CN104535827A - Defective point removing method and system used in AD sampling - Google Patents
Defective point removing method and system used in AD sampling Download PDFInfo
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Abstract
The invention provides a defective point removing method and system used in AD sampling. The defective point removing method comprises the following steps of obtaining current sampling values of sampling data in a current period and n previous-period sampling values at the corresponding positions of multiple previous periods, wherein n = 1, 2, 3, ...; calculating change values produced by the sampling data according to the current sampling values in the current period and the n previous-period sampling values; determining defective point criterion in the sampling data according to the change values and set threshold values including a high threshold value and a low threshold value; determining that the sampling values at the corresponding positions are defective points and calculating substitute values according to the sampling values at the corresponding positions of the multiple periods if the change values are greater than the high threshold value or are lower than the low threshold value, and using the substitute values to replace the sampling values of the defective points. By means of the technical scheme, defective point processing effect and accuracy are good, and sampling reliability and accuracy can be ensured.
Description
Technical field
The present invention relates to technical field of data processing, particularly relate to during a kind of AD samples and remove bad point method and system.
Background technology
AD sampling is usually used in electric system, as integrated ring main unit, need to carry out AD sampling to current data, occur a certain instance sample value transforming mistakes to solve in sampling process and cause subsequent calculations to occur the problem of deviation, needing to go bad point process to sampled value.
At present, AD sampled value go bad point technical scheme, traditional technology is generally adopt the mode that compares with the last cycle to carry out bad point judgement, and substitutes the sampled value of bad point position by the corresponding sampled value in previous cycle.Above-mentioned technology needs comparatively simple, but shortcoming is the situation that cannot judge multiple bad point, if also there is the situation of bad point or error in judgement in the previous cycle, and then erroneous judgement will be there is in follow-up process, thus, also just cannot judge that in this cycle, correspondence position occurs whether the more sampled value not in relevant position is bad point.
As can be seen here, traditional technology to the effect of the process of bad point and accuracy lower, be difficult to ensure sampling reliability and accuracy.
Summary of the invention
Based on this, be necessary, for the effect of the process of bad point and the lower problem of accuracy, in providing a kind of AD to sample, to remove bad point method and system.
Go bad point method in a kind of AD sampling, comprise the steps:
Obtain periods samples before the current sample values of the current period of sampled data and the n of correspondence position of multiple cycles before thereof, n=1,2,3,
The changing value that described sampled data produces is calculated according to periods samples before the current sample values of described current period and n;
According to the bad point criterion in described changing value and setting threshold value determination sampled data, comprise high threshold value and low threshold value;
If described changing value is greater than described high threshold value or lower than described low threshold value, then judge that the sampled value of correspondence position is as bad point, and calculate replacement values according to the sampled value of multiple cycle correspondence position, and with replacing the sampled value of described bad point.
Go bad point system in a kind of AD sampling, comprising:
Data sampling module, for periods samples before the n of the current sample values and correspondence position of multiple cycles before thereof that obtain the current period of sampled data, n=1,2,3,
Changing value computing module, for calculating the changing value that described sampled data produces according to periods samples before the current sample values of described current period and n;
Threshold value arranges module, for according to the bad point criterion in described changing value and setting threshold value determination sampled data, comprises high threshold value and low threshold value;
Bad point removes module, if be greater than described high threshold value for described changing value or lower than described low threshold value, then judge that the sampled value of correspondence position is as bad point, and calculate replacement values according to the sampled value of multiple cycle correspondence position, and with replacing the sampled value of described bad point.
Bad point method and system is removed in above-mentioned AD sampling, before utilizing, the sampled value of multiple sampled value of cycle correspondence position and the correspondence position in this cycle carries out discriminatory analysis, whether the sampled value analyzing this location point is in the scope of the high threshold arranged and low threshold value, thus judge the bad point in this cycle, to the effect of the process of bad point and accuracy good, the reliability of sampling and accuracy can be ensured.
Accompanying drawing explanation
Fig. 1 removes bad point method flow diagram in an embodiment A D sampling;
Fig. 2 removes bad point system architecture schematic diagram in an embodiment A D sampling.
Embodiment
The embodiment of bad point method and system is gone to be described in detail below in conjunction with accompanying drawing in AD sampling of the present invention.
Shown in figure 1, Fig. 1 removes bad point method flow diagram in an embodiment A D sampling, comprises the steps:
S10, obtains periods samples before the current sample values of the current period of sampled data and the n of correspondence position of multiple cycles before thereof, n=1,2,3,
In this step, the sampled data obtained comprises the sampled value of current period, n sampled value of multiple cycle correspondence position before also having current period.
S20, calculates according to periods samples before the current sample values of described current period and n the changing value that described sampled data produces;
In this step, the sampled value utilizing preceding step to obtain calculates the changing value that described sampled data produces, for calculating threshold value.
In one embodiment, calculate the step of changing value, can comprise as follows:
||f(0)-f(-T)|-|f(-T)-f(-2T)|-……|f(-(n-1)T)-f(-nT)||
Wherein, f (0) represents current sample values, n periods samples before f (-nT) represents, T indication cycle.The computing method of the present embodiment, can avoid common mode interference preferably.
S30, according to the bad point criterion in described changing value and setting threshold value determination sampled data, comprises high threshold value and low threshold value;
In this step, mainly calculate bad point criterion according to the changing value of sampled data with setting threshold value, the determination range consisted of high threshold value and low threshold value is here used as bad point criterion.
In one embodiment, calculate high threshold value and low threshold value step, can comprise as follows:
H＝α×ΔX+η
L＝β×H
Wherein, H represents high threshold value, and L represents low threshold value, and η represents setting threshold value, and Δ X represents changing value, and α represents setting variation factor, and β represents ratio value.
S40, if described changing value is greater than described high threshold value or lower than described low threshold value, then judge that the sampled value of correspondence position is as bad point, and calculates replacement values according to the sampled value of multiple cycle correspondence position, and with replacing the sampled value of described bad point.
In this step, by the sampled value of analyzing this location point whether in the scope of high threshold and low threshold value, thus the bad point in this cycle is judged; And the sampled value of multiple cycle correspondence position calculates the sampled value that replacement values replaces bad point before make use of, realize the object removing bad point, solve in AD sampling process and occur a certain instance sample value transforming mistakes and cause subsequent calculations to occur the problem of deviation, effectively improve sampling reliability and accuracy.
In one embodiment, described replacement values computing formula can be as follows:
f(0)’＝[f(-T)+f(-2T)+…+f(-nT)]/n
Wherein, f (0) ' represents replacement values, f (-T), f (-2T) ..., f (-nT) represents periods samples before n.
The scheme of above-described embodiment, by the mode of averaging, before utilization, the mean value of the sampled value of multiple cycle correspondence position replaces the sampled value of bad point, can calculate comparatively close replacement values, further increasing sampling reliability and accuracy.
As another embodiment, bad point method is gone in the AD sampling of the embodiment of the present invention, consider Significant Change factor, the sampled data of normal Significant Change is avoided to be mistaken for bad point, judge that the sampled value of correspondence position is as in bad point process in step S40, the processing procedure getting rid of Significant Change can also be comprised, specifically can be as follows:
The sampled value changing value adding up current period each sampled point interior of described sampled data is greater than described high threshold value or this number of times k lower than described low threshold value, if described number of times k exceedes set point number, then judge that sampled data is changed to Significant Change, otherwise be invalid change, judge that the sampled value of correspondence position is as bad point.
Be directed to the technical scheme of the various embodiments described above, set forth below during AD of the present invention samples and remove bad point method embody rule example more, with more clear technical scheme of the present invention.
In this embody rule example, η=0.2IN, α=0.1, β=1/2, n value is 2, and the sampled data in the first two cycle of namely getting carries out judgement bad point.
(1) for sampled data opens up the long buffering of three cycles, circulation is deposited, and sampled data is directly stored in this buffering.Then open up a buffering and deposit sampled data for calculating, if judge, sampled data is bad point, then do not refresh sampled data, now, sampled data for subsequent calculations is the sampled data of a upper cycle correspondence position, in addition, also needs to open up a buffering, deposit change flag (each sampled point of each passage all needs to judge), controlled by conversion mark.
(2) after sampling terminates, sampled data is cushioned stored in three cycles, calculate changing value and store.
Changing value computing formula is: Δ X=||f (0)-f (-T) |-| f (-T)-f (-2T) ||
F (0): represent current sample values;
F (-T): represent previous periods samples;
N periods samples before f (-2T) represents;
……
F (-nT): n periods samples before representing.
(3) two thresholds are set: high threshold and low threshold
Sample rate current fixes threshold η (namely setting threshold value): 0.2IN
High threshold H:H=0.1 × Δ X+0.2IN
Low threshold L:L=H/2
(4) when sampled data changing value is greater than high threshold or low threshold, temporarily do not refresh and calculate buffering, the number of times of high threshold value and low threshold value is exceeded in statistics one-period, if when number of times is greater than high threshold corresponding in table 1 or low threshold k value, think that change is effectively, refresh corresponding calculating buffered data, otherwise, replacement values calculating is carried out to the bad point that this cycle occurs, calculates the sampled value that replacement values substitutes bad point position.
Table 1: the reference value of threshold number of times
The reference value that above-mentioned table 1 provides, can select according to actual conditions.
The technical scheme of comprehensive the various embodiments described above, invention enhances the reliability that bad point judges, also improves the efficiency to the process of its bad point and accuracy, serves good booster action to the calculating of its follow-up effective value and breakdown judge.
Shown in figure 2, Fig. 2 removes bad point system architecture schematic diagram in an embodiment A D sampling.
Go bad point system in the AD sampling of the embodiment of the present invention, mainly comprise:
Data sampling module, for periods samples before the n of the current sample values and correspondence position of multiple cycles before thereof that obtain the current period of sampled data, n=1,2,3,
Changing value computing module, for calculating the changing value that described sampled data produces according to periods samples before the current sample values of described current period and n;
Threshold value arranges module, for according to the bad point criterion in described changing value and setting threshold value determination sampled data, comprises high threshold value and low threshold value;
Bad point removes module, if be greater than described high threshold value for described changing value or lower than described low threshold value, then judge that the sampled value of correspondence position is as bad point, and calculate replacement values according to the sampled value of multiple cycle correspondence position, and with replacing the sampled value of described bad point.
In one embodiment, described changing value computing module utilizes following formulae discovery changing value:
||f(0)-f(-T)|-|f(-T)-f(-2T)|-……|f(-(n-1)T)-f(-nT)||
Wherein, f (0) represents current sample values, n periods samples before f (-nT) represents, T indication cycle.
In one embodiment, described threshold value arranges module and utilizes following formula to determine high threshold value and low threshold value:
H＝α×ΔX+η
L＝β×H
Wherein, H represents high threshold value, and L represents low threshold value, and η represents setting threshold value, and Δ X represents changing value, and α represents setting variation factor, and β represents ratio value.
In one embodiment, described replacement values computing formula is as follows:
f(0)’＝[f(-T)+f(-2T)+…+f(-nT)]/n
Wherein, f (0) ' represents replacement values, f (-T), f (-2T) ..., f (-nT) represents periods samples before n.
In one embodiment, described bad point remove module also for:
The sampled value changing value adding up current period each sampled point interior of described sampled data is greater than described high threshold value or this number of times k lower than described low threshold value, if described number of times k exceedes set point number, then judge that sampled data is changed to Significant Change, otherwise be invalid change, judge that the sampled value of correspondence position is as bad point.
Bad point method one_to_one corresponding is removed in going bad point system and AD of the present invention to sample in AD sampling of the present invention, the technical characteristic going the embodiment of bad point method to set forth in above-mentioned AD sampling and beneficial effect thereof are all applicable to go, in the embodiment of bad point system, hereby to state in AD sampling.
The above embodiment only have expressed several embodiment of the present invention, and it describes comparatively concrete and detailed, but therefore can not be interpreted as the restriction to the scope of the claims of the present invention.It should be pointed out that for the person of ordinary skill of the art, without departing from the inventive concept of the premise, can also make some distortion and improvement, these all belong to protection scope of the present invention.Therefore, the protection domain of patent of the present invention should be as the criterion with claims.
Claims (10)
1. go a bad point method in AD sampling, it is characterized in that, comprise the steps:
Obtain periods samples before the current sample values of the current period of sampled data and the n of correspondence position of multiple cycles before thereof, n=1,2,3,
The changing value that described sampled data produces is calculated according to periods samples before the current sample values of described current period and n;
According to the bad point criterion in described changing value and setting threshold value determination sampled data, comprise high threshold value and low threshold value;
If described changing value is greater than described high threshold value or lower than described low threshold value, then judge that the sampled value of correspondence position is as bad point, and calculate replacement values according to the sampled value of multiple cycle correspondence position, and with replacing the sampled value of described bad point.
2. go bad point method in AD sampling according to claim 1, it is characterized in that, the step that the described current sample values according to described current period and front n periods samples calculate the changing value that described sampled data produces comprises:
||f(0)-f(-T)|-|f(-T)-f(-2T)|-……|f(-(n-1)T)-f(-nT)||
Wherein, f (0) represents current sample values, n periods samples before f (-nT) represents, T indication cycle.
3. go bad point method in AD sampling according to claim 1, it is characterized in that, according to the bad point criterion in described changing value and setting threshold value determination sampled data, the step comprising high threshold value and low threshold value comprises:
H＝α×ΔX+η
L＝β×H
Wherein, H represents high threshold value, and L represents low threshold value, and η represents setting threshold value, and Δ X represents changing value, and α represents setting variation factor, and β represents ratio value.
4. go bad point method in AD sampling according to claim 2, it is characterized in that, described replacement values computing formula is as follows:
f(0)’＝[f(-T)+f(-2T)+…+f(-nT)]/n
Wherein, f (0) ' represents replacement values, f (-T), f (-2T) ..., f (-nT) represents periods samples before n.
5. go bad point method in the AD sampling according to any one of Claims 1-4, it is characterized in that, also comprise:
The sampled value changing value adding up current period each sampled point interior of described sampled data is greater than described high threshold value or this number of times k lower than described low threshold value, if described number of times k exceedes set point number, then judge that sampled data is changed to Significant Change, otherwise be invalid change, judge that the sampled value of correspondence position is as bad point.
6. go a bad point system in AD sampling, it is characterized in that, comprising:
Data sampling module, for periods samples before the n of the current sample values and correspondence position of multiple cycles before thereof that obtain the current period of sampled data, n=1,2,3,
Changing value computing module, for calculating the changing value that described sampled data produces according to periods samples before the current sample values of described current period and n;
Threshold value arranges module, for according to the bad point criterion in described changing value and setting threshold value determination sampled data, comprises high threshold value and low threshold value;
Bad point removes module, if be greater than described high threshold value for described changing value or lower than described low threshold value, then judge that the sampled value of correspondence position is as bad point, and calculate replacement values according to the sampled value of multiple cycle correspondence position, and with replacing the sampled value of described bad point.
7. go bad point system in AD sampling according to claim 6, it is characterized in that, described changing value computing module utilizes following formulae discovery changing value:
||f(0)-f(-T)|-|f(-T)-f(-2T)|-……|f(-(n-1)T)-f(-nT)||
Wherein, f (0) represents current sample values, n periods samples before f (-nT) represents, T indication cycle.
8. go bad point system in AD sampling according to claim 6, it is characterized in that, described threshold value arranges module and utilizes following formula to determine high threshold value and low threshold value:
H＝α×ΔX+η
L＝β×H
Wherein, H represents high threshold value, and L represents low threshold value, and η represents setting threshold value, and Δ X represents changing value, and α represents setting variation factor, and β represents ratio value.
9. go bad point system in AD sampling according to claim 7, it is characterized in that, described replacement values computing formula is as follows:
f(0)’＝[f(-T)+f(-2T)+…+f(-nT)]/n
Wherein, f (0) ' represents replacement values, f (-T), f (-2T) ..., f (-nT) represents periods samples before n.
10. go bad point system in the AD sampling according to any one of claim 6 to 9, it is characterized in that, described bad point remove module also for:
The sampled value changing value adding up current period each sampled point interior of described sampled data is greater than described high threshold value or this number of times k lower than described low threshold value, if described number of times k exceedes set point number, then judge that sampled data is changed to Significant Change, otherwise be invalid change, judge that the sampled value of correspondence position is as bad point.
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Application publication date: 20150422 |