CN110730000A - Method and device for extracting key data from sampling data - Google Patents
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Abstract
The invention relates to a computer technology, in particular to a method and a device for extracting key data from sampling data, which are used for reducing data transmission load and improving data transmission efficiency. The method comprises the following steps: and respectively screening all sampling points with single-point recovery errors reaching a preset error threshold value as key sampling points aiming at each main control index in at least one main control index corresponding to the sampling data, and extracting the sampling data corresponding to each key sampling point as key data based on all key sampling points obtained corresponding to the at least one main control index. Therefore, the value of the single-point recovery error can reflect the key of the data, so that the sampling point with the single-point recovery error reaching the preset error threshold value is used as the key sampling point to extract the key data, and the redundant data in the sampled data can be removed to the maximum extent under the specified compression precision, thereby effectively reducing the data transmission load and further improving the data transmission efficiency.
Description
Technical Field
The present invention relates to computer technologies, and in particular, to a method and an apparatus for extracting key data from sampled data.
Background
In order to effectively monitor the operating state of the equipment, in general, a sensor is required to sample the working condition data of the equipment, and then the sampled data is transmitted back as it is. The sampling data is an important basis for remotely monitoring, analyzing and predicting the running state of the equipment.
In the prior art, a data sampling mode with a fixed period is mostly adopted. To ensure that abnormal condition data is not missed, the sampling period is usually set to be relatively small (e.g., 4 seconds). However, during the period of stable operation of the device, a small sampling period may cause over-dense data acquisition, which results in an excessive data retention amount, and further, when the sampled data is directly returned, the data transmission load is large, and the useless transmission cost is high.
In practical application, the amount of information contained in each sample data is different. For example, during the non-stationary operation of the apparatus (i.e., the data fluctuation region), the sampled data is mostly large information amount data and even necessary data, and during the stationary operation of the apparatus (i.e., the data balance region), the sampled data is mostly low information amount data and even zero information amount data. However, at present, the sensor can only sample data according to a fixed sampling period in a data fluctuation area and a data stable area. And the sampled data is not subjected to redundancy removal, namely, the sampled data is subjected to back transmission.
Therefore, redundant data in the sampled data are removed, data compression is achieved, and the method has important values for reducing data transmission scale, improving data transmission efficiency and reducing data transmission cost.
However, the conventional encoding and decoding data compression method cannot effectively remove the sampling redundant data with low information content in the sampling data, so that the data transmission load is still increased to a certain extent, and the data transmission efficiency is reduced.
In view of the above, there is a need to provide a method for removing redundant data, which overcomes the above-mentioned drawbacks.
Disclosure of Invention
The embodiment of the invention provides a method and a device for extracting key data from sampling data, which are used for reducing data transmission load and improving data transmission efficiency.
The embodiment of the invention provides the following specific technical scheme:
a method of extracting key data from sampled data, comprising:
determining at least one main control index corresponding to the sampling data, wherein one main control index represents a measurement parameter on one reference dimension;
respectively aiming at each master control index contained in the at least one master control index, executing the following operations: screening out sampling points with all single-point recovery errors reaching a preset error threshold value as key sampling points aiming at a main control index, wherein the single-point recovery errors are the difference values of interpolation data and corresponding sampling data of one sampling point;
and extracting sampling data corresponding to each key sampling point as key data based on all key sampling points obtained corresponding to the at least one main control index.
Optionally, for a main control index, screening out all sampling points with single-point recovery errors smaller than a preset error threshold as key sampling points, including:
determining at least two key sampling points specified for the one master index;
the following operations are executed in a loop:
determining a group of adjacent key sampling points, and performing linear interpolation on each non-key sampling point between the group of key sampling points to obtain corresponding interpolation data;
calculating single-point recovery errors of all non-critical sampling points, screening out the non-critical sampling points with the single-point recovery errors reaching a preset sampling precision threshold value, and selecting one from the screened non-critical sampling points to be converted into a critical sampling point;
and judging whether the single point recovery errors of all the non-key sampling points are smaller than the sampling precision threshold, if so, ending the operation, and otherwise, continuously selecting a group of adjacent key sampling points.
Optionally, selecting one of the screened non-critical sampling points to be converted into a critical sampling point, including;
selecting one non-critical sampling point with the largest single-point recovery error from the screened non-critical sampling points and converting the non-critical sampling point into a critical sampling point; if a plurality of non-key sampling points with the maximum single-point recovery error appear, one sampling point is randomly selected to be converted into a key sampling point.
Optionally, based on all key sampling points obtained corresponding to the at least one master control index, extracting sampling data corresponding to each key sampling point, as key data, including:
if the at least one main control index only comprises one main control index, extracting sampling data corresponding to the one main control index as key data based on each key sampling point corresponding to the one main control index;
if the at least one main control index comprises two or more main control indexes, respectively extracting the sampling data corresponding to the corresponding main control indexes based on each key sampling point corresponding to each main control index, and merging the sampling data corresponding to each main control index to obtain corresponding key data, or respectively taking the sampling data corresponding to each main control index as the key data.
Optionally, further comprising:
if the total data volume of the sampled data is determined to reach the set threshold, the sampled data is divided into a plurality of data segments according to the set data volume, and key data corresponding to at least one main control index are respectively extracted for each data segment.
Optionally, further comprising:
determining at least one main control index corresponding to the key data;
respectively aiming at each master control index contained in the at least one master control index, executing the following operations:
determining each key sampling point corresponding to one main control index;
and performing linear interpolation between the key data corresponding to every two adjacent key sampling points according to a set time interval to obtain corresponding interpolation data.
And taking all key data and interpolation data corresponding to the main control index as reduction sampling data corresponding to the main control index.
Optionally, further comprising:
calculating a compression loss parameter corresponding to the key data extraction process based on each interpolation data inserted in the key data and the sampling data at the corresponding position;
judging whether the compression loss parameter reaches a preset expected value or not;
if so, reducing the error threshold value according to a first set step length;
otherwise, increasing the error threshold value according to a second setting step.
Optionally, further comprising:
if the error threshold value is reduced according to the first set step length, when the compression loss parameter corresponding to the last key data extraction process is judged not to reach the preset expected value, and the compression loss parameter corresponding to the current key data extraction process reaches the preset expected value, the adjusted error threshold value after the current key data extraction is taken as the optimal error threshold value to be reported:
if the error threshold value is increased according to the second set step length, when the compression loss parameter corresponding to the last key data extraction process is judged to reach the preset expected value, and the compression loss parameter corresponding to the current key data extraction process does not reach the preset expected value, the adjusted error threshold value after the current key data extraction is taken as the optimal error threshold value to be reported.
An apparatus for extracting key data from sampled data, comprising:
the device comprises a determining unit, a calculating unit and a processing unit, wherein the determining unit is used for determining at least one main control index corresponding to sampling data, and one main control index represents a measurement parameter on one reference dimension;
a processing unit, configured to perform the following operations for each master index included in the at least one master index, respectively: screening out sampling points with all single-point recovery errors reaching a preset error threshold value as key sampling points aiming at a main control index, wherein the single-point recovery errors are the difference values of interpolation data and corresponding sampling data of one sampling point;
and the extraction unit is used for extracting sampling data corresponding to each key sampling point as key data based on all key sampling points obtained corresponding to the at least one main control index.
Optionally, when all sampling points with single-point recovery errors smaller than a preset error threshold are screened out as key sampling points for one master control index, the processing unit is configured to:
determining at least two key sampling points specified for the one master index;
the following operations are executed in a loop:
determining a group of adjacent key sampling points, and performing linear interpolation on each non-key sampling point between the group of key sampling points to obtain corresponding interpolation data;
calculating single-point recovery errors of all non-critical sampling points, screening out the non-critical sampling points with the single-point recovery errors reaching a preset sampling precision threshold value, and selecting one from the screened non-critical sampling points to be converted into a critical sampling point;
and judging whether the single point recovery errors of all the non-key sampling points are smaller than the sampling precision threshold, if so, ending the operation, and otherwise, continuously selecting a group of adjacent key sampling points.
Optionally, when one of the screened non-critical sampling points is selected to be converted into a critical sampling point, the processing unit is configured to:
selecting one non-critical sampling point with the largest single-point recovery error from the screened non-critical sampling points and converting the non-critical sampling point into a critical sampling point; if a plurality of non-key sampling points with the maximum single-point recovery error appear, one sampling point is randomly selected to be converted into a key sampling point.
Optionally, the extraction unit is configured to extract sampling data corresponding to each key sampling point based on all key sampling points obtained corresponding to the at least one master control indicator, and when the extracted sampling data is used as key data, the extraction unit is configured to:
if the at least one main control index only comprises one main control index, extracting sampling data corresponding to the one main control index as key data based on each key sampling point corresponding to the one main control index;
if the at least one main control index comprises two or more main control indexes, respectively extracting the sampling data corresponding to the corresponding main control indexes based on each key sampling point corresponding to each main control index, and combining the sampling data corresponding to each main control index to obtain corresponding key data.
Optionally, the processing unit is further configured to:
if the total data volume of the sampled data is determined to reach a set threshold value, dividing the sampled data into a plurality of data segments according to the set data volume;
the extraction unit is further configured to:
and respectively extracting key data corresponding to at least one main control index for each data segment.
Optionally, further comprising: a recovery unit for performing the following operations:
determining at least one main control index corresponding to the key data;
respectively aiming at each master control index contained in the at least one master control index, executing the following operations:
determining each key sampling point corresponding to one main control index;
and performing linear interpolation between the key data corresponding to every two adjacent key sampling points according to a set time interval to obtain corresponding interpolation data.
And taking all key data and interpolation data corresponding to the main control index as reduction sampling data corresponding to the main control index.
Optionally, the processing unit is further configured to:
calculating a compression loss parameter corresponding to the key data extraction process based on each interpolation data inserted in the key data and the sampling data at the corresponding position;
judging whether the compression loss parameter reaches a preset expected value or not;
if so, reducing the error threshold value according to a first set step length;
otherwise, increasing the error threshold value according to a second setting step.
Optionally, the processing unit is further configured to:
if the error threshold value is reduced according to the first set step length, when the compression loss parameter corresponding to the last key data extraction process is judged not to reach the preset expected value, and the compression loss parameter corresponding to the current key data extraction process reaches the preset expected value, the adjusted error threshold value after the current key data extraction is taken as the optimal error threshold value to be reported:
if the error threshold value is increased according to the second set step length, when the compression loss parameter corresponding to the last key data extraction process is judged to reach the preset expected value, and the compression loss parameter corresponding to the current key data extraction process does not reach the preset expected value, the adjusted error threshold value after the current key data extraction is taken as the optimal error threshold value to be reported.
A storage medium storing a program for implementing extraction of key data from sampled data, the program when executed by a processor performing the steps of:
determining at least one main control index corresponding to the sampling data, wherein one main control index represents a measurement parameter on one reference dimension;
respectively aiming at each master control index contained in the at least one master control index, executing the following operations: screening out sampling points with all single-point recovery errors reaching a preset error threshold value as key sampling points aiming at a main control index, wherein the single-point recovery errors are the difference values of interpolation data and corresponding sampling data of one sampling point;
and extracting sampling data corresponding to each key sampling point as key data based on all key sampling points obtained corresponding to the at least one main control index.
A communications apparatus comprising one or more processors; and
one or more computer-readable media having instructions stored thereon that, when executed by the one or more processors, cause the apparatus to perform the method of any of the above.
In the embodiment of the invention, aiming at each main control index in at least one main control index corresponding to sampling data, all sampling points with single-point recovery errors reaching a preset error threshold value are respectively screened out to be used as key sampling points, the single-point recovery errors are the difference values of interpolation data of one sampling point and corresponding sampling data, and then the sampling data corresponding to each key sampling point is extracted to be used as key data based on all key sampling points obtained corresponding to the at least one main control index. Therefore, the value of the single-point recovery error can reflect the criticality of the data, so that the sampling point with the single-point recovery error reaching the preset error threshold value is used as the key sampling point to extract the key data, and redundant data in the sampled data can be removed to the maximum extent under the specified compression precision, so that the data transmission load is effectively reduced, and the data transmission efficiency is improved; the technical scheme provided by the embodiment of the invention has the advantages of simple algorithm principle, low operation amount and easy function realization at a hardware end.
Drawings
FIG. 1 is a schematic flow chart illustrating a process of extracting target key data from sample data according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating key data matrix initialization according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating a key data matrix according to an embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating key data matrix fusion corresponding to different master control indexes according to an embodiment of the present disclosure;
FIG. 5 is a schematic diagram of key data matrix fusion corresponding to different data segments in an embodiment of the present invention;
fig. 6 is a functional structure diagram of an apparatus for extracting key data from sample data according to an embodiment of the present invention.
Detailed Description
In order to reduce data transmission load and improve data transmission efficiency, in the embodiment of the invention, sampling points with single-point recovery errors reaching a preset error threshold value are screened out from all sampling points to be used as key sampling points, and then sampling data corresponding to the key sampling points are extracted to be used as key data.
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
In the embodiment of the present invention, the structure characteristics of the sampling data of the device are as follows:
each sampling point is associated according to a time sequence dimension (hereinafter, referred to as a "sampling serial number"); the sampling sequence number can be represented by a specific time point, such as an X point Y minutes Z seconds, or can be represented by a number, such as 1, 2, and 3, which represents the collection sequence of the sampling points. Besides the sampling numbers, the sampling data corresponding to each sampling point includes a plurality of common measurement indexes (e.g., temperature and pressure … …) that change according to time sequence, and in the process of removing redundant data, a part of the measurement indexes needs to be extracted as reference dimensions to extract key data, these specified measurement indexes are called main control indexes, and other measurement indexes can also be used as auxiliary indexes.
Then, the data structure of the sampled data of one sample point is in the form of { sample number, main control index 1, main control index 2, … …, auxiliary index 1, auxiliary index 2 … … }.
Referring to fig. 1, in the embodiment of the present invention, a detailed process for extracting target key data from sample data is as follows:
step 100: and determining at least one main control index corresponding to the sampling data, wherein one main control index represents a measurement parameter on one reference dimension.
As described above, the data structure of the sampled data of one sample point is in the form of { sample sequence number, main index 1, main index 2, … …, auxiliary index 1, auxiliary index 2 … … }, and thus, one sampled data corresponds to at least one main index.
Step 110: respectively executing the following operations based on each master control index contained in the at least one master control index: and screening all sampling points with single-point recovery errors reaching a preset error threshold value as key sampling points aiming at a main control index, wherein the single-point recovery errors are the difference values of interpolation data and corresponding sampling data of one sampling point.
Specifically, taking any one main control index as an example (hereinafter referred to as a main control index x), when all sampling points with single-point recovery errors smaller than a preset error threshold value are screened out as key sampling points for the main control index x, the method specifically includes:
A. firstly, determining at least two key sampling points specified by a main control index x;
specifically, referring to fig. 2, in the embodiment of the present invention, a key data matrix needs to be established first for the main control index x, where the dimension of the key data matrix is 2N, where N is the total number of sampling points, the 1 st action is a sampling sequence number (expressed in a digital form as an example), and the 2 nd action is an identification period of a data criticality determination result.
For example, as shown in fig. 2, optionally, in the initialization process, the data criticality determination results of the sampling point 1 and the sampling point N are marked as 1, the data criticality determination results of the remaining sampling points are marked as 0, that is, the start sampling point and the end sampling point are marked as critical sampling points, and the remaining sampling points are temporarily marked as non-critical sampling points.
B. The following operations are executed in a loop:
determining a group of adjacent key sampling points, and performing linear interpolation on each non-key sampling point between the group of key sampling points to obtain corresponding interpolation data;
calculating single-point recovery errors of all non-critical sampling points, screening out the non-critical sampling points with the single-point recovery errors reaching a preset error threshold value, and selecting one from the screened non-critical sampling points to be converted into a critical sampling point;
and judging whether the single point recovery errors of all the non-key sampling points are smaller than the sampling precision threshold, if so, ending the operation, and otherwise, continuously selecting a group of adjacent key sampling points.
When one selected from the screened non-critical sampling points is converted into a critical sampling point, optionally, the non-critical sampling point with the largest single-point recovery error value can be selected to be converted into the critical sampling point, wherein if a plurality of non-critical sampling points with the largest single-point recovery errors occur, one selected non-critical sampling point is randomly converted into the critical sampling point (for example, the first non-critical sampling point with the largest single-point recovery error).
For example, as shown in fig. 2, assuming that a group of key sampling points selected for the first time is a designated key sampling point, sampling point 1 and sampling point N, then, a linear interpolation operation is performed on sampling point 2-sampling point N-1 as a non-key sampling point, and a single-point recovery error of each non-key sampling point is calculated, and assuming that the single-point recovery errors of sampling point 4, sampling point 5 and sampling point N-1 all reach a preset error threshold, then, a sampling point 5 with the largest single-point recovery error is selected from the non-key sampling points, and is converted into the key sampling point from the non-key sampling points.
Then, in the next iteration process, it is necessary to select sampling point 1 and sampling point 5 as a new set of adjacent key sampling points, and also to select sampling point 5 and sampling point N as a new set of adjacent key sampling points, and continue the above-mentioned repetitive operation, between sampling point 1 and sampling point 5, perform linear interpolation on non-key sampling points, and select a non-key sampling point whose single-point recovery error reaches a preset error threshold value and whose value is the largest, and convert it into a key sampling point, and between sampling point 5 and sampling point N, perform linear interpolation operation on non-key sampling points, and select a non-key sampling point whose single-point recovery error reaches a preset error threshold value and whose value is the largest, and convert it into a key sampling point, and then, based on the newly generated key sampling point, continue to select a new set of adjacent key sampling points, and continue to repeat, and repeating the iteration until the single point recovery errors of the non-key sampling points among all the key sampling points are smaller than a preset error threshold value.
The single-point recovery error of the non-critical sampling point between two adjacent critical sampling points is smaller than a preset error threshold value, which indicates that the section with the two adjacent critical sampling points as the end points has reached an approximate steady state, and then the section does not participate in the judgment process of any one time of searching the critical sampling points. Correspondingly, in the key data matrix shown in fig. 2, the data criticality determination result of the selected key sampling point may be marked as 1, and the data criticality determination result of the non-key sampling point may be marked as 0, so that all the key sampling points corresponding to the main control index x are finally obtained, and the key data matrix corresponding to the main control index x is finally formed.
The specific operation is as follows:
wherein K represents a linear interpolation slope between adjacent key sampling points, i represents the ith key sampling point in the key data matrix, and KiFor the sampling number, X, corresponding to the ith key sampling pointKiAnd YKiRespectively corresponding sampling data of the ith key sampling point on a time dimension and corresponding sampling data on a main control index, wherein M represents the number of the existing key sampling points in the current key data matrix, and j represents the number between K in the key data matrixiAnd Ki+1The jth non-critical sampling point in between,and indicating the interpolation data corresponding to the jth non-key sampling point on a main control index, wherein delta Y indicates a single-point recovery error at the jth j, and Thv indicates a preset error threshold value.
Step 120: and extracting sampling data corresponding to each key sampling point as key data based on all key sampling points obtained corresponding to the at least one main control index.
In order to remove redundant data to the maximum extent, and to ensure that the extracted key data does not lose required critical information after data compression and data recovery (i.e. to ensure the authenticity of the extracted key data), and to reduce the data transmission scale to a certain extent, the key data must be derived from the original data sequence obtained by sampling at a fixed period, and cannot be the fitting result.
In the embodiment of the present invention, when step 130 is executed, the following two cases can be divided into, but not limited to:
the first case is: the at least one master index only comprises one master index.
At this time, the sampling data corresponding to the one main control indicator may be extracted as the key data directly based on each key sampling point corresponding to the one main control indicator.
For example: referring to fig. 3, assuming that the key sampling points corresponding to the main control index 1 include a sampling point 1, a sampling point 5, and a sampling point 10, it is necessary to extract sampling data obtained at the sampling point 1, the sampling point 5, and the sampling point 10, respectively, as final key data.
After the key data are obtained, the key data can be directly transmitted back, and the compression of the sampling data is completed while the key data are obtained.
The second case is: if the at least one main control index comprises two or more main control indexes, respectively extracting corresponding sampling data corresponding to the main control indexes based on each key sampling point corresponding to each main control index, and combining the sampling data corresponding to each main control index to obtain corresponding key data; or, the sampling data corresponding to each main control index is respectively used as key data.
For example, as shown in fig. 4, if a key sampling point corresponding to the main control index 1 has sampling point 1, sampling point 5, and sampling point 10, and a key sampling point corresponding to the main control index 2 has sampling point 1, sampling point 3, sampling point 8, and sampling point 10, then sampling data corresponding to the main control index 1 (hereinafter referred to as sampling data 1) is extracted based on the sampling point 1, sampling point 5, and sampling point 10, and sampling data corresponding to the main control index 2 (hereinafter referred to as sampling data 2) is extracted based on the sampling point 1, sampling point 3, sampling point 8, and sampling point 10, and then after the sampling data 1 and the sampling data 2 are combined, the combined data is used as key data; optionally, deduplication processing may also be performed in the merging process.
Then, after the fused key data is obtained, the fused key data can be directly transmitted back, and the compression of the sampling data is completed while the key data is obtained.
For another example, still assuming that the key sampling point corresponding to the main control index 1 has sampling point 1, sampling point 5, and sampling point 10, and the key sampling point corresponding to the main control index 2 has sampling point 1, sampling point 3, sampling point 8, and sampling point 10, then the sampling data corresponding to the main control index 1 (hereinafter referred to as sampling data 1) is extracted based on the sampling point 1, sampling point 5, and sampling point 10, and the sampling data corresponding to the main control index 2 (hereinafter referred to as sampling data 2) is extracted based on the sampling point 1, sampling point 3, sampling point 8, and sampling point 10, and then the sampling data 1 and the sampling data 2 are respectively determined as the key data.
After the key data are obtained, the key data can be respectively transmitted back, namely the key data are subjected to sub-packet processing, and the compression of the sampling data is completed while the key data are obtained.
In practical application, the key data is necessary data for data engineering analysis and application, the contained data information amount is large, and the accurate key data can be finally obtained only by accurately extracting the sampling data of each key sampling point corresponding to each main control index contained in at least one main control index.
In the embodiment of the present invention, by using the above manner, accurate key data is extracted, and taking a main control index as an example, the key data corresponding to one main control index may characterize the change characteristics of the sampled data under the dimension of the main control index, specifically, the key data at least includes but is not limited to one or any combination of the following data: under the dimension (such as temperature, pressure and the like) of a main control index, the initial data and the ending data contained in the sampling data, the extreme value data (such as the most value data) contained in the sampling data and the corresponding process maintenance data, and the data collected in an approximate stable interval in the sampling data, wherein the approximate stable interval is the sampling interval with the data fluctuation lower than a set threshold value, and the like are potential critical data.
By adopting the technical scheme provided by the embodiment of the invention, the sampling data of each type can be accurately extracted and stored as key data, so that accurate reference information is provided for the working condition analysis of equipment.
Based on the above embodiment, in practical application, there may be oversized sampling data, and in this case, in the embodiment of the present invention, if it is determined that the total data volume of the sampling data reaches the set threshold, the sampling data is divided into a plurality of data segments according to the set data volume, and for each data segment, key data corresponding to at least one master control index is extracted.
Each data segment may correspond to one or more master indexes, and the extraction manner of the key data of each data facet corresponding to one master index or a plurality of master indexes may refer to steps 100 to 130 to describe the technical solution, which is not described herein again.
Correspondingly, the key data corresponding to each data segment are connected in series end to end, and the key data corresponding to the ultra-large-scale sampling data can be obtained finally.
For example, as shown in fig. 5, assuming that after the sampling data is divided into the data segment 1 and the data segment 2, corresponding key sampling points are extracted respectively, and then the final key sampling points are the sampling point 1, the sampling point 7, the sampling point 11, the sampling point 15, the sampling point 17, and the sampling point 20 through merging, then the sampling data extracted corresponding to these sampling points is the final required key data.
Correspondingly, in the embodiment of the present invention, after the key data is sent, sample data restoration may be performed based on the key data, which specifically includes:
determining at least one main control index corresponding to the key data;
respectively aiming at each master control index contained in the at least one master control index, executing the following operations:
determining each key sampling point corresponding to one main control index;
and performing linear interpolation between the key data corresponding to every two adjacent key sampling points according to a set time interval to obtain corresponding interpolation data.
And taking all key data and interpolation data corresponding to the main control index as reduction sampling data corresponding to the main control index.
TABLE 1
(equal interval interpolation processing in time dimension)
For example: taking a master control index as an example, referring to table 1, based on a given sampling interval of the sampled data, performing equal-interval linear interpolation between the key data corresponding to each adjacent key sampling point,
specifically, the following formula may be adopted: .
Wherein K represents a linear interpolation slope between adjacent key sampling points, i represents the ith key sampling point in the key data matrix, and KiFor the sampling number, X, corresponding to the ith key sampling pointKiAnd YKiRespectively corresponding key data of the ith key sampling point on a time dimension and corresponding key data on a main control index, wherein M represents the number of the existing key sampling points in the key data, delta t is a time interval of linear interpolation,to correspond to a positionThe interpolation data of (1).
Therefore, in the embodiment of the present invention, in the sampling data reduction process, since the time interval used for performing the linear interpolation is the sampling interval used for performing the data sampling, in practice, the linear interpolation is performed between adjacent key data according to the set time interval, that is, the linear interpolation is performed at the position of the non-key sampling point between two key sampling points, so that the key data corresponding to each key sampling point and the interpolated data corresponding to each non-key sampling point are finally merged, and the reduced sampling data is obtained.
Further, based on the above embodiment, in the embodiment of the present invention, after extracting the key data each time, optionally, the error threshold value used in the extraction process needs to be adjusted. This is because: the value of the error threshold value cannot be too small or too large. If the data transmission rate is too small, redundant data cannot be removed to the maximum extent, and system transmission load can be caused; if the size is too large, enough key data cannot be extracted, so that subsequent working condition analysis is influenced. Therefore, after extracting the key data each time, the error threshold value needs to be adjusted to reach the optimal value.
Optionally, in the embodiment of the present invention, when the error threshold is adjusted, the following method may be adopted, but is not limited to: calculating a compression loss parameter corresponding to the key data extraction process based on each interpolation data inserted in the key data and the sampling data at the corresponding position, and judging whether the compression loss parameter reaches a preset expected value, if so, reducing a preset error threshold value according to a first set step length, otherwise, increasing the preset error threshold value according to a second set step; the initial value of the error threshold may be set empirically, and the first setting step and the second setting step may be set as a fixed value or a relative value, for example, the first setting step and the second setting step are both set as: 0.01 (maximum value of sampling data of main control index-minimum value of sampling data of main control index).
For convenience of description, in the following embodiments, the first setting step length and the second setting step length are taken as the same value for illustration, and will not be described again.
The values of the first setting step length and the second setting step length can be the same or different, and can be flexibly configured according to specific application environments. While the error threshold value
In practical applications, the compression loss parameter can be described by using a mean square error or an energy loss metric, which are described below separately.
A first scenario: the compression loss parameter is the mean square error LavThe corresponding expected value is LThThe first setting step and the second setting step are both Δ Thr.
Then, the formula is adoptedCalculating the mean square error LavWherein, in the step (A),interpolation data, Y, corresponding to a main control index on a non-key sampling point llAmt represents the sequence data amount of the original sample data, which corresponds to a master index at the non-critical sample point l.
If L isav≥LThAccording to the formula Thr ═ Thr0- Δ Thr adjusting the currently used error threshold value if Lav<LThAccording to the formula Thr ═ Thr0+ Δ Thr adjusts the currently used error threshold value.
If according to Thr ═ Thr0Adjusting the currently used error threshold value by delta Thr, and judging the L corresponding to the last key data extraction processavNot reach LThAnd L corresponding to the key data extraction process at this timeavTo reach LThThen, the key data extracted this time is calledAnd reporting the integral error threshold value as an optimal error threshold value.
If according to Thr ═ Thr0Adjusting the currently used error threshold value by + delta Thr, and judging the L corresponding to the last key data extraction processavTo reach LThAnd L corresponding to the key data extraction process at this timeavNot reach LThAnd then reporting the error threshold value adjusted after the key data is extracted as the optimal error threshold value.
A second scenario: the compression loss parameter is an energy loss measure ELThe corresponding expected value is EThThe first setting step and the second setting step are both Δ Thr.
Then, the formula is adopted
Calculating an energy loss metric ELWherein, in the step (A),
interpolation data, Y, corresponding to a main control index on a non-key sampling point llAmt represents the sequence data amount of the original sample data, which corresponds to a master index at the non-critical sample point l.
If E isL≥EThAccording to the formula Thr ═ Thr0- Δ Thr adjusting the currently used error threshold value if EL<EThAccording to the formula Thr ═ Thr0+ Δ Thr adjusts the currently used error threshold value.
If according to Thr ═ Thr0Adjusting the currently used error threshold value by delta Thr, and judging the corresponding E in the last key data extraction processLNot reach EThAnd E corresponding to the process of extracting the key data this timeLTo reach EThAnd then reporting the error threshold value adjusted after the key data is extracted as the optimal error threshold value.
If according to Thr ═ Thr0Adjusting the currently used error threshold value by + delta Thr, and judging the corresponding E in the last key data extraction processLTo reach EThAnd E corresponding to the process of extracting the key data this timeLNot reach EThAnd then reporting the error threshold value adjusted after the key data is extracted as the optimal error threshold value.
Based on the foregoing embodiments, referring to fig. 6, in an embodiment of the present invention, an apparatus for extracting key data from sampled data at least includes:
a determining unit 60, configured to determine at least one master control indicator corresponding to the sample data, where one master control indicator represents a measurement parameter in one reference dimension;
a processing unit 61, configured to perform the following operations for each master index included in the at least one master index: screening out sampling points with all single-point recovery errors reaching a preset error threshold value as key sampling points aiming at a main control index, wherein the single-point recovery errors are the difference values of interpolation data and corresponding sampling data of one sampling point;
and the extracting unit 62 is configured to extract sampling data corresponding to each key sampling point as key data based on all key sampling points obtained corresponding to the at least one master control index.
Optionally, when all sampling points with single-point recovery errors smaller than a preset error threshold are screened out as key sampling points for one main control index, the processing unit 61 is configured to:
determining at least two key sampling points specified for the one master index;
the following operations are executed in a loop:
determining a group of adjacent key sampling points, and performing linear interpolation on each non-key sampling point between the group of key sampling points to obtain corresponding interpolation data;
calculating single-point recovery errors of all non-critical sampling points, screening out the non-critical sampling points with the single-point recovery errors reaching a preset sampling precision threshold value, and selecting one from the screened non-critical sampling points to be converted into a critical sampling point;
and judging whether the single point recovery errors of all the non-key sampling points are smaller than the sampling precision threshold, if so, ending the operation, and otherwise, continuously selecting a group of adjacent key sampling points.
Optionally, when one of the screened non-critical sampling points is selected to be converted into a critical sampling point, the processing unit 61 is configured to:
selecting one non-critical sampling point with the largest single-point recovery error from the screened non-critical sampling points and converting the non-critical sampling point into a critical sampling point; if a plurality of non-key sampling points with the maximum single-point recovery error appear, one sampling point is randomly selected to be converted into a key sampling point.
Optionally, the extraction unit 62 is configured to extract sampling data corresponding to each key sampling point based on all key sampling points obtained corresponding to the at least one master control indicator, and when the extracted sampling data is used as key data:
if the at least one main control index only comprises one main control index, extracting sampling data corresponding to the one main control index as key data based on each key sampling point corresponding to the one main control index;
if the at least one main control index comprises two or more main control indexes, respectively extracting the sampling data corresponding to the corresponding main control indexes based on each key sampling point corresponding to each main control index, and merging the sampling data corresponding to each main control index to obtain corresponding key data, or respectively taking the sampling data corresponding to each main control index as the key data.
Optionally, the processing unit 61 is further configured to:
if the total data volume of the sampled data is determined to reach a set threshold value, dividing the sampled data into a plurality of data segments according to the set data volume;
the extraction unit 62 is further configured to:
and respectively extracting key data corresponding to at least one main control index for each data segment.
Optionally, further comprising: a recovery unit 63 for performing the following operations:
determining at least one main control index corresponding to the key data;
respectively aiming at each master control index contained in the at least one master control index, executing the following operations:
determining each key sampling point corresponding to one main control index;
and performing linear interpolation between the key data corresponding to every two adjacent key sampling points according to a set time interval to obtain corresponding interpolation data.
And taking all key data and interpolation data corresponding to the main control index as reduction sampling data corresponding to the main control index.
Optionally, the processing unit 61 is further configured to:
calculating a compression loss parameter corresponding to the key data extraction process based on each interpolation data inserted in the key data and the sampling data at the corresponding position;
judging whether the compression loss parameter reaches a preset expected value or not;
if so, reducing the error threshold value according to a first set step length;
otherwise, increasing the error threshold value according to a second setting step.
Optionally, the processing unit 61 is further configured to:
if the error threshold value is reduced according to the first set step length, when the compression loss parameter corresponding to the last key data extraction process is judged not to reach the preset expected value, and the compression loss parameter corresponding to the current key data extraction process reaches the preset expected value, the adjusted error threshold value after the current key data extraction is taken as the optimal error threshold value to be reported:
if the error threshold value is increased according to the second set step length, when the compression loss parameter corresponding to the last key data extraction process is judged to reach the preset expected value, and the compression loss parameter corresponding to the current key data extraction process does not reach the preset expected value, the adjusted error threshold value after the current key data extraction is taken as the optimal error threshold value to be reported.
Based on the same inventive concept, an embodiment of the present invention provides a storage medium storing a program for implementing extraction of key data from sampled data, where the program, when executed by a processor, performs the following steps:
determining at least one main control index corresponding to the sampling data, wherein one main control index represents a measurement parameter on one reference dimension;
respectively aiming at each master control index contained in the at least one master control index, executing the following operations: screening out sampling points with all single-point recovery errors reaching a preset error threshold value as key sampling points aiming at a main control index, wherein the single-point recovery errors are the difference values of interpolation data and corresponding sampling data of one sampling point;
and extracting sampling data corresponding to each key sampling point as key data based on all key sampling points obtained corresponding to the at least one main control index.
Based on the same inventive concept, the embodiment of the invention provides a communication device, which comprises one or more processors; and
one or more computer-readable media having instructions stored thereon that, when executed by the one or more processors, cause the apparatus to perform the method of any of the above.
In summary, in the embodiment of the present invention, for each main control index of at least one main control index corresponding to the sampled data, all sampling points whose single-point recovery errors reach a preset error threshold are respectively screened out as key sampling points, where the single-point recovery errors are differences between interpolation data of one sampling point and corresponding sampled data, and then, based on all key sampling points obtained corresponding to the at least one main control index, the sampled data corresponding to each key sampling point is extracted as key data. Therefore, the value of the single-point recovery error can reflect the criticality of the data, so that the sampling point with the single-point recovery error reaching the preset error threshold value is used as the key sampling point to extract the key data, and redundant data in the sampled data can be removed to the maximum extent under the specified compression precision, so that the data transmission load is effectively reduced, and the data transmission efficiency is improved; the technical scheme provided by the embodiment of the invention has the advantages of simple algorithm principle, low operation amount and easy function realization at a hardware end.
Furthermore, in the embodiment of the present invention, a reference metric (i.e., a compression loss parameter) that can reflect compression loss can be provided by referring to the main control index and other auxiliary indexes except the main control index according to different compression precision requirements (even zero loss), so as to reasonably adjust an error threshold value, and further, in a subsequent data processing process, redundant data in original sample data can be more sufficiently removed, thereby improving compression precision.
Meanwhile, within the allowable range of compression precision, the extracted key data (namely, compressed data) can be subjected to low-loss or even lossless data restoration reconstruction at the receiving end of the key data, and the extracted key data (namely, the compressed data) is restored to approximate sampling data, so that the working condition analysis can be conveniently carried out.
On the other hand, reference basis for determining reasonable error threshold values can be provided for engineering technicians by providing a data recovery loss curve, reference measurement, iteration times and key data retention conditions (or data compression rates).
Through engineering actual measurement of sampling data of a plurality of devices, compared with the technical scheme that the sampling data is transmitted back directly under the prior art, by adopting the technical scheme provided by the embodiment of the invention, the average data transmission amount is reduced by about 80 percent, so that the benefits are remarkable in the aspects of reducing the data transmission scale and reducing the data transmission cost.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made in the embodiments of the present invention without departing from the spirit or scope of the embodiments of the invention. Thus, if such modifications and variations of the embodiments of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to encompass such modifications and variations.
Claims (11)
1. A method for extracting key data from sampled data, comprising:
determining at least one main control index corresponding to the sampling data, wherein one main control index represents a measurement parameter on one reference dimension;
respectively aiming at each master control index contained in the at least one master control index, executing the following operations: screening out sampling points with all single-point recovery errors reaching a preset error threshold value as key sampling points aiming at a main control index, wherein the single-point recovery errors are the difference values of interpolation data and corresponding sampling data of one sampling point;
and extracting sampling data corresponding to each key sampling point as key data based on all key sampling points obtained corresponding to the at least one main control index.
2. The method as claimed in claim 1, wherein screening all sampling points with single point recovery errors smaller than a preset error threshold as key sampling points for a main control index comprises:
determining at least two key sampling points specified for the one master index;
the following operations are executed in a loop:
determining a group of adjacent key sampling points, and performing linear interpolation on each non-key sampling point between the group of key sampling points to obtain corresponding interpolation data;
calculating single-point recovery errors of all non-critical sampling points, screening out the non-critical sampling points with the single-point recovery errors reaching a preset sampling precision threshold value, and selecting one from the screened non-critical sampling points to be converted into a critical sampling point;
and judging whether the single point recovery errors of all the non-key sampling points are smaller than the sampling precision threshold, if so, ending the operation, and otherwise, continuously selecting a group of adjacent key sampling points.
3. The method of claim 2, wherein selecting one of the screened non-keypoint sample points to convert to a keypoint sample point comprises;
selecting one non-critical sampling point with the largest single-point recovery error from the screened non-critical sampling points and converting the non-critical sampling point into a critical sampling point; if a plurality of non-key sampling points with the maximum single-point recovery error appear, one sampling point is randomly selected to be converted into a key sampling point.
4. The method according to claim 1, 2 or 3, wherein the extracting, as the key data, the sampling data corresponding to each key sampling point based on all key sampling points obtained corresponding to the at least one master control index comprises:
if the at least one main control index only comprises one main control index, extracting sampling data corresponding to the one main control index as key data based on each key sampling point corresponding to the one main control index;
if the at least one main control index comprises two or more main control indexes, respectively extracting the sampling data corresponding to the corresponding main control indexes based on each key sampling point corresponding to each main control index, and merging the sampling data corresponding to each main control index to obtain corresponding key data, or respectively taking the sampling data corresponding to each main control index as the key data.
5. The method of claim 4, further comprising:
if the total data volume of the sampled data is determined to reach the set threshold, the sampled data is divided into a plurality of data segments according to the set data volume, and key data corresponding to at least one main control index are respectively extracted for each data segment.
6. The method of claim 1, 2, or 3, further comprising:
determining at least one main control index corresponding to the key data;
respectively aiming at each master control index contained in the at least one master control index, executing the following operations:
determining each key sampling point corresponding to one main control index;
and performing linear interpolation between the key data corresponding to every two adjacent key sampling points according to a set time interval to obtain corresponding interpolation data.
And taking all key data and interpolation data corresponding to the main control index as reduction sampling data corresponding to the main control index.
7. The method of claim 6, further comprising:
calculating a compression loss parameter corresponding to the key data extraction process based on each interpolation data inserted in the key data and the sampling data at the corresponding position;
judging whether the compression loss parameter reaches a preset expected value or not;
if so, reducing the error threshold value according to a first set step length;
otherwise, increasing the error threshold value according to a second setting step.
8. The method of claim 7, further comprising:
if the error threshold value is reduced according to the first set step length, when the compression loss parameter corresponding to the last key data extraction process is judged not to reach the preset expected value, and the compression loss parameter corresponding to the current key data extraction process reaches the preset expected value, the adjusted error threshold value after the current key data extraction is taken as the optimal error threshold value to be reported:
if the error threshold value is increased according to the second set step length, when the compression loss parameter corresponding to the last key data extraction process is judged to reach the preset expected value, and the compression loss parameter corresponding to the current key data extraction process does not reach the preset expected value, the adjusted error threshold value after the current key data extraction is taken as the optimal error threshold value to be reported.
9. An apparatus for extracting key data from sampled data, comprising:
the device comprises a determining unit, a calculating unit and a processing unit, wherein the determining unit is used for determining at least one main control index corresponding to sampling data, and one main control index represents a measurement parameter on one reference dimension;
a processing unit, configured to perform the following operations for each master index included in the at least one master index, respectively: screening out sampling points with all single-point recovery errors reaching a preset error threshold value as key sampling points aiming at a main control index, wherein the single-point recovery errors are the difference values of interpolation data and corresponding sampling data of one sampling point;
and the extraction unit is used for extracting sampling data corresponding to each key sampling point as key data based on all key sampling points obtained corresponding to the at least one main control index.
10. A storage medium storing a program for implementing extraction of key data from sampled data, the program when executed by a processor performing the steps of:
determining at least one main control index corresponding to the sampling data, wherein one main control index represents a measurement parameter on one reference dimension;
respectively aiming at each master control index contained in the at least one master control index, executing the following operations: screening out sampling points with all single-point recovery errors reaching a preset error threshold value as key sampling points aiming at a main control index, wherein the single-point recovery errors are the difference values of interpolation data and corresponding sampling data of one sampling point;
and extracting sampling data corresponding to each key sampling point as key data based on all key sampling points obtained corresponding to the at least one main control index.
11. A communications apparatus comprising one or more processors; and
one or more computer-readable media having instructions stored thereon that, when executed by the one or more processors, cause the apparatus to perform the method of any of claims 1-9.
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