Data interaction system of concentrator and simulation table
By using a data interaction system between the simulation meter and the test platform, the problem of communication and metering failures between the concentrator and the energy meter was solved, reducing testing costs and improving testing efficiency.
Patent Information
- Application Number
- CN202511280634.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-09
- Publication Date
- 2025-11-14
AI Technical Summary
Existing concentrators and electricity meters suffer from communication and metering malfunctions, resulting in inaccurate data and high testing costs. Therefore, a low-cost and efficient testing method is needed.
Simulated meters are used instead of real meters. A simulated concentrator is configured and a simulated meter is created through a test platform to simulate interactive data under different task scenarios. The simulated data is then analyzed to evaluate the concentrator's performance.
This enables a reduction in testing costs, an increase in testing efficiency, and an accurate assessment of concentrator performance without the use of physical electricity meters.
Smart Images
Figure CN120948939A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of concentrator testing technology, specifically a data interaction system between a concentrator and a simulation table. Background Technology
[0002] In power systems, concentrators and electricity meters play key roles. Concentrators are responsible for collecting electricity consumption data from multiple electricity meters and uploading it to the main station system, serving as the hub for data transmission. Electricity meters, on the other hand, undertake the basic task of measuring users' electricity consumption.
[0003] However, current concentrators and electricity meters face numerous problems in actual operation. On the one hand, concentrators may fail to accurately collect electricity meter data or upload incorrect data due to communication failures, software vulnerabilities, etc., affecting the power sector's judgment of users' electricity consumption. On the other hand, electricity meters are affected by environmental factors and their own aging, which may lead to deviations in metering data. Furthermore, testing the performance of concentrators often requires a large number of electricity meters, resulting in high costs.
[0004] How to use simulated meters to replace real meters for testing, thereby significantly reducing testing costs and improving testing efficiency, is a problem we need to solve. To this end, we now provide a data interaction system between a concentrator and a simulated meter. Summary of the Invention
[0005] The purpose of this invention is to provide a data interaction system between a concentrator and a simulation table.
[0006] The objective of this invention can be achieved through the following technical solution: a data interaction system between a concentrator and a simulated table, comprising: The testing platform is used to create task scenarios and set up simulation tables based on the content of the task scenarios; The interaction module is used to acquire the interaction data between the concentrator and the simulation table; The analysis module is used to analyze the obtained interaction data and determine the concentrator test performance of the concentrator and simulation table in the corresponding task scenario based on the analysis results.
[0007] Furthermore, the testing platform includes a configuration unit and a creation unit; The configuration unit is used to configure the basic parameters and task scenarios of the concentrator to be tested. The task scenarios include simulating table data concurrency, simulating table offline, and simulating table failure. The creation unit is used by users to create simulated tables and configure simulation parameters for the simulated tables. The simulation parameters include the number of simulated tables, the communication protocol of the simulated tables, and the meter behavior, which includes normal status, communication abnormality, and operation abnormality. After configuring the basic parameters and task scenarios of the concentrator through the configuration unit, the concentrator to be tested is connected to the test platform to perform the test.
[0008] Furthermore, the process by which the interaction module acquires the interaction data between the concentrator and the simulation table is as follows: Based on the data acquisition cycle of the concentrator to be tested, periodic data acquisition instructions are generated, and the generated data acquisition instructions are mapped into the simulated concentrator. The simulation concentrator sends data acquisition instructions to each simulation table. Based on its own metering behavior, the simulation table generates corresponding simulation operation data according to the received instructions and uploads the simulation operation data to the simulation concentrator. The simulation concentrator then imports the simulation operation data uploaded by each simulation table into the concentrator to be tested. The interaction module obtains the processing parameters of the concentrator under test on the simulated running data and the simulation process parameters of the concentrator, thereby obtaining the interaction data corresponding to the data acquisition cycle.
[0009] Furthermore, the analysis module analyzes the obtained interaction data, and the process of determining the concentrator's performance and simulation table's performance in the corresponding task scenario based on the analysis results is as follows: When the concentrator to be tested is configured with a task scenario that simulates concurrent table data: Different task tiers are generated, and each task tier corresponds to a different number of simulation tables; Simulation operation data is sent to the concentrator simultaneously based on the simulation table corresponding to each task tier. The simulation concentrator generates corresponding simulation concentrator state variables based on the simulation operation data sent by each simulation table. The simulation concentrator state variables include simulation response time and simulation error rate. The concentrator under test then processes the simulated running data sent by the simulation table and obtains the state quantity of the concentrator under test after all the simulated running data has been processed. The state quantity of the concentrator under test includes response time and error rate. Based on the state variables of the concentrator under test and the simulated concentrator state, the processing performance evaluation coefficients for the corresponding task tiers are obtained. 1; when ≥q t If q is positive, it means the concentrator under test has satisfactory data concurrency processing capabilities; otherwise, it means it is unsatisfactory. t This is the evaluation threshold for the corresponding task tier in a scenario where concurrent table data is processed.
[0010] Furthermore, when the concentrator under test is configured with a task scenario simulating a table disconnection: Generate different task tiers, each task tier corresponding to a different number of communication failure disconnection simulation tables; The simulation concentrator makes communication connection calls to each disconnected simulation table, and records the number of calls and the call results. The communication success rate is obtained based on the number of calls and the call results. The concentrator under test then makes communication connection calls to each analog table, and records the number of calls and the call results to obtain the corresponding communication success rate. Based on the communication success rate between the simulated concentrator and the concentrator under test, the corresponding communication performance evaluation coefficient is obtained. : when ≥e t If the signal is positive, it indicates that the communication performance of the concentrator under test is qualified; otherwise, it indicates that it is unqualified. t This is the evaluation threshold for the corresponding task tier in a scenario where the table goes offline.
[0011] Furthermore, when the concentrator under test is configured with a simulated table failure scenario: Generate different task tiers, each task tier corresponding to a different number of fault simulation tables of operational anomalies; Simulation data is uploaded from the fault simulation table, and the simulation concentrator marks abnormal data in the simulation data. The simulated operation data is then uploaded to the concentrator under test, where abnormal data is marked. The range and location of the abnormal data marked by the concentrator under test are then compared with the range and location of the abnormal data marked by the simulated concentrator. Based on the comparison results, the labeling accuracy of the concentrator under test for the abnormal data in each fault simulation table is obtained. The labeling accuracy of the concentrator under test for the abnormal data in each fault simulation table is summarized, and the corresponding mean is obtained as the anomaly identification performance evaluation coefficient of the concentrator under test. ; when ≥r t If the result is positive, it indicates that the concentrator under test has satisfactory abnormal data recognition performance; otherwise, it indicates that it is unsatisfactory. Where r t This is the evaluation threshold for the corresponding task tier in a task scenario simulating table failure.
[0012] Furthermore, based on the obtained processing performance evaluation coefficients, communication performance evaluation coefficients, and anomaly detection performance evaluation coefficients, the comprehensive evaluation coefficient Zp of the concentrator under test is obtained, where: ; Where k1, k2, and k2 are weighting coefficients, and k1+k2+k2=1; The processing performance evaluation coefficient, communication performance evaluation coefficient, anomaly detection performance evaluation coefficient, and comprehensive evaluation coefficient are output as the test results of the concentrator under test.
[0013] Compared with the prior art, the beneficial effects of the present invention are: By configuring corresponding simulated concentrators and creating simulated meters within the testing platform according to testing requirements, the concentrator under test can be simulated under different task scenarios. By simulating different meter readings, the performance of the concentrator under different task scenarios can be simulated, thereby obtaining corresponding performance evaluation results. This allows the performance testing of concentrators to be completed without physical electricity meters, greatly reducing the cost of testing physical electricity meters and improving testing efficiency. Attached Figure Description
[0014] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.
[0015] Figure 1 This is a schematic diagram of the present invention. Detailed Implementation
[0016] like Figure 1 As shown, a data interaction system between a concentrator and a simulated table includes: The testing platform is used to create task scenarios and set up simulation tables based on the content of the task scenarios; The interaction module is used to acquire the interaction data between the concentrator and the simulation table; The analysis module is used to analyze the obtained interaction data and determine the concentrator test performance of the concentrator and simulation table in the corresponding task scenario based on the analysis results.
[0017] It should be noted that, in the specific implementation process, the test platform includes a configuration unit and a creation unit; The configuration unit is used to configure the basic parameters and task scenarios of the concentrator under test. It should be noted that users can perform a one-to-one simulation of the actual parameters of the concentrator under test in the configuration unit. By selecting parameter configurations that are consistent with the actual parameters of the concentrator, a simulated concentrator corresponding to the concentrator can be built in the test platform. The basic parameters of the concentrator are the applicable communication method, communication rate, data acquisition cycle and concurrent processing capability. The task scenarios include simulated table data concurrency, simulated table offline, and simulated table failure. The creation unit is used by users to create simulated tables and configure simulation parameters for the simulated tables. The simulation parameters include the number of simulated tables, the communication protocol of the simulated tables, and the meter behavior, which includes normal status, communication abnormality, and operation abnormality. After configuring the basic parameters and task scenarios of the concentrator through the configuration unit, the concentrator to be tested is connected to the test platform to perform the test.
[0018] It should be noted that the specific process by which the interaction module obtains the interaction data between the concentrator and the simulation table is as follows: Based on the data acquisition cycle of the concentrator to be tested, periodic data acquisition instructions are generated, and the generated data acquisition instructions are mapped into the simulated concentrator. The simulation concentrator sends data acquisition instructions to each simulation table. Based on its own metering behavior, the simulation table generates corresponding simulation operation data according to the received instructions and uploads the simulation operation data to the simulation concentrator. The simulation concentrator then imports the simulation operation data uploaded by each simulation table into the concentrator to be tested. The interaction module obtains the processing parameters of the concentrator under test on the simulated running data and the simulation process parameters of the concentrator, thereby obtaining the interaction data corresponding to the data acquisition cycle.
[0019] It should be noted that the analysis module analyzes the obtained interaction data and determines the concentrator's performance in the corresponding task scenario based on the analysis results. The specific process is as follows: When the concentrator to be tested is configured with a task scenario that simulates concurrent table data: Different task tiers are generated, and each task tier corresponds to a different number of simulation tables; Simulation operation data is sent to the concentrator simultaneously based on the simulation table corresponding to each task tier. The simulation concentrator generates corresponding simulation concentrator state variables based on the simulation operation data sent by each simulation table. The simulation concentrator state variables include simulation response time and simulation error rate. The concentrator under test then processes the simulated running data sent by the simulation table and obtains the state quantity of the concentrator under test after all the simulated running data has been processed. The state quantity of the concentrator under test includes response time and error rate. Based on the state variables of the concentrator under test and the simulated concentrator state, the processing performance evaluation coefficients for the corresponding task tiers are obtained, denoted as follows: 1, of which: ; in, Indicates the simulation response time of the analog concentrator. Indicates the response time of the analog concentrator. Indicates the analog error rate of the analog concentrator. Indicates the error rate of the analog concentrator. Indicates time threshold, Indicates the error rate threshold, k is a proportionality coefficient, and k depends on the number of simulation tables corresponding to the corresponding task tier, showing a positive correlation. When the concentrator to be tested is configured with a simulated table disconnection scenario: Generate different task tiers, each task tier corresponding to a different number of disconnection simulation tables; The analog concentrator initiates communication connection calls to each disconnected simulation table, recording the number of calls and the call results. The communication success rate is obtained based on the number of calls and the call results. It should be noted that the communication success rate is inversely proportional to the number of calls. For example, if there are 10 calls in total and the 10th call is successful, the communication success rate is 10%. If there are 5 calls in total and the 5th call is successful, the communication success rate is 20%. The concentrator under test then makes communication connection calls to each analog table, and records the number of calls and the call results to obtain the corresponding communication success rate. Based on the communication success rate between the simulated concentrator and the concentrator under test, the corresponding communication performance evaluation coefficient is obtained, denoted as . ,in: ; in, This indicates the communication success rate of the concentrator under test to the offline simulation table. This represents the communication success rate of the analog concentrator to the offline analog table, where n represents the total number of offline analog tables. When the concentrator to be tested is configured with a simulated table failure scenario: Different task tiers are generated, and each task tier corresponds to a different number of fault simulation tables; Simulation data is uploaded from the fault simulation table, and the simulation concentrator marks abnormal data in the simulation data. The simulated running data is then uploaded to the concentrator under test, where it marks abnormal data. The range and location of the abnormal data marked by the concentrator under test are then compared with those marked by the simulated concentrator. It should be noted that, by default, the simulated concentrator can mark all abnormal data in the simulated running data with 100% accuracy. Based on the comparison results, the labeling accuracy of the concentrator under test for the abnormal data in each fault simulation table is obtained. The labeling accuracy of the concentrator under test for the abnormal data in each fault simulation table is summarized, and the corresponding mean is obtained as the anomaly identification performance evaluation coefficient of the concentrator under test, denoted as . ; Set different evaluation thresholds for different task scenarios and task tiers; The obtained performance evaluation coefficients are compared with the corresponding evaluation thresholds to obtain the corresponding comparison results; when ≥q t If the result is positive, it means that the data concurrency processing capability of the concentrator under test is qualified; otherwise, it means that it is unqualified. when ≥e t If the value is 0, it means that the communication performance of the concentrator under test is qualified; otherwise, it means that it is unqualified. when ≥r t If the result is positive, it indicates that the concentrator under test has satisfactory abnormal data recognition performance; otherwise, it indicates that it is unsatisfactory. Where q t e t r t The evaluation thresholds for each task tier are respectively set for the task scenarios of simulated table data concurrency, simulated table offline, and simulated table failure. Based on the obtained performance evaluation coefficients, the comprehensive evaluation coefficient of the concentrator under test is obtained, denoted as Zp, where: ; Where k1, k2, and k2 are weighting coefficients, and k1+k2+k2=1; The processing performance evaluation coefficient, communication performance evaluation coefficient, anomaly detection performance evaluation coefficient, and comprehensive evaluation coefficient are output as the test results of the concentrator under test.
[0020] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any modifications or equivalent substitutions made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.
Claims
1. A data interaction system between a concentrator and an analog table, characterized in that, include: The testing platform is used to create task scenarios and set up simulation tables based on the content of the task scenarios; The interaction module is used to acquire the interaction data between the concentrator and the simulation table; The analysis module is used to analyze the obtained interaction data and determine the concentrator test performance of the concentrator and simulation table in the corresponding task scenario based on the analysis results.
2. The data interaction system between a concentrator and an analog table according to claim 1, characterized in that, The testing platform includes a configuration unit and a creation unit; The configuration unit is used to configure the basic parameters and task scenarios of the concentrator to be tested. The task scenarios include simulating table data concurrency, simulating table offline, and simulating table failure. The creation unit is used by users to create simulated tables and configure simulation parameters for the simulated tables. The simulation parameters include the number of simulated tables, the communication protocol of the simulated tables, and the meter behavior, which includes normal status, communication abnormality, and operation abnormality. After configuring the basic parameters and task scenarios of the concentrator through the configuration unit, the concentrator to be tested is connected to the test platform to perform the test.
3. The data interaction system between a concentrator and an analog table according to claim 2, characterized in that, The process by which the interaction module obtains the interaction data between the concentrator and the simulation table is as follows: Based on the data acquisition cycle of the concentrator to be tested, periodic data acquisition instructions are generated, and the generated data acquisition instructions are mapped into the simulated concentrator. The simulation concentrator sends data acquisition instructions to each simulation table. Based on its own metering behavior, the simulation table generates corresponding simulation operation data according to the received instructions and uploads the simulation operation data to the simulation concentrator. The simulation concentrator then imports the simulation operation data uploaded by each simulation table into the concentrator to be tested. The interaction module obtains the processing parameters of the concentrator under test on the simulated running data and the simulation process parameters of the concentrator, thereby obtaining the interaction data corresponding to the data acquisition cycle.
4. The data interaction system between a concentrator and an analog table according to claim 3, characterized in that, The analysis module analyzes the obtained interaction data and determines the concentrator's performance in the corresponding task scenario based on the analysis results. When the concentrator to be tested is configured with a task scenario that simulates concurrent table data: Different task tiers are generated, and each task tier corresponds to a different number of simulation tables; Simulation operation data is sent to the concentrator simultaneously based on the simulation table corresponding to each task tier. The simulation concentrator generates corresponding simulation concentrator state variables based on the simulation operation data sent by each simulation table. The simulation concentrator state variables include simulation response time and simulation error rate. The concentrator under test then processes the simulated running data sent by the simulation table and obtains the state quantity of the concentrator under test after all the simulated running data has been processed. The state quantity of the concentrator under test includes response time and error rate. Based on the state variables of the concentrator under test and the simulated concentrator state, the processing performance evaluation coefficients for the corresponding task tiers are obtained. 1; when ≥q t If q is positive, it means the concentrator under test has satisfactory data concurrency processing capabilities; otherwise, it means it is unsatisfactory. t This is the evaluation threshold for the corresponding task tier in a scenario where concurrent table data is processed.
5. The data interaction system between a concentrator and an analog table according to claim 4, characterized in that, When the concentrator to be tested is configured with a simulated table disconnection scenario: Generate different task tiers, each task tier corresponding to a different number of communication failure disconnection simulation tables; The simulation concentrator makes communication connection calls to each disconnected simulation table, and records the number of calls and the call results. The communication success rate is obtained based on the number of calls and the call results. The concentrator under test then makes communication connection calls to each analog table, and records the number of calls and the call results to obtain the corresponding communication success rate. Based on the communication success rate between the simulated concentrator and the concentrator under test, the corresponding communication performance evaluation coefficient is obtained. : when ≥e t If the signal is positive, it indicates that the communication performance of the concentrator under test is qualified; otherwise, it indicates that it is unqualified. t This is the evaluation threshold for the corresponding task tier in a scenario where the table goes offline.
6. The data interaction system between a concentrator and an analog table according to claim 5, characterized in that, When the concentrator to be tested is configured with a simulated table failure scenario: Generate different task tiers, each task tier corresponding to a different number of fault simulation tables of operational anomalies; Simulation data is uploaded from the fault simulation table, and the simulation concentrator marks abnormal data in the simulation data. The simulated operation data is then uploaded to the concentrator under test, where abnormal data is marked. The range and location of the abnormal data marked by the concentrator under test are then compared with the range and location of the abnormal data marked by the simulated concentrator. Based on the comparison results, the labeling accuracy of the concentrator under test for the abnormal data in each fault simulation table is obtained. The labeling accuracy of the concentrator under test for the abnormal data in each fault simulation table is summarized, and the corresponding mean is obtained as the anomaly identification performance evaluation coefficient of the concentrator under test. ; when ≥r t If the result is positive, it indicates that the concentrator under test has satisfactory abnormal data recognition performance; otherwise, it indicates that it is unsatisfactory. Where r t This is the evaluation threshold for the corresponding task tier in a task scenario simulating table failure.
7. The data interaction system between a concentrator and an analog table according to claim 6, characterized in that, Based on the obtained processing performance evaluation coefficient, communication performance evaluation coefficient, and anomaly detection performance evaluation coefficient, the comprehensive evaluation coefficient Zp of the concentrator under test is obtained, where: ； Where k1, k2, and k2 are weighting coefficients, and k1+k2+k2=1; The processing performance evaluation coefficient, communication performance evaluation coefficient, anomaly detection performance evaluation coefficient, and comprehensive evaluation coefficient are output as the test results of the concentrator under test.