CN114416753B - Electricity stealing evidence data processing method and system based on space-time vector four-dimensional data - Google Patents
Electricity stealing evidence data processing method and system based on space-time vector four-dimensional data Download PDFInfo
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Abstract
The invention provides a method and a system for processing electricity stealing evidence data based on space-time vector four-dimensional data, belonging to the technical field of data processing, wherein a preset four-dimensional data model is utilized to decompose data to be processed into time data, spatial position data, quantized data and a data carrier; reconstructing time data, spatial position data, quantized data and a data carrier based on a D-S evidence theory according to a first dynamic event window, a second dynamic event window, a fourth dynamic event window and a fifth dynamic event window; adding a trusted timestamp signature to the reconstructed data to obtain final electricity stealing evidence key data; according to the invention, a space-time vector four-dimensional evidence chain processing mechanism is established, original data, field detection evidence and field image evidence are refined into four dimensions of time, position space, quantized data and data carriers, the relevance among the evidences (time, place and same equipment acquisition) is strengthened, and the authenticity, integrity and effectiveness of evidence data are improved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a method and a system for processing electricity stealing evidence data based on space-time vector four-dimensional data.
Background
The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
Electric energy is widely used in various fields of national economy and production and life of people as clean energy. Because the electric energy cost accounts for a large proportion of the cost of enterprises, illegal operators and individual private owners earn violence and steal national electric energy by means. The legal rights and interests of enterprises and individuals are seriously damaged by the electricity stealing behavior, the normal power supply and utilization order is disturbed, the development of the electric power industry is hindered, and the serious threat is brought to the safe power utilization.
At present, an electric power worker is generally adopted to investigate related parties and witnesses, and 5 measures such as making an investigation record, looking up and copying related data, collecting evidence of electricity stealing by means of video recording, photography and the like, sealing an electricity stealing device, applying for evidence security and the like are adopted to obtain the evidence.
The inventor finds that the above mode of obtaining evidence has the following defects:
(1) the evidence obtained by each measure is insufficient; in order to ensure comprehensive and sufficient evidence obtaining, various analysis data and field detection data are used as part of evidence in the prior art, but the traditional computer electronic material evidence obtaining technology cannot solve the problem of reliable solidification of electronic material evidence and has adverse effects on the proving ability of the electronic material evidence;
(2) the evidences obtained by various measures are insufficient in mutual relevance, and the obtained evidences cannot be effectively proved to be obtained by aiming at the same electricity stealing user.
Disclosure of Invention
In order to solve the defects of the prior art, the invention provides a method and a system for processing electricity stealing evidence data based on space-time vector four-dimensional data, a space-time vector four-dimensional evidence chain processing mechanism is established, original data, field detection evidence and field image evidence are refined into four dimensions of time, position space, quantized data and a data carrier, the relevance among the evidence (the time, the place and the same equipment are obtained) is strengthened, and the authenticity, the integrity and the effectiveness of the evidence data are improved.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides a method for processing electricity stealing evidence data based on space-time vector four-dimensional data.
A method for processing electricity stealing evidence data based on space-time vector four-dimensional data comprises the following steps:
acquiring power utilization data, field detection data and field image data of user power utilization;
generating a first dynamic event window according to the change of the electricity utilization data before and after electricity stealing; generating a second dynamic event window according to field detection data in the electricity stealing process; generating a third dynamic event window according to the field image data in the electricity stealing process; generating a fourth dynamic event window according to the change of the power utilization data in and after the power stealing recovery; generating a fifth dynamic event window according to the change of the user electricity consumption data before electricity stealing occurs and after electricity stealing recovery;
the method comprises the steps that a first dynamic event window, a second dynamic event window, a third dynamic event window, a fourth dynamic event window and a fifth dynamic event window form data to be processed, and the data to be processed are decomposed into time data, spatial position data, quantitative data and a data carrier by utilizing a preset four-dimensional data model;
reconstructing time data, spatial position data, quantized data and a data carrier based on a D-S evidence theory according to a first dynamic event window, a second dynamic event window, a fourth dynamic event window and a fifth dynamic event window;
and adding a trusted timestamp signature to the reconstructed data to obtain final key data of the electricity stealing evidence.
Furthermore, the electricity consumption data comprises electric quantity data, voltage data, current data and power data.
Further, reconstructing the time data, the spatial position data, the quantization data and the data carrier based on the D-S evidence theory, comprising:
the product of the confidence level of the quantized data evidence and the fusion degree of the quantized data evidence is greater than zero, and the larger the product is, the higher the priority of the quantized data is.
Further, quantifying data evidence confidence, comprising:
when the variation of the electric quantity data, the current data, the voltage data and the power data of the user in the first event window and the fourth event window is larger than a first preset value and the duration is larger than a second preset value, judging that the reliability of the quantized data evidence is 1, otherwise, judging that the reliability of the quantized data evidence is 0;
recovering the electric quantity data, the current data, the voltage data and the power data in the fifth event window, judging that the evidence reliability of the quantized data is 1 if no obvious change exists in the preset time, and otherwise, judging that the evidence reliability of the quantized data is 0;
in the second event window, when a suspected electricity stealing point is detected on site, the reliability of the quantized data evidence is judged to be 1, otherwise, the reliability of the quantized data evidence is judged to be 0.
Furthermore, if the quantized data evidence occurs and other three types of evidence simultaneously occur, determining that the quantized data evidence fusion degree is a first value;
if the quantized data evidence occurs and two types of evidence simultaneously occur, judging that the quantized data evidence fusion degree is a second numerical value;
if the quantized data evidence occurs and simultaneously accompanies a type of evidence to occur simultaneously, judging that the quantized data evidence fusion degree is a third numerical value;
if the quantized data evidence occurs and no accompanying evidence occurs simultaneously, judging that the quantized data evidence fusion degree is a fourth numerical value;
the first, second, third and fourth values decrease in sequence.
The invention provides a power stealing evidence data processing system based on space-time vector four-dimensional data.
A system for processing electricity stealing evidence data based on space-time vector four-dimensional data, comprising:
a data acquisition module configured to: acquiring power utilization data, field detection data and field image data of user power utilization;
an event windowing module configured to: generating a first dynamic event window according to the change of the electricity utilization data before and after electricity stealing; generating a second dynamic event window according to field detection data in the electricity stealing process; generating a third dynamic event window according to the field image data in the electricity stealing process; generating a fourth dynamic event window according to the change of the power utilization data in and after the power stealing recovery; generating a fifth dynamic event window according to the change of the electricity utilization data of the user before electricity stealing occurs and after electricity stealing recovery;
a data decomposition module configured to: the method comprises the steps that a first dynamic event window, a second dynamic event window, a third dynamic event window, a fourth dynamic event window and a fifth dynamic event window form data to be processed, and the data to be processed are decomposed into time data, spatial position data, quantitative data and a data carrier by utilizing a preset four-dimensional data model;
a data reconstruction module configured to: reconstructing time data, spatial position data, quantized data and a data carrier based on a D-S evidence theory according to a first dynamic event window, a second dynamic event window, a fourth dynamic event window and a fifth dynamic event window;
a data signing module configured to: and adding a trusted timestamp signature to the reconstructed data to obtain final key data of the electricity stealing evidence.
Furthermore, the electricity consumption data comprises electric quantity data, voltage data, current data and power data.
Further, reconstructing the time data, the spatial position data, the quantization data and the data carrier based on the D-S evidence theory, comprising:
the product of the confidence level of the quantized data evidence and the fusion degree of the quantized data evidence is greater than zero, and the larger the product is, the higher the priority of the quantized data is.
Further, quantifying data evidence confidence, comprising:
when the variation of the electric quantity data, the current data, the voltage data and the power data of the user in the first event window and the fourth event window is larger than a first preset value and the duration is larger than a second preset value, judging that the reliability of the quantized data evidence is 1, otherwise, judging that the reliability of the quantized data evidence is 0;
recovering the electric quantity data, the current data, the voltage data and the power data in the fifth event window, judging that the evidence reliability of the quantized data is 1 if no obvious change exists in the preset time, and otherwise, judging that the evidence reliability of the quantized data is 0;
in the second event window, when a suspected electricity stealing point is detected on site, the reliability of the quantized data evidence is judged to be 1, otherwise, the reliability of the quantized data evidence is judged to be 0.
Furthermore, if the quantized data evidence occurs and other three types of evidence simultaneously occur, determining that the quantized data evidence fusion degree is a first value;
if the quantized data evidence occurs and two types of evidence simultaneously occur, judging that the quantized data evidence fusion degree is a second numerical value;
if the quantized data evidence occurs and simultaneously accompanies a type of evidence to occur simultaneously, judging that the quantized data evidence fusion degree is a third numerical value;
if the quantized data evidence occurs and no accompanying evidence occurs simultaneously, judging that the quantized data evidence fusion degree is a fourth numerical value;
the first, second, third and fourth values decrease in sequence.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the electricity stealing evidence data processing method and system based on the spatio-temporal vector four-dimensional data, provided by the invention, a spatio-temporal vector four-dimensional evidence chain processing mechanism is established, original data, field detection evidence and field image evidence are refined into four dimensions of time, position space, quantized data and a data carrier, the relevance among the evidences (the time, the place and the same equipment are obtained) is strengthened, and the authenticity, the integrity and the effectiveness of the evidence data are improved.
2. According to the electricity stealing evidence data processing method and system based on the space-time vector four-dimensional data, provided by the invention, a space-time vector four-dimensional data model based on time, space, quantized data and a data carrier is provided for the first time, so that various evidence data can be processed more clearly in the evidence obtaining process, and the reconstruction of subsequent evidence data is facilitated.
3. According to the electricity stealing evidence data processing method and system based on the space-time vector four-dimensional data, provided by the invention, the authenticity, objectivity and relevance of a reconstructed evidence chain are higher based on the D-S evidence theory multi-source information Dempster combination rule and the time logic of evidence organization.
4. According to the electricity stealing evidence data processing method and system based on the space-time vector four-dimensional data, provided by the invention, the credible timestamp signature is carried out on the original evidence chain after the aggregation reconstruction, so that the contents of the evidence chain can be kept complete and cannot be tampered in the migration and use processes, and the non-repudiation and non-repudiation of the evidence chain are improved.
Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
Fig. 1 is a schematic flow chart of a method for processing electricity stealing evidence data based on space-time vector four-dimensional data according to embodiment 1 of the present invention.
Fig. 2 is a schematic diagram of raw data sampling provided in embodiment 1 of the present invention.
Fig. 3 is a schematic diagram of an evidence data aggregation reconfiguration process provided in embodiment 1 of the present invention.
Fig. 4 is an exemplary diagram of an electricity stealing behavior audit report provided in embodiment 1 of the present invention.
Detailed Description
The invention is further described with reference to the following figures and examples.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The embodiments and features of the embodiments of the present invention may be combined with each other without conflict.
Example 1:
as shown in fig. 1, embodiment 1 of the present invention provides a method for processing electricity stealing evidence data based on space-time vector four-dimensional data, which ensures integrity, objectivity, validity, and non-repudiation of electricity stealing evidence, and includes the following steps:
s1: generating original data;
s2: cleaning and classifying original data;
s3: establishing a space-time vector four-dimensional processing model, and processing original data into a space-time vector four-dimensional data volume;
s4: performing polymerization reconstruction on the generated four-dimensional data body to generate an evidence chain prototype;
s5: and carrying out timestamp signature to generate a formal electricity stealing evidence chain.
In particular, the method comprises the following steps of,
s1 includes:
by utilizing a dynamic event window generation technology, as shown in fig. 2, a first dynamic event window is generated according to changes (i-ii) before and after electricity stealing of user electricity quantity data, voltage, current, function and other load data collected by a system;
generating a fourth dynamic event window according to the changes (II-V) of the load data such as the electric quantity data, the voltage, the current, the functions and the like of the user after the electricity stealing recovery in the electricity stealing process and the electricity stealing recovery;
generating a fifth dynamic event window according to the changes (i-v) of load data such as user electric quantity data, voltage, current, functions and the like before electricity stealing occurs and after electricity stealing recovery;
in the field detection process, the device is used for rapidly and accurately detecting the field metering device and the loop of the electricity stealing user without power outage (step three-step four), so that a second dynamic event window is generated, and a field detection evidence is generated;
the image recording device worn by the staff automatically records and takes pictures (the third-fourth process), and a third dynamic event window is generated to generate a scene image evidence.
S2 includes:
data cleaning and classification:
processing lost values, boundary-crossing values, inconsistent codes and repeated data of the data from the aspects of accuracy, completeness, consistency, uniqueness, timeliness and effectiveness of the data;
secondly, data are classified: and classifying and aggregating the original analysis data, the field detection data and the field image data according to the classification, sequencing, distance and scaling principles.
S3 includes:
any electricity stealing case occurrence and electricity stealing field detection (detection) process has Time, Space and place, occurrence Data variation and each basic attribute of a Data carrier, a Time-Space vector four-dimensional Data model (Time, Space, Quantitative and Data) TSQD model based on Time, Space, quantized Data and the Data carrier is established according to relevance and objectivity requirements in evidence triparence by combining evidentiary or evidence law, and original Data is decomposed into Time Data, Space position Data, quantized Data and Data carrier information.
The TSQD model comprises a comparison analysis of actual field operation data of user metering equipment, electricity stealing field position information, a time label and an electricity stealing result report, and the detailed model is as follows.
Firstly, the TSQD model is utilized to preliminarily analyze and screen the metering abnormality of the user metering equipmentAnd checking the approximate time point of the historical power utilization sudden change of the user, wherein the part is used as an auxiliary result of the power stealing abnormity and not used as actual evidence of the power stealing. If TSQD, as shown in equation (1) 1 If the current time is more than or equal to 30%, judging that electricity stealing behavior is suspected to exist in the month, the quarter or the year; if TSQD 1 And if the data is less than or equal to 30 percent, the data result is not taken as the evidence of suspected electricity stealing behavior.
Wherein TSQD 1 Metering a historical monthly, quarterly or yearly frozen power usage change rate, DJ, of a device for a user 1 Metering historical month, quarter or year frozen power usage, DJ, of a device for a user 2 Metering the historical freezing power consumption of the equipment for the user in the second month, the second year or the year, and preliminarily analyzing when the user has the electricity stealing behavior by comparing the historical power consumption data of different periods.
Wherein, EQ 1 The user is metered the accumulated amount of electricity over the time period from t1 to t2,Uis a value of the voltage to be applied,Iis a current value.
Wherein, EQ 2 For the user to check the accumulated electric quantity value in the time period from t1 to t2 from the same time as the user metering device,Uis a value of the voltage to be applied,Iis a current value.
Wherein TSQD 2 For relative error, if TSQD 2 If the measurement result is less than or equal to 2%, judging that the user metering equipment is normal; if TSQD 2 ≥2%And judging that the user metering equipment is abnormal and the suspicion of electricity stealing exists. According to the data result, the field inspection equipment issues an abnormal report of the user metering equipment, information such as issuing time, longitude and latitude position information, metering precision abnormal result data and the like is issued on the report content, the name of a third party detection mechanism is issued on the whole report, and the report is uploaded to a specific system in real time.
S4 includes:
and performing aggregation reconstruction on the dispersed and disordered time data, the spatial position data, the quantized data and the data carrier information processed by the space vector four-dimensional model according to the D-S evidence information fusion error correction and the evidence organization time logic, and outputting a true, objective, legal and highly-associated evidence chain, wherein the data aggregation reconstruction process is shown in FIG. 3.
Independent evidence bodies are known in 4 classes: the method comprises the following steps of time evidence, spatial position evidence, quantitative data evidence and data carrier evidence, wherein the quantitative data evidence and other 3 types of evidence in 4 types of evidence have direct association relation. Therefore, the quantized data is selected as a verification main line, whether time evidence, spatial position evidence and data carrier evidence are generated when the quantized data occurs is selected as target information for information verification, and three possibilities of generation of 3 types of evidence, generation of partial evidence and no evidence exist.
According to the D-S evidence theory, the quantitative data evidence fusion steps are as follows:
1) and (3) confirming the credibility E of the quantized data evidence: the quantized data evidence is obtained by analyzing and quantizing the original analysis evidence and the on-site detection evidence, and the change trend of the data in the event window is analyzed by utilizing the first dynamic event window, the second dynamic event window, the fourth dynamic event window and the fifth dynamic event window, so that the following judgment is made:
the electric quantity, the current, the voltage and the power load of the users in the first event window and the fourth event window are obviously and continuously changed (namely, when the change is greater than a first preset value and the duration is greater than a second preset value), the evidence credibility E of the quantized data is judged to be 1, otherwise, the evidence credibility E of the quantized data is 0;
if the user electric quantity, the current, the voltage and the power load are obviously recovered (namely, the third preset value is recovered) in the fifth event window, namely, the persistence has no obvious change (namely, the duration is greater than the fourth preset value), the evidence reliability E of the quantized data is judged to be 1, otherwise, the evidence reliability E of the quantized data is 0;
and in the second event window, if suspected electricity stealing points including electricity stealing equipment and electricity stealing methods are detected on the site, judging that the reliability E of the quantized data evidence is 1, otherwise, judging that the reliability E is 0.
In this embodiment, the first preset value, the second preset value, the third preset value and the fourth preset value are all artificial set values, and those skilled in the art can selectively set the values according to specific working conditions.
2) Quantitative data evidence fusion degree analysis: according to the direct incidence relation between the quantized data and other 3 types of evidences, whether the quantized data have time evidences, spatial position evidences and data carrier evidences when the quantized data occur is selected to generate target information for information verification, and three possibilities of 3 types of evidences, partial evidences and no evidences occur exist.
The determination is as follows:
if the quantized data evidence occurs and other 3 types of evidence occur simultaneously, judging that the quantized data evidence fusion degree R is 1 (namely a first numerical value);
if the quantized data evidence occurs and simultaneously occurs 2 types of evidence, judging that the quantized data evidence fusion degree R is 0.6 (namely a second numerical value);
if the quantized data evidence occurs and simultaneously occurs with 1 type of evidence, judging that the quantized data evidence fusion degree R is 0.3 (namely a third numerical value);
if the quantized data evidence occurs and no accompanying evidence occurs simultaneously, the quantized data evidence fusion degree R is judged to be 0 (namely, a fourth numerical value).
3) Occurrence time logic evidence reconstruction mechanism: and (4) reconstructing the evidence by taking the occurrence time of the evidence as a logic main line, wherein the selectable premise of selecting the evidence is that the product of the evidence credibility E and the evidence fusion degree R is greater than 0, and the higher the value is, the higher the priority is.
It can be understood that the first numerical value, the second numerical value, the third numerical value, and the fourth numerical value may also be selected according to specific working conditions, as long as the first numerical value, the second numerical value, the third numerical value, and the fourth numerical value are ensured to be decreased sequentially.
S5 includes:
the essence of the time stamp service is to bind the data of the user with the current accurate time, sign the data by using a digital certificate of a time stamp system on the basis, generate a time stamp which can be used for legal evidence by means of the authority authorization status of the time stamp system in law, prove the generation time of the data of the user and achieve the aim of 'non-repudiation' or 'anti-repudiation'. Based on the method, the credible timestamp signature is carried out on the original evidence chain after the aggregation reconstruction, so that the content of the data chain is kept complete and is not tampered in the migration and use processes, and the non-repudiation of the evidence chain are ensured.
Example 2:
a data acquisition module configured to: acquiring power utilization data, field detection data and field image data of user power utilization;
an event windowing module configured to: generating a first dynamic event window according to the change of the electricity utilization data before and after electricity stealing; generating a second dynamic event window according to field detection data in the electricity stealing process; generating a third dynamic event window according to the field image data in the electricity stealing process; generating a fourth dynamic event window according to the change of the power utilization data in and after the power stealing recovery; generating a fifth dynamic event window according to the change of the electricity utilization data of the user before electricity stealing occurs and after electricity stealing recovery;
a data decomposition module configured to: the method comprises the steps that a first dynamic event window, a second dynamic event window, a third dynamic event window, a fourth dynamic event window and a fifth dynamic event window form data to be processed, and the data to be processed are decomposed into time data, spatial position data, quantitative data and a data carrier by utilizing a preset four-dimensional data model;
a data reconstruction module configured to: reconstructing time data, spatial position data, quantized data and a data carrier based on a D-S evidence theory according to a first dynamic event window, a second dynamic event window, a fourth dynamic event window and a fifth dynamic event window;
a data signing module configured to: and adding a trusted timestamp signature to the reconstructed data to obtain final key data of the electricity stealing evidence.
The working method of the system is the same as the electricity stealing evidence data processing method based on the space-time vector four-dimensional data provided in embodiment 1, and details are not repeated here.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (4)
1. A method for processing electricity stealing evidence data based on space-time vector four-dimensional data is characterized by comprising the following steps:
the method comprises the following steps:
acquiring power utilization data, field detection data and field image data of user power utilization;
generating a first dynamic event window according to the change of the electricity utilization data before and after electricity stealing; generating a second dynamic event window according to field detection data in the electricity stealing process; generating a third dynamic event window according to the field image data in the electricity stealing process; generating a fourth dynamic event window according to the change of the power utilization data in and after the power stealing recovery; generating a fifth dynamic event window according to the change of the electricity utilization data of the user before electricity stealing occurs and after electricity stealing recovery;
the method comprises the steps that a first dynamic event window, a second event window, a third event window, a fourth dynamic event window and a fifth dynamic event window form data to be processed, and the data to be processed are decomposed into time data, spatial position data, quantitative data and a data carrier by utilizing a preset four-dimensional data model;
reconstructing time data, spatial position data, quantized data and a data carrier based on a D-S evidence theory according to a first dynamic event window, a second dynamic event window, a fourth dynamic event window and a fifth dynamic event window;
adding a trusted timestamp signature to the reconstructed data to obtain final electricity stealing evidence key data;
the electricity consumption data comprises electric quantity data, voltage data, current data and power data;
reconstructing time data, spatial position data, quantization data and a data carrier based on a D-S evidence theory, comprising:
the product of the credibility of the quantized data evidence and the fusion degree of the quantized data evidence is larger than zero, and the higher the product is, the higher the priority of the quantized data is;
quantifying data evidence confidence, including:
when the variation of the electric quantity data, the current data, the voltage data and the power data of the user in the first event window and the fourth event window is larger than a first preset value and the duration is larger than a second preset value, judging that the reliability of the quantized data evidence is 1, otherwise, judging that the reliability of the quantized data evidence is 0;
recovering the electric quantity data, the current data, the voltage data and the power data in the fifth event window, judging that the evidence reliability of the quantized data is 1 if no obvious change exists in the preset time, and otherwise, judging that the evidence reliability of the quantized data is 0;
in the second event window, when a suspected electricity stealing point is detected on site, the reliability of the quantized data evidence is judged to be 1, otherwise, the reliability of the quantized data evidence is judged to be 0.
2. The electricity stealing evidence data processing method based on space-time vector four-dimensional data as claimed in claim 1, wherein:
if the quantized data evidence occurs and other three types of evidence simultaneously occur, judging that the quantized data evidence fusion degree is a first numerical value;
if the quantized data evidence occurs and two types of evidence simultaneously occur, judging that the quantized data evidence fusion degree is a second numerical value;
if the quantized data evidence occurs and simultaneously accompanies a type of evidence to occur simultaneously, judging that the quantized data evidence fusion degree is a third numerical value;
if the quantized data evidence occurs and no accompanying evidence occurs simultaneously, judging that the quantized data evidence fusion degree is a fourth numerical value;
the first, second, third and fourth values decrease in sequence.
3. A steal electric evidence data processing system based on space-time vector body four-dimensional data, its characterized in that:
the method comprises the following steps:
a data acquisition module configured to: acquiring power utilization data, field detection data and field image data of user power utilization;
an event windowing module configured to: generating a first dynamic event window according to the change of the electricity utilization data before and after electricity stealing; generating a second dynamic event window according to field detection data in the electricity stealing process; generating a third dynamic event window according to the field image data in the electricity stealing process; generating a fourth dynamic event window according to the change of the power utilization data in and after the power stealing recovery; generating a fifth dynamic event window according to the change of the electricity utilization data of the user before electricity stealing occurs and after electricity stealing recovery;
a data decomposition module configured to: forming data to be processed according to the first dynamic event window, the second dynamic event window, the third dynamic event window, the fourth dynamic event window and the fifth dynamic event window, and decomposing the data to be processed into time data, spatial position data, quantitative data and a data carrier by utilizing a preset four-dimensional data model;
a data reconstruction module configured to: reconstructing time data, spatial position data, quantized data and a data carrier based on a D-S evidence theory according to a first dynamic event window, a second dynamic event window, a fourth dynamic event window and a fifth dynamic event window;
a data signing module configured to: adding a trusted timestamp signature to the reconstructed data to obtain final electricity stealing evidence key data;
the electricity consumption data comprises electric quantity data, voltage data, current data and power data;
reconstructing time data, spatial position data, quantization data and a data carrier based on a D-S evidence theory, comprising:
the product of the credibility of the quantized data evidence and the fusion degree of the quantized data evidence is larger than zero, and the higher the product is, the higher the priority of the quantized data is;
quantifying data evidence confidence, including:
when the variation of the electric quantity data, the current data, the voltage data and the power data of the user in the first event window and the fourth event window is larger than a first preset value and the duration is larger than a second preset value, judging that the reliability of the quantized data evidence is 1, otherwise, judging that the reliability of the quantized data evidence is 0;
recovering the electric quantity data, the current data, the voltage data and the power data in the fifth event window, judging that the evidence reliability of the quantized data is 1 if no obvious change exists in the preset time, and otherwise, judging that the evidence reliability of the quantized data is 0;
in the second event window, when a suspected electricity stealing point is detected on site, the reliability of the quantized data evidence is judged to be 1, otherwise, the reliability of the quantized data evidence is judged to be 0.
4. The space-time vector volume four-dimensional data-based electricity stealing evidence data processing system of claim 3, wherein:
if the quantized data evidence occurs and other three types of evidence simultaneously occur, judging that the quantized data evidence fusion degree is a first numerical value;
if the quantized data evidence occurs and two types of evidence simultaneously occur, judging that the quantized data evidence fusion degree is a second numerical value;
if the quantized data evidence occurs and simultaneously accompanies a type of evidence to occur simultaneously, judging that the quantized data evidence fusion degree is a third numerical value;
if the quantized data evidence occurs and no accompanying evidence occurs simultaneously, judging that the quantized data evidence fusion degree is a fourth numerical value;
the first, second, third and fourth values decrease in sequence.
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| CN113484572A (en) * | 2021-06-01 | 2021-10-08 | 国网吉林省电力有限公司信息通信公司 | Anti-electricity-stealing monitoring method and system based on electricity utilization big data |
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| CN113484572A (en) * | 2021-06-01 | 2021-10-08 | 国网吉林省电力有限公司信息通信公司 | Anti-electricity-stealing monitoring method and system based on electricity utilization big data |
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