Intelligent parameter monitoring method and device for nuclear power plant

Abstract

The invention belongs to the technical field of nuclear power, and particularly relates to an intelligent parameter monitoring method and device for a nuclear power plant. According to the intelligent parameter monitoring method for the nuclear power plant provided by the invention, parameter monitoring under two different working conditions of a steady state and a transient state is realized, different monitoring methods are introduced for different working conditions, and the precision and reliability of parameter monitoring are improved; parameter abnormity can be found in advance, operators can have sufficient intervention and processing time, and safe operation of the nuclear power plant is facilitated; the whole-process dynamic monitoring and abnormity identification of the parameters are realized, the monitoring pressure of operators is reduced, and the working efficiency is improved; the influence of human factors on the monitoring result is reduced, the inherent limitation of people is eliminated, and the parameter monitoring is more comprehensive and timely.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of nuclear power, and particularly relates to a parameter intelligent monitoring method and device for a nuclear power plant. BACKGROUND

[0002] The daily operation of a nuclear power plant involves the control of hundreds of systems, and the parameters of these systems are mostly transmitted to a DCS (Distributed Control System) to realize numerical display and logic control. However, at present, domestic nuclear power units generally rely on the patrol monitoring of operators in the aspect of DCS parameter monitoring. Due to the inherent limitations of humans, such as differences in skill level, concentration and degree of care, problems such as the fact that parameter degradation is not detected or parameter monitoring is not comprehensive may occur in the actual monitoring process. In addition, during the execution of important operations and shift handovers, operators have difficulty in timely detecting parameter changes, thereby causing response lag and affecting the safe operation of the unit. Therefore, it is urgent to realize the dynamic monitoring of parameters throughout the process to solve the above problems. SUMMARY

[0003] In order to overcome the problems in the related art, a parameter intelligent monitoring method and device for a nuclear power plant are provided.

[0004] According to an aspect of an embodiment of the present disclosure, a parameter intelligent monitoring method for a nuclear power plant is provided, and the method comprises:

[0005] Step 1: obtaining the current electric power parameter value of the nuclear power unit at a preset frequency, judging whether the difference between the electric power parameter value and the electric power set value is less than the deviation threshold value; when the difference between the electric power parameter value and the electric power set value is less than the deviation threshold value, performing intelligent monitoring of a steady-state parameter; when the difference between the electric power parameter value and the electric power set value is greater than or equal to the deviation threshold value, performing intelligent monitoring of a transient parameter;

[0006] Step 2: in the case of performing intelligent monitoring of a steady-state parameter, in an initial state, the parameter value of an operating parameter is captured as a reference value, and then the parameter value of the operating parameter is captured at a preset frequency, a plurality of reference thresholds are set, the percentages of different reference thresholds in the overall range of the operating parameter are different, and in the case where the difference between the parameter value and the reference value is greater than one or more reference thresholds, the first event alarm corresponding to the reference threshold with the largest value in all reference thresholds smaller than the difference is output;

[0007] Step 3: in the case of performing intelligent monitoring of a steady-state parameter, the parameter values of the operating parameter are collected at a preset frequency within a preset time window, and the steady-state threshold interval is obtained according to the minimum value and the maximum value in the plurality of parameter values; after the time window, in the case where the captured parameter value of the operating parameter exceeds the steady-state threshold interval, a second event alarm is output;

[0008] Step 4: In the case of performing transient parameter intelligent monitoring, the parameter value of the running parameter is captured at a preset frequency, it is judged whether the captured parameter value exceeds the transient threshold interval, and in the case that the captured parameter value exceeds the transient threshold interval, a third event alarm is outputted;

[0009] Step 5: After the event alarm is outputted, event display and recording are performed, and in the case that the corresponding running parameter returns to the normal range, the event monitoring of the running parameter is automatically reset, and a new round of monitoring is performed.

[0010] In a possible implementation, in step 2, the reference value N0 of the running parameter A is captured in the initial state, and then the parameter value Ni of the parameter is captured at a preset frequency, the maximum range of the running parameter A is a, the reference threshold set includes a*Y% and a*Z%, Z>Y, if |Ni-N0|>a*Y%, a first event alarm with yellow background and black characters is outputted, and if |Ni-N0|>a*Z% range, a first event alarm with red background and black characters is outputted;

[0011] In step 3, the parameter value of the running parameter is collected at a preset frequency within a time window T, the threshold interval of the running parameter is [Nmin, Nmax], Nmin is the minimum value of the running parameter recorded within the time window T, and Nmax is the maximum value of the running parameter recorded within the time window T, if Ni>Nmax or Ni

[0012] In step 4, the parameter value of the running parameter is collected at a preset frequency within a time window T, the threshold interval of the running parameter is [Nmin, Nmax], Nmin is the minimum value of the running parameter recorded within the time window T, and Nmax is the maximum value of the running parameter recorded within the time window T, if Ni>Nmax or Ni

[0013] In a possible implementation, the event alarms with different backgrounds have different priorities: green background and black characters event> white background and black characters event> red background and black characters event> yellow background and black characters event.

[0014] For example, in step 4, in the case of performing transient parameter intelligent monitoring, the time window T is 24h or longer, the threshold interval of the running parameter is [Nmin, Nmax], Nmin is the minimum value of the running parameter recorded within the time window T, and Nmax is the maximum value of the running parameter recorded within the time window T, if Ni>Nmax or Ni

[0015] In a possible implementation, different alarm events are arranged and displayed according to the output time sequence through the display screen.

[0016] In a possible implementation, if events of different colors are output simultaneously, the events are output in order of priority from high to low.

[0017] In a possible implementation, the preset frequency, the deviation threshold and the time window are set according to the monitoring requirement of the nuclear power unit and historical experience values.

[0018] According to another aspect of the embodiments of the present disclosure, a parameter intelligent monitoring device for a nuclear power plant is provided, and the device comprises:

[0019] a state judgment module, configured to acquire a current electric power parameter value of the nuclear power unit at a preset frequency, judge whether a difference between the electric power parameter value and an electric power set value is less than a deviation threshold, perform steady-state parameter intelligent monitoring when the difference between the electric power parameter value and the electric power set value is less than the deviation threshold, and perform transient-state parameter intelligent monitoring when the difference between the electric power parameter value and the electric power set value is greater than or equal to the deviation threshold;

[0020] a first steady-state detection module, configured to, in a case of performing the steady-state parameter intelligent monitoring, capture a parameter value of a running parameter as a reference value in an initial state, then capture parameter values of the running parameter at the preset frequency, set a plurality of reference thresholds, different reference thresholds occupying different percentages of a total range of the running parameter, and output a first event alarm corresponding to a reference threshold with a maximum value among all reference thresholds smaller than the difference when the difference between the parameter value and the reference value is greater than one or more reference thresholds;

[0021] a second steady-state detection module, configured to, in a case of performing the steady-state parameter intelligent monitoring, acquire parameter values of the running parameter at the preset frequency within a preset time window, obtain a steady-state threshold interval according to a minimum value and a maximum value in the plurality of parameter values, and output a second event alarm when the captured parameter values of the running parameter exceed the steady-state threshold interval after the time window;

[0022] a transient-state detection module, configured to, in a case of performing the transient-state parameter intelligent monitoring, capture parameter values of the running parameter at the preset frequency, judge whether the captured parameter values exceed a transient-state threshold interval, and output a third event alarm when the captured parameter values exceed the transient-state threshold interval;

[0023] an output and reset module, configured to output event alarms, then perform event display and recording, and automatically reset event monitoring of the running parameter and perform a new round of monitoring when the corresponding running parameter returns to a normal range.

[0024] According to another aspect of the embodiments of the present disclosure, a parameter intelligent monitoring device for a nuclear power plant is provided, and the device comprises:

[0025] a processor;

[0026] Memory used to store processor-executable instructions;

[0027] The processor is configured to execute the above-described method.

[0028] According to another aspect of the present disclosure, a non-volatile computer-readable storage medium is provided, on which computer program instructions are stored, which, when executed by a processor, implement the above-described method.

[0029] The beneficial effects of this disclosure are as follows: The intelligent parameter monitoring method for nuclear power plants provided by this disclosure realizes parameter monitoring under both steady-state and transient operating conditions. Different monitoring methods are introduced for different operating conditions, improving the accuracy and reliability of parameter monitoring; it helps to detect parameter anomalies in advance, giving operators sufficient time to intervene and handle them, thus contributing to the safe operation of nuclear power plants; it realizes dynamic monitoring and anomaly identification of parameters throughout the entire process, reducing the monitoring pressure on operators and improving work efficiency; it reduces the impact of human factors on monitoring results, overcoming the inherent limitations of humans, and making parameter monitoring more comprehensive and timely; this disclosure also introduces different types of event alarm settings for different abnormal situations, realizing priority judgment, which can avoid the impact of repetitive and redundant events on the event monitoring of operators, with high accuracy, strong directionality, and certain applicability. Attached Figure Description

[0030] Figure 1 This is a flowchart illustrating an intelligent parameter monitoring method for nuclear power plants, as shown in an embodiment of this disclosure.

[0031] Figure 2 This is a block diagram of an intelligent parameter monitoring device for nuclear power plants, as shown in an embodiment of this disclosure. Detailed Implementation

[0032] The present disclosure will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0033] Unless otherwise defined, the technical and scientific terms used in this disclosure have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains; the terminology used in this disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of this disclosure; the term "comprising" and any variations thereof in this disclosure are intended to cover non-exclusive inclusion. Clearly, the embodiments described in this disclosure are only a part of the embodiments of this disclosure, and not all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of this disclosure without inventive effort are within the scope of protection of this disclosure.

[0034] In this disclosure, the reference to "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this disclosure. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0035] Figure 1 This is a flowchart illustrating an intelligent parameter monitoring method for nuclear power plants, as shown in an embodiment of this disclosure. The method can be executed by a terminal device, which can be a server, desktop computer, or laptop computer, etc. This disclosure does not limit the type of terminal device. Figure 1 As shown, the method includes:

[0036] Step 1: Obtain the current electrical power parameter value of the nuclear power unit at a preset frequency, and determine whether the difference between the electrical power parameter value and the electrical power set value is less than the deviation threshold; if the difference between the electrical power parameter value and the electrical power set value is less than the deviation threshold, execute steady-state parameter intelligent monitoring; if the difference between the electrical power parameter value and the electrical power set value is greater than or equal to the deviation threshold, execute transient parameter intelligent monitoring.

[0037] Steady-state parameter intelligent monitoring refers to the monitoring of parameter anomalies when the unit's electrical power remains relatively constant and each parameter remains within a stable range. Transient parameter intelligent monitoring refers to the monitoring of parameter anomalies when the unit's electrical power changes and each parameter changes with the change in unit power.

[0038] In one possible implementation, preset frequencies and deviation thresholds can be set based on the monitoring needs of the nuclear power unit and historical experience values. This allows for dynamic adaptation to the parameter monitoring needs of different systems in different types of nuclear power units.

[0039] Step 2: When performing steady-state parameter intelligent monitoring, for the operating parameters that need to be monitored in the DCS system (operating parameters can be, for example, TW1GST001MD in the GST system, TW1GRV001MP in the GRV system, TW1CFI001MN in the CFI system, etc.), the baseline value of the operating parameter is captured in the initial state. Then, the parameter value of the operating parameter is captured at a preset frequency. Multiple reference thresholds with values ​​varying from small to large are set. The percentage of each reference threshold relative to the total range of the operating parameter is different. Different reference thresholds correspond to different forms of first event alarms. The larger the reference threshold value, the more severe the first event alarm. If the difference between the parameter value and the baseline value is greater than one or more reference thresholds, the first event alarm corresponding to the largest reference threshold value among all reference thresholds smaller than the difference is output.

[0040] For example, in step 2, the reference value N0 of operating parameter A is captured in the initial state, and then the parameter value Ni of this parameter is measured at a preset frequency. The maximum range of operating parameter A is a (range a can be expressed as the instrument range of the parameter value Ni of operating parameter A, for example, the range of TW1GST001MD is 0~200m). 3 / h, the range of TW1GRV001MP is 0~400kPa, and the range of TW1CFI001MN is -14000~8000mm. The range of the operating parameters can be directly captured from the DCS system. The set reference thresholds include: a*Y% and a*Z%, Z>Y. If |Ni-N0|>a*Y%, the first event alarm with yellow background and black text will be output. If |Ni-N0|>a*Z%, the first event alarm with red background and black text will be output. Y and Z can be set according to monitoring needs and experience values, as long as Z>Y.

[0041] Step 3: When performing steady-state parameter intelligent monitoring, a preset time window is set. Within the time window, the parameter values ​​of the operating parameters are collected at a preset frequency. The steady-state threshold range is obtained based on the minimum and maximum values ​​among the multiple parameter values. After the time window, the parameter values ​​of the operating parameters are captured at a preset frequency. It is determined whether the captured parameter values ​​exceed the threshold range. If the captured parameter values ​​exceed the threshold range, a second event alarm is output.

[0042] For example, in the case of performing intelligent monitoring of steady-state parameters, in step 3, the time window T can be 24 hours or longer, and the steady-state threshold range can be [Nmin, Nmax], where Nmin is the minimum value of the operating parameter recorded within the time window T, and Nmax is the maximum value of the operating parameter recorded within the time window T. If Ni > Nmax or Ni < Nmin, a second event alarm with white background and black text is output.

[0043] Step 4: When performing transient parameter intelligent monitoring, capture the parameter values ​​of the operating parameters at a preset frequency, determine whether the captured parameter values ​​exceed the transient threshold range, and output a third event alarm if the captured parameter values ​​exceed the transient threshold range.

[0044] For example, in step 4, when performing intelligent monitoring of transient parameters, the transient threshold range can be set to [Nmin, Nmax]. If the captured operating parameter value Ni > Nmax or Ni < Nmin, a third event alarm with green background and black text will be output.

[0045] In the process of steady-state parameter monitoring, this disclosure adopts a method of comparing the deviation of the real-time parameter value from the benchmark value with multiple reference thresholds to effectively monitor operating parameters with small fluctuations during normal operation, such as system pressure; and adopts a method of using historical extreme values ​​within a time window to effectively monitor operating parameters with large periodic fluctuations, such as forebay water level, and dynamically adapts to parameters with large fluctuations. In this way, by executing the above two monitoring methods in parallel, the steady-state operating parameters of nuclear power units can be effectively covered.

[0046] In one possible implementation, event alarms with different background colors have different priorities: green background with black text > white background with black text > red background with black text > yellow background with black text. Green background with black text events have the highest priority and require immediate user response when they occur. White background with black text events have higher reliability because they compare steady-state parameter ranges, so they have a higher priority than red background with black text and yellow background with black text events and require user attention and response when they occur. Red background with black text and yellow background with black text events represent different degrees of deviation from abnormal parameters and require user attention when they occur, but a delayed response or further observation is possible.

[0047] Step 5: After outputting the event alarm, the event is displayed and recorded. Once the operator responds to the abnormal operating parameters and the parameters return to the normal range, the event is automatically reset, and a new round of monitoring begins. Events of different colors are displayed on the screen in the order of their output. If events of different colors are output simultaneously, the alarms are output in descending order of priority to help users determine the urgency of the parameter anomaly. The output event alarms are recorded in the database, and users can export events by interval as needed.

[0048] In one application example, for intelligent monitoring of steady-state parameters, taking the flow rate (TW1GST001MD) of the generator stator cooling water system (GST) as an example, the flow rate is relatively stable (with slight fluctuations) during the steady-state operation of the unit. If an abnormal drop in flow rate occurs, it indicates that the pump is malfunctioning or there is a leak in the pipeline. At this time, it is necessary to detect and intervene as soon as possible. The monitoring method includes the following steps.

[0049] Set the values ​​of X, Y, Z, T, and Δt. Set X to 5MW, Y% to 5%, Z% to 10%, T to 24h, and Δt to 15s.

[0050] The system captures the power parameter value Gi, reads the power setpoint G0, and determines whether |Gi-G0| is less than 5MW, which is the steady-state entry condition. During stable operation, the value of Gi may fluctuate, but the absolute value of the difference between Gi and G0 is generally less than 3MW, so the entry condition of |Gi-G0|<5MW is met. Then, the system captures the power parameter value Gi again every 15s to re-determine the condition.

[0051] If the absolute value of the difference between Gi and G0 satisfies the entry condition, intelligent monitoring of steady-state parameters is executed. In the initial state, the reference value N0 of TW1GST001MD is captured, and then the parameter value Ni is recorded every 15 seconds. Y%*a = 200 × 5% = 10m is set. 3 / h, Z%*a=200×10%=20m 3 / h, if |Ni-N0|>10m 3 When / h, a yellow-background-black-text event alarm will be output. If |Ni-N0|>20m 3 When / h is displayed, a red-background, black-text event alarm will be output.

[0052] For comparing steady-state parameter ranges, the first 24 hours are used to capture extreme values, and after 24 hours, the steady-state parameter range [Nmin, Nmax] is output. For example, if Ni fluctuates within the first 24 hours, the output steady-state parameter range is [175, 185]m. 3 / h, then if the flow parameter Ni is greater than 185m after 24h. 3 / h or less than 175m 3 When / h is displayed, a white background with black text will be output as an event alarm.

[0053] Events of the same parameter but different colors are prioritized and then displayed and recorded as alarms to the operators. After the operators take measures to respond or intervene, if the parameter returns to the threshold range, the corresponding event alarm for that parameter is reset and a new round of intelligent monitoring of steady-state parameters continues.

[0054] In another application example, for intelligent monitoring of steady-state parameters, taking the forebay liquid level (TW1CFI001MN) of the circulating water filtration system (CFI) as an example, the level changes periodically over time (affected by tides) during steady-state operation of the unit. A decrease or increase in this parameter does not necessarily indicate an anomaly. However, such parameters often have a steady-state variation range. When the level exceeds this range, it indicates an abnormal parameter change. The monitoring method includes the following steps:

[0055] Initially set the values ​​of X, Y, Z, T, and Δt. Assume that X is set to 5MW, Y% to 5%, Z% to 10%, T to 24h, and Δt to 15s.

[0056] The system captures the power parameter value Gi, reads the power setpoint G0, and determines whether |Gi-G0| is less than 5MW, which is the steady-state entry condition. During stable operation, the value of Gi may fluctuate, but the absolute value of the difference between Gi and G0 is generally less than 3MW, so the entry condition of |Gi-G0|<5MW is met. Then, the system captures the power parameter value Gi again every 15s to re-determine the condition.

[0057] If the absolute value of the difference between Gi and G0 satisfies the entry condition, intelligent monitoring of steady-state parameters is executed. In the initial state, the reference value N0 of TW1CFI001MN is captured, and then the parameter value Ni is recorded every 15 seconds. Y%*a = 22000 × 5% = 1100 mm, Z%*a = 22000 × 10% = 2200 mm.

[0058] If |Ni-N0| > 1100mm, a yellow background with black text event alarm will be output; if |Ni-N0| > 2200mm, a red background with black text event alarm will be output.

[0059] For comparison of steady-state parameter ranges, the first 24 hours are used to capture extreme values, and after 24 hours, the steady-state parameter range [Nmin, Nmax] is output. For example, if the liquid level parameter Ni fluctuates within 24 hours, the output steady-state parameter range is [-4000, 1600] mm. Then, if the liquid level parameter Ni is greater than 1600 mm or less than -4000 mm after 24 hours, a white background black text event alarm will be output.

[0060] Then, continuously check whether the liquid level parameter Ni exceeds the above upper limit; prioritize events of the same parameter in different colors, and finally display and record the event alarm to the operators on the display screen; after the operators take measures to respond or intervene, if the parameter returns to the threshold range, reset the corresponding event alarm for that parameter and continue a new round of abnormal monitoring.

[0061] In another application example, for intelligent monitoring of transient parameters, taking the hydrogen pressure (TW1GRV001MP) of the generator hydrogen supply system (GRV) as an example, during the transient operation of the unit, the generator's hydrogen pressure changes with the change in electrical power. Steady-state monitoring cannot meet the monitoring requirements for this type of parameter. Therefore, it is necessary to introduce designed high and low limits. When the parameter exceeds the high limit or falls below the low limit, it indicates an abnormality, requiring intervention or response from operators. The monitoring method includes the following steps:

[0062] Initially set the values ​​of X, Y, Z, T, and Δt. Set X to 5MW, Y% to 5%, Z% to 10%, T to 24h, and Δt to 15s.

[0063] The power parameter value Gi is captured and the power parameter value G0 is read. During transient operation, the Gi parameter will change instantaneously or change unidirectionally with time, so the condition |Gi-G0|<5MW is not met. Then, the power parameter value Gi is captured again every 15s for re-determination.

[0064] If the absolute value of the difference between Gi and G0 does not meet the entry condition, transient parameter intelligent monitoring is executed. The current operating parameter value Ni of TW1GRV001MP is captured every 15 seconds. The upper limit of TW1GRV001MP is set to 320kPa and the lower limit is set to 260kPa. If Ni > 320kPa or Ni < 260kPa, a green-background black-text event alarm is output. Then, the pressure parameter Ni is continuously checked to see if it exceeds the above upper limit value.

[0065] Green-background, black-text events are also prioritized and then displayed and recorded as event alarms to operators on the screen. Once operators have taken measures to respond or intervene, if the parameter returns to the threshold range, the corresponding event alarm for that parameter is reset, and a new round of anomaly monitoring continues.

[0066] According to another aspect of the present disclosure, a smart parameter monitoring device for nuclear power plants is provided, the device comprising:

[0067] The status judgment module is used to acquire the current power parameter value of the nuclear power unit at a preset frequency, and determine whether the difference between the power parameter value and the power set value is less than the deviation threshold. When the difference between the power parameter value and the power set value is less than the deviation threshold, the module performs steady-state parameter intelligent monitoring. When the difference between the power parameter value and the power set value is greater than or equal to the deviation threshold, the module performs transient parameter intelligent monitoring.

[0068] The first steady-state detection module is used to capture the parameter value of the operating parameter as a reference value in the initial state when performing intelligent monitoring of steady-state parameters. Then, it captures the parameter value of the operating parameter at a preset frequency, sets multiple reference thresholds, and the percentage of each reference threshold relative to the total range of the operating parameter is different. When the difference between the parameter value and the reference value is greater than one or more reference thresholds, it outputs the first event alarm corresponding to the reference threshold with the largest value among all reference thresholds less than the difference.

[0069] The second steady-state detection module is used to perform intelligent monitoring of steady-state parameters, set a time window, collect the parameter values ​​of the operating parameters at a preset frequency within the time window, and obtain the steady-state threshold range based on the minimum and maximum values ​​among multiple parameter values; after the time window, capture the parameter values ​​of the operating parameters at a preset frequency, determine whether the captured parameter values ​​exceed the steady-state threshold range, and output a second event alarm if the captured parameter values ​​exceed the steady-state threshold range.

[0070] The transient detection module is used to capture the parameter values ​​of the running parameters at a preset frequency when performing intelligent monitoring of transient parameters, determine whether the captured parameter values ​​exceed the transient threshold range, and output a third event alarm if the captured parameter values ​​exceed the transient threshold range.

[0071] The output and reset module is used to display and record events after an alarm is output. When the corresponding operating parameters return to the normal range, the event monitoring of the operating parameters is automatically reset and a new round of monitoring is started.

[0072] The description of the above-mentioned apparatus has been elaborated in detail in the description of the above-mentioned method, and will not be repeated here.

[0073] Figure 2 This is a block diagram illustrating an intelligent parameter monitoring device for nuclear power plants, as shown in an embodiment of this disclosure. For example, device 1900 can be provided as a server. (See also...) Figure 2 The apparatus 1900 includes a processing component 1922, which further includes one or more processors, and memory resources represented by memory 1932 for storing instructions, such as application programs, that can be executed by the processing component 1922. The application programs stored in memory 1932 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 1922 is configured to execute instructions to perform the methods described above.

[0074] Device 1900 may also include a power supply component 1926 configured to perform power management of device 1900, a wired or wireless network interface 1950 configured to connect device 1900 to a network, and an input / output (I / O) interface 1958. Device 1900 can operate on an operating system stored in memory 1932, such as Windows Server™, MacOS X™, Unix™, Linux™, FreeBSD™, or similar.

[0075] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions that can be executed by a processing component 1922 of the device 1900 to perform the above-described method.

[0076] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0077] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination thereof. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0078] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0079] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0080] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0081] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0082] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0083] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0084] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or improvement of the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for intelligent monitoring of parameters in nuclear power plants, characterized in that, The method includes: Step 1: Obtain the current actual power value of the nuclear power unit at a preset frequency, and determine whether the difference between the actual power value and the set power value is less than the deviation threshold; if the difference between the actual power value and the set power value is less than the deviation threshold, execute intelligent monitoring of steady-state parameters; if the difference between the actual power value and the set power value is greater than or equal to the deviation threshold, execute intelligent monitoring of transient parameters. Step 2: When performing steady-state parameter intelligent monitoring, capture the parameter value of the operating parameter as the reference value in the initial state, and then capture the parameter value of the operating parameter at a preset frequency. Set multiple reference thresholds, and the percentage of different reference thresholds in the total range of the operating parameter is different. If the difference between the parameter value and the reference value is greater than one or more reference thresholds, output the first event alarm corresponding to the reference threshold with the largest value among all reference thresholds less than the difference. Step 3: When performing steady-state parameter intelligent monitoring, collect the parameter values ​​of the operating parameters at a preset frequency within a preset time window, and obtain the steady-state threshold range based on the minimum and maximum values ​​among these multiple parameter values; after the time window, if the captured operating parameter values ​​exceed the steady-state threshold range, output a second event alarm. Step 4: When performing transient parameter intelligent monitoring, capture the parameter values ​​of the operating parameters at a preset frequency, determine whether the captured parameter values ​​exceed the transient threshold range, and output a third event alarm if the captured parameter values ​​exceed the transient threshold range. Step 5: After outputting the event alarm, the event is displayed and recorded. When the corresponding operating parameters return to the normal range, the event monitoring of the operating parameters is automatically reset and a new round of monitoring is started.

2. The method according to claim 1, characterized in that, In step 2, the baseline value N0 of the running parameter A is captured in the initial state. Then, the parameter value Ni of the parameter is set at a preset frequency. The maximum range of the running parameter A is a. The set reference thresholds include a*Y% and a*Z%, Z>Y. If |Ni-N0|>a*Y%, the first event alarm with yellow background and black text is output. If |Ni-N0|>a*Z%, the first event alarm with red background and black text is output when the range is reached. In step 3, the parameter values ​​of the operating parameters are collected at a preset frequency within the time window T. The threshold range of the operating parameters is [Nmin, Nmax], where Nmin is the minimum value of the operating parameters recorded within the time window T, and Nmax is the maximum value of the operating parameters recorded within the time window T. If Ni > Nmax or Ni < Nmin, a second event alarm with white background and black text is output. In step 4, the parameter values ​​of the operating parameters are collected at a preset frequency within the time window T. The threshold range of the operating parameters is [Nmin, Nmax], where Nmin is the minimum value of the operating parameters recorded within the time window T, and Nmax is the maximum value of the operating parameters recorded within the time window T. If Ni > Nmax or Ni < Nmin, a third event alarm with green background and black text is output.

3. The method according to claim 4, characterized in that, Event alarms with different background colors have different priorities: green background with black text > white background with black text > red background with black text > yellow background with black text. For example, in step 4, when performing transient parameter intelligent monitoring, the time window T is 24 hours or longer, and the threshold range of the operating parameters is [Nmin, Nmax]. Nmin is the minimum value of the operating parameters recorded within the time window T; Nmax is the maximum value of the operating parameters recorded within the time window T; if Ni > Nmax or Ni < Nmin, then a third event alarm with green background and black text is output.

4. The method according to claim 1, characterized in that, Different alarm events are displayed on the screen in the order of their output.

5. The method according to claim 1, characterized in that, If events of different colors are output simultaneously, the alarms will be output in descending order of priority.

6. The method according to claim 1, characterized in that, The preset frequency, deviation threshold, and time window are set based on the monitoring needs of the nuclear power unit and historical experience values.

7. A parameter intelligent monitoring device for nuclear power plants, characterized in that, The device includes: The status judgment module is used to obtain the current actual power value of the nuclear power unit at a preset frequency, and determine whether the difference between the actual power value and the set power value is less than the deviation threshold. When the difference between the actual power value and the set power value is less than the deviation threshold, intelligent monitoring of steady-state parameters is performed. When the difference between the actual power value and the set power value is greater than or equal to the deviation threshold, intelligent monitoring of transient parameters is performed. The first steady-state detection module is used to capture the parameter value of the operating parameter as a reference value in the initial state when performing intelligent monitoring of steady-state parameters. Then, it captures the parameter value of the operating parameter at a preset frequency, sets multiple reference thresholds, and the percentage of each reference threshold relative to the total range of the operating parameter is different. When the difference between the parameter value and the reference value is greater than one or more reference thresholds, it outputs the first event alarm corresponding to the reference threshold with the largest value among all reference thresholds less than the difference. The second steady-state detection module is used to collect the parameter values ​​of the operating parameters at a preset frequency within a preset time window when performing intelligent monitoring of steady-state parameters, and to obtain the steady-state threshold range based on the minimum and maximum values ​​among the multiple parameter values; after the time window, if the captured operating parameter values ​​exceed the steady-state threshold range, a second event alarm is output. The transient detection module is used to capture the parameter values ​​of the running parameters at a preset frequency when performing intelligent monitoring of transient parameters, determine whether the captured parameter values ​​exceed the transient threshold range, and output a third event alarm if the captured parameter values ​​exceed the transient threshold range. The output and reset module is used to display and record events after an alarm is output. When the corresponding operating parameters return to the normal range, the event monitoring of the operating parameters is automatically reset and a new round of monitoring is started.

8. A parameter intelligent monitoring device for nuclear power plants, characterized in that, The device includes: processor; Memory used to store processor-executable instructions; The processor is configured to perform the method according to any one of claims 1 to 6.

9. A non-volatile computer-readable storage medium storing computer program instructions thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the method described in any one of claims 1 to 6.

Images