CN104914800A - Inert data filtering method - Google Patents
Inert data filtering method Download PDFInfo
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- CN104914800A CN104914800A CN201410089823.6A CN201410089823A CN104914800A CN 104914800 A CN104914800 A CN 104914800A CN 201410089823 A CN201410089823 A CN 201410089823A CN 104914800 A CN104914800 A CN 104914800A
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- inertia data
- value
- data
- current time
- inertia
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/4183—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by data acquisition, e.g. workpiece identification
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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]
Abstract
The present invention discloses an inert data filtering method. The method comprises the following steps that: inertia data at a current time point are acquired, so that an inertia data acquisition value at the current time point can be obtained; and based on the inertia data acquisition value at the current time point and an inertia data filtering value at a last time point, an inert data filtering value at the current time point can be obtained according to a polynomial extreme value, and corresponding control signals can be generated according to the inert data filtering value at the current time point. The inert data filtering method provided by the invention is simple and convenient in process, and can effectively filter out abruptly-varying inert data and improve the reliability and stability of the inert data, and therefore, a guarantee can be provided for the stable operation of a control system.
Description
Technical field
The present invention relates to signal processing technology field, specifically, relate to a kind of inertia data filtering methods.
Background technology
Temperature data is as the vehicle-mounted inertia data of one, and its characteristic is the level and smooth but not abrupt change of data variation process.The working control of temperature data to locomotive of the equipment such as main transformer device, main convertor, traction electric machine has significant impact, is also related to the security of operation of locomotive simultaneously.
In the mobile unit of locomotive, as full-vehicle control center network control system, need the temperature data gathering the equipment such as main transformer device, main convertor, traction electric machine, and according to the duty of these temperature data real time monitoring relevant devices, to make corresponding control treatment.
If the temperature data of network control system collection is unstable or be disturbed and abrupt change, the control that network control system can be made to make the mistake, have a strong impact on the normal work of whole locomotive, even machine is broken even may to cause locomotive operation fault.Therefore the reliability important in inhibiting of these temperature datas is ensured.
At present in production vehicles, usual way sets up certain number of times is carried out in buffer zone average value processing to temperature data, thus reach the effect of smoothed data abrupt change, realizes the filtering of inertia data.From filter effect, existing filtering method still cannot the part of l fraction effectively in filtering temperature data and abrupt change.In addition, existing temperature data filtering method also cannot stabilize the abrupt change data falling to continue for some time.This shows, under production vehicles has the condition of requirements at the higher level to reliability and security, existing temperature data filtering method is difficult to meet the demands.
Based on above-mentioned situation, need badly a kind of can the inertia data filtering methods of unstable data in effectively filtering inertia data and abrupt change data.
Summary of the invention
For solving the problem, the invention provides a kind of inertia data filtering methods, described method comprises:
Gather the inertia data of current time, obtain current time inertia data acquisition set value;
Based on the previous moment inertia data filtering value of described current time inertia data acquisition set value and storage, calculate current time inertia data filtering value according to polynomial expression extreme value, produce corresponding control signal for according to described current time inertia data filtering value.
According to one embodiment of present invention, current time inertia data filtering value according to following formulae discovery:
F(p,T
k)＝p×T
k+(1-p)×F(p,T
k-1)
Wherein, F (p, T
k) represent kth moment inertia data filtering value, T
krepresent kth moment inertia data acquisition set value, the kth moment represents current time, and p represents the regulating parameter of inertia data acquisition set value, F (p, T
k-1) represent kth-1 moment inertia data filtering value.
According to one embodiment of present invention, described inertia data comprise temperature data.
According to one embodiment of present invention, the span of described regulating parameter comprises [0.04,0.06].
According to one embodiment of present invention, the span of described regulating parameter comprises [0.94,0.96]
Inertia data filtering methods simple flow provided by the invention, by arranging rational regulating parameter, the unstable data that can occur in effectively filtering inertia data and abrupt change data.Meanwhile, compared to existing inertia data filtering methods, this method can also the inertia data that continue for some time of filtering abrupt change effectively.Inertia data filtering methods provided by the invention improves the reliability and stability of inertia data, for the stable operation of control system provides safeguard, ensure that the safe operation of vehicle.In addition, by arranging other rational regulating parameter, inertia data filtering methods provided by the invention can also be used for the detection of abrupt change data in inertia data.
Other features and advantages of the present invention will be set forth in the following description, and, partly become apparent from instructions, or understand by implementing the present invention.Object of the present invention and other advantages realize by structure specifically noted in instructions, claims and accompanying drawing and obtain.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, do simple introduction by accompanying drawing required in embodiment or description of the prior art below:
Fig. 1 is the process flow diagram of inertia data filtering methods according to an embodiment of the invention.
Embodiment
Describe embodiments of the present invention in detail below with reference to drawings and Examples, to the present invention, how application technology means solve technical matters whereby, and the implementation procedure reaching technique effect can fully understand and implement according to this.It should be noted that, only otherwise form conflict, each embodiment in the present invention and each feature in each embodiment can be combined with each other, and the technical scheme formed is all within protection scope of the present invention.
The feature of inertia data is that change is level and smooth, there will not be abrupt change in the change of inertia data under normal circumstances.For the inertia data of abrupt change in control system, in order to ensure the reliability of inertia data, need the smoothing process of inertia data to these abrupt changes.The present invention, according to the feature of the smooth change of inertia data, utilizes polynomial expression extreme value theory, proposes the iterative equation of inertia data, to utilize the inertia data of this iterative equation filtering abrupt change.
According to polynomial expression extreme value theory, for polynomial expression a
n-1+ a
n-2x+...+x
n-1, there is following formula:
As a=1, formula (1) then becomes:
As x < 1, and when n trend is infinite, so then have:
According to above-mentioned polynomial expression extreme value theory, the present embodiment proposes the iterative formula of inertia data as follows:
F(p,T
k)＝p×(T
k-F(p,T
k-1))+F(p,T
k-1)＝p×T
k+(1-p)×F(p,T
k-1) （4）
Wherein, F (p, T
k) represent kth moment inertia data filtering value, T
krepresent kth moment inertia data acquisition set value, p represents the regulating parameter of inertia data acquisition set value, F (p, T
k-1) represent kth-1 moment inertia data filtering value.
As can be seen from formula (4), kth moment inertia data filtering value F (p, T
k) equal kth moment inertia data acquisition set value T
kutilize the value after regulating parameter p weighting and kth-1 moment inertia data filtering value F (p, T
k-1) utilize the value after 1-p weighting and.When p get reasonably level off to 0 value time, kth moment inertia data compared with the variable quantity of kth-1 moment inertia data, for export filtered kth moment inertia data inertia data F (p, T
k) impact very little, so also just reach the effect of the abrupt change data in filtering inertia data.
Can be obtained further by formula (4):
F(p,T
k)＝p×T
k+p×(1-p)×T
k-1+...+p×(1-p)
k-1×T
1+(1-p)
kF(p,T
0) （5）
Wherein, T
0represent the initial value of inertia data.
In the present embodiment, by the initial value T of inertia data
0be set to 0, the initial value of inertia data filtering value is also 0, but the present invention is not limited thereto.
In order to better set forth principle of the present invention, object and advantage, in the present embodiment, setting inertia data
In the 1st moment, abrupt change occurs, the inertia data value after abrupt change remains unchanged, and continues for some time.So can be obtained by formula (5):
F(p,T
k)＝p×T+p×(1-p)×T+...+p×(1-p)
k-1×T＝p×T×[1+(1-p)+...+(1-p)
k-1] （6）
Wherein, T represents the value of the inertia data after abrupt change.
As can be seen from formula (6), inertia data filtering value F (p, T
kif) want the value T of the inertia data after equaling abrupt change, according to polynomial expression extreme value theory, then need superposition repeatedly infinite.In the additive process of limited number of time, the abrupt change of inertia data is less for the impact of output valve, thus realizes the filtering to abrupt change inertia data.
Based on above principle, present embodiments provide a kind of inertia data filtering methods, Fig. 1 shows the process flow diagram of this filtering method.
As shown in Figure 1, in step S101, first gather current time inertia data, obtain current time inertia data acquisition set value.In the present embodiment, using the kth moment as current time, current time inertia data acquisition set value is then T
k.In addition, in the present embodiment, inertia data are temperature data, but the present invention is not limited thereto, and in other embodiments of the invention, inertia data can also be other reasonable data.
Subsequently in step s 102, based on current time inertia data acquisition set value T
kwith the previous moment inertia data filtering value F (p, the T that store
k-1), calculate current time inertia data filtering value according to polynomial expression extreme value, produce corresponding control signal for control system according to current time inertia data filtering value.
In the present embodiment, formula (4) is utilized to calculate current time inertia data filtering value in step s 102.In order to reach the object of temperature data being carried out to smothing filtering effectively, in the present embodiment, according to the result of many experiments, the span of regulating parameter p is set as [0.04,0.06].Be 0.06 object of the present invention, principle and advantage to be further elaborated with regulating parameter below.
When p is 0.06, can obtain according to formula (4):
F(0.06,T
k)＝0.06×T
k+(1-0.06)×F(0.06,T
k-1) （6）
If temperature data produces abrupt change in the kth moment, the temperature data after abrupt change is T
k, then as can be seen from formula (6), by the present embodiment provide filtering method, the increment (T of kth moment temperature data
k-F (0.06, T
k-1)) in kth moment temperature filtering data, proportion is only 0.06, it is less to the variable effect of the temperature filtering data exported.So inertia data filtering methods provided by the invention can reach the effect of effective filtering abrupt change temperature data.
For the temperature data that abrupt change continues for some time, if the duration width of abrupt change data is greater than the time width carrying out average value processing of setting, so in the abrupt change duration, carry out the temperature data after average value processing and still can there is abrupt change.And according to inertia data filtering methods provided by the invention, the restriction of temperature data abrupt change duration can not be subject to.By setting rational regulating parameter, abrupt change data can be made very little for the influence of fluctuations of filtered temperature data, make the change curve of filtered temperature data more mild, thus reaching better smothing filtering effect.
As can be seen here, inertia data filtering methods provided by the invention is for the abrupt change data continued for some time, can effectively stabilize, eliminate inertia data unstable or be disturbed and produce the problem of abrupt change, thus provide stable status data, for the stable operation of control system provides reliable guarantee for control system.
It should be noted that, by changing the setting value of regulating parameter, inertia data filtering methods provided by the invention can also have other application.Such as when the span of regulating parameter p is set in [0.94,0.96], now current inertia data filtering value truly can reflect current inertia data acquisition set value.And if regulating parameter p is set to larger value, current inertia data filtering value is approximately current inertia data acquisition set value and amplifies the value after p times, and this is conducive to reflecting small data variation.
Although the embodiment disclosed by the present invention is as above, the embodiment that described content just adopts for the ease of understanding the present invention, and be not used to limit the present invention.Technician in any the technical field of the invention; under the prerequisite not departing from the spirit and scope disclosed by the present invention; any amendment and change can be done what implement in form and in details; but scope of patent protection of the present invention, the scope that still must define with appending claims is as the criterion.
Claims (5)
1. an inertia data filtering methods, is characterized in that, described method comprises:
Gather the inertia data of current time, obtain current time inertia data acquisition set value;
Based on the previous moment inertia data filtering value of described current time inertia data acquisition set value and storage, calculate current time inertia data filtering value according to polynomial expression extreme value, produce corresponding control signal for according to described current time inertia data filtering value.
2. the method for claim 1, is characterized in that, current time inertia data filtering value according to following formulae discovery:
F(p,T
k)＝p×T
k+(1-p)×F(p,T
k-1)
Wherein, F (p, T
k) represent kth moment inertia data filtering value, T
krepresent kth moment inertia data acquisition set value, the kth moment represents current time, and p represents the regulating parameter of inertia data acquisition set value, F (p, T
k-1) represent kth-1 moment inertia data filtering value.
3. the method for claim 1, is characterized in that, described inertia data comprise temperature data.
4. as right will go the method as described in 1, it is characterized in that, the span of described regulating parameter comprises [0.04,0.06].
5. the method for claim 1, is characterized in that, the span of described regulating parameter comprises [0.94,0.96].
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|---|---|---|---|
| CN201410089823.6A CN104914800A (en) | 2014-03-12 | 2014-03-12 | Inert data filtering method |
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|---|---|---|---|
| CN201410089823.6A CN104914800A (en) | 2014-03-12 | 2014-03-12 | Inert data filtering method |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1836785A (en) * | 2006-04-24 | 2006-09-27 | 西安交通大学 | Powder-making system automatic control method for heat engine plant steel ball coal grinding mill |
| CN101848118A (en) * | 2010-05-04 | 2010-09-29 | 电子科技大学 | Self-adaptive smooth treatment method of input time delay based on time delay gradient information |
| CN102457250A (en) * | 2010-10-20 | 2012-05-16 | Tcl集团股份有限公司 | Collected data filter processing method and device |
| US20130158937A1 (en) * | 2010-03-09 | 2013-06-20 | Invensys Systems, Inc. | Temperature Prediction Transmitter |
-
2014
- 2014-03-12 CN CN201410089823.6A patent/CN104914800A/en active Pending
Patent Citations (4)
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|---|---|---|---|---|
| CN1836785A (en) * | 2006-04-24 | 2006-09-27 | 西安交通大学 | Powder-making system automatic control method for heat engine plant steel ball coal grinding mill |
| US20130158937A1 (en) * | 2010-03-09 | 2013-06-20 | Invensys Systems, Inc. | Temperature Prediction Transmitter |
| CN101848118A (en) * | 2010-05-04 | 2010-09-29 | 电子科技大学 | Self-adaptive smooth treatment method of input time delay based on time delay gradient information |
| CN102457250A (en) * | 2010-10-20 | 2012-05-16 | Tcl集团股份有限公司 | Collected data filter processing method and device |
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| 张文庆: "用PLC的软件实现PID闭环控制", 《自动化技术与应用》 * |
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Application publication date: 20150916 |
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