CN108053085A - Quality of production control method and device - Google Patents
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- CN108053085A CN108053085A CN201810055177.XA CN201810055177A CN108053085A CN 108053085 A CN108053085 A CN 108053085A CN 201810055177 A CN201810055177 A CN 201810055177A CN 108053085 A CN108053085 A CN 108053085A
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Abstract
The present invention provides a kind of quality of production control method and device.The method is applied to electric power generation system control centre, and quality of production prediction model is stored in the electric power generation system control centre.The described method includes：Obtain legal actual production data；Abnormal conditions are judged whether according to actual production data and quality of production prediction model；If there is exception, production process is adjusted according to solution corresponding with abnormal conditions, to control power generation quality.Thus, judged to whether there is abnormal conditions in production process according to current creation data and quality of production prediction model, and abnormal conditions are handled, so as to scientifically control power generation quality, excessive human resources need not be consumed simultaneously, and also have the characteristics that error rate is low, regulation and control are convenient.
Description
Technical field
The present invention relates to Technology of Electrical Power Generation field, in particular to a kind of quality of production control method and device.
Background technology
With increasing, the key factor that electric power is lived as influence people of electronic product.Presently mainly
Power generation is controlled by the modes such as manually estimating, detecting, however, aforesaid way there are human resources consumption it is big, go out
How the problems such as error rate is high, the electric power qualification rate of production is low, therefore, control power generation quality by way of science
The problem of making while excessive human resources need not be consumed, be those skilled in the art's urgent need to resolve.
The content of the invention
In order to overcome above-mentioned deficiency of the prior art, the technical problems to be solved by the invention are to provide a kind of production matter
Amount control method and device can judge to be in production process according to current creation data and quality of production prediction model
It is no to be handled there are abnormal conditions, and to abnormal conditions, so as to scientifically control power generation quality, it is not required to simultaneously
Excessive human resources are consumed, and also have the characteristics that error rate is low, regulation and control are convenient.
The embodiment of the present invention provides a kind of quality of production control method, described applied to electric power generation system control centre
Quality of production prediction model is stored in electric power generation system control centre, the described method includes：
Obtain legal actual production data；
Abnormal conditions are judged whether according to the actual production data and the quality of production prediction model；
If there are abnormal conditions, production process is adjusted according to solution corresponding with abnormal conditions, with right
Power generation quality is controlled.
The embodiment of the present invention also provides a kind of quality of production control device, applied to electric power generation system control centre, institute
It states and quality of production prediction model is stored in electric power generation system control centre, described device includes：
Acquisition module, for obtaining legal actual production data；
Judgment module, it is different for being judged whether according to the actual production data and the quality of production prediction model
Reason condition；
Module is adjusted, for there are during abnormal conditions, according to solution corresponding with abnormal conditions to production process
It is adjusted, to control power generation quality.
In terms of existing technologies, the invention has the advantages that：
The embodiment of the present invention provides a kind of quality of production control method and device.The method is applied to electric power generation system
Control centre is stored with quality of production prediction model in the electric power generation system control centre.Obtain legal reality
Creation data, and judge whether abnormal conditions according to the actual production data and the quality of production prediction model.If
There are abnormal conditions, then production process are adjusted according to solution corresponding with abnormal conditions, with to power generation matter
Amount is controlled.Judged as a result, according to current creation data and quality of production prediction model in production process with the presence or absence of different
Reason condition, and abnormal conditions are handled, so as to scientifically control power generation quality, while need not consume
More human resources, and also have the characteristics that error rate is low, regulation and control are convenient.
For the above-mentioned purpose of invention, feature and advantage is enable to be clearer and more comprehensible, present pre-ferred embodiments cited below particularly, and
Attached drawing appended by cooperation, is described in detail below.
Description of the drawings
It in order to illustrate the technical solution of the embodiments of the present invention more clearly, below will be to needed in the embodiment attached
Figure is briefly described, it should be understood that the following drawings illustrates only certain embodiments of the present invention, therefore is not construed as pair
The restriction of scope, for those of ordinary skill in the art, without creative efforts, can also be according to this
A little attached drawings obtain other relevant attached drawings.
Fig. 1 is one of flow diagram of quality of production control method provided in an embodiment of the present invention.
Fig. 2 is the flow diagram of the sub-step that step S120 includes in Fig. 1.
Fig. 3 is the flow diagram of the sub-step that step S130 includes in Fig. 1.
Fig. 4 is the two of the flow diagram of quality of production control method provided in an embodiment of the present invention.
Fig. 5 is the flow diagram of the sub-step that step S110 includes in Fig. 4.
Fig. 6 is one of block diagram of quality of production control device provided in an embodiment of the present invention.
Fig. 7 is the two of the block diagram of quality of production control device provided in an embodiment of the present invention.
Icon：100- quality of production control devices；110- training modules；120- acquisition modules；130- judgment modules；140-
Adjust module；150- prediction modules.
Specific embodiment
Below in conjunction with attached drawing in the embodiment of the present invention, the technical solution in the embodiment of the present invention is carried out clear, complete
Ground describes, it is clear that described embodiment is only part of the embodiment of the present invention, instead of all the embodiments.Usually exist
The component of the embodiment of the present invention described and illustrated in attached drawing can configure to arrange and design with a variety of herein.Cause
This, the detailed description of the embodiment of the present invention to providing in the accompanying drawings is not intended to limit claimed invention below
Scope, but it is merely representative of the selected embodiment of the present invention.Based on the embodiment of the present invention, those skilled in the art are not doing
Go out all other embodiments obtained on the premise of creative work, belong to the scope of protection of the invention.
It should be noted that：Similar label and letter represents similar terms in following attached drawing, therefore, once a certain Xiang Yi
It is defined, then it further need not be defined and explained in subsequent attached drawing in a attached drawing.Meanwhile the present invention's
In description, term " first ", " second " etc. are only used for distinguishing description, and it is not intended that instruction or hint relative importance.
Below in conjunction with the accompanying drawings, elaborate to some embodiments of the present invention.In the case where there is no conflict, it is following
Feature in embodiment and embodiment can be mutually combined.
Fig. 1 is refer to, Fig. 1 is one of flow diagram of quality of production control method provided in an embodiment of the present invention.Institute
It states method and is applied to electric power generation system control centre, quality of production prediction is stored in the electric power generation system control centre
Model.The idiographic flow of quality of production control method is described in detail below.
Step S120 obtains legal actual production data.
Fig. 2 is refer to, Fig. 2 is the flow diagram of the sub-step that step S120 includes in Fig. 1.The step S120 can be with
Including sub-step S121 and sub-step S122.
Sub-step S121 obtains actual production data in preset time period.
Sub-step S122 sieves the actual production data according to the actual production data and default screening rule
Choosing.
In the present embodiment, controlled by the working condition of the sampler to being used to gather creation data, you can
Obtain actual creation data.Furthermore, it is necessary to actual production is obtained in preset time period according to the working method of sampler
Data.For example, sampler is after actual production data are obtained, every 5 minutes actual production data sendings by acquisition to institute
Electric power generation system control centre is stated, therefore, preset time period is 5 minutes.If sampler is by the actual production number of acquisition
Electric power generation system control centre is sent to when factually, preset time period is then 0.In specific implementation, the preset time period
It is configured according to the real work mode of sampler.
In the embodiment of the present embodiment, the electric power generation system control centre passes through serial server and at least one
A PLC controller is electrically connected, and the PLC controller electronic equipment related with power generation is electrically connected, as a result, the electricity
Power production system control centre obtains actual production data by PLC controller.Wherein, the electric power generation system control centre
It can be connected serial bus, by way of GPRS network connection or WiFi network connection, be communicated to connect with PLC controller.
Wherein, actual production data can be divided into power generation data and environmental data, and power generation data can include
The quality of production, production quantity and other data.In a kind of specific embodiment of the present embodiment, actual production data can wrap
Include steam turbine charge flow rate, steam turbine goes out throughput, fan outlet flow, pressure, temperature, specific volume, thermodynamic energy, enthalpy and entropy etc..
Specifically, the electric power generation system control centre can be electrically connected with a server, and the server receives
The power generation data and environmental data that PLC controller is sent.Wherein, it is pre-established with production process data in the server
The power generation data and environmental data of reception can be respectively stored in production process by storehouse and environment data base, the server
In database and environment data base.Further, after power generation data and environmental data is received, server can basis
Default screening rule screens the data of reception, to obtain legal actual production data, and is stored, so as to
It is used in follow-up.Wherein, the default screening rule can be set according to actual conditions.For example, in actual production, it is raw
It can not possibly be 0 to produce quantity, therefore will be set to be more than 0 for the screening rule of production quantity, then if the production quantity received is
0, then the data can be screened out.
Wherein, data can be sent to server in the following manner by PLC controller：Packet header is used as using " * * ",
" ## " is used as bag tail, used among each data "；" separate, while data are transmitted using ASCII character.
Step S130 judges whether abnormal feelings according to the actual production data and the quality of production prediction model
Condition.
Fig. 3 is refer to, Fig. 3 is the flow diagram of the sub-step that step S130 includes in Fig. 1.The step S130 can be with
Including sub-step S131, sub-step S132 and sub-step S133.
Sub-step S131 obtains other each production numbers according to default quality of production scope and the quality of production prediction model
According to safe range.
Sub-step S132, by each actual production data compared with the safe range of corresponding creation data.
Sub-step S133, if actual production data not in the safe range of corresponding creation data, judge that there are different
Reason condition.
In the present embodiment, (for example, quality of production qualification rate is at least 98%) in the range of the default quality of production, according to
The quality of production prediction model can obtain on the premise of default quality of production scope is met, the safety of other each creation datas
Scope.If the legal actual production data obtained symbolize not in the safe range of corresponding each creation data
Existing abnormal conditions.For example, in the range of the default quality of production, the safe model of pressure is obtained according to the quality of production prediction model
It encloses for 20-80, however it is 100 to obtain pressure in legal actual production data, then shows pressure beyond safety
There are abnormal conditions in scope.
Further, if there are abnormal conditions, can early warning or report be carried out according to the intensity of anomaly of abnormal conditions
Alert prompting.Specifically, the intensity of anomaly of abnormal conditions and early warning or the correspondence of alarm can be preset.Than
Such as, can according to the intensity of anomaly of abnormal conditions carry out 1 grade of early warning, 2 grades of early warning, 3 grades of early warning, 1 grade alarm, 2 grades alarm, 3 and
Alarm.Wherein, the intensity of anomaly of abnormal conditions can be more than the degree of corresponding safe range according to each creation data and/or surpass
The accounting of the creation data of corresponding safe range in the creation data obtained altogether etc. is crossed to be divided.The power generation
System Control Center, can this be different in the display screen display of electric power generation system control centre when judging to be abnormal situation
Reason condition, the trend of abnormal conditions and caused result etc. and/or control and electric power generation system control centre communication link
The working condition of the warning device connect is to be alarmed or early warning.
In the embodiment of the present embodiment, the display screen can be touch-screen, in the electric power generation system control
The heart can also receive the operation of input by the touch-screen or other input equipments, and pre- according to the operation setting of reception
If quality of production scope.Optionally, the default quality of production scope can also be by the electric power generation system control centre
It is automatically generated according to the quality of production prediction model.Here, not to the specific set-up mode of the default quality of production scope
It is defined.
Step S140 if there are abnormal conditions, carries out production process according to solution corresponding with abnormal conditions
Adjustment, to control power generation quality.
In the present embodiment, be previously stored in the electric power generation system control centre each abnormal conditions and with abnormal feelings
The corresponding solution of condition.Therefore, when judging to be abnormal situation, solution corresponding with the abnormal conditions is obtained, into
And production process is adjusted according to the solution.Thus, it can be achieved that control to power generation quality, it is ensured that generation is high
The electric power of quality.
Further, the electric power generation system control centre can will solution corresponding with abnormal conditions by touch-screen
Scheme and the anticipation trend of production status after being adjusted according to solution etc. are shown.The electric power generation system control
Center can also receive artificial correction and approval of the staff to solution by touch-screen or other input equipments etc., into
And production process is adjusted according to the solution of approval.
Specifically, the electric power generation system control centre can refer to the control generated according to the solution after approval
Order is sent to slave computer WINCC control systems, and control instruction is sent to PLC controls by WINCC control systems through serial server
Device, and the data sending that PLC controller is returned gives the electric power generation system control centre.Hereby it is achieved that producing
The control of journey.
It, can also be according to the creation data in actual production process to the production matter in the embodiment of the present embodiment
Amount prediction model is trained again, so as to correct the quality of production prediction model.
Fig. 4 is refer to, Fig. 4 is the two of the flow diagram of quality of production control method provided in an embodiment of the present invention.Institute
Stating creation data includes the quality of production, production quantity, external environment data and other data.The method can also include step
S150。
Step S150 is corresponded to according to planned production quantity, external environment data and the quality of production prediction model
Other data scope and the quality of production.
In practice, after the daily production schedule is generated, the electric power generation system control centre is according to by daily
Production quantity that the production schedule obtains, external environment data (for example, temperature, humidity etc.) obtained by sampler and described
Quality of production prediction model obtains the preferred plan of production control and the quality of production corresponding with preferred plan, thus predicts future
The rejection rate trend of production.Wherein, preferred plan is specially the scope of other data, for example, obtained by the daily production schedule
Production quantity is 10,000 degree, and the working quantity for calculating steam turbine automatically according to the quality of production prediction model is 1 and steam turbine
Occurrence, the steam turbine of charge flow rate go out occurrence of throughput etc..
Referring once again to Fig. 4, before step S120, the method can also include step S110.
Step S110 obtains legal sampling creation data, and is trained and given birth to according to the sampling creation data
Yield and quality prediction model.
Fig. 5 is refer to, Fig. 5 is the flow diagram of the sub-step that step S110 includes in Fig. 4.The step S110 can be with
Including sub-step S111 and sub-step S112.
Sub-step S111 screens the sampling creation data obtained in preset time period according to default screening rule.
In the present embodiment, gather creation data using as sampling creation data, and according to default screening rule to obtain
Sampling creation data screened, to obtain legal sampling creation data.
The description as described in sub-step S111 can refer to above to the detailed description of step S120.
Sub-step S112, using the external environment data after screening and other data as input variable, by the life after screening
Yield and quality and production quantity, which are brought into as output variable in neutral net, to be trained, and obtains quality of production prediction model.
In the present embodiment, neutral net is trained according to legal sampling creation data, so as to be had
Have in the case where inputting possible affecting parameters (for example, steam turbine charge flow rate), you can the production of the corresponding quality of production of output
Branch prediction model.Specifically, the external environment data after screening and other data are brought into nerve net as input variable
In network, the quality of production corresponding with the external environment data and other data of input and production quantity are brought into as output variable
Into neutral net, thus neutral net is trained.Wherein, external environment data and other data can include steam turbine into
Throughput, steam turbine go out throughput, fan outlet flow, pressure, temperature, specific volume, thermodynamic energy, enthalpy and entropy etc..
Fig. 6 is refer to, Fig. 6 is one of block diagram of quality of production control device 100 provided in an embodiment of the present invention.
The quality of production control device 100 is applied to electric power generation system control centre, in the electric power generation system control centre
It is stored with quality of production prediction model.The quality of production control device 100 may include acquisition module 120, judgment module 130 and
Adjust module 140.
Acquisition module 120, for obtaining legal actual production data.
The mode that the acquisition module 120 obtains legal actual production data can include：
Actual production data are obtained in preset time period；
The actual production data are screened according to the actual production data and default screening rule.
In the present embodiment, the acquisition module 120 is used to perform the step S120 in Fig. 1, on the acquisition module
120 specific descriptions are referred to the description of step S120 in Fig. 1.
Judgment module 130, for judging whether to deposit according to the actual production data and the quality of production prediction model
In abnormal conditions.
The judgment module 130 is judged whether according to the actual production data and the quality of production prediction model
The mode of abnormal conditions includes：
The safe model of other each creation datas is obtained according to default quality of production scope and the quality of production prediction model
It encloses；
By each actual production data compared with the safe range of corresponding creation data；
If actual production data not in the safe range of corresponding creation data, judge that there are abnormal conditions.
In the present embodiment, the judgment module 130 is used to perform the step S130 in Fig. 1, on the judgment module
130 specific descriptions are referred to the description of step S130 in Fig. 1.
Module 140 is adjusted, for there are during abnormal conditions, according to solution corresponding with abnormal conditions to producing
Journey is adjusted, to control power generation quality.
In the present embodiment, the adjustment module 140 is used to perform the step S140 in Fig. 1, on the adjustment module
140 specific descriptions are referred to the description of step S140 in Fig. 1.
Fig. 7 is refer to, Fig. 7 is the two of the block diagram of quality of production control device 100 provided in an embodiment of the present invention.
The creation data includes the quality of production, production quantity, external environment data and other data, the quality of production control device
100 can also include prediction module 150.
Prediction module 150, for being obtained according to planned production quantity, external environment data and the quality of production prediction model
To the scope and the quality of production of other corresponding data.
In the present embodiment, the prediction module 150 is used to perform the step S150 in Fig. 4, on the prediction module
150 specific descriptions are referred to the description of step S150 in Fig. 4.
Referring once again to Fig. 7, the creation data includes the quality of production, production quantity, external environment data and other numbers
According to the quality of production control device 100 can also include training module 110.
Training module 110, for obtaining legal sampling creation data, and according to the sampling creation data training
Obtain quality of production prediction model.
The training module 110 obtains legal sampling creation data, and according to the sampling creation data training
Obtaining the mode of quality of production prediction model includes：
The sampling creation data obtained in preset time period is screened according to default screening rule；
Using the external environment data after screening and other data as input variable, by the quality of production after screening and production
Quantity is brought into neutral net as output variable and is trained, and obtains quality of production prediction model.
In the present embodiment, the training module 110 is used to perform the step S110 in Fig. 4, on the training module
110 specific descriptions are referred to the description of step S110 in Fig. 4.
In conclusion the present invention provides a kind of quality of production control method and device.The method is applied to power generation
System Control Center is stored with quality of production prediction model in the electric power generation system control centre.It obtains legal
Actual production data, and judge whether abnormal feelings according to the actual production data and the quality of production prediction model
Condition.If there are abnormal conditions, production process is adjusted according to solution corresponding with abnormal conditions, to be given birth to electric power
Yield and quality is controlled.Judge whether deposited in production process according to current creation data and quality of production prediction model as a result,
It handles in abnormal conditions, and to abnormal conditions, so as to scientifically control power generation quality, while need not disappear
Excessive human resources are consumed, and also have the characteristics that error rate is low, regulation and control are convenient.
The foregoing is only a preferred embodiment of the present invention, is not intended to limit the invention, for the skill of this field
For art personnel, the invention may be variously modified and varied.Within the spirit and principles of the invention, that is made any repaiies
Change, equivalent substitution, improvement etc., should all be included in the protection scope of the present invention.
Claims (10)
1. a kind of quality of production control method, which is characterized in that applied to electric power generation system control centre, the power generation
Quality of production prediction model is stored in System Control Center, the described method includes：
Obtain legal actual production data；
Abnormal conditions are judged whether according to the actual production data and the quality of production prediction model；
If there are abnormal conditions, production process is adjusted according to solution corresponding with abnormal conditions, with to electric power
The quality of production is controlled.
2. according to the method described in claim 1, it is characterized in that, described the step of obtaining legal actual production data
Including：
Actual production data are obtained in preset time period；
The actual production data are screened according to the actual production data and default screening rule.
It is 3. according to the method described in claim 1, it is characterized in that, described according to the actual production data and the production matter
The step of amount prediction model judges whether abnormal conditions includes：
The safe range of other each creation datas is obtained according to default quality of production scope and the quality of production prediction model；
By each actual production data compared with the safe range of corresponding creation data；
If actual production data not in the safe range of corresponding creation data, judge that there are abnormal conditions.
It is 4. according to the method described in claim 1, it is characterized in that, described according to the actual production data and the production matter
After the step of amount prediction model judges whether abnormal conditions, the method further includes：
If there are abnormal conditions, early warning or alarm are carried out according to the intensity of anomaly of abnormal conditions.
5. according to the method described in claim 1, it is characterized in that, the creation data includes the quality of production, production quantity, outer
Portion's environmental data and other data, the method further include：
The model of other corresponding data is obtained according to planned production quantity, external environment data and the quality of production prediction model
It encloses and the quality of production.
6. according to the method described in claim 1, it is characterized in that, the creation data includes the quality of production, production quantity, outer
Portion's environmental data and other data, the method further include：
Legal sampling creation data is obtained, and trains to obtain quality of production prediction mould according to the creation data that samples
Type；
It is described to obtain legal sampling creation data, and train to obtain quality of production prediction according to the sampling creation data
The step of model, includes：
The sampling creation data obtained in preset time period is screened according to default screening rule；
Using the external environment data after screening and other data as input variable, by the quality of production and production quantity after screening
It is brought into neutral net and is trained as output variable, obtain quality of production prediction model.
7. a kind of quality of production control device, which is characterized in that applied to electric power generation system control centre, the power generation
Quality of production prediction model is stored in System Control Center, described device includes：
Acquisition module, for obtaining legal actual production data；
Judgment module, for judging whether abnormal feelings according to the actual production data and the quality of production prediction model
Condition；
Module is adjusted, for there are during abnormal conditions, being carried out according to solution corresponding with abnormal conditions to production process
Adjustment, to control power generation quality.
8. device according to claim 7, which is characterized in that the judgment module is according to the actual production data and institute
It states quality of production prediction model and judges whether that the mode of abnormal conditions includes：
The safe range of other each creation datas is obtained according to default quality of production scope and the quality of production prediction model；
By each actual production data compared with the safe range of corresponding creation data；
If actual production data not in the safe range of corresponding creation data, judge that there are abnormal conditions.
9. device according to claim 7, which is characterized in that the creation data includes the quality of production, production quantity, outer
Portion's environmental data and other data, described device further include：
Prediction module, for being corresponded to according to planned production quantity, external environment data and the quality of production prediction model
Other data scope and the quality of production.
10. device according to claim 7, which is characterized in that the creation data include the quality of production, production quantity,
External environment data and other data, described device further include：
Training module for obtaining legal sampling creation data, and is trained according to the sampling creation data and given birth to
Yield and quality prediction model；
The training module obtains legal sampling creation data, and is trained and produced according to the sampling creation data
The mode of quality prediction model includes：
The sampling creation data obtained in preset time period is screened according to default screening rule；
Using the external environment data after screening and other data as input variable, by the quality of production and production quantity after screening
It is brought into neutral net and is trained as output variable, obtain quality of production prediction model.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112580840A (en) * | 2019-09-27 | 2021-03-30 | 北京国双科技有限公司 | Data analysis method and device |
| CN113421264A (en) * | 2021-08-24 | 2021-09-21 | 深圳市信润富联数字科技有限公司 | Wheel hub quality detection method, device, medium, and computer program product |
| CN113510234A (en) * | 2021-09-14 | 2021-10-19 | 深圳市信润富联数字科技有限公司 | Quality monitoring method and device for low-pressure casting of hub and electronic equipment |
| CN113837420A (en) * | 2020-06-23 | 2021-12-24 | 三菱电机(中国)有限公司 | Power consumption prediction method, power consumption prediction system, and computer-readable storage medium |
| CN115187085A (en) * | 2022-07-14 | 2022-10-14 | 北京航空航天大学 | Real-time control method for complex equipment driven by fusion of data and rule models |
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| CN113421264B (en) * | 2021-08-24 | 2021-11-30 | 深圳市信润富联数字科技有限公司 | Wheel hub quality detection method, device, medium, and computer program product |
| CN113510234A (en) * | 2021-09-14 | 2021-10-19 | 深圳市信润富联数字科技有限公司 | Quality monitoring method and device for low-pressure casting of hub and electronic equipment |
| CN113510234B (en) * | 2021-09-14 | 2022-01-07 | 深圳市信润富联数字科技有限公司 | Quality monitoring method and device for low-pressure casting of hub and electronic equipment |
| CN115187085A (en) * | 2022-07-14 | 2022-10-14 | 北京航空航天大学 | Real-time control method for complex equipment driven by fusion of data and rule models |
| CN115187085B (en) * | 2022-07-14 | 2025-09-05 | 北京航空航天大学 | A real-time control method for complex equipment driven by the fusion of data and rule models |
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Application publication date: 20180518 |