Loop iteration interception resolution method and device

Abstract

The invention discloses a loop iteration interception distinguishing method and device, and relates to the field of meter box management.The loop iteration interception distinguishing method comprises the steps that carrier signals of electricity meters are obtained, the carrier signals are processed, electricity consumption of the electricity meters is obtained, then the electricity meters hung under each node are obtained in sequence in a loop iteration mode, and after iteration is completed, the electricity consumption of the electricity meters is obtained. Obtaining an anomaly index according to an affiliation result of the electricity meter hung under each node of the meter box, determining an anomaly type of the meter box through a threshold comparison mode, and making different strategies based on different anomaly types; according to the invention, through the precise iteration steps, the electric meters hung below the nodes in the meter box can be precisely judged, and the management level of electric power is powerfully improved.

Description

Technical Field

[0001] The present invention relates to the field of meter box management, and in particular to a cyclic iterative listening and distinguishing method and device. Background Art

[0002] Meter boxes often physically connect the aggregation node to the downstream meter to confirm the node's downstream meter. However, physical wiring affects aesthetics and can cause disconnection. Carrier communication is a common method of communication on power lines, but carrier communication receives all carrier signals simultaneously, making it impossible to distinguish the node's downstream meter without file configuration. Traditional methods often rely on simple power comparisons to determine meter ownership, lacking precise judgment logic and iterative optimization mechanisms. This makes the meter ownership determination process susceptible to interference and inaccurate, making it impossible to accurately determine the downstream meter of each node. Accurately judging the hanging meters at each node in the meter box is a problem we need to solve. To this end, a cyclic iterative listening and discrimination method and device are now provided. Summary of the Invention

[0003] The purpose of the present invention is to provide a cyclic iterative listening and distinguishing method and device.

[0004] The object of the present invention can be achieved by the following technical solution: a cyclic iterative listening and resolution method, comprising the following steps: S1: Obtain the carrier signals of all electricity meters, analyze the carrier signals, obtain the corresponding power consumption of all electricity meters, and number each electricity meter. The number is represented by i, i = 1, 2...n, and n represents the total number of electricity meters. Obtain the electric energy of each node in the meter box and number each node. The number is represented by r, r = 1, 2...k, and k represents the total number of nodes. S2: Obtain the marking status of the meter numbered i. If it is not marked, mark the meter numbered i and update the accumulated power of the node numbered r. Obtain the absolute value of the difference between the accumulated power of the node numbered r after the update and the power of the node as the power difference of the node. Preset the power difference threshold. If the power difference is less than or equal to the power difference threshold, proceed to step S3. Otherwise, proceed to step S4. If it is marked, update i and execute step S2 again. S3: retain the marking status of all marked meters, update r and initialize the value of i to 1, and re-enter step S2; S4: If the accumulated power of the node numbered r is less than the power of the node, the meter numbered i is assigned to the node numbered r, and i is updated, and the process re-enters step S2; if the accumulated power of the node numbered r is greater than the power of the node, the process proceeds to step S5; S5: cancel the mark of the electric meter numbered i, update i, and re-enter step S2; S6: According to the attribution results of the electric meters connected to each node, determine the abnormal type of the meter box, and formulate corresponding strategies according to the abnormal type of the meter box.

[0005] Preferably, the process of analyzing the carrier signal to obtain the power consumption corresponding to all the meters is: Analyze the collected carrier signal of the electric meter to determine the modulation mode of the electric meter; According to the modulation mode of the electric meter, a corresponding demodulation algorithm is selected to restore the carrier signal to a digital signal, and the digital signal is processed to obtain digital data; Obtain the communication protocol of the electric meter, parse the digital data according to the frame format of the communication protocol, and obtain the electric quantity data; The electricity data is preprocessed to obtain standard electricity data, and the electricity consumption corresponding to the meter is obtained according to the specific type of the standard electricity data.

[0006] Preferably, the process of analyzing the collected carrier signal of the electric meter and determining the modulation mode of the electric meter is: Preprocessing multiple carrier signals of known modulation modes, and then obtaining signal characteristics of the preprocessed carrier signals; Normalize the acquired signal features, and associate the normalized signal features with the modulation mode of the corresponding carrier signal to obtain a model data set; The convolutional neural network model is trained using the model data set to obtain a modulation classification model; The carrier signal of the electric meter is collected, the corresponding signal characteristics are obtained according to the carrier signal of the electric meter, the signal characteristics corresponding to the electric meter are input into the modulation classification model, and the modulation mode corresponding to the electric meter is obtained.

[0007] Preferably, the process of determining the abnormal type of the meter box according to the attribution result of the electric meters connected to each node is as follows: Get the sum of the electricity consumption of the meters under each node as the classified electricity consumption corresponding to the node. Obtain the absolute value of the difference between the classified power and the electric energy of the node as the classified power difference value, mark the node according to the comparison result of the classified power difference value and the power difference threshold, record the marked node as an abnormal node, and obtain the number of abnormal nodes as the number of abnormal nodes; Obtain the sum of the classified electricity differences of all abnormal nodes as the missing electricity sum, obtain the sum of the electricity consumption of all meters not attributed to any node as the classified electricity sum, and obtain the absolute value of the difference between the missing electricity sum and the classified electricity sum as the class missing difference; If the number of abnormal nodes is not 0, the number of abnormal nodes and the class deficiency are fused to obtain the abnormal index, and the abnormal index threshold is preset. The abnormal level of the meter box is determined based on the comparison result between the abnormal index and the abnormal index threshold; if the number of abnormal nodes is 0, no processing is performed.

[0008] Preferably, the process of determining the abnormality level of the meter box according to the comparison result of the abnormality index and the abnormality index threshold is: If the abnormality index is less than or equal to the abnormality index threshold, the abnormality type of the meter box is determined to be an electric meter abnormality; otherwise, the abnormality type of the meter box is determined to be a parameter abnormality.

[0009] Preferably, the process of formulating corresponding strategies according to the abnormal type of the meter box is: If the meter box abnormality type is meter abnormality, professional meter maintenance personnel will be assigned to repair or replace the meters that are not assigned to any node; if the meter box abnormality type is parameter abnormality, the power difference threshold value will be increased by 1%, and the abnormality index will be recalculated. If the abnormality type is still parameter abnormality, it will continue to be increased by 1% on the basis of the 1% increase until there is no abnormality type or the abnormality type is meter abnormality.

[0010] Preferably, a cyclic iterative listening and distinguishing device comprises: Power module: used to provide power; Acquisition module: used to collect the carrier signal of each meter and the electric energy of each node; Analysis module: used to analyze the collected carrier signal to obtain the power consumption corresponding to each meter; Iteration module: used to perform iterative steps based on the power consumption of each meter and the electric energy of each node to determine the connected meter of each node; Fault module: used to determine the abnormal type of the meter box based on the attribution results of the electricity meters under each node and formulate corresponding strategies.

[0011] Compared with the prior art, the present invention has the following beneficial effects: The present invention obtains the carrier signals of all electric meters and analyzes them to obtain the power consumption of each electric meter; obtains the marking status of the electric meter numbered i, and if it is not marked, marks and updates the accumulated power of the current node, calculates the absolute value of the difference between the accumulated power and the electric energy of the current node as the power difference, and compares it with the preset power difference threshold. If the power difference meets the standard, it means that the electric meter under the current node is confirmed, and the mark is retained to proceed to the judgment of the next node; if it does not meet the standard, then based on the relationship between the accumulated power and the electric energy, it is determined whether the electric meter belongs to the current node or the mark is cancelled. By repeating the iterative process, it is possible to accurately determine the electric meter corresponding to each node in the meter box; The present invention obtains the classified electricity of each node, and takes the absolute value of the difference between it and the electric energy corresponding to the node to obtain the classified electricity difference value, and obtains the number of abnormal nodes by presetting the classified electricity difference value threshold and comparing the threshold value; obtains the class deficiency by the classified electricity sum and the missing electricity sum, fuses the class deficiency and the number of abnormal nodes to obtain the abnormal index, determines the abnormal type according to the size of the abnormal index, and formulates different strategies based on different abnormal types, which can accurately locate the root cause of the fault and improve the efficiency and reliability of power management. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0013] Figure 1 This is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0014] like Figure 1 As shown, a cyclic iterative listening and distinguishing method includes the following steps: S1: Obtain the carrier signals of all electricity meters, analyze the carrier signals, obtain the corresponding power consumption of all electricity meters, and number each electricity meter. The number is represented by i, i = 1, 2...n, and n represents the total number of electricity meters; Obtain the electrical energy of each node in the meter box and number each node. The number is represented by r, where r = 1, 2...k, and k represents the total number of nodes. S1-1: Analyze the collected carrier signal of the electricity meter and determine the modulation mode of the electricity meter; Preprocessing multiple carrier signals of known modulation modes, obtaining signal features of the preprocessed carrier signals, normalizing the obtained signal features, correlating the normalized signal features with the modulation modes of the corresponding carrier signals to obtain a model data set, and using the model data set to train a convolutional neural network model to obtain a modulation classification model; Collect the carrier signal of the electric meter, use the same method to obtain the signal characteristics corresponding to the electric meter, input the signal characteristics corresponding to the electric meter into the modulation classification model, and thus obtain the modulation mode corresponding to the electric meter; Specifically, the purpose of normalizing the acquired features is to eliminate the influence of factors such as different signal amplitudes and powers on the signal features. The high-order statistics can be divided by the power of the signal or other relevant normalization factors to achieve normalization of the features. Specifically, preprocessing includes filtering and sampling, and signal characteristics include higher-order statistics such as third-order moments and fourth-order moments; S1-2: Select the corresponding demodulation algorithm according to the modulation mode of the meter, restore the carrier signal to a digital signal, process the digital signal, and obtain digital data; In detail, the modulation methods of the electricity meter include frequency shift keying modulation, phase shift keying modulation, etc. Each modulation method has a corresponding demodulation algorithm. For example, the demodulation algorithm corresponding to frequency shift keying modulation is envelope detection method, and the demodulation algorithm corresponding to phase shift keying modulation is coherent demodulation method. In detail, the collected digital signals can be processed using a digital signal processing chip or software algorithm to obtain digital data; Specifically, before transmitting data, the meter modulates the data representing the actual physical quantity (current, voltage, pulse number, etc.) through a specific modulation method so that it can be transmitted on the transmission medium (such as power lines, wireless channels, etc.). Digital data is the result of encoding and combining the actual physical quantity using a specific coding format; S1-3: Obtain the communication protocol of the electric meter, parse the digital data according to the frame format of the communication protocol, and obtain the electric quantity data; In detail, the power data includes: voltage, current, power and number of power pulses; Specifically, different communication protocols define specific data frame start and end flags. First, find the start and end flags of the data frame to determine a complete frame of data. Then, extract the power data according to the field order specified by the protocol. S1-4: Preprocess the electricity data to obtain standard electricity data, and obtain the electricity consumption corresponding to the meter based on the specific type of the standard electricity data; In detail, the preprocessing includes filtering and denoising, and the standard voltage data includes standard voltage, standard current, standard power, and standard number of electric energy pulses; Specifically, the process of obtaining the power consumption of the meter based on the standard power data is as follows: a curve of the standard power changing with time is drawn in a rectangular coordinate system, and a function fitting is performed to obtain a power function, and the power function is integrated to obtain the power consumption corresponding to the meter; The process of obtaining the meter's corresponding power consumption according to the standard voltage and standard current is as follows: multiplying the standard voltage by the standard current to obtain the corresponding power value, and then referring to the standard power data to obtain the meter's corresponding power consumption to obtain the meter's corresponding power consumption; The process of obtaining the corresponding power consumption of the meter according to the number of standard power pulses is as follows: dividing the number of standard power pulses by the pulse constant corresponding to the meter, thereby obtaining the corresponding power consumption of the meter; In detail, the electrical energy of a node refers to the sum of the electricity consumption of all meters attributed to the node; S2: Obtain the marking status of the meter numbered i. If it is not marked, mark the meter numbered i and update the accumulated power of the node numbered r. Obtain the absolute value of the difference between the accumulated power of the node numbered r after the update and the power of the node as the power difference of the node. Preset the power difference threshold. If the power difference is less than or equal to the power difference threshold, proceed to step S3. Otherwise, proceed to step S4. If it is marked, update i and execute step S2 again. In detail, the specific steps for updating the accumulated power are as follows: Use the formula sum=sum+val(i) to update the accumulated power of the node, where sum represents the accumulated power of the node and val(i) represents the power consumption of the meter numbered i. The meaning of the formula is to add the accumulated power of the node to the power consumption of the meter numbered i as the new accumulated power of the node; Specifically, i is updated using the formula i=i+1, which means increasing i by one unit; Specifically, each time the electricity meter connected to the next node is obtained, the initial value of sum is reset to 0 and the initial value of i is reset to 1; Specifically, when the value of i is (n+1), the iteration stops; S3: retain the marking status of all marked meters, update r and initialize the value of i to 1, and re-enter step S2; Specifically, when the power difference corresponding to a node is less than the power difference threshold, it means that the sum of the power consumption of all the meters under the node is exactly equal to the power corresponding to the node. All the meters under the node have been found, so the iteration process for the node can be terminated early. In detail, the meaning of updating r is the same as that of updating i; Specifically, when all the connected meters of a node are determined and the connected meter of the next node is about to be acquired, the marking status of the meter belonging to the node will not disappear when the connected meter of the next node is acquired; S4: If the accumulated power of the node numbered r is less than the power of the node, the meter numbered i is assigned to the node numbered r, and i is updated, and the process re-enters step S2; if the accumulated power of the node numbered r is greater than the power of the node, the process proceeds to step S5; S5: cancel the mark of the electric meter numbered i, update i, and re-enter step S2; Specifically, if the accumulated energy of a node is greater than the energy of the node and the energy difference is greater than the energy difference threshold, it means that the result of updating the accumulated energy of the node using the meter numbered i has caused energy overflow. In this case, the meter numbered i cannot be assigned to the node. S6: Determine the abnormality type of the meter box based on the ownership results of the electricity meters connected to each node, and formulate corresponding strategies based on the abnormality type of the meter box; Get the sum of the electricity consumption of the meters under each node as the classified electricity consumption corresponding to the node. Obtain the absolute value of the difference between the classified power and the electric energy of the node as the classified power difference value, mark the node according to the comparison result of the classified power difference value and the power difference threshold, record the marked node as an abnormal node, and obtain the number of abnormal nodes as the number of abnormal nodes; Specifically, if the classified power difference value of a node is greater than the power difference threshold, the node is marked as an abnormal node, otherwise, the node is not marked; Specifically, if the classified electricity difference value of a node is greater than the electricity difference threshold, it means that the downstream electricity meter under the node has not been completely found; Obtain the sum of the classified electricity differences of all abnormal nodes as the missing electricity sum, obtain the sum of the electricity consumption of all meters not attributed to any node as the classified electricity sum, and obtain the absolute value of the difference between the missing electricity sum and the classified electricity sum as the class missing difference; If the number of abnormal nodes is not 0, the number of abnormal nodes and the class deficiency are fused to obtain the abnormal index. The abnormal index threshold is preset, and the abnormal level of the meter box is determined based on the comparison result between the abnormal index and the abnormal index threshold. If the number of abnormal nodes is 0, no processing is performed. Specifically, fusion processing refers to a data processing method for combining data from multiple dimensions into one data to avoid the randomness caused by a single factor. In this embodiment, after normalizing the number of abnormal nodes and the class deficiency, weighted influence factors corresponding to the number of abnormal nodes and the class deficiency are preset, and the number of abnormal nodes and the class deficiency are weighted based on the preset weighted influence factors to obtain an abnormal index. Specifically, if the abnormality index is less than or equal to the abnormality index threshold, the abnormality type of the meter box is determined to be an electric meter abnormality; otherwise, the abnormality type of the meter box is determined to be a parameter abnormality; Specifically, if the abnormal indication is less than or equal to the abnormal index threshold, it means that there may be a problem with the metering function of individual meters; if the abnormal indication is greater than the abnormal index threshold, it means that the power difference threshold is set too small, resulting in a large number of meters not being able to find the corresponding nodes; Specifically, if the meter box anomaly is a meter anomaly, professional meter maintenance personnel will be assigned to repair or replace the meter that is not assigned to any node. If the meter box anomaly is a parameter anomaly, the power difference threshold will be increased by 1%, and the anomaly index will be recalculated. If the anomaly is still a parameter anomaly, the threshold will be increased by another 1% until there is no anomaly or the anomaly is a meter anomaly. A cyclic iterative listening and distinguishing device, comprising: Power module: used to provide power; Acquisition module: used to collect the carrier signal of each meter and the electric energy of each node; Analysis module: used to analyze the collected carrier signal to obtain the power consumption corresponding to each meter; Iteration module: used to perform iterative steps based on the power consumption of each meter and the electric energy of each node to determine the connected meter of each node; Fault module: used to determine the abnormal type of the meter box based on the attribution results of the electricity meters under each node and formulate corresponding strategies.

[0015] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as a preferred embodiment as above, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to equivalent embodiments using the technical contents disclosed above without departing from the scope of the technical solution of the present invention. However, any modification or equivalent replacement of the above embodiments made according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still falls within the scope of the technical solution of the present invention.

Claims

1. A cyclic iterative listening and distinguishing method, characterized in that: The following steps are involved: S1: Obtain the carrier signals of all electricity meters, analyze the carrier signals, obtain the corresponding power consumption of all electricity meters, and number each electricity meter. The number is represented by i, i = 1, 2...n, and n represents the total number of electricity meters. Obtain the electric energy of each node in the meter box and number each node. The number is represented by r, r = 1, 2...k, and k represents the total number of nodes. S2: Obtain the marking status of the meter numbered i. If it is not marked, mark the meter numbered i and update the accumulated power of the node numbered r. Obtain the absolute value of the difference between the accumulated power of the node numbered r after the update and the power of the node as the power difference of the node. Preset the power difference threshold. If the power difference is less than or equal to the power difference threshold, proceed to step S3. Otherwise, proceed to step S4. If it is marked, update i and execute step S2 again. S3: retain the marking status of all marked meters, update r and initialize the value of i to 1, and re-enter step S2; S4: If the accumulated power of the node numbered r is less than the power of the node, the meter numbered i is assigned to the node numbered r, and i is updated, and the process re-enters step S2; if the accumulated power of the node numbered r is greater than the power of the node, the process proceeds to step S5; S5: cancel the mark of the electric meter numbered i, update i, and re-enter step S2; S6: According to the attribution results of the electric meters connected to each node, determine the abnormal type of the meter box, and formulate corresponding strategies according to the abnormal type of the meter box.

2. The iterative listening and distinguishing method according to claim 1, characterized in that: The process of analyzing the carrier signal and obtaining the corresponding power consumption of all meters is as follows: Analyze the collected carrier signal of the electric meter to determine the modulation mode of the electric meter; According to the modulation mode of the electric meter, a corresponding demodulation algorithm is selected to restore the carrier signal to a digital signal, and the digital signal is processed to obtain digital data; Obtain the communication protocol of the electric meter, parse the digital data according to the frame format of the communication protocol, and obtain the electric quantity data; The electricity data is preprocessed to obtain standard electricity data, and the electricity consumption corresponding to the meter is obtained according to the specific type of the standard electricity data.

3. The iterative listening and distinguishing method according to claim 2, characterized in that: The process of analyzing the collected carrier signal of the meter and determining the modulation mode of the meter is as follows: Preprocessing multiple carrier signals of known modulation modes, and then obtaining signal characteristics of the preprocessed carrier signals; Normalize the acquired signal features, and associate the normalized signal features with the modulation mode of the corresponding carrier signal to obtain a model data set; The convolutional neural network model is trained using the model data set to obtain a modulation classification model; The carrier signal of the electric meter is collected, the corresponding signal characteristics are obtained according to the carrier signal of the electric meter, the signal characteristics corresponding to the electric meter are input into the modulation classification model, and the modulation mode corresponding to the electric meter is obtained.

4. The iterative listening and distinguishing method according to claim 3, characterized in that: Based on the attribution results of the electricity meters connected to each node, the process of determining the abnormal type of the meter box is as follows: Get the sum of the electricity consumption of the meters under each node as the classified electricity consumption corresponding to the node. Obtain the absolute value of the difference between the classified power and the electric energy of the node as the classified power difference value, mark the node according to the comparison result of the classified power difference value and the power difference threshold, record the marked node as an abnormal node, and obtain the number of abnormal nodes as the number of abnormal nodes; Obtain the sum of the classified electricity differences of all abnormal nodes as the missing electricity sum, obtain the sum of the electricity consumption of all meters not attributed to any node as the classified electricity sum, and obtain the absolute value of the difference between the missing electricity sum and the classified electricity sum as the class missing difference; If the number of abnormal nodes is not 0, the number of abnormal nodes and the class deficiency are fused to obtain the abnormal index, and the abnormal index threshold is preset. The abnormal level of the meter box is determined based on the comparison result between the abnormal index and the abnormal index threshold; if the number of abnormal nodes is 0, no processing is performed.

5. The iterative listening and distinguishing method according to claim 4, characterized in that: Based on the comparison results of the abnormality index and the abnormality index threshold, the process of determining the abnormality level of the meter box is as follows: If the abnormality index is less than or equal to the abnormality index threshold, the abnormality type of the meter box is determined to be an electric meter abnormality; otherwise, the abnormality type of the meter box is determined to be a parameter abnormality.

6. The iterative listening and distinguishing method according to claim 5, characterized in that: The process of formulating corresponding strategies according to the abnormal type of the meter box is as follows: If the meter box abnormality type is meter abnormality, professional meter maintenance personnel will be assigned to repair or replace the meters that are not assigned to any node; if the meter box abnormality type is parameter abnormality, the power difference threshold value will be increased by 1%, and the abnormality index will be recalculated. If the abnormality type is still parameter abnormality, it will continue to be increased by 1% on the basis of the 1% increase until there is no abnormality type or the abnormality type is meter abnormality.

7. A device for the iterative interception and resolution method according to any one of claims 1 to 6, characterized in that: include: Power module: used to provide power; Acquisition module: used to collect the carrier signal of each meter and the electric energy of each node; Analysis module: used to analyze the collected carrier signal to obtain the power consumption corresponding to each meter; Iteration module: used to perform iterative steps based on the power consumption of each meter and the electric energy of each node to determine the connected meter of each node; Fault module: used to determine the abnormal type of the meter box based on the attribution results of the electricity meters under each node and formulate corresponding strategies.

Images