CN111966648A - Industrial data processing method and electronic equipment - Google Patents
Industrial data processing method and electronic equipment Download PDFInfo
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- CN111966648A CN111966648A CN202010745505.6A CN202010745505A CN111966648A CN 111966648 A CN111966648 A CN 111966648A CN 202010745505 A CN202010745505 A CN 202010745505A CN 111966648 A CN111966648 A CN 111966648A
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Abstract
The invention relates to a processing method of industrial data and electronic equipment, wherein the method comprises the following steps: the method comprises the steps of marking the obtained original industrial data in a form of (N0, t0 and P0), when N0 is larger than a set compression filtering threshold value N, performing time axis data compression on the marked original industrial data (N0, t0 and P0) to obtain time position compressed data (N0, dT and P0), performing position axis data compression on the time position compressed data (N0, dT and P0) to obtain position compressed data (N0, dT and dP) and storing the position compressed data.
Description
Technical Field
The present invention relates to the field of data processing, and in particular, to a method for processing industrial data and an electronic device.
Background
With the widespread commercialization of 5G technology and the maturation of internet of things technology, many enterprises have begun a process of digital transformation, especially the construction of smart factories in the manufacturing industry. In the construction and the production process of intelligent factory, can produce a large amount of data, can effectively promote the whole operation efficiency of manufacturing based on the data that obtain, promote product quality. However, in the manufacturing process, the amount of data generated is huge, and it is necessary to match a very large capacity storage device, and the calculation and analysis of such a large amount of data to generate data convenient for decision and control requires a long time, even to match a high performance processor and a graphics card. This not only can make the input that manufacturing type enterprise invested into intelligent factory very big, can not guarantee to obtain good effect moreover, this has reduced the intelligent ROI investment rate of enterprise in intangible.
Disclosure of Invention
The invention provides a processing method of industrial data and electronic equipment, aiming at solving the problems of low ROI (region of interest) return rate of manufacturing enterprises caused by high industrial data storage cost, high operation cost and the like.
The technical scheme of the industrial data processing method is as follows:
marking the obtained original industrial data in a form of (N0, t0, P0), wherein N0 is the size of the current data, t0 is the obtaining time of the current data, and P0 is the position information of the current data;
and when N0 is larger than a set compression filtering threshold N, performing time axis data compression on the marked original industrial data (N0, t0 and P0) to obtain time position compressed data (N0, dT and P0), and performing position axis data compression on the time position compressed data (N0, dT and P0) to obtain position compressed data (N0, dT and dP) and storing the position compressed data (N0, dT and dP), wherein dT is compression time and dP is compression position.
The industrial data processing method has the following beneficial effects:
based on the strong time sequence type characteristic of industrial data, the industrial data is compressed and then stored, so that the problems of low Return On Investment (ROI) of manufacturing enterprises caused by high storage cost and high operation cost of the industrial data are solved. Meanwhile, the method is also beneficial to improving the data processing speed, better reflects the operation condition of an enterprise and is convenient for the upper layer to make reasonable decisions.
On the basis of the scheme, the processing method of the industrial data can be further improved as follows.
Further, before the obtained raw industrial data is marked in the form of (N0, t0, P0), the method further comprises the following steps:
the raw industrial data is obtained from production information of a production facility or process.
Further, the position information of the current data is the number of the production equipment.
Further, the compression filtering threshold N is set according to past experience and experience summary of data, or according to an early warning value and a conventional value of industrial data.
Further, still include: -decompressing said stored location compressed data (N0, dT, dP).
Further, when N0 is greater than the set compression filtering threshold N, the time axis data compression is performed on the marked original industrial data (N0, t0, P0) to obtain time position compressed data (N0, dT, P0), and the method includes:
the original industrial data is glided down along with time until (N1, t1, P0), and when the size N1 of the data corresponding to the time t1 exceeds the compression filtering threshold N, the original industrial data is compressed into (N0, dT0, P0);
and repeating the process, and compressing the time axis data until the time axis data compression of the original industrial data is completed to obtain the time position compressed data (N0, dT, P0).
The beneficial effect of adopting the further scheme is that: the data calculation and the data storage are convenient, the calculation speed is improved, and the data for warning are convenient to display.
Further, when the time t1 is a time point, the compression time dT0 is a time period; when the time t1 is a time period, the compressed data dT0 is the difference between two-dimensional arrays.
The beneficial effect of adopting the further scheme is that: the data calculation and the data storage are convenient, the calculation speed is improved, and the data for warning are convenient to display.
Further, when the time t1 is a time period, the compression filtering threshold N exceeding the time t1 is an upper limit exceeding the time period t 1.
Further, the performing position axis data compression on the time position compressed data (N0, dT, P0) to obtain position compressed data (N0, dT, dP) includes:
the original industrial data slide down along with the production link, corresponding (N1, dT, P1) when N0 is larger than a set compression filtering threshold value N is obtained from the time position compression data (N0, dT, P0), and (N1, dT, P1) is compressed into (N0, dT, dP 0);
and repeating the above processes to compress the position axis data until the position axis data compression of the time position compressed data is completed, and obtaining the position compressed data (N0, dT, dP).
The technical scheme of the electronic equipment is as follows:
comprising a memory, a processor and a program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps of a method for processing industrial data as described in any one of the above.
The electronic equipment has the following beneficial effects:
based on the strong time sequence type characteristic of industrial data, the industrial data is compressed and then stored, so that the problems of low Return On Investment (ROI) of manufacturing enterprises caused by high storage cost and high operation cost of the industrial data are solved. Meanwhile, the method is also beneficial to improving the data processing speed, better reflects the operation condition of an enterprise and is convenient for the upper layer to make reasonable decisions.
Drawings
FIG. 1 is a flow chart of a method for processing industrial data according to an embodiment of the present invention;
FIG. 2 is a second flowchart illustrating a method for processing industrial data according to an embodiment of the present invention;
FIG. 3 is a third flowchart illustrating a method for processing industrial data according to an embodiment of the present invention;
FIG. 4 is a schematic process diagram of compressing raw industrial data in a method for processing industrial data according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention;
Detailed Description
As shown in fig. 1, a method for processing industrial data according to an embodiment of the present invention includes the following steps:
s1, marking the obtained original industrial data in a form of (N0, t0 and P0), wherein N0 is the size of the current data, t0 is the obtaining time of the current data, and P0 is the position information of the current data;
s2, when N0 is larger than a set compression filtering threshold N, time axis data compression is carried out on the marked original industrial data (N0, t0, P0) to obtain time position compressed data (N0, dT, P0), position axis data compression is carried out on the time position compressed data (N0, dT, P0) to obtain position compressed data (N0, dT, dP), and the position compressed data are stored, wherein dT is compression time, and dP is compression position.
The industrial data is greatly different from the traditional social network data, and has the characteristics of strong time sequence, small volatility, high alarm performance and the like, so the invention provides an efficient industrial data processing method based on the characteristics of the industrial data, and solves the problems of low investment return rate ROI of manufacturing enterprises caused by high industrial data storage cost, high operation cost and the like. Meanwhile, the method is also beneficial to improving the data processing speed, better reflects the operation condition of an enterprise and is convenient for the upper layer to make reasonable decisions.
The industrial data processing method provided by the embodiment of the invention is mainly used for compressing industrial data based on the characteristics of the industrial data, compressing time axis data and then compressing position axis data, and optimizing a process and a production line after obtaining the position compressed data, so that the cost is saved.
Wherein, the compression filtering threshold N is set according to past experience and experience summary of data, or according to an early warning value and a conventional value of industrial data, specifically:
the compression filtering threshold value N can be self-defined in an actual industrial software interface, and the operator can derive from experience summary of past experience and data when self-defining the value; meanwhile, the compressed filtering threshold value N can be obtained by adopting intelligent big data analysis, and the lower limit of fluctuation between the normal value and the value higher than the early warning value is automatically defined as the compressed filtering threshold value N.
T0 may be represented by a specific number at a time point, or may be represented by a two-dimensional array at a time period.
As shown in fig. 2, preferably, in the above technical solution, before the marking the obtained original industrial data in the form of (N0, t0, P0), the method further includes:
s01, obtaining the original industrial data from the production information of the production equipment or the production process, specifically:
and the position information of the current data is the number of the production equipment. The production equipment corresponds to the production process. For example: the production equipment in the product quality detection link is video equipment, the corresponding data is shot product photos, and the corresponding production process is quality detection.
As shown in fig. 3, preferably, in the above technical solution, the method further includes:
s3, decompressing the stored position compressed data (N0, dT, dP).
The industrial data processing method provided by the embodiment of the invention is mainly characterized in that the industrial data is compressed to be convenient to store, and the decompression is the reverse process of the industrial data, namely, the process of changing the time period into the time point, and the compressed data can be decompressed if needed.
Preferably, in the above technical solution, in S2, when N0 is greater than the set compression filtering threshold N, the time-axis data compression is performed on the marked original industrial data (N0, t0, P0) to obtain time-position compressed data (N0, dT, P0), and the method includes:
s20, sliding down the original industrial data along with time until (N1, t1 and P0), and compressing the original industrial data into (N0, dT0 and P0) when the size N1 of the data corresponding to the time t1 exceeds the compression filtering threshold N;
and S21, repeating the above processes, and compressing the time axis data until the time axis data compression of the original industrial data is completed to obtain the time position compressed data (N0, dT, P0).
The data calculation and the data storage are convenient, the calculation speed is improved, and the data for warning are convenient to display.
When the time t1 is the time point, the compression time dT0 is the time period; when the time t1 is a time period, the compressed data dT0 is the difference between the two-dimensional arrays, and when the time t1 is the time period, the compressed filtering threshold N exceeding the time t1 is the upper limit exceeding the time period t 1.
The points to be explained are: the position of the data is not changed in the process of compressing the time axis data, so that the data calculation and the data storage are convenient, the calculation speed is improved, and the data for warning are convenient to display.
Preferably, in the above technical solution, in S2, the performing position axis data compression on the time position compressed data (N0, dT, P0) to obtain position compressed data (N0, dT, dP) includes:
s22, the original industrial data slide down along with the production link, corresponding (N1, dT, P1) when N0 is larger than a set compression filtering threshold N is obtained from the time position compressed data (N0, dT, P0), and (N1, dT, P1) is compressed into (N0, dT, dP 0);
and S23, repeating the above process, and compressing the position axis data until the position axis data compression of the time position compressed data is completed to obtain the position compressed data (N0, dT, dP).
For example, the normal indoor temperature of the boiler is 500 ℃, the fluctuation range is 25 ℃, that is, the set compression filtering threshold value N is 500 ℃ +25 ℃, and 100 sensors for acquiring the boiler temperature are arranged, that is, 100 pieces of position information are totally recorded as 1-100, and assuming that each sensor acquires the temperature every 10 seconds, then at 8: 00: at 00 hours, 100 temperature data, namely original industrial data, are collected, and the obtained original industrial data are marked in the form of (N0, t0, P0), which are respectively:
(475, 8: 00: 00, 1), (478, 8: 00: 00, 2), (479, 8: 00: 00, 3) … … (478, 8: 00: 00, 100), and assuming a ratio of 8: 00: when the temperature acquired by each sensor does not exceed the compression filtering threshold value N, no compression is performed;
and so on until the ratio at 12: 00: acquiring 100 temperature data, namely original industrial data, at 00 hours;
wherein, assume that at 10: 00: the temperature data collected by 30, i.e. the raw industrial data, are marked in the form of (N0, t0, P0), respectively:
(475, 10: 00: 30, 1), (478, 10: 00: 30, 2), (485, 10: 00: 30, 3) … … (545, 10: 00: 30, 99), (478, 10: 00: 30, 100), wherein, since the temperature acquired by the 99 th sensor exceeds the compression filtering threshold N, time-axis data compression is performed, i.e. N1 equals 545, t1 is 10: 00: at 30, P0 is the 99 th sensor, which will be 8: 00: 00-10: 00: 30 into (N0, dT0, P0), namely (545, 8: 00: 00-10: 00: 30, 1), (545, 8: 00: 00-10: 00: 30, 2) … … (545, 8: 00: 00-110: 00: 30, 100);
wherein, 8: 00: 00-10: 00: 30, dT0, may also be represented in the form of two-dimensional data: (10: 00: 30, 8: 00: 00), at which time (N0, dT0, P0) can be expressed as: (545, (8: 00: 00, 10: 00: 30), 1), (545, (8: 00: 00-10: 00: 30), 2) … … (545, (8: 00: 00-110: 00: 30), 100), which can also be expressed as (8: 00: 00, 10: 00: 30), and can also be expressed as (100030, 80000), and the setting can be made according to actual situations;
wherein, 8: 00: 00-10: 00: 30 or dT0 may also be expressed as the difference between two-dimensional arrays, for example, when 8: 00: 00 is represented by 80000, and when 10: 00: when 30 is represented by 100030, i.e. DT0 ═ 100030-: (545, 20030, 1), (545, 20030, 2) … … (545, 20030, 100);
then, for 10: 00: 30-12: 00: repeating the process for the acquired original industrial data between 00, and compressing the time axis data until the time axis data of the original industrial data is compressed to obtain time position compressed data (N0, dT, P0);
assume that only with 8: 00: 00-110: 00: 30, the time position compressed data (N0, dT, P0) is:
(545, 8: 00: 00-110: 00: 30, 1), (545, 8: 00: 00-110: 00: 30, 2) … … (545, 8: 00: 00-110: 00: 30, 100), when the temperature data collected by the 100 th sensor is 478 and does not exceed N, if N0 is greater than the set compression filtering threshold N, the P1 in (N1, dT, P1) is 99, and N1 is 545, then (N1, dT, P1) is compressed to (N0, dT, dP0), that is: (545, 8: 00: 00-110: 00: 30, 1-99), when the ratio of 10: 00: 30-12: 00: and when the time axis data compression is carried out on the acquired original industrial data between 00 hours and the conditions are met, repeating the process, and carrying out position axis data compression until the position axis data compression of the time position compressed data is finished to obtain the position compressed data (N0, dT, dP).
The process of performing time axis data compression and position axis data compression is shown in fig. 4, where i of (Ni, ti, P0) in fig. 4 is a positive integer and represents that the original industrial data collected for the first time, the second time, and the like are marked in the form of (N0, t0, P0), Ni represents the size of the current data collected for the first time, the second time, and the like, ti represents the obtaining time of the current data for the first time, the second time, and the like, (Ni, dTi, P0) represents time position compressed data obtained after the time axis data compression is performed for the first time and the time axis data compression is performed for the second time, and (Ni, dTi, Pj) represents: and (N1, dT, P1) corresponding to the case where N0 is greater than the set compression filtering threshold N is obtained from the time-position compressed data (N0, dT, P0), where j is a positive integer and (Ni, dTi, dPj) indicates position compressed data of the time-position compressed data obtained by performing position axis data compression for the first time and performing position axis data compression for the second time, where j is a positive integer and dPj indicates position information of the position axis data compression for the first time, position information of the position axis data compression for the second time, and the like, and finally the position compressed data (N0, dT, dP) is obtained and stored, that is, (N1, dT1, dP1) … … (Ni, dTi, dPj) and the like are stored. In this case, a solid black line indicates raw industrial data marked in the form of (N0, t0, P0), a dot-dash line indicates time-position compressed data, and a dotted line indicates position compressed data.
In the above embodiments, although the steps are numbered as S1, S2, etc., but only the specific embodiments are given in the present application, and those skilled in the art can adjust the execution sequence of S1, S2, etc. according to the actual situation, which is also within the protection scope of the present invention.
As shown in fig. 5, an electronic device 300 according to an embodiment of the present invention includes a memory 310, a processor 320, and a program 330 stored in the memory 310 and running on the processor 320, wherein when the processor 320 executes the program 330, the steps of any one of the above-described implemented industrial data processing methods are implemented.
Based on the strong time sequence type characteristic of industrial data, the industrial data is compressed and then stored, so that the problems of low Return On Investment (ROI) of manufacturing enterprises caused by high storage cost and high operation cost of the industrial data are solved. Meanwhile, the method is also beneficial to improving the data processing speed, better reflects the operation condition of an enterprise and is convenient for the upper layer to make reasonable decisions.
The electronic device 300 may be a computer, a mobile phone, or the like, and correspondingly, the program 330 is computer software or a mobile phone APP, and the parameters and the steps in the electronic device 300 of the present invention may refer to the parameters and the steps in the above embodiment of the method for processing industrial data, which are not described herein again.
In the present invention, the terms "first", "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. A method of processing industrial data, comprising:
marking the obtained original industrial data in a form of (N0, t0, P0), wherein N0 is the size of the current data, t0 is the obtaining time of the current data, and P0 is the position information of the current data;
and when N0 is larger than a set compression filtering threshold N, performing time axis data compression on the marked original industrial data (N0, t0 and P0) to obtain time position compressed data (N0, dT and P0), and performing position axis data compression on the time position compressed data (N0, dT and P0) to obtain position compressed data (N0, dT and dP) and storing the position compressed data (N0, dT and dP), wherein dT is compression time and dP is compression position.
2. The method for processing industrial data according to claim 1, further comprising, before labeling the acquired raw industrial data in the form of (N0, t0, P0):
the raw industrial data is obtained from production information of a production facility or process.
3. The method as claimed in claim 2, wherein the location information of the current data is the number of the production equipment.
4. The method as claimed in claim 1, wherein the compression filtering threshold N is set according to past experience and experience summary of data, or according to an early warning value and a conventional value of industrial data.
5. The method for processing industrial data according to claim 1, further comprising: -decompressing said stored location compressed data (N0, dT, dP).
6. The method for processing industrial data according to any one of claims 1 to 5, wherein when N0 is greater than a set compression filtering threshold N, time axis data compression is performed on the marked original industrial data (N0, t0, P0) to obtain time position compressed data (N0, dT, P0), and the method comprises:
the original industrial data is glided down along with time until (N1, t1, P0), and when the size N1 of the data corresponding to the time t1 exceeds the compression filtering threshold N, the original industrial data is compressed into (N0, dT0, P0);
and repeating the process, and compressing the time axis data until the time axis data compression of the original industrial data is completed to obtain the time position compressed data (N0, dT, P0).
7. The method for processing industrial data as claimed in claim 6, wherein when the time t1 is a time point, the compression time dT0 is a time period; when the time t1 is a time period, the compressed data dT0 is the difference between two-dimensional arrays.
8. The method as claimed in claim 6, wherein when the time t1 is a time period, the compression filtering threshold N exceeding the time t1 is an upper limit exceeding the time period t 1.
9. The method for processing industrial data according to claim 6, wherein the performing position axis data compression on the time position compressed data (N0, dT, P0) to obtain position compressed data (N0, dT, dP) comprises:
the original industrial data slide down along with the production link, corresponding (N1, dT, P1) when N0 is larger than a set compression filtering threshold value N is obtained from the time position compression data (N0, dT, P0), and (N1, dT, P1) is compressed into (N0, dT, dP 0);
and repeating the above processes to compress the position axis data until the position axis data compression of the time position compressed data is completed, and obtaining the position compressed data (N0, dT, dP).
10. An electronic device comprising a memory, a processor and a program stored on the memory and running on the processor, wherein the steps of a method of processing industrial data according to any one of claims 1 to 9 are implemented when the program is executed by the processor.
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