CN110703179A - Voltage and current metering exception handling method based on knowledge base - Google Patents
Voltage and current metering exception handling method based on knowledge base Download PDFInfo
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Abstract
The invention discloses a voltage and current metering exception handling method based on a knowledge base, and relates to a metering exception handling method. At present, on-site operation and maintenance personnel need to work by depending on personal knowledge level, and the requirement on the personnel is high and the efficiency is low. The invention comprises the following steps: performing remote master station analysis and exception handling on the voltage and current exception work order according to the knowledge base; when the error report, the contingency and the file data error are determined, the abnormal work orders are not processed, and other failed abnormal work orders try to be processed remotely; if the remote processing is successful and the unrecovered dispatch is sent to the field processing, the restored dispatch can be filed and finished; searching abnormal reasons, diagnosis methods and repair methods according to the knowledge base during field processing, and carrying out field processing according to corresponding methods; and the new exception handling method is added into the knowledge base. The technical scheme utilizes the knowledge base, improves the application level of the knowledge base, reduces the technical requirements on operation and maintenance personnel, improves the working efficiency and reduces the waste of human resources.
Description
Technical Field
The invention relates to a metering exception handling method, in particular to a voltage and current metering exception handling method based on a knowledge base.
Background
The collection operation and maintenance closed-loop management function is used as a module of the power consumption information collection master station system, in the operation and maintenance process, the method for processing the voltage and current measurement abnormity of the knowledge base mainly depends on the personal experience analysis and judgment of operation and maintenance personnel, and related experts analyze, evaluate and diagnose discrete fault events, and for the excavation of the knowledge base, the comprehensive coverage in the collection operation and maintenance knowledge base cannot be achieved, and the autonomous learning of the collection operation and maintenance measurement abnormity knowledge base is lacked. The operation and maintenance personnel on site need to rely on personal knowledge level to carry out operation and maintenance work, the requirement on the operation and maintenance personnel is high, the time for abnormal judgment is spent for a long time, the working efficiency is influenced, and the waste of human resources is caused.
Disclosure of Invention
The technical problem to be solved and the technical task to be solved by the invention are to perfect and improve the prior technical scheme and provide a voltage and current metering exception handling method based on a knowledge base, so as to achieve the aim. Therefore, the invention adopts the following technical scheme.
A voltage and current measurement exception handling method based on a knowledge base comprises the following steps:
1) acquiring abnormal information of voltage and current;
2) generating a voltage and current abnormity work order according to the voltage and current abnormity information;
3) performing remote master station analysis and exception handling on the voltage and current exception work order according to the knowledge base; analyzing recently reported abnormal equipment data according to the acquired master station file, the load data and the generated abnormal equipment work order; when false alarm, sporadic property and file data error are determined, the file can be archived without processing, and other failed abnormal work orders try to be remotely processed;
4) analyzing the result, and judging whether the abnormality is recovered; if the remote processing is successful and the unrecovered dispatch is sent to the field processing, the restored dispatch can be filed and finished;
5) dispatching, performing on-site exception handling, searching exception reasons, diagnosis methods and repair methods according to the knowledge base during on-site handling, and performing on-site handling according to corresponding methods;
6) after the field processing is finished, carrying out field feedback;
7) and checking and archiving the result, and supplementing the new exception handling method into a knowledge base.
The technical scheme uniformly puts abnormal reasons, diagnosis methods and processing methods for arranging and maintaining knowledge contents into the knowledge base, realizes the learning of the knowledge base, automatically applies the collected knowledge to the operation and maintenance collection work, and improves the application level of the knowledge base. The technical requirements on operation and maintenance personnel are reduced, the working efficiency is improved, and the waste of human resources is reduced.
As a preferable technical means: when remote exception handling is carried out in the step 3) and field exception handling is carried out in the step 5), exception handling is carried out based on the knowledge base, and the following modes are adopted:
A) carrying out optimal sorting on the abnormal phenomena in a knowledge base according to the weight;
A1) automatically diagnosing the abnormality;
A2) carrying out manual diagnosis on the abnormity which cannot be automatically diagnosed or needs to be diagnosed on site;
A3) if the diagnosis still cannot be carried out, the diagnosis means can be manually added and put in storage as new knowledge;
B) according to the diagnosis result, carrying out exception processing on the unfavorable diagnosis result;
B1) finding out the corresponding diagnosis result in the knowledge base, and automatically processing the diagnosis result which can be automatically processed;
B2) manual field treatment is carried out on the parts which cannot be automatically treated or need to be treated on site;
B3) if the problem still can not be solved, processing means can be added and the information can be put in storage as new knowledge;
C) when the abnormity is recovered, the knowledge is put into a warehouse;
C1) if new knowledge is generated in the exception handling, the knowledge of the knowledge base is supplemented in a newly added mode and used for next exception handling;
C2) if no new knowledge is generated, the solution for which the original knowledge successfully solves the problem is weighted for the next preference.
As a preferable technical means: when the remote diagnosis processing is carried out in the step 3), the method comprises the following substeps:
301) calling whether the data of the electric meter is abnormal or not, and if so, entering step 306); if not, go to step 302);
302) judging whether the voltage change at the same point is related to the current, if so, entering step 306); if not, go to step 303);
303) judging whether the voltage-loss phase current is gradually reduced, if so, entering step 306); if not, go to step 304);
304) judging whether the voltage of the voltage-loss phase is obviously reduced compared with the normal voltage, if so, entering step 306); if not, go to step 305);
305) judging whether the corresponding phase voltage of the calling terminal is abnormal or not, and if so, entering step 306); if not, go to step 310);
306) initiating a special inspection process and making remark basic judgment;
307) judging whether the load data is completely cleared; if yes, go to step 309); if not, go to step 308);
308) issuing a measuring point parameter re-throwing task; then step 309) is entered;
309) remotely diagnosing a recovery condition; if the remote processing is successful and the unrecovered dispatch is sent to the field processing, the restored dispatch can be filed and finished;
310) initiating a field processing flow; when the field processing is completed, field feedback is performed and step 309) is entered.
As a preferable technical means: in step 301), the load data of the electric meter is called, if the load data is abnormal, whether the load data is cleared or not is checked, if the load data is abnormal, whether the abnormality is recovered or not is further judged, and the unrecovered electric meter is dispatched to a site for processing; and issuing a measuring point parameter re-projection task without resetting the load data, restoring to be filed, dispatching the unrecovered load data to a field for processing, and restoring to be filed.
As a preferable technical means: in step 301), calling and testing self data and meter data of the terminal; comparing self data of the calling and testing terminal with meter data, if the terminal data is normal, primarily judging the terminal data to be a wiring problem or a meter problem, dispatching to a field for processing and checking, and if the terminal data is the wiring or meter problem, performing field adjustment; and archiving after processing and recovery.
As a preferable technical means: in step 302), checking the voltage and current changes at the same point when judging whether the voltage and current changes at the same point are related; if the voltage of the three phases changes current obviously along with the three-phase balance condition, the phase voltage with large current is reduced obviously, and the phase voltage with small current is increased obviously, the suspected neutral point drift is judged to cause the three-phase voltage difference, a special inspection process is initiated, and basic judgment is remarked; if the voltage is found to be normal sometimes and low sometimes, the voltage loop is judged to be in poor contact and unstable in voltage, and the voltage loss starting time and the recovery time can be called, or when the voltage is low and not recovered to be normal, the voltage is recovered to be normal and stable by carrying out measurement loop reconstruction after the field inspection.
As a preferable technical means: in step 303), checking for a loss of voltage phase change; if the voltage of the voltage loss phase is gradually reduced, the situation that a primary side fuse of the voltage transformer is fused, or a voltage sampling line of the current transformer is fused due to overheating or other voltage connectivity faults is judged.
As a preferable technical means: in step 304), looking for a no-voltage phase current change; if the current data of the voltage-loss phase is obviously reduced compared with the data before voltage loss, the fault of the primary side of the power supply is judged to be possible, the drop-out fuse wire is fused or the fault of low voltage of the high-voltage line is possible.
As a preferable technical means: the establishment of the knowledge base comprises the following steps:
firstly), analyzing voltage and current abnormity aiming at the electric energy meter under each terminal;
secondly), matching the abnormal conditions with a knowledge base, and listing all abnormal phenomena; the step is to determine the abnormal phenomena of the terminal and the electric energy meter;
thirdly) when the abnormal recovery and the knowledge are put in storage
If the abnormality is diagnosed as an adverse result by parameter verification due to parameter errors and the problem is solved by parameter reconfiguration, the parameter verification diagnosis is preferentially diagnosed when the same error occurs next time;
if the above diagnosis means can not effectively diagnose the cause of the abnormality, but solve the problem by adding a new diagnosis method and a new processing method, the knowledge base is added with the new diagnosis method and the new processing method so as to be used for the next time and the newly added knowledge base is returned.
As a preferable technical means: the knowledge base comprises an operator management module, a knowledge base retrieval module and a knowledge base application module
An operator management module: for defining system operating permissions for an operator, the permissions comprising: browsing knowledge, learning a knowledge base, inquiring authority, adding and modifying the authority of the knowledge base, submitting the authority, modifying the authority and finally auditing the authority;
a knowledge base management module: the system comprises a knowledge collection sub-module, a knowledge source management sub-module, a knowledge maintenance module and a knowledge auditing module; wherein:
a knowledge collection submodule: the method comprises the steps of knowledge numbering, knowledge title, keywords, release time, a publisher, whether to audit or not, detailed description and remarks of knowledge content;
knowledge source management submodule: the knowledge sources include: direct input and transfer of knowledge;
a knowledge maintenance submodule: modifying the title, the release time, the publisher, the remarks and the history of the knowledge; at the same time, the requirement can be deleted;
a knowledge auditing submodule: the operator with the auditing authority audits the knowledge; the knowledge can only take effect in the knowledge base after the knowledge passes the audit;
a knowledge base retrieval module: the system comprises a searching and browsing submodule, wherein the searching and browsing submodule is used for:
firstly, setting a rule:
(1) when the message sent by the user accords with the knowledge matching rule, the intelligent response automatically returns a corresponding answer;
(2) when the matching degree of the message sent by the user and the question sentence in the knowledge rule is not good enough, the recommendation information is returned in a menu form for the user to select independently; automatically matching knowledge rules after selection by a user;
problem intelligent matching:
(1) when the matching degree of the user consultation content after semantic analysis and the keywords or the knowledge names in the knowledge base is higher than 85%, returning an answer;
(2) when the matching degree of the user consultation content after semantic analysis and the keywords or the knowledge names in the knowledge base is less than 85%, intelligently responding to 1-5 pieces of similar information matched in the user-defined knowledge base for recommendation;
thirdly, fast searching: the quick matching can be respectively carried out according to the title, the keywords and the content, so that the workers can find out the answer quickly;
fourthly, self-defined search: an operator can customize a structured search mode according to needs;
a knowledge base application module: it is used for:
automatically calling a corresponding diagnosis algorithm or diagnosis logic according to the matched abnormal reason to perform automatic diagnosis;
(1) if the abnormal reason is determined, matching a corresponding repair scheme;
(2) if the abnormal phenomenon is determined not to be caused by the abnormal reason, directly skipping to match the next possible abnormal reason;
(3) if all remote abnormal reasons are traversed, the remote abnormal reasons are processed on site;
recording automatic processing log information;
thirdly, intelligently recommending the maximum possibility to the abnormal work order;
and fourthly, intelligently recommending fault reference opinions to the abnormal work orders, wherein the fault reference opinions comprise the fault rates of equipment of the same manufacturer and the same batch.
As a preferable technical means: the knowledge base stores abnormal types, abnormal reasons, diagnosis methods and modification methods, the corresponding relations among the abnormal types, the abnormal reasons, the diagnosis methods and the modification methods, and the corresponding weights are set for the abnormal reasons, the diagnosis methods and the modification methods; the list of voltage and current measurement anomalies of the initially set knowledge base is as follows:
has the advantages that:
the technical scheme adopts a knowledge base mode that an electrical information acquisition operation and maintenance closed-loop module is closely related, and in the processing process, closed loops of knowledge acquisition, analysis and application are completed. And adding new knowledge into a warehouse according to the principle of an effective method capable of solving the problems, and feeding the knowledge back to the field operation and maintenance personnel for analysis and diagnosis. The historical experience of metering abnormity is fully absorbed and analyzed, voltage and current abnormity analysis is carried out on each electric energy meter, the aim of simplifying the working process of a worker with the metering abnormity is fulfilled, a set of voltage and current type metering abnormity diagnosis method based on the acquisition operation and maintenance knowledge base is designed, the fault of the electric energy meter is diagnosed and analyzed by the most appropriate means, the operation and maintenance personnel on site can carry out operation and maintenance work without depending on personal knowledge level, a set of effective operation and maintenance system is formed, the working efficiency is improved, and the waste of human resources is reduced.
According to the technical scheme, a voltage and current metering abnormity remote diagnosis process is constructed by combining a big data technology, the operation state of the metering equipment is diagnosed and analyzed by collecting and processing the electric energy meter data of the main collection station and carrying out technical means such as data comparison, statistical analysis and data mining in the main collection system station, whether the metering equipment is in a normal operation state is judged, and an auxiliary decision making function is realized. The implementation process comprises the following steps: the method comprises the steps of acquiring electric energy meter metering data information of an electric energy meter of a collection master station and electric energy meters of collection terminals, such as equipment operation conditions, voltage curve data, current curve data and the like. And (3) checking the master station file and load data based on voltage and current metering abnormity remote diagnosis and analysis, and analyzing and judging the voltage and current abnormity phenomenon by combining voltage, current and electric quantity changes. The analysis results of the voltage, the current, the electric quantity and the load data can find the abnormalities of voltage phase failure, voltage out-of-limit, current loss, current imbalance, voltage imbalance and the like, and the abnormal historical data analysis can carry out parameter adjustment, or the field equipment can be analyzed and adjusted by combining the operation condition of the field equipment. And performing field adjustment aiming at the abnormality of the field operation equipment, and performing field processing feedback through dispatching to a field process. The method greatly improves the steps of the abnormal handling field and finds the source of the problem in a targeted manner, thereby better improving the field operation and maintenance efficiency.
Drawings
FIG. 1 is a flow chart of the present invention.
FIG. 2 is a schematic diagram of the knowledge base structure of the present invention.
FIG. 3 is a diagram of the knowledge relationship of voltage-current measurement anomaly according to the present invention.
Detailed Description
The technical scheme of the invention is further explained in detail by combining the drawings in the specification.
As shown in fig. 1, the present invention comprises the steps of:
1) acquiring abnormal information of voltage and current;
2) generating a voltage and current abnormity work order according to the voltage and current abnormity information;
3) performing remote master station analysis and exception handling on the voltage and current exception work order according to the knowledge base; analyzing recently reported abnormal equipment data according to the acquired master station file, the load data and the generated abnormal equipment work order; when false alarm, sporadic property and file data error are determined, the file can be archived without processing, and other failed abnormal work orders try to be remotely processed;
3) the remote master station analyzes and checks the master station file and the load data; analyzing the reported abnormal equipment data in the near term according to the generated abnormal equipment work order; when false alarm, sporadic and file data error are determined, the remote diagnosis processing comprises the following contents:
301) calling whether the data of the electric meter is abnormal or not, and if so, entering step 306); if not, go to step 302);
302) judging whether the voltage change at the same point is related to the current, if so, entering step 306); if not, go to step 303);
303) judging whether the voltage-loss phase current is gradually reduced, if so, entering step 306); if not, go to step 304);
304) judging whether the voltage of the voltage-loss phase is obviously reduced compared with the normal voltage, if so, entering step 306); if not, go to step 305);
305) judging whether the corresponding phase voltage of the calling terminal is abnormal or not, and if so, entering step 306); if not, go to step 310);
306) initiating a special inspection process and making remark basic judgment;
307) judging whether the load data is completely cleared; if yes, go to step 309); if not, go to step 308);
308) issuing a measuring point parameter re-throwing task; then step 309) is entered;
309) remotely diagnosing a recovery condition; if the remote processing is successful and the unrecovered dispatch is sent to the field processing, the restored dispatch can be filed and finished;
310) initiating a field processing flow; after the field processing is finished, performing field feedback, and entering step 309);
4) analyzing the result, and judging whether the abnormality is recovered; if the remote processing is successful and the unrecovered dispatch is sent to the field processing, the restored dispatch can be filed and finished;
5) dispatching, performing on-site exception handling, searching exception reasons, diagnosis methods and repair methods according to the knowledge base during on-site handling, and performing on-site handling according to corresponding methods;
6) after the field processing is finished, carrying out field feedback;
7) and checking and archiving the result, and supplementing the new exception handling method into a knowledge base.
The technical scheme uniformly puts abnormal reasons, diagnosis methods and processing methods for arranging and maintaining knowledge contents into the knowledge base, realizes the learning of the knowledge base, automatically applies the collected knowledge to the operation and maintenance collection work, and improves the application level of the knowledge base. The technical requirements on operation and maintenance personnel are reduced, the working efficiency is improved, and the waste of human resources is reduced.
When remote exception handling is carried out in the step 3) and field exception handling is carried out in the step 5), exception handling is carried out based on the knowledge base, and the following modes are adopted:
A) carrying out optimal sorting on the abnormal phenomena in a knowledge base according to the weight;
A1) automatically diagnosing the abnormality;
A2) carrying out manual diagnosis on the abnormity which cannot be automatically diagnosed or needs to be diagnosed on site;
A3) if the diagnosis still cannot be carried out, the diagnosis means can be manually added and put in storage as new knowledge;
B) according to the diagnosis result, carrying out exception processing on the unfavorable diagnosis result;
B1) finding out the corresponding diagnosis result in the knowledge base, and automatically processing the diagnosis result which can be automatically processed;
B2) manual field treatment is carried out on the parts which cannot be automatically treated or need to be treated on site;
B3) if the problem still can not be solved, processing means can be added and the information can be put in storage as new knowledge;
C) when the abnormity is recovered, the knowledge is put into a warehouse;
C1) if new knowledge is generated in the exception handling, the knowledge of the knowledge base is supplemented in a newly added mode and used for next exception handling;
C2) if no new knowledge is generated, the solution for which the original knowledge successfully solves the problem is weighted for the next preference.
In step 301), the load data of the electric meter is called, if the load data is abnormal, whether the load data is cleared or not is checked, if the load data is abnormal, whether the abnormality is recovered or not is further judged, and the unrecovered electric meter is dispatched to a site for processing; the load data is not cleared, the measurement point parameter re-projection task is issued, the recovered measurement point parameter is transferred to be filed, the unrecovered measurement point parameter is dispatched to the field for processing, and the restored measurement point parameter re-projection task can be filed; calling and testing self data and meter data of the terminal; comparing self data of the calling and testing terminal with meter data, if the terminal data is normal, primarily judging the terminal data to be a wiring problem or a meter problem, dispatching to a field for processing and checking, and if the terminal data is the wiring or meter problem, performing field adjustment; and archiving after processing and recovery.
In step 302), checking the voltage and current changes at the same point when judging whether the voltage and current changes at the same point are related; if the voltage of the three phases changes current obviously along with the three-phase balance condition, the phase voltage with large current is reduced obviously, and the phase voltage with small current is increased obviously, the suspected neutral point drift is judged to cause the three-phase voltage difference, a special inspection process is initiated, and basic judgment is remarked; if the voltage is found to be normal sometimes and low sometimes, the voltage loop is judged to be in poor contact and unstable in voltage, and the voltage loss starting time and the recovery time can be called, or when the voltage is low and not recovered to be normal, the voltage is recovered to be normal and stable by carrying out measurement loop reconstruction after the field inspection.
In step 303), checking for a loss of voltage phase change; if the voltage of the voltage loss phase is gradually reduced, the situation that a primary side fuse of the voltage transformer is fused, or a voltage sampling line of the current transformer is fused due to overheating or other voltage connectivity faults is judged.
In step 304), looking for a no-voltage phase current change; if the current data of the voltage-loss phase is obviously reduced compared with the data before voltage loss, the fault of the primary side of the power supply is judged to be possible, the drop-out fuse wire is fused or the fault of low voltage of the high-voltage line is possible.
As shown in fig. 2, in order to realize safe, convenient and efficient use; the knowledge base comprises an operator management module, a knowledge base retrieval module and a knowledge base application module; wherein:
an operator management module: for defining system operating permissions for an operator, the permissions comprising: browsing knowledge, learning a knowledge base, inquiring authority, adding and modifying the authority of the knowledge base, submitting the authority, modifying the authority and finally auditing the authority;
a knowledge base management module: the system comprises a knowledge collection sub-module, a knowledge source management sub-module, a knowledge maintenance module and a knowledge auditing module; wherein:
a knowledge collection submodule: the method comprises the steps of knowledge numbering, knowledge title, keywords, release time, a publisher, whether to audit or not, detailed description and remarks of knowledge content;
knowledge source management submodule: the knowledge sources include: direct input and transfer of knowledge;
a knowledge maintenance submodule: modifying the title, the release time, the publisher, the remarks and the history of the knowledge; at the same time, the requirement can be deleted;
a knowledge auditing submodule: the operator with the auditing authority audits the knowledge; the knowledge can only take effect in the knowledge base after the knowledge passes the audit;
a knowledge base retrieval module: the system comprises a searching and browsing submodule, wherein the searching and browsing submodule is used for:
firstly, setting a rule:
(1) when the message sent by the user accords with the knowledge matching rule, the intelligent response automatically returns a corresponding answer;
(2) when the matching degree of the message sent by the user and the question sentence in the knowledge rule is not good enough, the recommendation information is returned in a menu form for the user to select independently; automatically matching knowledge rules after selection by a user;
problem intelligent matching:
(1) when the matching degree of the user consultation content after semantic analysis and the keywords or the knowledge names in the knowledge base is higher than 85%, returning an answer;
(2) when the matching degree of the user consultation content after semantic analysis and the keywords or the knowledge names in the knowledge base is less than 85%, intelligently responding to 1-5 pieces of similar information matched in the user-defined knowledge base for recommendation;
thirdly, fast searching: the quick matching can be respectively carried out according to the title, the keywords and the content, so that the workers can find out the answer quickly;
fourthly, self-defined search: an operator can customize a structured search mode according to needs;
a knowledge base application module: it is used for:
automatically calling a corresponding diagnosis algorithm or diagnosis logic according to the matched abnormal reason to perform automatic diagnosis;
(1) if the abnormal reason is determined, matching a corresponding repair scheme;
(2) if the abnormal phenomenon is determined not to be caused by the abnormal reason, directly skipping to match the next possible abnormal reason;
(3) if all remote abnormal reasons are traversed, the remote abnormal reasons are processed on site;
recording automatic processing log information;
thirdly, intelligently recommending the maximum possibility to the abnormal work order;
and fourthly, intelligently recommending fault reference opinions to the abnormal work orders, wherein the fault reference opinions comprise the fault rates of equipment of the same manufacturer and the same batch.
In order to meet the requirement of voltage and current measurement exception handling, the knowledge base stores exception types, exception reasons, diagnosis methods and modification methods, the corresponding relations of the exception types, the exception reasons, the diagnosis methods and the modification methods, and the corresponding weights are set for the exception reasons, the diagnosis methods and the modification methods; the list of voltage and current measurement anomalies of the initially set knowledge base is as follows:
the database of the technical scheme utilizes the historical experience of long-term operation of the acquisition system, adds knowledge to be put in storage according to the principle of an effective method capable of solving problems, and feeds the knowledge back to the analysis, diagnosis and processing processes of the abnormal operation and maintenance problems of the metering to complete the closed loop of knowledge acquisition, analysis and application, and as shown in fig. 3, the establishment of the knowledge base comprises the following steps:
1. analyzing voltage and current abnormity of the electric energy meter under each terminal;
2. matching the abnormal conditions with a knowledge base, and listing all abnormal phenomena;
establishing an abnormal list of the abnormal phenomena of the qualitative terminal and the electric energy meter;
3. when the abnormal recovery, the knowledge is put in storage
3.1 if the abnormality is diagnosed as an unfavorable result by parameter verification due to parameter errors and the problem is solved by parameter reconfiguration, the parameter verification diagnosis is preferentially diagnosed when the same error occurs next time;
3.2 the diagnosis means as above can not diagnose the cause of the abnormal condition effectively, but solve by adding new diagnosis method and new processing method, then the knowledge base will add new diagnosis method and new processing method for the next use, the added knowledge base will return the following list:
the method for processing voltage and current metering exception based on knowledge base shown in fig. 1-3 is a specific embodiment of the present invention, which already embodies the substantial features and advances of the present invention, and can make equivalent modifications in shape, structure, etc. according to the practical use requirements, and is within the scope of protection of the present solution.
Claims (10)
1. A voltage and current measurement exception handling method based on a knowledge base is characterized by comprising the following steps: the method comprises the following steps:
1) acquiring abnormal information of voltage and current;
2) generating a voltage and current abnormity work order according to the voltage and current abnormity information;
3) performing remote master station analysis and exception handling on the voltage and current exception work order according to the knowledge base; analyzing recently reported abnormal equipment data according to the acquired master station file, the load data and the generated abnormal equipment work order; when false alarm, sporadic property and file data error are determined, the file can be archived without processing, and other failed abnormal work orders try to be remotely processed;
4) analyzing the result, and judging whether the abnormality is recovered; if the remote processing is successful and the unrecovered dispatch is sent to the field processing, the restored dispatch can be filed and finished;
5) dispatching, performing on-site exception handling, searching exception reasons, diagnosis methods and repair methods according to the knowledge base during on-site handling, and performing on-site handling according to corresponding methods;
6) after the field processing is finished, carrying out field feedback;
7) and checking and archiving the result, and supplementing the new exception handling method into a knowledge base.
2. The voltage current type metering exception handling method based on the knowledge base according to claim 1, characterized in that: when remote exception handling is carried out in the step 3) and field exception handling is carried out in the step 5), exception handling is carried out based on the knowledge base, and the following modes are adopted:
A) carrying out optimal sorting on the abnormal phenomena in a knowledge base according to the weight;
A1) automatically diagnosing the abnormality;
A2) carrying out manual diagnosis on the abnormity which cannot be automatically diagnosed or needs to be diagnosed on site;
A3) if the diagnosis still cannot be carried out, the diagnosis means can be manually added and put in storage as new knowledge;
B) according to the diagnosis result, carrying out exception processing on the unfavorable diagnosis result;
B1) finding out the corresponding diagnosis result in the knowledge base, and automatically processing the diagnosis result which can be automatically processed;
B2) manual field treatment is carried out on the parts which cannot be automatically treated or need to be treated on site;
B3) if the problem still can not be solved, processing means can be added and the information can be put in storage as new knowledge;
C) when the abnormity is recovered, the knowledge is put into a warehouse;
C1) if new knowledge is generated in the exception handling, the knowledge of the knowledge base is supplemented in a newly added mode and used for next exception handling;
C2) if no new knowledge is generated, the solution for which the original knowledge successfully solves the problem is weighted for the next preference.
3. The voltage current type metering exception handling method based on the knowledge base according to claim 1, characterized in that: when the remote diagnosis processing is carried out in the step 3), the method comprises the following substeps:
301) calling whether the data of the electric meter is abnormal or not, and if so, entering step 306); if not, go to step 302);
302) judging whether the voltage change at the same point is related to the current, if so, entering step 306); if not, go to step 303);
303) judging whether the voltage-loss phase current is gradually reduced, if so, entering step 306); if not, go to step 304);
304) judging whether the voltage of the voltage-loss phase is obviously reduced compared with the normal voltage, if so, entering step 306); if not, go to step 305);
305) judging whether the corresponding phase voltage of the calling terminal is abnormal or not, and if so, entering step 306); if not, go to step 310);
306) initiating a special inspection process and making remark basic judgment;
307) judging whether the load data is completely cleared; if yes, go to step 309); if not, go to step 308);
308) issuing a measuring point parameter re-throwing task; then step 309) is entered;
309) remotely diagnosing a recovery condition; if the remote processing is successful and the unrecovered dispatch is sent to the field processing, the restored dispatch can be filed and finished;
310) initiating a field processing flow; when the field processing is completed, field feedback is performed and step 309) is entered.
4. The voltage current type metering exception handling method based on the knowledge base according to claim 3, characterized in that: in step 301), the load data of the electric meter is called, if the load data is abnormal, whether the load data is cleared or not is checked, if the load data is abnormal, whether the abnormality is recovered or not is further judged, and the unrecovered electric meter is dispatched to a site for processing; the load data is not cleared, the measurement point parameter re-projection task is issued, the recovered measurement point parameter is transferred to be filed, the unrecovered measurement point parameter is dispatched to the field for processing, and the restored measurement point parameter re-projection task can be filed; calling and testing self data and meter data of the terminal; comparing self data of the calling and testing terminal with meter data, if the terminal data is normal, primarily judging the terminal data to be a wiring problem or a meter problem, dispatching to a field for processing and checking, and if the terminal data is the wiring or meter problem, performing field adjustment; and archiving after processing and recovery.
5. The voltage current type metering exception handling method based on the knowledge base according to claim 3, characterized in that: in step 302), checking the voltage and current changes at the same point when judging whether the voltage and current changes at the same point are related; if the voltage of the three phases changes current obviously along with the three-phase balance condition, the phase voltage with large current is reduced obviously, and the phase voltage with small current is increased obviously, the suspected neutral point drift is judged to cause the three-phase voltage difference, a special inspection process is initiated, and basic judgment is remarked; if the voltage is found to be normal sometimes and low sometimes, the voltage loop is judged to be in poor contact and unstable in voltage, and the voltage loss starting time and the recovery time can be called, or when the voltage is low and not recovered to be normal, the voltage is recovered to be normal and stable by carrying out measurement loop reconstruction after the field inspection.
6. The voltage current type metering exception handling method based on the knowledge base according to claim 3, characterized in that: in step 303), checking for a loss of voltage phase change; if the voltage of the voltage loss phase is gradually reduced, the situation that a primary side fuse of the voltage transformer is fused, or a voltage sampling line of the current transformer is fused due to overheating or other voltage connectivity faults is judged.
7. The voltage current type metering exception handling method based on the knowledge base according to claim 3, characterized in that: in step 304), looking for a no-voltage phase current change; if the current data of the voltage-loss phase is obviously reduced compared with the data before voltage loss, the fault of the primary side of the power supply is judged to be possible, the drop-out fuse wire is fused or the fault of low voltage of the high-voltage line is possible.
8. The voltage current class metering exception handling method based on the knowledge base according to any one of claims 1 to 7, characterized in that: the establishment of the knowledge base comprises the following steps:
firstly), analyzing voltage and current abnormity aiming at the electric energy meter under each terminal;
secondly), matching the abnormal conditions with a knowledge base, and listing all abnormal phenomena; the step is to determine the abnormal phenomena of the terminal and the electric energy meter;
thirdly) when the abnormal recovery and the knowledge are put in storage
If the abnormality is diagnosed as an adverse result by parameter verification due to parameter errors and the problem is solved by parameter reconfiguration, the parameter verification diagnosis is preferentially diagnosed when the same error occurs next time;
if the above diagnosis means can not effectively diagnose the cause of the abnormality, but solve the problem by adding a new diagnosis method and a new processing method, the knowledge base is added with the new diagnosis method and the new processing method so as to be used for the next time and the newly added knowledge base is returned.
9. The voltage current type metering exception handling method based on the knowledge base according to claim 8, characterized in that: the knowledge base comprises an operator management module, a knowledge base retrieval module and a knowledge base application module
An operator management module: for defining system operating permissions for an operator, the permissions comprising: browsing knowledge, learning a knowledge base, inquiring authority, adding and modifying the authority of the knowledge base, submitting the authority, modifying the authority and finally auditing the authority;
a knowledge base management module: the system comprises a knowledge collection sub-module, a knowledge source management sub-module, a knowledge maintenance module and a knowledge auditing module; wherein:
a knowledge collection submodule: the method comprises the steps of knowledge numbering, knowledge title, keywords, release time, a publisher, whether to audit or not, detailed description and remarks of knowledge content;
knowledge source management submodule: the knowledge sources include: direct input and transfer of knowledge;
a knowledge maintenance submodule: modifying the title, the release time, the publisher, the remarks and the history of the knowledge; at the same time, the requirement can be deleted;
a knowledge auditing submodule: the operator with the auditing authority audits the knowledge; the knowledge can only take effect in the knowledge base after the knowledge passes the audit;
a knowledge base retrieval module: the system comprises a searching and browsing submodule, wherein the searching and browsing submodule is used for:
firstly, setting a rule:
(1) when the message sent by the user accords with the knowledge matching rule, the intelligent response automatically returns a corresponding answer;
(2) when the matching degree of the message sent by the user and the question sentence in the knowledge rule is not good enough, the recommendation information is returned in a menu form for the user to select independently; automatically matching knowledge rules after selection by a user;
problem intelligent matching:
(1) when the matching degree of the user consultation content after semantic analysis and the keywords or the knowledge names in the knowledge base is higher than 85%, returning an answer;
(2) when the matching degree of the user consultation content after semantic analysis and the keywords or the knowledge names in the knowledge base is less than 85%, intelligently responding to 1-5 pieces of similar information matched in the user-defined knowledge base for recommendation;
thirdly, fast searching: the quick matching can be respectively carried out according to the title, the keywords and the content, so that the workers can find out the answer quickly;
fourthly, self-defined search: an operator can customize a structured search mode according to needs;
a knowledge base application module: it is used for:
automatically calling a corresponding diagnosis algorithm or diagnosis logic according to the matched abnormal reason to perform automatic diagnosis;
(1) if the abnormal reason is determined, matching a corresponding repair scheme;
(2) if the abnormal phenomenon is determined not to be caused by the abnormal reason, directly skipping to match the next possible abnormal reason;
(3) if all remote abnormal reasons are traversed, the remote abnormal reasons are processed on site;
recording automatic processing log information;
thirdly, intelligently recommending the maximum possibility to the abnormal work order;
and fourthly, intelligently recommending fault reference opinions to the abnormal work orders, wherein the fault reference opinions comprise the fault rates of equipment of the same manufacturer and the same batch.
10. The voltage current class metering exception handling method based on the knowledge base according to claim 9, characterized in that: the knowledge base stores abnormal types, abnormal reasons, diagnosis methods and modification methods, the corresponding relations among the abnormal types, the abnormal reasons, the diagnosis methods and the modification methods, and the corresponding weights are set for the abnormal reasons, the diagnosis methods and the modification methods; the list of voltage and current measurement anomalies of the initially set knowledge base is as follows:
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