Urban pipe network dynamic pressure monitoring method based on secondary water supply

Abstract

The invention provides an urban pipe network dynamic pressure monitoring method based on secondary water supply, which comprises the following steps of: monitoring the water inlet pressure of secondary water supply equipment in real time to form a pressure data table; carrying out binding association on the pressure data table and a GIS map; all the pressure blocks are modeled by using PYthon, and pressure points are converted into mutually associated thermal blocks; and a change point monitoring algorithm is established for dynamic calculation, and pressure mutation caused by water cut-off, pipe explosion and / or water leakage is confirmed, so that automatic real-time monitoring of the pressure abnormity of the pipe network is realized. According to the method, the problems of real-time monitoring and automatic judgment of the municipal pipe network pressure are solved, further refined regulation and control can be carried out on the market pipe network pressure on the basis, and the method plays a positive role in improving the operation stability of the pipe network and prolonging the service life of the pipe network and the valve. The real-time operation level of the pipe network is effectively presented, the dependence of pipe network management on manpower is reduced, and urban intelligent operation and management are optimized.

Description

Technical Field

[0001] The invention relates to the technical field of a method for monitoring the dynamic pressure of a city pipe network based on secondary water supply, and in particular to a method for monitoring the dynamic pressure of a city pipe network based on secondary water supply. Background Art

[0002] In urban tap water supply, pipe network pressure is related to the water demand of thousands of households and the safe operation of water company pipe networks. Real-time dynamic monitoring of pipe network pressure, including monitoring and analysis of water outages and pipe bursts, combined with pipe network zoning flow, can further monitor water supply pipe network leakage and quickly locate the area, thereby guiding pipe network maintenance staff to quickly find pipe bursts or leakage points, greatly improving troubleshooting efficiency and fully ensuring the normal supply of tap water in urban areas.

[0003] The current difficulties in real-time monitoring of urban pressure mainly lie in the sampling frequency and the installation and deployment of equipment. Generally, the pressure collection of the main pipeline network is mainly based on low-power pressure transmitters. Battery power cannot provide real-time data transmission, so it is impossible to locate the area of ​​pipe burst or leakage through sudden pressure changes. In addition, the working conditions of the pipeline network have great restrictions on the power supply of solar energy or municipal electricity. It is often difficult to deploy large areas at the nodes of the main pipeline network, and the deployment cost is very high. Summary of the invention

[0004] In view of this, the problem to be solved by the present invention is to provide a method for dynamic pressure monitoring of urban pipe networks based on secondary water supply, so as to realize real-time monitoring of regional pressure of water supply pipe networks and comprehensive data analysis of complex situations such as pipe burst and leakage.

[0005] The present invention solves the above technical problems through the following technical means: The present invention provides a method for monitoring the dynamic pressure of an urban pipe network based on secondary water supply, comprising the following steps:

[0006] Monitor the water inlet pressure of the secondary water supply equipment in real time, and form a pressure data table with the obtained water inlet pressure of the secondary water supply equipment to express the pressure distribution level of the water supply network node;

[0007] Obtain GIS maps through the front-end data platform, bind the pressure data table to the GIS map, and present it in the form of a pipe network pressure map to reflect the real-time block pressure in various areas of the urban area;

[0008] Use PYthon to model all pressure blocks, convert pressure points into thermal blocks that are related to each other, and form a dynamic pressure block thermal map through a thermal map based on the data platform;

[0009] Combined with the positioning of thermal map data, a change point monitoring algorithm is established for dynamic calculation and to confirm the sudden pressure change caused by water outage, pipe burst and / or water leakage, so as to realize automatic real-time monitoring of abnormal pressure in the pipeline network.

[0010] Furthermore, the real-time monitoring of the water inlet pressure of the secondary water supply equipment is to perform real-time sampling of the secondary water supply equipment in each community in the urban area, and the sampling is performed second by second and transmitted remotely to the data server, and then the formed pressure data table is stored.

[0011] Furthermore, the real-time monitoring of the water inlet pressure of the secondary water supply equipment also includes measuring the actual height of the secondary water supply pump room on site and correcting the average elevation obtained by combining the comprehensive elevation of the reference plane to obtain a corrected pressure data table for reflecting the actual pressure distribution of the pipe network.

[0012] Furthermore, the use of PYthon to model all pressure blocks also includes adding pressure transmitters and DTU gateways to the inlet and outlet water of the secondary water supply equipment in each community, integrating the DTU with networking function into the secondary water supply equipment distribution cabinet, reading the PLC point table through the Modbus communication protocol, pushing the inlet and outlet water pressures of the secondary water supply equipment to the data server in real time in the form of MQTT, and organizing them into pressure data forms with Python and storing them in the database.

[0013] Furthermore, the obtaining of GIS map through the front-end data platform also includes using Vue.js to bind the water inlet pressure of each community's secondary supply equipment in the corrected pressure data form to the data platform, and importing GIS pipe network data, thereby forming a pipe network GIS map with real-time pressure data, which is used to reflect the real-time pressure of each water supply area in the urban area.

[0014] Furthermore, the establishment of a change point monitoring algorithm for dynamic calculation also includes establishing a change monitoring algorithm for each pressure data point: preprocessing real-time data, removing abnormal jittering pressure values, and storing data within a normal threshold range to ensure the stability of the calculation.

[0015] Furthermore, the preprocessing of the real-time data also includes calculating the mean of the preprocessed and cleaned data, extracting n-1 pressure values ​​from the data table each time and adding the most recent sampling value to calculate the mean.

[0016] Furthermore, through the heat map method of the GIS data platform, the data of the two adjacent points are correlated and compared with the data of the abnormal point to determine whether it is a single point leak or a regional pipe burst.

[0017] Furthermore, using the data curve chart method of the Vue framework, the historical data of the determined abnormal points are captured onto the curve chart, and the correlation analysis of single-point or multi-point data abnormal changes is performed in the form of historical curves.

[0018] It can be seen from the above technical scheme that the beneficial effects of the present invention are as follows: the present invention provides a method for monitoring the dynamic pressure of a city pipe network based on secondary water supply, comprising the following steps: real-time monitoring of the water inlet pressure of the secondary water supply equipment, and forming a pressure data table with the water inlet pressure of the secondary water supply equipment to express the pressure distribution level of the water supply pipe network node; obtaining a GIS map through a front-end data platform, and binding and associating the pressure data table with the GIS map, and presenting it in the form of a pipe network pressure map to reflect the real-time block pressure of each area in the urban area; using PYthon to model all pressure blocks, converting pressure points into thermal blocks associated with each other, and forming a dynamic pressure block thermal map based on the data platform in the form of a thermal map; combining thermal map data positioning, establishing a change point monitoring algorithm for dynamic calculation, and confirming the pressure mutation caused by water outage, pipe burst and / or water leakage, so as to realize automatic real-time monitoring of abnormal pipe network pressure. The present invention solves the problem of real-time monitoring and automatic determination of municipal pipe network pressure, and on this basis, further refined regulation and control of market pipe network pressure can be carried out, which has a positive effect on improving the stability of pipe network operation and extending the service life of pipe network and valves. At the same time, based on the Internet of Things, GIS and information system technologies, the present invention effectively presents the real-time operation level of the pipeline network, reduces the dependence of pipeline network management on manual labor, and optimizes the intelligent operation and management of the city. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for the specific embodiments or the description of the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn according to the actual scale.

[0020] Figure 1 A schematic diagram of the steps of a method for monitoring dynamic pressure of an urban pipe network based on secondary water supply provided by the present invention;

[0021] Figure 2 A pressure monitoring thermodynamic origin diagram of a method for monitoring dynamic pressure of a city pipe network based on secondary water supply provided by the present invention;

[0022] Figure 3 A thermal origin diagram after binding pressure data of a method for monitoring dynamic pressure of a city pipe network based on secondary water supply provided by the present invention;

[0023] Figure 4 A thermal origin diagram of a method for monitoring the dynamic pressure of a city pipe network based on secondary water supply provided by the present invention after importing GIS pipe network data;

[0024] Figure 5A curve chart of historical data of inlet and outlet water pressures of a method for dynamic pressure monitoring of an urban pipe network based on secondary water supply provided by the present invention. DETAILED DESCRIPTION

[0025] The following embodiments of the technical solution of the present invention are described in detail in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and are therefore only used as examples, and cannot be used to limit the protection scope of the present invention.

[0026] See also Figures 1 to 5 The present invention provides a method for monitoring the dynamic pressure of an urban pipe network based on secondary water supply, comprising the following steps:

[0027] Real-time monitoring of the water inlet pressure of the secondary water supply equipment, and forming a pressure data table with the obtained water inlet pressure of the secondary water supply equipment to express the pressure distribution level of the water supply network node; the real-time monitoring of the water inlet pressure of the secondary water supply equipment is to sample the secondary water supply equipment of each community in the urban area in real time, and sample it second by second and transmit it to the data server, and then store the formed pressure data table;

[0028] Specifically, the water inlet pressure of each secondary water supply device in the urban area is sampled second by second and transmitted to the data server, and a data table expressing the pressure distribution level of the water supply network nodes is automatically formed for the storage and presentation of pressure data.

[0029] The actual height of the secondary water supply pump room is measured on site and corrected by combining the average height obtained from the comprehensive elevation of the reference plane to obtain a corrected pressure data table to reflect the actual pressure distribution of the pipe network;

[0030] Specifically, due to the inconsistency of underground floors where the secondary water supply equipment is installed in each community, there is a height difference in the pressure data of the monitoring point. In order to eliminate this objective difference and obtain the real data of the actual terrain and the inlet of the secondary water supply equipment, it is necessary to make a data correction for the comprehensive plane of all secondary water supply pump rooms and the community where they are located. By measuring the actual elevation of the secondary water supply pump room on the spot, the obtained value is subtracted from the comprehensive elevation of the community's base plane to obtain the average elevation of the community's pipe network, which is used to eliminate the height difference of the pump room on the underground floor, avoid data distortion caused by the location of the secondary water supply pump room, and ensure that the pressure presented by the data platform is always on the same plane, which is of guiding significance for determining the distribution and anomalies of pressure data.

[0031] The GIS map is obtained through the front-end data platform, and the pressure data table is bound to the GIS map, and presented in the form of a pipe network pressure map to reflect the real-time block pressure in various areas of the urban area; Vue.js is used to bind the water inlet pressure of each community's secondary supply equipment in the corrected pressure data form to the data platform, and the GIS pipe network data is imported to form a pipe network GIS map with real-time pressure data, which is used to reflect the real-time pressure of each water supply area in the urban area.

[0032] Use PYthon to model all pressure blocks, convert pressure points into thermal blocks that are related to each other, and form dynamic pressure block thermal maps based on the data platform through thermal maps; add pressure transmitters and DTU gateways to the inlet and outlet of secondary water supply equipment in each community, integrate the DTU with networking function into the power distribution cabinet of the secondary water supply equipment, read the PLC point table through the Modbus communication protocol, and push the inlet and outlet water pressure of the secondary water supply equipment to the data server in real time in the form of MQTT, and use Python to organize it into a pressure data form and store it in the database. Combined with the spatial distribution of the community pipe network, the pressure points are converted into water supply blocks, and with the help of the data platform, different pressure levels are displayed in color grading through thermal maps, which more intuitively presents the regional distribution of urban pipe network pressure.

[0033] Combined with the positioning of thermal map data, a change point monitoring algorithm is established for dynamic calculation, and the pressure mutation caused by water outage, pipe burst and / or water leakage is confirmed, so as to realize the automatic real-time monitoring of abnormal pressure in the pipeline network; Automatic monitoring of pipeline abnormality: Combined with the positioning of thermal map data, a change point monitoring algorithm is established to dynamically calculate and confirm the pressure mutation caused by water outage, pipe burst, water leakage, etc., so as to realize the automatic real-time monitoring of abnormal pressure in the pipeline network; In order to automatically monitor and analyze the situation of pipe burst and leakage in real time, it is necessary to establish a change monitoring algorithm for each pressure data point. Pre-process the real-time data, remove the abnormal jitter pressure value in time, and only store the data within the normal threshold range to ensure the stability of the calculation.

[0034] Specifically, the mean value is calculated for the preprocessed and cleaned data. Each time, n-1 pressure values ​​are extracted from the data table and added to the most recent sampling value to calculate the mean value:

[0035]

[0036] Calculate the deviation. For each data point xi, calculate its deviation d from the mean μ i :

[0037] d i =x i -μ.

[0038] Calculate the sum of squared deviations S:

[0039]

[0040] To calculate the variance, the sum of the squares of the deviations S divided by the total number of data points n gives the variance V:

[0041]

[0042] Then find the standard deviation, take the square root of the variance V, and get the standard deviation σ:

[0043]

[0044] Calculate the pressure change threshold k:

[0045]

[0046] Where k is the threshold used to determine whether the data is outside the normal fluctuation range. σ2 is the square of the standard deviation of the process, which represents the variability of the data. α is the significance level, which is a probability value used to determine the risk of false positives (i.e., incorrectly identifying a change point). The lower the significance level, the lower the risk of false positives, but at the same time it may increase the risk of false negatives (i.e., failing to identify a true change point);

[0047] Calculate the cumulative sum S n :

[0048] S n =∑i=1n(X i -μ)

[0049] And update the cumulative sum based on the deviation:

[0050] If S n-1 +d n >k, then S n =k; if S n-1 +d n <-k, then S n = -k; otherwise, S n =S n-1 +d n ;

[0051] At the same time, the calculated value is compared with the threshold k at a set interval. When Sn exceeds the threshold k or is lower than -k, it means that the data monitoring value of the pressure point has changed significantly.

[0052] Through the heat map method of the GIS data platform, the data of two adjacent points are correlated and compared with the data of the abnormal point to determine whether it is a single point leak or a regional pipe burst. Often, in the case of regional or large-scale pipe bursts, multi-point data will show a significant positive correlation and be presented in real time through the color level of the heat map. Using the data curve chart method of the vue framework, the historical data of the determined abnormal point is captured on the curve chart, and the correlation analysis of the abnormal changes of single or multiple points of data is performed in the form of historical curves, so as to further analyze the causes and provide a basis for response decisions. On the GIS pipe network map, the real-time data that has been corrected when the data is needed is bound to the data. At the same time, the single-point pressure of the pipe network is generalized in blocks when the data is presented. Logically, the pressure of the same circulation pipe section is consistent at each point, so the inlet pressure of the second supply equipment represents the comprehensive pressure of the entire community plane. When the data platform presents the image, the pressure of the branch pipe network is block-based in combination with the GIS pipe network map and the vue framework technology. And the pressure level color is given according to the pressure distribution threshold of the overall pipe network in the urban area, so as to more intuitively observe and understand the change level of the pressure block.

[0053] Due to the wide range of data points in the overall pipeline network, the complex structure of the pipeline network, and the possibility of instantaneous and sudden changes in pressure, automated technology is needed to monitor the changes in pressure points and automatically analyze the operation of the pipeline network, such as whether the pressure mutation is a sudden burst or a chronic water leakage. This requires automatic calculation from two dimensions: one is the monitoring and analysis of a single point, and the other is the analysis and judgment of the associated points. Single-point monitoring mainly uses the cumulative sum CUSUM algorithm to determine whether a signal mutation has occurred by accumulating the deviation between each sample value and the target value. Use Python to set variables in the data background, self-accumulate the data information of the single-point pressure data sample, accumulate the small offsets of the process, thereby amplifying the effect of the offset and improving the sensitivity to small offsets. In the detection of pressure point data changes, it mainly plays a role in determining whether a pressure point occurs and when it occurs. In addition, while monitoring the changes, the data between the associated pressure points will be compared according to the pressure point number. If the changes in the adjacent associated pressure points on the pipeline network are consistent, the associated points in the front or back will be further compared until a negatively correlated node is found. If the mutation point and the associated node change in the same way, there may be a pipe burst; if the changes are inconsistent, there may be a water leak at the node. Therefore, the data platform system will issue an early warning to the dispatch center and quickly query the historical data curve of the inlet and outlet pressure values ​​of the second supply equipment at the mutation node. It is convenient for manual combined with the data historical curve and the early warning of data mutation to make a comprehensive judgment, so as to quickly make dispatch decisions and send personnel to investigate the problem pipe network, thereby greatly improving the level of pipe network operation and management, and fully ensuring the efficient and orderly operation of water supply.

[0054] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A method for monitoring dynamic pressure of urban pipe network based on secondary water supply, characterized in that: The steps include: Monitor the water inlet pressure of the secondary water supply equipment in real time, and form a pressure data table with the obtained water inlet pressure of the secondary water supply equipment to express the pressure distribution level of the water supply network node; Obtain GIS maps through the front-end data platform, bind the pressure data table to the GIS map, and present it in the form of a pipe network pressure map to reflect the real-time block pressure in various areas of the urban area; Use PYthon to model all pressure blocks, convert pressure points into thermal blocks that are related to each other, and form a dynamic pressure block thermal map through a thermal map based on the data platform; Combined with the positioning of thermal map data, a change point monitoring algorithm is established for dynamic calculation and to confirm the sudden pressure change caused by water outage, pipe burst and / or water leakage, so as to realize automatic real-time monitoring of abnormal pressure in the pipeline network.

2. A method for monitoring dynamic pressure of urban pipe network based on secondary water supply according to claim 1, characterized in that: The real-time monitoring of the water inlet pressure of the secondary water supply equipment is to perform real-time sampling of the secondary water supply equipment in each community in the urban area, and the sampling is performed second by second and transmitted remotely to the data server, and then the formed pressure data table is stored.

3. A method for monitoring dynamic pressure of urban pipe network based on secondary water supply according to claim 2, characterized in that: The real-time monitoring of the water inlet pressure of the secondary water supply equipment also includes measuring the actual height of the secondary water supply pump room on site and correcting the average elevation obtained by combining the comprehensive elevation of the reference plane to obtain a corrected pressure data table for reflecting the actual pressure distribution of the pipe network.

4. The method for monitoring dynamic pressure of urban pipe network based on secondary water supply according to claim 1, characterized in that: The use of PYthon to model all pressure blocks also includes adding pressure transmitters and DTU gateways to the inlet and outlet water of the secondary water supply equipment in each community, integrating the DTU with networking function into the secondary water supply equipment distribution cabinet, reading the PLC point table through the Modbus communication protocol, pushing the inlet and outlet water pressures of the secondary water supply equipment to the data server in real time in the form of MQTT, and organizing them into pressure data forms using Python and storing them in the database.

5. The method for monitoring dynamic pressure of urban pipe network based on secondary water supply according to claim 3 is characterized in that: The method of obtaining the GIS map through the front-end data platform also includes using Vue.js to bind the water inlet pressure of each community's secondary supply equipment in the corrected pressure data form to the data platform, and importing the GIS pipe network data, thereby forming a pipe network GIS map with real-time pressure data, which is used to reflect the real-time pressure of each water supply area in the urban area.

6. The method for monitoring dynamic pressure of urban pipe network based on secondary water supply according to claim 1, characterized in that: The establishment of a change point monitoring algorithm for dynamic calculation also includes establishing a change monitoring algorithm for each pressure data point: preprocessing real-time data, removing abnormal jittering pressure values, and storing data within a normal threshold range to ensure calculation stability.

7. A method for monitoring dynamic pressure of urban pipe network based on secondary water supply according to claim 6, characterized in that: The preprocessing of the real-time data also includes calculating the mean of the preprocessed and cleaned data, extracting n-1 pressure values ​​from the data table each time and adding the most recent sampling value to calculate the mean.

8. The method for monitoring dynamic pressure of urban pipe network based on secondary water supply according to claim 1, characterized in that: Through the heat map method of the GIS data platform, the data of two adjacent points are correlated and compared with the data of the abnormal point to determine whether it is a single point leak or a regional pipe burst.

9. A method for monitoring dynamic pressure of urban pipe network based on secondary water supply according to claim 8, characterized in that: Use the data curve chart method of the vue framework to capture the historical data of the determined abnormal points onto the curve chart, and perform correlation analysis of single-point or multi-point data abnormal changes in the form of historical curves.

Images