Water pump intelligent data analysis system and analysis method

Abstract

The invention relates to a water pump intelligent data analysis system and analysis method. The system comprises a water pump, a distribution box, an intelligent data analyzer provided with a data analysis module and a digital display meter, a water pump inlet pressure sensor and a water pump outlet pressure sensor. The water pump inlet pressure sensor and the water pump outlet pressure sensor respectively monitor inlet pressure signals and outlet pressure signals in real time and transmit the pressure signals to the data analysis module, and the data analysis module calculates target parameters of the water pump at different rotating speeds and outputs the target parameters to the digital display meter for real-time display. On the premise that a flowmeter does not need to be assembled, the target parameters of the water pump under various rotating speed working conditions can be accurately obtained, the equipment cost is effectively reduced, and by means of the parameter identification technology, the calculated target parameters of the water pump under different rotating speeds have high precision and are highly matched with the actual operation condition; and firm and reliable data support is provided for the links of performance evaluation, fault diagnosis, overhaul and maintenance, energy-saving optimization control and the like of the water pump.

Description

Technical Field

[0001] The present invention relates to the technical field of water pump monitoring and data analysis, and particularly to a water pump intelligent data analysis system and an analysis method. Background Technique

[0002] In a central air conditioning system, the flow rate data of a water pump is a key parameter for analyzing the system performance and cooling capacity. Usually, the acquisition of the flow rate depends on a flow meter, but the flow meter has many limitations. First of all, the cost of the flow meter is relatively high and the installation cost is large, which to a certain extent limits its wide application in the system. Secondly, the data measured by the flow meter is easily interfered by external conditions, resulting in large data fluctuations and poor stability. In addition, due to cost and installation difficulty considerations, the flow meter is usually only installed on the main pipeline, and the pump branch often lacks flow rate data acquisition. This makes it difficult to analyze the operating performance of the water pump, and further affects the accurate implementation of the overhaul, maintenance and energy-saving control of the water pump.

[0003] In the prior art, there is a lack of a method that can accurately obtain the flow rate, power and efficiency data of a water pump at different speeds without relying on a flow meter, and upload these data to a host computer for analysis. Therefore, it is necessary to design a water pump intelligent data analyzer and an analysis method to solve the above technical problems. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a water pump intelligent data analysis system and an analysis method in view of the above-mentioned deficiencies of the prior art.

[0005] The technical solution for the present invention to solve the above technical problems is as follows: A water pump intelligent data analysis system includes a water pump, a distribution box, an intelligent data analyzer configured with a data analysis module and a digital display, a water pump inlet pressure sensor and a water pump outlet pressure sensor;

[0006] The distribution box is electrically connected to the water pump and the intelligent data analyzer respectively, and provides power for the water pump and the intelligent data analyzer;

[0007] The water pump inlet pressure sensor is used to monitor the pressure change at the water pump inlet in real time, and transmit the monitored inlet pressure signal to the data analysis module;

[0008] The water pump outlet pressure sensor is used to monitor the pressure change at the water pump outlet in real time, and transmit the monitored outlet pressure signal to the data analysis module;

[0009] The digital display is used to input the sample data of the water pump and also used to display the target parameters calculated by the data analysis module;

[0010] The data analysis module inputs the sample data, the inlet pressure signal, the outlet pressure signal, and the collected real-time working parameters of the water pump into a built-in calculation model, calculates the target parameters of the water pump at different rotational speeds, and outputs them to the digital display meter for real-time display;

[0011] Among them, the target parameters at least include the flow rate, efficiency, and power of the water pump.

[0012] Based on the above technical solution, the present invention can also be improved as follows:

[0013] Further: The specific implementation of the data analysis module inputting the inlet pressure signal, the outlet pressure signal, and the real-time working parameters collected by the water pump into the calculation model to calculate the target parameters of the water pump at different rotational speeds is as follows:

[0014] The parameter identification model in the data analysis module calculates the model coefficients of the calculation model according to the sample data of the water pump input from the digital display meter;

[0015] The data analysis module calculates the real-time head H of the water pump according to the inlet pressure signal and the outlet pressure signal;

[0016] The data analysis module inputs the real-time working parameters and the model coefficients into the calculation model, and combines the head H and the real-time working parameters to calculate the target parameters of the water pump at different rotational speeds;

[0017] Among them, the sample data includes sample flow rate, sample frequency, sample head, and sample power, and the working parameters include the ratio w of the operating frequency to the power frequency.

[0018] Further: The specific implementation of the data analysis module calculating the model coefficients of the calculation model according to the sample data of the water pump is as follows:

[0019] The data analysis module uses the Levenberg-Marquardt optimization algorithm combined with the orthogonal distance regression method to perform the least squares calculation according to the sample data of the water pump, and obtains the model coefficients of the calculation model.

[0020] Further: The calculation formula for the data analysis module to input the real-time working parameters and the model coefficients into the calculation model, and combine the head H and the real-time working parameters to calculate the real-time flow rate Q of the water pump at different rotational speeds is:

[0021]

[0022] Among them, H is the real-time head of the water pump, a, b, and c are the flow fitting model coefficients of the identification model respectively, and w is the ratio of the actual operating frequency of the water pump to the industrial frequency.

[0023] Furthermore: The data analysis module inputs the real-time working parameters and model coefficients into the calculation model, and combines the head H and real-time working parameters to calculate the formula for the efficiency η of the water pump at different rotational speeds as follows:

[0024]

[0025] Among them, Q is the flow rate of the water pump; j, k, and l are the efficiency fitting model coefficients of the identification model respectively; w is the ratio of the actual operating frequency of the water pump to the industrial frequency.

[0026] Furthermore: The data analysis module inputs the real-time working parameters and model coefficients into the calculation model, and combines the head H and real-time working parameters to calculate the formula for the power P of the water pump at different rotational speeds as follows:

[0027]

[0028] Among them, ρ is the fluid density, g is the acceleration due to gravity, H is the real-time head of the water pump; Q is the real-time flow rate of the water pump; η is the real-time efficiency of the water pump.

[0029] The present invention also provides a method for intelligent data analysis of a water pump, which uses the intelligent data analysis system of the water pump, and is characterized in that the method includes the following steps:

[0030] The water pump inlet pressure sensor and the water pump outlet pressure sensor respectively monitor the pressure changes at the inlet and outlet of the water pump in real time, and transmit the monitored inlet pressure signal and outlet pressure signal to the data analysis module;

[0031] Set and input the sample data of the water through the digital display meter;

[0032] The data analysis module inputs the sample data, the inlet pressure signal, the outlet pressure signal and the collected real-time working parameters of the water pump into the built-in calculation model, calculates the target parameters of the water pump at different rotational speeds, and outputs them to the digital display meter for real-time display;

[0033] Among them, the target parameters include the flow rate, efficiency and power of the water pump.

[0034] Further: The data analysis module inputs the sample data, the inlet pressure signal, and the outlet pressure signal, along with the collected real-time operating parameters of the water pump, into the calculation model, and calculates the target parameters of the water pump at different speeds. The specific steps are as follows:

[0035] The parameter identification model in the data analysis module calculates the model coefficients of the calculation model according to the sample data of the water pump input from the digital display meter;

[0036] The data analysis module calculates the real-time head H of the water pump according to the inlet pressure signal and the outlet pressure signal;

[0037] The data analysis module inputs the real-time operating parameters and model coefficients into the calculation model, and calculates the target parameters of the water pump at different speeds by combining the head H and the real-time operating parameters;

[0038] Among them, the sample data includes sample flow rate, sample frequency, sample head, and sample power, and the operating parameters include the ratio w of the operating frequency to the power frequency;

[0039] The formula for the data analysis module to input the real-time operating parameters and model coefficients into the calculation model, and calculate the target parameters of the water pump at different speeds by combining the head H and the real-time operating parameters is:

[0040]

[0041] Among them, H is the real-time head of the water pump, a, b, and c are the flow fitting model coefficients of the identification model respectively, w is the ratio of the actual operating frequency of the water pump to the power frequency, j, k, and l are the efficiency fitting model coefficients of the identification model respectively, ρ is the fluid density, g is the acceleration due to gravity, H is the real-time head of the water pump; Q is the real-time flow rate of the water pump; η is the real-time efficiency of the water pump, and P is the real-time power of the water pump.

[0042] The present invention also provides a computer-readable storage medium, which stores computer instructions for enabling a processor to implement the intelligent data analysis method of the water pump when executed.

[0043] The present invention also provides a water pump intelligent data analysis device, which includes:

[0044] At least one processor and a storage medium, and the storage medium is communicatively connected to the processor;

[0045] Among them, a computer program executable by the at least one processor is stored on the storage medium. The computer program is executed by the at least one processor so that the at least one processor can execute the intelligent data analysis method of the water pump.

[0046] The beneficial effects of the present invention are as follows: The intelligent data analysis system and method of the water pump of the present invention calculate the model coefficients of the built-in calculation model through sample data, and collect the pressure signals at the inlet and outlet of the water pump through the water pump inlet pressure sensor and the water pump outlet pressure sensor respectively. Then, the real-time working parameters of the water pump and the model coefficients are input into the built-in calculation model to calculate the target parameters of the water pump at different speeds. Without the need to install a flow meter, the target parameters of the water pump under various speed conditions can be accurately obtained, effectively reducing the equipment cost. With the help of parameter identification technology, the calculated target parameters of the water pump at different speeds have high accuracy and are highly consistent with the actual operation conditions; it can provide solid and reliable data support for the performance evaluation, fault diagnosis, maintenance, and energy-saving optimization control of the water pump, and help realize the refined management and efficient operation of the water pump equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a schematic structural diagram of the intelligent data analysis system of the water pump according to an embodiment of the present invention;

[0048] Figure 2 It is a schematic diagram of the fitting surface of the water pump head, frequency, and flow rate according to an embodiment of the invention;

[0049] Figure 3 It is a schematic diagram of the fitting surface of the water pump head, frequency, and flow rate according to an embodiment of the present invention;

[0050] Figure 4 It is a schematic diagram of the fitting curve of the water pump head and flow rate according to an embodiment of the present invention;

[0051] Figure 5 It is a schematic diagram of the fitting curve of the water pump head and flow rate according to another embodiment of the present invention;

[0052] Figure 6 It is a schematic diagram of the fitting curve of the water pump efficiency and flow rate according to an embodiment of the present invention;

[0053] Figure 7 It is a schematic diagram of the fitting curve of the water pump efficiency and flow rate according to another embodiment of the present invention.

[0054] Figure 8 It is a schematic flowchart of the intelligent data analysis method of the water pump according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0055] The principles and features of the present invention will be described below in conjunction with the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0056] As Figure 1 shown, a smart data analysis system for a water pump includes a water pump 1, a distribution box 2, a smart data analyzer 3 configured with a data analysis module 4 and a digital display 5, a water pump inlet pressure sensor 6, and a water pump outlet pressure sensor 7;

[0057] The distribution box 2 is electrically connected to the water pump 1 and the smart data analyzer 3 respectively, and provides power for the water pump 1 and the smart data analyzer 3;

[0058] The water pump inlet pressure sensor 6 is used to monitor the pressure change at the inlet of the water pump in real time, and transmit the monitored inlet pressure signal to the data analysis module 4;

[0059] The water pump outlet pressure sensor 7 is used to monitor the pressure change at the outlet of the water pump in real time, and transmit the monitored outlet pressure signal to the data analysis module 4;

[0060] The digital display 5 is used to input the sample data of the water pump 1 and also used to display the target parameters calculated by the data analysis module 4;

[0061] The data analysis module 4 inputs the sample data, the inlet pressure signal, the outlet pressure signal, and the real-time working parameters of the water pump 1 collected into a built-in calculation model, calculates the target parameters of the water pump 1 at different speeds, and outputs them to the digital display 5 for real-time display;

[0062] Among them, the target parameters at least include the flow rate, efficiency, and power of the water pump 1.

[0063] In one or more embodiments of the present invention, the data analysis module 4 inputs the sample data, the inlet pressure signal, the outlet pressure signal, and the real-time working parameters of the water pump 1 collected into the calculation model, and the steps of calculating the target parameters of the water pump 1 at different speeds are as follows:

[0064] The parameter identification model in the data analysis module 4 calculates the model coefficients of the calculation model according to the sample data of the water pump 1 input from the digital display 5;

[0065] The data analysis module 4 calculates the real-time head H of the water pump 1 according to the inlet pressure signal and the outlet pressure signal;

[0066] The data analysis module 4 inputs the real-time operating parameters and model coefficients into the calculation model, and calculates the target parameters of the water pump 1 at different speeds in combination with the head H and the real-time operating parameters;

[0067] Among them, the sample data includes sample flow rate, sample frequency, sample head, and sample power, and the operating parameters include the ratio w of the operating frequency to the power frequency.

[0068] In one or more embodiments of the present invention, the water pump inlet pressure sensor 6 is used to monitor the pressure change at the water pump inlet in real time, convert the monitored pressure signal into an electrical signal, and transmit it to the data analysis module 4; the water pump outlet pressure sensor 7 is used to monitor the pressure change at the water pump outlet in real time, convert the monitored pressure signal into an electrical signal, and transmit it to the data analysis module 4.

[0069] The intelligent data analyzer 3 is configured with an RS485 interface or an Ethernet interface, and can transmit data to the building automation system through the Modbus protocol or the TCP / IP protocol. At the same time, it can display data such as the flow rate, power, and efficiency of the water pump 1 at different speeds in the digital display meter 5. In the digital display meter 5, the (historical) sample data of the water pump 1 can be input, and the sample data is transmitted to the parameter identification model of the data analysis module 4 to calculate the model coefficients of the calculation model. Inputting the model coefficient values into the calculation model can calculate the flow rate, power, and efficiency data of the water pump 1 at different speeds, and transmit the data to the digital display meter 5 to display the flow rate, power, and efficiency data of the water pump 1 at different speeds in the digital display meter 5.

[0070] In one or more embodiments of the present invention, the specific implementation of the data analysis module 4 calculating the model coefficients of the calculation model according to the sample data of the water pump 1 is as follows:

[0071] The data analysis module 4 calculates the model coefficients of the calculation model using the least squares method according to the sample data of the water pump 1.

[0072] In practice, the model coefficients include the flow fitting model coefficients a, b, c and the efficiency fitting model coefficients j, k, l. In the embodiments of the present invention, the flow fitting model coefficients a, b, c are obtained by non-linear fitting through the Levenberg-Marquardt optimization algorithm combined with the orthogonal distance regression method, and the efficiency fitting model coefficients j, k, l are obtained by linear fitting through the Levenberg-Marquardt optimization algorithm combined with the orthogonal distance regression method. The specific fitting process is prior art and will not be elaborated here in detail.

[0073] It should be noted that in one or more embodiments of the present invention, sample data of the water pump 1 can be input into the digital display 5. The digital display 5 transmits the data to the parameter identification model in the data analysis module 4 to identify the flow fitting model coefficients a, b, and c. Sample data of the water pump 1 can be input into the digital display 5. The digital display 5 transmits the sample data to the parameter identification model in the data analysis module 4 to identify the efficiency fitting model coefficients j, k, and l of the efficiency. The head H of the water pump 1 can transmit the pressure signals at the inlet and outlet of the water pump 1 to the data analysis module 4 through the water pump inlet pressure sensor 6 and the water pump outlet pressure sensor 7, and then be calculated by the data analysis module 4. The specific calculation process is prior art and will not be elaborated here in detail.

[0074] In one or more embodiments of the present invention, the data analysis module 4 inputs the real-time working parameters and model coefficients into the calculation model, and combines the head H and the real-time working parameters to calculate the formula for the real-time flow rate Q of the water pump 1 at different rotational speeds as follows:

[0075]

[0076] Wherein, H is the real-time head of the water pump 1, a, b, and c are respectively the flow fitting model coefficients of the identification model, and w is the ratio of the actual operating frequency of the water pump 1 to the power frequency.

[0077] In one or more embodiments of the present invention, the data analysis module 4 inputs the real-time working parameters and model coefficients into the calculation model, and combines the head H and the real-time working parameters to calculate the formula for the efficiency η of the water pump 1 at different rotational speeds as follows:

[0078]

[0079] Wherein, Q is the flow rate of the water pump 1; j, k, and l are respectively the efficiency fitting model coefficients of the identification model; and w is the ratio of the actual operating frequency of the water pump to the power frequency.

[0080] In one or more embodiments of the present invention, the data analysis module 4 inputs the real-time working parameters and model coefficients into the calculation model, and combines the head H and the real-time working parameters to calculate the formula for the power P of the water pump 1 at different rotational speeds as follows:

[0081]

[0082] Wherein, ρ is the fluid density, g is the acceleration due to gravity, H is the real-time head of the water pump 1; Q is the real-time flow rate of the water pump 1; and η is the real-time efficiency of the water pump 1.

[0083] In a specific embodiment of the present invention, sample data of two water pumps, namely water pump one and water pump two, at different rotational speeds are substituted into the data analysis module 4, and the flow rate is calculated according to the flow rate calculation formula, and a fitted surface diagram of the head, frequency, and flow rate is drawn ( Figure 2 and Figure 3 ). By comparing the flow rate data calculated using this formula with the sample flow rate data, the average relative error of all frequencies of water pump one is calculated to be 4%, and the average relative error of all frequencies of water pump two is 4.75%, both within 5%, verifying the high precision and reliability of the present invention in water pump performance monitoring and data analysis.

[0084] In a specific embodiment of the present invention, sample data of water pump three and water pump four at different rotational speeds are substituted into the data analysis module 4, and the flow rate is calculated according to the flow rate calculation formula, and a fitted curve diagram of the water pump head and flow rate is drawn ( Figure 4 and Figure 5 ). By comparing the flow rate data calculated using this formula with the sample flow rate data, the average relative error of water pump three is calculated to be 3.6%, and the average relative error of water pump four is 1.14%, both within 5%; substituting the sample data of water pump three and water pump four into the data analysis module 4, the actual efficiency of the water pump is calculated, thereby deriving an efficiency calculation formula, and a fitted curve diagram of the water pump efficiency and flow rate is drawn ( Figure 6 and Figure 7 ). By comparing the efficiency data calculated using this formula with the sample efficiency data, the average relative error of water pump three is calculated to be 4.05%, and the average relative error of water pump four is 1.35%, both within 5%; based on the results of the above calculations, a power calculation formula can be derived. By comparing the power data calculated using this formula with the actual sample power data, the average relative error of water pump three is calculated to be 2.13%, and the average relative error of water pump four is 1.02%, both within 5%. This fully verifies the high precision and reliability of the present invention in calculating water pump flow rate, efficiency, and power data.

[0085] The present invention also provides a water pump intelligent data analysis method, which uses the above-mentioned water pump intelligent data analysis system, and is characterized in that the method includes the following steps:

[0086] S1: The water pump inlet pressure sensor 6 and the water pump outlet pressure sensor 7 respectively and real-time monitor the pressure changes at the inlet and outlet of the water pump, and transmit the monitored inlet pressure signal and outlet pressure signal to the data analysis module 4;

[0087] S2: Input the sample data of the water pump 1 through the digital display meter 5;

[0088] S3: The data analysis module 4 inputs the sample data, the inlet pressure signal, the outlet pressure signal, and the collected real-time operating parameters of the water pump 1 into a built-in calculation model, calculates the target parameters of the water pump 1 at different rotational speeds, and outputs them to the digital display 5 for real-time display;

[0089] Among them, the target parameters include the flow rate, efficiency, and power of the water pump 1.

[0090] In one or more embodiments of the present invention, the data analysis module 4 inputs the sample data, the inlet pressure signal, the outlet pressure signal, and the collected real-time operating parameters of the water pump 1 into the calculation model, and calculates the target parameters of the water pump 1 at different rotational speeds, specifically including the following steps:

[0091] The parameter identification model in the data analysis module 4 calculates the model coefficients of the calculation model according to the sample data of the water pump 1 input from the digital display 5;

[0092] The data analysis module 4 calculates the real-time head H of the water pump 1 according to the inlet pressure signal and the outlet pressure signal;

[0093] The data analysis module 4 inputs the real-time operating parameters and model coefficients into the calculation model, and calculates the target parameters of the water pump 1 at different rotational speeds in combination with the head H and the real-time operating parameters;

[0094] Among them, the sample data includes sample flow rate, sample frequency, sample head, and sample power, and the operating parameters include the ratio w of the operating frequency to the power frequency;

[0095] The formula for the data analysis module 4 to input the real-time operating parameters and model coefficients into the calculation model, and calculate the target parameters of the water pump 1 at different rotational speeds in combination with the head H and the real-time operating parameters is:

[0096]

[0097] Among them, H is the real-time head of the water pump 1, a, b, and c are the flow fitting model coefficients of the identification model respectively, w is the ratio of the actual operating frequency of the water pump 1 to the power frequency, j, k, and l are the efficiency fitting model coefficients of the identification model respectively, ρ is the fluid density, g is the acceleration due to gravity, H is the real-time head of the water pump 1; Q is the real-time flow rate of the water pump 1; η is the real-time efficiency of the water pump 1, and P is the real-time power of the water pump 1.

[0098] The present invention also provides a computer-readable storage medium storing computer instructions for causing a processor to implement the intelligent data analysis method for water pumps when executed.

[0099] The present invention also provides an intelligent data analysis device for water pumps, which includes:

[0100] at least one processor and a storage medium, the storage medium being communicatively connected to the processor;

[0101] wherein, a computer program executable by the at least one processor is stored on the storage medium, and the computer program is executed by the at least one processor so that the at least one processor can execute the intelligent data analysis method for water pumps.

[0102] For the intelligent data analysis system and method for water pumps of the present invention, the model coefficients of the built-in calculation model are calculated through sample data, and the pressure signals at the inlet and outlet of the water pump 1 are respectively collected by the water pump inlet pressure sensor 6 and the water pump outlet pressure sensor 7. Then, the real-time working parameters of the water pump 1 and the model coefficients are input into the built-in calculation model to calculate the target parameters of the water pump 1 at different rotational speeds. Without the need to install a flowmeter, the target parameters of the water pump 1 under various rotational speed conditions can be accurately obtained, effectively reducing the equipment cost. With the help of the parameter identification technology, the calculated target parameters of the water pump 1 at different rotational speeds have high accuracy and are highly consistent with the actual operation conditions; the device is equipped with a standardized general interface, and the collected data can be stably transmitted to the host computer system by means of wired or wireless communication technology; based on the flow rate, power, and efficiency data of the water pump at different rotational speeds calculated by this system, it can provide solid and reliable data support for the performance evaluation, fault diagnosis, maintenance, and energy-saving optimization control of the water pump, helping to achieve the refined management and efficient operation of the water pump equipment.

[0103] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection scope of the present invention.

Claims

1. A water pump intelligent data analysis system, characterized in that: It includes a water pump (1), a distribution box (2), a smart data analyzer (3) configured with a data analysis module (4) and a digital display meter (5), a water pump inlet pressure sensor (6), and a water pump outlet pressure sensor (7); The distribution box (2) is electrically connected to the water pump (1) and the smart data analyzer (3) respectively, and provides power for the water pump (1) and the smart data analyzer (3); The water pump inlet pressure sensor (6) is used to monitor the pressure change at the inlet of the water pump in real time, and transmit the monitored inlet pressure signal to the data analysis module (4); The water pump outlet pressure sensor (7) is used to monitor the pressure change at the outlet of the water pump in real time, and transmit the monitored outlet pressure signal to the data analysis module (4); The digital display meter (5) is used to input the sample data of the water pump (1), and is also used to display the target parameters calculated by the data analysis module (4); The data analysis module (4) inputs the sample data, the inlet pressure signal and the outlet pressure signal, together with the real-time working parameters of the water pump (1) collected, into a built-in calculation model, calculates the target parameters of the water pump (1) at different speeds, and outputs them to the digital display meter (5) for real-time display; Among them, the target parameters at least include the flow rate, efficiency and power of the water pump (1).

2. The intelligent data analysis system for water pumps according to claim 1, wherein: The specific implementation of the data analysis module (4) inputting the sample data, the inlet pressure signal and the outlet pressure signal, together with the real-time working parameters of the water pump (1) collected, into the calculation model to calculate the target parameters of the water pump (1) at different speeds is as follows: The parameter identification model in the data analysis module (4) calculates the model coefficients of the calculation model according to the sample data of the water pump (1) input from the digital display meter (5); The data analysis module (4) calculates the real-time head H of the water pump (1) according to the inlet pressure signal and the outlet pressure signal; The data analysis module (4) inputs the real-time working parameters and model coefficients into the calculation model, and calculates the target parameters of the water pump (1) at different speeds in combination with the head H and the real-time working parameters; Among them, the sample data includes sample flow rate, sample frequency, sample head and sample power, and the working parameters include the ratio w of the operating frequency to the power frequency.

3. The water pump intelligent data analysis system according to claim 2, wherein: The specific implementation of the data analysis module (4) calculating the model coefficients of the calculation model according to the sample data of the water pump (1) is as follows: The data analysis module (4) uses the Levenberg-Marquardt optimization algorithm combined with the orthogonal distance regression method to perform least squares calculation according to the sample data of the water pump (1) to obtain the model coefficients of the calculation model.

4. The water pump intelligent data analysis system according to claim 2, wherein: The formula for the data analysis module (4) to input the real-time working parameters and model coefficients into the calculation model, and calculate the real-time flow rate Q of the water pump (1) at different speeds in combination with the head H and the real-time working parameters is: Wherein, H is the real-time head of the water pump (1), a, b, and c are respectively the flow fitting model coefficients of the identification model, and w is the ratio of the actual operating frequency of the water pump (1) to the power frequency.

5. The intelligent data analysis system for a water pump according to claim 4, wherein: The data analysis module (4) inputs the real-time working parameters and model coefficients into the calculation model, and the calculation formula for the efficiency η of the water pump (1) at different rotational speeds in combination with the head H and the real-time working parameters is: Wherein, Q is the flow rate of the water pump (1); j, k, and l are respectively the efficiency fitting model coefficients of the identification model; and w is the ratio of the actual operating frequency of the water pump to the power frequency.

6. The intelligent data analysis system for water pumps according to claim 5, characterized in that: The data analysis module (4) inputs the real-time working parameters and model coefficients into the calculation model, and the calculation formula for the power P of the water pump (1) at different rotational speeds in combination with the head H and the real-time working parameters is: Wherein, ρ is the fluid density, g is the acceleration due to gravity, H is the real-time head of the water pump (1); Q is the real-time flow rate of the water pump (1); and η is the real-time efficiency of the water pump (1).

7. A method for intelligent data analysis of a water pump, which uses the water pump intelligent data analysis system described in any one of claims 1-6, characterized in that, The method includes the following steps: The water pump inlet pressure sensor (6) and the water pump outlet pressure sensor (7) respectively monitor the pressure changes at the inlet and outlet of the water pump in real time, and transmit the monitored inlet pressure signal and outlet pressure signal to the data analysis module (4); Input the sample data of the water pump (1) through the digital display meter (5); The data analysis module (4) inputs the sample data, the inlet pressure signal and the outlet pressure signal, together with the real-time working parameters of the water pump (1) collected, into the built-in calculation model, calculates the target parameters of the water pump (1) at different rotational speeds, and outputs them to the digital display meter (5) for real-time display; Wherein, the target parameters include the flow rate, efficiency, and power of the water pump (1).

8. The intelligent data analysis method of the water pump according to claim 7, characterized in that: The data analysis module (4) inputs the sample data, the inlet pressure signal and the outlet pressure signal, together with the real-time working parameters of the water pump (1) collected, into the calculation model, and calculates the target parameters of the water pump (1) at different rotational speeds, specifically including the following steps: The parameter identification model in the data analysis module (4) calculates the model coefficients of the calculation model according to the sample data of the water pump (1) input from the digital display meter (5); The data analysis module (4) calculates the real-time head H of the water pump (1) according to the inlet pressure signal and the outlet pressure signal; The data analysis module (4) inputs the real-time working parameters and model coefficients into the calculation model, and calculates the target parameters of the water pump (1) at different rotational speeds in combination with the head H and the real-time working parameters; Wherein, the sample data includes sample flow rate, sample frequency, sample head, and sample power, and the working parameters include the ratio w of the operating frequency to the power frequency; The data analysis module (4) inputs the real-time working parameters and model coefficients into the calculation model, and the calculation formula for the target parameters of the water pump (1) at different rotational speeds in combination with the head H and the real-time working parameters is: Wherein, H is the real-time head of the water pump (1), a, b, and c are respectively the flow fitting model coefficients of the identification model, w is the ratio of the actual operating frequency of the water pump (1) to the power frequency, j, k, and l are respectively the efficiency fitting model coefficients of the identification model, ρ is the fluid density, g is the acceleration due to gravity, H is the real-time head of the water pump (1); Q is the real-time flow rate of the water pump (1); η is the real-time efficiency of the water pump (1), and P is the real-time power of the water pump (1).

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a processor to implement the water pump intelligent data analysis method described in claim 7 or 8 when executed.

10. A water pump intelligent data analysis device, characterized in that: The water pump intelligent data analysis device includes: At least one processor and a storage medium, the storage medium being communicatively connected to the processor; Wherein, the storage medium stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the water pump intelligent data analysis method described in claim 7 or 8.

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