A verification method and system for reliable tripping of electric energy meters

Abstract

The present invention provides a method and system for verifying the reliable tripping of an electric energy meter, which relates to the technical field of electric energy meters. The method for verifying the reliable tripping of an electric energy meter comprises: obtaining electric energy meter detection parameters; performing parameter analysis on the electric energy meter detection parameters using an initial monitoring model to obtain analysis results; fine-tuning the initial monitoring model based on the analysis results to obtain an updated model; updating a trip threshold monitoring table based on the updated model; wherein the trip threshold monitoring table includes multiple trip monitoring thresholds and a trip mode formed by the trip monitoring thresholds; selecting a corresponding trip mode to control tripping based on the electric energy meter detection parameters and the trip threshold monitoring table; generating a trip result during the tripping process based on a feedback signal of the tripping process; and comparing the trip result with the trip mode. The verification method and system provided by the present invention can effectively ensure the reliability of the trip mode selection while also ensuring the reliability of the tripping process.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy meters, and in particular to a verification method and system for reliable tripping of electric energy meters. Background Art

[0002] Verifying reliable tripping of energy meters is a crucial step in power system operation and safety management. It not only impacts the stable operation of the power system but also directly affects the safe use of electricity by users and the economic benefits of power companies.

[0003] In the existing process of monitoring the tripping of the electricity meter, the tripping of the electricity meter can only be monitored by several pre-set parameter thresholds. However, if factors such as the operating environment of the electricity meter and the tripping device change, the rationality and accuracy of the setting of the corresponding parameter thresholds will be affected to a certain extent, thereby greatly reducing the reliability of the tripping of the electricity meter and posing certain risks in the use of the electricity meter. Summary of the Invention

[0004] In view of the shortcomings of the prior art described above, the purpose of the present invention is to provide a verification method and system for the reliable tripping of an electric energy meter, which is used to solve the problem in the prior art that during the process of monitoring the tripping of an electric energy meter, the conventional threshold monitoring method will cause the reliability of the electric energy meter tripping to be greatly reduced, and there will be certain risks in the use of the electric energy meter.

[0005] To achieve the above-mentioned purpose and other related purposes, the present invention provides a verification method for reliable tripping of an electric energy meter, comprising: obtaining detection parameters of the electric energy meter; performing parameter analysis on the detection parameters of the electric energy meter through an initial monitoring model to obtain analysis results; fine-tuning the initial monitoring model according to the analysis results to obtain an updated model; updating a tripping threshold monitoring table according to the updated model; wherein the tripping threshold monitoring table includes multiple tripping monitoring thresholds and a tripping mode formed by the tripping monitoring thresholds; selecting a corresponding tripping mode according to the detection parameters of the electric energy meter and the tripping threshold monitoring table to control tripping; during the tripping process, generating a tripping result according to a feedback signal of the tripping process; and comparing the tripping result with the tripping mode to determine the accuracy of the tripping.

[0006] In one embodiment of the present invention, the initial monitoring model is a simulation model that simulates the operation process of the electric energy meter and the tripping device through preset simulation conditions, and the preset simulation conditions include multiple abnormal influencing factors; the initial monitoring model is used to perform parameter analysis on the electric energy meter detection parameters to obtain analysis results, including: based on the electric energy meter detection parameters, the initial monitoring model is used to perform simulation deduction using the preset simulation conditions to simulate and obtain the deduction parameters closest to the electric energy meter detection parameters and the formation process data of the deduction parameters; based on the electric energy meter detection parameters, the deduction parameters and the formation process data of the deduction parameters, to obtain the analysis results.

[0007] In one embodiment of the present invention, an analysis result is obtained based on the detection parameters, deduced parameters and the formation process data of the deduced parameters of the electric energy meter, including: calculating the difference between the deduced parameters and the detection parameters of the electric energy meter to obtain the parameter difference; judging whether the parameter difference exceeds the set parameter range: if so, generating an adjustment signal for the initial monitoring model, and using the adjustment signal and the parameter difference as the analysis result; if not, using the initial tripping threshold monitoring table corresponding to the initial monitoring model to select the tripping mode according to the electric energy meter detection parameters and the initial tripping threshold monitoring table to control the tripping step.

[0008] In one embodiment of the present invention, the initial monitoring model is fine-tuned according to the analysis results to obtain an updated model, including: performing an exception query on the analysis results to obtain the target influencing factors corresponding to the analysis results; and fine-tuning the initial monitoring model based on the target influencing factors to obtain an updated model.

[0009] In one embodiment of the present invention, the analysis result includes the adjustment signal of the initial monitoring model and the parameter difference between the deduced parameters obtained by deducing the initial monitoring model and the detection parameters of the electric energy meter; the target influencing factors include a positive influencing factor combination and a negative influencing factor combination; an abnormal query is performed on the analysis result to obtain the target adjustment factor corresponding to the analysis result, including: monitoring the positive and negative values ​​of the parameter difference according to the adjustment signal; when the parameter difference is monitored to be positive, a positive influencing factor combination is obtained according to the parameter difference; wherein, the positive influencing factor combination includes at least one influencing factor item that has been executed in the initial monitoring model; when the parameter difference is monitored to be negative, a negative influencing factor combination is obtained according to the parameter difference; wherein, the negative influencing factor combination includes at least one influencing factor item that has not been executed in the initial monitoring model.

[0010] In one embodiment of the present invention, the initial monitoring model is fine-tuned based on the target influencing factors to obtain an updated model, including: when the parameter difference is monitored to be positive, a corresponding weakening adjustment factor is generated according to each positive influencing factor combination, and each weakening adjustment factor is added to the initial monitoring model to re-simulate and generate positive simulation deduction parameters corresponding to each positive influencing factor combination, sort all positive simulation deduction parameters, select the weakening adjustment factor corresponding to the positive simulation deduction parameter closest to the electric energy meter detection parameter, and fine-tune the initial monitoring model to obtain an updated model; when the parameter difference is monitored to be negative, a corresponding enhancing adjustment factor is generated according to each negative influencing factor combination, and each enhancing adjustment factor is added to the initial monitoring model to re-simulate and generate negative simulation deduction parameters corresponding to each negative influencing factor combination, sort all negative simulation deduction parameters, select the enhancing adjustment factor corresponding to the negative simulation deduction parameter closest to the electric energy meter detection parameter, and fine-tune the initial monitoring model to obtain an updated model.

[0011] In one embodiment of the present invention, updating the trip threshold monitoring table according to the updated model includes: deriving all corresponding updated trip monitoring thresholds through the updated model; replacing all updated trip monitoring thresholds with invalid trip monitoring thresholds in the original trip monitoring thresholds to update the trip threshold monitoring table.

[0012] In one embodiment of the present invention, all updated trip monitoring thresholds are replaced with invalid trip monitoring thresholds in the original trip monitoring thresholds to update the trip threshold monitoring table, including: replacing all updated trip monitoring thresholds with invalid trip monitoring thresholds in the original trip monitoring thresholds to obtain all final trip monitoring thresholds that are ultimately retained; combining the final trip monitoring thresholds to obtain a threshold combination; wherein the threshold combination includes at least one final trip monitoring threshold; detecting the threshold combination through a trip combination library; wherein the trip combination library includes preset combinations and trip modes corresponding to the preset combinations; when there is a preset combination corresponding to the threshold combination in the trip combination library, retaining the threshold combination and its corresponding trip mode.

[0013] In one embodiment of the present invention, a corresponding tripping mode is selected according to the detection parameters of the electric energy meter and the tripping threshold monitoring table to control the tripping, including: selecting the corresponding tripping mode according to the detection parameters of the electric energy meter and the tripping threshold monitoring table; generating a tripping signal according to the tripping mode to control the tripping.

[0014] To achieve the above-mentioned purpose and other related purposes, the present invention also provides a verification system for reliable tripping of an electric energy meter, comprising: an acquisition unit for acquiring detection parameters of the electric energy meter; an analysis unit for performing parameter analysis on the detection parameters of the electric energy meter through an initial monitoring model to obtain analysis results; a fine-tuning unit for fine-tuning the initial monitoring model according to the analysis results to obtain an updated model; an updating unit for updating a tripping threshold monitoring table according to the updated model; wherein the tripping threshold monitoring table includes multiple tripping monitoring thresholds and a tripping mode formed by the tripping monitoring thresholds; a selection unit for selecting a corresponding tripping mode to control tripping based on the detection parameters of the electric energy meter and the tripping threshold monitoring table; a generation unit for generating a tripping result according to a feedback signal of the tripping process during the tripping process; and a comparison unit for comparing the tripping result and the tripping mode to determine the tripping accuracy.

[0015] As described above, the present invention provides a method and system for verifying reliable tripping of an electric energy meter, which has the following beneficial effects: by utilizing an initial monitoring module to analyze the electric energy meter's detection parameters, it is possible to promptly detect abnormalities in the electric energy meter's detection parameters before determining that the electric energy meter has tripped. Based on the detected abnormalities in the electric energy meter's detection parameters, the initial monitoring module can be fine-tuned, thereby obtaining an updated model for the adjusted initial monitoring module. Furthermore, the updated model can be used to update the trip threshold monitoring table, thereby regenerating the trip monitoring thresholds or trip monitoring threshold combinations that constitute the trip mode. By continuously monitoring the electric energy meter's detection parameters, the updated trip threshold monitoring table is responded to, and when the electric energy meter's detection parameters meet the corresponding trip mode in the trip threshold monitoring table, the tripping action is accurately executed. Furthermore, during the tripping process, the feedback signal during the tripping process is used to determine the tripping result when the corresponding trip mode is used to control the tripping, and the tripping result is then compared with the trip mode to verify the accuracy of the current tripping, thereby ensuring the accuracy and reliability of the tripping action in response to different safety risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic flow chart of a method for verifying reliable tripping of an electric energy meter provided by an embodiment of the present invention.

[0017] Figure 2 Shown is a structural block diagram of a verification system for reliable tripping of an electric energy meter provided by an embodiment of the present invention.

[0018] Figure 3 Shown is a structural schematic diagram of an electronic device according to an embodiment of the present invention.

[0019] Component number description

[0020] Electronic device 1; verification system 11 for reliable tripping of an electric energy meter; memory 12; processor 13; acquisition unit 111; analysis unit 112; fine-tuning unit 113; updating unit 114; selection unit 115; generation unit 116; and comparison unit 117. DETAILED DESCRIPTION

[0021] The following describes the embodiments of the present invention through specific examples. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. The details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other unless they conflict.

[0022] It should be noted that the illustrations provided in the following embodiments are merely schematic illustrations of the basic concept of the present invention. Therefore, the illustrations only show components related to the present invention and are not drawn according to the number, shape, and size of components in actual implementation. In actual implementation, the type, quantity, and proportion of each component may be changed arbitrarily, and the component layout may also be more complex.

[0023] In the following description, numerous details are discussed to provide a more thorough explanation of the embodiments of the present invention. However, it will be apparent to those skilled in the art that the embodiments of the present invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring the embodiments of the present invention.

[0024] The present invention provides a method for verifying reliable tripping of an electric energy meter. By utilizing an initial monitoring module to analyze the electric energy meter's detection parameters, the method facilitates timely detection of abnormalities in the electric energy meter's detection parameters before determining that the electric energy meter has tripped. Based on the detected abnormalities in the electric energy meter's detection parameters, the initial monitoring module is fine-tuned, thereby obtaining an updated model for the adjusted initial monitoring module. Furthermore, utilizing the updated model, a trip threshold monitoring table can be updated to regenerate the trip monitoring thresholds or trip monitoring threshold combinations that constitute a trip mode. The updated trip threshold monitoring table is responded to by continuously monitoring the electric energy meter's detection parameters, and the tripping action is accurately completed when the electric energy meter's detection parameters meet the corresponding trip mode. Furthermore, during the tripping process, the feedback signal during the tripping process is used to determine the tripping result when the corresponding trip mode is used to control the tripping. The tripping result is then compared with the trip mode to verify the accuracy of the current tripping, thereby ensuring the accuracy and reliability of the tripping action under different risks.

[0025] Figure 1 The flowchart of the verification method for reliable tripping of an electric energy meter in an exemplary embodiment of the present application is shown, which is applied to the verification system and includes steps S10 to S70. Figure 1 The technical solution of this application will be described in detail.

[0026] First, step S10 is executed to obtain detection parameters of the electric energy meter.

[0027] Various sensors can be installed at the connection lines between the energy meter and the tripping device to detect various parameter information of the energy meter and the tripping device, and transmit them to the verification system as energy meter detection parameters. Among them, sensors can include voltage sensors, current sensors, temperature sensors, humidity sensors, etc. The energy meter detection parameters that can be obtained can include voltage values, current values, temperature values, humidity values, etc., to achieve diversified collection of energy meter detection parameters, thereby ensuring the accuracy of energy meter trip prediction.

[0028] Next, step S20 is executed to analyze the detection parameters of the electric energy meter using the initial monitoring model to obtain analysis results. The initial monitoring model is a simulation model that simulates the operation process of the electric energy meter and the tripping device under preset simulation conditions, and the preset simulation conditions include multiple abnormal influencing factors.

[0029] After obtaining the meter's detection parameters, the verification system of the present invention further forms an initial monitoring model using a plurality of pre-defined abnormality influencing factors, thereby enabling corresponding simulations and deductions using this initial monitoring model. For example, when the meter is monitored to be operating at a set time, the power consumption E is obtained. This power consumption can be one of the meter's detection parameters. Simultaneously, the initial monitoring model is used to perform a simulation based on the power consumption E, thereby obtaining deduced parameters based on the initial monitoring model's simulation of the meter and tripping device's operation. The meter's detection parameters and the deduced parameters are then compared and analyzed to determine whether any abnormalities exist in the meter's detection parameters, and the corresponding analysis results are output.

[0030] In step S20, performing parameter analysis on the detection parameters of the electric energy meter using the initial monitoring model to obtain analysis results may further include:

[0031] According to the detection parameters of the electric energy meter, the initial monitoring model is used to perform simulation deduction using preset simulation conditions to simulate and obtain the deduction parameters closest to the detection parameters of the electric energy meter and the formation process data of the deduction parameters;

[0032] The analysis results are obtained based on the electric energy meter detection parameters, deduction parameters and the formation process data of the deduction parameters.

[0033] The parameters of any electric energy meter are recorded as ,in, , Represents the set of all electric energy meter detection parameters. Any deduced parameter is recorded as ,in, , Represents the set of all deduced parameters. When performing parameter analysis on the electric energy meter detection parameters, by using the electric energy meter detection parameters The power consumption E in the data is then simulated using the initial monitoring model under pre-set simulation conditions. This allows the derivation of parameters that are closest to the meter's detection parameters, along with data on the process by which the derivation parameters were formed. Furthermore, the final analysis results can be determined by comparing the meter's detection parameters with the derivation parameters. Once the analysis results are determined, the initial monitoring model can be fine-tuned to ensure the accuracy of trip control based on the meter's detection parameters.

[0034] For example, the scenario conditions used by the electric energy meter include ambient temperature, ambient humidity, etc. If the electric energy meter is exposed to high temperature conditions or a long period of rain and humidity, both will affect the electric energy consumption per unit time of the electric energy meter. Furthermore, after the electric energy meter runs for a set time, the actual electric energy consumption of the electric energy meter at the end of each time period and the sum of the actual electric energy consumption of the electric energy meter at the end of all time periods, that is, the electric energy consumption E at the end of the last time period of the set time, can be obtained as the electric energy meter monitoring data. The electric energy consumption E and the corresponding set time are then input into the initial monitoring model, and a deduction simulation is performed based on the actual electric energy consumption of the electric energy meter at the end of each time period to predict the predicted electric energy consumption of the electric energy meter for each corresponding time period, so as to ensure that the actual electric energy consumption of the electric energy meter at the end of each time period is closest to the predicted electric energy consumption of the electric energy meter for each corresponding time period. That is, through the initial monitoring model under the preset simulation conditions, the predicted electric energy consumption distribution data of the electric energy meter that is closest to the actual electric energy consumption of the electric energy meter at the end of each time period can be simulated as the deduction data.

[0035] For example, in the initial state, the preset simulation conditions of the initial monitoring model do not include high temperature conditions and long-term rain and humid environment factors. In this case, if the electricity meter actually operates under high temperature conditions, the actual electricity consumption of the electricity meter at the end of each time period in the collected electricity meter monitoring data will differ from the predicted electricity consumption of the electricity meter simulated and deduced by the initial monitoring model. Therefore, by analyzing this difference, it is possible to determine whether high temperature interference is indeed present in the actual operation of the electricity meter. Specifically, the corresponding high temperature condition is added to the preset simulation conditions of the initial monitoring model to perform a simulation. Then, to determine the accuracy of the added condition, other conditions, such as the humidity condition mentioned above, are added to the initial monitoring model and the predicted electricity consumption of the electricity meter for each time period is predicted again. By comparing the closeness between the predicted electricity consumption of the electricity meter and the actual electricity consumption of the electricity meter when various conditions are added to the preset simulation conditions, the closest condition, such as only the high temperature condition, is added to the preset simulation conditions to ensure that the initial monitoring model can continue to accurately simulate and deduced the electricity meter detection parameters. Of course, there is also the possibility that the initial monitoring model adds high temperature conditions, for example, during simulation, but there are no high temperature conditions in actual situations. In this case, the actual power consumption of the electricity meter and the predicted power consumption of the electricity meter may not correspond. In this case, the high temperature conditions in the preset simulation conditions can be deleted to ensure the accuracy of the model prediction.

[0036] Specifically, obtaining analysis results based on the electric energy meter detection parameters, deduced parameters, and data of the formation process of the deduced parameters may further include:

[0037] Calculate the difference between the deduced parameters and the electric energy meter detection parameters to obtain the parameter difference;

[0038] Determine whether the parameter difference exceeds the set parameter range:

[0039] If so, an adjustment signal for the initial monitoring model is generated, and the adjustment signal and the parameter difference are used as the analysis result;

[0040] If not, the initial tripping threshold monitoring table corresponding to the initial monitoring model is used to select a tripping mode according to the detection parameters of the electric energy meter and the initial tripping threshold monitoring table to control the tripping step.

[0041] The deduction parameters are obtained by using the initial monitoring model Afterwards, the parameters are detected by the electric energy meter. Perform difference calculation to obtain parameter difference. Specifically, by Each energy meter parameter Perform difference calculation to get parameter difference Then further analyze the difference between each parameter and the difference between the parameters. In the case of Out of setting range When , it indicates the parameter difference If the parameter difference exceeds the standard range, the initial monitoring model needs to be adjusted. Then, an adjustment signal for the initial monitoring model will be generated, and the adjustment signal and the parameter difference will be used as the analysis result to fine-tune the initial monitoring model. Within the set range When , it indicates the current parameter difference Controllable, without adjusting the initial monitoring model. The initial trip threshold monitoring table corresponding to the initial monitoring model can be directly used to select a tripping mode based on the energy meter detection parameters and the initial trip threshold monitoring table to control tripping. Furthermore, during the tripping process, a tripping result is generated based on the feedback signal of the tripping process; the tripping result is compared with the tripping mode to determine tripping accuracy.

[0042] Next, step S30 is executed to fine-tune the initial monitoring model according to the analysis result to obtain an updated model.

[0043] After obtaining the analysis results, it is explained that the initial tripping threshold monitoring table corresponding to the previous initial monitoring model can no longer meet the requirements for monitoring the detection parameters of the electricity meter. It is necessary to further fine-tune the initial monitoring model according to the analysis results, so as to realize the generation of the corresponding tripping threshold monitoring table by the updated model obtained through fine-tuning, so as to realize the threshold monitoring of the detection parameters of the electricity meter, and when the set tripping mode of the tripping threshold monitoring table is met, the tripping is controlled according to the set tripping mode to ensure the reliability of the tripping process of the electricity meter.

[0044] In step S30, fine-tuning the initial monitoring model according to the analysis results to obtain an updated model may further include:

[0045] Perform abnormal query on the analysis results to obtain the target influencing factors corresponding to the analysis results;

[0046] The initial monitoring model is fine-tuned based on the target influencing factors to obtain an updated model.

[0047] When fine-tuning the initial monitoring model, an anomaly query can be performed on the analysis results to determine the target influencing factors corresponding to the analysis results of the corresponding abnormal conditions. After obtaining the target influencing factors, the initial monitoring model can be fine-tuned based on the target influencing factors to obtain an updated model. This can further generate a more reliable trip threshold monitoring table based on the fine-tuned updated model.

[0048] Among them, the analysis results include the adjustment signal of the initial monitoring model and the parameter difference between the deduced parameters obtained by deducing the initial monitoring model and the detection parameters of the electricity meter; the target influencing factors include a combination of positive influencing factors and a combination of negative influencing factors.

[0049] When analyzing the meter's detection parameters using the initial monitoring model, we can obtain analysis results for the initial monitoring model's adjustment signal and the difference between the deduced parameters derived from the initial monitoring model and the meter's detection parameters. When using this analysis result for anomaly inquiries, we can determine the corresponding form of the target influencing factors, namely, combinations of positive and negative influencing factors, based on the positive and negative values ​​of the parameter differences.

[0050] In addition, performing an abnormal query on the analysis result to obtain the target adjustment factor corresponding to the analysis result may further include:

[0051] Monitor the positive and negative values ​​of parameter differences based on the adjustment signal;

[0052] When the parameter difference is positive, a positive influencing factor combination is obtained according to the parameter difference; wherein the positive influencing factor combination includes at least one influencing factor item that has been executed in the initial monitoring model;

[0053] When the monitored parameter difference is negative, a negative influencing factor combination is obtained according to the parameter difference; wherein the negative influencing factor combination includes at least one influencing factor item that is not executed in the initial monitoring model.

[0054] After the analysis results are obtained, the positive and negative values ​​of the parameter difference are monitored according to the adjustment signal in the analysis results. When the parameter difference is positive, it means that the deduced parameter obtained by the initial monitoring model is greater than the electric energy meter detection parameter. According to the parameter difference, at least one influencing factor item included in the initial monitoring model can be used to Combine to obtain a combination of positive influencing factors Then, use the positive influencing factors combination Fine-tune the initial monitoring model to obtain an updated model. When the parameter difference is negative, it means that the deduced parameter obtained by the initial monitoring model is less than the electric energy meter detection parameter. According to the parameter difference, at least one influencing factor item not executed in the initial monitoring model can be used to Combine to obtain a combination of negative influencing factors Then, use the negative influencing factors combination Fine-tune the initial monitoring model to obtain an updated model.

[0055] Furthermore, the initial monitoring model is fine-tuned based on the target influencing factors to obtain an updated model, including:

[0056] When the monitored parameter difference is positive, a corresponding weakening adjustment factor is generated according to each positive influencing factor combination, and each weakening adjustment factor is added to the initial monitoring model to re-simulate and generate the positive simulation deduction parameters corresponding to each positive influencing factor combination. All positive simulation deduction parameters are sorted, and the weakening adjustment factor corresponding to the positive simulation deduction parameter closest to the electric energy meter detection parameter is selected. The initial monitoring model is fine-tuned to obtain an updated model;

[0057] When the monitored parameter difference is negative, a corresponding enhanced adjustment factor is generated according to each combination of negative influencing factors, and each enhanced adjustment factor is added to the initial monitoring model to re-simulate and generate the negative simulation deduction parameters corresponding to each combination of negative influencing factors. All the negative simulation deduction parameters are sorted, and the enhanced adjustment factors corresponding to the negative simulation deduction parameters closest to the electricity meter detection parameters are selected. The initial monitoring model is fine-tuned to obtain an updated model.

[0058] When the monitored parameter difference is positive, it can be determined that the target influencing factor is a positive influencing factor combination. Therefore, we can combine each positive influencing factor Generate corresponding weakening regulatory factors , where each positive influencing factor combination Corresponding to a weakening regulatory factor . And each weakening adjustment factor Added to the initial monitoring model to determine which specific weakening regulatory factor It can make the positive simulation deduction parameter closest to the electric energy meter detection parameter and output the weakening adjustment factor corresponding to the positive simulation deduction parameter To fine-tune the initial monitoring model to ensure the reliability of the updated model. Similarly, when the parameter difference is negative, it can be determined that the target influencing factor is a negative influencing factor combination. Therefore, we can combine the negative impact factors Generate corresponding enhancement regulatory factors , where each negative influencing factor combination Corresponding to an enhancing regulatory factor . And each enhancer regulatory factor Added to the initial monitoring model to determine which specific enhanced regulatory factor It can make the negative simulation deduction parameter closest to the electric energy meter detection parameter and output the enhanced adjustment factor corresponding to the negative simulation deduction parameter To fine-tune the initial monitoring model, the reliability of the updated model can also be achieved.

[0059] For example, when the monitored parameter difference is positive, it may be that the electric energy meter is not affected by the temperature condition when it is actually working, but the temperature condition is added to the initial monitoring model, which makes the deduced parameter derived by the initial monitoring model greater than the electric energy meter detection parameter. To determine which specific combination of positive influencing factors can make the positive simulation parameters derived from the initial monitoring model closest to the detection parameters of the electricity meter. Therefore, during the comparison, it can be determined that the temperature condition should be added as a positive influencing factor combination. Based on the temperature condition, the corresponding weakening adjustment factor can be obtained by looking up the table to adjust the weight of the positive simulation parameters generated by the initial monitoring model, so that the positive simulation parameters derived from the adjusted updated model are closest to the detection parameters of the electricity meter.

[0060] Similarly, when the monitored parameter difference is negative, it may be that the actual operation of the electric energy meter is affected by the temperature condition, and the initial monitoring model does not include the temperature condition, which makes the deduced parameter derived by the initial monitoring model smaller than the electric energy meter detection parameter. To determine which specific combination of negative influencing factors can make the negative simulation parameters derived by the initial monitoring model closest to the electric energy meter detection parameters. Therefore, during the comparison, it can be determined that the temperature condition is a negative influencing factor combination. Based on the temperature condition, the corresponding enhanced adjustment factor can be obtained by looking up the table to adjust the weight of the negative simulation parameters generated by the initial monitoring model, so that the negative simulation parameters derived by the adjusted updated model are closest to the electric energy meter detection parameters.

[0061] Next, step S40 is executed to update the tripping threshold monitoring table according to the updated model; wherein the tripping threshold monitoring table includes a plurality of tripping monitoring thresholds and tripping modes formed by the tripping monitoring thresholds.

[0062] After fine-tuning the initial monitoring model to obtain an updated model, the updated model can be used to further update the trip threshold monitoring table to help improve the accuracy and reliability of the monitoring of the thresholds of the electric energy meter detection parameters. In the trip threshold monitoring table, multiple types of trip monitoring thresholds corresponding to the updated model are configured. The trip monitoring threshold corresponds to at least one electric energy meter detection parameter, so that tripping can be controlled based on the trip monitoring threshold or a combination of different trip monitoring thresholds to form a tripping mode. In the process of controlling tripping, the tripping mode can include single-phase tripping, three-phase tripping, trip reclosing, non-closing, etc., and can be selected based on the severity of the feedback from factors such as the changing trend of the electric energy meter detection parameters and the degree of possible losses.

[0063] Wherein, updating the trip threshold monitoring table according to the updated model may further include:

[0064] Export all corresponding updated trip monitoring thresholds by updating the model;

[0065] All updated trip monitoring thresholds are replaced with invalid trip monitoring thresholds in the original trip monitoring thresholds to update the trip threshold monitoring table.

[0066] When updating the trip threshold monitoring table using the updated model, all corresponding updated trip monitoring thresholds are generated using the fine-tuned updated model. All updated trip monitoring thresholds are then used to replace invalid trip monitoring thresholds in the original trip monitoring thresholds, thereby updating the trip threshold monitoring table. Furthermore, if an updated trip monitoring threshold does not exist in the original trip monitoring threshold, it is directly added. If the updated trip monitoring threshold requires partial deletion of the original trip monitoring threshold, the invalid trip monitoring threshold is directly deleted from the original trip monitoring threshold to update the trip threshold monitoring table to meet the requirements of the updated trip monitoring threshold.

[0067] In addition, replacing all updated trip monitoring thresholds with invalid trip monitoring thresholds in the original trip monitoring thresholds to update the trip threshold monitoring table may further include:

[0068] Replacing all updated trip monitoring thresholds with invalid trip monitoring thresholds in the original trip monitoring thresholds to obtain all final trip monitoring thresholds that are retained;

[0069] Combining the final trip monitoring thresholds to obtain a threshold combination; wherein the threshold combination includes at least one final trip monitoring threshold;

[0070] The threshold combination is detected by a trip combination library; wherein the trip combination library includes preset combinations and trip modes corresponding to the preset combinations;

[0071] When there is a preset combination corresponding to the threshold combination in the trip combination library, the threshold combination and its corresponding trip mode are retained.

[0072] After replacing the invalid trip monitoring thresholds in the original trip monitoring thresholds with all updated trip monitoring thresholds, all remaining final trip monitoring thresholds are obtained. These final trip monitoring thresholds are then freely combined to select threshold combinations that meet different tripping modes. The trip threshold monitoring table is then updated using the remaining threshold combinations and their corresponding tripping modes.

[0073] Next, step S50 is executed to select a corresponding tripping mode according to the detection parameters of the electric energy meter and the tripping threshold monitoring table to control the tripping.

[0074] After obtaining the updated tripping threshold monitoring table, threshold monitoring of the electric energy meter detection parameters can be implemented to determine when the abnormality of the electric energy meter detection parameters reaches the set threshold, and select the corresponding tripping method to control the tripping to ensure the reliability of the electric energy meter tripping control.

[0075] In step S50, according to the detection parameters of the electric energy meter and the trip threshold monitoring table, a corresponding trip mode is selected to control the tripping, including:

[0076] Select the corresponding tripping mode according to the energy meter detection parameters and tripping threshold monitoring table;

[0077] According to the tripping mode, a tripping signal is generated to control the tripping.

[0078] When using the tripping threshold monitoring table to perform threshold monitoring on the detection parameters of the electric energy meter, when all types of electric energy meter detection parameters corresponding to the tripping mode exceed the corresponding final tripping monitoring threshold in the tripping threshold monitoring table, the corresponding tripping mode will be quickly selected, and the tripping signal corresponding to the tripping mode will be used to control the reliable tripping of the electric energy meter.

[0079] Next, step S60 and step S70 are executed. During the tripping process, a tripping result is generated according to the feedback signal of the tripping process; the tripping result is compared with the tripping mode to determine the tripping accuracy.

[0080] During the tripping process, each tripping action generates a feedback signal, which can be used to generate a tripping result. For example, if the tripping result is a single-phase trip, one feedback signal will be generated, and if the tripping result is a three-phase trip, three feedback signals will be generated. Therefore, the generated tripping result can be compared with the tripping method to determine whether the tripping result is consistent with the tripping method. If not, the staff will be notified in a timely manner for processing.

[0081] Please refer to 2. The present invention also provides a verification system 11 for reliable tripping of an electric energy meter, comprising: an acquisition unit 111 for acquiring detection parameters of the electric energy meter; an analysis unit 112 for performing parameter analysis on the detection parameters of the electric energy meter through an initial monitoring model to obtain analysis results; a fine-tuning unit 113 for fine-tuning the initial monitoring model according to the analysis results to obtain an updated model; an updating unit 114 for updating a tripping threshold monitoring table according to the updated model; wherein the tripping threshold monitoring table includes a plurality of tripping monitoring thresholds and a tripping mode formed by the tripping monitoring thresholds; a selection unit 115 for selecting a corresponding tripping mode to control tripping according to the detection parameters of the electric energy meter and the tripping threshold monitoring table; a generation unit 116 for generating a tripping result according to a feedback signal of the tripping process during the tripping process; and a comparison unit 117 for comparing the tripping result with the tripping mode to determine the tripping accuracy.

[0082] It should be noted that the verification system 11 for reliable tripping of an electric energy meter provided in the above embodiment and the verification method for reliable tripping of an electric energy meter provided in the above embodiment are based on the same concept, wherein the specific manner in which each module and unit performs operations has been described in detail in the method embodiment and will not be repeated here. In actual applications, the verification system 11 for reliable tripping of an electric energy meter provided in the above embodiment can, as needed, allocate the above functions to different functional modules, that is, divide the internal structure of the device into different functional modules to complete all or part of the functions described above, and this is not limited here.

[0083] See also Figure 3 The electronic device 1 may include a memory 12, a processor 13 and a bus, and may also include a computer program stored in the memory 12 and executable on the processor 13, such as a verification program for reliable tripping of an electric energy meter.

[0084] The memory 12 includes at least one type of readable storage medium, including flash memory, a removable hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 12 may be an internal storage unit of the electronic device 1, such as a removable hard disk of the electronic device 1. In other embodiments, the memory 12 may also be an external storage device of the electronic device 1, such as a plug-in removable hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. equipped on the electronic device 1. Furthermore, the memory 12 may include both an internal storage unit of the electronic device 1 and an external storage device. The memory 12 can be used not only to store application software installed in the electronic device 1 and various types of data, such as codes used to verify the reliable tripping of the electricity meter, but also to temporarily store data that has been output or is about to be output.

[0085] In some embodiments, the processor 13 may be comprised of an integrated circuit, such as a single packaged integrated circuit or multiple packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips. The processor 13 is the control core (control unit) of the electronic device 1. It utilizes various interfaces and circuits to connect the various components of the electronic device 1. It executes programs or modules stored in the memory 12 (such as a program for verifying reliable tripping of an energy meter) and accesses data stored in the memory 12 to perform various functions and process data.

[0086] The processor 13 executes the operating system and various installed application programs of the electronic device 1. The processor 13 executes the application programs to implement the steps in the above-mentioned verification method for reliable tripping of an electric energy meter.

[0087] Exemplarily, the computer program may be divided into one or more modules, which are stored in the memory 12 and executed by the processor 13 to implement the present application. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the electronic device 1. For example, the computer program may be divided into units used in a verification system for reliable tripping of an electric energy meter.

[0088] The above-mentioned integrated unit implemented in the form of a software functional module can be stored in a computer-readable storage medium, which can be either non-volatile or volatile. The above-mentioned software functional module is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, computer equipment, or network equipment, etc.) or a processor to perform part of the functions of the method for verifying the reliable tripping of an electric energy meter described in various embodiments of this application.

[0089] In summary, the present invention discloses a method and system for verifying reliable tripping of an electric energy meter. By utilizing an initial monitoring module to analyze the electric energy meter's detection parameters, the system can promptly detect abnormalities in the electric energy meter's detection parameters before determining that the electric energy meter has tripped. Based on the detected abnormalities in the electric energy meter's detection parameters, the system can fine-tune the initial monitoring module, thereby obtaining an updated model for the adjusted initial monitoring module. Furthermore, the updated model can be used to update the trip threshold monitoring table, thereby regenerating the trip monitoring thresholds or trip monitoring threshold combinations that constitute the trip mode. Furthermore, the system continuously monitors the electric energy meter's detection parameters to respond to the updated trip threshold monitoring table. When the electric energy meter's detection parameters meet the corresponding trip mode in the trip threshold monitoring table, the system accurately executes the tripping action. Furthermore, during the tripping process, the system utilizes a feedback signal during the tripping process to determine the tripping result when the corresponding trip mode is used to control the tripping. The tripping result is then compared with the trip mode to verify the accuracy of the current tripping action, thereby ensuring the accuracy and reliability of the tripping action when responding to different safety risks. Therefore, the present invention effectively overcomes various shortcomings of the prior art and has high industrial utilization value.

[0090] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the present invention. Anyone skilled in the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by one of ordinary skill in the art without departing from the spirit and technical principles disclosed herein are intended to be covered by the claims of the present invention.

Claims

1. A method for verifying reliable tripping of an electric energy meter, characterized in that: include: Get the detection parameters of the electric energy meter; Performing parameter analysis on the electric energy meter detection parameters using an initial monitoring model to obtain analysis results; Fine-tuning the initial monitoring model according to the analysis results to obtain an updated model; According to the updated model, the tripping threshold monitoring table is updated; wherein the tripping threshold monitoring table includes a plurality of tripping monitoring thresholds and tripping modes formed by the tripping monitoring thresholds; Selecting a corresponding tripping mode according to the electric energy meter detection parameters and the tripping threshold monitoring table to control tripping; During the tripping process, a tripping result is generated according to the feedback signal of the tripping process; Comparing the trip result with the trip mode to determine trip accuracy; Updating the trip threshold monitoring table according to the update model includes: deriving all corresponding updated trip monitoring thresholds through the updated model; replacing all the updated trip monitoring thresholds with invalid trip monitoring thresholds in the original trip monitoring thresholds to update the trip threshold monitoring table; Replacing all the updated trip monitoring thresholds with invalid trip monitoring thresholds in the original trip monitoring thresholds to update the trip threshold monitoring table, including: Replacing the invalid trip monitoring thresholds in the original trip monitoring thresholds with all the updated trip monitoring thresholds to obtain all the final trip monitoring thresholds that are retained; Combining the final trip monitoring thresholds to obtain a threshold combination; wherein the threshold combination includes at least one of the final trip monitoring thresholds; The threshold combination is detected by a trip combination library; wherein the trip combination library includes preset combinations and trip modes corresponding to the preset combinations; When there is a preset combination corresponding to the threshold combination in the trip combination library, the threshold combination and its corresponding trip mode are retained.

2. The method for verifying reliable tripping of an electric energy meter according to claim 1, characterized in that: The initial monitoring model is a simulation model that simulates the operation process of the electric energy meter and the tripping device through preset simulation conditions, and the preset simulation conditions include multiple abnormal influencing factors; Performing parameter analysis on the electric energy meter detection parameters using the initial monitoring model to obtain analysis results, including: According to the electric energy meter detection parameters, the initial monitoring model is used to perform simulation deduction using the preset simulation conditions to simulate and obtain deduction parameters that are closest to the electric energy meter detection parameters and formation process data of the deduction parameters; The analysis result is obtained according to the detection parameters of the electric energy meter, the deduced parameters and the formation process data of the deduced parameters.

3. The method for verifying reliable tripping of an electric energy meter according to claim 2, characterized in that: Obtaining the analysis result according to the electric energy meter detection parameter, the deduced parameter, and the data of the formation process of the deduced parameter, including: Performing a difference calculation between the deduced parameter and the electric energy meter detection parameter to obtain a parameter difference; Determine whether the parameter difference exceeds the set parameter range: If yes, generating an adjustment signal for the initial monitoring model, and taking the adjustment signal and the parameter difference as the analysis result; If not, the initial tripping threshold monitoring table corresponding to the initial monitoring model is used to select a tripping mode according to the electric energy meter detection parameters and the initial tripping threshold monitoring table to control the tripping step.

4. The method for verifying reliable tripping of an electric energy meter according to claim 1, characterized in that: Fine-tuning the initial monitoring model according to the analysis results to obtain an updated model includes: Perform an exception query on the analysis result to obtain the target influencing factors corresponding to the analysis result; The initial monitoring model is fine-tuned based on the target influencing factors to obtain the updated model.

5. The method for verifying reliable tripping of an electric energy meter according to claim 4, characterized in that: The analysis results include the adjustment signal of the initial monitoring model and the parameter difference between the deduced parameters obtained by deducing the initial monitoring model and the detection parameters of the electric energy meter; the target influencing factors include a combination of positive influencing factors and a combination of negative influencing factors; Performing an abnormal query on the analysis result to obtain the target adjustment factor corresponding to the analysis result includes: Monitoring the positive and negative values ​​of the parameter difference according to the adjustment signal; When it is monitored that the parameter difference is positive, the positive influencing factor combination is obtained according to the parameter difference; wherein the positive influencing factor combination includes at least one influencing factor item that has been executed in the initial monitoring model; When it is monitored that the parameter difference is negative, the negative influencing factor combination is obtained according to the parameter difference; wherein the negative influencing factor combination includes at least one influencing factor item that is not executed in the initial monitoring model.

6. The method for verifying reliable tripping of an electric energy meter according to claim 5, characterized in that: Fine-tuning the initial monitoring model based on the target influencing factors to obtain an updated model includes: When it is monitored that the parameter difference is positive, a corresponding weakening adjustment factor is generated according to each combination of the positive influencing factors, and each weakening adjustment factor is added to the initial monitoring model to re-simulate and generate positive simulation deduction parameters corresponding to each combination of the positive influencing factors, sort all the positive simulation deduction parameters, select the weakening adjustment factor corresponding to the positive simulation deduction parameter closest to the detection parameter of the electric energy meter, and fine-tune the initial monitoring model to obtain an updated model; When it is monitored that the parameter difference is negative, a corresponding enhanced adjustment factor is generated according to each combination of the negative influencing factors, and each enhanced adjustment factor is added to the initial monitoring model to re-simulate and generate negative simulation deduction parameters corresponding to each combination of the negative influencing factors. All the negative simulation deduction parameters are sorted, and the enhanced adjustment factor corresponding to the negative simulation deduction parameter closest to the electric energy meter detection parameter is selected, and the initial monitoring model is fine-tuned to obtain an updated model.

7. The method for verifying reliable tripping of an electric energy meter according to claim 1, characterized in that: Selecting a corresponding tripping mode according to the electric energy meter detection parameters and the tripping threshold monitoring table to control the tripping, including: Selecting a corresponding tripping mode according to the electric energy meter detection parameters and the tripping threshold monitoring table; According to the tripping mode, a tripping signal is generated to control the tripping.

8. A verification system for the method for verifying reliable tripping of an electric energy meter according to any one of claims 1 to 7, characterized in that: include: An acquisition unit, used for acquiring detection parameters of the electric energy meter; an analysis unit, configured to perform parameter analysis on the detection parameters of the electric energy meter using an initial monitoring model to obtain analysis results; a fine-tuning unit, configured to fine-tune the initial monitoring model according to the analysis result to obtain an updated model; An updating unit, configured to update a tripping threshold monitoring table according to the updated model; wherein the tripping threshold monitoring table includes a plurality of tripping monitoring thresholds and tripping modes formed by the tripping monitoring thresholds; a selection unit, configured to select a corresponding tripping mode according to the detection parameters of the electric energy meter and the tripping threshold monitoring table to control the tripping; a generating unit, configured to generate a tripping result according to a feedback signal of the tripping process during the tripping process; and A comparison unit is used to compare the trip result with the trip mode to determine the trip accuracy.

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