CN104238501A - Alarm data processing method and device for refining system - Google Patents
Alarm data processing method and device for refining system Download PDFInfo
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- CN104238501A CN104238501A CN201410418782.0A CN201410418782A CN104238501A CN 104238501 A CN104238501 A CN 104238501A CN 201410418782 A CN201410418782 A CN 201410418782A CN 104238501 A CN104238501 A CN 104238501A
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- 238000007670 refining Methods 0.000 title abstract 6
- 238000003672 processing method Methods 0.000 title abstract 2
- 238000012545 processing Methods 0.000 claims abstract description 83
- 238000000034 method Methods 0.000 claims abstract description 72
- 230000008569 process Effects 0.000 claims abstract description 35
- 230000005856 abnormality Effects 0.000 claims description 25
- 230000000153 supplemental effect Effects 0.000 claims description 20
- 238000010586 diagram Methods 0.000 claims description 12
- 230000002159 abnormal effect Effects 0.000 abstract description 8
- 230000008878 coupling Effects 0.000 description 7
- 238000010168 coupling process Methods 0.000 description 7
- 238000005859 coupling reaction Methods 0.000 description 7
- 239000007788 liquid Substances 0.000 description 7
- 238000005457 optimization Methods 0.000 description 7
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 7
- 238000002347 injection Methods 0.000 description 5
- 239000007924 injection Substances 0.000 description 5
- 238000012423 maintenance Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 230000036626 alertness Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000000052 comparative effect Effects 0.000 description 1
- 238000006731 degradation reaction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000001502 supplementing effect Effects 0.000 description 1
- 208000024891 symptom Diseases 0.000 description 1
- 230000001960 triggered effect Effects 0.000 description 1
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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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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Abstract
The invention provides an alarm data processing method and device of a refining system, wherein the method comprises the following steps: receiving alarm data of the refining system, wherein the alarm data comprises identification data of each sensor in the refining system and parameter data acquired by each sensor; generating node alarm processing data and sensor group alarm processing data according to the sensor identification data; generating sensor abnormal alarm processing data and single sensor alarm processing data according to parameter data acquired by each sensor; and generating an alarm data processing result of the refining system according to the node alarm processing data, the sensor group alarm processing data, the sensor abnormal alarm processing data and the single sensor alarm processing data. The invention combines the single sensor alarm method, the sensor group alarm method and the sensor self abnormity judgment to form the intelligent alarm of the refining process system, reduces redundant alarm, false alarm and alarm omission, and improves the processing efficiency of operators and the safety of the system.
Description
Technical field
The present invention relates to monitoring technique field, particularly about alarm data monitoring technique in refinery process, is a kind of alarm data disposal route and device of refinery system concretely.
Background technology
Warning system plays vital effect in refinery process, and operator is according to the alarm data search alarm cause of warning system and take appropriate measures, and when after abnormal elimination, device gets back to normal condition.
Alarm method in the refinery process of prior art, for the isolated data of single-sensor, lacks the oneself state considering mutual relationship between sensor, between equipment and sensor.In the refinery process of Frequent Accidents, due to sensor fault, information transmission are abnormal, personnel's maloperation hinders the factors such as alarm to cause redundant warning, false alarm with fail to report police, not only reduce the treatment effeciency of operating personnel, also there is great potential safety hazard.
Summary of the invention
For reducing redundant warning, false alarm and failing to report police, improve the treatment effeciency of operating personnel and the security of system, embodiments provide a kind of alarm data disposal route of refinery system, method comprises:
Receive the alarm data of refinery system, described alarm data comprises the supplemental characteristic of the identification data of each sensor in refinery system, the collection of each sensor;
Judge that whether the node data of the refinery system comprised in described alarm data is complete according to described each sensor identification data, generate node alarming processing data;
Judge that according to described each sensor identification data whether the data of each sensor group comprised in described alarm data are complete, generate sensor group alarming processing data;
The supplemental characteristic gathered according to described each sensor and the sensor abnormality parameter value preset generate sensor abnormality alarming processing data;
The supplemental characteristic gathered according to described each sensor and the alarm threshold value preset generate separated sensor alarming processing data;
According to the alarm data result of described node alarming processing data, sensor group alarming processing data, sensor abnormality alarming processing data and single-sensor alarming processing data genaration refinery system.
In addition, present invention also offers a kind of alarm data treating apparatus of refinery system, device comprises:
Data reception module, the supplemental characteristic that for receiving the alarm data of refinery system, described alarm data comprises the identification data of each sensor in refinery system, each sensor gathers;
Node warning processing module, for judging that whether the node data of the refinery system comprised in described alarm data is complete according to described each sensor identification data, generates node alarming processing data;
Sensor group warning processing module, whether the data for each sensor group judging to comprise in described alarm data according to described each sensor identification data are complete, generate sensor group alarming processing data;
Sensor abnormality warning processing module, generates sensor abnormality alarming processing data for the supplemental characteristic gathered according to described each sensor and the sensor abnormality parameter value preset;
Separated sensor warning processing module, generates separated sensor alarming processing data for the supplemental characteristic gathered according to described each sensor and the alarm threshold value preset;
Alarm result generation module, for the alarm data result according to described node alarming processing data, sensor group alarming processing data, sensor abnormality alarming processing data and single-sensor alarming processing data genaration refinery system.
The present invention is directed to process pipe instrument process flow diagram to analyze, set up corresponding Bayesian network model, judge to form refinery procedures system intelligent alarm in conjunction with separated sensor alarm method, sensor group alarm method and sensor self are abnormal simultaneously, reduce redundant warning, false alarm and fail to report police, improving the treatment effeciency of operating personnel and the security of system.
For above and other object of the present invention, feature and advantage can be become apparent, preferred embodiment cited below particularly, and coordinate institute's accompanying drawings, be described in detail below.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 is the process flow diagram of the alarm data disposal route of a kind of refinery system disclosed by the invention;
Fig. 2 is the block diagram of the alarm data treating apparatus of a kind of refinery system disclosed by the invention;
Fig. 3 is the process flow diagram that the present invention carries out the embodiment of refinery procedures system intelligent alarm;
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 sets up Bayesian network model according to the process pipe instrument process flow diagram of decompress(ion) flow process normal in refinery process in advance;
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 is separated sensor alarm building-block of logic.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.
As shown in Figure 1, be the alarm data disposal route of a kind of refinery system disclosed by the invention, comprise:
Step S101, receives the alarm data of refinery system, the supplemental characteristic that described alarm data comprises the identification data of each sensor in refinery system, each sensor gathers;
According to described each sensor identification data, step S102, judges that whether the node data of the refinery system comprised in described alarm data is complete, generate node alarming processing data;
Concrete, judge according to the identification data of each sensor the node data whether comprising last node of refinery system in alarm data, whether complete to judge the node data of refinery system.
Step S103, judges that according to described each sensor identification data whether the data of each sensor group comprised in described alarm data are complete, generates sensor group alarming processing data;
Judge whether the data of each sensor group in alarm data comprise the sensing data of last sensor of this sensor group, and judgement is according to the identification data of each sensor, then this sensor group data integrity.
Step S104, the supplemental characteristic gathered according to described each sensor and the sensor abnormality parameter value preset generate sensor abnormality alarming processing data;
Step S105, the supplemental characteristic gathered according to described each sensor and the alarm threshold value preset generate separated sensor alarming processing data;
Step S106, according to the alarm data result of described node alarming processing data, sensor group alarming processing data, sensor abnormality alarming processing data and separated sensor alarming processing data genaration refinery system.
Described method also comprises: pre-stored sets up the Bayesian network model of expression node relation according to the process pipe instrument process flow diagram in refinery process.In step S102, when judging that the node data of refinery system is complete, carry out coupling alarming processing based on the Bayesian network set up.
In addition, as shown in Figure 2, the invention also discloses a kind of alarm data treating apparatus of refinery system, device comprises:
Data reception module 201, the supplemental characteristic that for receiving the alarm data of refinery system, described alarm data comprises the identification data of each sensor in refinery system, each sensor gathers;
Node warning processing module 202, for judging that whether the node data of the refinery system comprised in described alarm data is complete according to described each sensor identification data, generates node alarming processing data;
Sensor group warning processing module 203, whether the data for each sensor group judging to comprise in described alarm data according to described each sensor identification data are complete, generate sensor group alarming processing data;
Sensor abnormality warning processing module 204, generates sensor abnormality alarming processing data for the supplemental characteristic gathered according to described each sensor and the sensor abnormality parameter value preset;
Separated sensor warning processing module 205, generates separated sensor alarming processing data for the supplemental characteristic gathered according to described each sensor and the alarm threshold value preset;
Alarm result generation module 206, for the alarm data result according to described node alarming processing data, sensor group alarming processing data, sensor abnormality alarming processing data and separated sensor alarming processing data genaration refinery system.
Below in conjunction with concrete embodiment, technical scheme of the present invention is described in further details:
As shown in Figure 3, for carrying out the process flow diagram of the embodiment of refinery procedures system intelligent alarm according to technical scheme of the present invention.
According to aforementioned, when the present invention specifically implements, receive the alarm data of refinery system, alarm starts, according to the identification data of each sensor comprised in alarm data, judge that whether the node data of the refinery system comprised in alarm data is complete, according to judged result, generate the node alarming processing data of response, namely carry out step S301, the S302 in Fig. 3, i.e. decision node data integrity, performs the coupling alarm of step S302.
Coupling warning in the present embodiment is the alarm mode for single node in system, when multiple node is because of a certain root primordium abnormal parameters, trigger alerts simultaneously, at short notice, a large amount of warning information occurs, the warning information of redundancy will increase security maintenance personal information work for the treatment of amount, and have impact on its degree of belief to alarm, alertness and formulate the decision edge of safety practice.Based on process pipe instrument process flow diagram figure, set up the relation between corresponding Bayesian network model expression node, and find out the coupled relation between node by the calculating of the conditional probability of Bayesian network, set up all dangerous scenes further, using this its as the theoretical foundation of the coupling alarm method in the embodiment of the present invention.As shown in Figure 4, be the building-block of logic of the coupling alarm based on Bayesian network in the present embodiment.
When the parameter of multiple node meets each alarm threshold value of certain dangerous scene, trigger coupling alarm, Bayesian network according to previously setting up directly infers the root primordium causing dangerous scene, alarm is carried out for root primordium, advise emergency measure simultaneously, as shown in Figure 5, in the present embodiment, set up Bayesian network model according to the process pipe instrument process flow diagram figure of decompress(ion) flow process normal in refinery process in advance.
In Fig. 5 of the present embodiment, Bayesian network interior joint letter represents event and sees the following form 1:
Table 1
| A: electrodesalting and electrodehydrating valve opens by mistake greatly; | H: water injection tank liquid level is high; |
| B: circulation waterflood pump fault; | I: primary tower temperature is high; |
| C: primary tower top heat interchanger blocks; | J: primary tower pressure 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; | ? |
5 dangerous scenes in normal decompress(ion) flow process are set up further, as table 2 by Bayesian network:
The dangerous scene of the normal decompress(ion) flow process of table 2
In the present embodiment to this kind of alarm mode of node decrease multinode abnormal time non-root malfunctioning node produce a large amount of redundant alarm information, improve the speed that warning efficiency and security maintenance personnel process information are taken measures.
This dangerous scene large is opened by mistake for electrodesalting and electrodehydrating valve, the normal/abnormal state of eight parameters such as analog electrical desalter water level, water injection rate, water injection tank liquid level, primary tower temperature, primary tower pressure, just top tank liquid level, fore-running tower top liquid level, fire box temperature, parameter simulation figure as shown in Figure 6.
After step S102, perform step S103 and judge that according to each sensor identification data whether the data of each sensor group comprised in alarm data are complete, generate sensor group alarming processing data, the step S303 in corresponding diagram 3, S304.Namely process for the one group of sensor parameters be installed in same device, when with group sensing data simultaneously close to upper alarm threshold or lower limit but when not triggering any alarm, equipment is also likely in the hole, should alarm be carried out.As shown in Figure 7, be the building-block of logic of the alarm method of sensor group in the present embodiment.
Ratio between the parameter of definition sensor and upper alarm threshold is that the upper limit judges that factor-alpha and lower limit judge factor-beta:
α
ibe that the upper alarm threshold of i-th sensor judges the factor; Q
iit is the parameter of i-th sensor; A
iit is the upper limit warning value of i-th sensor.
β
ibe that the lower alarm threshold of i-th sensor judges the factor; Q
iit is the parameter of i-th sensor; B
iit is the lower limit warning value of i-th sensor.
For judging that the alarm triggered condition of the factor is:
Or
Wherein
for judging the warning value of the factor.
When meeting trigger condition, carry out alarm, building-block of logic is shown in Fig. 7.For alarm optimization method the supplementing as single-sensor alarm of sensor group, alarm can be carried out when some catastrophe risk state, and can warning warping apparatus more early, for operating personnel reserve the time of taking measures more.
After step S103, perform step S104, the supplemental characteristic gathered according to described each sensor and the sensor abnormality parameter value preset generate sensor abnormality alarming processing data, namely carry out sensor self 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 fail to report police, for this kind of situation, the oneself state for sensor judges, when judging sensor failure, by this sensor cutout warning system.
In continuous time t, when sensor acquisition parameter be 0 or exceed in environment Reasonable Parameters value (as extreme maximum temperature value in tower) time, judge this sensor degradation, the alarm step after being isolated warning system, and point out more emat sensor, building-block of logic is shown in Fig. 8.
Finally, perform step S105, the supplemental characteristic gathered according to described each sensor and the alarm threshold value preset generate separated sensor alarming processing data, namely carry out separated sensor alarm optimization method.
Key equipment in refinery flow process and risk symptoms node sensor installation, for parameters such as measuring tempeature, pressure and liquid levels.According to the outdoor scene temperature of each sensor place equipment, historical data and self attributes setting alarm threshold value, the trigger alerts when sensor measurement data reaches alarm threshold value.
After trigger alerts, equipment is in the hole, and and if only if, and sensor parameters replys normal condition lower than upper alarm threshold or higher than during lower alarm threshold 5%, and can carry out the judgement that alarm is next time ejected, building-block of logic is shown in accompanying drawing 9.By this optimization method, sensor parameters can be avoided to carry out shaking near alarm limit value and the bulk redundancy alarm that produces, reduce the workload that operating personnel process bulk redundancy alarm.
The refinery procedures system intelligent alarm optimization method of the embodiment of the present invention have employed MATLAB to programming, and the simulated data that have chosen above steps is optimized alarm as input, and the result contrasted with tradition single alarm mode is as shown in table 3 below:
Table 3: refinery procedures system intelligent alarm optimization method and single alarm method Comparative result
| ? | Alarm rate by mistake | Correct alarm rate | Leak 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, adopt the correct alarm rate that improve traditional single alarm method of this refinery procedures system intelligent alarm optimization method, reduce alarm by mistake and leak alarm rate and reduce redundant alarm number of times.Absolutely prove the feasibility of refinery procedures system intelligent alarm optimization method for the alarm of refinery procedures system.
Apply specific embodiment in the present invention to set forth principle of the present invention and embodiment, the explanation of above embodiment just understands method of the present invention and core concept thereof for helping; Meanwhile, for one of ordinary skill in the art, according to thought of the present invention, all will change in specific embodiments and applications, in sum, this description should not be construed as limitation of the present invention.
Claims (10)
1. an alarm data disposal route for refinery system, is characterized in that, described method comprises:
Receive the alarm data of refinery system, described alarm data comprises the supplemental characteristic of the identification data of each sensor in refinery system, the collection of each sensor;
Judge that whether the node data of the refinery system comprised in described alarm data is complete according to described each sensor identification data, generate node alarming processing data;
Judge that according to described each sensor identification data whether the data of each sensor group comprised in described alarm data are complete, generate sensor group alarming processing data;
The supplemental characteristic gathered according to described each sensor and the sensor abnormality parameter value preset generate sensor abnormality alarming processing data;
The supplemental characteristic gathered according to described each sensor and the alarm threshold value preset generate separated sensor alarming processing data;
According to the alarm data result of described node alarming processing data, sensor group alarming processing data, sensor abnormality alarming processing data and single-sensor alarming processing data genaration refinery system.
2. alarm data disposal route as claimed in claim 1, is characterized in that, described judge that whether the node data of the refinery system comprised in described alarm data is complete according to each sensor identification data and comprises:
The node data whether comprising last node of refinery system in described alarm data is judged according to the identification data of described each sensor.
3. alarm data disposal route as claimed in claim 1, is characterized in that, described judge that whether the data of each sensor group comprised in described alarm data are complete according to each sensor identification data and comprises:
Judge whether the data of each sensor group in described alarm data comprise the sensing data of last sensor of this sensor group according to the identification data of described each sensor.
4. alarm data disposal route as claimed in claim 1, it is characterized in that, described method also comprises:
Pre-stored sets up the Bayesian network model of expression node relation according to the process pipe instrument process flow diagram in refinery process.
5. alarm data disposal route as claimed in claim 4, it is characterized in that, according to described each sensor identification data, described judges that whether the node data of the refinery system comprised in described alarm data is complete, generates node alarming processing data and comprises:
When judging that the node data of the refinery system comprised in described alarm data is complete, generate node alarming processing data according to described Bayesian network model.
6. an alarm data treating apparatus for refinery system, is characterized in that, described device comprises:
Data reception module, the supplemental characteristic that for receiving the alarm data of refinery system, described alarm data comprises the identification data of each sensor in refinery system, each sensor gathers;
Node warning processing module, for judging that whether the node data of the refinery system comprised in described alarm data is complete according to described each sensor identification data, generates node alarming processing data;
Sensor group warning processing module, whether the data for each sensor group judging to comprise in described alarm data according to described each sensor identification data are complete, generate sensor group alarming processing data;
Sensor abnormality warning processing module, generates sensor abnormality alarming processing data for the supplemental characteristic gathered according to described each sensor and the sensor abnormality parameter value preset;
Separated sensor warning processing module, generates separated sensor alarming processing data for the supplemental characteristic gathered according to described each sensor and the alarm threshold value preset;
Alarm result generation module, for the alarm data result according to described node alarming processing data, sensor group alarming processing data, sensor abnormality alarming processing data and single-sensor alarming processing data genaration refinery system.
7. alarm data treating apparatus as claimed in claim 6, it is characterized in that, described node warning processing module comprises:
Node judging unit, for judging according to the identification data of described each sensor the node data whether comprising last node of refinery system in described alarm data.
8. alarm data treating apparatus as claimed in claim 6, it is characterized in that, described sensor group warning processing module comprises:
According to the identification data of described each sensor, sensor judging unit, for judging whether the data of each sensor group in described alarm data comprise the sensing data of last sensor of this sensor group.
9. alarm data treating apparatus as claimed in claim 6, it is characterized in that, described method also comprises:
Memory module, sets up the Bayesian network model of expression node relation according to the process pipe instrument process flow diagram in refinery process for pre-stored.
10. alarm data treating apparatus as claimed in claim 9, it is characterized in that, described node warning processing module also comprises:
Node alarming processing unit, during for judging that the node data of the refinery system comprised in described alarm data is complete, generates node alarming processing data according to described Bayesian network model.
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| CN104238501B (en) | 2017-03-08 |
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