CN109932009B - Distributed tap water pipe network loss monitoring system and method - Google Patents
Distributed tap water pipe network loss monitoring system and method Download PDFInfo
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Abstract
The invention discloses a distributed tap water pipe network loss monitoring system which comprises a tap water pipe network monitoring system, wherein the tap water pipe network monitoring system is formed by a remote server, a regional water supply general table and user water meters in a region, intelligent terminals with narrow-band internet of things communication functions are arranged on the regional water supply general table and the user water meters, the intelligent terminals send flow data to the remote server at regular time, the remote server carries out model prediction and calculation analysis, identifies the region with abnormal pipe network flow and sends an alarm to a regional tap water manager. The intelligent terminal in the monitoring system can send water consumption data of each region and each user to the remote server in real time, and the server carries out modeling, prediction and analysis on the water consumption condition of each region according to the water consumption of the users in the region and the water supply quantity of the region, can quickly position the leakage region of the pipeline and give an alarm, saves a large amount of labor cost, and has a remarkable promoting effect on reducing water loss.
Description
Technical Field
The invention belongs to the technical field of a distributed tap water pipe network loss monitoring system, and particularly relates to a distributed tap water pipe network loss monitoring system and method.
Background
The problem of tap water loss has always been the most interesting issue for water supply enterprises. Even in urban areas of China, the leakage of a water supply network is quite serious, the average level is about 20% according to statistics, and the leakage rate of some cities is as high as more than 40%. The water loss of rural pipe networks is higher.
The existing pipe network leakage monitoring method is characterized in that a flowmeter is mounted at an inlet of each branch pipe network besides a main pipe at a water supply end, and the leakage condition is judged by comparing the difference value of the two. Due to the large number of flow meters, both investment and maintenance costs are high. Although each terminal user is provided with a tap water meter, the total water consumption in the same period of time cannot be accurately counted due to the fact that a manual meter reading mode is generally adopted at present, and therefore leakage calculation and diagnosis cannot be facilitated. In recent years, with the rapid development of the internet of things technology, wireless internet of things intelligent terminals are installed in flow meters and water meters, water consumption data can be sent in real time, heavy work such as meter reading is omitted, and meanwhile leakage monitoring of a tap water pipe network can be carried out accordingly.
Disclosure of Invention
The invention aims to provide a distributed tap water pipe network loss monitoring system and a method thereof, so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a distributed tap water pipe network loss monitoring system is established, and comprises a remote server, a regional water supply general table and a regional user water meter, wherein intelligent terminals with a narrowband Internet of things (NB-IoT) communication function are arranged on the regional water supply general table and the user water meter, and flow data are sent to the remote server at regular time; and the remote server performs model prediction and calculation analysis, identifies the area with abnormal pipe network flow and sends an alarm to a regional tap water manager.
A use method of a distributed tap water pipe network loss monitoring system comprises the following steps:
s1, the user water meter sends the current water meter accumulated flow to the remote server at regular time through the intelligent terminal;
s2, the remote server establishes a regional pipe network flow model, calculates the current total water accumulated flow according to the current water meter accumulated flow and the historical accumulated flow sent by each user in the region, and predicts the upper and lower limit thresholds of the current total water consumption in the region;
s3, the regional summary table sends the current total water supply flow to the database server at regular time through the intelligent terminal;
s4, the remote server compares the current total water supply flow of the area with the upper and lower limit thresholds of the total water consumption of the area, and if the total water supply flow exceeds the upper and lower limit thresholds of the total water consumption of the area, a water pipe leakage alarm is sent out;
s5, if the current total water supply flow is in the upper and lower threshold range of the regional total water consumption and the daily water supply increase exceeds the set threshold, the remote server sends out a water pipe leakage alarm;
and S6, if the current total water supply flow is in the upper and lower threshold ranges of the regional total water consumption and in the set time range, the fluctuation frequency of the water use accumulated flow curve exceeds the set threshold, and the remote server sends out a water pipe leakage alarm.
The method needs to model the flow of the regional pipe network, adopts autoregressive moving average modeling (ARIMA), and comprises the following steps:
a. taking the flow data of the area every day in the past year;
b. performing trend removing operation on the data;
c. detecting whether the data are stable, if so, turning to the step S5, otherwise, executing downwards;
d. performing difference operation on the data, and going to step S3;
e. respectively obtaining an autocorrelation coefficient and a partial autocorrelation coefficient from the obtained stationary time sequence, and recording a value of a horizontal axis of an autocorrelation coefficient curve passing through an upper confidence interval for the first time as p, wherein the value is a lag number of the data; the value of the horizontal axis of the partial autocorrelation coefficient curve passing through the upper confidence interval for the first time is marked as q, and is the lag number of the prediction error;
f. modeling is performed according to the values of p, q, and d, wherein d is the number of differences that the data is processed into a stationary time series, and the model is obtained as follows:
wherein the content of the first and second substances,
is a predicted value at time t, mu is a constant term, yt-iIs the true value at time t-i, et-iIs the prediction error at time t-i, phii、θiAre coefficients.
After the model is obtained, inputting the historical water consumption of the area for a certain time into the model for prediction to obtain the current water consumption of the area, and taking 130% of the predicted value as the upper limit threshold of the current total water consumption of the area; and taking 90% of the predicted value as a lower limit threshold of the current total water consumption of the area, and if the current daily water supply of the area exceeds the upper and lower limit thresholds of the total water consumption, sending out a water pipe leakage alarm.
If the current total water supply flow is in the upper and lower threshold ranges of the regional total water consumption, the increase of the daily water supply exceeds 10% of the yesterday water supply, and the remote server sends out a water pipe leakage alarm.
According to the water supply amount of the last 15 days, the frequency that the daily water supply amount is increased by 5 percent more than the previous day water supply amount exceeds 5 times, and a water pipe leakage alarm is sent out.
Has the advantages that: the invention constructs a distributed tap water pipe network loss monitoring system and a method, an intelligent terminal in the monitoring system can send water consumption data of each region and each user to a remote server in real time, and the server carries out modeling, prediction and analysis on the water consumption condition of each region according to the water consumption of the users in the region and the water supply quantity of the region, can quickly locate the leakage region of the pipeline and give an alarm, saves a large amount of labor cost, and has a remarkable promotion effect on reducing water loss.
Drawings
FIG. 1 is a schematic view of a tap water pipe network monitoring system according to the present invention;
FIG. 2 is a flow chart of a method for identifying water loss in a tap water network according to the present invention;
FIG. 3 is a flow chart of the flow modeling of the regional pipe network according to the present invention.
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 this case, taking the water consumption of 996 households in a certain area as an example, a tap water pipe network monitoring network is shown in fig. 1. Firstly, intelligent terminals with a narrowband Internet of things (NB-IoT) communication function are installed on a regional water supply total meter and a user water meter, water use data are uploaded to a remote server every day, the remote server carries out model prediction and calculation analysis, a region with abnormal pipe network flow is identified, and an alarm is sent to a regional tap water manager.
The implementation flow of this case is shown in fig. 2, and the specific implementation steps are as follows:
1) the server receives the accumulated water consumption of each household in the area until 7 months and 31 days in 2018, and the accumulated water consumption is subtracted from the historical accumulated flow to obtain the daily water consumption of each household in 7 months and 31 days, as shown in table 1. And (3) summing the daily water consumption of each household to obtain the daily water consumption of the region of 459.29m 3.
TABLE 1 daily water consumption of 7 months and 31 months for users in certain area（m3）
| House number | Current cumulative water consumption | Historical accumulated water consumption | Water consumption in the same day |
| 1-1 | 4265.30 | 4264.64 | 0.66 |
| 1-2 | 3110.65 | 3110.10 | 0.55 |
| 2-1 | 1755.41 | 1754.85 | 0.56 |
| 2-2 | 2566.73 | 2566.06 | 0.67 |
| 3-1 | 2009.63 | 2009.14 | 0.49 |
| 3-2 | 380.75 | 380.50 | 0.25 |
| 4-1 | 1200.34 | 1200.04 | 0.30 |
| 4-2 | 617.47 | 615.47 | 2.00 |
| 5-1 | 920.35 | 920.02 | 0.33 |
| 5-2 | 1200.52 | 1200.26 | 0.26 |
| 6-1 | 2086.91 | 2086.51 | 0.40 |
| 6-2 | 249.22 | 249.22 | 0.00 |
| …… | …… | …… | …… |
| 498-1 | 4513.67 | 4513.57 | 0.10 |
| 498-2 | 4723.99 | 4723.99 | 0.00 |
2) Reading data of the past year of the regional daily water consumption, and establishing a regional pipe network flow model by adopting a classical ARIMA time sequence analysis method, wherein the modeling process is shown in figure 3. After the detrending and the dereriodic operation, p =10 and q =3 are taken according to the autocorrelation coefficient and the partial autocorrelation coefficient of the data, and d =0 because the data are already stable without differential operation. According to the three parameters p, q and d and the stable water consumption data, the flow model of the regional pipe network can be obtained as follows:
and inputting the data of the latest 30 days of the regional daily water consumption into a regional pipe network flow model, and calculating a predicted value of the regional daily water consumption, wherein the predicted value is shown in a table 2.
TABLE 2 daily water supply and prediction (m) for regional pipe network3）
3) And after receiving the current total water supply of the region sent by the region summary table, the server subtracts the historical water supply of the region to obtain the water supply of 532.70m3 in 31 days in 7 months. The upper and lower threshold values of the daily water supply of the region are 602.85 and 417.36 respectively according to the predicted value of the daily water consumption of the region, and 532.70 is in the range, so that the water pipe leakage alarm is not sent out. On the contrary, if the daily water supply amount of the region is not in the reasonable interval range, the water pipe leakage alarm is sent out at the moment.
4) The water supply in the region of 7 months and 30 days was read as 547.10m3, and the water supply in the same day as 532.70m3 was subtracted therefrom to give an increase of-14.40 m 3. The threshold value is taken as 10 percent of the regional daily water supply of 7 months and 30 days, the water supply is 54.71m3, obviously, the amplification is smaller than the threshold value, and a water pipe leakage alarm is not sent out. If the water supply amount of the region today is 602.74m3, the water supply amount is within a reasonable interval range of the daily water supply amount, the water supply amount is subtracted from the daily water supply amount of the region in 30 days of 7 months, the amplification is 55.64m3 and is larger than the threshold value 54.71, and a water pipe leakage alarm is sent out.
5) The regional daily water supply and amplification data of 15 days in the past are read, and as shown in table 3, the frequency that the regional daily water supply amplification is greater than 5% of the previous daily water supply is calculated, and only 7 months and 17 days are carried out, and the frequency is less than the threshold value 5, and no water pipe leakage alarm is given.
TABLE 3 regional daily Water supply amplification (m 3)
| Date | Daily water supply of region | The water supply amount on the previous day is 5% | Amplification of |
| 7 month and 17 days | 555.21 | 26.42 | 26.81 |
| 7 month and 18 days | 571.74 | 27.76 | 16.53 |
| 7 month and 19 days | 554.90 | 28.59 | -16.84 |
| 7 month and 20 days | 558.67 | 27.75 | 3.77 |
| 7 month and 21 days | 550.93 | 27.93 | -7.74 |
| …… | …… | …… | …… |
| 7 month and 30 days | 547.23 | 27.55 | -3.70 |
| 7 month and 31 days | 532.70 | 27.36 | -14.53 |
As shown in Table 4, the number of times that the increase of the regional daily water supply amount is greater than 5% of the previous daily water supply amount is 6 times, and if the increase exceeds the threshold 5, the water pipe leakage alarm is issued.
TABLE 4 regional daily Water supply increase (m 3)
| Date | Daily water supply of region | The water supply amount on the previous day is 5% | Amplification of | Status of state |
| 7 month and 17 days | 555.21 | 26.42 | 26.81 | Abnormality (S) |
| 7 month and 18 days | 571.74 | 27.76 | 16.53 | |
| 7 month and 19 days | 554.90 | 28.59 | -16.84 | |
| 7 month and 20 days | 585.67 | 27.75 | 30.77 | Abnormality (S) |
| 7 month and 21 days | 550.93 | 29.28 | -34.74 | |
| 7 month and 22 days | 588.67 | 27.75 | 33.77 | Abnormality (S) |
| 7 month and 23 days | 550.93 | 29.43 | -37.74 | |
| 7 month and 24 days | 585.92 | 27.55 | 34.99 | Abnormality (S) |
| 7 month and 25 days | 558.64 | 29.30 | -27.28 | |
| 7 month and 26 days | 589.61 | 27.93 | 30.97 | Abnormality (S) |
| 7 month and 27 days | 559.40 | 29.48 | -30.21 | |
| 7 month and 28 days | 589.68 | 27.97 | 30.28 | Abnormality (S) |
| 7 month and 29 days | 551.00 | 29.48 | -38.68 | |
| 7 month and 30 days | 547.23 | 27.55 | -3.77 | |
| 7 month and 31 days | 532.70 | 27.36 | -14.53 |
The invention discloses a system and a method for monitoring the loss of a distributed tap water pipe network.A tap water pipe network monitoring system consisting of a remote server, a regional water supply general table and a regional user water meter is established, intelligent terminals with a narrow-band Internet of things communication function are arranged on the regional water supply general table and the user water meter, and flow data are sent to the remote server at regular time; and the remote server performs model prediction and calculation analysis, identifies the area with abnormal pipe network flow and sends an alarm to a regional tap water manager. The invention can quickly find out the leakage area of the pipeline and give an alarm, saves a large amount of labor cost and has obvious promotion effect on reducing water loss.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments or portions thereof without departing from the spirit and scope of the invention.
Claims (4)
1. A use method of a distributed tap water pipe network loss monitoring system comprises the following steps: a tap water pipe network monitoring system consisting of a remote server, a regional water supply general table and user water meters in a region is established, intelligent terminals with a narrow-band Internet of things communication function are arranged on the regional water supply general table and the user water meters, the intelligent terminals send flow data to the remote server at regular time, the remote server carries out model prediction and calculation analysis, identifies the region with abnormal pipe network flow and sends an alarm to a regional tap water manager;
the method specifically comprises the following steps:
s1, the user water meter sends the current water meter accumulated flow to the remote server at regular time through the intelligent terminal;
s2, the remote server establishes a regional pipe network flow model, calculates the current total water accumulated flow according to the current water meter accumulated flow and the historical accumulated flow sent by each user in the region, and predicts the upper and lower limit thresholds of the current total water consumption in the region;
s3, the regional summary table sends the current total water supply flow to the database server at regular time through the intelligent terminal;
s4, the remote server compares the current total water supply flow of the area with the upper and lower limit thresholds of the total water consumption of the area, and if the total water supply flow exceeds the upper and lower limit thresholds of the total water consumption of the area, a water pipe leakage alarm is sent out;
s5, if the current total water supply flow is in the upper and lower threshold range of the regional total water consumption and the daily water supply increase exceeds the set threshold, the remote server sends out a water pipe leakage alarm;
s6, if the current total water supply flow is in the upper and lower threshold ranges of the regional total water consumption and in the set time range, the fluctuation frequency of the water use accumulated flow curve exceeds the set threshold, the remote server sends out a water pipe leakage alarm;
the method adopts autoregressive integral sliding modeling for regional pipe network flow and comprises the following steps:
a. taking the flow data of the area every day in the past year;
b. performing trend removing operation on the data;
c. detecting whether the data are stable, if so, turning to the step S5, otherwise, executing downwards;
d. performing difference operation on the data, and going to step S3;
e. respectively obtaining an autocorrelation coefficient and a partial autocorrelation coefficient from the obtained stationary time sequence, and recording a value of a horizontal axis of an autocorrelation coefficient curve passing through an upper confidence interval for the first time as p, wherein the value is a lag number of the data; the value of the horizontal axis of the partial autocorrelation coefficient curve passing through the upper confidence interval for the first time is marked as q, and is the lag number of the prediction error;
f. modeling is performed according to the values of p, q, and d, wherein d is the number of differences that the data is processed into a stationary time series, and the model is obtained as follows:
wherein the content of the first and second substances,
is a predicted value at time t, mu is a constant term, yt-iIs the true value at time t-i, et-iIs the prediction error at time t-i, phii、θiIs a coefficient of yt-iWhere "i" denotes: any real number in 1-p, et-iWhere "i" denotes: 1-q.
2. The use method of the distributed tap water pipe network loss monitoring system according to claim 1, characterized in that: inputting the historical water consumption of the region for a certain time into a model and predicting to obtain the current water consumption of the region, wherein 130% of the predicted value is taken as the upper limit threshold of the current total water consumption of the region; and taking 90% of the predicted value as a lower threshold value of the current total water consumption of the area.
3. The use method of the distributed tap water pipe network loss monitoring system according to claim 2, characterized in that: the 10% of the yesterday water supply was taken as the threshold for the water supply increase on the day.
4. The use method of the distributed tap water pipe network loss monitoring system according to claim 3, characterized in that: according to the water supply amount of the last 15 days, the frequency that the daily water supply amount is increased by 5 percent more than the previous day water supply amount exceeds 5 times, and a water pipe leakage alarm is sent out.
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