Water flow metering method and water flow metering system

Abstract

The invention relates to a water flow metering method and a water flow metering system, and belongs to the field of water resource metering. The water flow metering method comprises the steps that temperature data, humidity data and water quality data in a target time period are obtained through a temperature and humidity sensor and a water quality sensor respectively to serve as input data of a water flow model. Wherein environment information around the water pump is collected in real time through the temperature and humidity sensor and the water quality sensor and serves as input of the water flow model. Temperature data, humidity data and water quality data are input into a water flow model, and the water flow model outputs a real-time coefficient for converting water with electricity, so that the optimal coefficient for converting water with electricity can be obtained in real time according to the change of a complex actual environment; and more accurate water flow data can be obtained by substituting the power consumption in the period of time and the optimal coefficient of converting electricity into water into a water flow calculation formula.

Description

Technical Field

[0001] The present application relates to the field of water resource measurement, and in particular to a water flow measurement method and a water flow measurement system. Background Art

[0002] In order to facilitate the recording of water consumption, the water pump flow rate is generally calculated and recorded to obtain the specific water consumption. Since traditional mechanical water pumps are affected by various factors and are prone to measurement errors, resulting in inaccurate water consumption calculation results, the more widespread method now is to calculate the water pump flow rate by converting electricity into water, that is, converting the measured electricity consumption into water consumption.

[0003] However, the existing method of measuring water consumption or water flow by converting electricity to water has the following problems: only the electricity usage data of the water pump is collected, and the electricity usage data is weighted by the manually predicted water-electricity conversion coefficient to calculate the water consumption. The problem with this is that the water consumption obtained after the electricity weighting is accurate only when the actual situation meets the predicted water-electricity conversion coefficient, and the actual situation is definitely more complicated than the predicted situation. For example, rainy days, low temperatures, high temperatures and other environments, or different water quality in different regions, will lead to different water pump flow rates under the same power consumption, or different water pump power consumption in the same time, which will ultimately lead to large errors in the water consumption obtained after the electricity weighting, and ultimately cause the problem of inaccurate water consumption calculation.

[0004] There is currently no effective solution to the problem of inaccurate water consumption calculation when the predicted water-to-electricity conversion coefficient does not conform to the actual complex situation in the existing method of measuring water consumption by converting electricity to water. Summary of the invention

[0005] The present invention provides a water flow metering method and a water flow metering system to solve the problem of inaccurate water consumption calculation when the predicted water-to-electricity conversion coefficient does not conform to the actual complex situation in the existing method of measuring water consumption by converting electricity into water.

[0006] In a first aspect, the present invention provides a water flow model training method, comprising obtaining a plurality of pre-constructed sample data groups, each sample data group comprising sample temperature data, sample humidity data, sample water quality data and a sample label; training a deep learning model through a plurality of sample temperature data, sample humidity data, sample water quality data and their corresponding sample labels to obtain a water flow model; wherein the sample data group construction step comprises: building a water flow test channel, installing a target water pump in the water flow test channel, and installing a temperature and humidity sensor and a water quality sensor on the target water pump; providing water of a target flow rate to the water flow test channel, and obtaining sample temperature data, sample humidity data and sample water quality data through the temperature and humidity sensor and the water quality sensor respectively, and obtaining the power consumption of the target water pump through an electric meter, and obtaining a sample label according to the power consumption of the target water pump and the target flow rate of water, and the sample temperature data, sample humidity data, sample water quality data and the sample label constitute a sample data group.

[0007] In a second aspect, a water flow metering method is provided in the present invention, and the steps are as follows: temperature data, humidity data and water quality data within a target time period are respectively obtained through a temperature and humidity sensor and a water quality sensor as input data of a water flow model; the electricity-to-water coefficient within the target time period is obtained through the water flow model; the electric meter data of a target water pump within the target time period is obtained, and the water flow data within the target time period is obtained by combining the electric meter data of the target water pump and the electricity-to-water coefficient.

[0008] Furthermore, the target time period includes a plurality of continuous sub-time periods, the temperature data within the target time period includes the average temperature within the plurality of sub-time periods; the humidity data within the target time period includes the average humidity within the plurality of sub-time periods; the water quality data within the target time period includes the average water quality within the plurality of sub-time periods; the electricity-to-water coefficient within the target time period includes the average electricity-to-water coefficient within the plurality of sub-time periods within the target time period; the electric meter data of the target water pump within the target time period includes the average power consumption of the target water pump within the plurality of sub-time periods within the target time period;

[0009] Combining the electricity meter data of the target water pump and the electricity-to-water coefficient to obtain the water flow data within the target time period includes: substituting the average power consumption of the target water pump in multiple sub-time periods within the target time period and the average electricity-to-water coefficient into the electricity-to-water formula to obtain the water flow in multiple sub-time periods within the target time period.

[0010] Furthermore, the temperature data within the target time period includes the average temperature within the target time period; the humidity data within the target time period includes the average humidity within the target time period; the water quality data within the target time period includes the average water quality within the target time period; the electricity-to-water coefficient within the target time period includes the average electricity-to-water coefficient within the target time period; the electric meter data of the target water pump within the target time period includes the average power consumption of the target water pump within the target time period;

[0011] Combining the electricity meter data of the target water pump and the electricity-to-water coefficient to obtain the water flow data in the target time period includes: substituting the average power consumption and the average electricity-to-water coefficient of the target water pump in the target time period into the electricity-to-water formula to obtain the water flow in the target time period.

[0012] Furthermore, the temperature data within the target time period includes the instantaneous temperature at each moment within the target time period; the humidity data within the target time period includes the instantaneous humidity at each moment within the target time period; the water quality data within the target time period includes the instantaneous water quality at each moment within the target time period; the electricity-to-water coefficient within the target time period includes the instantaneous electricity-to-water coefficient at each moment within the target time period; the electric meter data of the target water pump within the target time period includes the instantaneous power of the target water pump at each moment within the target time period; the water flow data within the target time period includes the instantaneous water flow rate at each moment within the target time period;

[0013] Combining the electric meter data of the target water pump and the electricity-to-water coefficient to obtain the water flow data within the target time period includes: obtaining the instantaneous water flow rate at each moment within the target time period according to the instantaneous electricity-to-water coefficient and the instantaneous power of the target water pump at each moment within the target time period; integrating the instantaneous water flow rate at each moment within the target time period to obtain the water flow within the target time period.

[0014] Furthermore, the formula for converting electricity to water is:

[0015] WD=CD×Ed

[0016] Among them, CD is the hydropower conversion coefficient, the unit is cubic meter per kilowatt-hour (m 3 / kWh, WD is the water output in a certain period of time, in cubic meters (m 3 ), Ed is the electricity consumption in a certain period of time, in kilowatt-hours (kWh).

[0017] In a third aspect, the present invention provides a water flow metering system, which includes a water pump, a temperature and humidity sensor, a water quality sensor, an electric meter and a server. The temperature and humidity sensor is installed on the water pump and is used to detect the temperature and humidity of the environment around the water pump. The water quality sensor is installed on the water pump and is used to detect the water quality of the environment around the water pump. The electric meter is used to detect the power consumption of the water pump. The server is equipped with a water flow model, and is used to obtain data from the temperature and humidity sensor, the water quality sensor and the electric meter and input the data into the water flow model to obtain the electricity-to-water coefficient, and is used to substitute the electricity-to-water coefficient and the power consumption read by the electric meter into the electricity-to-water formula to obtain the predicted water flow.

[0018] Furthermore, the water flow metering system also includes a data terminal, which is electrically connected to the server and is used to input instructions for obtaining sample data and sample labels to the server.

[0019] Compared with the related art, the present invention has the following beneficial effects:

[0020] 1. The environmental information around the water pump is collected in real time through temperature and humidity sensors and water quality sensors as the input of the water flow model. By inputting temperature data, humidity data and water quality data into the water flow model, the water flow model outputs a real-time electricity-to-water coefficient, so that the best electricity-to-water coefficient can be obtained in real time according to the changes in the complex actual environment. Substituting the power consumption during this period and the best electricity-to-water coefficient into the water flow calculation formula can obtain more accurate water flow data.

[0021] 2. Multiple continuous sub-time periods can be understood as sub-time periods of the same length or as sub-time periods of different lengths. The purpose of the target time period including multiple continuous sub-time periods is that the server can collect multiple copies of data at one time and process them synchronously, and finally output multiple copies of data at the same time, which is conducive to improving the efficiency of data processing.

[0022] 3. The average temperature within the target time period can be understood as a temperature value that remains a constant within a certain time period. If the time region for calculating the water flow can be divided into a small number of intervals with uniform data, then the final water flow data is simply the sum of the interval water flow, which helps to reduce the difficulty of calculation.

[0023] 4. The instantaneous temperature at each moment in the target time period can be understood as dividing the target time period into several time units, each time unit corresponds to an instantaneous temperature. When calculating the water flow in complex situations, since the temperature and humidity data and water quality data are always in a changing state, it is difficult to accurately calculate the water flow as the average value in the time period. At this time, the principle of calculus can be used. The water flow model converts the sample data in each time unit into the corresponding instantaneous electricity-to-water coefficient. The instantaneous water flow rate is obtained by the instantaneous electricity-to-water coefficient and the power consumption rate of each time unit. The instantaneous water flow rate is then integrated on the time axis to obtain a more accurate water flow, which is more conducive to the accurate calculation of water flow data in complex situations.

[0024] 5. According to the changes in temperature, humidity and water quality data in different target time periods, you can choose one of the three methods to calculate the water flow as needed. The combination of the three methods can make the flow calculation process faster and the data more accurate.

[0025] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a flow chart of a water flow model training method in an embodiment;

[0027] Figure 2 is a flow chart of steps for constructing a sample data set in an embodiment;

[0028] Figure 3 is a flow chart of the water flow metering method in the embodiment. DETAILED DESCRIPTION

[0029] In order to more clearly understand the purpose, technical solutions and advantages of the present application, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments.

[0030] Unless otherwise defined, the technical terms or scientific terms involved in this application shall have the general meaning understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the", "these" and the like in this application do not represent quantitative restrictions, and they can be singular or plural. The terms "include", "comprise", "have" and any variants thereof involved in this application are intended to cover non-exclusive inclusions; for example, a process, method and system, product or device comprising a series of steps or modules (units) is not limited to the listed steps or modules (units), but may include unlisted steps or modules (units), or may include other steps or modules (units) inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether directly or indirectly. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, "A and / or B" can mean: A exists alone, A and B exist at the same time, and B exists alone. Usually, the character " / " indicates that the objects associated with each other are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0031] In the present embodiment, a water flow metering method and a water flow metering system are provided, aiming to provide a water flow metering method to more accurately calculate the water flow of a water pump within a period of time by means of electricity-to-water conversion, so as to achieve accurate water flow calculation by changing the electricity-to-water conversion coefficient according to the environment when encountering actual complex situations. The present embodiment includes: a water flow metering method and a water flow metering system. Since the water flow metering method involves a special deep learning model, namely a water flow model, the present embodiment also provides a water flow model training method.

[0032] See also Figure 1 In this embodiment, a water flow model training method is provided, including steps S100 and S200.

[0033] S100, obtaining a plurality of pre-constructed sample data groups, each sample data group including sample temperature data, sample humidity data, sample water quality data and a sample label.

[0034] S200, training a deep learning model using multiple sample temperature data, sample humidity data, sample water quality data and their corresponding sample labels to obtain a water flow model.

[0035] Each sample data set can be used to train a deep learning model. After constructing multiple sample data sets, some of the sample data sets can be used as training sets and other sample data sets can be used as test sets.

[0036] Among them, see Figure 2 The steps of constructing the sample data set include steps S110, S120, S130 and S140.

[0037] S110, building a water flow test channel, installing a target water pump in the water flow test channel, and installing a temperature and humidity sensor and a water quality sensor on the target water pump.

[0038] S120, providing water of a target flow rate to the water flow test channel, and obtaining sample temperature data, sample humidity data, and sample water quality data through a temperature and humidity sensor and a water quality sensor, respectively.

[0039] S130, obtaining the power consumption of the target water pump through the electric meter, and obtaining a sample label according to the power consumption of the target water pump and the target flow rate of water.

[0040] S140, the sample temperature data, the sample humidity data, the sample water quality data and the sample label form a sample data group.

[0041] It can be understood that when the target water pump is at a certain power, the sample temperature data, sample humidity data and sample water quality data obtained by the temperature and humidity sensor and the water quality sensor are in a mapping relationship with the sample label. The sample temperature data, sample humidity data, sample water quality data and sample label constitute a sample data group, and the deep learning model can be trained through the sample data group, and the deep learning model can be iterated through the cross entropy loss function. When the change of the cross entropy loss function tends to be stable or iterates a certain number of times (such as 30 times), the water flow model can be obtained. The process of model iteration belongs to mature existing technology, so it will not be repeated.

[0042] In step S130, a sample label is obtained according to the power consumption of the target water pump and the target water flow rate. This can be explained as: substituting the power consumption of the target water pump and the target water flow rate into the power-to-water coefficient formula to obtain the target power-to-water coefficient, and using the target power-to-water coefficient as the sample label. The target flow rate is the actual water flow rate passing through the target water pump.

[0043] The formula for the electricity-to-water coefficient is:

[0044] CD=WD / Ed

[0045] Among them, CD is the hydropower conversion coefficient, the unit is cubic meter per kilowatt-hour (m 3 / kWh, WD is the water output in a certain period of time, in cubic meters (m3 ), Ed is the electricity consumption in a certain period of time, in kilowatt-hours (kWh).

[0046] See also Figure 3 , this embodiment also provides a water flow metering method, the steps include S300, S310, S320.

[0047] S300, obtaining temperature data, humidity data and water quality data within a target time period through a temperature and humidity sensor and a water quality sensor respectively as input data for a water flow model.

[0048] S310, obtaining the electricity-to-water conversion coefficient within the target time period through a water flow model.

[0049] S320, obtaining the electricity meter data of the target water pump within the target time period, and combining the electricity meter data of the target water pump with the electricity-to-water coefficient to obtain the water flow data within the target time period.

[0050] In the above steps, the purpose of step S300 is to collect the environmental information around the water pump in real time through the temperature and humidity sensor and the water quality sensor as the input of the water flow model. The purpose of step S310 is to input the temperature data, humidity data and water quality data into the water flow model, and the water flow model outputs the real-time electricity-to-water coefficient, so that the best electricity-to-water coefficient can be obtained in real time according to the changes in the complex actual environment, and the power consumption during this period and the best electricity-to-water coefficient can be substituted into the water flow calculation formula to obtain more accurate water flow data.

[0051] Since different ways of dividing the target time period can bring different beneficial effects, three ways of dividing are introduced below:

[0052] In this embodiment, the target time period includes a plurality of continuous sub-time periods, and the temperature data within the target time period includes the average temperature within the plurality of sub-time periods. The humidity data within the target time period includes the average humidity within the plurality of sub-time periods. The water quality data within the target time period includes the average water quality within the plurality of sub-time periods. The electricity-to-water coefficient within the target time period includes the average electricity-to-water coefficient within the plurality of sub-time periods within the target time period. The electric meter data of the target water pump within the target time period includes the average power consumption of the target water pump within the plurality of sub-time periods within the target time period.

[0053] This method can be understood in combination with step S320 as combining the electric meter data of the target water pump and the electricity-to-water coefficient to obtain the water flow data within the target time period, including: substituting the average power consumption of the target water pump in multiple sub-time periods within the target time period and the average electricity-to-water coefficient into the electricity-to-water formula to obtain the water flow in multiple sub-time periods within the target time period.

[0054] Among them, multiple continuous sub-time periods can be understood as sub-time periods of the same length, or as sub-time periods of different lengths. The purpose of the target time period including multiple continuous sub-time periods is that the server can collect multiple copies of data at one time and process them synchronously, and finally output multiple copies of data at the same time, which is conducive to improving data processing efficiency.

[0055] In some other embodiments, the temperature data within the target time period includes the average temperature within the target time period; the humidity data within the target time period includes the average humidity within the target time period; the water quality data within the target time period includes the average water quality within the target time period; the electricity-to-water coefficient within the target time period includes the average electricity-to-water coefficient within the target time period; and the electric meter data of the target water pump within the target time period includes the average power consumption of the target water pump within the target time period.

[0056] In step S320, combining the electricity meter data of the target water pump and the electricity-to-water coefficient to obtain the water flow data within the target time period includes: substituting the average power consumption of the target water pump within the target time period and the average electricity-to-water coefficient into the electricity-to-water formula to obtain the water flow within the target time period.

[0057] Among them, the average temperature within the target time period can be understood as a temperature value that remains a constant within a certain time period. If the time area where the water flow needs to be calculated can be divided into a small number of intervals with uniform data, then the final water flow data is simply the sum of the interval water flow, which helps to reduce the difficulty of calculation.

[0058] In other embodiments, the temperature data within the target time period includes the instantaneous temperature at each moment within the target time period; the humidity data within the target time period includes the instantaneous humidity at each moment within the target time period; the water quality data within the target time period includes the instantaneous water quality at each moment within the target time period; the electricity-to-water coefficient within the target time period includes the instantaneous electricity-to-water coefficient at each moment within the target time period; the electric meter data of the target water pump within the target time period includes the instantaneous power of the target water pump at each moment within the target time period; and the water flow data within the target time period includes the instantaneous water flow rate at each moment within the target time period.

[0059] In step S320, the water flow data within the target time period is obtained by combining the electric meter data of the target water pump and the electricity-to-water coefficient, including: obtaining the instantaneous water flow rate at each moment in the target time period according to the instantaneous electricity-to-water coefficient and the instantaneous power of the target water pump at each moment in the target time period; integrating the instantaneous water flow rate at each moment in the target time period to obtain the water flow rate within the target time period.

[0060] Among them, the instantaneous temperature at each moment in the target time period can be understood as dividing the target time period into several time units, each time unit corresponds to an instantaneous temperature, and when calculating the water flow in complex situations, since the temperature and humidity data and water quality data are always in a changing state, it is difficult to accurately calculate the water flow as an average value in the time period. At this time, the principle of calculus can be used. The water flow model converts the sample data in each time unit into the corresponding instantaneous electricity-to-water coefficient, and the instantaneous water flow rate is obtained by the instantaneous electricity-to-water coefficient and the power consumption rate of each time unit. The instantaneous water flow rate is then integrated on the time axis to obtain a more accurate water flow, which is more conducive to the accurate calculation of water flow data in complex situations.

[0061] Furthermore, the formula for converting electricity to water is:

[0062] WD=CD×Ed

[0063] Among them, CD is the hydropower conversion coefficient, the unit is cubic meter per kilowatt-hour (m 3 / kWh, WD is the water output in a certain period of time, in cubic meters (m 3 ), Ed is the electricity consumption in a certain period of time, in kilowatt-hours (kWh).

[0064] In general, in addition to the above-mentioned effects, the three methods of specifying target time periods also provide an effect, which is to increase the strategic nature of the water flow metering method. According to the changes in different temperature and humidity data and water quality data in different target time periods, one of the three methods can be selected as needed to calculate the water flow. The combination of the three methods can make the flow calculation process faster and the data more accurate.

[0065] In addition, a water flow metering system is also provided in this embodiment, which includes a water pump, a temperature and humidity sensor, a water quality sensor, an electric meter and a server. The temperature and humidity sensor is installed on the water pump and is used to detect the temperature and humidity of the environment around the water pump. The water quality sensor is installed on the water pump and is used to detect the water quality of the environment around the water pump. The electric meter is used to detect the power consumption of the water pump. The server is equipped with a water flow model, and is used to obtain data from the temperature and humidity sensor, the water quality sensor and the electric meter and input the data into the water flow model to obtain the electricity-to-water coefficient, and is used to substitute the electricity-to-water coefficient and the power consumption read by the electric meter into the electricity-to-water formula to obtain the predicted water flow. In order to implement the above-mentioned water flow model and water flow metering method, the water flow metering system includes a water pump, a temperature and humidity sensor, a water quality sensor, an electric meter and a server structure. During the water flow model training process, the server receives the operator's instructions to input sample data (temperature and humidity, water quality) and sample labels into the deep learning model, and the deep learning model is iterated to obtain the water flow model, wherein the sample data is obtained by the server controlling the temperature and humidity sensor and the water quality sensor. During the use of the water flow model, the server automatically obtains the temperature data, humidity data and water quality data from the temperature and humidity sensors and the water quality sensors and inputs them into the water flow model. The water flow model derives the current electricity-to-water coefficient based on the input temperature data, humidity data and water quality data. After the server obtains the electricity-to-water coefficient, the server reads the power consumption of the water pump through the electric meter, and calculates the current water flow based on the electricity-to-water coefficient and the power consumption. The entire operation process is intelligent, which greatly reduces the labor intensity and effectively improves the accuracy of water flow calculation.

[0066] Furthermore, the water flow metering system also includes a data terminal, which is electrically connected to the server and is used to input instructions for obtaining sample data and sample labels to the server. The data terminal can facilitate the operator to interact with the server. For example, the data terminal has a human-computer language conversion function (such as SQL statement and natural language conversion in the prior art), thereby improving the applicability of the system and lowering the operating threshold.

[0067] It should be understood that the specific embodiments described herein are only used to explain the application, rather than to limit it. Based on the embodiments provided in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the protection scope of this application.

[0068] Obviously, the drawings are only some examples or embodiments of the present application. For ordinary technicians in the field, the present application can also be applied to other similar situations based on these drawings without creative work. In addition, it is understandable that although the work done in this development process may be complicated and lengthy, for ordinary technicians in the field, certain changes in design, manufacturing or production based on the technical content disclosed in this application are only conventional technical means and should not be regarded as insufficient content disclosed in this application.

Claims

1. A water flow model training method, comprising: Acquire a plurality of pre-constructed sample data sets, each sample data set comprising sample temperature data, sample humidity data, sample water quality data and a sample label; The deep learning model is trained through multiple sample temperature data, sample humidity data, sample water quality data and their corresponding sample labels to obtain a water flow model; The steps of constructing the sample data set include: Build a water flow test channel, install the target water pump in the water flow test channel, and install a temperature and humidity sensor and a water quality sensor on the target water pump; Water of target flow rate is provided to the water flow test channel, and sample temperature data, sample humidity data and sample water quality data are respectively obtained through temperature and humidity sensors and water quality sensors, and the power consumption of the target water pump is obtained through an electric meter. The sample label is obtained according to the power consumption of the target water pump and the target water flow rate. The sample temperature data, sample humidity data, sample water quality data and the sample label constitute a sample data group.

2. The water flow model training method according to claim 1, characterized in that: The sample labels are obtained based on the target water pump power consumption and the target water flow rate, including: Substitute the power consumption of the target water pump and the target water flow rate into the electricity-to-water coefficient formula to obtain the target electricity-to-water coefficient, and use the target electricity-to-water coefficient as a sample label.

3. The water flow model training method according to claim 2, characterized in that: The formula for the electricity-to-water coefficient is: CD=WD / Ed Among them, CD is the hydropower conversion coefficient, the unit is cubic meter per kilowatt-hour (m 3 / kWh, WD is the water output in a certain period of time, in cubic meters (m 3 ), Ed is the electricity consumption in a certain period of time, in kilowatt-hours (kWh).

4. A water flow measurement method, characterized in that: include: The temperature data, humidity data and water quality data in the target time period are respectively obtained by a temperature and humidity sensor and a water quality sensor as input data of a water flow model; wherein the water flow model is obtained by the water flow model training method described in any one of claims 1 to 3; The electricity-to-water conversion coefficient within the target time period is obtained through the water flow model; The electric meter data of the target water pump within the target time period is obtained, and the water flow data within the target time period is obtained by combining the electric meter data of the target water pump and the electricity-to-water coefficient.

5. The water flow measurement method according to claim 4, characterized in that: The target time period includes a plurality of continuous sub-time periods, and the temperature data in the target time period includes an average temperature in the plurality of sub-time periods; The humidity data in the target time period includes the average humidity in multiple sub-time periods; The water quality data in the target time period includes the average water quality in multiple sub-time periods; The electricity-to-water coefficient in the target time period includes an average electricity-to-water coefficient in a plurality of sub-time periods in the target time period; The electric meter data of the target water pump in the target time period includes the average power consumption of the target water pump in multiple sub-time periods in the target time period; The water flow data in the target time period obtained by combining the electric meter data of the target water pump and the electricity-to-water coefficient include: Substitute the average power consumption of the target water pump in multiple sub-time periods within the target time period and the average power-to-water coefficient into the power-to-water formula to obtain the water flow in multiple sub-time periods within the target time period.

6. The water flow measurement method according to claim 4, characterized in that: The temperature data within the target time period includes the average temperature within the target time period; The humidity data in the target time period includes the average humidity in the target time period; The water quality data during the target time period include the average water quality during the target time period; The electricity-to-water conversion coefficient in the target time period includes the average electricity-to-water conversion coefficient in the target time period; The electric meter data of the target water pump in the target time period includes the average power consumption of the target water pump in the target time period; The water flow data in the target time period obtained by combining the electric meter data of the target water pump and the electricity-to-water coefficient include: Substitute the average power consumption of the target water pump within the target time period and the average electricity-to-water coefficient into the electricity-to-water formula to obtain the water flow within the target time period.

7. The water flow measurement method according to claim 4, characterized in that: The temperature data within the target time period includes the instantaneous temperature at each moment within the target time period; The humidity data within the target time period includes the instantaneous humidity at each moment within the target time period; The water quality data within the target time period includes the instantaneous water quality at each moment within the target time period; The electricity-to-water coefficient within the target time period includes the instantaneous electricity-to-water coefficient at each moment within the target time period; The electric meter data of the target water pump in the target time period includes the instantaneous power of the target water pump at each moment in the target time period; The water flow data within the target time period includes the instantaneous water flow rate at each moment within the target time period; The water flow data in the target time period obtained by combining the electric meter data of the target water pump and the electricity-to-water coefficient include: According to the instantaneous electricity-to-water coefficient and the instantaneous power of the target water pump at each moment in the target time period, the instantaneous water flow rate at each moment in the target time period is obtained; The instantaneous water flow rate at each moment in the target time period is integrated to obtain the water flow rate in the target time period.

8. The water flow measurement method according to claim 5 or 6, characterized in that: The formula for converting electricity to water is: WD=CD×Ed Among them, CD is the hydropower conversion coefficient, the unit is cubic meter per kilowatt-hour (m 3 / kWh, WD is the water output in a certain period of time, in cubic meters (m 3 ), Ed is the electricity consumption in a certain period of time, in kilowatt-hours (kWh).

9. A water flow metering system, characterized in that: include: Water pump; A temperature and humidity sensor is installed on the water pump and is used to detect the temperature and humidity of the environment around the water pump; A water quality sensor is installed on the water pump and is used to detect the water quality of the environment around the water pump; An electric meter, which is used to detect the power consumption of the water pump; The server is equipped with a water flow model and is used to obtain data from temperature and humidity sensors, water quality sensors and electric meters and input the data into the water flow model to obtain the electricity-to-water coefficient, and is used to substitute the electricity-to-water coefficient and the power consumption read by the electric meter into the electricity-to-water formula to obtain the predicted water flow.

10. The water flow metering system according to claim 9, characterized in that: The water flow metering system also includes a data terminal, which is electrically connected to the server and is used to input instructions for obtaining sample data and sample labels to the server.

Images