A real-time control method and system based on high-voltage electric water pump of power plant

Abstract

The application provides a real-time control method and system based on a high-voltage electric water pump of a power plant. The method comprises the following steps: obtaining historical failure time information of a reference water pump and historical output power information corresponding to the historical failure time information; determining sampling time period information of a target water pump based on the historical failure time information; determining a plurality of measured output power information of the target water pump based on the sampling time period information; and generating failure prediction result information based on the plurality of measured output power information. The application can accurately predict the failure time period, provide a valuable early warning window for the maintenance of the high-voltage electric water pump of the power plant, and enable the operation and maintenance personnel to develop and implement a targeted treatment scheme before the actual failure occurs, thereby changing passive repair to active prevention, and greatly improving the operation reliability and safety.

Description

Technical Field

[0001] This application relates to the field of intelligent detection technology, specifically to a real-time control method and system based on a high-pressure electric water pump in a power plant. Background Technology

[0002] High-pressure electric water pumps play a crucial dual role in power plants, serving as both startup safeguards and emergency backups. They are the sole power source for establishing water circulation during unit startup and the "last line of defense" ensuring boiler safety in case of steam-driven feedwater pump failure. They also bear the important responsibility of providing cooling media to core equipment such as generators and turbines. By adopting doubly-fed variable-speed motors, high-pressure electric water pumps not only achieve significant energy savings, but their speed control devices also exhibit remarkable economic efficiency because they only need to handle the slip power of the rotor circuit. This completely eliminates valve throttling losses at the source, improving system operating efficiency.

[0003] Currently, high-pressure electric water pumps are typically maintained on a regular basis. However, problems often only become apparent after the pump has deteriorated to a certain extent, lacking early warning capabilities and exhibiting low reliability. Further improvements are needed. Summary of the Invention

[0004] The embodiments of this application aim to at least solve one of the technical problems existing in the prior art, and provide a real-time control method and system based on a high-pressure electric water pump in a power plant.

[0005] On one hand, embodiments of this application provide a real-time control method based on a high-pressure electric water pump in a power plant, the method comprising: Obtain historical fault time information of the reference water pump and historical output power information corresponding to the historical fault time information; Based on historical fault information, the sampling time period information of the target water pump is determined; Based on the sampling time period information, multiple measured output power information of the target water pump are determined; Based on multiple measured output power information, fault prediction results are generated.

[0006] On the other hand, embodiments of this application provide a real-time control system based on a high-pressure electric water pump in a power plant, the system comprising: Historical Fault Time Information Acquisition Module: Used to acquire historical fault time information of the reference water pump and historical output power information corresponding to the historical fault time information; Sampling time period information determination module: used to determine the sampling time period information of the target water pump based on historical fault time information; Measured output power information determination module: used to determine multiple measured output power information of the target water pump based on the sampling time period information; Fault prediction result information generation module: used to generate fault prediction result information based on multiple measured output power information.

[0007] On the other hand, embodiments of this application also provide a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described above.

[0008] On the other hand, embodiments of this application also provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described above.

[0009] The real-time control method and system based on high-voltage electric water pumps in power plants provided in this application embodiment allows the terminal equipment to first acquire historical fault time information and corresponding historical output power information of a reference water pump. Then, based on the historical fault time information, it quickly determines the sampling time period information of the target water pump. Based on the sampling time period information, it effectively determines multiple measured output power information of the target water pump. Finally, based on the multiple measured output power information, it accurately generates fault prediction result information. This enables the system to predict the fault occurrence time in advance, providing maintenance personnel with sufficient response time to take preventive measures in advance, reduce the impact of faults from the source, effectively improve equipment operational reliability, and to a certain extent solve the current problem of low reliability. Attached Figure Description

[0010] Figure 1 This is a flowchart illustrating a real-time control method based on a high-pressure electric water pump in a power plant, according to an embodiment of this application. Figure 2 This is a flowchart illustrating step S200 in a real-time control method based on a high-voltage electric water pump in a power plant, according to an embodiment of this application. Figure 3 This is a flowchart illustrating the process before step S220 in a real-time control method based on a high-voltage electric water pump in a power plant, according to an embodiment of this application. Figure 4 This is a flowchart illustrating step S400 in a real-time control method based on a high-voltage electric water pump in a power plant, according to an embodiment of this application. Figure 5 This is a schematic diagram of the first process after step S400 in a real-time control method based on a high-pressure electric water pump in a power plant according to an embodiment of this application. Figure 6 This is a schematic diagram of the second process after step S400 in a real-time control method based on a high-voltage electric water pump in a power plant according to an embodiment of this application. Figure 7This is a block diagram of a real-time control system based on a high-pressure electric water pump in a power plant, according to an embodiment of this application. Figure 8 This is a schematic diagram of a terminal device according to an embodiment of this application. Detailed Implementation

[0011] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0012] In the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0013] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0014] To illustrate the technical solution described in this application, specific embodiments are provided below.

[0015] Please see Figure 1 , Figure 1 This is a flowchart illustrating a real-time control method for a high-pressure electric water pump in a power plant, as provided in an embodiment of this application. In this embodiment, the execution subject of the real-time control method is a terminal device. It is understood that the types of terminal devices include, but are not limited to, tablet computers, laptops, Ultra-Mobile Personal Computers (UMPCs), netbooks, Personal Digital Assistants (PDAs), etc., and this embodiment of the application does not impose any restrictions on the specific type of terminal device.

[0016] Please see Figure 1 The real-time control method provided in this application includes, but is not limited to, the following steps: In S100, the historical fault time information of the reference water pump and the historical output power information corresponding to the historical fault time information are obtained.

[0017] Specifically, the terminal equipment can first obtain the historical fault time information of the reference water pump and the corresponding historical output power information. The reference water pump can be a water pump of the same model and operating conditions as the high-voltage electric water pump of the power plant to be monitored. The historical fault time information describes the time when the reference water pump failed in the past, and the historical fault time information can be identified by the cumulative running time when the fault occurred. The historical output power information describes the output power of the reference water pump at the historical fault time. It should be noted that when the high-voltage electric water pump of the power plant fails, the output power will drop and fall below the normal operating level.

[0018] In S200, the sampling time period information of the target water pump is determined based on historical fault time information.

[0019] Specifically, after the terminal device acquires historical output power information, it can quickly determine the sampling time period of the target water pump based on the historical fault time information, thereby effectively locating the time period during which the target water pump is most likely to fail. The target water pump is used to describe the high-voltage electric water pump of the power plant to be monitored.

[0020] In some possible implementations, to quickly determine the sampling time period information of the target water pump, please refer to [link / reference needed]. Figure 2 Step S200 includes, but is not limited to, the following steps: In S210, the predicted fault time information is determined based on the historical fault time information.

[0021] Specifically, after the terminal device obtains historical output power information, the terminal device can determine the predicted fault time information based on the historical fault time information. For example, when the historical fault time information is the 8.5th year of cumulative operation, the predicted fault time information is also the 8.5th year of cumulative operation.

[0022] In S220, the start sampling time information is determined based on the predicted fault time information and the preset associated duration information, and the end sampling time information is determined based on the predicted fault time information and the associated duration information.

[0023] Specifically, after the terminal device determines the predicted fault time information, it can effectively determine the start sampling time information based on the predicted fault time information and the preset associated duration information. At the same time, it can effectively determine the end sampling time information based on the predicted fault time information and the associated duration information. The start sampling time information is earlier than the predicted fault time information, and the time interval between the start sampling time information and the predicted fault time information is the associated duration information. The value of the associated duration information is a preset value, such as 15 days.

[0024] In S230, the sampling time period information is determined based on the start sampling time information and the end sampling time information.

[0025] Specifically, after the terminal device determines the termination sampling time information, the terminal device can quickly sample the time period information based on the start sampling time information and the termination sampling time information. The sampling time period information is used to describe the time period constructed by the start time information and the termination sampling time information.

[0026] In some possible implementations, to improve the accuracy of fault prediction, please refer to [link / reference]. Figure 3 Prior to step S220, the method further includes, but is not limited to, the following steps: In S221, the cumulative number of failures of the target water pump is obtained.

[0027] Specifically, before the terminal device determines the start sampling time information and the end sampling time information, the terminal device can obtain the cumulative number of failures of the target water pump. The cumulative number of failures information can be the total number of failures that have occurred during the operation of the target water pump.

[0028] In S222, if the cumulative number of faults is greater than the preset fault count threshold, the associated duration information is determined to be the first duration information; otherwise, the associated duration information is determined to be the second duration information.

[0029] Specifically, if the cumulative number of faults is greater than a preset fault count threshold, the terminal device can determine the associated duration information as the first duration information; otherwise, it determines the associated duration information as the second duration information. The fault count threshold is a preset value, such as 10 or 15 times. Both the first duration information and the second duration information are preset values, and the first duration information is greater than the second duration information. For example, the first duration information can be 15 days, and the second duration information can be 7 days.

[0030] In S300, based on the sampling time period information, multiple measured output power information of the target water pump are determined.

[0031] Specifically, after the terminal device determines the sampling time period information, it can quickly determine multiple measured output power information of the target water pump based on the sampling time period information, thereby quickly determining the specific output power of the target water pump during the time period when it is most likely to fail.

[0032] In some possible implementations, if the sampling period involves future times, the measured output power information can be extrapolated using the trends in historical data. For example, assuming the output power has decreased by 2% in the past fifteen days, the terminal device can predict that it will continue to decrease at that rate in the next fifteen days, thereby supplementing the missing output power information.

[0033] In some possible implementations, to further improve the accuracy of fault prediction, after step S300, the method may include, but is not limited to, the following steps: The sampling time period information is divided proportionally to generate the first time period information, the second time period information, and the third time period information.

[0034] Specifically, after the terminal device determines multiple measured output power information, the terminal device can divide the sampling time period information into equal proportions to effectively generate first time period information, second time period information, and third time period information, wherein the duration of the first time period information, second time period information, and third time period information is equal.

[0035] In the S400, fault prediction results are generated based on multiple measured output power information.

[0036] Specifically, after the terminal device determines multiple measured output power information, the terminal device can accurately generate fault prediction result information based on the multiple measured output power information. The fault prediction result information includes high probability fault information or low probability fault information. High probability fault information indicates that the target water pump is likely to fail within the sampling time period, while low probability fault information indicates that the target water pump is unlikely to fail within the sampling time period.

[0037] For some possible implementations, please refer to [link to relevant documentation] for accurate generation of fault prediction results. Figure 4 Step S400 includes, but is not limited to, the following steps: In S410, the first average output power information is generated based on multiple measured output power information corresponding to the first time period information.

[0038] Specifically, after the terminal device divides the sampling time period information into equal proportions, the terminal device can effectively generate the first average output power information based on the average value of multiple measured output power information corresponding to the first time period information.

[0039] In S420, a second average output power information is generated based on multiple measured output power information corresponding to the second time period information.

[0040] Specifically, after the terminal device generates the first average output power information, the terminal device can effectively generate the second average output power information based on the average value of multiple measured output power information corresponding to the second time period information.

[0041] In S430, a third average output power information is generated based on multiple measured output power information corresponding to the third time period information.

[0042] Specifically, after the terminal device generates the second average output power information, the terminal device can effectively generate the third average output power information based on the average value of multiple measured output power information corresponding to the third time period information.

[0043] In S440, the first output power descent ratio information is determined based on the quotient of the second average output power information divided by the first average output power information.

[0044] Specifically, after the terminal device generates the third average output power information, the terminal device can effectively determine the first output power descent ratio information based on the quotient of the second average output power information divided by the first average output power information.

[0045] In S450, the second output power descent ratio information is determined based on the quotient of the third average output power information divided by the second average output power information.

[0046] Specifically, after the terminal device determines the first output power descent ratio information, the terminal device can effectively determine the second output power descent ratio information based on the quotient of the third average output power information divided by the second average output power information.

[0047] In S460, the drop ratio difference information is generated based on the difference between the first output power drop ratio information and the second output power drop ratio information.

[0048] Specifically, after the terminal device determines the second output power descent ratio information, the terminal device can effectively generate descent ratio difference information by subtracting the second output power descent ratio information from the first output power descent ratio information.

[0049] In S470, the descent ratio difference information is compared with the preset phase difference threshold information.

[0050] Specifically, after the terminal device generates the drop ratio difference information, the terminal device can compare the drop ratio difference information with the preset phase difference threshold information, where the phase difference threshold information can be a preset value.

[0051] In S480, if the difference in the drop ratio is greater than the difference threshold, the fault prediction result is determined to be a high-probability fault; otherwise, the fault prediction result is determined to be a low-probability fault.

[0052] Specifically, if the difference in the drop ratio is greater than the difference threshold, it indicates that the output power has dropped significantly, so the terminal device can determine that the fault prediction result is a high-probability fault. Otherwise, it indicates that the output power has not dropped significantly, so the terminal device can determine that the fault prediction result is a low-probability fault.

[0053] In some possible implementations, to issue an early warning before a failure occurs, please refer to [link / reference needed]. Figure 5 If the fault prediction result is determined to be a high-probability fault, then after step S400, the method further includes, but is not limited to, the following steps: In S500, warning time information is generated based on the predicted fault time information and the preset warning duration information.

[0054] Specifically, after the terminal device generates the fault prediction result information, the terminal device can effectively generate warning time information based on the predicted fault time information and the preset warning duration information. The warning time information is earlier than the predicted fault time information, and the time interval between the warning time information and the predicted fault time information is the warning duration information. The warning duration information is a preset value, such as 3 days.

[0055] In S510, the first fault alert instruction is generated based on the warning time information.

[0056] Specifically, after the terminal device generates the warning time information, the terminal device can generate a first fault reminder instruction based on the warning time information. The first fault reminder instruction is used to remind maintenance personnel of an impending fault at the warning time.

[0057] For a wider range of possible implementations, please refer to [link / reference]. Figure 6 After step S400, the method further includes, but is not limited to, the following steps: In S610, the occurrence time information corresponding to peak electricity consumption events is obtained.

[0058] Specifically, after the terminal device generates fault prediction result information, the terminal device can obtain the occurrence time information corresponding to the peak power consumption event, where the occurrence time information corresponding to the peak power consumption event is a preset value.

[0059] In S620, it is determined whether the warning time information is later than the occurrence time information.

[0060] Specifically, after the terminal device obtains the occurrence time information corresponding to the peak power consumption event, the terminal device can determine whether the warning time information is later than the occurrence time information.

[0061] In S630, if the warning time information is later than the occurrence time information, a second fault reminder command information is sent.

[0062] Specifically, if the warning time information is later than the occurrence time information, a second fault reminder instruction is sent to avoid sudden faults during peak power consumption events.

[0063] The implementation principle of the real-time control method for high-voltage electric water pumps in power plants according to this application embodiment is as follows: The terminal equipment can first obtain the historical fault time information of the reference water pump and the historical output power information corresponding to the historical fault time information. Then, based on the historical fault time information, it quickly determines the sampling time period information of the target water pump. Based on the sampling time period information, it effectively determines multiple measured output power information of the target water pump. Finally, based on the multiple measured output power information, it accurately generates fault prediction result information. This enables the operation and maintenance personnel to gain sufficient response time by predicting the fault occurrence time in advance, so as to take preventive measures in advance, reduce the impact of faults from the source, and effectively improve the reliability of equipment operation.

[0064] It should be noted that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0065] Embodiments of this application also provide a real-time control system based on a high-pressure electric water pump in a power plant. For ease of explanation, only the parts relevant to this application are shown, such as... Figure 7 As shown, the system 70 includes: Historical fault time information acquisition module 71: used to acquire historical fault time information of the reference water pump and historical output power information corresponding to the historical fault time information; Sampling time period information determination module 72: used to determine the sampling time period information of the target water pump based on historical fault time information; Module 73 for determining measured output power information: Based on the sampling time period information, it determines multiple measured output power information of the target water pump; Fault prediction result information generation module 74: used to generate fault prediction result information based on multiple measured output power information.

[0066] Optionally, the above sampling time period information determination module 72 includes: The predictive fault timing information determination submodule is used to determine the predicted fault timing information based on historical fault timing information. The sampling time information determination submodule is used to determine the start sampling time information based on the predicted fault time information and the preset associated duration information, and to determine the end sampling time information based on the predicted fault time information and the associated duration information; wherein, the start sampling time information is earlier than the predicted fault time information, and the end sampling time information is later than the predicted fault time information. The sampling time period information determination submodule is used to determine the sampling time period information based on the start sampling time information and the end sampling time information. The sampling time period information describes the time period constructed by using the start sampling time information as the start sampling time information and the end sampling time information as the end sampling time information.

[0067] Accordingly, the system 70 also includes: Cumulative Failure Count Information Acquisition Module: Used to acquire the cumulative failure count information of the target water pump; Duration information determination module: If the cumulative number of faults is greater than the preset fault number threshold, the associated duration information is determined as the first duration information; otherwise, the associated duration information is determined as the second duration information, wherein the first duration information is greater than the second duration information.

[0068] Optionally, the system 70 also includes: Time period information generation module: used to divide the sampled time period information into equal proportions to generate first time period information, second time period information, and third time period information; wherein the duration of the first time period information, second time period information, and third time period information is equal; Accordingly, the fault prediction result information includes high-probability fault information or low-probability fault information; the fault prediction result information generation module 74 includes: First average output power information generation submodule: used to generate first average output power information based on multiple measured output power information corresponding to the first time period information; Second average output power information generation submodule: used to generate second average output power information based on multiple measured output power information corresponding to the second time period information; The third average output power information generation submodule is used to generate third average output power information based on multiple measured output power information corresponding to the third time period information. First output power descent ratio information determination submodule: used to determine the first output power descent ratio information based on the quotient of the second average output power information divided by the first average output power information; Second output power descent ratio information determination submodule: used to determine the second output power descent ratio information based on the quotient of the third average output power information divided by the second average output power information; The descent ratio difference information generation submodule is used to generate descent ratio difference information based on the difference between the first output power descent ratio information and the second output power descent ratio information. The descent ratio difference information comparison submodule is used to compare the descent ratio difference information with the preset phase difference threshold information. The high-probability fault information determination submodule is used to determine the fault prediction result as high-probability fault information if the difference in the drop ratio is greater than the difference threshold information, and otherwise determine the fault prediction result as low-probability fault information.

[0069] Optionally, the system 70 also includes: Warning time information generation module: used to generate warning time information based on the predicted fault time information and the preset warning duration information; wherein, the warning time information is earlier than the predicted fault time information; First fault alert instruction information generation module: used to generate first fault alert instruction information based on the warning time information.

[0070] Optionally, the system 70 also includes: The occurrence time information acquisition module is used to acquire the occurrence time information corresponding to peak electricity consumption events; Warning time information judgment module: used to determine whether the warning time information is later than the occurrence time information; The second fault alert instruction information sending module is used to send a second fault alert instruction information if the warning time information is later than the occurrence time information.

[0071] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0072] This application also provides a terminal device, such as... Figure 8 As shown, the terminal device 80 in this embodiment includes: a processor 81, a memory 82, and a computer program 83 stored in the memory 82 and executable on the processor 81. When the processor 81 executes the computer program 83, it implements the steps described in the real-time control method embodiment above, for example... Figure 1Steps S100 to S400 are shown; or, when processor 81 executes computer program 83, it implements the functions of each module in the above-described device, for example... Figure 7 The functions of modules 71 to 74 are shown.

[0073] The terminal device 80 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device, and includes, but is not limited to, a processor 81 and a memory 82. Those skilled in the art will understand that... Figure 8 This is merely an example of terminal device 80 and does not constitute a limitation on terminal device 80. It may include more or fewer components than shown, or combine certain components, or different components. For example, terminal device 80 may also include input / output devices, network access devices, buses, etc.

[0074] The processor 81 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.; the general-purpose processor can be a microprocessor or any conventional processor, etc.

[0075] The memory 82 can be an internal storage unit of the terminal device 80, such as a hard disk or memory of the terminal device 80. The memory 82 can also be an external storage device of the terminal device 80, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the terminal device 80. Furthermore, the memory 82 can include both internal storage units and external storage devices of the terminal device 80. The memory 82 can also store computer program 83 and other programs and data required by the terminal device 80. The memory 82 can also be used to temporarily store data that has been output or will be output.

[0076] One embodiment of this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can include any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0077] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the methods, principles and structures of this application should be covered within the scope of protection of this application.

Claims

1. A real-time control method based on a high-pressure electric water pump in a power plant, characterized in that, The method includes: Obtain historical fault time information of the reference water pump and historical output power information corresponding to the historical fault time information; Based on historical fault information, the sampling time period information of the target water pump is determined; Based on the sampling time period information, multiple measured output power information of the target water pump are determined; Based on multiple measured output power information, fault prediction results are generated.

2. The method according to claim 1, characterized in that, The determination of the sampling time period information for the target water pump based on historical fault time information includes: Based on historical failure time information, determine the predicted failure time information; Based on the predicted fault time information and the preset associated duration information, the start sampling time information is determined, and based on the predicted fault time information and the associated duration information, the end sampling time information is determined; wherein, the start sampling time information is earlier than the predicted fault time information, and the end sampling time information is later than the predicted fault time information. Based on the start sampling time information and the end sampling time information, the sampling time period information is determined; wherein, the sampling time period information is used to describe the time period constructed by the start time information and the end time information. Accordingly, before determining the start sampling time information based on the predicted fault time information and the preset associated duration information, and before determining the end sampling time information based on the predicted fault time information and the associated duration information, the method further includes: Obtain the cumulative number of failures of the target water pump; If the cumulative number of faults is greater than a preset fault count threshold, then the associated duration information is determined to be the first duration information; otherwise, the associated duration information is determined to be the second duration information; wherein, the first duration information is greater than the second duration information.

3. The method according to claim 2, characterized in that, The method further includes, after determining multiple measured output power information of the target water pump based on the sampling time period information, dividing the sampling time period information into equal proportions to generate first time period information, second time period information, and third time period information; wherein the duration of the first time period information, the second time period information, and the third time period information is equal. Accordingly, the fault prediction result information includes high-probability fault information or low-probability fault information; the step of generating fault prediction result information based on multiple measured output power information includes: Based on the multiple measured output power information corresponding to the first time period information, generate the first average output power information; Based on the multiple measured output power information corresponding to the second time period information, a second average output power information is generated; Based on the multiple measured output power information corresponding to the third time period information, a third average output power information is generated; The first output power descent ratio information is determined based on the quotient of the second average output power information divided by the first average output power information. The second output power descent ratio information is determined based on the quotient of the third average output power information divided by the second average output power information. Based on the difference between the first output power descent ratio information and the second output power descent ratio information, descent ratio difference information is generated; Compare the decrease ratio difference information with the preset phase difference threshold information; If the difference in the descent ratio is greater than the difference threshold, the fault prediction result is determined to be a high-probability fault; otherwise, the fault prediction result is determined to be a low-probability fault.

4. The method according to claim 3, characterized in that, If the fault prediction result information is determined to be high-probability fault information, then after generating the fault prediction result information based on multiple measured output power information, the method further includes: Based on the predicted fault time information and the preset warning duration information, warning time information is generated; wherein, the warning time information is earlier than the predicted fault time information; Based on the warning time information, a first fault reminder instruction is generated.

5. The method according to claim 4, characterized in that, The method further includes, after generating fault prediction result information based on multiple measured output power information, obtaining the occurrence time information corresponding to the peak power consumption event; Determine whether the warning time information is later than the occurrence time information; If the warning time information is later than the occurrence time information, a second fault reminder instruction information is sent.

6. A real-time control system based on a high-pressure electric water pump in a power plant, characterized in that, The system includes: Historical Fault Time Information Acquisition Module: Used to acquire historical fault time information of the reference water pump and historical output power information corresponding to the historical fault time information; Sampling time period information determination module: used to determine the sampling time period information of the target water pump based on historical fault time information; Measured output power information determination module: used to determine multiple measured output power information of the target water pump based on the sampling time period information; Fault prediction result information generation module: used to generate fault prediction result information based on multiple measured output power information.

7. The system according to claim 6, characterized in that, The sampling time period information determination module includes: The predictive fault timing information determination submodule is used to determine the predicted fault timing information based on historical fault timing information. The sampling time information determination submodule is used to determine the start sampling time information based on the predicted fault time information and the preset associated duration information, and to determine the end sampling time information based on the predicted fault time information and the associated duration information; wherein the start sampling time information is earlier than the predicted fault time information, and the end sampling time information is later than the predicted fault time information. The sampling time period information determination submodule is used to determine the sampling time period information based on the start sampling time information and the end sampling time information; wherein, the sampling time period information is used to describe the time period constructed by the start time information and the end time information.

8. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 5.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 5.

Images