0098] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for monitoring the sealing of a tuyere sleeve, characterized in that: The specific method includes the following steps: Step 1: During the monitoring period, obtain the pressure data of the tuyere sleeve at each monitoring time point, and analyze it to obtain the abnormal monitoring time point; Step 2: Based on the acquired abnormal monitoring time point, obtain the abnormal data at the abnormal monitoring time point, analyze it, and calculate the pressure abnormality assessment value; Among them, the abnormal data include the percentage of abnormal monitoring time points and the total value of abnormal pressure deviation value; Step 3: Compare the pressure anomaly assessment value with the pressure anomaly assessment threshold to evaluate the sealing performance of the tuyere sleeve; Step 4: Based on the evaluation results of the sealing performance of the tuyere sleeve, analyze the analysis points of the abnormal monitoring time points to obtain low-risk fault points and high-risk fault points.

2. A method for monitoring the sealing of a tuyere sleeve according to claim 1, characterized in that: The process of obtaining the abnormal monitoring time point is as follows: Obtain the ratio of large pressure deviation values, and compare the ratio of large pressure deviation values ​​with the threshold of large pressure deviation ratio; If the proportion of large pressure deviation values ​​is greater than the pressure deviation large value proportion threshold, a deviation abnormality signal is generated; The monitoring time point corresponding to the generated deviation abnormal signal is obtained and marked as the abnormal monitoring time point.

3. A method for monitoring the sealing of a tuyere sleeve according to claim 2, characterized in that: The process of obtaining the proportion of the large value of the pressure deviation is as follows: Obtaining a pressure deviation value, and comparing the pressure deviation value with a pressure deviation threshold; If the pressure deviation value is greater than the pressure deviation threshold, a large pressure deviation signal is generated; The number of generated large pressure deviation signals is obtained, and the number of generated large pressure deviation signals is ratioed with the number of analysis points to obtain the proportion of large pressure deviation values.

4. A method for monitoring the sealing of a tuyere sleeve according to claim 3, characterized in that: The process of obtaining the pressure deviation value is as follows: The contact surface between the tuyere sleeve and the coal furnace is divided into several analysis points, a monitoring cycle is preset, and the monitoring cycle is divided into several monitoring time points; At each monitoring time point, the pressure value of each analysis point is obtained, the pressure value of each analysis point is summed and averaged to obtain the pressure mean, the pressure value of each analysis point is calculated to be different from the pressure mean, the absolute value of the difference is taken to obtain the pressure deviation value.

5. A method for monitoring the sealing of a tuyere sleeve according to claim 1, characterized in that: The process of obtaining the pressure abnormality assessment value is as follows: Obtain the percentage of abnormal monitoring time points and the total value of abnormal pressure deviation value ratio; Substitute into the formula The pressure anomaly assessment value is calculated, where GS represents the ratio of the number of abnormal monitoring time points, CD represents the ratio of the abnormal pressure deviation value to the total value, and s1 and s2 are preset proportional coefficients.

6. A method for monitoring the sealing of a tuyere sleeve according to claim 1, characterized in that: The process of obtaining the percentage of the number of abnormal monitoring time points is as follows: Obtain the abnormal monitoring time point and the value of the abnormal monitoring time point within the monitoring period; The ratio of the number of abnormal monitoring time points to the total number of monitoring time points is processed to obtain the proportion of the number of abnormal monitoring time points.

7. A method for monitoring the sealing of a tuyere sleeve according to claim 1, characterized in that: The process of obtaining the abnormal pressure deviation value degree ratio total value is as follows: At each abnormal monitoring time point, the pressure deviation value corresponding to the generated pressure deviation large signal is obtained, the pressure deviation values ​​are summed and averaged to obtain the abnormal pressure deviation mean, the difference between the abnormal pressure deviation mean and the pressure deviation threshold is calculated, and the difference is calculated to the pressure deviation threshold to obtain the abnormal pressure deviation value degree ratio; The abnormal pressure deviation value degree ratios at all abnormal monitoring time points are summed up to obtain the total value of the abnormal pressure deviation value degree ratio.

8. A method for monitoring the sealing of a tuyere sleeve according to claim 1, characterized in that: The process of evaluating the sealing performance of the tuyere sleeve is as follows: Obtaining a pressure anomaly assessment value, and comparing the pressure anomaly assessment value with a pressure anomaly assessment threshold; If the pressure abnormality assessment value is less than or equal to the pressure abnormality assessment threshold, a normal sealing performance signal is generated; If the pressure abnormality assessment value is greater than the pressure abnormality assessment threshold, a sealing performance abnormality signal is generated.

9. A method for monitoring the sealing of a tuyere sleeve according to claim 1, characterized in that: The process of obtaining the low-risk fault points and the high-risk fault points is as follows: Obtain a value of the number of times the number to be analyzed is marked, and compare the value of the number of times the number to be analyzed is marked with a threshold value of the number of times the number to be analyzed is marked; If the percentage of times the number to be analyzed is marked is equal to the threshold of times the number to be analyzed is marked, the analysis point is marked as a low-risk fault point; If the percentage of times the number to be analyzed is marked is greater than the threshold of the percentage of times the number to be analyzed is marked, the analysis point is marked as a high-risk fault point.

10. A method for monitoring the sealing of a tuyere sleeve according to claim 9, characterized in that: The process of obtaining the value of the percentage of times the number to be analyzed is marked is as follows: Number all analysis points from 1 to N; At each abnormal monitoring time point, the analysis point corresponding to the generation of a large pressure deviation signal is obtained and marked as an abnormal analysis point, and the number of each abnormal analysis point is obtained and marked; Among the numbers of all abnormal analysis points, different numbers are extracted and marked as numbers to be analyzed; Obtain the number of times the number to be analyzed is marked, and perform ratio processing on the number of times the number to be analyzed is marked and the value of the abnormal monitoring time point to obtain the ratio of the number to be analyzed.

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