CN110737752A - electric power monitoring information identification method, device and system - Google Patents
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Abstract
The invention discloses a electric power monitoring information identification method, device and system, wherein the method comprises the steps of receiving a imported point table needing to be checked, wherein the point table comprises a plurality of pieces of monitoring information, filtering the monitoring information times by using a non-uploading information knowledge base in an expert knowledge integration base, filtering the monitoring information secondarily by using a fuzzy information knowledge base in the expert knowledge integration base, replacing keywords of the monitoring information after secondary filtering by using a similar information knowledge base in the expert knowledge integration base, and matching the replaced monitoring information with standard information in a standard information base to generate an identification result.
Description
Technical Field
The invention relates to the technical field of power system information, in particular to power monitoring information identification methods, devices and systems.
Background
With the rapid development of the regulation and control integration and the deepened application of unattended transformer substations, a power grid company puts higher requirements on the quality of monitoring information, the monitoring information and alarm setting of an access scheduling end are standardized, and new challenges are brought to the access of the monitoring information of the transformer substations.
At present, in the face of a large amount of monitoring information of a transformer substation, the conventional method mainly depends on a manual means, that is, a provided point table is checked manually, and then is compared with standard monitoring information of a standard information base by turns to find corresponding information, and naming and alarm setting are standardized, and the method has the following defects:
(1) transformer substations usually have thousands of information, so that the method is backward, a large amount of time and energy are consumed, the efficiency is low, the error rate is high, and omission is easy to occur by purely depending on a manual mode;
(2) the point list provided on site has no system , even if the monitoring information is the same as types of monitoring information, the information names of different manufacturers and different types of equipment have no system , namely, no fixed auditing standard exists during manual auditing, and the randomness of the auditing standard exists.
Disclosure of Invention
The invention provides power monitoring information identification methods, devices and systems, which aim to solve the defects of the prior art.
In order to achieve the above purpose, the present invention provides the following technical solutions:
, an embodiment of the present invention provides methods for identifying power monitoring information, including:
receiving an imported point table needing to be checked, wherein the point table comprises a plurality of pieces of monitoring information;
times of filtering is carried out on the monitoring information by utilizing a non-uploading information knowledge base in an expert knowledge integration base;
performing secondary filtering on the monitoring information by using a fuzzy information knowledge base in an expert knowledge integration base;
performing keyword replacement on the monitoring information after secondary filtering by using a similar information knowledge base in an expert knowledge integration base;
and matching the replaced monitoring information with standard information in a standard information base to generate an identification result.
, the power monitoring information identification method, wherein the step of filtering the monitoring information times by using the non-uploading information knowledge base in the expert knowledge integration base, comprises:
selecting a non-uploading information knowledge base from an expert knowledge integration base;
and respectively detecting whether each piece of monitoring information has a non-uploading keyword in the non-uploading information knowledge base or not, and carrying out times of filtering on the monitoring information with the non-uploading keyword.
, in the power monitoring information identification method, the step of performing secondary filtering on the monitoring information by using the fuzzy information knowledge base in the expert knowledge integration base includes:
selecting a fuzzy information knowledge base from an expert knowledge integration base;
and respectively detecting whether each piece of monitoring information has abnormal keywords in the fuzzy information knowledge base, and carrying out secondary filtering on the monitoring information without the abnormal keywords.
, in the power monitoring information identification method, the step of performing keyword replacement on the secondarily filtered monitoring information by using a similar information knowledge base in an expert knowledge integration base includes:
selecting a similar information knowledge base from an expert knowledge integration base;
and respectively detecting whether similar keywords associated with the standard keywords in the similar information knowledge base exist in each piece of monitoring information after secondary filtering, and replacing the similar keywords associated with the standard keywords.
Further , in the power monitoring information recognition method, the step of matching the replaced monitoring information with standard information in a standard information base to generate a recognition result includes:
matching the replaced monitoring information with standard information in a standard information base respectively;
and when the matching degree of the monitoring information and the standard information reaches a preset proportion, marking the monitoring information as being matched with the certain standard information, and generating an identification result.
, in the power monitoring information identification method, when the matching degree of the monitoring information and the standard information reaches a preset ratio, the step of marking the monitoring information as matching with the certain standard information and generating an identification result includes:
when the matching degree of certain monitoring information and certain standard information reaches a preset proportion, marking the certain monitoring information as being matched with the certain standard information, and generating an identification result;
when the matching degrees of certain two pieces of monitoring information and certain standard information reach a preset proportion, marking pieces of monitoring information with higher matching degrees as being matched with the certain standard information, and generating an identification result.
Further , the method for identifying power monitoring information further includes, after the step of filtering the monitoring information twice by using the fuzzy information knowledge base in the expert knowledge integration base:
and sorting the monitoring information after the secondary filtering, and generating a fuzzy information list for a regulator to check.
In a second aspect, an embodiment of the present invention provides kinds of power monitoring information identification devices, including:
the receiving module is used for receiving an imported point table needing to be checked, and the point table comprises a plurality of pieces of monitoring information;
the filtering module is used for times of filtering the monitoring information by utilizing the non-uploading information knowledge base in the expert knowledge integration base and for secondary filtering the monitoring information by utilizing the fuzzy information knowledge base in the expert knowledge integration base;
the replacing module is used for replacing the keywords of the monitoring information after the secondary filtering by utilizing a similar information knowledge base in the expert knowledge integration base;
and the matching module is used for matching the replaced monitoring information with standard information in a standard information base so as to generate an identification result.
In a third aspect, an embodiment of the present invention provides power monitoring information identification systems, including an expert knowledge integration base and a power monitoring information identification apparatus as described in the second aspect.
In the power monitoring information identification system, the expert knowledge integration base comprises a similar information knowledge base, a non-uploading information knowledge base and a fuzzy information knowledge base in step .
The electric power monitoring information identification method, the device and the system provided by the embodiment of the invention have great significance for standardization and normalization of the monitoring information after regulation and control are integrated, the limitation caused by manual auditing is eliminated, the workload of monitoring and acceptance of automation personnel is greatly reduced, and the normalization and the accuracy of scheduling monitoring information are ensured, so that the operation safety of equipment and a power grid is ensured, and the working efficiency of a regulation and control body is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and other drawings can be obtained by those skilled in the art without inventive exercise.
Fig. 1 is a schematic flowchart of power monitoring information identification methods according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of power monitoring information identification devices provided by the embodiment of the invention;
fig. 3 is a schematic diagram of an expert knowledge integration base provided by an embodiment of the present invention.
Detailed Description
The present invention will now be described in further detail with reference to the drawings and examples, it being understood that the specific embodiments herein described are merely illustrative of and not restrictive on the broad invention, and it should be further noted that for the purposes of description, only some, but not all, of the structures associated with the present invention are shown in the drawings.
Example
Referring to fig. 1, a flow chart of a power monitoring information identification method according to an embodiment of the present invention is shown, where the method specifically includes the following steps:
s101, receiving an imported point table needing to be checked, wherein the point table comprises a plurality of pieces of monitoring information;
it should be noted that, when a new substation or a new interval needs to be accessed to scheduling monitoring, a point table containing monitoring information is automatically established according to manufacturer data, and then the point table is imported into the system.
S102, times of filtering of the monitoring information is carried out by utilizing a non-uploading information knowledge base in an expert knowledge integration base;
specifically, the step S102 further includes:
selecting a non-uploading information knowledge base from an expert knowledge integration base;
and respectively detecting whether each piece of monitoring information has a non-uploading keyword in the non-uploading information knowledge base or not, and carrying out times of filtering on the monitoring information with the non-uploading keyword.
For example, when the key words include 'record start', when the point table has a '# 1 main transformer fault record start', the information is filtered because the key word of 'record start' appears.
S103, performing secondary filtration on the monitoring information by using a fuzzy information knowledge base in an expert knowledge integration base;
specifically, the step S103 further includes:
selecting a fuzzy information knowledge base from an expert knowledge integration base;
and respectively detecting whether each piece of monitoring information has abnormal keywords in the fuzzy information knowledge base, and carrying out secondary filtering on the monitoring information without the abnormal keywords.
It should be noted that the scheduling monitoring is mainly to monitor information such as accidents, anomalies, notifications, and the like, and the information contains abnormal keywords of information attributes, such as alarms, closing, disappearing, disconnection, loss of voltage, locking, and the like. For example, the information "220 kV × line switch SF6 low pressure" in the dot table, which means that is the alarm? Or closing and opening of the locking switch? The attribute of the information is not expressed, the information is considered to be fuzzy information, so the logic is that the information does not have abnormal keywords in a fuzzy information knowledge base, and the logic is considered to be fuzzy information and is filtered.
S104, performing keyword replacement on the monitoring information subjected to secondary filtering by using a similar information knowledge base in an expert knowledge integration base;
specifically, the step S104 further includes:
selecting a similar information knowledge base from an expert knowledge integration base;
and respectively detecting whether similar keywords associated with the standard keywords in the similar information knowledge base exist in each piece of monitoring information after secondary filtering, and replacing the similar keywords associated with the standard keywords.
It should be noted that, taking the standard information "110 kV × line × switch control loop disconnection" as an example, the point table information to be checked may be "110 kV × line × switch control loop disconnection", and the recognition rate of the information is improved by replacing the similar keyword "control loop disconnection" with the corresponding standard keyword "control loop disconnection". Taking a standard keyword '110 kV x line PT voltage loss' as an example, monitoring information in a point table to be audited may be several possibilities of similar keywords '110 kV x line TYD voltage loss', '110 kV x line voltage transformer voltage loss', '110 kV x line TV voltage loss', etc., and by replacing 'voltage transformer', 'TV' and 'TYD' with corresponding standard keyword 'PT', the recognition rate of the monitoring information is improved, and accurate recognition is realized.
And S105, matching the replaced monitoring information with standard information in a standard information base to generate a recognition result.
Specifically, the step S105 further includes:
matching the replaced monitoring information with standard information in a standard information base respectively;
and when the matching degree of the monitoring information and the standard information reaches a preset proportion, marking the monitoring information as being matched with the certain standard information, and generating an identification result.
It should be noted that the preset ratio may be set arbitrarily, for example, to 80%.
Preferably, when the matching degree between the monitoring information and the standard information reaches a preset ratio, the step of marking the monitoring information as matching with the certain standard information and generating the identification result further includes:
when the matching degree of certain monitoring information and certain standard information reaches a preset proportion, marking the certain monitoring information as being matched with the certain standard information, and generating an identification result;
when the matching degrees of certain two pieces of monitoring information and certain standard information reach a preset proportion, marking pieces of monitoring information with higher matching degrees as being matched with the certain standard information, and generating an identification result.
Preferably, after step S103, the method further includes:
and sorting the monitoring information after the secondary filtering, and generating a fuzzy information list for a regulator to check.
The electric power monitoring information identification methods provided by the embodiment of the invention have great significance for standardization and normalization of the monitoring information after regulation and control are integrated, the limitation caused by manual review is eliminated, the workload of monitoring and acceptance of automation personnel is greatly reduced, and the normalization and accuracy of the scheduling monitoring information are ensured, so that the operation safety of equipment and a power grid is ensured, and the working efficiency of a regulation and control body is improved.
Example two
Referring to fig. 2, the power monitoring information identification devices according to the second embodiment of the present invention include:
the receiving module 21 is configured to receive an imported point table that needs to be audited, where the point table includes a plurality of pieces of monitoring information;
the filtering module 22 is used for times of filtering the monitoring information by using the non-uploading information knowledge base in the expert knowledge integration base and for secondary filtering the monitoring information by using the fuzzy information knowledge base in the expert knowledge integration base;
a replacement module 23, configured to perform keyword replacement on the monitoring information after the secondary filtering by using a similar information knowledge base in an expert knowledge integration base;
and the matching module 24 is configured to match the replaced monitoring information with standard information in a standard information base to generate a recognition result.
The filtering module 22 is specifically configured to:
selecting a non-uploading information knowledge base from an expert knowledge integration base;
and respectively detecting whether each piece of monitoring information has a non-uploading keyword in the non-uploading information knowledge base or not, and carrying out times of filtering on the monitoring information with the non-uploading keyword.
The filtering module 22 is further specifically configured to:
selecting a fuzzy information knowledge base from an expert knowledge integration base;
and respectively detecting whether each piece of monitoring information has abnormal keywords in the fuzzy information knowledge base, and carrying out secondary filtering on the monitoring information without the abnormal keywords.
The replacement module 23 is specifically configured to:
selecting a similar information knowledge base from an expert knowledge integration base;
and respectively detecting whether similar keywords associated with the standard keywords in the similar information knowledge base exist in each piece of monitoring information after secondary filtering, and replacing the similar keywords associated with the standard keywords.
The matching module 24 is specifically configured to:
matching the replaced monitoring information with standard information in a standard information base respectively;
and when the matching degree of the monitoring information and the standard information reaches a preset proportion, marking the monitoring information as being matched with the certain standard information, and generating an identification result.
When the matching degree of the monitoring information and the standard information reaches a preset proportion, marking the monitoring information as being matched with the certain standard information, and generating an identification result, wherein the step of marking the monitoring information as being matched with the certain standard information comprises the following steps:
when the matching degree of certain monitoring information and certain standard information reaches a preset proportion, marking the certain monitoring information as being matched with the certain standard information, and generating an identification result;
when the matching degrees of certain two pieces of monitoring information and certain standard information reach a preset proportion, marking pieces of monitoring information with higher matching degrees as being matched with the certain standard information, and generating an identification result.
Preferably, the apparatus further comprises:
and the generating module is used for sorting the monitoring information after the secondary filtering and generating a fuzzy information list for a regulator to check.
The electric power monitoring information recognition devices provided by the embodiment of the invention have great significance for standardization and normalization of the monitoring information after regulation and control are integrated, limitations caused by manual auditing are eliminated, the workload of monitoring and acceptance of automation personnel is greatly reduced, and the normalization and accuracy of scheduling monitoring information are guaranteed, so that the operation safety of equipment and a power grid is guaranteed, and the working efficiency of a regulation and control body is improved.
EXAMPLE III
The third embodiment of the invention provides power monitoring information identification systems, which comprise an expert knowledge integration library and the power monitoring information identification device of the second embodiment.
The expert knowledge integration base is used for integrating expert experiences and providing support for identification of monitoring information and comprises a similar information knowledge base, an un-uploading information knowledge base and a fuzzy information knowledge base.
Referring to fig. 3, the corresponding knowledge base can be selected and expert knowledge can be added.
A similar information knowledge base: establishing an input function, establishing a similar information knowledge base, and providing input of similar keywords and standard keywords of the point table, such as: the input point table is similar to the keyword 'control loop disconnection', and the standard information is corresponding to the standard keyword to input 'control loop disconnection'.
Not uploading the information knowledge base: and an input function is established, a non-uploading information knowledge base is established, and information which is considered to be unnecessary to be uploaded in the expert audit can be input to form the knowledge base. The function inputs abnormal keywords, and the logic represented by the abnormal keywords is as follows: when the abnormal keyword appears in the monitoring information, the information is judged not to be sent. Such as: recording start, repressing start, regulating voltage, alarming the position of a knife switch, filtering oil, starting air cooling and the like, wherein the information is not required to be sent to a dispatching monitoring end for monitoring.
Fuzzy information knowledge base: and establishing an input function and establishing a fuzzy information knowledge base. The function inputs abnormal keywords and the logic represented is as follows: when the monitoring information does not have the abnormal keyword, the information judges fuzzy information.
And setting an extraction function for the 3 libraries, and setting the operations of modifying, deleting and storing the extracted expert knowledge base information. Thus, the expert knowledge base can be continuously perfected. The expert knowledge base is equivalent to the brain of a human, the more the stored knowledge is, the higher the content accuracy is, and the higher the accuracy is when the monitoring information is identified.
The electric power monitoring information identification systems provided by the embodiment of the invention have great significance for standardization and normalization of the monitoring information after regulation and control are integrated, the limitation caused by manual review is eliminated, the workload of monitoring and acceptance of automation personnel is greatly reduced, and the normalization and accuracy of the scheduling monitoring information are ensured, so that the operation safety of equipment and a power grid is ensured, and the working efficiency of a regulation and control body is improved.
The above embodiments are merely to illustrate the technical solutions of the present invention, and not to limit the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1, electric power monitoring information identification method, characterized by comprising:
receiving an imported point table needing to be checked, wherein the point table comprises a plurality of pieces of monitoring information;
times of filtering is carried out on the monitoring information by utilizing a non-uploading information knowledge base in an expert knowledge integration base;
performing secondary filtering on the monitoring information by using a fuzzy information knowledge base in an expert knowledge integration base;
performing keyword replacement on the monitoring information after secondary filtering by using a similar information knowledge base in an expert knowledge integration base;
and matching the replaced monitoring information with standard information in a standard information base to generate an identification result.
2. The method according to claim 1, wherein the step of filtering the monitoring information times by using a non-uploading information knowledge base in an expert knowledge integration base comprises:
selecting a non-uploading information knowledge base from an expert knowledge integration base;
and respectively detecting whether each piece of monitoring information has a non-uploading keyword in the non-uploading information knowledge base or not, and carrying out times of filtering on the monitoring information with the non-uploading keyword.
3. The power monitoring information identification method according to claim 1, wherein the step of secondarily filtering the monitoring information using a fuzzy information knowledge base in an expert knowledge integration base includes:
selecting a fuzzy information knowledge base from an expert knowledge integration base;
and respectively detecting whether each piece of monitoring information has abnormal keywords in the fuzzy information knowledge base, and carrying out secondary filtering on the monitoring information without the abnormal keywords.
4. The power monitoring information recognition method according to claim 1, wherein the step of performing keyword replacement on the secondarily filtered monitoring information by using a similar information knowledge base in an expert knowledge integration base comprises:
selecting a similar information knowledge base from an expert knowledge integration base;
and respectively detecting whether similar keywords associated with the standard keywords in the similar information knowledge base exist in each piece of monitoring information after secondary filtering, and replacing the similar keywords associated with the standard keywords.
5. The power monitoring information identification method according to claim 1, wherein the step of matching the replaced monitoring information with standard information in a standard information base to generate an identification result comprises:
matching the replaced monitoring information with standard information in a standard information base respectively;
and when the matching degree of the monitoring information and the standard information reaches a preset proportion, marking the monitoring information as being matched with the certain standard information, and generating an identification result.
6. The power monitoring information identification method according to claim 5, wherein the step of marking the monitoring information as being matched with the certain standard information and generating the identification result when the matching degree of the monitoring information and the standard information reaches a preset ratio comprises:
when the matching degree of certain monitoring information and certain standard information reaches a preset proportion, marking the certain monitoring information as being matched with the certain standard information, and generating an identification result;
when the matching degrees of certain two pieces of monitoring information and certain standard information reach a preset proportion, marking pieces of monitoring information with higher matching degrees as being matched with the certain standard information, and generating an identification result.
7. The power monitoring information identification method according to claim 1, further comprising, after the step of secondarily filtering the monitoring information using a fuzzy information knowledge base in an expert knowledge integration base:
and sorting the monitoring information after the secondary filtering, and generating a fuzzy information list for a regulator to check.
8, kinds of electric power monitoring information recognition device, characterized by comprising:
the receiving module is used for receiving an imported point table needing to be checked, and the point table comprises a plurality of pieces of monitoring information;
the filtering module is used for times of filtering the monitoring information by utilizing the non-uploading information knowledge base in the expert knowledge integration base and for secondary filtering the monitoring information by utilizing the fuzzy information knowledge base in the expert knowledge integration base;
the replacing module is used for replacing the keywords of the monitoring information after the secondary filtering by utilizing a similar information knowledge base in the expert knowledge integration base;
and the matching module is used for matching the replaced monitoring information with standard information in a standard information base so as to generate an identification result.
An power monitoring information recognition system of claim 9 or , comprising an expert knowledge integration library and the power monitoring information recognition apparatus of claim 8.
10. The power monitoring information identification system of claim 9, wherein the integrated expert knowledge base comprises a similar information knowledge base, a no-load information knowledge base, and a fuzzy information knowledge base.
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