CN103713275B - The inaccurate abnormal method of electric energy meter metering is judged based on Mining Multidimensional Association Rules - Google Patents
The inaccurate abnormal method of electric energy meter metering is judged based on Mining Multidimensional Association Rules Download PDFInfo
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- 230000002159 abnormal effect Effects 0.000 title claims abstract description 37
- 238000000034 method Methods 0.000 title claims abstract description 18
- 238000005065 mining Methods 0.000 title claims abstract description 16
- 230000005611 electricity Effects 0.000 claims abstract description 20
- 238000012544 monitoring process Methods 0.000 claims abstract description 18
- 230000008569 process Effects 0.000 claims abstract description 6
- 230000007547 defect Effects 0.000 claims description 8
- 230000008030 elimination Effects 0.000 claims description 7
- 238000003379 elimination reaction Methods 0.000 claims description 7
- 230000002596 correlated effect Effects 0.000 claims description 6
- 230000008878 coupling Effects 0.000 claims description 6
- 238000010168 coupling process Methods 0.000 claims description 6
- 238000005859 coupling reaction Methods 0.000 claims description 6
- 230000000977 initiatory effect Effects 0.000 claims description 6
- 230000009897 systematic effect Effects 0.000 claims description 6
- 230000008859 change Effects 0.000 claims description 4
- 238000004140 cleaning Methods 0.000 claims description 3
- 238000011156 evaluation Methods 0.000 claims description 3
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- 230000008439 repair process Effects 0.000 abstract description 2
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Abstract
The invention discloses a kind of based on Mining Multidimensional Association Rules judge electric energy meter metering inaccurate abnormal method, on-line monitoring and the intelligent diagnosis system of measuring apparatus and collecting device, judge the algorithm (getting rid of user's electricity filching behavior) of electric energy meter self-metering exception, the inaccurate fault of electric energy meter self-metering comprises electric energy meter and stops walking (containing being careful) and fly away two classes extremely, metering on-line monitoring system is by analyzing the on-the-spot all kinds of electricity consumption data of user, check archive information and the sales service flow process of user, in conjunction with the event that harvester generates, comprehensively analyzed by Apriori character Mining Multidimensional Association Rules, judge that electric energy meter stops walking (containing being careful) and fly away abnormal confidence level and support.Abnormal for judging whether electric energy meter exists metering, Utilities Electric Co. is the need of carrying out on-the-spot calibration or repair based on condition of component provides technological means and reference frame.
Description
Technical field
The present invention relates to power industry Power marketing and field of measuring techniques, particularly relate to a kind of based on Mining Multidimensional Association Rules judge electric energy meter metering inaccurate abnormal method.
Background technology
It is an important ingredient in metering on-line monitoring system that electric energy meter stops walking (containing being careful) and the metering fault that flies away, metering on-line monitoring system is that framework is in power information acquisition system, sales service system, data mining on the electric energy system of critical point and analytic system, what it made full use of that power information acquisition system and critical point electric energy system provide collection in worksite enriches data, the archives provided in conjunction with marketing system and Workflow messages, by to electric energy meter, the voltage of metering, current transformer and secondary circuit, electric energy metering cabinet (case), collecting devices etc. carry out on-line operation monitoring of working condition, comprehensive analysis and intelligent diagnostics, can be accurately, find exception and the fault of measuring apparatus and collecting device intuitively, and to fault or abnormal timely defect elimination, raising business is ageing, reduce operating loss, customer complaint risk, reduce the workload of the specialized department personnel such as metering and power utility check, meet the demand that the operating mode of Utilities Electric Co. to scene operation measuring apparatus carries out Real-Time Monitoring.
Summary of the invention
The object of the invention is exactly the defect in order to make up prior art, provides a kind of and judges the inaccurate abnormal method of electric energy meter metering based on Mining Multidimensional Association Rules.
The present invention is achieved by the following technical solutions:
Judge the inaccurate abnormal method of electric energy meter metering based on Mining Multidimensional Association Rules, comprise following content:
1, the inaccurate abnormal step of user's electric energy meter metering is specially become as follows:
(1) all kinds of electricity consumption data that user gathers are checked to cleaning mistake or abnormal data get rid of the sample point producing suddenly very large data due to harvester exception; Check that user's business in marketing system applies to install flow process, get rid of marketing system and walking to tear open table, changing the user of surface low journey; Check in User Profile information, whether the metering method of electric energy meter and rated voltage, the mode of connection be consistent, the problem of eliminating files on each of customers typing mistake;
(2) electric energy meter stops the judgement walking or be careful: metering on-line monitoring system is by analyzing current acquisition sample points on the same day, and whether arbitrary in statistics three-phase to be greater than counting of 0.05A mutually satisfied with 5 time points; Whether the electric energy meter registration increment △ Q simultaneously analyzing the same day is less than 0.1kWh; When above-mentioned two situations all meet, include this user in analytic target;
(3) electric energy meter flies away judgement: the theoretical power consumption Q=S*24*K of user, wherein S represents that user applies to install capacity, and K represents weights, and weights scope is (0,100], between, K value category of employment, electricity consumption classification, load character, importance condition at user set after carrying out Comprehensive Evaluation; Metering on-line monitoring system, by calculating user's one day actual power consumption, when the ratio I of actual power consumption and theoretical power consumption Q is greater than 1, includes this user in analytic target;
(4) formulate terminal within the cycle of checking meter, judge that electric energy meter stops walking or being careful and flying away the algorithm of event:
1) electric energy meter stops walking or being careful: check meter in the cycle for one, the initial value of copy reading electric energy meter, all end-of-period values and week the end of term current requirement, when the value difference of initial value and all end-of-period values is more than or equal to 0.01kWh, then think that electric energy meter is normal; When the value difference of initial value and all end-of-period values is zero, then whether the current requirement in computation period end is more than or equal to 0.01kWh with the charge value of cycle gained of checking meter, and in this way, is then judged as that electric energy meter stops walking or being careful;
2) electric energy meter flies away: check meter in the cycle for one, the initial value of copy reading electric energy meter, all end-of-period values and all end of term current requirements, the current requirement in computation period end and the charge value △ of cycle gained of checking meter, when initial value and all end-of-period values are all more than or equal to 10 △, be then judged as that electric energy meter flies away;
(5) on-line monitoring system is measured when analyzing special change user electric energy meter and stopping walking or being careful and flying away abnormal, according to Apriori character Mining Multidimensional Association Rules principle, stop walking or being careful and flying away by this user's electric energy meter of system statistics the abnormal number of times support that occurs within a period of time and terminal send electric energy meter stops walking to be careful, the confidence level of event of flying away frequency simultaneously, the support that the exception that coupling system is analyzed occurs and confidence level, draw the operation flow of whether initiating to carry out on-the-spot defect elimination or calibration, specific as follows:
If I={i
1, i
2, i
3... i
mthe set of item, and if the data D that task is correlated with is the set of db transaction, D={T
1, T
2, T
3... T
m, make
each affairs has an identifier TID, if A is an item collection, affairs T comprises A, and and if only if
correlation rule be shape as
implication, wherein
and rule is set up in affairs D has support S and degree of confidence C,
S=Support（A=>B）=P(AUB)
C=Confidence（A=>B）=P（B|A）
Wherein, A represents that systematic analysis user electric energy meter stops exception record of walking or be careful or fly away, and B represents terminal send electric energy meter to stop walking, flying away event;
The rule meeting minimum support threshold value and minimal confidence threshold is become strong rule; The set of item is called item collection, if item collection meets minimum support, then claims it to be frequent item set;
2, the inaccurate abnormal step of low-voltage customer electric energy meter metering is as follows:
It is a lot of less that power information kind analogy due to low-voltage customer collection specially becomes user, and the on-site data gathering device used also is had any different with the terminal specially becoming user, so analytical approach is with special to become user different.
(1) first analysis user object meter reading data checked and cleared up, getting rid of check meter failure or the abnormal user that checks meter;
(2) for low-voltage customer electric energy meter, 1,2,7,8,9, Dec, get I according to class of subscriber
maxcalculate the theoretical daily power consumption of user by 8 hours or 12 hours, 3,4,5,6,10, November, get 3*I according to class of subscriber
bthe theoretical daily power consumption of user is calculated by 8 hours, 12 hours:
Theoretical power consumption=K*220*Imax*24/1000 of single-phase user's day;
Three-phase general industry and commerce day theoretical power consumption:
If directly adopt table, then computing formula=K*220*Imax*24*3/1000;
If connect secondary circuit, then computing formula=K*220*CT*5*24*3/1000;
By theoretical for user power consumption and the same day actual electricity compare, if ratio K 1 is more than or equal to 1, be set to be seen;
(3) for user to be seen, in terminal, the electric energy meter of installation is then set to emphasis user electric energy meter, requires the voltage of terminal copy reading electric energy meter, electric current, and according to the actual power consumption of sample data measuring and calculating user gathered:
Single-phase user: △ I=K* (I
i-I
i-1)/2,
Directly adopt table: △ I=K*3* (I
i-I
i-1)/2,
Connect secondary circuit: △ I=K*3*CT* (I
i-I
i-1)/2
K is regulation coefficient;
(4) by the daily power consumption of estimation user average power measuring and calculating user, compare and measure daily power consumption and actual power consumption, when K value is greater than specific threshold value, generate the differential event of electricity;
(5) on-line monitoring system is measured when analyzing low-voltage customer electric energy meter and flying away abnormal, according to Apriori character Mining Multidimensional Association Rules principle, to be flown away by this user's electric energy meter of system statistics the confidence level of the abnormal number of times support that occurs within a period of time and the differential event of electricity frequency simultaneously, the support that the exception that coupling system is analyzed occurs and confidence level, draw the operation flow of whether initiating to carry out on-the-spot defect elimination or calibration, specific as follows:
If I={i
1, i
2, i
3... i
mthe set of item, and if the data D that task is correlated with is the set of db transaction, D={T
1, T
2, T
3... T
m, make
each affairs has an identifier TID, if A is an item collection, affairs T comprises A, and and if only if
correlation rule be shape as
implication, wherein
and rule is set up in affairs D has support S and degree of confidence C,
S=Support（A=>B）=P(AUB)
C=Confidence（A=>B）=P（B|A）
Wherein, A represents that systematic analysis user electric energy meter stops walking (containing being careful) or the exception record that flies away, and B represents the differential event of this user's electricity;
The rule meeting minimum support threshold value and minimal confidence threshold is become strong rule, and the set of item is called item collection, if item collection meets minimum support, then claims it to be frequent item set.
Advantage of the present invention is: the present invention is comprehensively analyzed by Apriori character Mining Multidimensional Association Rules, judge that electric energy meter stops walking (containing being careful) and fly away abnormal confidence level and support, abnormal for judging whether electric energy meter exists metering, Utilities Electric Co. is the need of carrying out on-the-spot calibration or repair based on condition of component provides technological means and reference frame.
Accompanying drawing explanation
Fig. 1 is that the present invention specially becomes user's electric energy meter and stops walking (containing being careful) or the process flow diagram that flies away.
Fig. 2 is that low-voltage customer electric energy meter of the present invention stops walking (containing being careful) or the process flow diagram that flies away.
Embodiment
As shown in Figure 1, 2, a kind of based on Mining Multidimensional Association Rules judge electric energy meter metering inaccurate abnormal method, comprise following content:
1, the inaccurate abnormal step of user's electric energy meter metering is specially become as follows:
(1) all kinds of electricity consumption data that user gathers are checked to cleaning mistake or abnormal data get rid of the sample point producing suddenly very large data due to harvester exception; Check that user's business in marketing system applies to install flow process, get rid of marketing system and walking to tear open table, changing the user of surface low journey; Check in User Profile information, whether the metering method of electric energy meter and rated voltage, the mode of connection be consistent, the problem of eliminating files on each of customers typing mistake;
(2) electric energy meter stops the judgement walking or be careful: metering on-line monitoring system is by analyzing current acquisition sample points on the same day, and whether arbitrary in statistics three-phase to be greater than counting of 0.05A mutually satisfied with 5 time points; Whether the electric energy meter registration increment △ Q simultaneously analyzing the same day is less than 0.1kWh; When above-mentioned two situations all meet, include this user in analytic target;
(3) electric energy meter flies away judgement: the theoretical power consumption Q=S*24*K of user, wherein S represents that user applies to install capacity, and K represents weights, and weights scope is (0,100], between, K value category of employment, electricity consumption classification, load character, importance condition at user set after carrying out Comprehensive Evaluation; Metering on-line monitoring system, by calculating user's one day actual power consumption, when the ratio I of actual power consumption and theoretical power consumption Q is greater than 1, includes this user in analytic target;
(4) formulate terminal within the cycle of checking meter, judge that electric energy meter stops walking or being careful and flying away the algorithm of event:
1) electric energy meter stops walking or being careful: check meter in the cycle for one, the initial value of copy reading electric energy meter, all end-of-period values and week the end of term current requirement, when the value difference of initial value and all end-of-period values is more than or equal to 0.01kWh, then think that electric energy meter is normal; When the value difference of initial value and all end-of-period values is zero, then whether the current requirement in computation period end is more than or equal to 0.01kWh with the charge value of cycle gained of checking meter, and in this way, is then judged as that electric energy meter stops walking or being careful;
2) electric energy meter flies away: check meter in the cycle for one, the initial value of copy reading electric energy meter, all end-of-period values and all end of term current requirements, the current requirement in computation period end and the charge value △ of cycle gained of checking meter, when initial value and all end-of-period values are all more than or equal to 10 △, be then judged as that electric energy meter flies away;
(5) on-line monitoring system is measured when analyzing special change user electric energy meter and stopping walking or being careful and flying away abnormal, according to Apriori character Mining Multidimensional Association Rules principle, stop walking or being careful and flying away by this user's electric energy meter of system statistics the abnormal number of times support that occurs within a period of time and terminal send electric energy meter stops walking to be careful, the confidence level of event of flying away frequency simultaneously, the support that the exception that coupling system is analyzed occurs and confidence level, draw the operation flow of whether initiating to carry out on-the-spot defect elimination or calibration, specific as follows:
If I={i
1, i
2, i
3... i
mthe set of item, and if the data D that task is correlated with is the set of db transaction, D={T
1, T
2, T
3... T
m, make
each affairs has an identifier TID, if A is an item collection, affairs T comprises A, and and if only if
correlation rule be shape as
implication, wherein
and rule is set up in affairs D has support S and degree of confidence C,
S=Support（A=>B）=P(AUB)
C=Confidence（A=>B）=P（B|A）
Wherein, A represents that systematic analysis user electric energy meter stops exception record of walking or be careful or fly away, and B represents terminal send electric energy meter to stop walking, flying away event;
The rule meeting minimum support threshold value and minimal confidence threshold is become strong rule; The set of item is called item collection, if item collection meets minimum support, then claims it to be frequent item set;
2, the inaccurate abnormal step of low-voltage customer electric energy meter metering is as follows:
It is a lot of less that power information kind analogy due to low-voltage customer collection specially becomes user, and the on-site data gathering device used also is had any different with the terminal specially becoming user, so analytical approach is with special to become user different.
(1) first analysis user object meter reading data checked and cleared up, getting rid of check meter failure or the abnormal user that checks meter;
(2) for low-voltage customer electric energy meter, 1,2,7,8,9, Dec, get I according to class of subscriber
maxcalculate the theoretical daily power consumption of user by 8 hours or 12 hours, 3,4,5,6,10, November, get 3*I according to class of subscriber
bthe theoretical daily power consumption of user is calculated by 8 hours, 12 hours:
Theoretical power consumption=K*220*Imax*24/1000 of single-phase user's day;
Three-phase general industry and commerce day theoretical power consumption:
If directly adopt table, then computing formula=K*220*Imax*24*3/1000;
If connect secondary circuit, then computing formula=K*220*CT*5*24*3/1000;
By theoretical for user power consumption and the same day actual electricity compare, if ratio K 1 is more than or equal to 1, be set to be seen;
(3) for user to be seen, in terminal, the electric energy meter of installation is then set to emphasis user electric energy meter, requires the voltage of terminal copy reading electric energy meter, electric current, and according to the actual power consumption of sample data measuring and calculating user gathered:
Single-phase user: △ I=K* (I
i-I
i-1)/2,
Directly adopt table: △ I=K*3* (I
i-I
i-1)/2,
Connect secondary circuit: △ I=K*3*CT* (I
i-I
i-1)/2
K is regulation coefficient;
(4) by the daily power consumption of estimation user average power measuring and calculating user, compare and measure daily power consumption and actual power consumption, when K value is greater than specific threshold value, generate the differential event of electricity;
(5) on-line monitoring system is measured when analyzing low-voltage customer electric energy meter and flying away abnormal, according to Apriori character Mining Multidimensional Association Rules principle, to be flown away by this user's electric energy meter of system statistics the confidence level of the abnormal number of times support that occurs within a period of time and the differential event of electricity frequency simultaneously, the support that the exception that coupling system is analyzed occurs and confidence level, draw the operation flow of whether initiating to carry out on-the-spot defect elimination or calibration, specific as follows:
If I={i
1, i
2, i
3... i
mthe set of item, and if the data D that task is correlated with is the set of db transaction, D={T
1, T
2, T
3... T
m, make
each affairs has an identifier TID, if A is an item collection, affairs T comprises A, and and if only if
correlation rule be shape as
implication, wherein
and rule is set up in affairs D has support S and degree of confidence C,
S=Support（A=>B）=P(AUB)
C=Confidence（A=>B）=P（B|A）
Wherein, A represents that systematic analysis user electric energy meter stops walking (containing being careful) or the exception record that flies away, and B represents the differential event of this user's electricity;
The rule meeting minimum support threshold value and minimal confidence threshold is become strong rule, and the set of item is called item collection, if item collection meets minimum support, then claims it to be frequent item set.
Claims (1)
1. judge the inaccurate abnormal method of electric energy meter metering based on Mining Multidimensional Association Rules, it is characterized in that: comprise following content:
A, the inaccurate abnormal step of special change user electric energy meter metering are as follows:
(1) all kinds of electricity consumption data that user gathers are checked to cleaning mistake or abnormal data get rid of the sample point producing suddenly very large data due to harvester exception; Check that user's business in marketing system applies to install flow process, get rid of marketing system and walking to tear open table, changing the user of surface low journey; Check in User Profile information, whether the metering method of electric energy meter and rated voltage, the mode of connection be consistent, the problem of eliminating files on each of customers typing mistake;
(2) electric energy meter stops the judgement walking or be careful: metering on-line monitoring system is by analyzing current acquisition sample points on the same day, and whether arbitrary in statistics three-phase to be greater than counting of 0.05A mutually satisfied with 5 time points; Whether the electric energy meter registration increment △ Q simultaneously analyzing the same day is less than 0.1kWh; When above-mentioned two situations all meet, include this user in analytic target;
(3) electric energy meter flies away judgement: the theoretical power consumption Q=S*24*K of user, wherein S represents that user applies to install capacity, and K represents weights, and weights scope is (0,100], between, K value category of employment, electricity consumption classification, load character, importance condition at user set after carrying out Comprehensive Evaluation; Metering on-line monitoring system, by calculating user's one day actual power consumption, when the ratio of actual power consumption and theoretical power consumption Q is greater than 1, includes this user in analytic target;
(4) formulate terminal within the cycle of checking meter, judge that electric energy meter stops walking or being careful and flying away the algorithm of event:
1) electric energy meter stops walking or being careful: check meter in the cycle for one, the initial value of copy reading electric energy meter, all end-of-period values and week the end of term current requirement, when the value difference of initial value and all end-of-period values is more than or equal to 0.01kWh, then think that electric energy meter is normal; When the value difference of initial value and all end-of-period values is zero, then whether the current requirement in computation period end is more than or equal to 0.01kWh with the charge value of cycle gained of checking meter, and in this way, is then judged as that electric energy meter stops walking or being careful;
2) electric energy meter flies away: check meter in the cycle for one, the initial value of copy reading electric energy meter, all end-of-period values and all end of term current requirements, the current requirement in computation period end and the charge value △ of cycle gained of checking meter, when initial value and all end-of-period values are all more than or equal to 10 △, be then judged as that electric energy meter flies away;
(5) on-line monitoring system is measured when analyzing special change user electric energy meter and stopping walking or being careful and flying away abnormal, according to Apriori character Mining Multidimensional Association Rules principle, stop walking or being careful and flying away by this user's electric energy meter of system statistics the abnormal number of times support that occurs within a period of time and terminal send electric energy meter stops walking to be careful, the confidence level of event of flying away frequency simultaneously, the support that the exception that coupling system is analyzed occurs and confidence level, draw the operation flow of whether initiating to carry out on-the-spot defect elimination or calibration, specific as follows:
If I={i
1, i
2, i
3... i
mthe set of item, and if the data D that task is correlated with is the set of db transaction, D={T
1, T
2, T
3... T
m, make
each affairs has an identifier TID, if A is an item collection, affairs T comprises A, and and if only if
, correlation rule be shape as
implication, wherein
,
and rule is set up in affairs D has support S and degree of confidence C,
S=Support（A=>B）=P(AUB)
C=Confidence（A=>B）=P（B|A）
Wherein, A represents that systematic analysis user electric energy meter stops exception record of walking or be careful or fly away, and B represents terminal send electric energy meter to stop walking, flying away event;
The rule meeting minimum support threshold value and minimal confidence threshold is called strong rule; The set of item is called item collection, if item collection meets minimum support, then claims it to be frequent item set;
The inaccurate abnormal step of b, low-voltage customer electric energy meter metering is as follows:
(1) first analysis user object meter reading data checked and cleared up, getting rid of check meter failure or the abnormal user that checks meter;
(2) for low-voltage customer electric energy meter, 1,2,7,8,9, Dec, get I according to class of subscriber
maxcalculate the theoretical daily power consumption of user by 8 hours or 12 hours, 3,4,5,6,10, November, get 3*I according to class of subscriber
bthe theoretical daily power consumption of user is calculated by 8 hours, 12 hours:
Theoretical power consumption=K*220*Imax*24/1000 of single-phase user's day;
Three-phase general industry and commerce day theoretical power consumption:
If directly adopt table, then computing formula=K*220*Imax*24*3/1000;
If connect secondary circuit, then computing formula=K*220*CT*5*24*3/1000;
By theoretical for user power consumption and the same day actual electricity compare, if ratio K 1 is more than or equal to 1, be set to be seen;
(3) for user to be seen, in terminal, the electric energy meter of installation is then set to emphasis user electric energy meter, requires the voltage of terminal copy reading electric energy meter, electric current, and according to the actual power consumption of sample data measuring and calculating user gathered:
Single-phase user: △ I=K* (I
i-I
i-1)/2,
Directly adopt table: △ I=K*3* (I
i-I
i-1)/2,
Connect secondary circuit: △ I=K*3*CT* (I
i-I
i-1)/2
K is regulation coefficient;
(4) by the daily power consumption of estimation user average power measuring and calculating user, compare and measure daily power consumption and actual power consumption, when K value is greater than specific threshold value, generate the differential event of electricity;
(5) on-line monitoring system is measured when analyzing low-voltage customer electric energy meter and flying away abnormal, according to Apriori character Mining Multidimensional Association Rules principle, to be flown away by this user's electric energy meter of system statistics the confidence level of the abnormal number of times support that occurs within a period of time and the differential event of electricity frequency simultaneously, the support that the exception that coupling system is analyzed occurs and confidence level, draw the operation flow of whether initiating to carry out on-the-spot defect elimination or calibration, specific as follows:
If I={i
1, i
2, i
3... i
mthe set of item, and if the data D that task is correlated with is the set of db transaction, D={T
1, T
2, T
3... T
m, make
each affairs has an identifier TID, if A is an item collection, affairs T comprises A, and and if only if
, correlation rule be shape as
implication, wherein
,
and rule is set up in affairs D has support S and degree of confidence C,
S=Support（A=>B）=P(AUB)
C=Confidence（A=>B）=P（B|A）
Wherein, A represents that systematic analysis user electric energy meter stops exception record of walking or be careful or fly away, and B represents the differential event of this user's electricity;
The rule meeting minimum support threshold value and minimal confidence threshold is called strong rule, and the set of item is called item collection, if item collection meets minimum support, then claims it to be frequent item set.
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