CN114429407A - Auxiliary service assessment data processing method and device - Google Patents
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Abstract
The application discloses an auxiliary service assessment data processing method and device, relates to the technical field of electric power assessment management, and can improve the auxiliary service assessment data processing efficiency. The method comprises the following steps: respectively acquiring initial auxiliary service assessment data from a computer monitoring system and an auxiliary service assessment system of a power grid company; screening the initial auxiliary service assessment data to obtain target messages corresponding to a plurality of auxiliary service types; respectively extracting characteristic data of the target message aiming at each auxiliary service type to obtain characteristic data corresponding to a plurality of auxiliary service types; and generating reports corresponding to different preset formats according to the characteristic data corresponding to the plurality of auxiliary service types. The method and the device are suitable for processing the electric power auxiliary service assessment data.
Description
Technical Field
The application relates to the technical field of electric power examination and management, in particular to a method and a device for processing auxiliary service examination data.
Background
In recent years, the requirement of power grid companies on the power quality of power generation enterprises is gradually increased, and as a management and control means, the power grid companies can perform monthly assessment on the execution condition of power adjustment instructions of the power generation enterprises, namely, auxiliary service assessment. The auxiliary service is the service provided by power generation enterprises, power grid management enterprises and power consumers except normal power production, transmission and use for maintaining the safe and stable operation of the power system and ensuring the power quality, and comprises primary frequency modulation, automatic power generation control, peak regulation, automatic voltage reactive power control, standby and the like. In order to reduce economic losses brought to enterprises by unqualified assessment items, power generation enterprises need to regularly summarize and analyze generated auxiliary service assessment data so as to find the unqualified assessment items in time and modify the unqualified assessment items.
At present, auxiliary service assessment data exist in systems of two different network partitions, data communication cannot be achieved between the auxiliary service assessment data and the systems, data needs to be exported manually, most message data are text files, complex screening and searching cannot be conducted, the message information needs to be checked line by line and data extraction needs to be conducted manually, and in the face of the situation that the current message data quantity is large and redundant data are large, data analysis and processing difficulty is large, so that the problems that time and labor cost are high, and data processing efficiency and accuracy are low exist in the existing auxiliary service assessment data processing method based on manual work.
Disclosure of Invention
In view of the above, the present application provides an auxiliary service assessment data processing method and apparatus, and mainly aims to solve the problems of high time and labor cost, and low data processing efficiency and accuracy of the existing artificial-based auxiliary service assessment data processing method.
According to one aspect of the application, an auxiliary service assessment data processing method is provided, and the method comprises the following steps:
respectively acquiring initial auxiliary service assessment data from a computer monitoring system and an auxiliary service assessment system of a power grid company;
screening the initial auxiliary service assessment data to obtain target messages corresponding to a plurality of auxiliary service types;
respectively extracting characteristic data of the target message aiming at each auxiliary service type to obtain characteristic data corresponding to a plurality of auxiliary service types;
and generating reports corresponding to different preset formats according to the characteristic data corresponding to the plurality of auxiliary service types.
According to another aspect of the present application, there is provided an auxiliary service assessment data processing apparatus, the apparatus comprising:
an acquisition module: the system comprises a computer monitoring system, a power grid company auxiliary service assessment system and a data processing system, wherein the computer monitoring system and the power grid company auxiliary service assessment system are used for respectively acquiring initial auxiliary service assessment data;
a screening module: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring initial auxiliary service assessment data;
an extraction module: the system comprises a target message acquisition module, a service type classification module and a service type classification module, wherein the target message acquisition module is used for acquiring a plurality of auxiliary service types;
a generation module: and generating reports corresponding to different preset formats according to the characteristic data corresponding to the plurality of auxiliary service types.
According to yet another aspect of the present application, there is provided a storage medium having stored thereon a computer program which, when executed by a processor, implements the above-described supplementary service assessment data processing method.
According to yet another aspect of the present application, there is provided a computer device comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor implements the auxiliary service assessment data processing method when executing the program.
By means of the technical scheme, compared with the existing manual-based auxiliary service assessment data processing method, the method and the device for processing the auxiliary service assessment data respectively obtain initial auxiliary service assessment data from a computer monitoring system and an auxiliary service assessment system of a power grid company, target messages corresponding to a plurality of auxiliary service types are obtained by screening the initial auxiliary service assessment data, feature data extraction is respectively carried out on the target messages according to each auxiliary service type, feature data corresponding to the plurality of auxiliary service types are obtained, and reports corresponding to different preset formats are generated according to the feature data corresponding to the plurality of auxiliary service types. Therefore, initial auxiliary service assessment data are automatically acquired from systems of different network partitions, feature data extraction is carried out based on data screening results, and reports of different preset formats are generated according to feature data extraction results, so that the technical problems of high time and labor cost and low data processing efficiency and accuracy of the conventional artificial auxiliary service assessment data processing method can be effectively solved, the full-flow automatic processing of the auxiliary service assessment data is realized, the time and labor cost is effectively reduced, the data processing efficiency is improved, and the accuracy of the data processing result is ensured.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
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The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a flow chart diagram illustrating a method for processing auxiliary service assessment data according to an embodiment of the present disclosure;
FIG. 2 is a flow chart diagram illustrating another method for processing auxiliary service assessment data provided by an embodiment of the present application;
FIG. 3 is a schematic structural diagram of an auxiliary service assessment data processing device provided by an embodiment of the present application;
FIG. 4 is a schematic structural diagram of another auxiliary service assessment data processing device provided by the embodiment of the application.
Detailed Description
The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
The method aims at the technical problems that the time and labor cost are high and the accuracy of an analysis result is low in the existing method for processing the examination data of the manual auxiliary service. The embodiment provides an auxiliary service assessment data processing method, which is characterized in that initial auxiliary service assessment data are obtained from systems of different network partitions at regular time, characteristic data are extracted based on data screening results, and reports are generated according to different preset formats according to the characteristic data, so that the full-flow automatic processing of the auxiliary service assessment data is realized, the time and labor cost are effectively reduced, the data processing efficiency is improved, and the accuracy of data processing results is ensured. As shown in fig. 1, the method includes:
In the embodiment, the computer monitoring system and the power grid company auxiliary service assessment system belong to different network areas, and in order to realize data communication between different systems, initial auxiliary service assessment data are respectively obtained from the two systems by two modes of cross-network area data transmission and same-network area data transmission, and simultaneously, the initial auxiliary service assessment data is read regularly through an interface program according to the preset timing task, the automatic import of the auxiliary service assessment data from the unused network partition is realized, wherein, the message format of the initial auxiliary service assessment data can comprise a text document format and an excel spreadsheet format, and meanwhile, the preset timing task can be set according to the data analysis requirement, in this embodiment, the data of each natural month needs to be processed, and the preset timing task is to read the initial auxiliary service assessment data of the previous natural month from the zero point of the first day of the current natural month.
And 102, screening the initial auxiliary service assessment data to obtain target messages corresponding to a plurality of auxiliary service types.
In this embodiment, the obtained initial auxiliary service assessment data corresponds to a plurality of auxiliary service types, where the auxiliary service types include: primary frequency modulation, bus Voltage, Automatic Voltage Control (AVC), and the like. The initial auxiliary service assessment data of each auxiliary service type comprises complex messages, the proportion of the messages needing to be specifically analyzed is small, the messages needing to be specifically analyzed are screened from the initial auxiliary service assessment data aiming at each auxiliary service type, target messages corresponding to a plurality of auxiliary service types are obtained, data redundancy in the initial auxiliary service assessment data can be removed, accordingly, workload of backward feature data extraction is reduced, and work efficiency of data processing is improved.
And 103, respectively extracting characteristic data of the target message aiming at each auxiliary service type to obtain characteristic data corresponding to a plurality of auxiliary service types.
In this embodiment, the feature data includes first feature data obtained by extracting feature data according to the target packet and second feature data obtained by calculating according to the first feature data. The method comprises the steps of respectively extracting feature data of a target message aiming at each auxiliary service type to obtain first feature data corresponding to a plurality of auxiliary service types, wherein the first feature data comprise time data and reason data of corresponding auxiliary services in an exit state in power unit equipment, and data of whether the exit state belongs to an auxiliary service assessment-free category set by a power grid company, and further, second feature data are respectively obtained through calculation according to the exit state time data, the reason data and the data of whether the exit state belongs to the assessment-free category, wherein the second feature data comprise: the system comprises a unit full stop time, auxiliary service exit total time, monthly check-free time, auxiliary service commissioning rate and the like.
And 104, generating reports corresponding to different preset formats according to the characteristic data corresponding to the plurality of auxiliary service types.
In this embodiment, different preset formats correspond to different report template formats, the report template is obtained based on a report template file issued by a power grid company, and specifically includes a first report template in an excel spreadsheet format and a second report template in a word electronic document format, and feature data corresponding to a plurality of auxiliary service types are imported into the first report template by using a preset import function to generate a first report; and further, importing the screenshot file of the first report into a second report template by using a preset import function to generate a second report. When a power grid company issues a new report template file, the new report template file needs to be imported, wherein before the report template file is imported, the name (including a complete path) of the report template file and a dictionary of replacement contents need to be manually input into a preset import function, so that the preset import function can be identified.
In an actual application scenario, the electric power enterprise needs to provide reports to the power grid company every month, the report template is generated according to the report template file issued by the power grid company, the extracted feature data is imported into corresponding positions of different templates, and the reports meeting the format requirements of the power grid company are generated, so that the report generation efficiency and accuracy can be effectively improved, and the labor cost and the time cost are reduced.
For the embodiment, according to the scheme, initial auxiliary service assessment data is respectively obtained from a computer monitoring system and an auxiliary service assessment system of a power grid company, target messages corresponding to a plurality of auxiliary service types are obtained by screening the initial auxiliary service assessment data, feature data extraction is respectively carried out on the target messages aiming at each auxiliary service type, feature data corresponding to the plurality of auxiliary service types are obtained, reports corresponding to different preset formats are generated according to the feature data corresponding to the plurality of auxiliary service types, compared with the existing artificial-based auxiliary service assessment data processing method, the embodiment automatically obtains the initial auxiliary service assessment data from systems of different network partitions, carries out feature data extraction based on data screening results, and further generates reports of different preset formats according to feature data extraction results, the method can effectively solve the technical problems of high time and labor cost and low data processing efficiency and accuracy of the conventional manual-based auxiliary service assessment data processing method, thereby realizing the full-flow automatic processing of the auxiliary service assessment data, effectively reducing the time and labor cost, improving the data processing efficiency and ensuring the accuracy of a data processing result.
Further, as a refinement and an extension of the specific implementation of the above embodiment, in order to fully illustrate the specific implementation process of the embodiment, another auxiliary service assessment data processing method is provided, as shown in fig. 2, the method includes:
In implementation, aiming at a computer monitoring system belonging to different network partitions from a data processing side, cross-region data transmission is carried out through a firewall and a transverse isolation device, and an interface program is used for regularly reading initial auxiliary service assessment data of the side; the power grid company auxiliary service assessment system which belongs to the same network partition as a data processing side performs data transmission in the same area through a network switch and reads initial auxiliary service assessment data of the side regularly by using an interface program, wherein the power grid company auxiliary service assessment system can be a southern power grid 1+5 auxiliary service assessment system, a network partition of a server in which the power grid company auxiliary service assessment system is located belongs to a safety III area (a production management area), a computer monitoring system can be a monitoring system of a power equipment side, a network partition of a server in which the power grid company auxiliary service assessment system is located belongs to a safety I area (a production real-time control large area), auxiliary service assessment data of different network partitions are obtained through a firewall and a transverse isolation device, the problem of data cross-area transmission can be effectively solved, and the safety of data transmission is guaranteed.
And 203, screening the initial auxiliary service assessment data message by using a preset keyword to obtain a target message containing the preset keyword, wherein the preset keyword is set according to a plurality of auxiliary service types of the initial auxiliary service assessment data.
In implementation, the preset keywords are set based on the message signal content to be specifically analyzed in the historical auxiliary service data of each auxiliary service type, the corresponding preset keywords are respectively used for matching the message of the initial auxiliary service assessment data aiming at each auxiliary service type, and the message containing the preset keywords is reserved as a target message, so that unnecessary processing messages in the initial auxiliary service assessment data are removed and necessary processing messages are extracted.
And 204, respectively extracting characteristic data of the target message aiming at each auxiliary service type to obtain first characteristic data corresponding to a plurality of auxiliary service types.
For the purpose of illustrating the specific implementation of step 204, as a preferred embodiment, step 204 specifically includes: for each auxiliary service type, sequentially judging a plurality of message signals in the target message by utilizing a corresponding preset condition judgment process, and determining the arrangement sequence of different message signals; and according to the arrangement sequence of the different message signals, judging the characteristic data corresponding to each message signal output by the process according to the preset condition, and obtaining the first characteristic data of the target message.
In implementation, each target packet includes a plurality of packet signals arranged according to a time sequence, where the packet signals include content, state, and time, where the content and state of different packet signals represent different operating states of an auxiliary service, the time of a packet signal corresponds to the time when the auxiliary service is put into or taken out of operation, and the occurrence sequence of adjacent different operating states of the auxiliary service represents different reasons for the auxiliary service to take out of operation, and the predetermined condition judgment process is used to sequentially judge a plurality of packet signals of each target packet to determine an arrangement combination formed by each two adjacent different packet signals, and further determine a corresponding relationship between the arrangement combination of different packet signals in the process and predetermined output feature data according to the predetermined condition to obtain first feature data of the target packet, where the first feature data at least includes: the method comprises the steps of inputting time, quitting time, total quitting time, a first preset reason and a second preset reason, wherein the condition of exemption is met, and the condition of exemption is not met, wherein the total quitting time is the difference value of the inputting time and the quitting time.
Specifically, the preset condition judgment process includes five conditional branches, which specifically include:
the first conditional branch is: acquiring a message and a flag bit equal to False; judging the first message signal: whether the message signal content contains "auxiliary service investment"; if yes, entering a second conditional branch; if not, determining that the message signal contains 'unit shutdown state' and 'action'; and further judging: whether the flag bit is False or not; if not, ending the current message signal; if yes, acquiring the current message signal time as 'input time'; the quit reason is the 'first preset reason'; whether the condition of exemption is satisfied is 'yes'; assigning the flag bit as tube; acquiring the Time of a current message signal; and further judging: whether the message is finished or not; if yes, the flow is ended; if not, reading the next message signal.
The second condition is that: and (3) judging: whether the message signal state contains a "reset"; if yes, acquiring the current message signal time as exit time, finishing the current message signal, and reading the next message signal; otherwise, the third conditional branch is entered.
The third condition is as follows: and (3) judging: whether or not 'flag bit ═ False'; if yes, go to the fourth conditional branch; if not, taking the 'Time' in the first conditional branch as the 'exit Time'; acquiring current message signal time as 'input time'; the quit reason is the "second preset reason"; whether the condition of exemption is satisfied is 'no'; ending the current message signal.
The fourth condition is as follows: and (3) judging: whether the populated data list is empty; if not, entering a fifth conditional branch; if yes, taking the first date and hour of the current natural month as exit time; acquiring current message signal time as 'input time'; the quit reason is the 'second preset reason'; whether the condition of exemption is satisfied is 'no'; ending the current message signal.
The fifth condition is that: acquiring current message signal time as 'input time'; the quit reason is the 'first preset reason'; whether the condition of exemption is satisfied is 'yes'; ending the current message signal.
It should be noted that the "input time" of the first conditional branch and the "input time" of the fifth conditional branch both correspond to the "exit time" of the second conditional branch, and in addition, the characteristic data (first characteristic data) such as the exit time, the input time, the exit reason, and whether to avoid examination, which are obtained by the preset condition judgment process, are all filled into the data list with a single natural month as the statistical period, and whether the data list filled by the judgment statement "in the" fourth conditional branch "is empty" is judged, that is, whether the current message signal is the first message signal of the current natural month is judged.
Further, the correspondence between different message signal permutation and combination and the preset output characteristic data specifically includes:
if the message signal corresponds to the permutation and combination of the power unit action signal and the auxiliary service input signal, the exit time is the time of the power unit action signal, the input time is the time of the auxiliary service input signal, and the exit reason is 'unit halt' and does not meet the requirement of exemption;
if the message signal corresponds to a reset signal of auxiliary service input and a permutation and combination of power unit action signals, the exit time is the time of the auxiliary service input reset signal, the input time is the time of the power unit action signal, and the exit reason is 'centralized control exit auxiliary service', so that the requirement of exemption from examination is met;
if the message signal corresponds to a reset signal of auxiliary service input and a permutation combination of auxiliary service input signals, the exit time is the time of inputting the reset signal by the auxiliary service, the input time is the time of inputting the signal by the auxiliary service, and the exit reason is 'centralized control exit of the auxiliary service', so that the requirement of no check is met;
if the first message signal of the target message is an auxiliary service input signal, the exit time is zero of the first day of the month, the input time is the auxiliary service input signal time, and the exit reason is 'unit halt' and does not meet the requirement of no examination.
Specifically, the method is explained by taking a process link of an automatic voltage control AVC auxiliary service type as an example, where the content and the state of the message signal corresponding to the AVC auxiliary service type include: the method includes that a unit AVC is input, a unit AVC is input and is reset, a unit is in a shutdown state and is operated, a first preset reason included in first characteristic data is that before the unit is shutdown, centralized control exits from the unit AVC, a second preset reason is that the unit is shutdown, a preset condition judgment flow corresponding to an AVC auxiliary service type is used for judging a message signal, and first characteristic data are obtained, and the method specifically includes the following steps:
if the current message signal is 'unit AVC input' and the data list is empty, the flow passes through a fourth conditional branch, the zero point of the first day of the current natural month is taken as exit time, the current message signal time is taken as input time, the total exit time is the input time-exit time, and the exit reason is 'unit halt' and whether the assessment-free 'no' is met or not is judged.
And if the current message signal is 'unit AVC input' and 'reset', the current message signal is acquired as exit time by passing through a second conditional branch.
If the current message signal is in a unit shutdown state and an action state, and the previous message signal is in a unit AVC input state and a reset state, the current message signal flows through a first conditional branch, the exit Time obtained by the previous message signal is obtained as the exit Time, the current message signal Time is obtained as the input Time, the total exit Time is the input Time and the exit Time, the exit reason is that before the unit is shutdown, the unit AVC is intensively controlled to exit, whether the examination-free condition is met or not, the flag bit is Ture, and the current message signal Time is obtained and stored as the Time.
If the current message signal is 'unit AVC input' and the last message signal is 'unit shutdown state' and 'action', the flow goes through a third conditional branch, the Time is obtained as the exit Time, the current message signal Time is obtained as the input Time, the total exit Time is the input Time-the exit Time, the exit reason is 'unit shutdown', and whether the condition of no check is met or not is judged.
If the current message signal is 'unit AVC input' and the previous message signal is 'unit AVC input' and 'reset', the flow is through a fifth conditional branch, the current message signal time is obtained as input time, the exit time obtained by the previous message signal is obtained as exit time, the total exit time is the input time-the exit time, and the exit reason is that 'before the unit stops, the stand-alone AVC is exited in a centralized control manner', whether the examination-free 'yes' is met.
In an actual application scenario, the message signals representing different auxiliary service operating states are not in one-to-one correspondence with the first characteristic data, the first characteristic data cannot be directly obtained in a key value pairing mode of the keyword dictionary, the first characteristic data needs to be extracted according to the sequence of occurrence of two adjacent different auxiliary service operating states, the characteristic data of the message signals in the target message is extracted by using a preset condition judgment process, the characteristic data represented by the message signals can be accurately extracted, and therefore the efficiency and the accuracy of auxiliary service examination data processing are improved.
And step 205, for each auxiliary service type, calculating according to the first characteristic data to obtain second characteristic data corresponding to a plurality of auxiliary service types.
In an implementation, the second characteristic data includes: "total exit time of auxiliary service", "total stop time of unit", "check-free time of month", and "commissioning rate of auxiliary service". For each auxiliary service type, respectively calculating to obtain second feature data according to the first feature data specifically includes: summing all the exit time in the current data list to obtain the total exit time of the auxiliary service; summing all exit time of the corresponding exit reason in the current data list, namely 'unit shutdown', to obtain 'unit full shutdown time'; summing all exit times corresponding to yes in the current data list to obtain monthly check-free time; and (3) taking the ratio of the difference value of the auxiliary service total exiting time and the unit total stopping time to the current natural month total time to obtain the auxiliary service commissioning rate.
And step 206, generating a first report according to the first characteristic data and the second characteristic data and a preset format corresponding to a first report template.
In implementation, first characteristic data output after a message signal undergoes a preset condition judgment process is filled into a first characteristic data area (data list) of a first report template, and further, second characteristic data is filled into a second characteristic data area of the first report template to obtain a first report, wherein the first report is a data type report meeting the excel spreadsheet format of a power grid company and is used for storing all data analysis results and providing data basis for generation of the second report, a third report and a data diagram.
And step 207, filling the screenshot of the corresponding content of the first report into the second report template according to the preset format of the second report template, and generating a second report.
In the implementation, the content of the screenshot in the first report is determined according to the key words in the current picture filling area of the second report template, determining the maximum filling size of the current picture filling area of the second report template and the size of the screenshot area corresponding to the content to be intercepted in the first report by using a preset screenshot function, further obtaining one or more screenshot files corresponding to the content to be intercepted by using the preset screenshot function according to the maximum filling size and the size of the screenshot area, generating a second report according to the preset format of the second preset template based on the first report and the one or more screenshot files, wherein the second report is a report type report meeting the format of a word electronic document of a power grid company, the corresponding second report form template comprises a plurality of picture filling areas, and keywords and explanation descriptions corresponding to filling contents, and the specific process comprises the following steps:
1) and calculating to obtain the maximum filling size of the picture filling area in the second report template in the current page by using a preset screenshot function based on the fixed text format of the second report template, such as font, line spacing and the like.
2) The data in the first report can be converted into text data in the program reading process, and the beginning of the content to be intercepted comprises a text field which has a unique corresponding relation with the picture filling area key word, so that the content to be intercepted can be determined from the first report according to the key word of the picture filling area, further, the area to be intercepted is determined according to the position of the content to be intercepted in the excel cell, and then the size of the area to be intercepted is calculated by utilizing a preset screenshot function based on a fixed cell format.
3) Intercepting the area to be shot by using a shot function and an adjusting and judging statement: comparing the length of the size of the area to be captured with the length of the maximum filling size, and if the length of the size of the area to be captured is less than or equal to the length of the maximum filling size, capturing the area to be captured to obtain a capture file; and if the length of the area to be captured is greater than the maximum filling size length, splitting and capturing the area to be captured to obtain a plurality of captured files, wherein the first report and the second report are in a fixed format, and the default captured area size width is smaller than the maximum filling size width. In addition, each time the capture is completed, the final position of the last capture is recorded so that the capture area is automatically transferred to a position without capture with reference to the position of the last capture at the time of the next capture to ensure the integrity and non-overlap of the capture areas, for example, the area to be captured is [ a1: i80], the maximum filling size of the current page of the second report template corresponds to the size of 30 rows of data, the filling size of the blank page corresponds to the size of 50 rows of data, the screenshot area is intercepted twice, screen _ area is [ 'A1: I30', 'A31: I80' ], and flag: y, picture _ name is [ '1', '2' ], namely a screenshot file 1 and a screenshot file 2 are obtained.
The preset screenshot function comprises 5 inputs, and specifically comprises the following steps: # filename: excel filename (including full path), # sheetname: sheet page name of excel file, # screen _ area: screenshot areas, stored in list form as: [ 'A1: M11', 'A13: L23', 'A26: L36' ], which shows that 3 regions are each cut: a1 to M11, a13 to L23, a26 to L36, # picture _ name: the filename of the screenshot (including the full path) is generated, stored in list form, and the program is added with the png suffix such as: [ 'E:/png1', 'E:/png2', 'E:/png3' ], # flag: if the mark is not needed to be processed continuously, y represents that the screenshot is abnormal, all screenshots are not generated, the preset screenshot function needs to be called again, and the non-generated screenshots are processed; if all the processing is completed, n is indicated.
4) And importing the obtained one or more screenshot files into a corresponding filling area of a second report template by using a preset import function to generate a second report.
In an actual application scenario, data graphs corresponding to different dimensions can be generated in real time according to requirements of users for different dimensions, wherein the dimensions of the data graphs specifically include: time dimension such as month and year, auxiliary service type dimension such as primary frequency modulation auxiliary service type, bus voltage auxiliary service type, AVC auxiliary service type, and device dimension such as number 1 unit, AVC substation, and the data diagram type may specifically include: the data analysis method comprises the steps of obtaining a histogram, a pie chart, a line chart and the like, wherein the histogram, the pie chart, the line chart and the like are not particularly limited, and in addition, the obtained data chart can be used for importing a first report, a second report and a third report to provide reference for further data analysis of a user, so that the analysis requirements of the user on data with different dimensions are met while data visualization display is achieved.
And 209, summarizing the first report form corresponding to the time period to obtain a third report form.
In implementation, according to the time period requirement of a user on data analysis, a plurality of first reports in a corresponding time period are read through a preset storage path, ring ratio and same ratio operation is performed on data in the plurality of first reports, and then a third report is generated according to the operation result of the ring ratio and the same ratio, wherein the third report is used for analyzing auxiliary service assessment data inside an electric power enterprise, and can be an annual report, a quarterly report and the like, which is not specifically limited here.
By applying the technical scheme of the embodiment, initial auxiliary service assessment data is respectively obtained from a computer monitoring system and an auxiliary service assessment system of a power grid company, target messages corresponding to a plurality of auxiliary service types are obtained by screening the initial auxiliary service assessment data, feature data extraction is respectively carried out on the target messages aiming at each auxiliary service type, feature data corresponding to the plurality of auxiliary service types are obtained, reports corresponding to different preset formats are generated according to the feature data corresponding to the plurality of auxiliary service types, compared with the existing artificial-based auxiliary service assessment data analysis and processing method, the embodiment automatically obtains the initial auxiliary service assessment data from systems of different network partitions, carries out feature data extraction based on data screening results, and further generates reports of different preset formats according to feature data extraction results, the method can effectively solve the technical problems of high time and labor cost and low data processing efficiency and accuracy of the conventional manual-based auxiliary service assessment data processing method, thereby realizing the full-flow automatic processing of the auxiliary service assessment data, effectively reducing the time and labor cost, improving the data processing efficiency and ensuring the accuracy of a data processing result.
Further, as a specific implementation of the method in fig. 1, an embodiment of the present application provides an apparatus for detecting an abnormality of a user access behavior, as shown in fig. 3, the apparatus includes: the device comprises an acquisition module 31, a screening module 32, an extraction module 33 and a generation module 34.
The acquisition module 31: the method can be used for respectively acquiring initial auxiliary service assessment data from the computer monitoring system and the auxiliary service assessment system of the power grid company.
The screening module 32: the method can be used for screening the messages in the initial auxiliary service assessment data by using preset keywords corresponding to a plurality of auxiliary service types to obtain target messages corresponding to a plurality of auxiliary service types.
The extraction module 33: the method and the device can be used for respectively extracting the feature data of the target message aiming at each auxiliary service type to obtain the feature data corresponding to a plurality of auxiliary service types, wherein the feature data comprises first feature data and second feature data.
The generation module 34: the method and the device can be used for generating reports corresponding to different preset formats according to the characteristic data corresponding to the plurality of auxiliary service types, wherein the different preset formats correspond to the first report template preset format and the second report template preset format.
In a specific application scenario, as shown in fig. 4, the obtaining module 31 includes a first obtaining unit 311 and a second obtaining unit 312.
The first obtaining unit 311 may be configured to perform data transmission across a network area through a firewall and a horizontal isolation device, and obtain initial auxiliary service assessment data on the computer monitoring system side.
The second obtaining unit 312 may be configured to perform data transmission in the same network area through a network switch, and obtain initial auxiliary service assessment data of the auxiliary service assessment system side of the power grid company.
In a specific application scenario, the screening module 32 may be specifically configured to screen the message of the initial auxiliary service assessment data by using a preset keyword, so as to obtain a target message including the preset keyword; the preset keywords are set according to a plurality of auxiliary service types of the initial auxiliary service assessment data.
In a specific application scenario, the extraction module 33 includes a first extraction unit 331 and a second extraction unit 332.
The first extracting unit 331 may be configured to, for each auxiliary service type, respectively perform feature data extraction on the target packet, so as to obtain first feature data corresponding to a plurality of auxiliary service types.
The second extracting unit 332 may be configured to perform calculation according to the first feature data for each auxiliary service type, so as to obtain second feature data corresponding to a plurality of auxiliary service types.
In a specific application scenario, the first extracting unit 331 may be specifically configured to, for each auxiliary service type, sequentially determine, by using a corresponding preset condition determination process, a plurality of message signals in the target message, and determine an arrangement order between different message signals; and according to the arrangement sequence of the different message signals, judging the characteristic data corresponding to each message signal output by the process according to the preset condition, and obtaining the first characteristic data of the target message.
In a specific application scenario, the generating module 34 includes a first report generating unit 341, a second report generating unit 342, a data map generating unit 343, and a third report generating unit 344.
The first report generating unit 341 is configured to generate a first report according to the first characteristic data and the second characteristic data and according to the preset format of the first report template.
The second report generating unit 342 may be configured to fill the screenshot of the content corresponding to the first report into the second report template according to the preset format of the second report template, so as to generate a second report.
The data diagram generating unit 343 may be configured to generate, according to the first report, data diagrams of different dimensions, where the data diagrams of different dimensions at least include: a data graph of a time dimension, a data graph of a device dimension, and a data graph of an auxiliary service type dimension.
The third report generating unit 344 may be configured to obtain a third report according to the first report corresponding to the time period.
It should be noted that other corresponding descriptions of the functional units related to the auxiliary service assessment data processing apparatus provided in the embodiment of the present application may refer to the corresponding descriptions in fig. 1 and fig. 2, and are not described herein again.
Based on the above-mentioned methods shown in fig. 1 and fig. 2, correspondingly, the embodiment of the present application further provides a storage medium, on which a computer program is stored, and the program, when executed by a processor, implements the above-mentioned auxiliary service assessment data processing method shown in fig. 1 and fig. 2.
Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, which may be stored in a storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, or the like), and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the method described in the implementation scenarios of the present application.
Based on the above methods shown in fig. 1 and fig. 2 and the virtual device embodiment shown in fig. 4, in order to achieve the above object, an embodiment of the present application further provides a computer device, which may specifically be a personal computer, a server, a network device, and the like, where the entity device includes a storage medium and a processor; a storage medium for storing a computer program; a processor for executing a computer program to implement the above-described auxiliary service assessment data processing method as shown in fig. 1 and 2.
Optionally, the computer device may further include a user interface, a network interface, a camera, Radio Frequency (RF) circuitry, a sensor, audio circuitry, a WI-FI module, and so forth. The user interface may include a Display screen (Display), an input unit such as a keypad (Keyboard), etc., and the optional user interface may also include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (e.g., a bluetooth interface, WI-FI interface), etc.
It will be understood by those skilled in the art that the structure of a computer device provided in the present embodiment does not constitute a limitation of the physical device, and may include more or fewer components, or some components in combination, or a different arrangement of components.
The storage medium may further include an operating system and a network communication module. An operating system is a program that manages the hardware and software resources of a computer device, supporting the operation of information handling programs, as well as other software and/or programs. The network communication module is used for realizing communication among components in the storage medium and other hardware and software in the entity device.
Through the above description of the embodiments, those skilled in the art will clearly understand that the present application can be implemented by software plus a necessary general hardware platform, and can also be implemented by hardware. By applying the technical scheme of the application, compared with the existing manual-based auxiliary service assessment data processing method, the initial auxiliary service assessment data are automatically acquired from systems of different network partitions, the characteristic data are extracted based on the data screening result, and then reports of different preset formats are generated according to the characteristic data extraction result, so that the technical problems of high time and labor cost and low data processing efficiency and accuracy of the existing manual-based auxiliary service assessment data processing method can be effectively solved, the full-flow automatic processing of the auxiliary service assessment data is realized, the time and labor cost is effectively reduced, and the accuracy of the data processing result is ensured while the data processing efficiency is improved.
Those skilled in the art will appreciate that the figures are merely schematic representations of one preferred implementation scenario and that the blocks or flow diagrams in the figures are not necessarily required to practice the present application. Those skilled in the art will appreciate that the modules in the devices in the implementation scenario may be distributed in the devices in the implementation scenario according to the description of the implementation scenario, or may be located in one or more devices different from the present implementation scenario with corresponding changes. The modules of the implementation scenario may be combined into one module, or may be further split into a plurality of sub-modules.
The above application serial numbers are for description purposes only and do not represent the superiority or inferiority of the implementation scenarios. The above disclosure is only a few specific implementation scenarios of the present application, but the present application is not limited thereto, and any variations that can be made by those skilled in the art are intended to fall within the scope of the present application.
Claims (10)
1. An auxiliary service assessment data processing method is characterized by comprising the following steps:
respectively acquiring initial auxiliary service assessment data from a computer monitoring system and an auxiliary service assessment system of a power grid company;
screening the initial auxiliary service assessment data to obtain target messages corresponding to a plurality of auxiliary service types;
respectively extracting characteristic data of the target message aiming at each auxiliary service type to obtain characteristic data corresponding to a plurality of auxiliary service types;
and generating reports corresponding to different preset formats according to the characteristic data corresponding to the plurality of auxiliary service types.
2. The method as claimed in claim 1, wherein the step of obtaining the initial auxiliary service assessment data from the computer monitoring system and the power grid company auxiliary service assessment system respectively comprises:
performing data transmission across network areas through a firewall and a transverse isolation device to obtain initial auxiliary service assessment data of the computer monitoring system side;
and performing data transmission in the same network area through a network switch to obtain initial auxiliary service assessment data of the auxiliary service assessment system side of the power grid company.
3. The method according to claim 1, wherein the obtaining of the target packet corresponding to the plurality of auxiliary service types by screening the initial auxiliary service assessment data specifically comprises:
screening the messages of the initial auxiliary service assessment data by using preset keywords to obtain target messages containing the preset keywords;
the preset keywords are set according to a plurality of auxiliary service types of the initial auxiliary service assessment data.
4. The method according to claim 1, wherein the feature data includes first feature data and second feature data, and the extracting feature data from the target packet for each auxiliary service type to obtain feature data corresponding to a plurality of auxiliary service types specifically includes:
respectively extracting characteristic data of the target message aiming at each auxiliary service type to obtain first characteristic data corresponding to a plurality of auxiliary service types;
and aiming at each auxiliary service type, calculating according to the first characteristic data to obtain second characteristic data corresponding to a plurality of auxiliary service types.
5. The method according to claim 4, wherein the extracting feature data of the target packet for each auxiliary service type to obtain first feature data corresponding to a plurality of auxiliary service types includes:
for each auxiliary service type, sequentially judging a plurality of message signals in the target message by utilizing a corresponding preset condition judgment process, and determining the arrangement sequence of different message signals;
and according to the arrangement sequence of the different message signals, judging the characteristic data corresponding to each message signal output by the process according to the preset condition, and obtaining the first characteristic data of the target message.
6. The method according to claim 1, wherein the different preset formats correspond to a first report template preset format and a second report template preset format, and the generating reports corresponding to the different preset formats according to the feature data of the target packet specifically comprises:
generating a first report according to the first characteristic data and the second characteristic data and a preset format of the first report template;
and filling the screenshot of the corresponding content of the first report into the second report template according to the preset format of the second report template to generate a second report.
7. The method according to claim 1 or 6, wherein generating reports corresponding to different preset formats according to the feature data corresponding to the plurality of auxiliary service types further comprises:
generating data graphs with different dimensions according to the first report, wherein the data graphs with different dimensions at least comprise: a data graph of a time dimension, a data graph of an equipment dimension and a data graph of an auxiliary service type dimension;
and summarizing according to the first report corresponding to the time period to obtain a third report.
8. An auxiliary service assessment data processing apparatus, comprising:
an acquisition module: the system comprises a computer monitoring system, a power grid company auxiliary service assessment system and a data processing system, wherein the computer monitoring system and the power grid company auxiliary service assessment system are used for respectively acquiring initial auxiliary service assessment data;
a screening module: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring initial auxiliary service assessment data;
an extraction module: the system comprises a target message acquisition module, a service type classification module and a service type classification module, wherein the target message acquisition module is used for acquiring a plurality of auxiliary service types;
a generation module: and generating reports corresponding to different preset formats according to the characteristic data corresponding to the plurality of auxiliary service types.
9. A storage medium on which a computer program is stored, which program, when being executed by a processor, implements the auxiliary service assessment data processing method of any one of claims 1 to 7.
10. A computer device comprising a storage medium, a processor and a computer program stored on the storage medium and executable on the processor, wherein the processor implements the auxiliary service assessment data processing method of any one of claims 1 to 7 when executing the program.
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