A method for monitoring the sealing of a small air vent sleeve

Abstract

The present invention relates to the field of sealing monitoring technology, and specifically discloses a method for monitoring the sealing of an air vent sleeve. The specific method includes the following steps: Step 1: within a monitoring period, obtain the pressure data of the air vent sleeve at each monitoring time point, analyze the data, and obtain an abnormal monitoring time point; Step 2: based on the acquired abnormal monitoring time point, obtain the abnormal data of the abnormal monitoring time point, analyze the data, and calculate the pressure abnormality evaluation value; wherein the abnormal data includes the proportion of the number of abnormal monitoring time points and the abnormal pressure deviation value ratio to the total value. Thus, the abnormality can be detected before the sealing performance shows a significant decline, 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, thereby improving production efficiency and product quality.

Description

Technical Field

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

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

[0003] The tuyere sleeve is usually composed of two parts: the inner sleeve and the outer sleeve. The inner sleeve is a tube with a smaller inner diameter, 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, 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 the maintenance personnel regularly inspect the tuyere sleeve after the blast furnace has been in operation for a period of time, and judge its sealing performance by observing its appearance, listening to the sound or measuring the temperature. However, this method has many shortcomings. First, manual inspections are difficult to achieve real-time monitoring and cannot detect abnormal changes in the sealing performance of the tuyere sleeve in time. Second, empirical judgments often rely on the personal skills and experience of the maintenance personnel and lack objectivity and accuracy. In addition, even if an abnormality is found, it is difficult to accurately locate the fault point, and the time for investigation 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 includes the following steps: step 1: within a monitoring period, obtaining pressure data of the air vent sleeve at each monitoring time point, analyzing the data, and obtaining abnormal monitoring time points; step 2: based on the obtained abnormal monitoring time points, obtaining abnormal data of the abnormal monitoring time points, analyzing the data, and calculating a pressure anomaly assessment value; wherein the abnormal data includes a proportion of the number of abnormal monitoring time points and a total value of the abnormal pressure deviation value ratio; step 3: comparing the pressure anomaly assessment value with a pressure anomaly assessment threshold to evaluate the sealing performance of the air vent sleeve; step 4: 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 the ratio of large pressure deviation values;

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

[0012] Obtain the monitoring time point corresponding to the generation of the deviation abnormal signal and mark it 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 ratio of the generated large pressure deviation signals to the number of analysis points is processed 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 ratio 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 abnormal monitoring time points, CD represents the ratio of 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 ratio of the number of abnormal monitoring time points is as follows:

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

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

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

[0027] At each abnormal monitoring time point, the pressure deviation value corresponding to the large pressure deviation signal is obtained, these 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 ratio of the difference to the pressure deviation threshold is calculated 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 a total value of the abnormal pressure deviation value degree ratios.

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

[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 evaluation value is greater than the pressure abnormality evaluation 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 as follows:

[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 greater than the threshold, 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 percentage of times the number to be analyzed is marked is as follows:

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

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

[0040] Among all the abnormal analysis point numbers, extract the different numbers and mark them 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 within 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 condition 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 analysis points, the abnormal analysis point corresponding to each abnormal monitoring time point is obtained. The different numbers of all abnormal analysis points are obtained to obtain the number to be analyzed. The proportion of the number to be analyzed is calculated and compared with the threshold of the proportion of the number to be analyzed. The low-risk fault point and the high-risk fault point are obtained. Thus, all 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 determined, 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 with reference to the accompanying drawings.

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

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

[0048] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making any creative efforts shall fall within the scope of protection of the present invention.

[0049] Example 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 includes the following steps:

[0051] Step 1: During the monitoring period, obtain the pressure data of the tuyere sleeve at each monitoring time point, analyze it, and 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 period is preset, and the monitoring period is divided into several monitoring time points, wherein the monitoring period is set by those 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, where the pressure deviation threshold is a critical value used to determine the magnitude of the pressure deviation and is set by those 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 large pressure deviation signals, perform ratio processing on the number of generated large pressure deviation signals and the number of analysis point values, and obtain the proportion of large pressure deviation values;

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

[0059] Compare the ratio of large pressure deviation values ​​with the threshold for the ratio of large pressure deviations. The threshold is a critical value used to determine whether the pressure deviation at the monitoring time point is normal. It is set by those skilled in the art based on historical experimental data.

[0060] If the proportion of large pressure deviation values ​​is less than or equal to the threshold of the proportion of large pressure deviation values, it means that the pressure deviation of the tuyere sleeve 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 threshold of large pressure deviation proportion, it means that the pressure deviation of the tuyere sleeve 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, abnormal data includes the ratio of abnormal monitoring time points and the ratio of abnormal pressure deviation value to total value;

[0065] In some embodiments, obtaining abnormal monitoring time points and abnormal monitoring time point values ​​within a monitoring period;

[0066] Ratio the number of abnormal monitoring time points to the total number of monitoring time points 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 large pressure deviation signal is obtained, these 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 ratio of the difference to the pressure deviation threshold is calculated to obtain the abnormal pressure deviation value degree ratio;

[0068] Sum up the abnormal pressure deviation value ratios at all abnormal monitoring time points to obtain a total value of the abnormal pressure deviation value ratio;

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

[0070] It should be explained that the meaning reflected by the pressure anomaly assessment value is: the pressure anomaly assessment value is calculated by the ratio of the number of abnormal monitoring time points and the ratio of the abnormal pressure deviation value to the total value, that is, the greater the ratio of the number of abnormal monitoring time points, the greater the pressure anomaly assessment value, and then, within the monitoring period, the more abnormal monitoring time there is, the more serious the abnormal sealing performance of the tuyere sleeve, that is, the greater the ratio of the abnormal pressure deviation value to the total value, the greater the pressure anomaly assessment value, and then, within the monitoring period, the greater the deviation degree of the abnormal pressure deviation value at the abnormal monitoring time point is, 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 compared with a pressure anomaly assessment threshold value, wherein the pressure anomaly assessment threshold value is a critical value used to judge the sealing performance of the tuyere sleeve and is set by those skilled in the art based on historical 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 normal 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 to obtain abnormal monitoring points, calculating the abnormal data of the abnormal monitoring points based on the obtained abnormal monitoring points, 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 shows a significant decline, which helps to take measures early and reduce the deterioration of the problem, and calculating the pressure abnormality evaluation value based on the abnormal data of the abnormal monitoring points can quantitatively evaluate the sealing performance of the air vent sleeve, 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] Example 2:

[0077] Based on Example 1, please refer to Figure 2 As shown, the embodiment of the present invention provides a method for monitoring the sealing of a tuyere sleeve, and the specific method 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 point 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, obtain the analysis point corresponding to the generation of a large pressure deviation signal, mark it as an abnormal analysis point, obtain the number of each abnormal analysis point and mark it;

[0081] Among all the abnormal analysis point numbers, extract the different numbers and mark them as numbers to be analyzed;

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

[0083] Compare the percentage of times the number to be analyzed is marked with a threshold value of the percentage of times the number to be analyzed is marked, wherein the percentage 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 ratio of the number to be analyzed to be marked is greater than the threshold, it means that the abnormality 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 percentage of times the number to be analyzed is marked is greater than the threshold, 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, staff will immediately conduct investigations and repairs, and the equipment will need to be shut down for inspection to ensure safe operation;

[0088] The technical solution of the embodiment of the present invention is mainly as follows: based on the generated sealing performance abnormality signal, by numbering all analysis points, obtaining the abnormal analysis point corresponding to each abnormal monitoring time point, obtaining the different numbers of all abnormal analysis points, obtaining the number to be analyzed, calculating the proportion of the number to be analyzed being marked, and comparing it with the threshold of the proportion of the number to be analyzed being 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 determine the high-risk fault location, 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] Example 3:

[0090] Based on Example 1 and Example 2, a system for monitoring the sealing of a tuyere sleeve according to an embodiment of the present invention includes:

[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, obtains the abnormal data at the abnormal monitoring time point, analyzes it, and calculates 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 to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technical personnel 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, and the proportion of the number of abnormal monitoring time points and the total value of the abnormal pressure deviation value ratio of many groups are processed to obtain the pressure anomaly evaluation value of the corresponding group. The staff evaluates the sealing status of the air outlet sleeve based on so many groups of pressure anomaly evaluation values, thereby obtaining a corresponding relationship between a pressure anomaly evaluation value and the sealing status of the air outlet sleeve, and then derives and divides the threshold of the pressure anomaly evaluation value according to the sealing status of the air outlet sleeve, thereby obtaining a pressure anomaly evaluation threshold, and compares the obtained pressure anomaly evaluation value with the pressure anomaly evaluation threshold, that is, completes the identification of the sealing status of the air outlet sleeve corresponding to the pressure anomaly evaluation 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 those skilled in the art according to the actual situation; for example: A person skilled in the art collects multiple sets of test data and sets a corresponding pressure anomaly assessment value for each set 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 to the total value); substitutes the set pressure anomaly assessment value and the acquired test data into a formula, and any two formulas form a system of linear equations of two variables. The calculated factors are screened and averaged, and the values ​​of s1 and s2 are obtained to be 3.68 and 1.32, respectively;

[0097] The size of the factor is to quantify each parameter to obtain a specific numerical value for the convenience of 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 numerical 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. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope 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, analyze it, and obtain the abnormal monitoring time point; The acquisition process of the abnormal monitoring time point 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 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; comparing the pressure deviation value to a pressure deviation threshold; If the pressure deviation value is greater than the pressure deviation threshold, a large pressure deviation signal is generated; Obtain the number of generated large pressure deviation signals, perform ratio processing on the number of generated large pressure deviation signals and the number of analysis point values, and obtain the proportion of large pressure deviation values; 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 threshold of the proportion of large pressure deviation values, a deviation abnormality signal is generated; Obtain the monitoring time point corresponding to the generated deviation abnormal signal and mark it as 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, abnormal data includes the ratio of abnormal monitoring time points and the ratio of abnormal pressure deviation value to total value; Substitute the ratio of the number of abnormal monitoring time points and the total value of the abnormal pressure deviation value into the formula , calculate the pressure anomaly assessment value, 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; 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 results of evaluating 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 percentage of abnormal monitoring time points is as follows: Obtain the abnormal monitoring time point and the abnormal monitoring time point value within the monitoring period; The ratio of the number of abnormal monitoring time points to the total number of monitoring time points is calculated.

3. The 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 ratio is as follows: At each abnormal monitoring time point, the pressure deviation value corresponding to the large pressure deviation signal is obtained, these 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 ratio of the difference to the pressure deviation threshold is calculated 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 a total value of the abnormal pressure deviation value degree ratios.

4. The 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 evaluation value is greater than the pressure abnormality evaluation threshold, a sealing performance abnormality signal is generated.

5. The 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 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 greater than the threshold, 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.

6. A method for monitoring the sealing of a tuyere sleeve according to claim 5, characterized in that: The process of obtaining 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, obtain the analysis point corresponding to the generation of a large pressure deviation signal, mark it as an abnormal analysis point, obtain the number of each abnormal analysis point and mark it; Among all the abnormal analysis point numbers, extract the different numbers and mark them 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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