CN112377821A - Pipeline leakage troubleshooting method and system based on intelligent water meter platform big data - Google Patents
Pipeline leakage troubleshooting method and system based on intelligent water meter platform big data Download PDFInfo
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- CN112377821A CN112377821A CN202011034684.9A CN202011034684A CN112377821A CN 112377821 A CN112377821 A CN 112377821A CN 202011034684 A CN202011034684 A CN 202011034684A CN 112377821 A CN112377821 A CN 112377821A
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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
- F17D5/06—Preventing, monitoring, or locating loss using electric or acoustic means
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F15/00—Details of, or accessories for, apparatus of groups G01F1/00 - G01F13/00 insofar as such details or appliances are not adapted to particular types of such apparatus
- G01F15/07—Integration to give total flow, e.g. using mechanically-operated integrating mechanism
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M3/00—Investigating fluid-tightness of structures
- G01M3/02—Investigating fluid-tightness of structures by using fluid or vacuum
- G01M3/26—Investigating fluid-tightness of structures by using fluid or vacuum by measuring rate of loss or gain of fluid, e.g. by pressure-responsive devices, by flow detectors
- G01M3/28—Investigating fluid-tightness of structures by using fluid or vacuum by measuring rate of loss or gain of fluid, e.g. by pressure-responsive devices, by flow detectors for pipes, cables or tubes; for pipe joints or seals; for valves ; for welds
- G01M3/2807—Investigating fluid-tightness of structures by using fluid or vacuum by measuring rate of loss or gain of fluid, e.g. by pressure-responsive devices, by flow detectors for pipes, cables or tubes; for pipe joints or seals; for valves ; for welds for pipes
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Abstract
The invention relates to a method and a system for checking pipeline leakage based on big data of an intelligent water meter platform, wherein the method comprises the following steps: acquiring general table data of an area to be monitored and user water meter data of the area to be monitored; obtaining the current leakage amount based on the general table data and the user water meter data; determining the current leakage rate according to the current leakage amount and the summary table data; and judging whether the area to be monitored is damaged or not according to the current leakage rate. The invention can automatically identify whether the pipeline in the area to be monitored is leaked or not, has simple structure, low cost and easy maintenance, can inform maintenance personnel in real time, greatly saves the labor cost and reduces the resource waste.
Description
Technical Field
The invention relates to the technical field of water monitoring, in particular to a method and a system for checking pipeline leakage based on intelligent water meter platform big data.
Background
Leakage from town water networks is a common problem and identification and location of leakage has been difficult.
The current common scheme is to use hardware such as sensor to go to detect, but these schemes use cost is higher, and the installation is difficult, and the maintenance degree of difficulty is big, can not inform the maintenance personal in real time moreover and overhaul, causes unnecessary water waste.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide a method and a system for checking pipeline leakage based on big data of an intelligent water meter platform, aiming at the above defects in the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows: a pipeline leakage troubleshooting method based on intelligent water meter platform big data is constructed, and the method comprises the following steps:
acquiring general table data of an area to be monitored and user water meter data of the area to be monitored;
obtaining the current leakage amount based on the general table data and the user water meter data;
determining the current leakage rate according to the current leakage amount and the summary table data;
and judging whether the area to be monitored is damaged or not according to the current leakage rate.
Preferably, the obtaining the current leakage amount based on the summary table data and the user water meter data includes:
summing the user water meter data to obtain total data of the user water meter;
the summary data and the total data of the user water meter are subjected to difference operation, and a difference value between the summary data and the total data of the user water meter is obtained;
and the difference value between the summary table data and the total data of the user water meters is the current leakage quantity.
Preferably, the determining the current leakage rate according to the current leakage amount and the summary table data includes:
the current leakage amount and the summary table data are subjected to quotient operation, and a quotient value of the current leakage amount and the summary table data is obtained;
and the quotient of the current leakage quantity and the summary table data is the current leakage rate.
Preferably, the determining whether the area to be monitored is damaged according to the current leakage rate includes:
comparing the current leakage rate with a preset leakage rate range;
judging whether the current leakage rate is larger than a preset leakage rate range or not;
if so, judging that the area to be monitored is leaked;
and if not, judging that the area to be monitored has no leakage.
Preferably, the method further comprises:
if the leakage of the area to be monitored is judged, then:
collecting first general table data and first user water meter data of the area to be monitored at a first collection time interval;
judging whether leakage occurs or not according to the first general table data and the first user water meter data;
if the data is judged to be leakage, acquiring second to Nth general table data of the area to be monitored and second to Nth user water meter data of the area to be monitored in sequence from a second acquisition time interval to an Nth acquisition time interval; n is a natural number greater than or equal to 0;
judging whether leakage occurs according to the second to Nth master meter data and the second to Nth user water meter data;
if yes, outputting leakage alarm information.
Preferably, the determining whether a loss occurs according to the first total table data includes:
obtaining a first leakage rate according to the first general table data and the first user water meter data;
judging whether the first leakage rate is larger than the preset leakage rate range or not;
if yes, judging that the area to be monitored is leaked;
if not, judging that the difference to be monitored has no leakage.
Preferably, the judging whether the leakage is caused according to the second to nth summary data and the second to nth user water meter data includes:
obtaining a second leakage rate according to the second summary table data and the second user water meter data;
judging whether the second leakage rate is larger than the preset leakage rate range or not;
if yes, obtaining an Nth leakage rate according to the Nth general table data and the Nth user water meter data;
judging whether the Nth leakage rate is larger than the preset leakage rate range or not;
and if so, judging the leakage of the area to be monitored.
Preferably, the second acquisition time interval is smaller than the first acquisition time interval.
Preferably, the acquiring summary data of the area to be monitored and the user water meter data of the area to be monitored comprises:
acquiring historical summary table data of the area to be monitored and historical user water meter data of the area to be monitored;
obtaining historical leakage according to the historical summary table data and the historical user water meter data;
the historical leakage amount and the historical summary table data are subjected to quotient operation, and a quotient value of the historical leakage amount and the historical summary table data is obtained; the quotient of the historical leakage amount and the historical summary table data is the historical leakage rate;
drawing a leakage rate curve based on the historical leakage rate;
and obtaining the preset leakage rate range according to the leakage rate curve.
Preferably, the obtaining of the historical leakage amount according to the historical summary table data and the historical water meter data of the user includes:
summing the data of the water meters of the historical users to obtain total data of the water meters of the historical users;
the historical summary data and the historical user water meter total data are subjected to difference, and a difference value between the historical summary data and the historical user water meter total data is obtained;
and the difference value between the historical summary table data and the historical user water meter total data is the historical leakage amount.
The invention also provides a pipeline leakage troubleshooting system based on the intelligent water meter platform big data, which comprises the following components: the intelligent water meter monitoring system comprises one or more general meters arranged in an area to be monitored, user water meters in the area to be monitored and an intelligent water meter platform;
the general meter is used for collecting the total water consumption of the area to be monitored and outputting general meter data;
the user water meter is used for collecting the water consumption of a user corresponding to the user water meter and outputting user level data;
the intelligent water meter platform is respectively communicated with the general meter and the user water meter and is used for:
acquiring general table data of an area to be monitored and user water meter data of the area to be monitored;
obtaining the current leakage amount based on the general table data and the user water meter data;
determining the current leakage rate according to the current leakage amount and the summary table data;
and judging whether the area to be monitored is damaged or not according to the current leakage rate.
Preferably, the method further comprises the following steps:
and the terminal is communicated with the intelligent water meter platform to receive and display the alarm information output by the intelligent water meter platform.
Preferably, the summary table is associated with the user water meter.
The pipeline leakage troubleshooting method and the system based on the intelligent water meter platform big data have the following beneficial effects that: the method comprises the following steps: acquiring general table data of an area to be monitored and user water meter data of the area to be monitored; obtaining the current leakage amount based on the general table data and the user water meter data; determining the current leakage rate according to the current leakage amount and the summary table data; and judging whether the area to be monitored is damaged or not according to the current leakage rate. The invention can automatically identify whether the pipeline in the area to be monitored is leaked or not, has simple structure, low cost and easy maintenance, can inform maintenance personnel in real time, greatly saves the labor cost and reduces the resource waste.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
fig. 1 is a schematic flow chart of a pipeline leakage inspection method based on big data of an intelligent water meter platform according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a pipeline leakage inspection system based on intelligent water meter platform big data according to an embodiment of the present invention.
Detailed Description
For a more clear understanding of the technical features, objects and effects of the present invention, embodiments of the present invention will now be described in detail with reference to the accompanying drawings.
The invention provides a pipeline leakage inspection method and a system based on intelligent water meter platform big data, which can automatically identify whether a pipeline in a region to be monitored is leaked or not by utilizing the intelligent water meter platform big data, have low cost and easy maintenance, can inform maintenance personnel in real time, reduce labor cost and greatly reduce resource waste in order to solve the problems that the existing pipeline leakage monitoring adopts hardware detection, has high use cost, difficult installation and great maintenance difficulty and cannot inform maintenance personnel in real time to overhaul so as to cause unnecessary resource waste.
Referring to fig. 1, fig. 1 is a schematic flow chart of an alternative embodiment of each embodiment of a pipeline leakage inspection method based on big data of an intelligent water meter platform according to the present invention.
As shown in fig. 1, the method for checking the pipeline leakage based on the big data of the intelligent water meter platform comprises the following steps:
and S101, obtaining general table data of the area to be monitored and user water meter data of the area to be monitored.
Specifically, the summary table data is a summary table installed in an area to be monitored, and one or several summary tables may be installed generally. When a summary table is installed in an area to be monitored, the summary table data is the data monitored by the summary table. When a plurality of general tables are installed in the area to be monitored, the data of the general tables are the average value of the data monitored by the general tables.
The user water meter data of the area to be monitored is data monitored by all water meters of all residential users in the area to be monitored.
And S102, obtaining the current leakage quantity based on the summary data and the user water meter data.
Specifically, in some embodiments, obtaining the current leakage amount based on the summary table data and the user water meter data includes:
and step S1021, summing the data of the user water meters to obtain the total data of the user water meters.
And step S1022, subtracting the summary data from the total data of the user water meter to obtain a difference value between the summary data and the total data of the user water meter.
And step S1023, taking the difference value between the summary data and the total data of the user water meter as the current leakage quantity.
And step S103, determining the current leakage rate according to the current leakage amount and the summary table data.
Specifically, in some embodiments, determining the current leakage rate according to the current leakage amount and the summary table data includes: the current leakage amount and the summary table data are subjected to quotient operation, and a quotient value of the current leakage amount and the summary table data is obtained; and the quotient of the current leakage amount and the summary table data is the current leakage rate.
And step S104, judging whether the area to be monitored is damaged or not according to the current leakage rate.
Specifically, in some embodiments, determining whether the area to be monitored is damaged according to the current leakage rate includes:
step S1041, comparing the current leakage rate with a preset leakage rate range.
Step S1042, determine whether the current leakage rate is greater than a preset leakage rate range.
And S1043, if yes, judging that the area to be monitored is lost.
And step S1044, if not, judging that the area to be monitored has no leakage.
In step S1042 and step S1043, when it is determined that the region to be monitored has a leakage, it is a preliminary determination, that is, it is preliminarily determined that the region to be monitored may have a leakage. Therefore, in order to further determine whether the area to be monitored is actually leaky, the present invention further makes the following determination:
specifically, if it is determined that the area to be monitored is lost, then:
step S10431, collecting first total meter data and first user water meter data of the area to be monitored at a first collecting time interval.
It should be noted that the first summary data here is a reading of the summary data at the first collection time interval, and the first user water meter data here is water meter data of all users in the area to be monitored at the first collection time interval.
And S10432, judging whether the leakage occurs or not according to the first total table data and the first user water meter data.
Wherein, the step S10432 may include: obtaining a first leakage rate according to the first main table data and the first user water meter data; judging whether the first leakage rate is larger than a preset leakage rate range or not; if yes, judging the leakage of the area to be monitored; if not, judging that the difference to be monitored has no leakage.
Step S10433, if the leakage is judged, collecting second to Nth general table data of the area to be monitored and second to Nth user water meter data in sequence from the second collection time interval to the Nth collection time interval; n is a natural number not less than 0. It should be noted that the second summary table data here is a reading of the summary table data at the second collection time interval, and the second user water meter data here is water meter data of all users in the area to be monitored at the second collection time interval. It should be noted that, the nth summary table data herein is a reading of the summary table data at the nth collection time interval, and the nth user water meter data herein is water meter data of all users in the area to be monitored at the nth collection time interval.
And S10434, judging whether the leakage occurs or not according to the second to Nth summary data and the second to Nth user water meter data.
Wherein, the step S10434 may include: obtaining a second leakage rate according to the second summary table data and the second user water meter data;
judging whether the second leakage rate is larger than a preset leakage rate range or not;
if yes, obtaining an Nth leakage rate according to the Nth general table data and the Nth user water meter data;
judging whether the Nth leakage rate is larger than a preset leakage rate range or not;
if yes, judging the leakage of the area to be monitored.
And step S10435, if yes, outputting leakage alarm information.
The first acquisition time interval is smaller than the initial acquisition time interval of the summary table and the user water meter, the second acquisition time interval is smaller than the first acquisition time interval, the third acquisition time interval is smaller than the second acquisition time interval, … …, and the Nth acquisition time interval is smaller than the Nth-1 acquisition time interval. Namely, the next acquisition time interval is smaller than the last acquisition time interval until whether the area to be monitored has leakage can be accurately judged. Generally, in practical application, whether the area to be monitored has leakage or not can be accurately judged by the progressive mode for 3-5 times. Of course, it is understood that, in order to improve the accuracy and precision of the determination, the acquisition time interval may be continuously shortened, and the determination times may be sequentially increased, which is not specifically limited by the present invention.
Assuming that the initial collection time interval is 1 hour, the summary data and the user water meter data are read once, the first collection time interval is changed from 1 hour to half an hour, the second collection time interval is 15 minutes, the third collection time interval is 10 minutes, the fourth collection time interval is 5 minutes, and N is 4.
Specifically, if it is preliminarily determined in step S1043 that there is a leakage in the area to be monitored, the first total table data and the first user water meter data are further read at a first collection time interval (half an hour), the first user water meter data are summed, then the first total table data and the first user water meter data are subtracted to obtain a first leakage amount, the first leakage amount and the first total table data are taken as a quotient to obtain a first leakage rate, the first leakage rate is compared with a preset leakage rate range, and if the first leakage rate is greater than the preset leakage rate range (i.e., is greater than an upper limit of the preset leakage rate range), it is determined that there is a leakage. And continuously reading the second summary table data and the second user water meter data once at a second acquisition time interval (15 minutes), summing the second user water meter data, subtracting the second summary table data from the second user water meter data to obtain a second leakage quantity, dividing the second leakage quantity by the second summary table data to obtain a second leakage rate, comparing the second leakage rate with a preset leakage rate range, and if the second leakage rate is greater than the preset leakage rate range (namely, is greater than the upper limit of the preset leakage rate range), judging that the second leakage rate is lost. And continuously reading the third summary table data and the third user water meter data once at a third acquisition time interval (10 minutes), summing the first user water meter data, subtracting the third summary table data from the third user water meter data to obtain a third leakage quantity, quoting the third leakage quantity with the third summary table data to obtain a third leakage rate, comparing the third leakage rate with a preset leakage rate range, and if the third leakage rate is greater than the preset leakage rate range (namely, is greater than the upper limit of the preset leakage rate range), judging as leakage. And continuously reading the fourth master meter data and the fourth user water meter data once at a fourth acquisition time interval (5 minutes), summing the fourth user water meter data, subtracting the fourth master meter data from the fourth user water meter data to obtain a fourth leakage quantity, dividing the fourth leakage quantity by the fourth master meter data to obtain a fourth leakage rate, comparing the fourth leakage rate with a preset leakage rate range, and judging that the leakage is caused if the fourth leakage rate is greater than the preset leakage rate range (namely, is greater than the upper limit of the preset leakage rate range).
Furthermore, after the leakage is determined, the leakage area can be determined according to the relevance between the general table and the area to be monitored, and the leakage warning information is sent to maintenance personnel, so that the maintenance personnel can check and overhaul on site in time.
Further, the method for checking the pipeline leakage based on the big data of the intelligent water meter platform comprises the following steps before the data of a summary table of the area to be monitored and the data of a user water meter of the area to be monitored are obtained:
and step S00, acquiring historical summary table data of the area to be monitored and historical user water meter data of the area to be monitored.
And step S01, obtaining historical leakage quantity according to the historical summary table data and the historical user water meter data.
Step S02, quotient of the historical leakage quantity and the historical summary table data is obtained, and the quotient value of the historical leakage quantity and the historical summary table data is obtained; and the quotient of the historical leakage quantity and the historical summary table data is the historical leakage rate.
And step S03, drawing a leakage rate curve based on the historical leakage rate.
And step S04, obtaining a preset leakage rate range according to the leakage rate curve.
Further, in the embodiment of the invention, after the preset leakage rate range is obtained according to the leakage rate curve, the preset leakage rate range can be gradually corrected based on the accumulation of the big data of the intelligent water meter, so that the accuracy of the preset leakage rate range is improved, and the judgment precision is further improved.
Further, in some embodiments, obtaining the historical leakage amount based on the historical summary table data and the historical customer water meter data comprises:
and step S011, summing the data of the water meters of the historical users to obtain the total data of the water meters of the historical users.
Step S012, subtracting the historical summary data from the total data of the water meters of the historical users to obtain the difference value between the historical summary data and the total data of the water meters of the historical users; and the difference value between the historical summary data and the historical user water meter total data is historical leakage.
Referring to fig. 2, fig. 2 is a schematic structural diagram of an alternative embodiment of each embodiment of a pipeline leakage inspection system based on intelligent water meter platform big data according to an embodiment of the present invention. The pipeline leakage troubleshooting system can be used for realizing the pipeline leakage troubleshooting method based on the intelligent water meter platform big data disclosed by the embodiment of the invention.
Specifically, as shown in fig. 2, the system for checking the pipe leakage based on the big data of the intelligent water meter platform may include: the intelligent water meter monitoring system comprises one or more general meters arranged in a region to be monitored, user water meters arranged in the region to be monitored and an intelligent water meter platform.
The general meter is used for collecting the total water consumption of an area to be monitored and outputting general meter data; the user water meter is used for collecting the water consumption of a user corresponding to the user water meter and outputting user level data; the intelligent water meter platform is respectively communicated with the general meter and the user water meter. In the embodiment of the invention, the summary table is associated with the user water meter.
This intelligence water gauge platform is used for: acquiring general table data of an area to be monitored and user water meter data of the area to be monitored; obtaining the current leakage quantity based on the data of the general table and the data of the water meter of the user; determining the current leakage rate according to the current leakage amount and the summary table data; and judging whether the area to be monitored is damaged or not according to the current leakage rate.
Further, in some embodiments, the method further comprises: and the terminal is communicated with the intelligent water meter platform to receive and display the alarm information output by the intelligent water meter platform.
As shown in figure 2, one or a plurality of general tables are installed in each area, the general table installed in each area is installed in the area, the general table installed in each area is also associated with the water meter of the user in the area, monitoring of the total water quantity of each area and the water quantity of each user in each area can be achieved through the association principle, leakage inspection is achieved based on the monitored water quantity data, the purpose of automatically identifying whether the pipeline is leaked or not based on the big data of the intelligent water meter platform is achieved, the purpose can be achieved only by installing a small number of general tables in each area, cost is low, maintenance is easy, maintenance personnel can be informed in real time, labor cost is further reduced, and waste of resources is reduced.
Of course, it can be understood that the invention can be applied not only to the inspection of water pipe leakage, but also to occasions such as gas leakage and heating leakage.
The above embodiments are merely illustrative of the technical ideas and features of the present invention, and are intended to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the scope of the present invention. All equivalent changes and modifications made within the scope of the claims of the present invention should be covered by the claims of the present invention.
Claims (13)
1. A pipeline leakage troubleshooting method based on intelligent water meter platform big data is characterized by comprising the following steps:
acquiring general table data of an area to be monitored and user water meter data of the area to be monitored;
obtaining the current leakage amount based on the general table data and the user water meter data;
determining the current leakage rate according to the current leakage amount and the summary table data;
and judging whether the area to be monitored is damaged or not according to the current leakage rate.
2. The intelligent water meter platform big data-based pipeline leakage troubleshooting method of claim 1, wherein said obtaining a current leakage quantity based on said summary table data and said customer water meter data comprises:
summing the user water meter data to obtain total data of the user water meter;
the summary data and the total data of the user water meter are subjected to difference operation, and a difference value between the summary data and the total data of the user water meter is obtained;
and the difference value between the summary table data and the total data of the user water meters is the current leakage quantity.
3. The intelligent water meter platform big data-based pipeline leakage troubleshooting method of claim 1, wherein said determining a current leakage rate based on said current leakage quantity and said summary table data comprises:
the current leakage amount and the summary table data are subjected to quotient operation, and a quotient value of the current leakage amount and the summary table data is obtained;
and the quotient of the current leakage quantity and the summary table data is the current leakage rate.
4. The intelligent water meter platform big data-based pipeline leakage troubleshooting method of claim 1, wherein said determining whether said area to be monitored is leaking according to said current leakage rate comprises:
comparing the current leakage rate with a preset leakage rate range;
judging whether the current leakage rate is larger than a preset leakage rate range or not;
if so, judging that the area to be monitored is leaked;
and if not, judging that the area to be monitored has no leakage.
5. The intelligent water meter platform big data-based pipeline leakage troubleshooting method of claim 4, further comprising:
if the leakage of the area to be monitored is judged, then:
collecting first general table data and first user water meter data of the area to be monitored at a first collection time interval;
judging whether leakage occurs or not according to the first general table data and the first user water meter data;
if the data is judged to be leakage, acquiring second to Nth general table data of the area to be monitored and second to Nth user water meter data of the area to be monitored in sequence from a second acquisition time interval to an Nth acquisition time interval; n is a natural number greater than or equal to 0;
judging whether leakage occurs according to the second to Nth master meter data and the second to Nth user water meter data;
if yes, outputting leakage alarm information.
6. The intelligent water meter platform big data-based pipeline leakage troubleshooting method of claim 5, wherein said determining whether leakage is based on said first summary table data comprises:
obtaining a first leakage rate according to the first general table data and the first user water meter data;
judging whether the first leakage rate is larger than the preset leakage rate range or not;
if yes, judging that the area to be monitored is leaked;
if not, judging that the difference to be monitored has no leakage.
7. The intelligent water meter platform big data-based pipeline leakage checking method according to claim 5, wherein the judging whether leakage occurs according to the second to nth summary table data and the second to nth user water meter data comprises:
obtaining a second leakage rate according to the second summary table data and the second user water meter data;
judging whether the second leakage rate is larger than the preset leakage rate range or not;
if yes, obtaining an Nth leakage rate according to the Nth general table data and the Nth user water meter data;
judging whether the Nth leakage rate is larger than the preset leakage rate range or not;
and if so, judging the leakage of the area to be monitored.
8. The intelligent water meter platform big data-based pipeline leakage troubleshooting method of claim 5, wherein said second collection time interval is less than said first collection time interval.
9. The intelligent water meter platform big data-based pipeline leakage troubleshooting method of claim 4, wherein said obtaining summary data of the area to be monitored and said user water meter data of the area to be monitored comprises:
acquiring historical summary table data of the area to be monitored and historical user water meter data of the area to be monitored;
obtaining historical leakage according to the historical summary table data and the historical user water meter data;
the historical leakage amount and the historical summary table data are subjected to quotient operation, and a quotient value of the historical leakage amount and the historical summary table data is obtained; the quotient of the historical leakage amount and the historical summary table data is the historical leakage rate;
drawing a leakage rate curve based on the historical leakage rate;
and obtaining the preset leakage rate range according to the leakage rate curve.
10. The intelligent water meter platform big data-based pipeline leakage troubleshooting method of claim 9, wherein said obtaining historical leakage from said historical summary table data and said historical customer water meter data comprises:
summing the data of the water meters of the historical users to obtain total data of the water meters of the historical users;
the historical summary data and the historical user water meter total data are subjected to difference, and a difference value between the historical summary data and the historical user water meter total data is obtained;
and the difference value between the historical summary table data and the historical user water meter total data is the historical leakage amount.
11. The utility model provides a pipeline leakage investigation system based on intelligence water gauge platform big data which characterized in that includes: the intelligent water meter monitoring system comprises one or more general meters arranged in an area to be monitored, user water meters in the area to be monitored and an intelligent water meter platform;
the general meter is used for collecting the total water consumption of the area to be monitored and outputting general meter data;
the user water meter is used for collecting the water consumption of a user corresponding to the user water meter and outputting user level data;
the intelligent water meter platform is respectively communicated with the general meter and the user water meter and is used for:
acquiring general table data of an area to be monitored and user water meter data of the area to be monitored;
obtaining the current leakage amount based on the general table data and the user water meter data;
determining the current leakage rate according to the current leakage amount and the summary table data;
and judging whether the area to be monitored is damaged or not according to the current leakage rate.
12. The intelligent water meter platform big data based pipeline leakage troubleshooting system of claim 11 further comprising:
and the terminal is communicated with the intelligent water meter platform to receive and display the alarm information output by the intelligent water meter platform.
13. The intelligent water meter platform big data based pipeline leak troubleshooting system of claim 11 wherein said summary table is associated with said customer water meter.
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