CN117387008A - Early warning classification method for judging leakage of water supply pipeline through pressure - Google Patents
Early warning classification method for judging leakage of water supply pipeline through pressure Download PDFInfo
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- CN117387008A CN117387008A CN202311355096.9A CN202311355096A CN117387008A CN 117387008 A CN117387008 A CN 117387008A CN 202311355096 A CN202311355096 A CN 202311355096A CN 117387008 A CN117387008 A CN 117387008A
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- 238000000034 method Methods 0.000 title claims abstract description 25
- 238000012502 risk assessment Methods 0.000 claims abstract description 18
- 238000012544 monitoring process Methods 0.000 claims abstract description 14
- 230000008859 change Effects 0.000 claims abstract description 12
- 230000008569 process Effects 0.000 claims abstract description 7
- 238000011156 evaluation Methods 0.000 claims description 101
- 230000006378 damage Effects 0.000 claims description 18
- 238000012549 training Methods 0.000 claims description 9
- 230000002093 peripheral effect Effects 0.000 claims description 7
- 238000013210 evaluation model Methods 0.000 claims description 6
- 238000007418 data mining Methods 0.000 claims description 5
- 238000009933 burial Methods 0.000 claims description 4
- 238000012423 maintenance Methods 0.000 claims description 4
- 238000013507 mapping Methods 0.000 claims description 4
- 239000000463 material Substances 0.000 claims description 3
- 239000002184 metal Substances 0.000 claims description 3
- 230000002159 abnormal effect Effects 0.000 abstract description 2
- 230000004044 response Effects 0.000 abstract description 2
- 238000003064 k means clustering Methods 0.000 description 4
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Classifications
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/02—Preventing, monitoring, or locating loss
Abstract
The invention discloses a water supply pipeline leakage early warning grading method based on pressure judgment, which relates to the technical field of water supply pipeline leakage early warning and comprises the following steps: s1, identifying whether leakage occurs in the water supply pipeline or not through pressure change of the water supply pipeline based on pressure data of daily monitoring of the water supply pipeline, S2, performing risk assessment on the leaked water supply pipeline based on a risk assessment model, and assessing leakage risk level of the water supply pipeline, and S3, outputting leakage early warning level through the pressure data of daily monitoring of the water supply pipeline and the leakage risk level of the water supply pipeline. According to the invention, through monitoring the pressure change of the water supply pipeline in real time, abnormal conditions can be captured in time, and once leakage is found, an early warning signal can be immediately given out, so that the response time of the leakage can be greatly shortened, the recognition and treatment efficiency of leakage events can be improved, the occurrence and risk degree of the leakage can be automatically judged, and the early warning process can be completed without manual intervention.
Description
Technical Field
The invention relates to the technical field of water supply pipeline leakage early warning, in particular to a water supply pipeline leakage early warning grading method based on pressure judgment.
Background
The leakage of the water supply pipeline can bring potential threat to the surrounding environment and life safety of people, firstly, the water leakage of the water supply pipeline can lead to deterioration of water quality, when the water in the pipeline flows out, impurities and pollutants in the water can flow out along with the water, so as to pollute the water source of a water supply system, secondly, the water leakage of the water supply pipeline can lead to ground collapse, when the water leakage of the pipeline occurs, the water in the water supply pipeline can infiltrate into the ground, so that the soil becomes soft and loses stability, and the soft soil can gradually run off over time, so that cavities are formed under the ground, and if the cavities are too large, the ground collapses, so that huge risks are brought to the life safety and property safety of surrounding buildings and residents;
at present, the water supply pipeline mainly adopts leakage monitor equipment, whether leakage is detected by monitoring vibration and sound frequency of the pipeline, and the main principle of judging the early warning level through a sensor is as follows: 1. setting a threshold range according to the corresponding early warning level, 2, accessing real-time sensor monitoring data, 3, judging the corresponding level of the early warning according to the real-time monitoring data and the threshold range set by the corresponding early warning level; because the water supply leakage monitor detects the sound wave around the water pipe to find the water leakage condition, when other noises such as human voice, vehicle voice and the like exist around the water pipe, the leakage monitor can report by mistake, and under the condition that the pipeline is shallow in burial depth or the pipeline is aged, the situation of false report is easy to occur.
Disclosure of Invention
The invention aims to provide a water supply pipeline leakage early warning classification method based on pressure judgment, so as to solve the problems in the background technology.
In order to achieve the above purpose, the present invention provides the following technical solutions: a method for judging leakage early warning classification of a water supply pipeline by pressure comprises the following steps:
s1, identifying whether leakage occurs in a water supply pipeline or not through pressure change of the water supply pipeline based on daily monitored pressure data of the water supply pipeline;
s2, performing risk assessment on the leakage water supply pipeline based on a risk assessment model, and assessing the leakage risk level of the water supply pipeline;
and S3, outputting a leakage early warning grade through pressure data of daily monitoring of the water supply pipeline and the leakage risk grade of the water supply pipeline.
Preferably, the step S1 specifically includes the following steps:
s101, marking numbers for the water supply pipeline segments based on the positions of the water supply pipeline segments;
s102, installing a pressure sensor at a node of the water supply pipeline section, and monitoring the pressure change of the water supply pipeline in real time through the pressure sensor.
Preferably, the step S2 specifically includes the following steps:
s201, determining an evaluation index of the leakage risk level of the water supply pipeline;
s202, determining corresponding evaluation index weights by adopting a analytic hierarchy process according to different evaluation indexes of leakage risk levels of the water supply pipelines;
s203, constructing a pipeline risk assessment model according to an assessment index of the leakage risk level of the water supply pipeline;
s204, acquiring training data according to an evaluation index of the leakage risk level of the water supply pipeline, and training the pipeline risk evaluation model according to the training data so as to obtain a trained pipeline risk evaluation model;
s205, performing risk assessment on the target according to the constructed pipeline risk assessment model, and converting the assessment result into a corresponding pipeline leakage risk level.
Preferably, the evaluation indexes comprise a first-level evaluation index, a second-level evaluation index and a third-level evaluation index, wherein the first-level evaluation index comprises pipe network failure probability, pipe network leakage hazard and current running conditions, the second-level evaluation index of the pipe network failure probability comprises pipe network basic attributes, natural damage and artificial damage factors, the third-level evaluation index of the pipe network basic attributes comprises pipe age, pipe materials, burial depths and whether auxiliary facilities exist above the pipe, the third-level evaluation index of the natural damage comprises whether an anticorrosive layer of a metal pipe is damaged or not and whether geological disaster hidden danger points exist in the range of 100 meters around, and the third-level evaluation index of the artificial damage factors comprises the type of a region where the pipe is located, the type of a place above the pipe and pipe protection measures.
Preferably, the second-level evaluation index of the pipe network leakage hazard comprises the type of the road network, the population density of the area, the economic density of the area, the pipe diameter, the season and the number of large water users within the range of 3 km around, and the second-level evaluation index of the current running condition comprises the leakage condition of 3 years, the maintenance condition after leakage, the alarm condition of the peripheral pressure flow loss monitor and the alarm disposal condition.
Preferably, the evaluation index weight comprises a first-level evaluation index weight, a second-level evaluation index weight and a third-level evaluation index weight, wherein the pipe network failure probability weight of the first-level evaluation index is specifically calculated by 20%, the pipe network leakage hazard weight of the first-level evaluation index is specifically calculated by 30%, the current running condition of the first-level evaluation index is specifically calculated by 50%, the pipe network basic attribute weight of the second-level evaluation index is specifically calculated by 30%, the natural destruction weight of the second-level evaluation index is specifically calculated by 30%, the artificial destruction factor weight of the second-level evaluation index is specifically calculated by 40%, the road network type weight of the second-level evaluation index is specifically calculated by 10%, the regional population density weight of the second-level evaluation index is specifically calculated by 10%, the pipe diameter weight of the second-level evaluation index is specifically calculated by 30%, the seasonal weight of the second-level evaluation index is specifically calculated by 20%, the large water consumption user number weight in the peripheral 3 km range of the second-level evaluation index is specifically calculated by 20%, the second-level evaluation index is specifically calculated by 10%, and the second-level evaluation index is calculated by 30%, and the leakage alarm condition is calculated by 30%.
Preferably, the pipeline leakage risk level comprises low risk, general risk, larger risk and major risk, and the pipeline leakage early warning level comprises primary early warning, secondary early warning, tertiary early warning and quaternary early warning.
Preferably, the step S3 specifically includes the following steps:
s301, analyzing pressure data through a data mining algorithm, obtaining a pressure change trend of the current time, and fitting a predicted value P of the current time 0 The data mining algorithm is specifically a K-means clustering algorithm, and the K-means clustering algorithm is specifically as follows:
J＝∑(∑||x-u′|| 2 )
wherein J represents an objective function, x represents the collected pressure data sample and u' represents the center point of the collected pressure data cluster;
s302, according to the collected real-time pressure data P and predicted value P of the current time 0 Calculating to obtain P/P 0 Is a ratio of (2);
s303, determining different P/P according to the constructed water supply pipeline leakage risk level classification standard 0 Mapping relation between the ratio range and each risk level;
s304, according to the calculated P/P 0 The ratio is used for determining the corresponding pipeline leakage risk level;
and S305, outputting the risk level of the pipeline leakage as a pipeline leakage early warning level according to the determined risk level of the pipeline leakage.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, through monitoring the pressure change of the water supply pipeline in real time, abnormal conditions can be captured in time, and once leakage is found, an early warning signal can be immediately given out, so that the response time of the leakage can be greatly shortened, the recognition and processing efficiency of leakage events can be improved, the occurrence and risk degree of the leakage can be automatically judged, the early warning process can be completed without manual intervention, and therefore, misjudgment or delay caused by human factors can be reduced, and human resources and cost can be saved;
2. the invention can pointedly judge the occurrence position and the range of leakage through the recognition and the risk assessment of the pressure of the water supply pipeline, and improves the accuracy of diagnosis, thereby being capable of more accurately positioning the leakage point after the occurrence of the leakage event, pointedly carrying out disposal and repair, avoiding unnecessary loss and waste.
Drawings
FIG. 1 is a flowchart of an overall method provided by an embodiment of the present invention;
FIG. 2 is a flowchart of step S1 in FIG. 1 according to an embodiment of the present invention;
FIG. 3 is a flowchart of step S2 in FIG. 1 according to an embodiment of the present invention;
FIG. 4 is a flowchart of step S3 in FIG. 1 according to an embodiment of the present invention;
FIG. 5 shows a P/P scheme according to an embodiment of the present invention 0 Mapping relation diagram of ratio range and each risk level;
fig. 6 is a hierarchical analysis chart of evaluation indexes and evaluation index weights according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-6, the present invention provides a technical solution: a method for judging leakage early warning classification of a water supply pipeline by pressure comprises the following steps:
s1, identifying whether leakage occurs in a water supply pipeline or not through pressure change of the water supply pipeline based on daily monitored pressure data of the water supply pipeline;
s2, performing risk assessment on the leakage water supply pipeline based on a risk assessment model, and assessing the leakage risk level of the water supply pipeline;
and S3, outputting a leakage early warning grade through pressure data of daily monitoring of the water supply pipeline and the leakage risk grade of the water supply pipeline.
The step S1 specifically comprises the following steps:
s101, marking numbers for the water supply pipeline segments based on the positions of the water supply pipeline segments;
s102, installing a pressure sensor at a node of a water supply pipeline section, and monitoring the pressure change of the water supply pipeline in real time through the pressure sensor;
the step S2 specifically comprises the following steps:
s201, determining an evaluation index of the leakage risk level of the water supply pipeline;
s202, determining corresponding evaluation index weights by adopting a analytic hierarchy process according to different evaluation indexes of leakage risk levels of the water supply pipelines;
s203, constructing a pipeline risk assessment model according to an assessment index of the leakage risk level of the water supply pipeline;
s204, acquiring training data according to an evaluation index of the leakage risk level of the water supply pipeline, and training the pipeline risk evaluation model according to the training data so as to obtain a trained pipeline risk evaluation model;
s205, performing risk assessment on the target according to the constructed pipeline risk assessment model, and converting the assessment result into a corresponding pipeline leakage risk level;
the evaluation indexes comprise a first-level evaluation index, a second-level evaluation index and a third-level evaluation index, wherein the first-level evaluation index comprises pipe network failure probability, pipe network leakage hazard and current running conditions, the second-level evaluation index of the pipe network failure probability comprises pipe network basic properties, natural damage and artificial damage factors, the third-level evaluation index of the pipe network basic properties comprises pipe age, pipe materials, burial depth and whether auxiliary facilities exist above the pipe, the natural damage third-level evaluation index comprises whether an anticorrosive layer of a metal pipe is damaged or not and whether geological disaster hidden danger exists in the range of 100 meters around, and the third-level evaluation index of the artificial damage factors comprises the type of the area where the pipe is located, the type of the land above the pipe and pipe protection measures;
the secondary evaluation indexes of the pipe network leakage hazard comprise the type of the road network, the population density of the area, the economic density of the area, the pipe diameter, the season and the large water consumption user number within the range of 3 km around, and the secondary evaluation indexes of the current running condition comprise the leakage condition of 3 years, the maintenance condition after leakage, the alarm condition of a peripheral pressure flow leakage monitor and the alarm disposal condition;
the evaluation index weight comprises a first-level evaluation index weight, a second-level evaluation index weight and a third-level evaluation index weight, wherein the pipe network failure probability weight of the first-level evaluation index is 20%, the pipe network leakage hazard weight of the first-level evaluation index is 30%, the current running condition of the first-level evaluation index is 50%, the pipe network basic attribute weight of the second-level evaluation index is 30%, the natural destruction weight of the second-level evaluation index is 30%, the artificial destruction factor weight of the second-level evaluation index is 40%, the road network type weight of the second-level evaluation index is 10%, the regional population density weight of the second-level evaluation index is 10%, the regional economic density weight of the second-level evaluation index is 10%, the pipe diameter weight of the second-level evaluation index is 30%, the seasonal weight of the second-level evaluation index is 20%, the number of large water users in the peripheral 3 km range of the second-level evaluation index is 20%, the leakage condition of the second-level evaluation index is 10%, the maintenance condition weight of the second-level evaluation index is 30%, and the peripheral pressure monitoring alarm condition is 30%;
the pipeline leakage risk level comprises low risk, general risk, larger risk and important risk, and the pipeline leakage early warning level comprises primary early warning, secondary early warning, tertiary early warning and quaternary early warning;
the step S3 specifically comprises the following steps:
s301, analyzing pressure data through a data mining algorithm, obtaining a pressure change trend of the current time, and fitting a predicted value P of the current time 0 The data mining algorithm is specifically a K-means clustering algorithm, and the K-means clustering algorithm is specifically as follows:
J＝∑(∑||x-u′|| 2 )
wherein J represents an objective function, x represents the collected pressure data sample and u' represents the center point of the collected pressure data cluster;
s302, according to the collected real-time pressure data P and predicted value P of the current time 0 Calculating to obtain P/P 0 Is a ratio of (2);
s303, determining different P/P according to the constructed water supply pipeline leakage risk level classification standard 0 Mapping relation between the ratio range and each risk level;
s304, according to the calculated P/P 0 The ratio is used for determining the corresponding pipeline leakage risk level;
and S305, outputting the risk level of the pipeline leakage as a pipeline leakage early warning level according to the determined risk level of the pipeline leakage.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. The method for judging the leakage early warning classification of the water supply pipeline by pressure is characterized by comprising the following steps of:
s1, identifying whether leakage occurs in a water supply pipeline or not through pressure change of the water supply pipeline based on daily monitored pressure data of the water supply pipeline;
s2, performing risk assessment on the leakage water supply pipeline based on a risk assessment model, and assessing the leakage risk level of the water supply pipeline;
and S3, outputting a leakage early warning grade through pressure data of daily monitoring of the water supply pipeline and the leakage risk grade of the water supply pipeline.
2. The method for warning and classifying leakage of a water supply pipeline by pressure judgment according to claim 1, wherein: the step S1 specifically comprises the following steps:
s101, marking numbers for the water supply pipeline segments based on the positions of the water supply pipeline segments;
s102, installing a pressure sensor at a node of the water supply pipeline section, and monitoring the pressure change of the water supply pipeline in real time through the pressure sensor.
3. The method for warning and classifying leakage of a water supply pipeline by pressure judgment according to claim 1, wherein: the step S2 specifically includes the following steps:
s201, determining an evaluation index of the leakage risk level of the water supply pipeline;
s202, determining corresponding evaluation index weights by adopting a analytic hierarchy process according to different evaluation indexes of leakage risk levels of the water supply pipelines;
s203, constructing a pipeline risk assessment model according to an assessment index of the leakage risk level of the water supply pipeline;
s204, acquiring training data according to an evaluation index of the leakage risk level of the water supply pipeline, and training the pipeline risk evaluation model according to the training data so as to obtain a trained pipeline risk evaluation model;
s205, performing risk assessment on the target according to the constructed pipeline risk assessment model, and converting the assessment result into a corresponding pipeline leakage risk level.
4. A water supply pipe leakage warning classification method according to claim 3, characterized in that: the evaluation indexes comprise a first-level evaluation index, a second-level evaluation index and a third-level evaluation index, wherein the first-level evaluation index comprises pipe network failure probability, pipe network leakage hazard and current running conditions, the second-level evaluation index of the pipe network failure probability comprises pipe network basic attributes, natural damage and artificial damage factors, the third-level evaluation index of the pipe network basic attributes comprises pipe age, pipe materials, burial depths and whether auxiliary facilities exist above the pipe, the natural damage third-level evaluation index comprises whether an anticorrosive layer of a metal pipe is damaged or not and whether geological disaster hidden dangers exist in the range of 100 meters at the periphery, and the third-level evaluation index of the artificial damage factors comprises the type of a region where the pipe is located, the type of a place above the pipe and pipe protection measures.
5. The method for warning and classifying leakage of a water supply pipeline by pressure judgment according to claim 4, wherein: the secondary evaluation indexes of the pipe network leakage hazard comprise the type of the road network, the population density of the area, the economic density of the area, the pipe diameter, the season and the quantity of large water users within the range of 3 km around, and the secondary evaluation indexes of the current running condition comprise the leakage condition of nearly 3 years, the maintenance condition after leakage, the alarm condition of a peripheral pressure and flow loss monitor and the alarm disposal condition.
6. The method for warning and classifying leakage of a water supply pipeline by pressure judgment according to claim 5, wherein: the evaluation index weight comprises a first-level evaluation index weight, a second-level evaluation index weight and a third-level evaluation index weight, wherein the pipe network failure probability weight of the first-level evaluation index is 20%, the pipe network leakage hazard weight of the first-level evaluation index is 30%, the current running condition of the first-level evaluation index is 50%, the pipe network basic attribute weight of the second-level evaluation index is 30%, the natural destruction weight of the second-level evaluation index is 30%, the artificial destruction factor weight of the second-level evaluation index is 40%, the road network type weight of the second-level evaluation index is 10%, the area population density weight of the second-level evaluation index is 10%, the pipe diameter weight of the second-level evaluation index is 30%, the season weight of the second-level evaluation index is 20%, the large water user quantity weight in the peripheral 3 km range of the second-level evaluation index is 20%, the road network type weight of the second-level evaluation index is 10%, the second-level evaluation index is 30% of the second-level evaluation index is 30%, and the second-level evaluation index is 30% of the leakage alarm condition.
7. The method for warning and classifying leakage of a water supply pipe by pressure judgment according to claim 2, wherein: the pipeline leakage risk level comprises low risk, general risk, larger risk and important risk, and the pipeline leakage early warning level comprises primary early warning, secondary early warning, tertiary early warning and quaternary early warning.
8. The method for warning and classifying leakage of a water supply pipe by pressure judgment according to claim 7, wherein: the step S3 specifically comprises the following steps:
s301, analyzing pressure data through a data mining algorithm, obtaining a pressure change trend of the current time, and fitting a predicted value P of the current time 0 ；
S302, according to the collected real-time pressure data P and predicted value P of the current time 0 Calculating to obtain P/P 0 Is a ratio of (2);
s303, according to constructionIs used for determining different P/P (P/P) according to the water supply pipeline leakage risk classification standard 0 Mapping relation between the ratio range and each risk level;
s304, according to the calculated P/P 0 The ratio is used for determining the corresponding pipeline leakage risk level;
and S305, outputting the risk level of the pipeline leakage as a pipeline leakage early warning level according to the determined risk level of the pipeline leakage.
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