CN113864664A - Pipe network leakage early warning method and system based on flow distribution probability calculation - Google Patents
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Abstract
The invention discloses a pipe network leakage early warning method and system based on flow distribution probability calculation. The method comprises the following steps: calculating the mean value and the standard deviation of the flow of the area to be monitored in a first preset time; determining a leakage grade early warning limit according to the mean value and the standard deviation of the flow of the area to be monitored in a first preset time; calculating early warning proportions of the flow of the area to be monitored in a second preset time, which are greater than the early warning limit of the leakage level, and respectively recording as a first early warning proportion, a second early warning proportion and a third early warning proportion; and judging whether leakage occurs or not according to the real-time flow, the leakage grade early warning limit and the early warning proportion of the area to be monitored. The method takes the mean value, the upper limit of the 40% confidence interval and the upper limit of the 80% confidence interval as the limits of different levels of leakage early warning respectively, and has simple process and small calculated amount; and comparing the actually measured water use data with the early warning upper limit and the early warning proportion to judge whether leakage occurs or not, and meanwhile, determining the leakage level.
Description
Technical Field
The invention relates to the technical field of urban water supply pipe network monitoring, in particular to a pipe network leakage early warning method and system based on flow distribution probability calculation.
Background
The water supply network is an important infrastructure of a city, the stable operation of the water supply network is a basic condition for guaranteeing the life of people and the industrial and agricultural production, and is also a foundation for maintaining normal social order, but the leakage of the water supply network is a common problem in the domestic and foreign water supply industry. Pipe network leakage early warning is the important auxiliary technology of control pipe network leakage, and after the pipe network takes place the leakage, can produce an extra flow, so flow can change on relevant pipeline, forms the flow mode different before the leakage takes place, in recent years, along with wisdom water utilities rapid development, has produced a large amount of, meticulous water supply network operating data, utilizes abnormal flow data early warning leakage's method to obtain wide application. However, these leakage early warning methods are often established on the basis of complex data analysis methods or models, and have certain difficulty in application.
Disclosure of Invention
In order to solve the problems, the invention provides a pipe network leakage early warning method and system based on flow distribution probability calculation.
In order to achieve the purpose, the invention provides the following scheme:
a pipe network leakage early warning method based on flow distribution probability calculation comprises the following steps:
calculating the mean value and the standard deviation of the flow of the area to be monitored in a first preset time;
determining a leakage grade early warning limit according to the mean value and the standard deviation of the flow of the area to be monitored in a first preset time; the leakage grade early warning limit comprises a grade 1 early warning limit, a grade 2 early warning limit and a grade 3 early warning limit;
calculating early warning proportions of the flow of the area to be monitored in a second preset time, which are greater than the leakage grade early warning limit, and respectively recording as a first early warning proportion, a second early warning proportion and a third early warning proportion;
and judging whether leakage occurs or not according to the real-time flow of the area to be monitored, the leakage grade early warning limit and the early warning proportion.
Optionally, the determining a leakage level early warning limit according to a mean value and a standard deviation of a flow of an area to be monitored within a first preset time specifically includes:
taking the average value of the flow of the area to be monitored in the first preset time as a level 1 early warning limit;
calculating the upper limit of a confidence interval of 40% according to the mean value and the standard deviation of the flow of the area to be monitored in the first preset time, and taking the upper limit as a 2-level early warning limit;
and calculating an upper limit of an 80% confidence interval according to the mean value and the standard deviation of the flow of the area to be monitored in the first preset time, and taking the upper limit as a 3-level early warning limit.
Optionally, the calculation formula of the upper limit of the 40% confidence interval is as follows:
UB40％＝μi,d+0.52×σi,d
wherein, UB40％At 40% upper confidence interval, μi,dIs the average value, sigma, of the flow of the area to be monitored in the first preset timei,dThe standard deviation of the flow of the area to be monitored in a first preset time is obtained;
the upper limit of the 80% confidence interval is calculated as follows:
UB80％＝μi,d+1.28×σi,d
wherein, UB80％Is the upper limit of the 80% confidence interval.
Optionally, the method further comprises: and when the leakage is judged to occur, determining the leakage grade.
Optionally, the method for judging whether leakage occurs according to the real-time flow of the region to be monitored, the leakage level early warning limit and the early warning proportion specifically includes:
when the real-time flow of the area to be monitored is smaller than the average value of the flow of the area to be monitored in the first preset time, judging that no leakage occurs;
when the real-time flow of the area to be monitored is larger than the average value of the flow of the area to be monitored in a first preset time and the first early warning proportion is larger than 90%, judging that the leakage is 1 level;
when the real-time flow of the area to be monitored is larger than the upper limit of the confidence interval of 40% and the second early warning proportion is larger than 70%, judging that the leakage is level 2;
and when the real-time flow of the area to be monitored is greater than the upper limit of the confidence interval of 80% and the third early warning proportion is greater than 50%, judging that the leakage is level 3.
Optionally, multiple levels of leakage occur simultaneously within the same time, with a high level as a standard; when multi-level leakage occurs in continuous time, the high level is taken as the standard.
The invention also provides a pipe network leakage early warning system based on flow distribution probability calculation, which comprises the following components:
the mean value and standard deviation calculation module is used for calculating the mean value and standard deviation of the flow of the area to be monitored in the first preset time;
the leakage grade early warning limit determining module is used for determining a leakage grade early warning limit according to the mean value and the standard deviation of the flow of the area to be monitored in the first preset time; the leakage grade early warning limit comprises a grade 1 early warning limit, a grade 2 early warning limit and a grade 3 early warning limit;
the early warning proportion calculation module is used for calculating early warning proportions that the flow of the area to be monitored is greater than the early warning limit of the leakage level within second preset time, and recording the early warning proportions as a first early warning proportion, a second early warning proportion and a third early warning proportion respectively;
and the leakage judgment module is used for judging whether leakage occurs or not according to the real-time flow of the area to be monitored, the leakage grade early warning limit and the early warning proportion.
Optionally, the method further comprises: and the leakage grade determining module is used for determining the leakage grade after the leakage is judged to occur.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides a pipe network leakage early warning method based on flow distribution probability calculation, which comprises the following steps: calculating the mean value and the standard deviation of the flow of the area to be monitored in a first preset time; determining a leakage grade early warning limit according to the mean value and the standard deviation of the flow of the area to be monitored in a first preset time; the leakage grade early warning limit comprises a grade 1 early warning limit, a grade 2 early warning limit and a grade 3 early warning limit; calculating early warning proportions of the flow of the area to be monitored in a second preset time, which are greater than the leakage grade early warning limit, and respectively recording as a first early warning proportion, a second early warning proportion and a third early warning proportion; and judging whether leakage occurs or not according to the real-time flow of the area to be monitored, the leakage grade early warning limit and the early warning proportion. The method takes the mean value, the upper limit of the 40% confidence interval and the upper limit of the 80% confidence interval as the limits of different levels of leakage early warning respectively, and has simple process and small calculated amount; and comparing the actually measured water use data with the early warning upper limit and the early warning proportion to judge whether leakage occurs or not, and meanwhile, determining the leakage level. The invention has simple analysis process and can carry out leakage early warning classification.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a flow chart of a pipe network leakage early warning method based on flow distribution probability calculation according to an embodiment of the present invention;
fig. 2 shows the early warning result of leakage from 2018-6-25 to 2018-7-1.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
As shown in fig. 1, the pipe network leakage early warning method based on flow distribution probability calculation provided by the present invention includes the following steps:
step 101: and calculating the mean value and the standard deviation of the flow of the area to be monitored in the first preset time.
Selecting a region, typically a DMA (direct memory access, independent metering zone, refers to a small region divided from a water supply network, the region typically having only one water inlet, i.e. all water in the region comes from the water inlet. typically the region is 2000-family 5000 residents), continuously monitoring the water inlet amount, preferably for 15min, and dividing the day into 96 periods, denoted ti(i 1, 2.., 96), recording t each dayiTime interval of flow q of the regioni。
Calculating tiThe mean and standard deviation of the flow from the current day to the first 14 days in the time period are recorded as mui,dAnd σi,dThe formula is as follows:
wherein i represents the ith time period; d represents the current date and can be any day; d-j represents the previous j days of the current date, and the value range is 0-13.
Step 102: determining a leakage grade early warning limit according to the mean value and the standard deviation of the flow of the area to be monitored in a first preset time; the leakage grade early warning limit comprises a grade 1 early warning limit, a grade 2 early warning limit and a grade 3 early warning limit.
The upper confidence interval limits of 40% and 80% were calculated, respectively, as follows:
upper limit of 40% confidence interval: UB40％＝μi,d+0.52×σi,d (3)
Upper 80% confidence interval: UB80％＝μi,d+1.28×σi,d (4)
The mean value mui,dAs a level 1 warning limit, an upper limit UB of a 40% confidence interval40％＝μi,d+0.52×σi,dAs a level 2 warning limit, an upper limit UB of 80% confidence interval80％＝μi,d+1.28×σi,dAs a level 3 warning limit.
Step 103: and calculating early warning proportions of the flow of the area to be monitored in the second preset time, which are greater than the leakage level early warning limit, and recording the early warning proportions as a first early warning proportion, a second early warning proportion and a third early warning proportion respectively.
Calculating the proportion of the flow rate greater than the early warning limits of level 1, level 2 and level 3 in the past 72 hours, and respectively recording the proportion as r1、r2、r3The formula is as follows:
step 104: and judging whether leakage occurs or not according to the real-time flow of the area to be monitored, the leakage grade early warning limit and the early warning proportion. And when the leakage is judged to occur, determining the leakage grade.
For the water flow q occurring in real time, if q < mui,dIf so, judging that no leakage exists; if q > mui,dAnd r is1>If 90%, judging as level 1 leakage; if q > UB40％And r is2>If 70%, judging as 2-level leakage; if q > UB80％And r is3>And if 50%, judging as 3-level leakage. At the same time, the leakage loss of the 1 level, the 2 level and the 3 level occur at the same time, and the high level is taken as the standard; when multi-level leakage occurs in continuous time, the high level is taken as the standard.
The specific numbers (such as 40% confidence interval, 80% confidence interval, and 50%, 70%, and 90% comparison value of the early warning ratio) in the present invention can be adjusted according to the actual situation in the practical application, and are not limited to the above numbers.
According to the method, after flow data are collected and sequences are divided according to collection intervals, the 14-day moving average value and the standard deviation of each sequence data are calculated, then the upper limits of the 40% confidence intervals and the 80% confidence intervals are calculated, the average value, the upper limit of the 40% confidence intervals and the upper limit of the 80% confidence intervals are respectively used as the different level limits of leakage early warning, the process is simple, and the calculated amount is small; and comparing the actually measured water use data with the early warning upper limit and the early warning proportion to judge whether leakage occurs or not, and meanwhile, determining the leakage level. The analysis process is simple and leakage early warning grading can be carried out.
The specific embodiment is as follows:
(1) continuously monitoring the DMA inlet water amount from 19 days 12 and 19 months 2017 to 30 days 6 and 2020, wherein the monitoring time interval is 15min, and the DMA inlet water amount is divided into 96 time periods each day and recorded as ti(i 1, 2.., 96), solving for t each dayiTime of day the water flow q in the regioni. Data for 7 days in 2018, month 6 and 25 to 2018, month 7 and 1 are excerpted here as an example, see table 1.
TABLE 1 certain DMA2018-6-25 to 2018-7-1 water flow (m) throughout the 96 th day period3/h)
(2) Calculating t by using the formulas (1) and (2)iThe mean and standard deviation of the flow from the current day to the first 14 days in the time period are recorded as mui,dAnd σi,d。
The results are shown in tables 2 and 3.
TABLE 214 day traffic data moving average μi,d(m3/h)
Table 314 day traffic data mobile standard deviation sigmai,d(m3/h)
(3) The upper limit of the confidence interval was calculated by the following equations (3) and (4) to be 40% and 80%, respectively, and the results are shown in Table 4.
Upper limit of 40% confidence interval: UB40％＝μi,d+0.52×σi,d (3)
Upper 80% confidence interval: UB80％＝μi,d+1.28×σi,d (4)
Since the amount of data of 7 days is large, the calculation process is shown in table 4 by taking data of 2018, 6 months and 25 days as an example.
Table 42018-6-25 flow data confidence interval upper and lower limits and real-time monitoring data (m)3/h)
(4) The mean value mui,dAs a level 1 warning limit, an upper limit UB of a 40% confidence interval40％＝μi,d+0.52×σi,dAs a level 2 warning limit, an upper limit UB of 80% confidence interval80％＝μi,d+1.28×σi,dAs a level 3 warning limit.
(5) Calculating the proportion of the flow exceeding the early warning limits of level 1, level 2 and level 3 in the past 72 hours by using the formulas (5), (6) and (7), and respectively recording the proportion as r1、r2、r3The results are shown in Table 5.
Table 52018-6-25 to 2018-7-1 proportion (%) -of flow exceeding 1,2 and 3 grade early warning limits
(6) For the water flow q occurring in real time, if q < mui,dIf so, judging that no leakage exists; if q > mui,dAnd r is1>If 90%, judging as level 1 leakage; if q > UB40％And r is2>If 70%, judging as 2-level leakage; if q > UB80％And r is3>And if 50%, judging as 3-level leakage. At the same time, the leakage loss of the 1 level, the 2 level and the 3 level occur at the same time, and the high level is taken as the standard; when multi-level leakage occurs in continuous time, the high level is taken as the standard.
The DMA data is analyzed by the method, and through statistics, 14 leakage early warnings are generated between 2018-6-25 and 2018-7-1, wherein 1 level of leakage early warning is 1 time, 2 levels of leakage early warning is 10 times, and 3 levels of leakage early warning are 3 times. Fig. 2 shows the leakage early warning results from 2018-6-25 to 2018-7-1.
The invention also provides a pipe network leakage early warning system based on flow distribution probability calculation, which comprises the following components:
the mean value and standard deviation calculation module is used for calculating the mean value and standard deviation of the flow of the area to be monitored in the first preset time;
the leakage grade early warning limit determining module is used for determining a leakage grade early warning limit according to the mean value and the standard deviation of the flow of the area to be monitored in the first preset time; the leakage grade early warning limit comprises a grade 1 early warning limit, a grade 2 early warning limit and a grade 3 early warning limit;
the early warning proportion calculation module is used for calculating early warning proportions that the flow of the area to be monitored is greater than the early warning limit of the leakage level within second preset time, and recording the early warning proportions as a first early warning proportion, a second early warning proportion and a third early warning proportion respectively;
and the leakage judgment module is used for judging whether leakage occurs or not according to the real-time flow of the area to be monitored, the leakage grade early warning limit and the early warning proportion.
Further comprising: and the leakage grade determining module is used for determining the leakage grade after the leakage is judged to occur.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (8)
1. A pipe network leakage early warning method based on flow distribution probability calculation is characterized by comprising the following steps:
calculating the mean value and the standard deviation of the flow of the area to be monitored in a first preset time;
determining a leakage grade early warning limit according to the mean value and the standard deviation of the flow of the area to be monitored in a first preset time; the leakage grade early warning limit comprises a grade 1 early warning limit, a grade 2 early warning limit and a grade 3 early warning limit;
calculating early warning proportions of the flow of the area to be monitored in a second preset time, which are greater than the leakage grade early warning limit, and respectively recording as a first early warning proportion, a second early warning proportion and a third early warning proportion;
and judging whether leakage occurs or not according to the real-time flow of the area to be monitored, the leakage grade early warning limit and the early warning proportion.
2. The pipe network leakage early warning method based on flow distribution probability calculation of claim 1, wherein the determining of the leakage level early warning limit according to the mean value and the standard deviation of the flow of the area to be monitored in the first preset time specifically comprises:
taking the average value of the flow of the area to be monitored in the first preset time as a level 1 early warning limit;
calculating the upper limit of a confidence interval of 40% according to the mean value and the standard deviation of the flow of the area to be monitored in the first preset time, and taking the upper limit as a 2-level early warning limit;
and calculating an upper limit of an 80% confidence interval according to the mean value and the standard deviation of the flow of the area to be monitored in the first preset time, and taking the upper limit as a 3-level early warning limit.
3. The pipe network leakage early warning method based on flow distribution probability calculation of claim 2, wherein the calculation formula of the upper limit of the 40% confidence interval is as follows:
UB40％＝μi,d+0.52×σi,d
wherein, UB40％At 40% upper confidence interval, μi,dIs the average value, sigma, of the flow of the area to be monitored in the first preset timei,dThe standard deviation of the flow of the area to be monitored in a first preset time is obtained;
the upper limit of the 80% confidence interval is calculated as follows:
UB80％＝μi,d+1.28×σi,d
wherein, UB80％Is the upper limit of the 80% confidence interval.
4. The pipe network leakage early warning method based on flow distribution probability calculation of claim 1, further comprising: and when the leakage is judged to occur, determining the leakage grade.
5. The pipe network leakage early warning method based on flow distribution probability calculation of claim 4, wherein the judging whether leakage occurs or not according to the real-time flow of the region to be monitored, the leakage level early warning limit and the early warning proportion specifically comprises:
when the real-time flow of the area to be monitored is smaller than the average value of the flow of the area to be monitored in the first preset time, judging that no leakage occurs;
when the real-time flow of the area to be monitored is larger than the average value of the flow of the area to be monitored in a first preset time and the first early warning proportion is larger than 90%, judging that the leakage is 1 level;
when the real-time flow of the area to be monitored is larger than the upper limit of the confidence interval of 40% and the second early warning proportion is larger than 70%, judging that the leakage is level 2;
and when the real-time flow of the area to be monitored is greater than the upper limit of the confidence interval of 80% and the third early warning proportion is greater than 50%, judging that the leakage is level 3.
6. The pipe network leakage early warning method based on flow distribution probability calculation of claim 5, wherein multiple levels of leakage occur simultaneously within the same time, subject to high level; when multi-level leakage occurs in continuous time, the high level is taken as the standard.
7. The utility model provides a pipe network leakage early warning system based on flow distribution probability calculates which characterized in that includes:
the mean value and standard deviation calculation module is used for calculating the mean value and standard deviation of the flow of the area to be monitored in the first preset time;
the leakage grade early warning limit determining module is used for determining a leakage grade early warning limit according to the mean value and the standard deviation of the flow of the area to be monitored in the first preset time; the leakage grade early warning limit comprises a grade 1 early warning limit, a grade 2 early warning limit and a grade 3 early warning limit;
the early warning proportion calculation module is used for calculating early warning proportions that the flow of the area to be monitored is greater than the early warning limit of the leakage level within second preset time, and recording the early warning proportions as a first early warning proportion, a second early warning proportion and a third early warning proportion respectively;
and the leakage judgment module is used for judging whether leakage occurs or not according to the real-time flow of the area to be monitored, the leakage grade early warning limit and the early warning proportion.
8. The pipe network leakage early warning system based on flow distribution probability calculation of claim 7, further comprising:
and the leakage grade determining module is used for determining the leakage grade after the leakage is judged to occur.
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| 江永伟;杨奇;王海涛;应志豪;何必仕;徐哲;: "小区漏损预警中最小夜间流量法的改进与应用", 浙江水利水电学院学报, no. 01, pages 68 - 71 * |
| 郝志萍;侯煜堃;崔昌: "计量小区(DMA)夜间最小流量解析方法探讨与案例研究", 南水北调与水利科技, no. 04, pages 124 - 127 * |
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