DMA cell stock leakage judgment method based on analysis and data fitting method

Abstract

The invention discloses a DMA (Direct Memory Access) cell stock leakage judgment method based on an analysis and data fitting method. The method comprises the following steps of: searching a cell drawing to determine a DMA cell header position; high-frequency flow equipment is installed; continuously measuring and recording the flow data of the cell in unit time, analyzing whether the flow data of the cell has a value of 0 or not, if not, taking the minimum value as a stock leakage value, and judging that the cell has stock; if the value is 0, the community does not leak, the minimum flow at night of the community is legal water consumption at night, and the minimum flow at night and the actual number of residents are recorded; repeating the above steps to obtain numerical values of N cells, and fitting the night minimum traffic of the N cells with the actual check-in household number data to obtain a fitting equation of the household number and the night minimum traffic; the fitting equation is applied to other DMA cells with low-frequency flowmeters, the actual night minimum flow is compared with the night minimum flow of the fitting equation value, and if the actual night minimum flow is higher than a set threshold value, it is judged that stock leakage exists.

Description

Technical Field

[0001] The invention relates to a DMA cell stock leakage determination technology, in particular to a DMA cell stock leakage determination method based on analysis and data fitting methods. Background Art

[0002] At present, the MNF nighttime minimum flow method is still the main basis for judging whether there is physical leakage in the DMA cell, but MNF includes physical leakage and user nighttime water consumption (such as Figure 1 As shown in Figure 2, how to separate the user's nighttime water consumption from the MNF is a problem worth studying. In the past, the nighttime water consumption of this user was mainly estimated based on the nighttime water quota. [Li Lan, Wu Shan, Kou Xiaoxia, et al. Research progress on the minimum nighttime flow rate based on independent metering areas [J]. Water Supply and Drainage, 2018 (6): 135-141.] The UK determined that the nighttime water consumption of residential users is 1.8-2.5L / (household·h), Canada is 3L / (household·h), and Australia is 1.08L / (household·h); [Liu Xiaofei, Liu Su, He Yuanchun, et al. Research on the legal nighttime water consumption of residents in Guangzhou communities [J]. China Water Supply and Drainage, 2017 (9): 45-48.] In China, the Shenzhen Water Company is 3L / (household·h), the Guangzhou Water Company is 3.27L / (household·h), and the Nanjing Water Company is 1L / (household·h). The estimation methods in the above literature are not accurate enough.

[0003] In addition, based on the relationship between the nighttime water consumption of DMA community users and the actual number of households in the DMA community measured above, eight DMA communities that meet the above conditions were continuously collected, and then the nighttime water consumption of users and the number of users were fitted to establish a mathematical model to obtain a mathematical relationship, which was then applied to other DMA communities to determine whether the MNF values ​​of other communities are reasonable and whether there is a stock loss in this community. In the past, whether the MNF value was reasonable was based on the estimation of the user's nighttime water quota, and there was no actual measured value. Summary of the invention

[0004] In view of the problems existing in the prior art, the present invention provides a method for accurately determining the stock leakage of a DMA cell.

[0005] The purpose of the present invention is achieved through the following technical solutions.

[0006] A method for determining the stock leakage of a DMA cell based on analysis and data fitting method, comprising the following steps:

[0007] 1) Find the cell map to determine the location of the DMA cell master;

[0008] 2) Install high-frequency flow equipment;

[0009] 3) Continuously measure and record the flow data of the community within a unit time, and analyze whether there is a 0 value in the flow data of the community. If not, take the minimum value as the stock leakage value to determine that the community has stock; if there is a 0 value, it means that the community does not leak, and the minimum nighttime flow of the community is the legal nighttime water consumption. Record the minimum nighttime flow and the actual number of households, and the community is recorded as D1;

[0010] 4) Repeat steps 1) to 3) to obtain the values ​​of N communities in total, fit the nighttime minimum flow and the actual number of households in the N communities, and obtain the fitting equation of the number of households and the nighttime minimum flow;

[0011] 5) Apply the fitting equation to other low-frequency flow meter DMA cells, compare the actual nighttime minimum flow with the nighttime minimum flow of the fitting equation value, and if it is higher than the set threshold, it is determined that there is stock leakage.

[0012] The high-frequency flow equipment in step 2) has a collection frequency of no less than once per minute.

[0013] The continuous measurement and recording unit time in step 3) is 1 day.

[0014] In the step 4), N is greater than or equal to 8.

[0015] In step 5), the threshold is set to be no higher than 30%.

[0016] The fitting equation of the number of households and the minimum flow at night through excel software is: y = 0.0029x-0.0613; R 2 =0.8653, where x is the number of households, y is the minimum flow at night, R 2 is the correlation coefficient.

[0017] Compared with the prior art, the advantages of the present invention are: the present invention adopts a high-frequency ultrasonic flow meter and uses the analytical method in mathematical statistics to measure the user's nighttime water consumption. According to the knowledge in mathematical statistics, it can be known that at a certain moment in the night, there is always a situation where no one uses water. This is a pure physical loss. If the instantaneous value is 0, it means that there is no physical loss in the DMA cell, and MNF is the user's nighttime water consumption value; if the instantaneous value is not 0, then the value is the physical loss (stock loss) of the DMA cell. Through the fitting equation of N cell data (the instantaneous value is 0), it is applied to other low-frequency flow meter DMA cells, and the actual nighttime minimum flow is compared with the nighttime minimum flow of the fitting equation value, it can be accurately judged whether the DMA cell has stock leakage. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Schematic diagram of MNF physical leakage and users' nighttime water consumption.

[0019] Figure 2 It is a flow chart of the present invention.

[0020] Figure 3 The present invention provides a mathematical model for fitting the nighttime water consumption of users and the actual number of users. DETAILED DESCRIPTION

[0021] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0022] like Figure 2 As shown, a method for determining the stock leakage of a DMA cell based on analysis and data fitting method comprises the following steps:

[0023] 1) Find the cell map to determine the location of the DMA cell master;

[0024] 2) Install high-frequency flow equipment;

[0025] 3) Continuously measure and record the flow data of the community within a unit time, and analyze whether there is a 0 value in the flow data of the community. If not, take the minimum value as the stock leakage value to determine that the community has stock; if there is a 0 value, it means that the community does not leak, and the minimum nighttime flow of the community is the legal nighttime water consumption. Record the minimum nighttime flow and the actual number of households, and the community is recorded as D1;

[0026] 4) Repeat steps 1) to 3) to obtain the values ​​of N communities in total, fit the nighttime minimum flow and the actual number of households in the N communities, and obtain the fitting equation of the number of households and the nighttime minimum flow;

[0027] 5) Apply the fitting equation to other low-frequency flow meter DMA cells, compare the actual nighttime minimum flow with the nighttime minimum flow of the fitting equation value, and if it is higher than the set threshold, it is determined that there is stock leakage.

[0028] The high-frequency flow equipment in step 2) has a collection frequency of no less than once per minute.

[0029] The continuous measurement and recording unit time in step 3) is 1 day.

[0030] In the step 4), N is greater than or equal to 8.

[0031] In step 5), the threshold is set to be no higher than 30%.

[0032] The fitting equation of the number of households and the minimum flow at night through Excel software is: y = 0.0029x-0.0613, R 2 =0.8653, where x is the number of households, y is the minimum flow at night, R 2 is the correlation coefficient.

[0033] Example

[0034] Find the community drawings to determine the location of the DMA community main pipe, and install high-frequency flow equipment (1 data per minute or higher). Continuously measure and record the community flow data for 1 day, and analyze whether the data has a 0 value. If not, take the minimum value as the stock leakage value to determine whether the community has stock leakage; if there is a 0 value, it means that the community has no leakage. The minimum nighttime flow of the community is the legal nighttime water consumption. Record the minimum nighttime flow (tons / hour) and the actual number of households. The community is recorded as D1;

[0035] Use an ultrasonic flow meter to collect 8 DMA cells with instantaneous values ​​of 0, as follows:

[0036] Community A

[0037] time Flow rate (tons / hour) 2024 / 5 / 11 3:42 1.71093 2024 / 5 / 11 3:43 2.16073 2024 / 5 / 11 3:44 2.76614 2024 / 5 / 11 3:45 2.13169 2024 / 5 / 11 3:46 1.88064 2024 / 5 / 11 3:47 2.21312 2024 / 5 / 11 3:48 3.56475 2024 / 5 / 11 3:49 2.32733 2024 / 5 / 11 3:50 0 2024 / 5 / 11 3:51 2.21085

[0038] B Community

[0039] time Flow rate (tons / hour) 2024 / 5 / 10 3:02 1.14729 2024 / 5 / 10 3:03 0.860328 2024 / 5 / 10 3:04 0.889769 2024 / 5 / 10 3:05 0.771733 2024 / 5 / 10 3:06 0 2024 / 5 / 10 3:07 0 2024 / 5 / 10 3:08 1.86529 2024 / 5 / 10 3:09 1.25102 2024 / 5 / 10 3:10 0.761538 2024 / 5 / 10 3:11 1.07584

[0040] C Community

[0041]

[0042]

[0043] D Community

[0044] time Flow rate (tons / hour) 2024 / 4 / 24 3:15 0.425085 2024 / 4 / 24 3:16 0.406654 2024 / 4 / 24 3:17 0 2024 / 4 / 24 3:18 0 2024 / 4 / 24 3:19 0 2024 / 4 / 24 3:20 0 2024 / 4 / 24 3:21 0 2024 / 4 / 24 3:22 0.765611 2024 / 4 / 24 3:23 0 2024 / 4 / 24 3:24 0

[0045] E Community

[0046] time Flow rate (tons / hour) 2024 / 5 / 27 3:20 0.956032 2024 / 5 / 27 3:21 0 2024 / 5 / 27 3:22 1.66382 2024 / 5 / 27 3:23 0.900127 2024 / 5 / 27 3:24 1.33181 2024 / 5 / 27 3:25 0.937829 2024 / 5 / 27 3:26 1.2054 2024 / 5 / 27 3:27 1.43698 2024 / 5 / 27 3:28 0.908914 2024 / 5 / 27 3:29 0

[0047] F Community

[0048]

[0049]

[0050] G Community

[0051] time Flow rate (tons / hour) 2024 / 5 / 7 4:00 5.51248 2024 / 5 / 7 4:01 3.94679 2024 / 5 / 7 4:02 4.41441 2024 / 5 / 7 4:03 2.15545 2024 / 5 / 7 4:04 0 2024 / 5 / 7 4:05 2.81807 2024 / 5 / 7 4:06 3.81985 2024 / 5 / 7 4:07 2.61929 2024 / 5 / 7 4:08 4.08109 2024 / 5 / 7 4:09 3.24656

[0052] H Community

[0053] time Flow rate (tons / hour) 2024 / 5 / 23 1:00 1.95945 2024 / 5 / 23 1:01 1.22083 2024 / 5 / 23 1:02 0 2024 / 5 / 23 1:03 0 2024 / 5 / 23 1:04 0 2024 / 5 / 23 1:05 0 2024 / 5 / 23 1:06 1.06382 2024 / 5 / 23 1:07 2.30135 2024 / 5 / 23 1:08 2.93102 2024 / 5 / 23 1:09 3.20428

[0054] Count the minimum nighttime traffic MNF and the actual number of households in these 8 DMA communities

[0055] Community MNF (tons / hour) Number of households Community A 2.59 629 B Community 0.82 136 C Community 2.50 1018 D Community 0.13 212 E Community 0.87 435 F Community 0.07 178 G Community 3.51 1300 H Community 2.94 885

[0056] The nighttime minimum flow rate of the eight communities and the actual number of households were fitted to obtain the fitting equation of the number of households and the nighttime minimum flow rate through excel software. The fitting equation of the number of households and the nighttime minimum flow rate is: y = 0.0029x-0.0613, R 2 =0.8653, where x is the number of households, y is the minimum flow at night, R 2 is the correlation coefficient. Figure 3 It can be seen that there is a good correlation between the user's nighttime water consumption and the number of users. The fitting equation is applied to other low-frequency flow meter DMA cells, and the actual nighttime minimum flow is compared with the nighttime minimum flow of the fitting equation value. If it is higher than 30%, it is determined that there is stock leakage.

[0057] The frequency of data collection in the I cell is low, once every 15 minutes, and the minimum flow rate at night is 5.2 (tons / hour). The actual number of households is 1068. According to the fitting equation y=0.0029x-0.0613, the reasonable minimum flow rate at night should be 3.0359. The current minimum flow rate at night is 71% higher than the reasonable minimum flow rate at night, which is greater than the threshold of 30%. Therefore, it is determined that there is a stock loss in the DMA cell. After arranging for leak detection and repair, the minimum flow rate at night in the I cell is 2.6 (tons / hour), which is 30% lower than the threshold.

[0058] time Flow rate (tons / hour) 2024-07-1902:00 5.2 2024-07-1902:15 5.2 2024-07-1902:30 5.2 2024-07-1902:45 5.2 2024-07-1903:00 5.2 2024-07-1903:15 5.2 2024-07-1903：30 4.8 2024-07-1903:45 6 2024-07-1904:00 6 2024-07-1904:15 5.2 2024-07-1904:30 6.4 2024-07-1904:45 6.8 2024-07-1905:00 10

[0059] time Flow rate (tons / hour) 2024-08-0602：00 3.2 2024-08-0602:15 2.4 2024-08-0602:30 2 2024-08-0602:45 3.2 2024-08-0603:00 2.8 2024-08-0603:15 3.2 2024-08-0603：30 3.2 2024-08-0603:45 2.8 2024-08-0604:00 3.6 2024-08-0604:15 4 2024-08-0604:30 3.2 2024-08-0604:45 5.2 2024-08-0605:00 6 .

Claims

1. A method for determining the leakage of DMA cell inventory based on analysis and data fitting method, characterized by the following steps: include: 1) Find the cell map to determine the location of the DMA cell master; 2) Install high-frequency flow equipment; 3) Continuously measure and record the flow data of the community within a unit time, and analyze whether there is a 0 value in the flow data of the community. If not, take the minimum value as the stock leakage value to determine that the community has stock; if there is a 0 value, it means that the community does not leak, and the minimum nighttime flow of the community is the legal nighttime water consumption. Record the minimum nighttime flow and the actual number of households, and the community is recorded as D1; 4) Repeat steps 1) to 3) to obtain the values ​​of N communities in total, fit the nighttime minimum flow and the actual number of households in the N communities, and obtain the fitting equation of the number of households and the nighttime minimum flow; 5) Apply the fitting equation to other low-frequency flow meter DMA cells, compare the actual nighttime minimum flow with the nighttime minimum flow of the fitting equation value, and if it is higher than the set threshold, it is determined that there is stock leakage.

2. A DMA cell inventory leakage determination method based on analysis and data fitting method according to claim 1, characterized in that The high-frequency flow equipment in step 2) has a collection frequency of no less than once per minute.

3. A DMA cell inventory leakage determination method based on analysis and data fitting method according to claim 1, characterized in that The continuous measurement and recording unit time in step 3) is 1 day.

4. A DMA cell inventory leakage determination method based on analysis and data fitting method according to claim 1, characterized in that In the step 4), N is greater than or equal to 8.

5. A DMA cell inventory leakage determination method based on analysis and data fitting method according to claim 1, characterized in that In step 5), the threshold is set to be no higher than 30%.

6. A DMA cell inventory leakage determination method based on analysis and data fitting method according to claim 1, characterized in that The fitting equation of the number of households and the minimum flow rate at night in step 4) is: y=0.0029x-0.0613, R 2 =0.8653, where x is the number of households, y is the minimum flow at night, R 2 is the correlation coefficient.

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