CN109406848A - A kind of electric power stealing detection warning system and method - Google Patents
A kind of electric power stealing detection warning system and method Download PDFInfo
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- CN109406848A CN109406848A CN201811230373.2A CN201811230373A CN109406848A CN 109406848 A CN109406848 A CN 109406848A CN 201811230373 A CN201811230373 A CN 201811230373A CN 109406848 A CN109406848 A CN 109406848A
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R11/00—Electromechanical arrangements for measuring time integral of electric power or current, e.g. of consumption
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Abstract
The present invention relates to a kind of electric power stealing detection warning system and methods, comprising: electric power stealing detection module, the electric power stealing detection module include data source unit, data acquisition unit, data storage cell and data processing unit；Database module: database module is to store waiting task；Wireless communication module: the waiting task stored in database module is sent to remote control center, remote control center sends waiting task information to the handheld terminal of maintenance personal；Handheld terminal: position is sent to remote control center in real time, remote control center is according to the geographical location of waiting task information, waiting task information is sent to handheld terminal nearest around, handheld terminal receives the waiting task information of remote control center, and carries out maintenance operation.
Description
Technical field
The invention belongs to the stealing detection technique fields of electric system, and in particular to a kind of electric power stealing detection warning system
And method.
Background technique
In the prior art, there are serious stealing power stealing phenomenons for power grid user；This is also always the class that electric system is difficult to resolve
Topic.
Tune connects zero firewire electricity filching means, and this stealing electricity method is in advance to connect the fire of electric energy meter end of incoming cables, zero curve tune, according to
The internal circuit configuration of electric energy meter, connecing the input of zero line side with output is shorted with joining piece, and therefore, stealing family using setting certainly
The zero curve electricity consumption of (or separately connecing), and electric energy meter leads to electricity because the current loop of not no opposite direction is by the current coil of electric energy meter
Table stalling.
This stealing electricity method must install back brake control switch indoors, make the zero curve by electric energy meter and set ground wire certainly
(or separately connecing zero curve) can freely control.But ground wire is set certainly can bring to the safety utilization of electric power of user and seriously threaten.
Electricity filching means off zero, this stealing electricity method in advance must by the zero curve of electric energy meter end of incoming cables disconnect and by its it is hidden.
With adjusting connection stealing similar, requires separately to connect or set ground wire certainly, and installation back brake switch indoors.
After disconnecting ammeter input zero curve, current coil still can be by electric current, and potential winding can lose voltage, at this moment,
The electricity consumption of stealing family, ammeter will not measure.
When stealing family think ammeter rotation metering when, can from ammeter zero line output end be reversely connected zero potential (separately connect zero curve or from
If ground wire), potential winding obtains voltage, ammeter rotation.Second, the series resistor on the conducting wire of reversal connection zero potential, with under-voltage method
It is similar, play the role of few quantity calculation.Such mode is also referred to as method off zero.
No matter which kind of stealing mode, all there is some potential safety problems to entire power supply system.This for the prior art not
Foot place.
Therefore, in view of the above-mentioned drawbacks in the prior art, provide and design a kind of electric power stealing detection warning system and method；
To solve drawbacks described above in the prior art, it is necessary.
Summary of the invention
It is an object of the present invention to design a kind of electric power stealing detection in view of the above-mentioned drawbacks of the prior art, providing
Warning system and method, to solve the above technical problems.
To achieve the above object, the present invention provides following technical scheme:
A kind of electric power stealing detection warning system characterized by comprising
Electric power stealing detection module, the electric power stealing detection module include data source unit, data acquisition unit, number
According to storage unit and data processing unit；
The data source unit include power grid basis account related data, power network topology graph data, files on each of customers with
Make a copy of electricity related data, switch account and automatic collection electricity exponent data, user and distribution transforming automatic data collection, switch is born
Lotus and switch state data；
The data acquisition unit carries out at data pick-up, data conversion and data cleansing the data of data source unit
Reason, the mass data needed daily is synchronized in distributed file system；
Data storage cell stores data using HDFS, the storage inquiry towards full categorical data, file data
It is stored on the storage medium of dispersion, consistent file access interface is externally provided, use the column storing data library HBase to arrange
Associated storage framework carries out data storage, the data file of structuring is mapped as a database table, and provide class SQL and look into
It askes, and query statement is converted into MapReduce；
Data processing unit analyzes building demand according to electric power stealing, and design data excavates business model, using common
Cluster, recurrence, classification and association analysis data mining algorithm, mining data potential value, analysis prediction electric power stealing rate rule；
According to sample data training optimization data mining model, runs, obtain needed for electric power stealing analysis parallel under big data environment
Implicit operation of power networks mode and result；Identify potential electric power stealing position；And it is arrived location information as processing task storage
Database module；
Database module: database module is to store waiting task；
Wireless communication module: being sent to remote control center for the waiting task stored in database module, long-range to control
Center processed sends waiting task information to the handheld terminal of maintenance personal；
Handheld terminal: sending position to remote control center in real time, and remote control center is believed according to waiting task
The geographical location of breath sends waiting task information to handheld terminal nearest around, and handheld terminal receives remote control center
Waiting task information, and carry out maintenance operation；
The wireless communication module is realized by following steps and is filtered:
S1: being directly based upon reception data, carries out matched filtering；
S2: data are received after bandpass filtering, carry out matching treatment；
S3: whitening processing directly is carried out to reception data；
S4: data are received after bandpass filtering, carry out whitening processing；
S5: data are received after bandpass filtering, carry out the filter design treatment under similar constraint.
Whitening processing mode is as follows in the step S3 and S4:
Wherein, receiving data is column vector r, and () T indicates that transposition, R are noise covariance matrix, and s -1, s+1 indicate hair
Deliver letters breath " -1 ", "+1 " waveform, d be when leading decision symbol；
In the step S5, similar constraint refers to control filter and emits at a distance from signal within the scope of some, from
And filter characteristic is constrained indirectly.The expression formula of similar constraint is denoted as:
||w-s||2≤ε
Wherein, w is filter response, and s is transmitting signal, and ε is the constraint upper limit, | | | | indicate two norms；
Under similarity constraint condition, indicated by the filter of optimization aim of signal-to-noise ratio are as follows:
s.t.||w||2=1, | | s | |2=1, | wTs|≥1-ε/2；
Optimal solution are as follows:
Wherein, ε wf is the similarity in the case of prewhitening filter, related with noise R covariance；And λ ε be certain equation only
One solution.
Preferably, the data pick-up in the data acquisition unit passes through the data pick-up between Sqoop carry out system,
Progress big data between relational database (RDBMS) and Hadoop is exchanged by Apache Sqoop, by relevant database
Data imported into the data storage component in Hadoop (such as HBase and Hive), data are extracted in Hadoop system
And it exports in relevant database；
Data conversion converts the business information of importing according to electric power stealing analysis data mining model；
Data cleansing converts dirty data to the data for meeting electric power stealing analysis model quality requirement.
Preferably, power grid basis account related data is provided by production management PMS system in the data source unit,
Power network topology graph data is provided by power grid GIS system, files on each of customers with make a copy of electricity related data and mentioned by SG186 marketing system
For switch account is provided with automatic collection electricity exponent data by Electric Energy Acquisition System, user and distribution transforming automatic data collection
It is provided by power information acquisition system, switch load and switch state data are provided by SCADA system.
A kind of electric power stealing detection alarming method for power, which comprises the following steps:
S1: electric power stealing detecting step, specifically includes the following steps:
Data source obtaining step obtains power grid basis account related data, power network topology graph data, files on each of customers and copies
Record electricity related data, switch account and automatic collection electricity exponent data, user and distribution transforming automatic data collection, switch load
And switch state data；
Data collection steps carry out data pick-up, data conversion and data cleaning treatment to the data of data source unit, will
The mass data needed daily is synchronized in distributed file system；
Data storing steps store data using HDFS, the storage inquiry towards full categorical data, file data
It is stored on the storage medium of dispersion, consistent file access interface is externally provided, use the column storing data library HBase to arrange
Associated storage framework carries out data storage, the data file of structuring is mapped as a database table, and provide class SQL and look into
It askes, and query statement is converted into MapReduce；
Data processing step analyzes building demand according to electric power stealing, and design data excavates business model, using common
Cluster, recurrence, classification and association analysis data mining algorithm, mining data potential value, analysis prediction electric power stealing rate rule；
According to sample data training optimization data mining model, runs, obtain needed for electric power stealing analysis parallel under big data environment
Implicit operation of power networks mode and result；Identify potential electric power stealing position；And it is arrived location information as processing task storage
Database module；
S2: database module stores waiting task information；
S3: the waiting task stored in database module is sent to remote control center by wireless communication module, remotely
Control centre sends waiting task information to the handheld terminal of maintenance personal；
S4: handheld terminal sends position to remote control center in real time, and remote control center is according to waiting task
The geographical location of information sends waiting task information to handheld terminal nearest around, and handheld terminal receives in long-range control
The waiting task information of the heart, and carry out maintenance operation；
In the step S3, wireless communication module is realized by following steps and is filtered:
S1: being directly based upon reception data, carries out matched filtering；
S2: data are received after bandpass filtering, carry out matching treatment；
S3: whitening processing directly is carried out to reception data；
S4: data are received after bandpass filtering, carry out whitening processing；
S5: data are received after bandpass filtering, carry out the filter design treatment under similar constraint.
Whitening processing mode is as follows in the step S3 and S4:
Wherein, receiving data is column vector r, and () T indicates that transposition, R are noise covariance matrix, and s -1, s+1 indicate hair
Deliver letters breath " -1 ", "+1 " waveform, d be when leading decision symbol；
In the step S5, similar constraint refers to control filter and emits at a distance from signal within the scope of some, from
And filter characteristic is constrained indirectly.The expression formula of similar constraint is denoted as:
||w-s||2≤ε
Wherein, w is filter response, and s is transmitting signal, and ε is the constraint upper limit, | | | | indicate two norms；
Under similarity constraint condition, indicated by the filter of optimization aim of signal-to-noise ratio are as follows:
s.t.||w||2=1, | | s | |2=1, | wTs|≥1-ε/2；
Optimal solution are as follows:
Wherein, ε wf is the similarity in the case of prewhitening filter, related with noise R covariance；And λ ε be certain equation only
One solution.
Preferably, in the step S1, data pick-up in the data acquisition unit by Sqoop carry out system it
Between data pick-up, by Apache Sqoop between relational database (RDBMS) and Hadoop carry out big data exchange, will
The data of relevant database are imported into the data storage component in Hadoop (such as HBase and Hive), data from
It extracts and is exported in relevant database in Hadoop system；
Data conversion converts the business information of importing according to electric power stealing analysis data mining model；
Data cleansing converts dirty data to the data for meeting electric power stealing analysis model quality requirement.
Preferably, in the data source unit, power grid basis account related data is by production management in the step S1
PMS system provides, and power network topology graph data provides by power grid GIS system, files on each of customers and make a copy of electricity related data by
SG186 marketing system provides, and switch account is provided with automatic collection electricity exponent data by Electric Energy Acquisition System, user and matches
Become automatic data collection to be provided by power information acquisition system, switch load and switch state data are provided by SCADA system.
The beneficial effects of the present invention are be acquired processing by the electric power stealing to route, and what be will test matches
Electric power stealing location information is stored as task, is then sent to handheld terminal in time, notify maintenance personal carry out and
When inquire；Improve the efficiency of electric power stealing processing.
In addition, design principle of the present invention is reliable, structure is simple, has very extensive application prospect.
It can be seen that compared with prior art, the present invention have substantive distinguishing features outstanding and it is significant ground it is progressive, implementation
Beneficial effect be also obvious.
Detailed description of the invention
Fig. 1 is a kind of functional block diagram of electric power stealing detection warning system provided by the invention.
Wherein, 1- electric power stealing detection module, 1.1- data source unit, 1.2- data acquisition unit, the storage of 1.3- data
Unit, 1.4- data processing unit, 2- database module, 3- wireless communication module, 4- remote control center, 5- handheld terminal.
Specific embodiment
The present invention will be described in detail with reference to the accompanying drawing and by specific embodiment, and following embodiment is to the present invention
Explanation, and the invention is not limited to following implementation.
Embodiment 1:
As shown in Figure 1, a kind of electric power stealing provided by the invention detects warning system, comprising:
Electric power stealing detection module 1, the electric power stealing detection module 1 include data source unit 1.1, data acquisition list
Member 1.2, data storage cell 1.3 and data processing unit 1.4；
The data source unit 1.1 includes power grid basis account related data, power network topology graph data, files on each of customers
With make a copy of electricity related data, switch account and automatic collection electricity exponent data, user and distribution transforming automatic data collection, switch
Load and switch state data；
The data acquisition unit 1.2 carries out data pick-up, data conversion and data cleansing to the data of data source unit
Processing, the mass data needed daily is synchronized in distributed file system；
Data storage cell 1.3 stores data using HDFS, the storage inquiry towards full categorical data, number of files
According on the storage medium for being stored in dispersion, externally provide consistent file access interface, use the column storing data library HBase with
Column associated storage framework carries out data storage, the data file of structuring is mapped as a database table, and provide class SQL and look into
It askes, and query statement is converted into MapReduce；
Data processing unit 1.4 analyzes building demand according to electric power stealing, and design data excavates business model, using common
Cluster, recurrence, classification and association analysis data mining algorithm, mining data potential value, analysis prediction electric power stealing rate rule
Rule；According to sample data training optimization data mining model, is run parallel under big data environment, obtain electric power stealing and analyze institute
Operation of power networks mode and result need to be implied；Identify potential electric power stealing position；And it is stored location information as processing task
To database module；
Database module 2: database module is to store waiting task；
Wireless communication module 3: the waiting task stored in database module is sent to remote control center 4, remotely
Control centre sends waiting task information to the handheld terminal of maintenance personal；
Handheld terminal 5: sending position to remote control center in real time, and remote control center is believed according to waiting task
The geographical location of breath sends waiting task information to handheld terminal nearest around, and handheld terminal receives remote control center
Waiting task information, and carry out maintenance operation；
The wireless communication module is realized by following steps and is filtered:
S1: being directly based upon reception data, carries out matched filtering；
S2: data are received after bandpass filtering, carry out matching treatment；
S3: whitening processing directly is carried out to reception data；
S4: data are received after bandpass filtering, carry out whitening processing；
S5: data are received after bandpass filtering, carry out the filter design treatment under similar constraint.
Whitening processing mode is as follows in the step S3 and S4:
Wherein, receiving data is column vector r, and () T indicates that transposition, R are noise covariance matrix, and s -1, s+1 indicate hair
Deliver letters breath " -1 ", "+1 " waveform, d be when leading decision symbol；
In the step S5, similar constraint refers to control filter and emits at a distance from signal within the scope of some, from
And filter characteristic is constrained indirectly.The expression formula of similar constraint is denoted as:
||w-s||2≤ε
Wherein, w is filter response, and s is transmitting signal, and ε is the constraint upper limit, | | | | indicate two norms；
Under similarity constraint condition, indicated by the filter of optimization aim of signal-to-noise ratio are as follows:
s.t.||w||2=1, | | s | |2=1, | wTs|≥1-ε/2；
Optimal solution are as follows:
Wherein, ε wf is the similarity in the case of prewhitening filter, related with noise R covariance；And λ ε be certain equation only
One solution.
In the present embodiment, the data pick-up in the data acquisition unit is taken out by the data between Sqoop carry out system
It takes, progress big data between relational database (RDBMS) and Hadoop is exchanged by Apache Sqoop, by relational data
The data in library are imported into the data storage component in Hadoop (such as HBase and Hive), and data are taken out in Hadoop system
It takes and exports in relevant database；
Data conversion converts the business information of importing according to electric power stealing analysis data mining model；
Data cleansing converts dirty data to the data for meeting electric power stealing analysis model quality requirement.
In the present embodiment, in the data source unit, power grid basis account related data is mentioned by production management PMS system
For, power network topology graph data is provided by power grid GIS system, files on each of customers and make a copy of electricity related data by SG186 market be
System provides, and switch account is provided with automatic collection electricity exponent data by Electric Energy Acquisition System, user and distribution transforming automatic collection
Data are provided by power information acquisition system, and switch load and switch state data are provided by SCADA system.
Embodiment 2:
The present embodiment provides a kind of electric power stealings to detect alarming method for power, which comprises the following steps:
S1: electric power stealing detecting step, specifically includes the following steps:
Data source obtaining step obtains power grid basis account related data, power network topology graph data, files on each of customers and copies
Record electricity related data, switch account and automatic collection electricity exponent data, user and distribution transforming automatic data collection, switch load
And switch state data；
Data collection steps carry out data pick-up, data conversion and data cleaning treatment to the data of data source unit, will
The mass data needed daily is synchronized in distributed file system；
Data storing steps store data using HDFS, the storage inquiry towards full categorical data, file data
It is stored on the storage medium of dispersion, consistent file access interface is externally provided, use the column storing data library HBase to arrange
Associated storage framework carries out data storage, the data file of structuring is mapped as a database table, and provide class SQL and look into
It askes, and query statement is converted into MapReduce；
Data processing step analyzes building demand according to electric power stealing, and design data excavates business model, using common
Cluster, recurrence, classification and association analysis data mining algorithm, mining data potential value, analysis prediction electric power stealing rate rule；
According to sample data training optimization data mining model, runs, obtain needed for electric power stealing analysis parallel under big data environment
Implicit operation of power networks mode and result；Identify potential electric power stealing position；And it is arrived location information as processing task storage
Database module；
S2: database module stores waiting task information；
S3: the waiting task stored in database module is sent to remote control center by wireless communication module, remotely
Control centre sends waiting task information to the handheld terminal of maintenance personal；
S4: handheld terminal sends position to remote control center in real time, and remote control center is according to waiting task
The geographical location of information sends waiting task information to handheld terminal nearest around, and handheld terminal receives in long-range control
The waiting task information of the heart, and carry out maintenance operation；
In the step S3, wireless communication module is realized by following steps and is filtered:
S1: being directly based upon reception data, carries out matched filtering；
S2: data are received after bandpass filtering, carry out matching treatment；
S3: whitening processing directly is carried out to reception data；
S4: data are received after bandpass filtering, carry out whitening processing；
S5: data are received after bandpass filtering, carry out the filter design treatment under similar constraint.
Whitening processing mode is as follows in the step S3 and S4:
Wherein, receiving data is column vector r, and () T indicates that transposition, R are noise covariance matrix, and s -1, s+1 indicate hair
Deliver letters breath " -1 ", "+1 " waveform, d be when leading decision symbol；
In the step S5, similar constraint refers to control filter and emits at a distance from signal within the scope of some, from
And filter characteristic is constrained indirectly.The expression formula of similar constraint is denoted as:
||w-s||2≤ε
Wherein, w is filter response, and s is transmitting signal, and ε is the constraint upper limit, | | | | indicate two norms；
Under similarity constraint condition, indicated by the filter of optimization aim of signal-to-noise ratio are as follows:
s.t. ||w||2=1, | | s | |2=1, | wTs|≥1-ε/2；
Optimal solution are as follows:
Wherein, ε wf is the similarity in the case of prewhitening filter, related with noise R covariance；And λ ε be certain equation only
One solution.
In the present embodiment, in the step S1, the data pick-up in the data acquisition unit carries out system by Sqoop
Between data pick-up, by Apache Sqoop between relational database (RDBMS) and Hadoop carry out big data exchange,
The data of relevant database are imported into the data storage component in Hadoop (such as HBase and Hive), data from
It extracts and is exported in relevant database in Hadoop system；
Data conversion converts the business information of importing according to electric power stealing analysis data mining model；
Data cleansing converts dirty data to the data for meeting electric power stealing analysis model quality requirement.
In the present embodiment, in the step S1, in the data source unit, power grid basis account related data is managed by production
PMS system is managed to provide, power network topology graph data provides by power grid GIS system, files on each of customers and make a copy of electricity related data by
SG186 marketing system provides, and switch account is provided with automatic collection electricity exponent data by Electric Energy Acquisition System, user and matches
Become automatic data collection to be provided by power information acquisition system, switch load and switch state data are provided by SCADA system.
Disclosed above is only the preferred embodiment of the present invention, but the present invention is not limited to this, any this field
What technical staff can think does not have creative variation, and without departing from the principles of the present invention made by several improvement and
Retouching, should all be within the scope of the present invention.
Claims (6)
1. a kind of electric power stealing detects warning system characterized by comprising
Electric power stealing detection module, the electric power stealing detection module include that data source unit, data acquisition unit, data are deposited
Storage unit and data processing unit；
The data source unit includes power grid basis account related data, power network topology graph data, files on each of customers and makes a copy of
Electricity related data, switch account and automatic collection electricity exponent data, user and distribution transforming automatic data collection, switch load and
Switch state data；
The data acquisition unit carries out data pick-up, data conversion and data cleaning treatment to the data of data source unit, will
The mass data needed daily is synchronized in distributed file system；
Data storage cell stores data using HDFS, the storage inquiry towards full categorical data, file data storage
On the storage medium of dispersion, consistent file access interface is externally provided, uses the column storing data library HBase to arrange correlation
Storage architecture carries out data storage, the data file of structuring is mapped as a database table, and provide class SQL query, and
Query statement is converted into MapReduce；
Data processing unit analyzes building demand according to electric power stealing, and design data excavates business model, using common cluster,
It returns, electric power stealing rate rule is predicted in classification and association analysis data mining algorithm, mining data potential value, analysis；According to
Sample data training optimization data mining model, runs parallel under big data environment, obtains implicit needed for electric power stealing analysis
Operation of power networks mode and result；Identify potential electric power stealing position；And it stores location information as processing task to data
Library module；
Database module: database module is to store waiting task；
Wireless communication module: being sent to remote control center for the waiting task stored in database module, in long-range control
The heart sends waiting task information to the handheld terminal of maintenance personal；
Handheld terminal: position is sent to remote control center in real time, remote control center is according to waiting task information
Geographical location sends waiting task information to nearest handheld terminal around, handheld terminal receive remote control center to
Mission bit stream is handled, and carries out maintenance operation；
The wireless communication module is realized by following steps and is filtered:
S1: being directly based upon reception data, carries out matched filtering；
S2: data are received after bandpass filtering, carry out matching treatment；
S3: whitening processing directly is carried out to reception data；
S4: data are received after bandpass filtering, carry out whitening processing；
S5: data are received after bandpass filtering, carry out the filter design treatment under similar constraint；
Whitening processing mode is as follows in the step S3 and S4:
Wherein, receiving data is column vector r, and () T indicates that transposition, R are noise covariance matrix, and s-1, s+1 indicate to send letter
The waveform of " -1 ", "+1 " is ceased, d is when leading decision symbol；
In the step S5, similar constraint refers to control filter and emits at a distance from signal within the scope of some, thus
Connect constraint filter characteristic；The expression formula of similar constraint is denoted as:
||w-s||2≤ε
Wherein, w is filter response, and s is transmitting signal, and ε is the constraint upper limit, | | | | indicate two norms；
Under similarity constraint condition, indicated by the filter of optimization aim of signal-to-noise ratio are as follows:
s.t||w||2=1, | | s | |2=1, | wTs|≥1-ε/2；
Optimal solution are as follows:
Wherein, ε wf is the similarity in the case of prewhitening filter, related with noise R covariance；And λ ε is the unique of certain equation
Solution.
2. a kind of electric power stealing according to claim 1 detects warning system, which is characterized in that the data acquisition unit
In data pick-up by the data pick-up between Sqoop carry out system, by Apache Sqoop to relational database with
Big data exchange is carried out between Hadoop, and the data of relevant database are imported into the data storage component in Hadoop,
Data are extracted and exported in relevant database in Hadoop system；
Data conversion converts the business information of importing according to electric power stealing analysis data mining model；
Data cleansing converts dirty data to the data for meeting electric power stealing analysis model quality requirement.
3. a kind of electric power stealing according to claim 2 detects warning system, which is characterized in that the data source unit
In, power grid basis account related data is provided by production management PMS system, and power network topology graph data is mentioned by power grid GIS system
For, files on each of customers with make a copy of electricity related data and provided by SG186 marketing system, switch account and automatic collection electricity index number
It is provided according to by Electric Energy Acquisition System, user and distribution transforming automatic data collection are provided by power information acquisition system, switch load
And switch state data are provided by SCADA system.
4. a kind of electric power stealing detects alarming method for power, which comprises the following steps:
S1: electric power stealing detecting step, specifically includes the following steps:
Data source obtaining step obtains power grid basis account related data, power network topology graph data, files on each of customers and makes a copy of electricity
Amount related data switchs account and automatic collection electricity exponent data, user and distribution transforming automatic data collection, switch load and opens
Off status data；
Data collection steps carry out data pick-up, data conversion and data cleaning treatment to the data of data source unit, will be daily
The mass data needed is synchronized in distributed file system；
Data storing steps store data using HDFS, the storage inquiry towards full categorical data, file data storage
On the storage medium of dispersion, consistent file access interface is externally provided, uses the column storing data library HBase to arrange correlation
Storage architecture carries out data storage, the data file of structuring is mapped as a database table, and provide class SQL query, and
Query statement is converted into MapReduce；
Data processing step analyzes building demand according to electric power stealing, and design data excavates business model, using common poly-
Class, recurrence, classification and association analysis data mining algorithm, mining data potential value, analysis prediction electric power stealing rate rule；Root
It according to sample data training optimization data mining model, runs, obtains hidden needed for electric power stealing analysis parallel under big data environment
Mode containing operation of power networks and result；Identify potential electric power stealing position；And it stores location information as processing task to number
According to library module；
S2: database module stores waiting task information；
S3: the waiting task stored in database module is sent to remote control center by wireless communication module, long-range to control
Center sends waiting task information to the handheld terminal of maintenance personal；
S4: handheld terminal sends position to remote control center in real time, and remote control center is according to waiting task information
Geographical location, send waiting task information to nearest handheld terminal around, handheld terminal receives remote control center
Waiting task information, and carry out maintenance operation；
In the step S3, wireless communication module is realized by following steps and is filtered:
S1: being directly based upon reception data, carries out matched filtering；
S2: data are received after bandpass filtering, carry out matching treatment；
S3: whitening processing directly is carried out to reception data；
S4: data are received after bandpass filtering, carry out whitening processing；
S5: data are received after bandpass filtering, carry out the filter design treatment under similar constraint；
Whitening processing mode is as follows in the step S3 and S4:
Wherein, receiving data is column vector r, and () T indicates that transposition, R are noise covariance matrix, and s-1, s+1 indicate to send letter
The waveform of " -1 ", "+1 " is ceased, d is when leading decision symbol；
In the step S5, similar constraint refers to control filter and emits at a distance from signal within the scope of some, thus
Connect constraint filter characteristic；The expression formula of similar constraint is denoted as:
||w-s||2≤ε
Wherein, w is filter response, and s is transmitting signal, and ε is the constraint upper limit, | | | | indicate two norms；
Under similarity constraint condition, indicated by the filter of optimization aim of signal-to-noise ratio are as follows:
s.t||w||2=1, | | s | |2=1, | wTs|≥1-ε/2；
Optimal solution are as follows:
Wherein, ε wf is the similarity in the case of prewhitening filter, related with noise R covariance；And λ ε is the unique of certain equation
Solution.
5. a kind of electric power stealing according to claim 4 detects alarming method for power, which is characterized in that in the step S1, institute
The data pick-up in data acquisition unit is stated by the data pick-up between Sqoop carry out system, passes through Apache Sqoop couple
Big data is carried out between relational database (RDBMS) and Hadoop to exchange, and the data of relevant database are imported into Hadoop
In data storage component (such as HBase and Hive) in, data are extracted in Hadoop system and export to relational data
In library；
Data conversion converts the business information of importing according to electric power stealing analysis data mining model；
Data cleansing converts dirty data to the data for meeting electric power stealing analysis model quality requirement.
6. a kind of electric power stealing according to claim 5 detects alarming method for power, which is characterized in that in the step S1, institute
It states in data source unit, power grid basis account related data is provided by production management PMS system, and power network topology graph data is by electricity
Net generalized information system provides, and files on each of customers and makes a copy of electricity related data and is provided by SG186 marketing system, switch account and adopt automatically
Current collection volume index data are provided by Electric Energy Acquisition System, and user and distribution transforming automatic data collection are mentioned by power information acquisition system
For switch load and switch state data are provided by SCADA system.
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