Monitoring and decision-making method for continuous gas supply state of gas pipeline

Abstract

The invention relates to a gas pipeline continuous gas supply state monitoring decision-making method, which comprises the following steps that S1, original gas leakage collection data are obtained, and the original gas leakage collection data comprise an annual gas leakage point number original value, a gas leakage point interval original value, use year time, a pipeline anti-corrosion level and gas operation pressure; s2, processing the original gas leakage collection data; and S3, making a gas pipeline maintenance decision by using the processed original gas leakage acquisition data. The gas pipeline continuous gas supply state monitoring decision-making method solves the problem that in the prior art, gas leakage point data of gas pipelines in the past cannot be used for deciding whether subsequent gas pipelines should be completely replaced or not.

Description

Technical Field

[0001] The present invention relates to the field of gas pipeline monitoring and decision-making, and in particular to a method for monitoring and decision-making of a continuous gas supply state of a gas pipeline. Background Art

[0002] The Chinese patent discloses an intelligent high-level scheduling and operation and maintenance system and method for a gas transmission network with an application number of CN202111025717.8. The intelligent high-level scheduling and operation and maintenance system and method for the gas transmission network include: a SCADA system for real-time collection of operating parameter data of the gas transmission network; an intermediate database for real-time storage of operating parameter data of the gas transmission network and historical gas usage data of users; a pipeline network integrity management system for real-time determination of the pressure and current limiting of field station equipment and gas pipelines in the gas transmission network, and online early warning of abnormal data; a scheduling analysis system for obtaining scheduling auxiliary analysis results of the gas transmission network; a scheduling command system for determining decision results; a control system for generating instructions based on the determined decision results to control the operation of each field station equipment in the gas transmission network.

[0003] Although the intelligent high-level scheduling and operation and maintenance system and method of the gas transmission network can be widely used in the field of natural gas long-distance pipeline and gas transmission network operation and scheduling technology, the intelligent high-level scheduling and operation and maintenance system and method of the gas transmission network still has the disadvantage that it cannot use the previous gas pipeline leakage point data to decide whether the subsequent gas pipeline should be replaced completely. Summary of the invention

[0004] The present invention aims to provide a method for monitoring and deciding the continuous gas supply status of a gas pipeline, so as to solve the problem in the prior art that the previous gas pipeline leakage point data cannot be used to decide whether the subsequent gas pipeline should be completely replaced.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] The present invention provides a method for monitoring and making decisions on the continuous gas supply status of a gas pipeline, comprising the following steps:

[0007] S1. Obtaining the original gas leakage collection data, which includes: the original value of the number of annual leakage points, the original value of the distance between leakage points, the service time in years, the pipeline anti-corrosion level and the gas operation pressure. The original value of the number of annual leakage points indicates the number of leakage points in the gas pipeline each year, the original value of the distance between leakage points is the distance between two adjacent leakage points, the service time in years indicates how many years it has been used since it was put into use, the pipeline anti-corrosion level indicates the expert's rating of the pipeline anti-corrosion operation, and the rating range is an integer within (0,5), and the gas operation pressure indicates the gas pressure in the gas pipeline;

[0008] S2. Processing the original gas leakage collection data;

[0009] S3. Use the processed raw gas leakage collection data to make gas pipeline maintenance and repair decisions.

[0010] Preferably, a pressure gauge is installed on the gas pipeline, and the pressure gauge is used to detect the gas pressure in the gas pipeline. The output end of the pressure gauge is connected to the input end of the signal processing module, and the output end of the signal processing module is connected to the input end of the controller. The controller is communicatively connected to the first communication module, the first communication module is communicatively connected to the second communication module, and the second communication module is communicatively connected to the overall monitoring cloud platform.

[0011] Preferably, step S2 comprises the following steps:

[0012] S21, removing the data group whose original value of annual leakage point number is less than or equal to 2;

[0013] S22, classifying the original gas leakage collection data according to the pipeline anti-corrosion level, and the original gas leakage collection data corresponding to each pipeline anti-corrosion level is a level of original gas leakage collection data group;

[0014] S23. Utilize the prediction model and the original gas leakage collection data set of each level to obtain the predicted value of the annual number of gas leakage points and the predicted value of the distance between gas leakage points of each level.

[0015] Preferably, step S23 includes the following steps:

[0016] S231, set the original value of the annual gas leakage point number in each level of original gas leakage collection data group to be N 1 , the original value of the leakage point spacing is D 1 , the annual service time is T and the gas operating pressure is P, the annual number of gas leakage points is predicted to be N 2 The predicted value of the distance between leakage points is D 2 , the original value of the annual leakage point number is N 1 Contains M annual leakage point number original point value {n 11 ,n 12 ,…,n 1M}; Original value of leakage point spacing D 1 Contains M leakage points with original point values ​​{d 11 ,d 12 ,…,d 1M};

[0017] S232, establishing a prediction model, the prediction model including: a first regression model and a second regression model;

[0018] The first regression model is: The constant a 0 , a1 , a 2 , a 3 , b 1 , b 2 and b 3 The method of obtaining is: the original value of the annual leakage point number N 1 Substitute N into Formula 1 2 Statistical regression yields;

[0019] The second regression model is: The constant c 0 , c 1 , c 2 , c 3 , d 1 , d 2 and 3 The method of obtaining is: the original value of the leakage point spacing D 1 Substitute D into Formula 1 2 Statistical regression yields;

[0020] S233, substitute the annual usage time T and the gas operating pressure P into formula 1 to obtain the annual leakage point number prediction value N 2 , annual leakage point number prediction value N 2 Contains M annual leakage point number prediction point values ​​{n 21 ,n 22 ,…,n 2M}; Substitute the service time T and gas operating pressure P into formula 1 to obtain the predicted value D of the leakage point spacing 2 , predicted value of leakage point spacing D 2 Contains M leakage point spacing prediction point values ​​{d 21 ,d 22 ,…,d 2M};

[0021] S234, Calculation

[0022] S235, correct the original value of the number of annual leakage points N 1 Get the corrected annual leakage point number N 3 , Correct the original value of the leakage point spacing to get the corrected annual leakage point number D 3 , The correction formula is:

[0023]

[0024] Preferably, in S3, the number of annual leakage points N after correction is calculated. 3 And the number of annual leakage points after correction D 3 Make decisions on gas pipeline maintenance and repair.

[0025] Preferably, step S3 comprises the following steps:

[0026] S31. Assume the total length of the gas pipeline is L0;

[0027] S32, calculation

[0028] S33, calculate L 1 The number of Q that meets condition one is:

[0029] S34. Determine whether Q is greater than or equal to If so, execute decision one; if not, execute decision two; decision one is: replace all gas pipelines; decision two is: repair part of the gas pipelines.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] In this application, the previous gas pipeline leakage point data (that is, the original gas leakage collection data, which includes the original value of the annual number of leakage points, the original value of the leakage point spacing, the years of use, the pipeline corrosion protection level and the gas operating pressure) are used to decide whether all subsequent gas pipelines should be replaced. As a result, there is no basis for replacing all gas pipelines, which leads to the decision being separated from the original gas leakage collection data, and all gas pipelines that are close to the edge of damage cannot be replaced in time.

[0032] Other advantages, objectives and features of the present invention will be embodied in part through the following description, and in part will be understood by those skilled in the art through study and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A flow chart of a decision-making method for monitoring the continuous gas supply status of a gas pipeline. DETAILED DESCRIPTION

[0034] In order to make the technical means, creative features, objectives and functions achieved by the present invention clearer and easier to understand, the present invention is further explained below in conjunction with the accompanying drawings and specific implementation methods.

[0035] like Figure 1 As shown, the present invention provides a method for monitoring and making decisions on the continuous gas supply status of a gas pipeline, comprising the following steps:

[0036] S1. Obtaining the original gas leakage collection data, which includes: the original value of the number of annual leakage points, the original value of the distance between leakage points, the service time in years, the pipeline anti-corrosion level and the gas operation pressure. The original value of the number of annual leakage points indicates the number of leakage points in the gas pipeline each year, the original value of the distance between leakage points is the distance between two adjacent leakage points, the service time in years indicates how many years it has been used since it was put into use, the pipeline anti-corrosion level indicates the expert's rating of the pipeline anti-corrosion operation, and the rating range is an integer within (0,5), and the gas operation pressure indicates the gas pressure in the gas pipeline;

[0037] S2. Processing the original gas leakage collection data;

[0038] S3. Use the processed raw gas leakage collection data to make gas pipeline maintenance and repair decisions.

[0039] A pressure gauge is installed on the gas pipeline, and the pressure gauge is used to detect the gas pressure in the gas pipeline. The output end of the pressure gauge is connected to the input end of the signal processing module, and the output end of the signal processing module is connected to the input end of the controller. The controller is connected to the first communication module, and the first communication module is connected to the second communication module, and the second communication module is connected to the general monitoring cloud platform. The gas operation pressure is obtained through real-time monitoring.

[0040] Step S2 includes the following steps:

[0041] S21. Remove the data group with the original value of the annual leakage point number less than or equal to 2; (to avoid the interference of less data with the subsequent judgment results. When there is less data, less information can be used)

[0042] S22, classifying the original gas leakage collection data according to the pipeline anti-corrosion level, and the original gas leakage collection data corresponding to each pipeline anti-corrosion level is a level of original gas leakage collection data group;

[0043] S23, using the prediction model and each level of original gas leakage collection data group to obtain the annual leakage point number prediction value and leakage point spacing prediction value of each level. (The annual leakage point number prediction value and leakage point spacing prediction value are calculated based on each level of original gas leakage collection data group, providing a basis for subsequent correction values)

[0044] Step S23 includes the following steps:

[0045] S231, set the original value of the annual gas leakage point number in each level of original gas leakage collection data group to be N 1 , the original value of the leakage point spacing is D 1 , the annual service time is T and the gas operating pressure is P, the annual number of gas leakage points is predicted to be N 2 The predicted value of the distance between leakage points is D2 , the original value of the annual leakage point number is N 1 Contains M annual leakage point number original point value {n 11 ,n 12 ,…,n 1M}; Original value of leakage point spacing D 1 Contains M leakage points with original point values ​​{d 11 ,d 12 ,…,d 1M};

[0046] S232, establishing a prediction model, the prediction model including: a first regression model and a second regression model;

[0047] The first regression model is: The constant a 0 , a 1 , a 2 , a 3 , b 1 , b 2 and b 3 The method of obtaining is: the original value of the annual leakage point number N 1 Substitute N into Formula 1 2 Statistical regression yields;

[0048] The second regression model is: The constant c 0 , c 1 , c 2 , c 3 , d 1 , d 2 and 3 The method of obtaining is: the original value of the leakage point spacing D 1 Substitute D into Formula 1 2 Statistical regression yields;

[0049] S233, substitute the annual usage time T and the gas operating pressure P into formula 1 to obtain the annual leakage point number prediction value N 2 , annual leakage point number prediction value N 2 Contains M annual leakage point number prediction point values ​​{n 21 ,n 22 ,…,n 2M}; Substitute the service time T and gas operating pressure P into formula 1 to obtain the predicted value D of the leakage point spacing 2 , predicted value of leakage point spacing D 2 Contains M leakage point spacing prediction point values ​​{d 21 ,d 22 ,…,d 2M}; (Through the first regression model and the second regression model, the predicted values ​​(i.e., the predicted value of the annual number of leakage points and the predicted value of the distance between leakage points) are obtained)

[0050] S234, Calculation (The mean absolute error between the predicted value and the original value is obtained)

[0051] S235, correct the original value of the number of annual leakage points N 1 Get the corrected annual leakage point number N 3 , Correct the original value of the leakage point spacing to get the corrected annual leakage point number D 3 , The correction formula is:

[0052]

[0053] (Since there is definitely a large error between the original value and the predicted value, and because the actual original value may change due to some factors, in order to eliminate the error between the original value and the predicted value, this application uses the proportional relationship between the difference and the mean absolute error, adds the proportional difference, and takes a value between the original value and the predicted value as the corrected value, so that the original value is close to the predicted value, thereby retaining the possibility that the actual original value may change due to some factors, and also using the predicted value, which is more in line with the decision-making needs, making the decision more practical and more accurate)

[0054] S3 is based on the corrected annual number of leakage points N 3 And the number of annual leakage points after correction D 3 Make a gas pipeline maintenance decision. Finally, the corrected value is used to make a gas pipeline maintenance decision, which is whether to replace all gas pipelines or repair part of the gas pipeline.

[0055] Step S3 includes the following steps: (Specific steps for making a decision)

[0056] S31. Assume the total length of the gas pipeline is L0;

[0057] S32, calculation

[0058] S33, calculate L 1 The number of Q that meets condition one is:

[0059] S34. Determine whether Q is greater than or equal to If so, execute decision one; if not, execute decision two; decision one is: replace all gas pipelines; decision two is: repair part of the gas pipelines.

[0060] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A method for monitoring and making decisions on the continuous gas supply status of a gas pipeline, characterized in that: The steps include: S1. Obtaining the original gas leakage collection data, which includes: the original value of the number of annual leakage points, the original value of the distance between leakage points, the service life, the pipeline anti-corrosion level and the gas operation pressure. The original value of the number of annual leakage points indicates the number of leakage points in the gas pipeline each year, the original value of the distance between leakage points is the distance between two adjacent leakage points, the service life indicates how many years it has been used since it was put into use, the pipeline anti-corrosion level indicates the expert's rating of the pipeline anti-corrosion operation, and the rating range is an integer within (0,5), and the gas operation pressure indicates the gas pressure in the gas pipeline; S2. Processing the original gas leakage collection data; S3. Use the processed raw gas leakage collection data to make gas pipeline maintenance and repair decisions.

2. A method for monitoring and deciding the continuous gas supply status of a gas pipeline according to claim 1, characterized in that: A pressure gauge is installed on the gas pipeline, and the pressure gauge is used to detect the gas pressure in the gas pipeline. The output end of the pressure gauge is connected to the input end of the signal processing module, and the output end of the signal processing module is connected to the input end of the controller. The controller is communicatively connected to the first communication module, the first communication module is communicatively connected to the second communication module, and the second communication module is communicatively connected to the overall monitoring cloud platform.

3. A method for monitoring and deciding the continuous gas supply status of a gas pipeline according to claim 1, characterized in that: Step S2 includes the following steps: S21, removing the data group whose original value of annual leakage point number is less than or equal to 2; S22, classifying the original gas leakage collection data according to the pipeline anti-corrosion level, and the original gas leakage collection data corresponding to each pipeline anti-corrosion level is a level of original gas leakage collection data group; S23. Utilize the prediction model and the original gas leakage collection data set of each level to obtain the predicted value of the annual number of gas leakage points and the predicted value of the distance between gas leakage points of each level.

4. A method for monitoring and deciding the continuous gas supply status of a gas pipeline according to claim 3, characterized in that: Step S23 includes the following steps: S231, assuming that the original value of the annual number of gas leakage points in each level of the original gas leakage collection data group is N1, the original value of the gas leakage point spacing is D1, the annual use time is T and the gas operation pressure is P, the annual gas leakage point number prediction value is N2, the leakage point spacing prediction value is D2, the annual gas leakage point number original value is N1, and contains M annual gas leakage point number original point values ​​{n 11 ,n 12 ,…,n 1M }; The original value D1 of the leakage point spacing contains M original point values ​​of the leakage point spacing {d 11 ,d 12 ,…,d 1M }; S232, establishing a prediction model, the prediction model including: a first regression model and a second regression model; The first regression model is: The constants a0, a1, a2, a3, b1, b2 and b3 in the formula are obtained by substituting the original value of the annual leakage point number N1 into N2 in formula 1 for statistical regression; The second regression model is: The constants c0, c1, c2, c3, d1, d2 and d3 in the formula are obtained by substituting the original value D1 of the leakage point spacing into D2 in formula 1 for statistical regression; S233, substituting the annual use time T and the gas operating pressure P into Formula 1 to obtain the annual leakage point number prediction value N2, the annual leakage point number prediction value N2 contains M annual leakage point number prediction point values ​​{n 21 ,n 22 ,…,n 2M }; Substitute the usage time T and the gas operating pressure P into formula 1 to obtain the leakage point spacing prediction value D2, which contains M leakage point spacing prediction point values ​​{d 21 ,d 22 ,…,d 2M }; S234, Calculation S235. Correct the original value N1 of the annual leakage point number to obtain the corrected annual leakage point number Correct the original value of the leakage point spacing to get the corrected annual leakage point number The correction formula is:

5. A method for monitoring and deciding the continuous gas supply status of a gas pipeline according to claim 4, characterized in that: In S3, a gas pipeline maintenance decision is made based on the corrected annual number of gas leakage points N3 and the corrected annual number of gas leakage points D3.

6. A method for monitoring and deciding the continuous gas supply status of a gas pipeline according to claim 5, characterized in that: Step S3 includes the following steps: S31. Assume the total length of the gas pipeline is L0; S32, calculation S33, calculate the number Q of L1 that meets condition 1, where condition 1 is: S34. Determine whether Q is greater than or equal to If so, execute decision one; if not, execute decision two; decision one is: replace all gas pipelines; decision two is: repair part of the gas pipelines.

Images