Water meter type selection rationality diagnosis method

Abstract

The invention provides a water meter model selection rationality diagnosis method, and aims to provide a simple and feasible diagnosis method for judging model selection rationality for a water meter lacking real-time high-frequency instantaneous flow. According to the method, the relationship between the instantaneous flow distribution of the remote water meter and the daily accumulated water quantity data is analyzed to obtain the daily accumulated water quantity reference value of the water meter with each caliber, so that the daily accumulated water quantity of other water meters can be compared with the reference value of the corresponding caliber, and the water meter with unreasonable model selection can be found out.

Description

Technical Field

[0001] The present invention belongs to the technical field of water meter measurement, and particularly relates to a method for selecting a water meter type. Background Art

[0002] The measurement accuracy of a water meter is closely related to the flow rate. Taking a water meter with an accuracy class of 2 as an example, in the low-flow range (Q 1 ≤Q<Q 2 ), the maximum allowable error is ±5%; in the high-flow range (Q 2 ≤Q<Q 4 ), the maximum allowable error is related to the water temperature. When the water temperature range is 0.1°C to 30°C, the maximum allowable error is ±2%, and when the water temperature is higher than 30°C, the maximum allowable error is ±3%. Among them, Q 1 is the minimum flow rate, which represents the lowest flow rate at which the water meter meets the maximum allowable error requirement; Q 2 is the demarcation flow rate, which represents the flow rate that appears between the normal flow rate and the minimum flow rate and divides the flow rate range into two zones, namely the "high zone" and the "low zone", each with a specific maximum allowable error; Q 3 is the normal flow rate, which represents the maximum flow rate at which the water meter meets the maximum allowable error requirement under rated working conditions; the flow rate Q 4 is the overload flow rate, which represents the maximum flow rate at which it is required that the water meter can meet the maximum allowable error requirement in a short time and then still maintain the metering characteristics under rated working conditions. Therefore, operating the water meter within the high-flow range helps to reduce the metering error and ensure the accuracy of the measurement.

[0003] Currently, there are mainly two methods for judging the rationality of water meter type selection. The first method is to judge through the distribution of the instantaneous flow rate of the water meter. The specific scheme is as follows: collect the instantaneous flow rate data of the water meter, count the proportion of the instantaneous flow rate in each flow rate interval, and judge the rationality of the water meter caliber selection by analyzing the proportion. The main defect of this scheme is that it is difficult to obtain the real-time high-frequency instantaneous flow rate data of the water meter. In practical applications, most water meters lack real-time high-frequency instantaneous flow rate data. Although electromagnetic water meters and ultrasonic water meters can provide instantaneous flow rate data, they still face problems such as battery life and cost. Therefore, it is relatively difficult to obtain the instantaneous flow rate distribution of the water meter, which affects the evaluation of the rationality of water meter type selection.

[0004] The second method is to calculate the metering efficiency of the water meter by estimating the normal flow rate of the user. The specific scheme is as follows: obtain the recorded water volume, metering days, and daily water usage time within the statistical period of the user, then divide the recorded water volume by the number of water usage days and then by the daily water usage time to obtain the normal flow rate, and then compare the normal flow rate of the user with the demarcation flow rate Q 2 and the normal flow rate Q 3 . If the normal flow rate of the user is between Q 2 and Q3 If it is between them, it is determined that the current water meter measurement efficiency is stable. The main defect of this scheme is that it is difficult to obtain the accurate daily water usage time of users, resulting in a large calculation error of the user's common flow rate, which in turn affects the analysis of the water meter measurement efficiency. Summary of the Invention

[0005] In view of this, the present invention proposes a diagnostic method for the rationality of water meter selection, aiming to provide a simple, feasible and accurate diagnostic method for judging the rationality of selection for water meters lacking real-time high-frequency instantaneous flow rate. The present invention analyzes the relationship between the instantaneous flow rate distribution and the daily cumulative water volume data of a certain amount of remote water meters to obtain the reference value of the daily cumulative water volume of each caliber water meter, so that the daily cumulative water volume of other water meters can be compared with the reference value of the corresponding caliber, and then find out the water meters with the situation of "using a big horse to pull a small cart". Using a big horse to pull a small cart means that the water meter selection is too large, resulting in the phenomenon of a large water meter with a small flow rate. Most of the instantaneous flow rates of the water meter are lower than the demarcation flow rate Q 2 , which results in a large measurement error. The rationality described in the present invention means that the water meter does not have the situation of "using a big horse to pull a small cart".

[0006] The specific technical solution is as follows:

[0007] A diagnostic method for the rationality of water meter selection,

[0008] Step 1: Analyze the relationship between the instantaneous flow rate distribution and the average daily cumulative water volume data of remote water meters of each caliber through statistical data;

[0009] Step 2: Use the relationship between the instantaneous flow rate distribution and the average daily cumulative water volume data to obtain the reference value of the daily cumulative water volume of each caliber water meter;

[0010] Step 3: Obtain the daily cumulative water volume of the water meter to be diagnosed, and judge the rationality of the selection of the water meter to be diagnosed through the reference value of the daily cumulative water volume of the water meter of the corresponding caliber.

[0011] Furthermore, the specific method for analyzing the relationship between the instantaneous flow rate distribution and the average daily cumulative water volume data of a certain caliber remote water meter is to collect the instantaneous flow rate and cumulative water volume data of multiple remote water meters of a certain caliber at a certain frequency; count the number of each remote water meter whose instantaneous flow rate is higher than the demarcation flow rate Q 2 ; count the total number of instantaneous flow rates of each remote water meter; calculate the proportion y of the number of each remote water meter whose instantaneous flow rate is higher than the demarcation flow rate Q 2 in the total number of instantaneous flow rates; use the statistical data to calculate the average daily cumulative water volume x of each remote water meter; fit the functional relationship between the proportion y and the average daily cumulative water volume x, where the demarcation flow rate Q 2 represents the flow rate that appears between the common flow rate and the minimum flow rate and divides the flow rate range into a high zone and a low zone with specific maximum allowable errors.

[0012] Further, the fitting curve includes a Logistic curve, an exponential function, a logarithmic function, or is obtained by a machine learning algorithm.

[0013] Further, the method for determining the daily cumulative water volume reference value is to determine a ratio as the standard for judging the rationality of the water meter selection type, and substituting this value into the fitting equation to obtain the daily cumulative water volume reference value.

[0014] Further, step 3 specifically includes that when the daily cumulative water volume of the water meter to be diagnosed is greater than the daily cumulative water volume reference value of the water meter with the corresponding caliber, it indicates that the water meter selection type to be diagnosed is reasonable, otherwise it is unreasonable.

[0015] Beneficial effects

[0016] 1. The present invention can judge whether there is a situation of "using a big horse to pull a small cart" for water meters lacking real-time high-frequency instantaneous flow data.

[0017] 2. The present invention can obtain the daily cumulative water volume reference value for judging whether a water meter is "using a big horse to pull a small cart" according to the judgment boundary of any water meter "using a big horse to pull a small cart" required, that is, the proportion of the number of times the instantaneous flow rate of the water meter is higher than Q 2 in the total number of instantaneous flow rates.

[0018] 3. After obtaining the daily cumulative water volume reference value of the water meter according to the requirements, the present invention only needs to compare the daily cumulative water volume of other water meters with the reference value to obtain the judgment result. Description of the drawings

[0019] Figure 1 Flowchart of the method;

[0020] Figure 2 a. Fitting curve between the average daily cumulative water volume of a water meter with a caliber of DN50 and the proportion of the number of times the instantaneous flow rate is higher than Q 2 in the total number of instantaneous flow rates;

[0021] Figure 2 b. Fitting curve between the average daily cumulative water volume of a water meter with a caliber of DN80 and the proportion of the number of times the instantaneous flow rate is higher than Q 2 in the total number of instantaneous flow rates;

[0022] Figure 2 c. Fitting curve between the average daily cumulative water volume of a water meter with a caliber of DN100 and the proportion of the number of times the instantaneous flow rate is higher than Q 2 in the total number of instantaneous flow rates;

[0023] Figure 2 d. Fitting curve between the average daily cumulative water volume of a water meter with a caliber of DN150 and the proportion of the number of times the instantaneous flow rate is higher than Q 2The fitting curve between the proportion of the number of [specific conditions] and the total number of instantaneous flow rates;

[0024] Figure 2 e. The average daily cumulative water volume and instantaneous flow rate of water meters with a water meter diameter of DN200 are higher than Q 2 The fitting curve between the proportion of the number of [specific conditions] and the total number of instantaneous flow rates;

[0025] Figure 2 f. The average daily cumulative water volume and instantaneous flow rate of water meters with a water meter diameter of DN300 are higher than Q 2 The fitting curve between the proportion of the number of [specific conditions] and the total number of instantaneous flow rates. Detailed implementation method

[0026] (1) For a water meter of a certain diameter, collect the instantaneous flow rate and cumulative water volume data of a certain number of remote water meters at a certain frequency. The shorter the data collection time interval, the better, preferably 5 minutes. The longer the collection period, the better, not less than 1 month. The more remote water meters, the better, not less than 50.

[0027] (2) Count the proportion of the number of times the instantaneous flow rate of each remote water meter is higher than Q 2 in the total number of instantaneous flow rates, denoted as r, and the formula is as follows:

[0028]

[0029] where x 1 represents the number of times the instantaneous flow rate of the water meter is higher than Q 2 , and x represents the total number of instantaneous flow rates of the water meter.

[0030] (3) Divide the cumulative water consumption of the water meter during the collection period by the number of collection days to calculate the average daily cumulative water volume of each water meter, denoted as Q a , and the formula is as follows:

[0031]

[0032] where Q t represents the cumulative water consumption of the water meter during the collection period, and N represents the number of collection days.

[0033] (4) Determine the relationship between the proportion of the number of times the instantaneous flow rate of the water meter is higher than Q 2 in the total number of instantaneous flow rates and the average daily cumulative water volume: Use the average daily cumulative water volume as the abscissa and the proportion of the number of times the instantaneous flow rate is higher than Q 2 in the total number of instantaneous flow rates as the ordinate to make a scatter plot of the data of this diameter water meter. Analyze the distribution of the scatter plot, select an appropriate fitting curve to fit the data points, and obtain the fitting equation of the two.

[0034] (5) Select a suitable instantaneous flow rate of the water meter higher than Q2 The proportion of the number of [specific condition] in the total number of instantaneous flows is used as the criterion for judging whether a water meter of the corresponding caliber is "using a big horse to pull a small cart".

[0035] (6) Substitute this proportion into the fitting equation of the water meter of the corresponding caliber to calculate and determine the reference value of the daily cumulative water volume for judging whether the water meter of the corresponding caliber is "using a big horse to pull a small cart".

[0036] (7) For water meters of other calibers, repeat steps (1)-(6) above to obtain the reference value of the daily cumulative water volume for judging whether each caliber of water meter is "using a big horse to pull a small cart".

[0037] The data interval time of the remote water meter is not necessarily limited to the 5 minutes described in the present invention. It can also be other time intervals, and the shorter the time interval, the better. Specifically, it should be selected according to the performance of the remote water meter.

[0038] The data acquisition period of the remote water meter is not necessarily limited to the 1 month described in the present invention. It can also be other periods, and the longer the number of acquisition days, the better.

[0039] The sampling quantity of each caliber of remote water meter is not necessarily limited to the 50 described in the present invention. It can also be other quantities, and the more the quantity, the better.

[0040] When analyzing the relationship between the average daily cumulative water volume of the water meter and the proportion of the number of instantaneous flows higher than Q 2 in the total number of instantaneous flows, the fitting equation is not necessarily limited to the Logistic curve described in the present invention. Exponential functions and logarithmic functions, etc. can be flexibly selected according to their trends, or machine learning algorithms can also be used for judgment.

[0041] Any proportion of the number of instantaneous flows higher than Q 2 in the total number of instantaneous flows can be selected as the criterion for judging whether the water meter is "using a big horse to pull a small cart". In this embodiment, 50% is used as the judgment criterion, but in specific implementations, it is not necessarily limited to the 50% described in this embodiment.

[0042] The following is an explanation of the process of judging whether a water meter is "using a big horse to pull a small cart" using the reference value of the daily cumulative water volume for the remote water meters in a certain southern city of China. The instantaneous flow and cumulative water volume data of the remote water meters were collected. The data acquisition time was from May 1, 2024 to May 31, 2024, for a total of 31 days, and the acquisition time interval was 5 minutes. 15 DN50 water meters, 74 DN80 water meters, 75 DN100 water meters, 85 DN150 water meters, 37 DN200 water meters, and 16 DN300 water meters were selected, totaling 302 water meters for analysis.

[0043] The number of times the instantaneous flow of each water meter is higher than Q 2The proportion of the number of [instantaneous flow rate] higher than Q in the total number of instantaneous flow rates was calculated, and the average daily cumulative water volume was calculated. Using the average daily cumulative water volume as the abscissa and the proportion of the number of instantaneous flow rates higher than Q in the total number of instantaneous flow rates as the ordinate, scatter plots of water meters of each caliber were drawn. According to the distribution of the scatter plots, a Logistic curve was selected for fitting. The curve equation is shown in Equation (3), and the fitting results are shown in 2 The proportion of the number of [instantaneous flow rate] higher than Q in the total number of instantaneous flow rates was used as the ordinate, and scatter plots of water meters of each caliber were drawn. According to the distribution of the scatter plots, a Logistic curve was selected for fitting. The curve equation is shown in Equation (3), and the fitting results are shown in Figure 2 a- Figure 2 f.

[0044]

[0045] The fitting equations between the average daily cumulative water volume of water meters of each caliber and the proportion of the number of instantaneous flow rates higher than Q in the total number of instantaneous flow rates can be obtained, as shown in Table 1. 2 The fitting equations between the average daily cumulative water volume of water meters of each caliber and the proportion of the number of instantaneous flow rates higher than Q in the total number of instantaneous flow rates can be obtained, as shown in Table 1.

[0046] Table 1 Relationship equations between the proportion (y) of the number of instantaneous flow rates higher than Q in the total number of instantaneous flow rates of water meters of each caliber and the average daily cumulative water volume (x) 2 The relationship equations between the proportion (y) of the number of instantaneous flow rates higher than Q in the total number of instantaneous flow rates of water meters of each caliber and the average daily cumulative water volume (x)

[0047]

[0048] Assuming that the proportion (y) of the number of instantaneous flow rates higher than Q in the total number of instantaneous flow rates of the water meter is 50% as the boundary for judging "using a big horse to pull a small cart", substituting it into the fitting curve equations of water meters of each caliber, the corresponding x value is calculated and used as the reference value of the daily cumulative water volume for judging "using a big horse to pull a small cart", as shown in Table 2. 2 Assuming that the proportion (y) of the number of instantaneous flow rates higher than Q in the total number of instantaneous flow rates of the water meter is 50% as the boundary for judging "using a big horse to pull a small cart", substituting it into the fitting curve equations of water meters of each caliber, the corresponding x value is calculated and used as the reference value of the daily cumulative water volume for judging "using a big horse to pull a small cart", as shown in Table 2.

[0049] Table 2 Reference values of daily cumulative water volume of water meters of each caliber

[0050] Water meter caliber <![CDATA[Daily cumulative water volume reference value (m 3 ) <!-- 4 -->]]> DN50 3.22 DN80 21.6 DN100 28.58 DN150 108.61 DN200 176.34 DN300 550.97

[0051] According to the above method, when the daily cumulative water volume of the existing water meter is less than the reference value of the daily cumulative water volume of the water meter of the corresponding caliber, it can be defined that there is a situation of "using a big horse to pull a small cart".

[0052] In this article, specific examples are used to elaborate on the principle and implementation mode of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation mode and application scope (such as applied to flow meters, or other fluid flow measurement instruments such as hot water and petroleum). In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A method for diagnosing the rationality of water meter selection, characterized by: Step 1: Analyze the relationship between the instantaneous flow distribution and the average daily accumulated water volume data of each caliber remote water meter through statistical data; Step 2: Using the relationship between the instantaneous flow distribution and the average daily cumulative water volume data, obtain the daily cumulative water volume reference value of each caliber water meter; Step 3: Obtain the daily cumulative water volume of the water meter to be diagnosed, and determine the rationality of the selection of the water meter to be diagnosed based on the daily cumulative water volume reference value of the water meter of the corresponding caliber.

2. A method for diagnosing the rationality of water meter selection according to claim 1, characterized in that: The specific method for analyzing the relationship between the instantaneous flow distribution and the average daily cumulative water volume data of a certain caliber remote water meter is to collect the instantaneous flow and cumulative water volume data of multiple remote water meters of a certain caliber at a certain frequency; count the number of each remote water meter whose instantaneous flow is higher than the boundary flow Q2; count the total number of instantaneous flow of each remote water meter; Calculate the ratio y of the number of instantaneous flow rates of each remote water meter that is higher than the boundary flow rate Q2 to the total number of instantaneous flow rates; calculate the average daily cumulative water volume x of each remote water meter using statistical data; and obtain the functional relationship between the ratio y and the average daily cumulative water volume x by fitting, wherein the boundary flow rate Q2 represents the flow rate that appears between the normal flow rate and the minimum flow rate, dividing the flow range into high and low zones, each with a specific maximum allowable error.

3. A method for diagnosing the rationality of water meter selection according to claim 2, characterized in that: The fitting curve includes a logistic curve, an exponential function, a logarithmic function, or is obtained through a machine learning algorithm.

4. A method for diagnosing the rationality of water meter selection according to claim 1, characterized in that: The method for determining the daily cumulative water volume reference value is to determine a ratio as a standard for judging the rationality of water meter selection, and to substitute this value into the fitting equation to obtain the daily cumulative water volume reference value.

5. A method for diagnosing the rationality of water meter selection according to any one of claims 1 to 4, characterized in that: Step 3 specifically includes: when the daily cumulative water volume of the water meter to be diagnosed is greater than the daily cumulative water volume reference value of the water meter of the corresponding caliber, it indicates that the selection of the water meter to be diagnosed is reasonable, otherwise it is unreasonable.

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