CN111008518A - Dynamic friction industry identification analysis data updating method and system - Google Patents
Dynamic friction industry identification analysis data updating method and system Download PDFInfo
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- CN111008518A CN111008518A CN201911259377.8A CN201911259377A CN111008518A CN 111008518 A CN111008518 A CN 111008518A CN 201911259377 A CN201911259377 A CN 201911259377A CN 111008518 A CN111008518 A CN 111008518A
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Abstract
The invention discloses a dynamic friction industry identification analysis data updating method, which comprises the following steps: acquiring an identification code; extracting the code version number of the identification code; when the coding version number is not consistent with the current version number, obtaining the coding rule of the coding version number and the current version number; restoring the identification code to original data based on the code version number; converting the original data into a new identification code based on the current version number. The invention judges whether the identification code is the used coding rule or not by comparing the version numbers, and can automatically convert the identification code adopting the used coding rule into the coding rule adopting the new identification code, thereby realizing the updating of the used identification code when the coding rule changes.
Description
Technical Field
The invention relates to the technical field of identification analysis, in particular to a method and a system for updating identification analysis data in an MOM industry.
Background
In the internet era, an analysis system becomes a central nervous system of the internet, and the ecology of the whole internet is prosperous; in the era of internet of things with interconnection of everything, the strategic need is to consider in advance and build a layout identification analysis system to construct the ecology of the internet of things with interconnection of everything.
In the prior art, information of various materials in the motorcycle (motorcycle and power equipment) industry can be formed into corresponding codes for storage through an identification analysis technology. However, due to the rapid development and progress of the technology, particularly for the dynamic and dynamic industry, which is an industry that is composed of a large number of components, the structure of the product changes at any time along with the progress of the technology. In addition, due to the complex structure of the dynamic friction industry, the relationship between different links changes at any time. These changes may cause the encoding rules to change, and the encoding rules may also change correspondingly in order to adapt to the change of the product structure, however, this will inevitably cause the original encoding not to conform to the new encoding rules, thereby causing the analysis of the old data to be wrong.
In summary, how to update the old identification code when the coding rule changes becomes a problem that needs to be solved urgently by those skilled in the art.
Disclosure of Invention
Aiming at the defects of the prior art, the problems actually solved by the invention are as follows: how to update the old identification code when the coding rule changes is realized.
The invention adopts the following technical scheme:
a dynamic friction industry identification analysis data updating method comprises the following steps:
acquiring an identification code;
extracting the code version number of the identification code;
when the coding version number is not consistent with the current version number, obtaining the coding rule of the coding version number and the current version number;
restoring the identification code to original data based on the code version number;
converting the original data into a new identification code based on the current version number.
Preferably, the identification code comprises a version number field, and the extracting of the coded version number of the identification code comprises extracting the version number field; and when the version number field is different from the version number field of the current version, judging that the coded version number is not consistent with the current version number.
Preferably, the version number field includes a version identifier that is not included in any other field, the extracted version number field includes a version identifier in the identification code, and the field including the version identifier is determined as the version number field to be extracted.
Preferably, the extracting of the coded version number of the identification code includes:
and inputting the identification code into a version classification neural network, and outputting to obtain the code version number.
Preferably, the method of training the version classification neural network comprises:
s1, acquiring different coding version numbers and corresponding identification coding sets;
s2, dividing the identification code set of each code version number into a training set and a test set;
s3, training the version classification neural network to be trained by adopting different coding version numbers and corresponding training sets;
and S4, testing the trained version classification neural network by adopting different coding version numbers and corresponding test sets, finishing training when the classification accuracy is greater than the preset accuracy, and otherwise, returning to the step S3.
The utility model provides a move trade mark analytic data update system that rubs, includes data acquisition module, draws module, contrast module and conversion module, wherein:
the data acquisition module is used for acquiring the identification code;
the extraction module is used for extracting the code version number of the identification code;
the comparison module is used for comparing whether the coding version number is consistent with the current version number or not;
when the coding version number is not consistent with the current version number, the data acquisition module is also used for acquiring the coding rule of the coding version number and the current version number;
the conversion module is used for reducing the identification code into original data based on the code version number;
the conversion module is further configured to convert the original data into a new identification code based on the current version number.
Preferably, the identification code comprises a version number field, and the extracting of the coded version number of the identification code comprises extracting the version number field; and when the version number field is different from the version number field of the current version, judging that the coded version number is not consistent with the current version number.
Preferably, the version number field includes a version identifier that is not included in any other field, the extracted version number field includes a version identifier in the identification code, and the field including the version identifier is determined as the version number field to be extracted.
Preferably, the extracting of the coded version number of the identification code includes:
and inputting the identification code into a version classification neural network, and outputting to obtain the code version number.
Preferably, the method of training the version classification neural network comprises:
s1, acquiring different coding version numbers and corresponding identification coding sets;
s2, dividing the identification code set of each code version number into a training set and a test set;
s3, training the version classification neural network to be trained by adopting different coding version numbers and corresponding training sets;
and S4, testing the trained version classification neural network by adopting different coding version numbers and corresponding test sets, finishing training when the classification accuracy is greater than the preset accuracy, and otherwise, returning to the step S3.
In summary, the invention discloses a method for updating analysis data of an identification in an MOM industry, which comprises the following steps: acquiring an identification code; extracting the code version number of the identification code; when the coding version number is not consistent with the current version number, obtaining the coding rule of the coding version number and the current version number; restoring the identification code to original data based on the code version number; converting the original data into a new identification code based on the current version number. The invention judges whether the identification code is the used coding rule or not by comparing the version numbers, and can automatically convert the identification code adopting the used coding rule into the coding rule adopting the new identification code, thereby realizing the updating of the used identification code when the coding rule changes.
Drawings
For purposes of promoting a better understanding of the objects, aspects and advantages of the invention, reference will now be made in detail to the present invention as illustrated in the accompanying drawings, in which:
FIG. 1 is a flow chart of a dynamic friction industry logo parsing data updating method disclosed by the present invention;
fig. 2 is a schematic structural diagram of an identification parsing data updating system for the mobile motorcycle industry disclosed in the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
As shown in fig. 1, the invention discloses a method for updating identification analysis data of an MOM industry, which comprises the following steps:
acquiring an identification code;
extracting the code version number of the identification code;
when the coding version number is not consistent with the current version number, obtaining the coding rule of the coding version number and the current version number;
restoring the identification code to original data based on the code version number;
converting the original data into a new identification code based on the current version number.
In case the encoding rules are known, no further details are given here regarding the interconversion between encoding and data.
The invention judges whether the identification code is the used coding rule or not by comparing the version numbers, and can automatically convert the identification code adopting the used coding rule into the coding rule adopting the new identification code, thereby realizing the updating of the used identification code when the coding rule changes.
In specific implementation, the identification code comprises a version number field, and the code version number for extracting the identification code comprises an extracted version number field; and when the version number field is different from the version number field of the current version, judging that the coded version number is not consistent with the current version number.
The identification code may include a plurality of different fields, each field for indicating a different meaning. Thus, a fixed version number field may be provided at a fixed location of each segment of the identification code, e.g., the beginning or end of the identification code is provided as a version number field. Thus, the extraction of the version number can be performed quickly.
In specific implementation, the version number field includes a version identifier that is not included in any other field, the extracted version number field includes a version identifier in the identification code, and the field including the version identifier is determined as the version number field to be extracted.
When there is no fixed location of the version number field, special characters that are not included in any of the other fields, such as "+", "&" and the like, may be set in the version number field as version identifiers. In this way, the version number can be quickly looked up by identifying the version identifier even if there is no provision for the location of the version number field to be determined.
In specific implementation, the extracting of the code version number of the identification code includes:
and inputting the identification code into a version classification neural network, and outputting to obtain the code version number.
Except for the mode of setting a special version number field, because the coded identification codes of the coding rules of different versions have different characteristics, the version classification neural network can be obtained through training of the neural network, and the classification of the codes is expressed through the neural network, so that the coded version number is obtained.
In specific implementation, the method for training the version classification neural network comprises the following steps:
s1, acquiring different coding version numbers and corresponding identification coding sets;
s2, dividing the identification code set of each code version number into a training set and a test set;
s3, training the version classification neural network to be trained by adopting different coding version numbers and corresponding training sets;
and S4, testing the trained version classification neural network by adopting different coding version numbers and corresponding test sets, finishing training when the classification accuracy is greater than the preset accuracy, and otherwise, returning to the step S3.
The present invention is not limited to the use of a particular neural network. For the parameter setting of the neural network, the setting can be performed according to specific conditions.
As shown in fig. 2, the present invention further discloses a system for updating analysis data of an identification in an attorney race industry, which includes a data acquisition module, an extraction module, a comparison module and a conversion module, wherein:
the data acquisition module is used for acquiring the identification code;
the extraction module is used for extracting the code version number of the identification code;
the comparison module is used for comparing whether the coding version number is consistent with the current version number or not;
when the coding version number is not consistent with the current version number, the data acquisition module is also used for acquiring the coding rule of the coding version number and the current version number;
the conversion module is used for reducing the identification code into original data based on the code version number;
the conversion module is further configured to convert the original data into a new identification code based on the current version number.
In specific implementation, the identification code comprises a version number field, and the code version number for extracting the identification code comprises an extracted version number field; and when the version number field is different from the version number field of the current version, judging that the coded version number is not consistent with the current version number.
In specific implementation, the version number field includes a version identifier that is not included in any other field, the extracted version number field includes a version identifier in the identification code, and the field including the version identifier is determined as the version number field to be extracted.
In specific implementation, the extracting of the code version number of the identification code includes:
and inputting the identification code into a version classification neural network, and outputting to obtain the code version number.
In specific implementation, the method for training the version classification neural network comprises the following steps:
s1, acquiring different coding version numbers and corresponding identification coding sets;
s2, dividing the identification code set of each code version number into a training set and a test set;
s3, training the version classification neural network to be trained by adopting different coding version numbers and corresponding training sets;
and S4, testing the trained version classification neural network by adopting different coding version numbers and corresponding test sets, finishing training when the classification accuracy is greater than the preset accuracy, and otherwise, returning to the step S3.
Finally, it is noted that the above-mentioned embodiments illustrate rather than limit the invention, and that, while the invention has been described with reference to preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A dynamic friction industry identification analysis data updating method is characterized by comprising the following steps:
acquiring an identification code;
extracting the code version number of the identification code;
when the coding version number is not consistent with the current version number, obtaining the coding rule of the coding version number and the current version number;
restoring the identification code to original data based on the code version number;
converting the original data into a new identification code based on the current version number.
2. The MOR industry identification resolution data update method of claim 1, wherein the identification code comprises a version number field, and the extracting of the coded version number of the identification code comprises extracting the version number field; and when the version number field is different from the version number field of the current version, judging that the coded version number is not consistent with the current version number.
3. The MOR industry mark resolution data updating method as claimed in claim 2, wherein the version number field comprises a version identifier which is not included in any other field, the extracted version number field comprises a version identifier in the mark code, and the field comprising the version identifier is judged as the version number field to be extracted.
4. The mobile Morgan industry identification resolution data updating method of claim 1, wherein the extracting the coded version number of the identification code comprises:
and inputting the identification code into a version classification neural network, and outputting to obtain the code version number.
5. The attorney business identification resolution data update method according to claim 4, wherein the method of training the version classification neural network comprises:
s1, acquiring different coding version numbers and corresponding identification coding sets;
s2, dividing the identification code set of each code version number into a training set and a test set;
s3, training the version classification neural network to be trained by adopting different coding version numbers and corresponding training sets;
and S4, testing the trained version classification neural network by adopting different coding version numbers and corresponding test sets, finishing training when the classification accuracy is greater than the preset accuracy, and otherwise, returning to the step S3.
6. The utility model provides a move trade mark analytic data update system that rubs which characterized in that, includes data acquisition module, draws module, contrast module and conversion module, wherein:
the data acquisition module is used for acquiring the identification code;
the extraction module is used for extracting the code version number of the identification code;
the comparison module is used for comparing whether the coding version number is consistent with the current version number or not;
when the coding version number is not consistent with the current version number, the data acquisition module is also used for acquiring the coding rule of the coding version number and the current version number;
the conversion module is used for reducing the identification code into original data based on the code version number;
the conversion module is further configured to convert the original data into a new identification code based on the current version number.
7. The mobile Morgan industry identification resolution data update system of claim 6, wherein the identification code comprises a version number field, the extracting the coded version number of the identification code comprises extracting the version number field; and when the version number field is different from the version number field of the current version, judging that the coded version number is not consistent with the current version number.
8. The MOR industry mark resolution data update system of claim 2, wherein the version number field comprises a version identifier which is not included in any other field, the extracted version number field comprises a version identifier in the mark code, and the field comprising the version identifier is judged as the version number field to be extracted.
9. The mobile Morgan industry identification resolution data update system of claim 1, wherein said extracting the coded version number of the identification code comprises:
and inputting the identification code into a version classification neural network, and outputting to obtain the code version number.
10. The attorney business identification resolution data update system of claim 4, wherein the method of training said version classification neural network comprises:
s1, acquiring different coding version numbers and corresponding identification coding sets;
s2, dividing the identification code set of each code version number into a training set and a test set;
s3, training the version classification neural network to be trained by adopting different coding version numbers and corresponding training sets;
and S4, testing the trained version classification neural network by adopting different coding version numbers and corresponding test sets, finishing training when the classification accuracy is greater than the preset accuracy, and otherwise, returning to the step S3.
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