CN112464192A - Power grid data asset management system based on big data - Google Patents
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Abstract
The invention discloses a power grid data asset management system based on big data, which comprises a login module, an identity verification module, a data right-lifting module, a data import module, a data receiving module, a master control module, an alarm sending module, a backup storage module, a storage cloud and a data extraction module, wherein the login module is used for storing the identity verification module; the system comprises a login module, an identity verification module, a data import module and a data receiving module, wherein the login module is used for a user to log in the system to extract and import data assets, the identity verification module is used for verifying the identity of a person logged in the system through the login module, alarm information is generated when the person is not verified in the identity verification module, the data extraction module is used for extracting the data assets of the user who passes the verification, the data import module is used for importing the data asset information into the system through the user who passes the verification, and the data receiving module is used for receiving the data asset information imported through the data import module. The invention can better ensure the safety of the power grid data assets and can better manage the power grid data assets.
Description
Technical Field
The invention relates to the field of power grid management, in particular to a power grid data asset management system based on big data.
Background
The whole of the substation and the transmission and distribution line of various voltages in the power system is called a power grid. The system comprises three units of power transformation, power transmission and power distribution. The task of the power grid is to transmit and distribute electric energy, change voltage, and be a kind of grid data, which needs to be managed and operated.
The existing power grid data asset management system is low in safety, easily causes leakage of power grid data assets, and brings certain influence to the use of the power grid data asset management system, so that the power grid data asset management system based on big data is provided.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: how to solve the problems that the existing power grid data asset management system is low in safety, easily causes leakage of power grid data assets and brings certain influence to the use of the power grid data asset management system, and the power grid data asset management system based on big data is provided.
The invention solves the technical problems through the following technical scheme that the system comprises a login module, an identity authentication module, a data right-lifting module, a data import module, a data receiving module, a master control module, an alarm sending module, a backup storage module, a storage cloud and a data extraction module;
the system comprises a login module, an identity authentication module, a data receiving module, a master control module and a backup storage module, wherein the login module is used for a user to log in the system to extract and import data assets, the identity authentication module is used for authenticating the identity of a person logged in the system through the login module, alarm information is generated when the person is not authenticated in the identity authentication module, the data extracting module is used for extracting the data assets of the authenticated user, the data importing module is used for importing data asset information into the system through the authenticated user, the data receiving module is used for receiving the data asset information imported through the data importing module, the master control module is used for generating a backup control instruction, and the backup control instruction is sent to the backup storage module;
the backup storage module backs up the data asset information received by the data receiving module to the hard disk, and backs up the data asset information to the storage cloud;
the master control module converts the alarm information into an alarm instruction and sends the alarm instruction to the alarm sending module, and the alarm sending module sends the alarm instruction to the instructed mobile terminal.
Preferably, the login module comprises a login keyboard, a display screen and a face recognition camera, the login keyboard is used for inputting account and password information by a user, the display screen is used for displaying prompting performance, and the face recognition camera is used for collecting face information of the login user.
Preferably, the authentication module stores preset login information of a user allowed to login, and the specific processing procedure of the authentication module is as follows:
the method comprises the following steps: obtaining a user real-time account password coefficient M after a user inputs an account and a passwordFruit of Chinese wolfberry；
Step two: extracting a prestored user prestored account password coefficient MPreparation of；
Step three: calculating the real-time account password coefficient MFruit of Chinese wolfberryAnd a prestored account password coefficient MPreparation ofThe difference value between the account number and the password coefficient difference M is obtainedDifference (D)When the account number password coefficient difference MDifference (D)The verification is passed, and when the input account password is completely consistent with the pre-stored account password, the face verification is carried out;
step four: extracting the acquired real-time face image information and acquiring a real-time face coefficient PFruit of Chinese wolfberry；
Step five: then extracting the pre-stored face coefficient PPreparation ofReal-time face coefficient PFruit of Chinese wolfberryWith prestored face coefficients PPreparation ofThe difference between them is used to obtain the face coefficient difference PDifference (D)When the face coefficient difference PDifference (D)When the verification result is smaller than the preset value, the verification is passed;
step six: when the account number password coefficient passes the verification and the face image verification is carried out, alarm information is generated when the face image verification does not pass more than the preset times continuously.
Preferably, the specific processing procedure of the account password coefficient is as follows:
s1: recording the account input duration of the user to obtain an account input duration M1;
s2: time length information M2 when the user input password is recorded;
s3: by the formula (M1+ M2)/(M1-M1) ═ MFruit of Chinese wolfberryObtaining the real-time account password coefficient MFruit of Chinese wolfberry。
Preferably, the specific processing procedure of the face coefficient is as follows:
SS 1: extracting user face image information acquired in real time, wherein the face image information is a real-time face picture;
SS 2: marking two mouth corners in the face in the real-time face picture as a point A1 and a point A2, and marking a nose tip point as a point A3;
SS 3: connecting a point A1 and a point A2 to obtain a line segment L1, and respectively connecting a point A1 and a point A2 with a point A3 to obtain a line segment L2 and a line segment L3;
SS 4: a point A3 is used as an end point to make a line segment L4 which is perpendicular to the line segment L1, and the lengths of the line segment L4 and the line segment L1 are measured;
SS 5: by the formula L1L 4/2PFruit of Chinese wolfberryObtaining the real-time face coefficient PFruit of Chinese wolfberry。
Preferably, the login module is also used for the user to directly use the face to perform identity authentication.
Preferably, the backup storage of the backup storage module specifically comprises the following processes:
SSS 1: the backup storage module automatically backs up the data assets to the hard disk at preset time intervals;
SSS 2: the backup storage module compares data with the storage cloud at preset time intervals, when the data in the backup storage module is completely the same as the data in the storage cloud, backup is not performed, and when the data in the backup storage module is deviated from the data in the storage cloud and the size of the data in the backup storage module is larger than that of the data in the storage cloud, cloud backup processing is performed.
Compared with the prior art, the invention has the following advantages: this electric wire netting data asset management system based on big data, the safety of assurance electric wire netting data asset that can be better, when the user carries out data asset and uploads and draws, verify user's identity, the effectual condition emergence of revealing of electric wire netting data asset that leads to other people falsely account number that has avoided user's account number password data to reveal the condition that leads to has realized better automatic backup of data, the effectual condition emergence of data disclosure that has avoided system's trouble to lead to.
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FIG. 1 is a system block diagram of the present invention.
Detailed Description
The following examples are given for the detailed implementation and specific operation of the present invention, but the scope of the present invention is not limited to the following examples.
As shown in fig. 1, the present embodiment provides a technical solution: a power grid data asset management system based on big data comprises a login module, an identity authentication module, a data right-lifting module, a data import module, a data receiving module, a master control module, an alarm sending module, a backup storage module, a storage cloud and a data extraction module;
the system comprises a login module, an identity authentication module, a data receiving module, a master control module and a backup storage module, wherein the login module is used for a user to log in the system to extract and import data assets, the identity authentication module is used for authenticating the identity of a person logged in the system through the login module, alarm information is generated when the person is not authenticated in the identity authentication module, the data extracting module is used for extracting the data assets of the authenticated user, the data importing module is used for importing data asset information into the system through the authenticated user, the data receiving module is used for receiving the data asset information imported through the data importing module, the master control module is used for generating a backup control instruction, and the backup control instruction is sent to the backup storage module;
the backup storage module backs up the data asset information received by the data receiving module to the hard disk, and backs up the data asset information to the storage cloud;
the master control module converts the alarm information into an alarm instruction and sends the alarm instruction to the alarm sending module, and the alarm sending module sends the alarm instruction to the instructed mobile terminal.
The login module comprises a login keyboard, a display screen and a face recognition camera, wherein the login keyboard is used for inputting account and password information by a user, the display screen is used for displaying prompting performance, and the face recognition camera is used for collecting face information of the login user.
The authentication module stores preset login information of a user allowed to login, and the specific processing process of the authentication module is as follows:
the method comprises the following steps: obtaining a user real-time account password coefficient M after a user inputs an account and a passwordFruit of Chinese wolfberry；
Step two: extracting a prestored user prestored account password coefficient MPreparation of；
Step three: calculating the real-time account password coefficient MFruit of Chinese wolfberryAnd a prestored account password coefficient MPreparation ofThe difference value between the account number and the password coefficient difference M is obtainedDifference (D)When the account number password coefficient difference MDifference (D)The verification is passed, and when the input account password is completely consistent with the pre-stored account password, the face verification is carried out;
step four: extracting the acquired real-time face image information and acquiring a real-time face coefficient PFruit of Chinese wolfberry；
Step five: then extracting the pre-stored face coefficient PPreparation ofReal-time face coefficient PFruit of Chinese wolfberryWith prestored face coefficients PPreparation ofThe difference between them is used to obtain the face coefficient difference PDifference (D)When the face coefficient difference PDifference (D)When the verification result is smaller than the preset value, the verification is passed;
step six: when the account number password coefficient passes the verification and the face image verification is carried out, alarm information is generated when the face image verification does not pass more than the preset times continuously.
The specific processing process of the account password coefficient is as follows:
s1: recording the account input duration of the user to obtain an account input duration M1;
s2: time length information M2 when the user input password is recorded;
s3: by the formula (M1+ M2)/(M1-M1) ═ MFruit of Chinese wolfberryObtaining the real-time account password coefficient MFruit of Chinese wolfberry。
Preferably, the specific processing procedure of the face coefficient is as follows:
SS 1: extracting user face image information acquired in real time, wherein the face image information is a real-time face picture;
SS 2: marking two mouth corners in the face in the real-time face picture as a point A1 and a point A2, and marking a nose tip point as a point A3;
SS 3: connecting a point A1 and a point A2 to obtain a line segment L1, and respectively connecting a point A1 and a point A2 with a point A3 to obtain a line segment L2 and a line segment L3;
SS 4: a point A3 is used as an end point to make a line segment L4 which is perpendicular to the line segment L1, and the lengths of the line segment L4 and the line segment L1 are measured;
SS 5: by the formula L1L 4/2PFruit of Chinese wolfberryObtaining the real-time face coefficient PFruit of Chinese wolfberry。
The login module is also used for the user to directly use the face to carry out identity authentication.
The backup storage process of the backup storage module is as follows:
SSS 1: the backup storage module automatically backs up the data assets to the hard disk at preset time intervals;
SSS 2: the backup storage module compares data with the storage cloud at preset time intervals, when the data in the backup storage module is completely the same as the data in the storage cloud, backup is not performed, and when the data in the backup storage module is deviated from the data in the storage cloud and the size of the data in the backup storage module is larger than that of the data in the storage cloud, cloud backup processing is performed.
In summary, when the invention is used, a login module user logs in the system to extract and import data assets, an identity verification module performs identity verification on personnel logged in the system through the login module, alarm information is generated when the verification fails in the identity verification module, a data extraction module performs data asset extraction on a user who passes the verification, a data import module imports data asset information into the system through a user who passes the verification, a data receiving module is used for receiving the data asset information imported through the data import module, a master control module generates a backup control instruction, the backup control instruction is sent to a backup storage module, the backup storage module backs up the data asset information received by the data receiving module to a hard disk for processing, meanwhile, the data asset information is backed up to a storage cloud, and the master control module converts the alarm information into an alarm instruction to be sent to an alarm sending module, and the alarm sending module sends the alarm instruction to the instructed mobile terminal.
Furthermore, the terms "first", "second" and "first" 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 (7)
1. A power grid data asset management system based on big data is characterized by comprising a login module, an identity verification module, a data right-lifting module, a data import module, a data receiving module, a master control module, an alarm sending module, a backup storage module, a storage cloud and a data extraction module;
the system comprises a login module, an identity authentication module, a data receiving module, a master control module and a backup storage module, wherein the login module is used for a user to log in the system to extract and import data assets, the identity authentication module is used for authenticating the identity of a person logged in the system through the login module, alarm information is generated when the person is not authenticated in the identity authentication module, the data extracting module is used for extracting the data assets of the authenticated user, the data importing module is used for importing data asset information into the system through the authenticated user, the data receiving module is used for receiving the data asset information imported through the data importing module, the master control module is used for generating a backup control instruction, and the backup control instruction is sent to the backup storage module;
the backup storage module backs up the data asset information received by the data receiving module to the hard disk, and backs up the data asset information to the storage cloud;
the master control module converts the alarm information into an alarm instruction and sends the alarm instruction to the alarm sending module, and the alarm sending module sends the alarm instruction to the instructed mobile terminal.
2. The big data-based power grid data asset management system according to claim 1, wherein: the login module comprises a login keyboard, a display screen and a face recognition camera, wherein the login keyboard is used for inputting account and password information by a user, the display screen is used for displaying prompting performance, and the face recognition camera is used for collecting face information of the login user.
3. The big data-based power grid data asset management system according to claim 2, wherein: the authentication module stores preset login information of a user allowed to login, and the specific processing process of the authentication module is as follows:
the method comprises the following steps: obtaining a user real-time account password coefficient M after a user inputs an account and a passwordFruit of Chinese wolfberry；
Step two: extracting a prestored user prestored account password coefficient MPreparation of；
Step three: calculating the real-time account password coefficient MFruit of Chinese wolfberryAnd a prestored account password coefficient MPreparation ofThe difference value between the account number and the password coefficient difference M is obtainedDifference (D)When the account number password coefficient difference MDifference (D)The verification is passed, and when the input account password is completely consistent with the pre-stored account password, the face verification is carried out;
step four: extracting the acquired real-time face image information and acquiring a real-time face coefficient PFruit of Chinese wolfberry；
Step five: then extracting the pre-stored face coefficient PPreparation ofReal-time face coefficient PFruit of Chinese wolfberryWith prestored face coefficients PPreparation ofThe difference between them is used to obtain the face coefficient difference PDifference (D)When the face coefficient difference PDifference (D)When the verification result is smaller than the preset value, the verification is passed;
step six: when the account number password coefficient passes the verification and the face image verification is carried out, alarm information is generated when the face image verification does not pass more than the preset times continuously.
4. The big data based power grid data asset management system according to claim 3, wherein: the specific processing process of the account password coefficient is as follows:
s1: recording the account input duration of the user to obtain an account input duration M1;
s2: time length information M2 when the user input password is recorded;
s3: by the formula (M1+ M2)/(M1-M1) ═ MFruit of Chinese wolfberryObtaining the real-time account password coefficient MFruit of Chinese wolfberry。
5. The big data based power grid data asset management system according to claim 3, wherein: the specific processing process of the face coefficient is as follows:
SS 1: extracting user face image information acquired in real time, wherein the face image information is a real-time face picture;
SS 2: marking two mouth corners in the face in the real-time face picture as a point A1 and a point A2, and marking a nose tip point as a point A3;
SS 3: connecting a point A1 and a point A2 to obtain a line segment L1, and respectively connecting a point A1 and a point A2 with a point A3 to obtain a line segment L2 and a line segment L3;
SS 4: a point A3 is used as an end point to make a line segment L4 which is perpendicular to the line segment L1, and the lengths of the line segment L4 and the line segment L1 are measured;
SS 5: by the formula L1L 4/2PFruit of Chinese wolfberryObtaining the real-time face coefficient PFruit of Chinese wolfberry。
6. The big data-based power grid data asset management system according to claim 1, wherein: the login module is also used for the user to directly use the face to carry out identity authentication.
7. The big data-based power grid data asset management system according to claim 1, wherein: the backup storage process of the backup storage module is as follows:
SSS 1: the backup storage module automatically backs up the data assets to the hard disk at preset time intervals;
SSS 2: the backup storage module compares data with the storage cloud at preset time intervals, when the data in the backup storage module is completely the same as the data in the storage cloud, backup is not performed, and when the data in the backup storage module is deviated from the data in the storage cloud and the size of the data in the backup storage module is larger than that of the data in the storage cloud, cloud backup processing is performed.
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