An intelligent early warning system for electric meter operation safety based on data analysis

Abstract

The present invention discloses an intelligent early warning system for the operation safety of an electric meter based on data analysis, which relates to the technical field of electric meter monitoring and comprises a monitoring center, wherein the monitoring center is communicatively connected with a data acquisition module, a data processing module, a data analysis module and an intelligent early warning module, and by setting correspondingly associated data acquisition terminals for the input end, the output end and different lines inside the electric meter, the corresponding power consumption situation is acquired in real time through the set data acquisition terminals, and the characteristics of the time window are used to perform a comprehensive analysis on the operation status of the electric meter, and then the operation of the electric meter is isolated and evaluated according to the comprehensive analysis results, and the position causing the abnormal operation of the electric meter is further determined, thereby realizing effective monitoring of the operation status of the electric meter itself and being able to quickly determine the position causing the abnormal operation of the electric meter when the operation of the electric meter is abnormal.

Description

Technical Field

[0001] The invention relates to the technical field of electric meter monitoring, and in particular to an electric meter operation safety intelligent early warning system based on data analysis. Background Art

[0002] At present, most of the electric energy meters removed from the site have a low reuse rate due to the lack of sample testing. A small number of electric energy meters removed are only subjected to simple testing and cannot be effectively supervised. During the sorting and testing of the removed meters, the relevant data of the removed smart electric energy meters are not effectively collected due to the non-standard entry of fault information, which seriously affects the data statistics of faulty electric energy meters and the analysis of fault causes, and cannot meet the requirements of closed-loop management of the entire life cycle of electric energy meters. At the same time, large-scale scrapping will also lead to a waste of social resources and fail to reflect the social consensus on saving production.

[0003] In the prior art, the monitoring of the electric meter can often only be reflected in the electricity consumption information, while there is a lag in the monitoring of whether there is any abnormality in the operating status of the electric meter itself, and after the electric meter has an abnormality, it is impossible to locate the position that caused the abnormality of the electric meter. How to effectively monitor the operating safety of the electric meter itself and quickly locate the position that caused the abnormality of the electric meter after the electric meter has an abnormality is a problem we need to solve. To this end, an intelligent early warning system for electric meter operation safety based on data analysis is provided. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent early warning system for electric meter operation safety based on data analysis.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] An intelligent early warning system for electric meter operation safety based on data analysis, comprising a monitoring center, wherein the monitoring center is communicatively connected with a data acquisition module, a data processing module, a data analysis module and an intelligent early warning module;

[0007] The data acquisition module is used to collect the operation data of the electric meter in real time;

[0008] The data processing module is used to process the collected meter operation data to obtain the meter safety assessment coefficient;

[0009] The data analysis module is used to analyze the operation status of the electric meter according to the obtained safety assessment coefficient of the electric meter, and determine whether the electric meter has any abnormality according to the analysis result, and if there is any abnormality, generate a safety warning instruction;

[0010] The intelligent early warning module is used to locate the abnormal position of the electric meter according to the generated safety early warning instruction and generate corresponding safety early warning information.

[0011] Furthermore, the data acquisition module is composed of a plurality of data acquisition terminals, which are arranged at the input end, the output end and the monitoring node inside the electric meter, and are used to collect the electric meter operation data in real time, wherein the electric meter operation data includes the input current, the output current and the operation current, and each monitoring node is associated with a corresponding line;

[0012] Corresponding data acquisition terminals are respectively provided at the input and output ends of the electric meter;

[0013] The input current of the electric meter is obtained in real time through a data acquisition terminal arranged at the input end of the electric meter;

[0014] The output current of the electric meter is obtained in real time through a data acquisition terminal arranged at the output end of the electric meter.

[0015] Furthermore, the process of the data processing module for processing the collected electric meter operation data includes:

[0016] According to the distribution of the internal lines of the electric meter, a virtual model of the electric meter is constructed, and corresponding virtual nodes are generated at corresponding positions in the virtual model of the electric meter;

[0017] Establish a two-dimensional coordinate system of time with respect to current;

[0018] Generate a corresponding input current variation curve according to the input current obtained at the input end;

[0019] Generate a corresponding output current variation curve according to the output current obtained at the output end;

[0020] According to the operating current obtained by each monitoring node, a corresponding operating current change curve is generated respectively;

[0021] Mapping each generated current variation curve into a two-dimensional coordinate system;

[0022] Set the meter monitoring time window;

[0023] Intercept each current change curve within the meter monitoring time window, and obtain the power consumption of the corresponding monitoring node according to each intercepted current change curve, and

[0024] The power consumption of the input and output ends during the meter monitoring time window;

[0025] Obtain the meter safety assessment coefficient within the meter monitoring time window.

[0026] Furthermore, each virtual node is associated with a monitoring node in the electric meter, and the virtual node is provided with a corresponding operating state, the operating state includes a normal state and an abnormal state, and the initial state of each virtual node is a normal state.

[0027] Furthermore, the process of the data analysis module analyzing the operation status of the electric meter according to the obtained electric meter safety assessment coefficient includes:

[0028] The obtained safety assessment coefficient of the electric meter is compared with the set assessment coefficient threshold to obtain a corresponding comparison result, and whether the operation state of the electric meter is abnormal is determined according to the comparison result. If the operation state of the electric meter is abnormal, an abnormal assessment instruction is generated;

[0029] According to the abnormal evaluation instruction, a secondary evaluation is performed on the operating status of the electric meter.

[0030] Furthermore, the process of secondary evaluation of the operating status of the electric meter includes:

[0031] The moment when the abnormal evaluation instruction is generated is recorded as the initial evaluation moment;

[0032] Establishing a two-dimensional coordinate system of time with respect to the evaluation coefficient, and taking the initial evaluation moment as the starting point, generating a curve of the change of the safety evaluation coefficient of the electric meter, and mapping the generated curve of the change of the safety evaluation coefficient of the electric meter into the two-dimensional coordinate system;

[0033] Generate a corresponding number of periodic evaluation nodes according to the number of monitoring nodes in the electric meter, and generate corresponding periodic evaluation nodes according to the input and output ends of the electric meter, associate the input and output ends with corresponding periodic evaluation nodes respectively, associate each monitoring node with a periodic evaluation node respectively, and obtain the theoretical line loss electricity of the object associated with the periodic evaluation node;

[0034] According to the generated periodic evaluation nodes, the electric meters are respectively subjected to partition evaluation to obtain corresponding partition evaluation coefficients;

[0035] The obtained isolation assessment coefficient is compared with the set isolation coefficient threshold, and whether the operation of the object associated with the periodic assessment node is abnormal is determined according to the comparison result. If the operation of the object associated with the periodic assessment node is abnormal, a corresponding safety warning instruction is generated.

[0036] Furthermore, the process in which the intelligent warning module locates the abnormal position of the electric meter according to the generated safety warning instruction and generates corresponding safety warning information includes:

[0037] Mapping the abnormal point to the corresponding virtual node in the virtual model of the electric meter, and marking the operating state of the corresponding virtual node as an abnormal state;

[0038] Acquire a monitoring node associated with the virtual node in an abnormal state, and mark a line associated with the monitoring node as abnormal;

[0039] The virtual nodes in abnormal state and the lines marked as abnormal are summarized, corresponding safety warning information is generated, and the generated safety warning information is sent to the monitoring center.

[0040] Compared with the prior art, the beneficial effects of the present invention are as follows: by setting corresponding associated data acquisition terminals for the input end, output end and different lines inside the electric meter, the corresponding power consumption situation is obtained in real time through the set data acquisition terminals, and the characteristics of the time window are used to conduct a comprehensive analysis of the operating status of the electric meter, and then the operation of the electric meter is isolated and evaluated based on the comprehensive analysis results, and the location that causes the abnormal operation of the electric meter is further determined, thereby achieving effective monitoring of the operating status of the electric meter itself and when the operation of the electric meter is abnormal, the location that causes the abnormality of the electric meter can be quickly determined. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0042] like Figure 1 As shown, an intelligent early warning system for electric meter operation safety based on data analysis includes a monitoring center, and the monitoring center is communicatively connected with a data acquisition module, a data processing module, a data analysis module and an intelligent early warning module;

[0043] The data acquisition module is used to collect the operation data of the electric meter in real time;

[0044] The data processing module is used to process the collected meter operation data to obtain the meter safety assessment coefficient;

[0045] The data analysis module is used to analyze the operation status of the electric meter according to the obtained safety assessment coefficient of the electric meter, and determine whether the electric meter has any abnormality according to the analysis result, and if there is any abnormality, generate a safety warning instruction;

[0046] The intelligent early warning module is used to locate the abnormal position of the electric meter according to the generated safety early warning instruction and generate corresponding safety early warning information.

[0047] It should be further explained that, in the specific implementation process, the data acquisition module is composed of several data acquisition terminals, which are arranged at the input end, output end and monitoring node inside the electric meter, and are used to collect the electric meter operation data in real time. The electric meter operation data includes input current, output current and operation current. The specific process includes:

[0048] Corresponding data acquisition terminals are respectively provided at the input and output ends of the electric meter;

[0049] The input current of the meter is obtained in real time through a data acquisition terminal arranged at the input end of the meter, which is recorded as Ir;

[0050] The output current of the electric meter is obtained in real time through a data acquisition terminal arranged at the output end of the electric meter, which is recorded as Ic;

[0051] Several monitoring nodes are set inside the electric meter, and a corresponding data acquisition terminal is set at each monitoring node, and the corresponding operating current is collected in real time through the data acquisition terminal set at each monitoring node; it should be further explained that in the specific implementation process, each monitoring node is associated with a corresponding line;

[0052] In the specific implementation process, each monitoring node inside the electric meter is labeled as i, where i=1, 2, ..., n, n is an integer, and n>0;

[0053] The operating current obtained by the data acquisition terminal set at the monitoring node labeled i is recorded as Iy i .

[0054] The data processing module is used to process the collected meter operation data, and the specific process includes:

[0055] According to the distribution of the internal lines of the electric meter, a virtual model of the electric meter is constructed, and corresponding virtual nodes are generated at corresponding positions in the virtual model of the electric meter; it should be further explained that in the specific implementation process, each virtual node is associated with a monitoring node in the electric meter, and the virtual node is provided with a corresponding operating state, the operating state includes a normal state and an abnormal state, and the initial state of each virtual node is a normal state;

[0056] and setting a storage node linked to each virtual node for storing the meter operation data collected by the data collection terminal at the monitoring node associated with the virtual node;

[0057] Establish a two-dimensional coordinate system of time with respect to current;

[0058] Generate a corresponding input current variation curve according to the input current obtained at the input end;

[0059] Generate a corresponding output current variation curve according to the output current obtained at the output end;

[0060] According to the operating current obtained by each monitoring node, a corresponding operating current change curve is generated respectively;

[0061] Mapping each generated current variation curve into a two-dimensional coordinate system;

[0062] Set the meter monitoring time window (t1, t2), where the duration from t1 to t2 is recorded as T, and t2 represents the current time;

[0063] Each current change curve within the meter monitoring time window is intercepted, and the power consumption of the corresponding monitoring node is obtained according to each intercepted current change curve, which is recorded as Q(t);

[0064]

[0065] Where I(t) represents the current variation curve;

[0066] The power consumption of the input terminal during the meter monitoring time window is recorded as Q r ;

[0067] The power consumption of the output terminal during the meter monitoring time window is recorded as Q c ;

[0068] The power consumption of the monitoring node labeled i during the meter monitoring time window is recorded as Q i ;

[0069] Then obtain the meter safety assessment coefficient within the meter monitoring time window, denoted as Dx;

[0070] in,

[0071] Where K i represents the line loss coefficient of the line associated with the monitoring node labeled i;

[0072] The obtained safety assessment coefficient of the electric meter is uploaded to the data analysis module, and the data analysis module analyzes the operating status of the electric meter according to the obtained safety assessment coefficient of the electric meter.

[0073] It should be further explained that, in a specific implementation process, the process in which the data analysis module analyzes the operation status of the electric meter according to the obtained electric meter safety assessment coefficient includes:

[0074] Set the evaluation coefficient threshold, denoted as Kd;

[0075] Compare the obtained electric meter safety assessment coefficient Dx with the set assessment coefficient threshold to obtain a corresponding comparison result;

[0076] When Dx>Kd is satisfied, it means that the meter is operating normally;

[0077] When Dx≤Kd is satisfied, it means that the operation status of the meter is abnormal, and an abnormal evaluation instruction is generated;

[0078] According to the abnormal evaluation instruction, a secondary evaluation is performed on the operating status of the electric meter.

[0079] It should be further explained that, in the specific implementation process, the process of secondary evaluation of the operating status of the electric meter includes:

[0080] The time when the abnormal evaluation instruction is generated is recorded as the evaluation initial time Pt1;

[0081] Establishing a two-dimensional coordinate system of time with respect to the evaluation coefficient, and taking the initial evaluation moment as the starting point, generating a curve of the change of the safety evaluation coefficient of the electric meter, and mapping the generated curve of the change of the safety evaluation coefficient of the electric meter into the two-dimensional coordinate system;

[0082] According to the number of monitoring nodes in the electric meter, a corresponding number of periodic evaluation nodes are generated, and corresponding periodic evaluation nodes are generated according to the input end and the output end of the electric meter, and the input end and the output end are respectively associated with the corresponding periodic evaluation nodes, and each monitoring node is respectively associated with a periodic evaluation node; it should be further explained that in the specific implementation process, the interval time of each adjacent periodic evaluation node is the same, and each periodic evaluation node is associated with only one object;

[0083] The evaluation node for each cycle is denoted as j, where j = 1, 2, ..., m, where m = n + 2;

[0084] The time corresponding to the periodic evaluation node labeled j is recorded as Zt j ;

[0085] The theoretical line loss of the object associated with the periodic evaluation node labeled j is recorded as Yd j ;

[0086] According to the generated periodic evaluation nodes, the electric meters are separated and evaluated respectively to obtain the corresponding separation evaluation coefficient, which is recorded as Dg j ; It should be further explained that, in the specific implementation process, the isolation assessment means that when the corresponding periodic assessment node is reached, the line loss electricity of all monitoring nodes and input and output ends corresponding to the object associated with the periodic assessment node from the initial assessment time Pt1 to the periodic assessment node is obtained, and the line loss electricity is isolated, and the meter safety assessment coefficient of the meter is re-obtained, that is, the monitoring node does not participate in the calculation of the meter safety assessment coefficient, and the re-obtained meter safety assessment coefficient is recorded as the isolation assessment coefficient;

[0087] in,

[0088] Set the cutoff coefficient threshold Y j ; It should be further explained that, in the specific implementation process, objects associated with different periodic evaluation nodes are all set with corresponding isolation coefficient thresholds, and the isolation coefficient thresholds depend on the length, cross-sectional area and material of the corresponding line;

[0089] When Dg j ≤Y j When , it means that the object associated with the periodic evaluation node labeled j is running normally;

[0090] When Dg j >Y j When , it means that the object associated with the periodic evaluation node labeled j is running abnormally, then the object is marked as an abnormal point and a corresponding safety warning instruction is generated;

[0091] By setting the isolation evaluation, the objects associated with each periodic evaluation node are isolated, and the impact of each object on the isolation evaluation coefficient is obtained, so as to determine the location that causes the abnormal operation of the meter.

[0092] The process in which the intelligent early warning module locates the abnormal position of the electric meter according to the generated safety early warning instruction and generates corresponding safety early warning information includes:

[0093] Mapping the abnormal point to the corresponding virtual node in the virtual model of the electric meter, and marking the operating state of the corresponding virtual node as an abnormal state;

[0094] Acquire the monitoring node associated with the virtual node in the abnormal state, and mark the line related to the monitoring node as abnormal; it should be further explained that, in the specific implementation process, if the input end or the output end is abnormal, the input end and the output end of the virtual model of the electric meter are directly marked as abnormal;

[0095] Summarize the virtual nodes in abnormal state and the lines marked as abnormal, generate corresponding safety warning information, and send the generated safety warning information to the monitoring center;

[0096] By setting corresponding data acquisition terminals for the input end, output end and different lines inside the meter, the corresponding power consumption situation is obtained in real time through the set data acquisition terminals, and the characteristics of the time window are used to conduct a comprehensive analysis of the meter's operating status. The meter operation is then isolated and evaluated based on the comprehensive analysis results, and the location that causes the meter's abnormal operation is further determined, thereby achieving effective monitoring of the meter's own operating status. When the meter's operation is abnormal, the location that causes the meter's abnormality can be quickly determined and sent to the monitoring center in the form of safety warning information.

[0097] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An intelligent early warning system for electric meter operation safety based on data analysis, including a monitoring center, characterized in that: The monitoring center is communicatively connected to a data acquisition module, a data processing module, a data analysis module and an intelligent early warning module; The data acquisition module is used to collect the operation data of the electric meter in real time; The data processing module is used to process the collected meter operation data to obtain the meter safety assessment coefficient; The data analysis module is used to analyze the operation status of the electric meter according to the obtained safety assessment coefficient of the electric meter, and determine whether the electric meter has any abnormality according to the analysis result, and if there is any abnormality, generate a safety warning instruction; The intelligent warning module is used to locate the abnormal position of the electric meter according to the generated safety warning instruction and generate corresponding safety warning information; The data acquisition module is composed of a plurality of data acquisition terminals, which are arranged at the input end, output end and monitoring nodes inside the electric meter, and are used to collect the operation data of the electric meter in real time. The operation data of the electric meter includes input current, output current and operation current, and each monitoring node is associated with a corresponding line; The process of the data processing module for processing the collected electric meter operation data includes: According to the distribution of the internal lines of the electric meter, a virtual model of the electric meter is constructed, and corresponding virtual nodes are generated at corresponding positions in the virtual model of the electric meter; Establish a two-dimensional coordinate system of time with respect to current; Generate a corresponding input current variation curve according to the input current obtained at the input end; Generate a corresponding output current variation curve according to the output current obtained at the output end; According to the operating current obtained by each monitoring node, a corresponding operating current change curve is generated respectively; Mapping each generated current variation curve into a two-dimensional coordinate system; Set the meter monitoring time window; Intercept each current change curve within the meter monitoring time window, and obtain the power consumption of the corresponding monitoring node according to each intercepted current change curve, and The power consumption of the input and output ends during the meter monitoring time window; Obtaining the electric meter safety assessment coefficient within the electric meter monitoring time window; Each virtual node is associated with a monitoring node in the electric meter, and the virtual node is provided with a corresponding operating state, the operating state includes a normal state and an abnormal state, and the initial state of each virtual node is a normal state; The process of the data analysis module analyzing the operation status of the electric meter according to the obtained electric meter safety assessment coefficient includes: The obtained safety assessment coefficient of the electric meter is compared with the set assessment coefficient threshold to obtain a corresponding comparison result, and whether the operation state of the electric meter is abnormal is determined according to the comparison result. If the operation state of the electric meter is abnormal, an abnormal assessment instruction is generated; Conduct a secondary assessment of the operating status of the electric meter according to the abnormal assessment instruction; The process of secondary evaluation of the operating status of the meter includes: The moment when the abnormal evaluation instruction is generated is recorded as the initial evaluation moment; Establishing a two-dimensional coordinate system of time with respect to the evaluation coefficient, and taking the initial evaluation moment as the starting point, generating a curve of the change of the safety evaluation coefficient of the electric meter, and mapping the generated curve of the change of the safety evaluation coefficient of the electric meter into the two-dimensional coordinate system; Generate a corresponding number of periodic evaluation nodes according to the number of monitoring nodes in the electric meter, and generate corresponding periodic evaluation nodes according to the input and output ends of the electric meter, associate the input and output ends with corresponding periodic evaluation nodes respectively, associate each monitoring node with a periodic evaluation node respectively, and obtain the theoretical line loss electricity of the object associated with the periodic evaluation node; According to the generated periodic evaluation nodes, the electric meters are respectively subjected to partition evaluation to obtain corresponding partition evaluation coefficients; The obtained isolation assessment coefficient is compared with the set isolation coefficient threshold, and whether the operation of the object associated with the periodic assessment node is abnormal is determined according to the comparison result. If the operation of the object associated with the periodic assessment node is abnormal, a corresponding safety warning instruction is generated.

2. According to claim 1, an intelligent early warning system for electric meter operation safety based on data analysis is characterized in that: The process in which the intelligent early warning module locates the abnormal position of the electric meter according to the generated safety early warning instruction and generates corresponding safety early warning information includes: Mapping the abnormal point to the corresponding virtual node in the virtual model of the electric meter, and marking the operating state of the corresponding virtual node as an abnormal state; Acquire a monitoring node associated with the virtual node in an abnormal state, and mark a line associated with the monitoring node as abnormal; The virtual nodes in abnormal state and the lines marked as abnormal are summarized, corresponding safety warning information is generated, and the generated safety warning information is sent to the monitoring center.

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