A data processing method for a high-power flexible rectifier control mainboard

Abstract

The present invention discloses a data processing method for a high-power flexible rectifier control mainboard. The present invention relates to the field of data processing technology and solves the technical problem that data cannot be effectively classified and sorted, and at the same time, traditional data storage cannot guarantee the security of data. The present invention classifies the control mainboard data by time by defining the classification period and taking the time point that the operator can set by himself as the starting point, and can accurately divide the data according to the time interval, which is convenient for subsequent analysis and processing of data in different time periods. By processing redundant data, the data is made more concise and clear, which is convenient for subsequent data analysis and mining. Key information can be extracted more quickly, providing more accurate data support for decision-making. By segmenting the reorganized data in different ways, the flexible segmentation method can adapt to the needs of different data characteristics, ensuring that the size of the segmented package after segmentation is reasonable, and convenient for management and processing.

Description

Technical Field

[0001] The invention relates to the technical field of data processing, in particular to a data processing method for a high-power flexible rectification control mainboard. Background Art

[0002] In today's information age, the amount of data generated and stored is growing explosively. For various control systems, such as those containing control motherboards, efficient management and storage of data is essential.

[0003] According to publication number CN202110941765.5, a data storage method based on a Feiteng processor is disclosed, which is applied to an embedded storage chip, wherein the embedded storage chip board is attached to the Feiteng processor, the embedded storage chip is electrically connected to the Feiteng processor, and the embedded storage chip includes a controller, a flash memory, and a cache; the method includes: receiving a storage signal transmitted by the Feiteng processor, the storage signal carrying data to be processed, and the storage signal is used to instruct the embedded storage chip to store the data to be processed; sending the storage signal to the flash memory and / or the cache through the controller; and storing the data to be processed based on the storage signal through the flash memory and / or the cache.

[0004] With the continuous development of technology, the requirements for data storage and processing are getting higher and higher. Not only does it need to effectively classify and organize data to improve data availability and retrieval efficiency, but it is also necessary to consider data security and storage efficiency. Traditional data processing methods may not meet the needs of modern complex systems for data management, so more advanced data processing technologies are needed to meet these challenges. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a data processing method for a high-power flexible rectifier control mainboard, which solves the problem that data cannot be effectively classified and sorted and that traditional data storage cannot guarantee data security.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a data processing method for a high-power flexible rectifier control mainboard, comprising:

[0007] Step S001, classifying the control mainboard data according to the generation time to obtain time-classified data, and performing secondary classification on the time-classified data according to the data correlation to obtain important data and regular data;

[0008] Step S002, performing storage analysis on the obtained important data and regular data, generating corresponding storage indexes according to the redundant data, and generating reorganized data according to the combined storage indexes;

[0009] Step S003, segmenting the obtained reorganized data to obtain segmented packets, calculating the characteristic sorting values ​​of the segmented packets, and generating sorting labels according to the characteristic sorting values;

[0010] Step S004, comparing and analyzing the generated sorting number with the original number, analyzing the different corresponding number situations in the comparison process, and generating encrypted sorting information by combining the sum of the sorting number and the original number value;

[0011] Step S005, storing the control mainboard data according to the generated encrypted storage information.

[0012] As a further solution of the present invention: the specific method of obtaining the time classification data in step S001 is:

[0013] First, all control motherboard data is obtained, and the generation time corresponding to the control motherboard data is obtained, and the classification period is defined. Then, starting from time t and based on the defined classification period, the control motherboard data is classified to obtain time classification data, and then the obtained time classification data is secondary classified.

[0014] As a further solution of the present invention: the specific method of performing secondary classification on the obtained time classification data in step S001 is:

[0015] The same type of control mainboard data in all time classification data is obtained, and the control mainboard data is labeled as i, and i=1, 2, ..., j, where j represents the number of the same type of control mainboard data. At the same time, the data type corresponding to the same type of control mainboard data is obtained, and the data type is compared with the associated standard. If the data type meets the associated standard, the corresponding control mainboard data of the same type is classified as primary data. If the data type does not meet the associated standard, the corresponding control mainboard data of the same type is classified as regular data.

[0016] As a further solution of the present invention: the specific method of generating the reorganized data in step S002 is:

[0017] Obtain the classified important data and regular data, obtain the corresponding redundant data in the important data and regular data, extract the redundant data, mark the remaining data as feature data, and analyze the important data as an example, label the redundant data with a, and a=1, 2, ..., b, where b represents the type of redundant data;

[0018] The quantity corresponding to the redundant data a is obtained and recorded as La, and the data capacity Wa corresponding to the redundant data a is obtained at the same time. Then, a data index is generated based on the quantity La and the data capacity Wa, and the generated data index is combined with the characteristic data to obtain the reconstructed data.

[0019] As a further solution of the present invention: the specific method of segmenting the reorganized data to obtain segmented packets in step S003 is:

[0020] Get all the reorganized data, and take one of the groups as the target object for analysis. Divide the target object into nine equal parts to obtain multiple groups of split packages. Label the obtained split packages as n, where n=1, 2, ..., 9. The specific split package is numbered according to the position of the original reorganized data. Then insert the split package n into the sorting template in the order of the labels.

[0021] As a further solution of the present invention: the specific method of calculating the feature ranking value of the segmented package in step S003 is:

[0022] Get the redundant data type a corresponding to the split package n n , and obtain the data capacity Wa corresponding to the redundant data a n and the number of data La n , and substitute the obtained parameters into the formula The characteristic ranking value Qn corresponding to the segmented package n is calculated, and the segmented package n is labeled twice from small to large according to the characteristic ranking value Qn, and a ranking label is generated.

[0023] As a further solution of the present invention: the specific method of comparing and analyzing the generated sorting number with the original number in step S004 is:

[0024] Obtain the sorting number and the original number of the split package, and determine the relationship between the sorting number and the original number. If the sorting number is the same as the original number, do not process the split package. If the sorting number is different from the original number, record the corresponding split package as the split package to be analyzed.

[0025] Get all the split packages to be analyzed, and get the sorting number and original number of the split packages to be analyzed, and calculate the sum of the sorting number and the original number as the sum value to be analyzed, then sort the split packages to be analyzed according to the sum value to be analyzed, and generate the number to be analyzed, and determine whether the sum value to be analyzed has the same value, and analyze based on different numerical conditions.

[0026] As a further solution of the present invention: the specific method of generating the encrypted sorting information by combining the sorting number and the sum of the original number values ​​in step S004 is:

[0027] If the to-be-analyzed and the value do not have the same situation, the to-be-analyzed split package is inserted into the sorting template with the generated to-be-analyzed label, and the encrypted sorting information is generated;

[0028] If the to-be-analyzed and value are the same, the corresponding split package to be analyzed is obtained, and the split package to be analyzed is sorted from beginning to end. The specific sorting method is as follows:

[0029] Get the original number corresponding to the split package to be analyzed, and put the split package to be analyzed with a smaller original number as the first place in the sorting, and insert the split package to be analyzed into the sorting template, put the split package to be analyzed with a larger original number as the last place in the sorting, and insert the split package to be analyzed into the sorting template, and generate encrypted storage information.

[0030] The present invention provides a data processing method for a high-power flexible rectifier control mainboard. Compared with the prior art, it has the following beneficial effects:

[0031] The present invention classifies the control mainboard data by time by defining the classification period and taking the time point that the operator can set as the starting point, and can accurately divide the data according to the time interval, which is convenient for subsequent analysis and processing of data in different time periods. By processing redundant data, the data is made more concise and clear, which is convenient for subsequent data analysis and mining. It can extract key information more quickly and provide more accurate data support for decision-making. By segmenting the reorganized data in different ways, the flexible segmentation method can adapt to the needs of different data characteristics, ensuring that the size of the segmented package after segmentation is reasonable, which is convenient for management and processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a diagram of the steps of the present invention.

[0033] Figure 2 This is a schematic diagram of sorting the sorting template of the present invention. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] For example, see Figure 1 The present application provides a data processing method for a high-power flexible rectifier control mainboard, which specifically includes the following steps:

[0036] In step S001, the control mainboard data is classified according to the generation time to obtain time-classified data, and the time-classified data is secondary classified according to the data correlation to obtain important data and regular data.

[0037] First, all the control mainboard data is obtained, and the generation time corresponding to the control mainboard data is obtained, and the classification period is defined, and the classification period here represents the generation time interval. Then, time t is taken as the starting point, and the specific value of time t is set by the operator. The control mainboard data is classified according to the defined classification period to obtain time classification data. For example, suppose there is a series of control mainboard data, and the generation times are 10:00, 10:05, 10:12, 10:25, and 10:30 on September 26, 2024. Now define the classification period as an interval of every 10 minutes, with 10:00 as the starting point of time t, then these data can be classified into two time classification data groups, namely [10:00-10:10] contains the data group generated at 10:00 and 10:05 on September 26, 2024, and [10:10-10:20] contains the data group generated at 10:12 on September 26, 2024, and so on, and then perform secondary classification on the obtained time classification data;

[0038] The same type of control mainboard data in all time classification data is obtained, and the control mainboard data is labeled as i, and i=1, 2, ..., j, where j represents the number of the same type of control mainboard data. At the same time, the data type corresponding to the same type of control mainboard data is obtained, and the data type is compared with the association standard. If the data type meets the association standard, the corresponding control mainboard data of the same type is classified as primary data. If the data type does not meet the association standard, the corresponding control mainboard data of the same type is classified as regular data. The specific association standard here is set by the operator. For example, the content corresponding to the association standard includes the fault parameters, operation parameters and system parameters of the control mainboard. As long as it belongs to the above parameter content, it is important data.

[0039] Next, in step S002, storage analysis is performed on the obtained important data and regular data, and corresponding storage indexes are generated according to the redundant data, and reorganized data is generated according to the combined storage indexes.

[0040] The important data and regular data obtained by classification are obtained, and it should be noted that the important data and regular data here belong to the same type of time classification data. At the same time, the corresponding redundant data in the important data and regular data are obtained, and the redundant data are extracted, and the remaining data is marked as feature data. At the same time, the important data is taken as an example for analysis, and the redundant data is labeled with a, and a=1, 2, ..., b, where b represents the type of redundant data, and the number corresponding to the redundant data a is obtained and recorded as La. At the same time, the data capacity Wa corresponding to the redundant data a is obtained, and the specific data capacity Wa is the same. Then, a data index is generated with the quantity La and the data capacity Wa. The specific index form is [La, Wa], and the generated data index is combined with the feature data to obtain reorganized data. By analogy, all important data and regular data are processed to obtain reorganized data.

[0041] Next, in step S003, the obtained reorganized data is segmented to obtain segmented packets, and the characteristic sorting values ​​of the segmented packets are calculated, and sorting labels are generated according to the size of the characteristic sorting values.

[0042] Get all the reorganized data, and analyze one of the groups as the target object. Divide the target object into nine equal parts to obtain multiple groups of split packages. The split is performed based on the data capacity. The split packages are labeled as n, where n=1, 2, ..., 9. The specific split package number is based on the position of the original reorganized data. Then, the split package n is inserted into the sorting template in the order of the number, as shown in the attached figure. Figure 2 As shown;

[0043] Get the redundant data type a corresponding to the split package n n , and obtain the data capacity Wa corresponding to the redundant data a n and the number of data La n , and substitute the obtained parameters into the formula The characteristic ranking value Qn corresponding to the segmented package n is calculated, and the segmented package n is labeled twice from small to large according to the characteristic ranking value Qn, and a ranking label is generated.

[0044] Next, in step S004, the generated sorting number is compared and analyzed with the original number, and the different corresponding number situations in the comparison process are analyzed, and the encrypted sorting information is generated by combining the sum of the sorting number and the original number value.

[0045] Obtain the sorting number and the original number of the split package, and determine the relationship between the sorting number and the original number. If the sorting number is the same as the original number, do not process the split package. If the sorting number is different from the original number, record the corresponding split package as the split package to be analyzed.

[0046] Obtain all the segmented packages to be analyzed, and obtain the sorting labels and original labels of the segmented packages to be analyzed, and calculate the sum of the sorting labels and the original labels as the sum value to be analyzed, then sort the segmented packages to be analyzed according to the sum value to be analyzed, and generate the labels to be analyzed, and the sorting method here is to sort from small to large according to the sum value to be analyzed, and at the same time determine whether the sum value to be analyzed has the same value, and analyze based on different value situations;

[0047] In a specific example, for example, suppose there are several split packets, the original label of split packet A is 3, and the sorting label is 4; the original label of split packet B is 2, and the sorting label is 2; the original label of split packet C is 5, and the sorting label is 1. For split packet A, its sorting label is different from the original label, and it is recorded as the split packet to be analyzed, and its sum to be analyzed is 3+4=7. Since the sorting label of split packet B is the same as the original label, it is not processed, and split packet C is also recorded as the split packet to be analyzed, and its sum to be analyzed is 5+1=6. Sort by sum to be analyzed from small to large, and process split packet C first, then process split packet A. If at this time, the sum to be analyzed of split packets D and split packets E is also 6, then it is necessary to further analyze and process these split packets to be analyzed with the same values ​​according to other features or rules.

[0048] If the to-be-analyzed and the value do not have the same situation, the to-be-analyzed split package is inserted into the sorting template with the generated to-be-analyzed label, and the encrypted sorting information is generated;

[0049] If the to-be-analyzed and value are the same, the corresponding split package to be analyzed is obtained, and the split package to be analyzed is sorted from beginning to end. The specific sorting method is as follows:

[0050] Obtain the original number corresponding to the split package to be analyzed, and sort the split package to be analyzed with a smaller original number as the first place, and insert the split package to be analyzed into the sorting template, and sort the split package to be analyzed with a larger original number as the last place, and insert the split package to be analyzed into the sorting template, and generate encrypted storage information;

[0051] In a specific example, for example, assume that there are three split packets to be analyzed, namely split packet X, split packet Y, and split packet Z. After calculation, the sum value to be analyzed of split packet X is 8, the sum value to be analyzed of split packet Y is 10, and the sum value to be analyzed of split packet Z is 12. Since their sum values ​​to be analyzed are different, split packets X, Y, and Z are sequentially inserted into the sorting template according to the numbers to be analyzed, and encrypted sorting information is generated.

[0052] Assume that there are three more split packets to be analyzed. The sum of split packet A to be analyzed is 15, the sum of split packet B to be analyzed is also 15, and the sum of split packet C to be analyzed is 18. Check their original labels. Assume that the original label of split packet A is 4 and the original label of split packet B is 5. Then insert split packet A into the sorting template as the first position in the sorting, and insert split packet B into the sorting template as the last position in the sorting, and generate encrypted storage information for this situation. Since the sum of split packet C to be analyzed is different from the others, it is inserted into the sorting template according to the normal process and encrypted sorting information is generated (this processing method is used if the sum to be analyzed is unique).

[0053] Finally, in step S005, the control mainboard data is stored according to the generated encrypted storage information.

[0054] Embodiment 2, as Embodiment 2 of the present invention, differs from Embodiment 1 in that:

[0055] In step S003, the reorganized data is evenly divided based on its capacity to obtain segmented packets, and the specific segmentation method is: the data capacity of the reorganized data is obtained, and the data capacity is judged. If the value of the data capacity is an odd number, all odd numbers within ten are obtained, and the data capacity is divided by the odd numbers in turn, and the largest odd number that can be divided is selected as the segmentation standard, and the reorganized data is segmented to obtain segmented packets;

[0056] If the value of the data capacity is an even number, all even numbers within ten are obtained. The same is true for odd numbers. The largest even number that can be divided evenly is selected as the segmentation standard, and the segmentation is performed to obtain the segmentation packets.

[0057] Embodiment 3, as the embodiment 3 of the present invention, focuses on combining the implementation processes of embodiment 1 and embodiment 2 for implementation.

[0058] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0059] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A data processing method for a high-power flexible rectifier control mainboard, characterized in that: include: Step S001, classifying the control mainboard data according to the generation time to obtain time-classified data, and performing secondary classification on the time-classified data according to the data correlation to obtain important data and regular data; Step S002, obtaining the corresponding redundant data in the important data and the regular data, marking the remaining data as characteristic data, obtaining the corresponding number and corresponding data capacity of the redundant data and generating a data index, the data index format is [La, Wa], where La is the number of data corresponding to the redundant data a, Wa is the data capacity corresponding to the redundant data a, and combining the data index with the characteristic data to obtain the reconstructed data; Step S003, segment the obtained reorganized data to obtain segmented packets, label the obtained segmented packets as n, where n=1, 2, ..., 9, calculate the characteristic sorting value of the segmented packets, and generate a sorting label based on the characteristic sorting value, and the specific calculation formula of the characteristic sorting value is: , where Wa n is the data capacity corresponding to the redundant data a, La n is the number of data corresponding to redundant data a, a is the redundant data label, and a=1, 2, ..., b, where b represents the type of redundant data, and Qn is the feature ranking value corresponding to segmentation package n; Step S004, obtaining the sorting number and original number of the segmented packages. If the sorting number is different from the original number, the corresponding segmented package is recorded as the segmented package to be analyzed, and all the segmented packages to be analyzed are obtained, and the sorting number and original number of the segmented packages to be analyzed are obtained, and the sum of the sorting number and the original number is calculated and recorded as the sum value to be analyzed; if the sum value to be analyzed is the same, the original number corresponding to the segmented package to be analyzed is obtained, and the segmented package to be analyzed with a smaller original number is ranked first, and the segmented package to be analyzed is inserted into the sorting template, and the segmented package to be analyzed with a larger original number is ranked last, and the segmented package to be analyzed is inserted into the sorting template, and encrypted storage information is generated; Step S005, storing the control mainboard data according to the generated encrypted storage information.

2. The data processing method of a high-power flexible rectifier control mainboard according to claim 1 is characterized in that: The specific method of obtaining the time classification data in step S001 is: First, all control motherboard data is obtained, and the generation time corresponding to the control motherboard data is obtained, and the classification period is defined. Then, starting from time t and based on the defined classification period, the control motherboard data is classified to obtain time classification data, and then the obtained time classification data is secondary classified.

3. The data processing method of a high-power flexible rectifier control mainboard according to claim 2 is characterized in that: The specific method of performing secondary classification on the obtained time classification data in step S001 is: The same type of control mainboard data in all time classification data is obtained, and the control mainboard data is labeled as i, and i=1, 2, ..., j, where j represents the number of the same type of control mainboard data. At the same time, the data type corresponding to the same type of control mainboard data is obtained, and the data type is compared with the associated standard. If the data type meets the associated standard, the corresponding control mainboard data of the same type is classified as primary data. If the data type does not meet the associated standard, the corresponding control mainboard data of the same type is classified as regular data.

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