High and low frequency data processing method and system for on-line monitoring of nuclear power plant

Abstract

The invention provides a high and low frequency data processing method and system for on-line monitoring of a nuclear power plant. The method comprises the following steps: acquiring real-time data corresponding to a high frequency parameter of on-line monitoring of the nuclear power plant from a PI system at a first frequency; acquiring real-time data corresponding to the low-frequency parameter from the PI system at a second frequency; carrying out data transmission on the real-time data in a Json format, and storing the real-time data in the form of an SQL (Structured Query Language) database file; counting a preset maximum power value and a corresponding duration when the accumulative operation time is greater than or equal to a preset duration, and a preset maximum power value and a corresponding duration when the accumulative operation time is less than the preset duration; and outputting an overpower statistical curve. Through data structure setting of high and low frequency data, a storage format of result data output and design of automatic statistics of overpower, the problems of low data security and data processing efficiency and inaccurate statistical result of an existing PI system due to direct access of multiple application programs are solved.

Description

Technical Field

[0001] The present application belongs to the technical field of online monitoring of nuclear power plants, and specifically relates to a high- and low-frequency data processing method and system for online monitoring of nuclear power plants. Background Art

[0002] At present, various data in the operation of nuclear power plants are stored in the PI system (Plant Information System), which is a real-time data management system. On the one hand, nuclear power plants use multiple information systems and databases from different suppliers for different purposes. Since the versions of the PI systems of various nuclear power plants are different, the supported API interface forms are different, which brings inconvenience to other applications to obtain data in the PI system; on the other hand, multiple applications directly access the PI system, which will also bring certain risks to the data security of the PI system. In addition, when nuclear power plant operators perform rapid power increase operations after core power reduction, they need to accumulate the maximum power value of more than 72 hours of operation as a data reference. In the past, rough manual statistics were performed based on historical data, which was inefficient and the statistical results were not accurate enough. Summary of the invention

[0003] In view of this, the embodiments of the present application are committed to providing a method and system for processing high and low frequency data for online monitoring of nuclear power plants. By setting the data structure of high and low frequency data, the storage format of result data output, and the design of automatic statistics of overpower, the problems of data security, low data processing efficiency and inaccurate statistical results in the existing PI system due to direct access by multiple applications are solved.

[0004] The first aspect of the present application provides a method for processing high- and low-frequency data of online monitoring of a nuclear power plant, the method comprising: obtaining high-frequency parameters and low-frequency parameters in the data of online monitoring of the nuclear power plant; obtaining real-time data corresponding to the high-frequency parameters from a PI system at a first frequency; obtaining real-time data corresponding to the low-frequency parameters from the PI system at a second frequency, the first frequency being greater than the second frequency; transmitting the real-time data corresponding to the high-frequency parameters and the real-time data corresponding to the low-frequency parameters in Json format, storing the real-time data corresponding to the high-frequency parameters and the real-time data corresponding to the low-frequency parameters in the form of an SQL database file; counting the preset maximum power value and the corresponding time when the cumulative running time is greater than or equal to the preset time, and the preset maximum power value and the corresponding time when the cumulative running time is less than the preset time; outputting an over-power statistical curve, in which the preset maximum power value and the corresponding time when the cumulative running time is greater than or equal to the preset time, and the preset maximum power value and the corresponding time when the cumulative running time is less than the preset time are displayed in different colors.

[0005] In a specific embodiment of the present application, before counting the preset maximum power value and the corresponding time when the cumulative operating time is greater than or equal to the preset time, and the preset maximum power value and the corresponding time when the cumulative operating time is less than the preset time, the high and low frequency data processing method for online monitoring of the nuclear power plant also includes: obtaining the input type and power type selected by the user, wherein the input type includes automatic input and manual input, and the power type includes 30 days and 7 days; determining the preset maximum power value according to the input type.

[0006] In a specific embodiment of the present application, the high-frequency parameters include the measured data acquisition time, core power, the number of control rod group withdrawal steps, the core boron concentration, the source range measurement channel count rate, the intermediate range measurement channel count rate and the external detector current; the low-frequency parameters include the measured data acquisition time, the core cycle burnup depth, the average temperature of the first-loop coolant, the boration water injection amount, the boron dilution water injection amount and the concentration of the injected concentrated boron water.

[0007] In a specific embodiment of the present application, the method for processing high- and low-frequency data for online monitoring of a nuclear power plant also includes: updating the high-frequency parameters and low-frequency parameters in the online monitoring data of the nuclear power plant according to changes in real-time data corresponding to high-frequency parameters and real-time data corresponding to low-frequency parameters acquired at different acquisition times.

[0008] In a specific implementation of the present application, the preset duration is 72 hours.

[0009] In a specific embodiment of the present application, the preset maximum power value and the corresponding duration in the over-power statistical curve whose cumulative running time is greater than or equal to the preset duration are displayed in green, and the preset maximum power value and the corresponding duration whose cumulative running time is less than the preset duration are displayed in red.

[0010] The second aspect of the present application provides a high- and low-frequency data processing system for online monitoring of a nuclear power plant, which includes an acquisition module, a storage module, a statistical module, and an output module. The acquisition module is used to obtain high-frequency parameters and low-frequency parameters in the data of online monitoring of the nuclear power plant; obtain real-time data corresponding to high-frequency parameters from the PI system at a first frequency; obtain real-time data corresponding to low-frequency parameters from the PI system at a second frequency, and the first frequency is greater than the second frequency. The storage module is used to transmit the real-time data corresponding to the high-frequency parameters and the real-time data corresponding to the low-frequency parameters in the Json format, and store the real-time data corresponding to the high-frequency parameters and the real-time data corresponding to the low-frequency parameters in the form of an SQL database file. The statistical module is used to count the preset maximum power value and the corresponding time when the cumulative running time is greater than or equal to the preset time, and the preset maximum power value and the corresponding time when the cumulative running time is less than the preset time. The output module is used to output an over-power statistical curve, and the preset maximum power value and the corresponding time when the cumulative running time is greater than or equal to the preset time, and the preset maximum power value and the corresponding time when the cumulative running time is less than the preset time are displayed in different colors in the over-power statistical curve.

[0011] The third aspect of the present application provides a computer device, which includes a processor and a memory. The processor is used to execute the high and low frequency data processing method for online monitoring of a nuclear power plant provided in the first aspect of the present application. The memory is used to store executable instructions of the processor.

[0012] The fourth aspect of the present application provides a computer-readable storage medium on which computer executable instructions are stored. When the executable instructions are executed by a processor, the high- and low-frequency data processing method for online monitoring of a nuclear power plant provided in the first aspect of the present application is implemented.

[0013] The fifth aspect of the present application provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the high and low frequency data processing method for online monitoring of a nuclear power plant provided in the first aspect of the present application.

[0014] The beneficial effect of the technical solution of the present application is that by dividing the data structure of the data of the online monitoring of the nuclear power plant into two categories: high-frequency parameters and low-frequency parameters, the corresponding data is obtained at different frequencies for the high-frequency parameters and low-frequency parameters, and the result data is set to be transmitted in Json format and stored in the form of SQL database files, thereby realizing the rapid processing and storage of the real-time data of the nuclear power plant, and providing a unified system interface for other applications to access the real-time data of the nuclear power plant. In addition, the high- and low-frequency data processing method for online monitoring of the nuclear power plant can quickly and automatically count the cumulative operating time under a certain power, and better support the nuclear power plant operators to control the core. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 The figure is a flow chart of a method for processing high and low frequency data for online monitoring of a nuclear power plant provided by an embodiment of the present application.

[0016] Figure 2 Shown is a schematic diagram of an over-power statistical curve provided in an embodiment of the present application. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0018] At least one embodiment of the present application provides a method for processing high and low frequency data for online monitoring of a nuclear power plant. The execution subject of the method for processing high and low frequency data for online monitoring of a nuclear power plant may be a processor or a server. Figure 1 The high and low frequency data processing method for online monitoring of a nuclear power plant may include the following steps.

[0019] S1: Obtain high-frequency and low-frequency parameters in the online monitoring data of nuclear power plants.

[0020] It should be noted that the data structure of high- and low-frequency data (i.e., divided into high-frequency parameters and low-frequency parameters) can be defined on a computer or server with an "operating environment that supports the above process", and the high-frequency parameters and low-frequency parameters can be allocated corresponding storage space. Mainstream Windows and Linux machines can support the implementation of the high- and low-frequency data processing method for online monitoring of nuclear power plants. The most basic software and hardware requirements may include: 1) Memory: ≥4G; 2) Hard disk space: ≥50G; 3) Operating system: Windows, Linux system. For example, the computer or server that "supports the operating environment of the above process" can choose a mainstream Windows stand-alone computer on the market, 1T hard disk space, 6G memory, and Intel chip.

[0021] S2: Acquire real-time data corresponding to the high-frequency parameters from the PI system at the first frequency.

[0022] Specifically, the processor can call the real-time data corresponding to the high-frequency parameter from the PI system at a first frequency. The PI system is also the real-time data management system of the nuclear power plant.

[0023] S3: Acquire real-time data corresponding to the low-frequency parameter from the PI system at the second frequency. The first frequency is greater than the second frequency.

[0024] In some embodiments, the first frequency is once every 2 seconds, and the second frequency is once every 10 minutes. Thus, when the first frequency is once every 2 seconds, in step S1, the real-time data corresponding to the high-frequency parameters is refreshed once every 2 seconds from the PI system (corresponding to the above S1); when the second frequency is once every 10 minutes, the real-time data corresponding to the low-frequency parameters is refreshed once every 10 minutes from the PI system (corresponding to the above S2).

[0025] S4: The real-time data corresponding to the high-frequency parameters and the real-time data corresponding to the low-frequency parameters are transmitted in Json format, and the real-time data corresponding to the high-frequency parameters and the real-time data corresponding to the low-frequency parameters are stored in the form of an SQL database file.

[0026] S5: Counting the preset maximum power value and the corresponding duration when the cumulative running time is greater than or equal to the preset duration, and the preset maximum power value and the corresponding duration when the cumulative running time is less than the preset duration.

[0027] S6: Outputting an over-power statistical curve. The over-power statistical curve displays the preset maximum power value and the corresponding duration when the cumulative running time is greater than or equal to the preset duration, and the preset maximum power value and the corresponding duration when the cumulative running time is less than the preset duration in different colors.

[0028] In some embodiments, the preset time period is 72 hours.

[0029] For example, refer to Figure 2 The default color of the over-power statistical curve is black, the curve that meets the 72-hour power value is green, and the curve that does not meet the 72-hour power value and is the preset maximum power value is red.

[0030] According to the technical solution provided in the embodiment of the present application, by dividing the data structure of the data monitored online by the nuclear power plant into two categories: high-frequency parameters and low-frequency parameters, corresponding data is obtained at different frequencies for the high-frequency parameters and low-frequency parameters, and the result data is set to be transmitted in Json format and stored in the form of SQL database files, thereby realizing rapid processing and storage of real-time data of the nuclear power plant, and providing a unified system interface for other applications to access the real-time data of the nuclear power plant. In addition, the high- and low-frequency data processing method for online monitoring of the nuclear power plant can quickly and automatically count the cumulative operating time under a certain power, so as to better support nuclear power plant operators in core control.

[0031] The data structure of high-frequency and low-frequency data can be divided according to the specific situation of the nuclear power unit. It can be a fixed setting or adjusted in real time according to the data update frequency. The embodiment of the present application does not make specific limitations on this.

[0032] In at least one embodiment of the present application, the high-frequency parameters include the measured data acquisition time, core power, the number of steps of the control rod group, the core boron concentration, the source range measurement channel count rate, the intermediate range measurement channel count rate and the external detector current. The low-frequency parameters include the measured data acquisition time, the core cycle burnup depth, the average temperature of the primary coolant, the boronization water injection amount, the boron dilution water injection amount and the concentration of the injected concentrated boron water.

[0033] For example, the data structure of high-frequency, low-frequency, daily reports and other data is shown in Table 1 below.

[0034] Table 1 Data structure of high and low frequency, daily reports and other data

[0035]

[0036]

[0037]

[0038] Json file is a commonly used data exchange format that stores data in a text form that is easy to read and write. It consists of key-value pairs and is surrounded by curly brackets {}. In each key-value pair, the key and value are separated by a colon, and different key-value pairs are separated by commas. The key is a string, and the value can be a string, number, Boolean value, array, object, or null.

[0039] For example, in combination with Table 1 above, the Json format of the real-time data corresponding to the high-frequency parameters and the real-time data corresponding to the low-frequency parameters in the above S4 is as follows:

[0040] {

[0041] "ad_AxiPowDev":[-3.826,-3.818,-3.63,-3.638],

[0042] "ad_EFPD":[254.3,4586],

[0043] "ad_NucPow":[98.44,98.65,98.86,98.61],

[0044] "ad_RIC01":10.76,

[0045] "ad_RIC02":10.54,

[0046] "ad_UR":[0.6671,1.008,1.034,1.062,0.9908,0.7976,0.6732,1.033,1.123,1.104,1.028,0.8 299,0.6713,0.9398,1.055,1.023,0.9921,0.8161,0.6816,1.003,1.08,1.129,0.9857,0.8248],

[0047] "ad_thermoco":[20307,20308,20309,20310,20311,20312,20313,20314,20315,20316,20317,20318,20319,20320 ,20321,20322,20323,20324,20325,20326,20327,20328,20329,20330,20331,20332,20333,20334,20335,20330]

[0048] "d_AverTemp":309.9,

[0049] "d_CoreBuDeepR":4586,

[0050] "d_CoreConcBR":921.6,

[0051] "d_CorePowR":0.991,

[0052] "d_ElePow":664.7,

[0053] "d_KME":99.34,

[0054] "d_PriPress":15.44,

[0055] "d_PriTemp":300,

[0056] "d_QuaInc":0,

[0057] "d_RCP":99.11,

[0058] "d_SRC1":0,

[0059] "d_SRC2":0,

[0060] "d_SeaTemp1":24,

[0061] "d_SeaTemp2":26,

[0062] "d_SeaTemp3":23,

[0063] "d_coretemp1":309.8,

[0064] "d_coretemp2":309.8,

[0065] "d_irc1":0.000294,

[0066] "d_irc2":0.0003044,

[0067] "d_mdistIn":0.03,

[0068] "d_mdistOut":0,

[0069] "d_powChange":1,

[0070] "d_uGyH":116.4,

[0071] "d_waterLevel1":6.01,

[0072] "d_waterLevel2":5.01,

[0073] "i_OverlapRod":577,

[0074] "i_StickAR":225,

[0075] "i_StickBR":225,

[0076] "i_StickCR":225,

[0077] "i_StickDR":207,

[0078] "i_StickSR":225,

[0079] "i_Time":"XXX-XX-XX XXXX"}

[0080] Real-time data is stored in the SQL database in the form of a table structure. A table is the basic unit for storing data in a SQL database and consists of rows and columns. Each row represents a record and each column represents an attribute. The table contains a primary key, which is used to uniquely identify each row of data.

[0081] For example, in the above S4, the data format in the SQL database is as shown in Table 2. The primary key in Table 2 is a sequence number.

[0082] Table 2 Data format in SQL database

[0083]

[0084]

[0085]

[0086]

[0087] In at least one embodiment of the present application, the method for processing high and low frequency data for online monitoring of a nuclear power plant further includes S7.

[0088] S7: According to the changes of the real-time data corresponding to the high-frequency parameters and the real-time data corresponding to the low-frequency parameters acquired at different collection times, the high-frequency parameters and the low-frequency parameters in the online monitoring data of the nuclear power plant are updated.

[0089] It should be noted that step S7 can be updated according to the update frequency set by the user. If the data change in the originally defined high-frequency parameters is not obvious, they can be changed to low-frequency parameters. If the data change difference in the originally defined low-frequency parameters is large, they can be changed to high-frequency parameters. Accordingly, after the specific contents of the high-frequency parameters and the low-frequency parameters are updated, the updated high-frequency parameters and low-frequency parameters are re-obtained in the above step S1.

[0090] In at least one embodiment of the present application, the above-mentioned S5 also includes S41 and S42.

[0091] S41: Obtain the input type and power type selected by the user. The input type includes automatic input and manual input; the power type includes 30 days and 7 days.

[0092] S42: Obtain a preset maximum power value according to the input type.

[0093] Select "30 days":

[0094] If "Automatic Input" is selected, "Power % Pn" (i.e., the setting of the preset maximum power value) does not need to be filled in by the user, and the maximum power value and corresponding duration of the cumulative continuous operation greater than or equal to 72 hours will be counted. If the maximum power value of more than 72 hours of continuous operation is not met, the maximum power value and corresponding duration of the cumulative continuous operation time less than 72 hours will be counted; If "Manual Input" is selected, "Power % Pn" needs to be filled in by the user, and the maximum continuous operation time greater than or equal to the input power value will be counted; click the "Query" button to perform data statistics according to the selected type. If the statistical result meets the continuous operation of 72 hours, the data color display values ​​of "Power % Pn" and "Cumulative Operation Time (h)" will be green; if the continuous operation does not meet 72 hours, the data color display values ​​of "Power % Pn" and "Cumulative Operation Time (h)" will be red;

[0095] Select "7 days":

[0096] If "Automatic Input" is selected, the user does not need to fill in "Power % Pn", and the maximum power value that meets the cumulative running time greater than or equal to 72 hours is counted. If the maximum power value of more than 72 hours is not met, the maximum power value and the corresponding duration of the cumulative running time less than 72 hours are counted; If "Manual Input" is selected, the user needs to fill in "Power % Pn", and the power value greater than or equal to the input is counted; click the "Query" button to perform data statistics according to the selected type. If the statistical result meets the cumulative running time of 72 hours, the data color display values ​​of "Power % Pn" and "Cumulative Running Time (h)" are green; if it does not meet 72 hours, the data color display values ​​of "Power % Pn" and "Cumulative Running Time (h)" are red.

[0097] At least one embodiment of the present application further provides a high- and low-frequency data processing system for online monitoring of a nuclear power plant. The high- and low-frequency data processing system for online monitoring of a nuclear power plant includes an acquisition module, a storage module, a statistics module, and an output module.

[0098] The acquisition module is used to obtain high-frequency parameters and low-frequency parameters in the online monitoring data of the nuclear power plant; obtain real-time data corresponding to the high-frequency parameters from the PI system at a first frequency; obtain real-time data corresponding to the low-frequency parameters from the PI system at a second frequency, and the first frequency is greater than the second frequency.

[0099] The storage module is used to transmit the real-time data corresponding to the high-frequency parameters and the real-time data corresponding to the low-frequency parameters in the Json format, and store the real-time data corresponding to the high-frequency parameters and the real-time data corresponding to the low-frequency parameters in the form of an SQL database file.

[0100] The statistics module is used to count the preset maximum power value and the corresponding time when the cumulative running time is greater than or equal to the preset time, and the preset maximum power value and the corresponding time when the cumulative running time is less than the preset time.

[0101] The output module is used to output an over-power statistical curve, in which the preset maximum power value and the corresponding duration when the cumulative running time is greater than or equal to the preset duration, and the preset maximum power value and the corresponding duration when the cumulative running time is less than the preset duration are displayed in different colors.

[0102] In at least one embodiment of the present application, the acquisition module is also used to obtain the input type and power type selected by the user, the input type includes automatic input and manual input, and the power type includes 30 days and 7 days; and the preset maximum power value is obtained according to the input type.

[0103] The embodiment of the present application provides a high- and low-frequency data processing system for online monitoring of a nuclear power plant, which can realize rapid processing and storage of real-time data of the nuclear power plant, and provide a unified system interface for other applications to access the real-time data of the nuclear power plant. In addition, the system can quickly and automatically count the accumulated operating time under a certain power, and better support nuclear power plant operators in core control.

[0104] The high and low frequency data processing system for online monitoring of a nuclear power plant is a processing system corresponding to the high and low frequency data processing method for online monitoring of a nuclear power plant in any of the above embodiments of the present application, includes the corresponding technical features of the high and low frequency data processing method for online monitoring of a nuclear power plant in any of the above embodiments of the present application, has the corresponding technical effects, and will not be repeated here.

[0105] It should be noted that the combination of the various technical features in the embodiments of the present application is not limited to the combination described in the embodiments of the present application or the combination described in the specific embodiments, and all technical features described in the present application can be freely combined or combined in any way unless there is a contradiction between them.

[0106] As shown in this application and claims, unless the context clearly indicates an exception, the words "a", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the term "comprising" only indicates that the steps and elements that have been clearly identified are included, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0107] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for processing high and low frequency data for online monitoring of a nuclear power plant, characterized in that: include: Obtain high-frequency and low-frequency parameters in the online monitoring data of nuclear power plants; Acquire real-time data corresponding to the high-frequency parameter at a first frequency from the PI system; acquiring real-time data corresponding to the low-frequency parameter at a second frequency from the PI system, the first frequency being greater than the second frequency; The real-time data corresponding to the high-frequency parameters and the real-time data corresponding to the low-frequency parameters are transmitted in the Json format, and the real-time data corresponding to the high-frequency parameters and the real-time data corresponding to the low-frequency parameters are stored in the form of an SQL database file; Count the preset maximum power value and corresponding duration when the cumulative running time is greater than or equal to the preset duration, and the preset maximum power value and corresponding duration when the cumulative running time is less than the preset duration; An over-power statistical curve is output, wherein the over-power statistical curve displays the preset maximum power value and the corresponding duration when the cumulative running time is greater than or equal to the preset duration, and the preset maximum power value and the corresponding duration when the cumulative running time is less than the preset duration in different colors.

2. The high and low frequency data processing method for online monitoring of a nuclear power plant according to claim 1 is characterized in that: Before counting the preset maximum power value and the corresponding duration when the cumulative running time is greater than or equal to the preset duration, and the preset maximum power value and the corresponding duration when the cumulative running time is less than the preset duration, the method further includes: Obtain the input type and power type selected by the user, where the input type includes automatic input and manual input, and the power type includes 30 days and 7 days; The preset maximum power value is determined according to the input type.

3. The high and low frequency data processing method for online monitoring of a nuclear power plant according to claim 1, characterized in that: High-frequency parameters include measured data acquisition time, core power, control rod group withdrawal steps, core boron concentration, source range measurement channel count rate, intermediate range measurement channel count rate and external detector current; The low-frequency parameters include the measured data acquisition time, core cycle burnup depth, primary coolant average temperature, boronization water injection volume, boron dilution water injection volume and injected concentrated boron water concentration.

4. The method for processing high and low frequency data for online monitoring of a nuclear power plant according to claim 1, characterized in that: Also includes: According to the changes in the real-time data corresponding to the high-frequency parameters and the real-time data corresponding to the low-frequency parameters obtained at different collection times, the high-frequency parameters and the low-frequency parameters in the online monitoring data of the nuclear power plant are updated.

5. The method for processing high and low frequency data for online monitoring of a nuclear power plant according to any one of claims 1 to 4, characterized in that: The default duration is 72 hours.

6. The method for processing high and low frequency data for online monitoring of a nuclear power plant according to any one of claims 1 to 4, characterized in that: In the over-power statistical curve, the preset maximum power value and the corresponding duration when the cumulative running time is greater than or equal to the preset duration are displayed in green, and the preset maximum power value and the corresponding duration when the cumulative running time is less than the preset duration are displayed in red.

7. A high and low frequency data processing system for online monitoring of a nuclear power plant, characterized in that: include: An acquisition module is used to acquire high-frequency parameters and low-frequency parameters in the online monitoring data of the nuclear power plant; acquire real-time data corresponding to the high-frequency parameters from the PI system at a first frequency; acquire real-time data corresponding to the low-frequency parameters from the PI system at a second frequency, wherein the first frequency is greater than the second frequency; A storage module is used to transmit the real-time data corresponding to the high-frequency parameters and the real-time data corresponding to the low-frequency parameters in the Json format, and store the real-time data corresponding to the high-frequency parameters and the real-time data corresponding to the low-frequency parameters in the form of an SQL database file; A statistics module, used to count the preset maximum power value and the corresponding duration when the cumulative running time is greater than or equal to the preset duration, and the preset maximum power value and the corresponding duration when the cumulative running time is less than the preset duration; The output module is used to output an over-power statistical curve, wherein the over-power statistical curve displays the preset maximum power value and corresponding duration when the cumulative running time is greater than or equal to the preset duration, and the preset maximum power value and corresponding duration when the cumulative running time is less than the preset duration in different colors.

8. A computer device, characterized in that: include: A processor, configured to execute the high- and low-frequency data processing method for online monitoring of a nuclear power plant according to any one of claims 1 to 6; as well as A memory is used to store executable instructions of the processor.

9. A computer-readable storage medium having computer executable instructions stored thereon, characterized in that: When the executable instructions are executed by the processor, the high- and low-frequency data processing method for online monitoring of a nuclear power plant according to any one of claims 1 to 6 is implemented.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the high- and low-frequency data processing method for online monitoring of a nuclear power plant according to any one of claims 1 to 6 is implemented.

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