CN104238501B - A kind of alarm data processing method and processing device of refinery system - Google Patents
A kind of alarm data processing method and processing device of refinery system Download PDFInfo
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- CN104238501B CN104238501B CN201410418782.0A CN201410418782A CN104238501B CN 104238501 B CN104238501 B CN 104238501B CN 201410418782 A CN201410418782 A CN 201410418782A CN 104238501 B CN104238501 B CN 104238501B
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The invention provides a kind of alarm data processing method and processing device of refinery system, method includes：The alarm data of refinery system is received, alarm data includes the mark data of each sensor in refinery system, the supplemental characteristic of each sensor collection；According to each sensor identification data genaration node alarming processing data, sensor group alarming processing data；Supplemental characteristic according to the collection of each sensor generates sensor abnormality alarming processing data, separated sensor alarming processing data；The alarm data result of refinery system is generated according to node alarming processing data, sensor group alarming processing data, sensor abnormality alarming processing data and single sensor alarms processing data.Pin of the present invention judges to form refinery procedures system intelligent alarm with reference to separated sensor alarm method, sensor group alarm method and sensor itself extremely, reduces redundant warning, false alarm and fails to report police, improves the treatment effeciency of operating personnel and the security of system.
Description
Technical field
The present invention relates to monitoring technology field, especially with regard to alarm data monitoring technology during refinery, concretely
It is a kind of alarm data processing method and processing device of refinery system.
Background technology
Warning system plays vital effect during refinery, and operator is looked into according to the alarm data of warning system
Look for alarm cause and take appropriate measures, after abnormal elimination, device returns to normal condition.
Alarm method during the refinery of prior art lacks consideration sensor for the isolated data of single-sensor
Between, the oneself state of the correlation between equipment and sensor.During the refinery of Frequent Accidents, due to sensor
Fault, information transfer are abnormal, personnel's maloperation hinders the redundant warning, false alarm and fail to report police that the factors such as alarm cause, not only
Reduce the treatment effeciency of operating personnel, also there is great potential safety hazard.
Content of the invention
For reducing redundant warning, false alarm and police being failed to report, the treatment effeciency of operating personnel and the security of system is improved, this
Inventive embodiments provide a kind of alarm data processing method of refinery system, and method includes：
The alarm data of refinery system is received, the alarm data includes the mark number of each sensor in refinery system
Supplemental characteristic according to the collection of, each sensor；
Judge that the node data of the refinery system included in the alarm data is according to each sensor identification data
No complete, generate node alarming processing data；
Whether the data of each sensor group judged to include in the alarm data according to each sensor identification data
Completely, sensor group alarming processing data are generated；
Supplemental characteristic and default sensor abnormality parameter value generation sensor abnormality according to each sensor collection
Alarming processing data；
Supplemental characteristic and default alarm threshold value generation separated sensor alarming processing according to each sensor collection
Data；
According to the node alarming processing data, sensor group alarming processing data, sensor abnormality alarming processing data
And single sensor alarms processing data generates the alarm data result of refinery system.
Additionally, present invention also offers a kind of alarm data processing meanss of refinery system, device includes：
Data reception module, for receiving the alarm data of refinery system, the alarm data is included in refinery system
The mark data of each sensor, the supplemental characteristic of each sensor collection；
Node warning processing module, for judged to include in the alarm data according to each sensor identification data
Whether the node data of refinery system is complete, generates node alarming processing data；
Sensor group warning processing module, for judging to wrap in the alarm data according to each sensor identification data
Whether the data of each sensor group for containing are complete, generate sensor group alarming processing data；
Sensor abnormality warning processing module, for supplemental characteristic and default sensing according to each sensor collection
Device anomaly parameter value generates sensor abnormality alarming processing data；
Separated sensor warning processing module, for supplemental characteristic and default warning according to each sensor collection
Threshold value generates separated sensor alarming processing data；
Alarm result generation module, for according to the node alarming processing data, sensor group alarming processing data, biography
Sensor abnormality alarming processing data and single sensor alarms processing data generate the alarm data result of refinery system.
The present invention is analyzed for process pipe instrument flow chart, sets up corresponding Bayesian network model, while knot
Close separated sensor alarm method, sensor group alarm method and sensor itself to judge extremely to form refinery procedures system intelligence
Alarm, reduces redundant warning, false alarm and fails to report police, improve the treatment effeciency of operating personnel and the security of system.
It is that the above and other objects, features and advantages of the present invention can be become apparent, preferred embodiment cited below particularly,
And coordinate institute's accompanying drawings, it is described in detail below.
Description of the drawings
In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
Accompanying drawing to be used needed for technology description is had to be briefly described, it should be apparent that, drawings in the following description are only this
Some embodiments of invention, for those of ordinary skill in the art, on the premise of not paying creative work, acceptable
Other accompanying drawings are obtained according to these accompanying drawings.
Fig. 1 is a kind of flow chart of the alarm data processing method of refinery system disclosed by the invention；
Fig. 2 is a kind of block diagram of the alarm data processing meanss of refinery system disclosed by the invention；
The flow chart that Fig. 3 carries out the embodiment of refinery procedures system intelligent alarm for the present invention；
Fig. 4 is the building-block of logic of the coupling alarm based on Bayesian network in the present embodiment；
Fig. 5 is that the embodiment of the present invention is set up previously according to the process pipe instrument flow chart for often decompressing flow process during refinery
Bayesian network model；
Fig. 6 is the parameter simulation figure of the embodiment of the present invention；
Fig. 7 is the building-block of logic of the alarm method of sensor group in the present embodiment；
Fig. 8 is sensor abnormality alarming processing building-block of logic；
Fig. 9 alerts building-block of logic for separated sensor.
Specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation is described, it is clear that described embodiment is only a part of embodiment of the present invention, rather than whole embodiments.It is based on
Embodiment in the present invention, it is every other that those of ordinary skill in the art are obtained under the premise of creative work is not made
Embodiment, belongs to the scope of protection of the invention.
As shown in figure 1, for a kind of alarm data processing method of refinery system disclosed by the invention, including：
Step S101, receives the alarm data of refinery system, and the alarm data includes each sensor in refinery system
Mark data, each sensor collection supplemental characteristic；
Step S102, the section of the refinery system judged to include in the alarm data according to each sensor identification data
Whether point data is complete, generates node alarming processing data；
Specifically, judged whether comprising last section of refinery system in alarm data according to the mark data of each sensor
Whether the node data of point is complete with the node data that judges refinery system.
Step S103, each sensor group judged to include in the alarm data according to each sensor identification data
Whether data are complete, generate sensor group alarming processing data；
Whether the mark data according to each sensor judges the data of each sensor group in alarm data comprising the sensor
The sensing data of last sensor of group, judgement is that then the sensor group data are complete.
Step S104, according to supplemental characteristic and the default sensor abnormality parameter value generation biography of each sensor collection
Sensor abnormality alarming processing data；
Step S105, according to supplemental characteristic and the default alarm threshold value generation separated sensor of each sensor collection
Alarming processing data；
Step S106, according to the node alarming processing data, sensor group alarming processing data, sensor abnormality alarm
Processing data and the alarm data result of separated sensor alarming processing data genaration refinery system.
Methods described also includes：Pre-stored sets up expression node pass according to the process pipe instrument flow chart during refinery
The Bayesian network model of system.In step S102, when judging that the node data of refinery system is complete, based on the Bayesian network that sets up
Network carries out coupling alarming processing.
Additionally, as shown in Fig. 2 the invention also discloses a kind of alarm data processing meanss of refinery system, device includes：
Data reception module 201, for receiving the alarm data of refinery system, the alarm data is included in refinery system
Each sensor mark data, each sensor collection supplemental characteristic；
Node warning processing module 202, for judging to wrap in the alarm data according to each sensor identification data
Whether the node data of the refinery system for containing is complete, generates node alarming processing data；
Sensor group warning processing module 203, for judging the alarm data according to each sensor identification data
In the data of each sensor group that include whether complete, generate sensor group alarming processing data；
Sensor abnormality warning processing module 204, for according to the supplemental characteristic of each sensor collection and default
Sensor abnormality parameter value generates sensor abnormality alarming processing data；
Separated sensor warning processing module 205, for according to the supplemental characteristic of each sensor collection and default
Alarm threshold value generates separated sensor alarming processing data；
Alarm result generation module 206, for according to the node alarming processing data, sensor group alarming processing number
Knot is processed according to the alarm data of, sensor abnormality alarming processing data and separated sensor alarming processing data genaration refinery system
Really.
With reference to specific embodiment, technical scheme is described in further details：
As shown in figure 3, being the stream of the embodiment for carrying out refinery procedures system intelligent alarm according to technical scheme
Cheng Tu.
According to aforementioned, the alarm data of refinery system when the present invention is embodied as, is received, alarm starts, according to alarm
The mark data of each sensor included in data, judges whether the node data of refinery system included in alarm data is complete
Whole, according to judged result, the node alarming processing data of response are generated, that is, step S301, S302 in Fig. 3 is carried out, that is, is judged
Node data is complete, the coupling alarm of execution step S302.
Coupling warning in the present embodiment is the alarm mode for single node in system, and multiple nodes are because of a certain original
During because of abnormal parameters, while triggering alarm, at short notice, substantial amounts of warning information occurs, and the warning information of redundancy will increase
Security maintenance personal information processes workload, and have impact on its to alert degree of belief, alertness and formulate safety measure
Decision edge.Based on process pipe instrument flow chart figure, the pass set up between corresponding Bayesian network model expression node
System, and the coupled relation between node is found out by the calculating of the conditional probability of Bayesian network, set up all of danger further
Dangerous scene, using this its as the coupling alarm method in the embodiment of the present invention theoretical foundation.As shown in figure 4, being the present embodiment
In based on Bayesian network coupling alarm building-block of logic.
When the parameter of multiple nodes meets each alarm threshold value of certain dangerous scene, triggering coupling alarm, according to elder generation
The Bayesian network of front foundation is directly inferred to cause the root primordium of dangerous scene, is alerted for root primordium, while suggestion
Emergency measure, as shown in figure 5, in the present embodiment, previously according to the process pipe instrument stream of normal decompression flow process during refinery
Journey figure figure sets up Bayesian network model.
In Fig. 5 of the present embodiment, Bayesian network interior joint letter represents event and see the table below 1：
Table 1
| A：Electric desalting and dewatering valve is opened by mistake greatly； | H：Water injection tank liquid level is high； |
| B：Circulation water filling failure of pump； | I：Primary distillation tower temperature is high； |
| C：The heat exchanger blocking of primary distillation tower top； | J：Fore-running pressure tower is high； |
| D：Water injection rate is excessive； | K：Just top tank liquid level is low； |
| E：Atmospheric pressure kiln tracheal rupture； | L：Fore-running tower top liquid level is low； |
| F：Electrical desalter water level is low； | M：Fire box temperature is low； |
| G：Water injection rate interrupts； |
The 5 dangerous scenes that is set up in often decompression flow process further by Bayesian network, such as table 2：
Table 2 often decompresses the dangerous scene of flow process
When this kind of alarm mode to node in the present embodiment reduces multinode exception, non-root malfunctioning node produces big
The redundant alarm information of amount, improves the speed that warning efficiency and security maintenance personnel's processing information take measures.
This dangerous scene big, simulation electrical desalter water level, water injection rate, water injection tank liquid are opened by mistake for electric desalting and dewatering valve
Position, primary distillation tower temperature, fore-running pressure tower, just eight parameters such as top tank liquid level, fore-running tower top liquid level, fire box temperature is normal/different
Normal state, parameter simulation figure are as shown in Figure 6.
After step S102, each biography that execution step S103 judges to include in alarm data according to each sensor identification data
Whether the data of sensor group are complete, generate sensor group alarming processing data, step S303, S304 in corresponding Fig. 3.It is directed to
One group of sensor parameters being installed in same device are processed, when with group sensing data and meanwhile be close to upper alarm threshold or
Lower limit but when not triggering any alarm, equipment is also possible in the hole, should be alerted.As shown in fig. 7, for originally
The building-block of logic of the alarm method of sensor group in embodiment.
For the upper limit, the ratio defined between the parameter of sensor and upper alarm threshold judges that factor-alpha and lower limit judge factor-beta:
αiThe factor is judged for the upper alarm threshold of i-th sensor；QiParameter for i-th sensor；AiSense for i-th
The upper limit warning value of device.
βiThe factor is judged for the lower alarm threshold of i-th sensor；QiParameter for i-th sensor；BiSense for i-th
The lower limit warning value of device.
For the alarm triggered condition for judging the factor it is：
Or
WhereinFor judging the warning value of the factor.
When trigger condition is met, alerted, building-block of logic is shown in Fig. 7.Alarm optimization method for sensor group
As single-sensor alarm supplement, can be alerted in some catastrophe risk states, and can be earlier warning
Warping apparatus, are that operating personnel reserve more times for taking measures.
After step S103, execution step S104, according to supplemental characteristic and the default sensor of each sensor collection
Anomaly parameter value generates sensor abnormality alarming processing data, that is, enter line sensor itself abnormality judgment method.
When sensor can not carry out normal acquisition function because of factors such as power depletion, external environment, own loss, often
Occur false alarm or failing to report police, for this kind of situation, the oneself state for sensor judges, when judging that sensor loses
During effect, by this sensor cutout warning system.
In continuous time t, when sensor acquisition parameter is 0 or beyond the Reasonable Parameters value in environment (as pole in tower
End maximum temperature value) when, judge this sensor degradation, the alarm step after warning system is isolated, and point out to change
Fig. 8 is shown in by sensor, building-block of logic.
Finally, execution step S105, according to supplemental characteristic and the generation of default alarm threshold value of each sensor collection
Separated sensor alarming processing data, that is, carry out separated sensor alarm optimization method.
Key equipment in refinery flow process and risk symptoms node install sensor, for measurement temperature, pressure and liquid level etc.
Parameter.Outdoor scene temperature, historical data according to each sensor place equipment and self attributes set alarm threshold value, in sensor
Triggering alarm when measurement data reaches alarm threshold value.
After triggering alarm, equipment is in the hole, and and if only if, and sensor parameters less than upper alarm threshold or are higher than to accuse
State back to normal during alert lower limit 5%, can be alerted the judgement of ejection next time, and building-block of logic is shown in accompanying drawing 9.By this
Optimization method is planted, the bulk redundancy alarm that sensor parameters can be avoided to be shaken and produced near alarm limit value, is reduced
Operating personnel process the workload of bulk redundancy alarm.
The refinery procedures system intelligent alarm optimization method of the embodiment of the present invention employs MATLAB to being programmed, choosing
The analogue data for having taken above steps is optimized alarm as input, as follows with result that traditional single alarm mode is contrasted
Shown in table 3：
Table 3：Refinery procedures system intelligent alarm optimization method and single alarm method Comparative result
| False alarm rate | Correct alarm rate | Leakage alarm rate | Redundant alarm number of times | |
| Single alarm method | 3.3% | 78.7% | 21.3% | 77% |
| Optimize alarm method | 0% | 85.5% | 14.5% | 12% |
As can be seen from the table, traditional single alarm improve using the refinery procedures system intelligent alarm optimization method
The correct alarm rate of method, reduces by mistake and alerts and leak alarm rate and reduce redundant alarm number of times.Refinery process is absolutely proved
System intelligent alarm optimization method is used for the feasibility of refinery procedures system alarm.
Apply specific embodiment to be set forth the principle of the present invention and embodiment in the present invention, above example
Explanation be only intended to help and understand the method for the present invention and its core concept；Simultaneously for one of ordinary skill in the art,
According to the thought of the present invention, all will change in specific embodiments and applications, in sum, in this specification
Appearance should not be construed as limiting the invention.
Claims (10)
1. a kind of alarm data processing method of refinery system, it is characterised in that described method includes：
The alarm data of refinery system is received, the alarm data includes the mark data of each sensor in refinery system, each
The supplemental characteristic of sensor collection；
Whether the node data of the refinery system judged to include in the alarm data according to each sensor identification data is complete
Whole, generate node alarming processing data；
Whether the data of each sensor group judged to include in the alarm data according to each sensor identification data are complete,
Generate sensor group alarming processing data；
Processed for one group of sensor parameters being installed in same device, when with group sensing data while being close to announcement
When warning the upper limit or lower limit but any alarm is not triggered, sensor group alarming processing data are generated；
Supplemental characteristic and the generation sensor abnormality alarm of default sensor abnormality parameter value according to each sensor collection
Processing data；
Supplemental characteristic and default alarm threshold value generation separated sensor alarming processing data according to each sensor collection；
According to the node alarming processing data, sensor group alarming processing data, sensor abnormality alarming processing data and list
Individual sensor alarms processing data generates the alarm data result of refinery system.
2. alarm data processing method as claimed in claim 1, it is characterised in that described according to each sensor identification data
Judge whether the node data of the refinery system included in the alarm data completely includes：
Whether the mark data according to each sensor is judged comprising last node of refinery system in the alarm data
Node data.
3. alarm data processing method as claimed in claim 1, it is characterised in that described according to each sensor identification data
Judge whether the data of each sensor group included in the alarm data completely include：
Whether the mark data according to each sensor judges the data of each sensor group in the alarm data comprising the biography
The sensing data of last sensor of sensor group.
4. alarm data processing method as claimed in claim 1, it is characterised in that described method also includes：
Pre-stored sets up the Bayesian network model of expression node relation according to the process pipe instrument flow chart during refinery.
5. alarm data processing method as claimed in claim 4, it is characterised in that described according to each sensor identification
Data judge whether the node data of the refinery system included in the alarm data is complete, generates node alarming processing packet
Include：
When judging that the node data of refinery system that includes in the alarm data is complete, given birth to according to the Bayesian network model
Become node alarming processing data.
6. a kind of alarm data processing meanss of refinery system, it is characterised in that described device includes：
Data reception module, for receiving the alarm data of refinery system, the alarm data includes each biography in refinery system
The mark data of sensor, the supplemental characteristic of each sensor collection；
Node warning processing module, for judging, according to each sensor identification data, the refinery included in the alarm data
Whether the node data of system is complete, generates node alarming processing data；
Sensor group warning processing module, for judged to include in the alarm data according to each sensor identification data
Whether the data of each sensor group are complete, generate sensor group alarming processing data；And, for being installed in same device
One group of sensor parameters processed, when with group sensing data while being close to upper alarm threshold or lower limit but not triggering any
During alarm, sensor group alarming processing data are generated；
Sensor abnormality warning processing module, the supplemental characteristic and default sensor for being gathered according to each sensor are different
Often parameter value generates sensor abnormality alarming processing data；
Separated sensor warning processing module, for supplemental characteristic and default alarm threshold value according to each sensor collection
Generate separated sensor alarming processing data；
Alarm result generation module, for according to the node alarming processing data, sensor group alarming processing data, sensor
Abnormality alarming processing data and single sensor alarms processing data generate the alarm data result of refinery system.
7. alarm data processing meanss as claimed in claim 6, it is characterised in that described node warning processing module bag
Include：
Whether node judging unit, for judging comprising refinery in the alarm data according to the mark data of each sensor
The node data of last node of system.
8. alarm data processing meanss as claimed in claim 6, it is characterised in that described sensor group warning processing module
Including：
Sensor judging unit, for judging each sensor group in the alarm data according to the mark data of each sensor
Data whether last sensor comprising the sensor group sensing data.
9. alarm data processing meanss as claimed in claim 6, it is characterised in that described device also includes：
Memory module, sets up the shellfish of expression node relation for pre-stored according to the process pipe instrument flow chart during refinery
This network model of leaf.
10. alarm data processing meanss as claimed in claim 9, it is characterised in that described node warning processing module is also
Including：
Node alarming processing unit, when the node data of the refinery system for judging to include in the alarm data is complete, root
Node alarming processing data are generated according to the Bayesian network model.
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| CN105700517B (en) * | 2016-03-09 | 2018-10-12 | 中国石油大学(北京) | A kind of the initial failure monitoring method and device of refinery process adaptive data-driven |
| CN107728599B (en) * | 2017-09-01 | 2020-12-18 | 北京中燕信息技术有限公司 | Method and device for determining state of refining device valve |
| CN114237180B (en) * | 2021-12-17 | 2023-10-13 | 内蒙古工业大学 | Industrial control system attack detection method and device |
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