CN110175756A - Nuclear power station information system operational safety method for early warning, device, equipment and medium - Google Patents
Nuclear power station information system operational safety method for early warning, device, equipment and medium Download PDFInfo
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Abstract
The invention belongs to nuclear power station informatization technical fields, a kind of nuclear power station information system operational safety method for early warning, device, computer equipment and storage medium suitable for the monitoring of information machine room dynamic environment is disclosed, method includes: distribution from designated equipment system acquisition information computer room information system relevant device, environmental parameter；Important parameter and anomaly parameter are chosen from the operating parameter；By the important parameter and anomaly parameter input nucleus power station information system operation risk prediction model, the risk classifications and risk class of the nuclear power station information system operation risk prediction model output, the corresponding risk class of each risk classifications are obtained；When the risk class corresponding to the risk classifications reaches predetermined level, warning information is sent to designated terminal.Nuclear power station can be improved to the judgement precision of security risk in nuclear power station information system operational safety method for early warning provided by the invention, while guaranteeing the timeliness of systematic risk feedback.
Description
Technical field
The present invention relates to nuclear power station informatization technical field more particularly to a kind of nuclear plant safety method for early warning safety
Method for early warning, device, computer equipment and storage medium.
Background technique
With resident power demand it is growing, it is desirable to provide more power supply sources.Nuclear power station is that one kind can
To utilize the power supply source that a large amount of thermal energy generate electricity caused by one or several power reactor.Although nuclear power station
Powerful power supply can be provided, but there are some potential safety problemss for nuclear power station.Such as, nuclear power station once occur nuclear fuel or
Nuke rubbish leakage, can generate serious safety hazard and environmental hazard.Thus, during the operation of nuclear power station information system, need
The operating parameter for each equipment being related to it carries out strict control, guarantees the safe operation of nuclear power station.
However, nuclear power station is during operation, there are multiple information communication systems, such as emergency broadcase system, audible alarm system
System, telephonic communication system, production network system etc., each system can generate a large amount of operating parameter.Operating parameter is usually
According to system property, the significance level of device attribute and divide, these operating parameters are divided into important parameter and insignificant
Parameter.In some cases, early warning can be just only generated when exception occurs in important parameter, although and abnormal insignificant parameter also can
It is processed, but there are certain hysteresis qualitys.And it will be unable to carry out in time by the caused systematic risk of the exception of insignificant parameter
Early warning generates biggish security risk to the normal operation of nuclear power station.
Summary of the invention
Based on this, it is necessary in view of the above technical problems, provide a kind of nuclear power station information system operational safety method for early warning,
Device, computer equipment and storage medium guarantee systematic risk feedback to improve nuclear power station to the judgement precision of security risk
Timeliness.
A kind of nuclear power station information system operational safety method for early warning, comprising:
Operating parameter is obtained from designated equipment system；
Important parameter and anomaly parameter are chosen from the operating parameter；
By the important parameter and anomaly parameter input nucleus power station information system operation risk prediction model, the core is obtained
The risk classifications and risk class of power station information system operation risk prediction model output, the corresponding risk of each risk classifications
Grade；
When the risk class corresponding to the risk classifications reaches predetermined level, warning information is sent to designated terminal.
A kind of nuclear power station information system operational safety prior-warning device, comprising:
Get parms module, for obtaining operating parameter from designated equipment system；
Extracting parameter module, for choosing important parameter and anomaly parameter from the operating parameter；
Model processing modules, for the important parameter and anomaly parameter input nucleus power station information system operation risk is pre-
Model is surveyed, the risk classifications and risk class of the nuclear power station information system operation risk prediction model output, Mei Gefeng are obtained
The corresponding risk class of dangerous type；
Risk reminding module, when reaching predetermined level for the risk class corresponding to the risk classifications, Xiang Zhiding
Terminal sends warning information.
A kind of computer equipment, including memory, processor and storage are in the memory and can be in the processing
The computer program run on device, the processor realize above-mentioned nuclear power station information system operation when executing the computer program
Safe early warning method.
A kind of computer readable storage medium, the computer-readable recording medium storage have computer program, the meter
Calculation machine program realizes above-mentioned nuclear power station information system operational safety method for early warning when being executed by processor.
Above-mentioned nuclear power station information system security method for early warning, device, computer equipment and storage medium, from designated equipment system
System obtains operating parameter, to obtain the initial data for judging risk.Important parameter and different is chosen from the operating parameter
Normal parameter, to reduce the treating capacity of operating parameter.The important parameter and anomaly parameter input nucleus power station information system are run
Risk forecast model obtains the risk classifications and risk class of the nuclear power station information system operation risk prediction model output,
The corresponding risk class of each risk classifications, to obtain calculated risk class, with the current risk level of determination.Work as institute
When stating risk class corresponding to risk classifications and reaching predetermined level, warning information is sent to designated terminal, to remind safety negative
Duty people is handled in time.Nuclear power station information system operational safety method for early warning provided by the invention, can be improved nuclear power station to safety
The judgement precision of risk, while guaranteeing the timeliness of systematic risk feedback.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below by institute in the description to the embodiment of the present invention
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the invention
Example, for those of ordinary skill in the art, without any creative labor, can also be according to these attached drawings
Obtain other attached drawings.
Fig. 1 is the application environment signal of one embodiment of the invention center power station information system operational safety method for early warning
Figure；
Fig. 2 is a flow diagram of one embodiment of the invention center power station information system operational safety method for early warning；
Fig. 3 is a flow diagram of one embodiment of the invention center power station information system operational safety method for early warning；
Fig. 4 is a flow diagram of one embodiment of the invention center power station information system operational safety method for early warning；
Fig. 5 is a flow diagram of one embodiment of the invention center power station information system operational safety method for early warning；
Fig. 6 is a flow diagram of one embodiment of the invention center power station information system operational safety method for early warning；
Fig. 7 is a structural schematic diagram of one embodiment of the invention center power station information system operational safety prior-warning device；
Fig. 8 is a schematic diagram of computer equipment in one embodiment of the invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are some of the embodiments of the present invention, instead of all the embodiments.Based on this hair
Embodiment in bright, every other implementation obtained by those of ordinary skill in the art without making creative efforts
Example, shall fall within the protection scope of the present invention.
Nuclear power station information system operational safety method for early warning provided in this embodiment, can be applicable to the application environment such as Fig. 1
In, wherein terminal is communicated by network with server-side.Wherein, terminal includes but is not limited to various personal computers, notes
This computer, smart phone, tablet computer and portable wearable device.Server-side can be either multiple with independent server
The server cluster of server composition is realized.
In one embodiment, as shown in Fig. 2, a kind of nuclear power station information system operational safety method for early warning is provided, with the party
Method is illustrated for applying the server-side in Fig. 1, is included the following steps:
S10, operating parameter is obtained from designated equipment system；
S20, important parameter and anomaly parameter are chosen from the operating parameter；
S30, by the important parameter and anomaly parameter input nucleus power station information system operation risk prediction model, obtain institute
The risk classifications and risk class of the output of nuclear power station information system operation risk prediction model are stated, each risk classifications are one corresponding
Risk class；
When S40, the risk class corresponding to the risk classifications reach predetermined level, early warning letter is sent to designated terminal
Breath.
In the present embodiment, designated equipment system can refer to one or more information systems in nuclear power station, such as can be and answer
One or more of anxious broadcast system, audible alarm system, telephonic communication system, production network system etc..In one example,
Nuclear power information system power & environment supervision system includes integrated data processing system, alarm processing system, platform operating system and alarm
The subsystems such as supplying system.Multiple operating parameters can be obtained from each designated equipment system.It such as, can be from data processing system
The operating parameter that system obtains includes multiple ON/OFF amount signals and analog quantity information.Wherein, ON/OFF amount signal can be used for examining
The variation of the working condition of some component in examining system, such as switch are in off state from open state transformation or flow meters
Switch to dormant state from working condition.
Operating parameter may include information machine room information system relevant device with electrical parameter or environmental parameter.All
In operating parameter, the operating parameter of part is used to detect the working condition of emphasis equipment, and the operating parameter of this part can be marked
It is denoted as important parameter.For example, the operating parameters such as temperature, pressure of some equipment for detection system, these operating parameters are to being
The stability influence of system is great, once being abnormal, then there may be serious accidents.These operating parameters are then defined as
Important parameter.Important parameter can include but is not limited to the power supply state of running equipment, backup accumulator status, operation machine
The air-conditioning state in room, the temperature and humidity state in computer room, equipment machine room gate inhibition's state.And for other operating parameters, it can be pre-
One variation range is first set, if the operating parameter is more than or less than the variation range, assert that the operating parameter is in different
Normal state, as anomaly parameter.Here, anomaly parameter refers to that abnormal insignificant parameter occurs in parameter value.Important parameter
Parameter value can be normally, be also possible to abnormal.In the important parameter and anomaly parameter being selected, usual situation
Under, the quantity of important parameter is a constant, and the quantity of anomaly parameter can then generate the fluctuation of certain row.When system is in less
When stable state, anomaly parameter would generally be increased significantly.
Nuclear power station information system operation risk prediction model can be to the important parameter and anomaly parameter got at
Reason, generates corresponding prediction data, i.e. risk classifications and corresponding risk class.In one example, nuclear power station information system is transported
The prediction data of row risk forecast model output is as shown in table 1.
The risk classifications and risk class of 1 nuclear power station information system operation risk prediction model of table output
| Serial number | Risk classifications | Risk class |
| 1 | A | In |
| 2 | B | It is low |
| 3 | C | It is low |
Wherein, nuclear power station information system operation risk prediction model can predict at least one risk classifications.Risk class
Type can be related to equipment fault risk, be operating abnormally risk and system cumulative bad risk etc..Every kind of risk classifications can basis
It needs to divide and locates different risk class, can such as be divided into high, medium and low three risk class, or normal and abnormal two wind
Dangerous grade.
Different technological means building nuclear power station information system operation risk prediction models can be used.Such as, it can be based on
The operation logic of nuclear power station information system and related equipment operation characteristic construct corresponding nuclear power station information system operation
Risk forecast model.For example, risk point first can be generated based on the service impact range of each information system, including consequent malfunction,
That is then theoretical parameter value carries out adaptability amendment to above-mentioned theory parameter value according to the parameter value of actual measurement.In some cases
Under, nuclear power station information system operation risk prediction model can be computer based simulation computation model.
In other cases, nuclear power station information system operation risk prediction model can also be recorded based on the operation of history
And it constructs.The operation record of history includes the record of the operating parameter of the specified running equipment system of multiple periods.It can be with
The risk class that the period event is assessed according to the warning information of the period and actual processing scheme, carries out forming one
A risk assessment sample.The corresponding sample label (including risk classifications and grade) of each risk assessment sample.And then it can
To generate a large amount of risk assessment sample.Suitable machine learning model is selected to be trained above-mentioned risk assessment sample, it can
To obtain required nuclear power station information system operation risk prediction model.During model training, in order to simplify operation, subtract
Few calculation amount, for normal insignificant operating parameter (i.e. neither important parameter is also not anomaly parameter), parameter value
It can be set to 0 or 1.
It, can be with after the risk classifications and risk class for obtaining the output of nuclear power station information system operation risk prediction model
Process is reminded in setting alarm, realizes the auto-alarming of system.Such as, when the risk classifications of prediction reach predetermined level, then Xiang Zhiding
Terminal sends warning information.Specifically, predetermined level corresponding to different risk classifications can be different.Such as, risk class
The predetermined level of type A can be set to " in ", the predetermined level of risk classifications B can be set to "high".Risk classifications A's is default
Grade can be set to " in ", it is meant that, only when the risk class of risk classifications A meets or exceeds predetermined level, then can
Warning information is sent to designated terminal.In other words, when the risk class of risk classifications A is " in " or when "high", can Xiang Zhiding
Terminal sends warning information, and when the risk class of risk classifications A is " low ", then warning information is not sent to designated terminal.
Warning information may include the risk classifications and risk class that nuclear power station information system operation risk prediction model is exported.
Here, designated terminal can refer to the terminal device of central control room, be also possible to tie up with nuclear power station safety total system
Fixed personal device terminal, such as the mobile phone of safety director.
In step S10-S40, operating parameter is obtained from designated equipment system, to obtain the original number for judging risk
According to.Important parameter and anomaly parameter are chosen, from the operating parameter to reduce the treating capacity of operating parameter.By the important ginseng
Several and anomaly parameter input nucleus power station information system operation risk prediction model, obtains the nuclear power station information system operation risk
The risk classifications and risk class of prediction model output, the corresponding risk class of each risk classifications are calculated to obtain
Risk class, with the current risk level of determination.When the risk class corresponding to the risk classifications reaches predetermined level, to
Designated terminal sends warning information, to remind safety director to handle in time.
Optionally, as shown in figure 3, step S20 includes:
S201, judge whether the operating parameter includes important logo；
If S202, the operating parameter include important logo, it is determined that the operating parameter comprising important logo is attached most importance to
Parameter is wanted, and chooses the important parameter；
If S203, the operating parameter do not include important logo, the operating parameter for not including important logo is read
Parameter value and preset parameter range；
Whether the parameter value for the operating parameter that S204, judgement do not include important logo is in the parameter preset
In range；
If the parameter value of S205, the operating parameter for not including important logo are not at the preset parameter range
It is interior, it is determined that the operating parameter not comprising important logo corresponding with the parameter value is anomaly parameter, and it is different to choose this
Normal parameter.
In the present embodiment, special process flow can be set, the operating parameter obtained from designated equipment system is carried out
Screening reduces nuclear power station information system operation risk prediction model to the treating capacity of operating parameter.For important parameter, its own
Important logo is contained, the form of the important logo can be set according to demand.Each operating parameter may include one
A importance mark, for example, the operating parameter contains important logo if the value of importance mark is "Yes"；If this is heavy
The value of the property wanted mark is "No", then the operating parameter does not include important logo.When being screened to operating parameter, if operation ginseng
Number includes important logo, then chooses the operating parameter (i.e. important parameter).And the operating parameter for not including important logo, then
Check whether its parameter value is in its preset parameter area.If parameter value is in preset parameter area, the operation
Parameter is normal parameter.If parameter value is not in preset parameter area, which is anomaly parameter.At this point, choosing
The anomaly parameter.Such as, the parameter value of an operating parameter be 9, preset parameter range be 1~5,9 be not at 1~5 range it
It is interior.Thus, which is anomaly parameter.It should be noted that here, if operating parameter is important parameter, but it is joined
The operating parameter will be divided into important parameter at this time by numerical exception, rather than anomaly parameter.
In step S201-S205, judge whether the operating parameter includes important logo, to detect the important of operating parameter
Mark.If the operating parameter includes important logo, it is determined that the operating parameter is important parameter, and chooses the important ginseng
Number, to obtain the important parameter for being used for calculation risk grade.If the operating parameter does not include important logo, the fortune is read
The parameter value and preset parameter range of row parameter, to obtain the information for the operating parameter for not including important logo.Judge the ginseng
Whether numerical value is in the preset parameter range, to judge whether the operating parameter for not including important logo is abnormal.If described
Parameter value is not in the preset parameter range, it is determined that and the operating parameter is anomaly parameter, and chooses the anomaly parameter,
To obtain the anomaly parameter for being used for calculation risk grade.
Optionally, as shown in figure 4, before step S30, comprising:
S31, history data is obtained；
S32, the history data is handled as multiple training samples according to preset processing rule；
S33, it will be trained in the preset prediction model of the multiple training sample input, after training described in acquisition
Nuclear power station information system operation risk prediction model.
In the present embodiment, history data can refer to the first operation data of nuclear power station.It in some cases, can also be with
Using the detection data with current nuclear power station same type, such as using the operation data in the power station of identical control system.
Preset processing rule is for being the training sample that can be used for model training by history data processing.For example,
By preset duration by history data cutting be multiple training samples, then from the operating parameter in each training sample
Extract important parameter and anomaly parameter.Here, preset duration can be 1 hour, 0.5 hour or other setting times.
In one example, a training sample may be expressed as:
The operating parameter that training sample after table 2 is extracted is included
| Operating parameter | Time point 1 | Time point 2 | …… | Time point x |
| Important parameter 1 | Parameter value a11 | Parameter value a12 | …… | Parameter value a1x |
| Important parameter 2 | Parameter value a21 | Parameter value a22 | …… | Parameter value a2x |
| …… | …… | …… | …… | …… |
| Important parameter m | Parameter value am1 | Parameter value am2 | …… | Parameter value amx |
| Anomaly parameter 1 | Parameter value b11 | Parameter value b12 | …… | Parameter value b1x |
| Anomaly parameter 2 | Parameter value b21 | Parameter value b22 | …… | Parameter value b2x |
| …… | …… | …… | …… | …… |
| Anomaly parameter n | Parameter value bn1 | Parameter value bn2 | …… | Parameter value bnx |
Each training sample further comprises corresponding risk class label.Training sample can correspond to multiple and different types
Risk class label.Risk class label can according to the event that the time of origin of training sample occurs within rear a period of time and
Its risk class or subsequent processing grade are determined.It can be determined according to the actual situation in rear a period of time, such as
It can be 2 hours, 5 hours or other setting times.Corresponding grade corresponding relationship can be set, in order to quickly determine to instruct
Practice the risk class label of sample.Such as, subsequent processing grade is " level-one ", and corresponding risk class is " low ".
In step S31-S33, history data is obtained, to obtain the primary data for training pattern.According to default
Processing rule the history data is handled as multiple training samples, it is raw to be pre-processed to history data
At training sample.The multiple training sample is inputted in preset prediction model and is trained, after training described in acquisition
Nuclear power station information system operation risk prediction model, to obtain processing model (the i.e. nuclear power station information for being used for estimated risk grade
System operation risk prediction model).
Optionally, as shown in figure 5, step S30 includes:
S301, the acquisition nuclear power station information system operation risk prediction model are included corresponding with the risk classifications
Empirical formula；
S302, the important parameter and anomaly parameter are handled according to the empirical formula, obtains the wind
The corresponding risk class of dangerous type.
In the present embodiment, nuclear power station information system operation risk prediction model is preset with one or more experiences and calculates public affairs
Formula, each empirical formula are corresponding with a risk classifications.
Empirical formula may include two component parts, and first part includes important parameter, i.e., important parameter is to this
Risk classifications have a direct impact；Second part includes insignificant parameter, and insignificant parameter is the subset of anomaly parameter, these are non-
Important parameter can generate the risk classifications to be influenced indirectly.Important parameter can be determined according to the operation logic of system, and
Insignificant parameter then can be according to first operation data, and analyzing in data with the risk classifications there is the operation of correlation to join
Number, and determine it as insignificant parameter.Here, the correlation that operating parameter has with the risk classifications can be positive
It closes, is also possible to negative correlation.
After the impact factor (i.e. above-mentioned important parameter and insignificant parameter) for determining risk classifications, to impact factor
The data being related to are fitted, and obtain optimal fitting formula, as empirical formula.
After obtaining empirical formula, rule of thumb calculation formula handles important parameter and anomaly parameter,
Risk class corresponding with risk classifications can be obtained.Here, risk class can be indicated with the grade serial number of discrete type, can also
Numerical value to be continuous type indicates.
In step S301-S302, obtain that the nuclear power station information system operation risk prediction model included with it is described
The corresponding empirical formula of risk classifications, to obtain matched empirical formula.According to the empirical formula to institute
It states important parameter and anomaly parameter is handled, the corresponding risk class of the risk classifications is obtained, to assess current system
Risk level.
Optionally, as shown in fig. 6, step S40 includes:
S401, the warning information is sent to the designated terminal by the first communication channel；
S402, when not receiving the feedback information that the designated terminal is sent within the first specified time, pass through second
Communication channel sends the warning information to the designated terminal.
In the present embodiment, the first communication channel is used to send warning information to designated terminal, and adoptable mode includes
But it is not limited to the short message of foreign operator, phone, mail.Second communication channel can be the data different from the first communication channel
Transmission mode, adoptable mode include but is not limited to internal note system, content mail system.First specified time can root
It is set according to actual needs.The first different specified times can be set in different risk classifications；Same risk classifications, but wind
Dangerous grade is different, and the first different specified times also can be set.The feedback information that designated terminal is sent includes but is not limited to back
Multiple short message, phone reply, mail receipt.
In step S401, the warning information is sent to the designated terminal by the first communication channel, to issue first
Secondary prompting.It is described when not received within the first specified time (length of first specified time can be set according to demand)
When the feedback information that designated terminal is sent, the warning information is sent to the designated terminal by the second communication channel, with hair
It reminds for second out.
Optionally, after step S402, further includes:
S403, when not receiving the feedback information that the designated terminal is sent within the second specified time, then by the
One communication channel and/or the second communication channel send the warning information to standby terminal.
In the present embodiment, if after issuing second of prompting to designated terminal using the second communication channel, the specified end
End, which is not sent within the second specified time (length of second specified time can be set according to demand) to system, feeds back
Information needs at this point, system can not determine whether receive the warning information using the staff of designated terminal to spare end
End sends warning information.Here, can be different from the staff of designated terminal is used using the staff of standby terminal,
It also can be with identical.
In step S403, after issuing second of prompting to designated terminal, do not received within the second specified time
When the feedback information that the designated terminal is sent, then sent out by the first communication channel and/or the second communication channel to standby terminal
The warning information is sent, is reminded with issuing third time.
It should be understood that the size of the serial number of each step is not meant that the order of the execution order in above-described embodiment, each process
Execution sequence should be determined by its function and internal logic, the implementation process without coping with the embodiment of the present invention constitutes any limit
It is fixed.
In one embodiment, a kind of nuclear plant safety prior-warning device is provided, the nuclear plant safety prior-warning device and above-mentioned reality
A center power station information system operational safety method for early warning is applied to correspond.As shown in fig. 7, the nuclear plant safety prior-warning device packet
Include the module 10 that gets parms, extracting parameter module 20, model processing modules 30 and risk reminding module 40.Each functional module is detailed
It is described as follows:
The module that gets parms 10, for obtaining operating parameter from designated equipment system；
Extracting parameter module 20, for choosing important parameter and anomaly parameter from the operating parameter；
Model processing modules 30 are used for the important parameter and anomaly parameter input nucleus power station information system operation risk
Prediction model obtains the risk classifications and risk class of the nuclear power station information system operation risk prediction model output, each
Risk classifications correspond to a risk class；
Risk reminding module 40, when reaching predetermined level for the risk class corresponding to the risk classifications, to finger
Determine terminal and sends warning information.
Optionally, extracting parameter module 20 includes:
Recognition unit is identified, for judging whether the operating parameter includes important logo；
Important parameter unit is chosen, if including important logo for the operating parameter, it is determined that include important logo
The operating parameter is important parameter, and chooses the important parameter；
Parameters unit is read, if not including important logo for the operating parameter, reads and does not include important logo
The parameter value and preset parameter range of the operating parameter；
Parameter judging unit, for judging whether the parameter value of the operating parameter not comprising important logo is in
In the preset parameter range；
Anomaly parameter unit is chosen, if the parameter value of the operating parameter for not including important logo is not at
In the preset parameter range, it is determined that the operating parameter not comprising important logo corresponding with the parameter value is abnormal
Parameter, and choose the anomaly parameter.
Optionally, nuclear plant safety prior-warning device further includes model construction module, which includes:
Historical data unit is obtained, for obtaining history data；
Training sample unit is generated, for handling the history data for multiple instructions according to preset processing rule
Practice sample；
Training pattern unit is trained for inputting the multiple training sample in preset prediction model, training
After obtain the nuclear power station information system operation risk prediction model.
Optionally, model processing modules 30 include:
Obtain formula cells, for obtain that the nuclear power station information system operation risk prediction model included with it is described
The corresponding empirical formula of risk classifications；
Risk Calculation unit, for according to the empirical formula to the important parameter and anomaly parameter at
Reason, obtains the corresponding risk class of the risk classifications.
Optionally, risk reminding module 40 includes:
First transmission unit, for sending the warning information to the designated terminal by the first communication channel；
Second transmission unit, for when the feedback information for not receiving the designated terminal transmission within the first specified time
When, the warning information is sent to the designated terminal by the second communication channel.
Optionally, risk reminding module 40 further include:
Third transmission unit, for when the feedback information for not receiving the designated terminal transmission within the second specified time
When, then the warning information is sent to standby terminal by the first communication channel and/or the second communication channel.
Specific restriction about nuclear plant safety prior-warning device may refer to run above for nuclear power station information system
The restriction of safe early warning method, details are not described herein.Modules in above-mentioned nuclear plant safety prior-warning device can whole or portion
Divide and is realized by software, hardware and combinations thereof.Above-mentioned each module can be embedded in the form of hardware or independently of computer equipment
In processor in, can also be stored in a software form in the memory in computer equipment, in order to processor calling hold
The corresponding operation of the above modules of row.
In one embodiment, a kind of computer equipment is provided, which can be server, internal junction
Composition can be as shown in Figure 8.The computer equipment include by system bus connect processor, memory, network interface and
Database.Wherein, the processor of the computer equipment is for providing calculating and control ability.The memory packet of the computer equipment
Include non-volatile memory medium, built-in storage.The non-volatile memory medium is stored with operating system, computer program and data
Library.The built-in storage provides environment for the operation of operating system and computer program in non-volatile memory medium.The calculating
The database of machine equipment is for storing data involved in nuclear power station information system operational safety method for early warning.The computer equipment
Network interface be used to communicate with external terminal by network connection.To realize one when the computer program is executed by processor
Seed nucleus power station information system operational safety method for early warning.
In one embodiment, a kind of computer equipment is provided, including memory, processor and storage are on a memory
And the computer program that can be run on a processor, processor perform the steps of when executing computer program
Operating parameter is obtained from designated equipment system；
Important parameter and anomaly parameter are chosen from the operating parameter；
By the important parameter and anomaly parameter input nucleus power station information system operation risk prediction model, the core is obtained
The risk classifications and risk class of power station information system operation risk prediction model output, the corresponding risk of each risk classifications
Grade；
When the risk class corresponding to the risk classifications reaches predetermined level, warning information is sent to designated terminal.
In one embodiment, a kind of computer readable storage medium is provided, computer program is stored thereon with, is calculated
Machine program performs the steps of when being executed by processor
Operating parameter is obtained from designated equipment system；
Important parameter and anomaly parameter are chosen from the operating parameter；
By the important parameter and anomaly parameter input nucleus power station information system operation risk prediction model, the core is obtained
The risk classifications and risk class of power station information system operation risk prediction model output, the corresponding risk of each risk classifications
Grade；
When the risk class corresponding to the risk classifications reaches predetermined level, warning information is sent to designated terminal.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, the computer program can be stored in a non-volatile computer
In read/write memory medium, the computer program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein,
To any reference of memory, storage, database or other media used in each embodiment provided herein,
Including non-volatile and/or volatile memory.Nonvolatile memory may include read-only memory (ROM), programming ROM
(PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM) or flash memory.Volatile memory may include
Random access memory (RAM) or external cache.By way of illustration and not limitation, RAM is available in many forms,
Such as static state RAM (SRAM), dynamic ram (DRAM), synchronous dram (SDRAM), double data rate sdram (DDRSDRAM), enhancing
Type SDRAM (ESDRAM), synchronization link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM
(RDRAM), direct memory bus dynamic ram (DRDRAM) and memory bus dynamic ram (RDRAM) etc..
It is apparent to those skilled in the art that for convenience of description and succinctly, only with above-mentioned each function
Can unit, module division progress for example, in practical application, can according to need and by above-mentioned function distribution by different
Functional unit, module are completed, i.e., the internal structure of described device is divided into different functional unit or module, more than completing
The all or part of function of description.
Embodiment described above is merely illustrative of the technical solution of the present invention, rather than its limitations；Although referring to aforementioned reality
Applying example, invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each
Technical solution documented by embodiment is modified or equivalent replacement of some of the technical features；And these are modified
Or replacement, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution should all
It is included within protection scope of the present invention.
Claims (14)
1. a kind of nuclear power station information system operational safety method for early warning characterized by comprising
Operating parameter is obtained from designated equipment system；
Important parameter and anomaly parameter are chosen from the operating parameter；
By the important parameter and anomaly parameter input nucleus power station information system operation risk prediction model, the nuclear power station is obtained
The risk classifications and risk class of information system operation risk prediction model output, corresponding risk of each risk classifications etc.
Grade；
When the risk class corresponding to the risk classifications reaches predetermined level, warning information is sent to designated terminal.
2. nuclear power station information system operational safety method for early warning as described in claim 1, which is characterized in that described from the fortune
Important parameter and anomaly parameter are chosen in row parameter, comprising:
Judge whether the operating parameter includes important logo；
If the operating parameter includes important logo, it is determined that the operating parameter comprising important logo is important parameter, and
Choose the important parameter；
If the operating parameter do not include important logo, read do not include important logo the operating parameter parameter value and
Preset parameter range；
Whether the parameter value that judgement does not include the operating parameter of important logo is in the preset parameter range；
If the parameter value for not including the operating parameter of important logo is not in the preset parameter range, it is determined that
The operating parameter not comprising important logo corresponding with the parameter value is anomaly parameter, and chooses the anomaly parameter.
3. nuclear power station information system operational safety method for early warning as described in claim 1, which is characterized in that it is described will be described heavy
Parameter and anomaly parameter input nucleus power station information system operation risk prediction model are wanted, the nuclear power station information system operation is obtained
Before the risk classifications and risk class of risk forecast model output, comprising:
Obtain history data；
The history data is handled as multiple training samples according to preset processing rule；
The multiple training sample is inputted in preset prediction model and is trained, the nuclear power station letter is obtained after training
Breath system operation risk prediction model.
4. nuclear power station information system operational safety method for early warning as described in claim 1, which is characterized in that it is described will be described heavy
Parameter and anomaly parameter input nucleus power station information system operation risk prediction model are wanted, the nuclear power station information system operation is obtained
The risk classifications and risk class of risk forecast model output, comprising:
Obtain the experience meter corresponding with the risk classifications that the nuclear power station information system operation risk prediction model is included
Calculate formula；
The important parameter and anomaly parameter are handled according to the empirical formula, it is corresponding to obtain the risk classifications
Risk class.
5. nuclear power station information system operational safety method for early warning as described in claim 1, which is characterized in that described to work as the wind
When risk class corresponding to dangerous type reaches predetermined level, warning information is sent to designated terminal, comprising:
The warning information is sent to the designated terminal by the first communication channel；
When not receiving the feedback information that the designated terminal is sent within the first specified time, by the second communication channel to
The designated terminal sends the warning information.
6. nuclear power station information system operational safety method for early warning as claimed in claim 5, which is characterized in that described when first
When not receiving the feedback information that the designated terminal is sent in specified time, by the second communication channel to the designated terminal
After sending the warning information, further includes:
When not receiving the feedback information that the designated terminal is sent within the second specified time, then pass through the first communication channel
And/or second communication channel to standby terminal send the warning information.
7. a kind of nuclear power station information system operational safety prior-warning device characterized by comprising
Get parms module, for obtaining operating parameter from designated equipment system；
Extracting parameter module, for choosing important parameter and anomaly parameter from the operating parameter；
Model processing modules, for the important parameter and anomaly parameter input nucleus power station information system operation risk to be predicted mould
Type obtains the risk classifications and risk class of the nuclear power station information system operation risk prediction model output, each risk class
Type corresponds to a risk class；
Risk reminding module, when reaching predetermined level for the risk class corresponding to the risk classifications, to designated terminal
Send warning information.
8. nuclear power station information system operational safety prior-warning device as claimed in claim 7, which is characterized in that the extracting parameter
Module includes:
Recognition unit is identified, for judging whether the operating parameter includes important logo；
Important parameter unit is chosen, if including important logo for the operating parameter, it is determined that comprising described in important logo
Operating parameter is important parameter, and chooses the important parameter；
Parameters unit is read, if not including important logo for the operating parameter, reads and does not include the described of important logo
The parameter value and preset parameter range of operating parameter；
Parameter judging unit, for judging whether the parameter value of the operating parameter not comprising important logo is in described
In preset parameter range；
Choose anomaly parameter unit, if the parameter value of the operating parameter for not including important logo be not at it is described
In preset parameter range, it is determined that the operating parameter not comprising important logo corresponding with the parameter value is abnormal ginseng
Number, and choose the anomaly parameter.
9. nuclear power station information system operational safety prior-warning device as claimed in claim 7, further includes model construction module, described
Model construction module includes:
Historical data unit is obtained, for obtaining history data；
Training sample unit is generated, for handling the history data for multiple trained samples according to preset processing rule
This；
Training pattern unit is trained for inputting the multiple training sample in preset prediction model, and training finishes
After obtain the nuclear power station information system operation risk prediction model.
10. nuclear power station information system operational safety prior-warning device as claimed in claim 7, which is characterized in that at the model
Managing module includes:
Formula cells are obtained, it is being included with the risk for obtaining the nuclear power station information system operation risk prediction model
The corresponding empirical formula of type；
Risk Calculation unit is obtained for being handled according to the empirical formula the important parameter and anomaly parameter
Obtain the corresponding risk class of the risk classifications.
11. nuclear power station information system operational safety prior-warning device as claimed in claim 7, which is characterized in that the risk mentions
Awake module, comprising:
First transmission unit, for sending the warning information to the designated terminal by the first communication channel；
Second transmission unit, for when not receiving the feedback information that the designated terminal is sent within the first specified time,
The warning information is sent to the designated terminal by the second communication channel.
12. nuclear power station information system operational safety prior-warning device as claimed in claim 11, which is characterized in that the risk mentions
Awake module further include:
Third transmission unit, for when not receiving the feedback information that the designated terminal is sent within the second specified time,
The warning information is then sent to standby terminal by the first communication channel and/or the second communication channel.
13. a kind of computer equipment, including memory, processor and storage are in the memory and can be in the processor
The computer program of upper operation, which is characterized in that the processor realized when executing the computer program as claim 1 to
Any one of 6 nuclear power station information system operational safety method for early warning.
14. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists
In realization nuclear power station information system as described in any one of claim 1 to 6 is run when the computer program is executed by processor
Safe early warning method.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104425046A (en) * | 2013-08-31 | 2015-03-18 | 中广核工程有限公司 | Method and system for quantizing operation security indexes of nuclear power station |
| CN106773993A (en) * | 2017-01-04 | 2017-05-31 | 国网山东省电力公司菏泽供电公司 | Field data acquiring terminal and system |
| US20180114176A1 (en) * | 2015-03-31 | 2018-04-26 | Mitsubishi Heavy Industries, Ltd. | Work planning system, work planning method, decision-making support system, computer program, and storage medium |
| CN108108839A (en) * | 2017-12-18 | 2018-06-01 | 华北电力大学 | Grid information system equipment state method for early warning based on reverse Fuzzy Level Analytic Approach |
-
2019
- 2019-05-07 CN CN201910376639.2A patent/CN110175756B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104425046A (en) * | 2013-08-31 | 2015-03-18 | 中广核工程有限公司 | Method and system for quantizing operation security indexes of nuclear power station |
| US20180114176A1 (en) * | 2015-03-31 | 2018-04-26 | Mitsubishi Heavy Industries, Ltd. | Work planning system, work planning method, decision-making support system, computer program, and storage medium |
| CN106773993A (en) * | 2017-01-04 | 2017-05-31 | 国网山东省电力公司菏泽供电公司 | Field data acquiring terminal and system |
| CN108108839A (en) * | 2017-12-18 | 2018-06-01 | 华北电力大学 | Grid information system equipment state method for early warning based on reverse Fuzzy Level Analytic Approach |
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