Power transmission detection method and system for sorting and identifying electricity meters

Abstract

This invention discloses a power transmission detection method and system for sorting and identifying electricity meters, relating to the field of power system technology, with the main objective of solving the problem of poor efficiency in existing power transmission detection methods. The method includes: acquiring historical transmission duration and historical power data of the transmission belt of the electricity meters to be sorted, and determining the transmission fluctuation time range through the historical transmission duration and historical power data; configuring correction parameters for the power data to be transmitted, and predicting the transmission start time point of the power data for sorting and identifying electricity meters based on the power transmission detection correction parameters; if the number of transmissions corresponding to the transmission start time point is greater than a preset threshold, classifying the target electricity meters, and adjusting the transmission start time point of the electricity meter sorting and identification according to the classification results; and sending transmission instructions to the mechanical equipment transmitting the power data for sorting and identifying electricity meters.

Description

Technical Field

[0001] This invention relates to the field of power system technology, and in particular to a power transmission detection method and system for sorting and identifying electricity meters. Background Technology

[0002] In power systems, electricity meters serve as terminal power data transmission instruments, used to transmit electricity consumption data from power-consuming terminals or transmission nodes to accurately analyze the power transmission status of these terminals and nodes. For the safe and correct use of electricity meters, sorting and verification platforms are typically used to sort and inspect them. For example, electricity meters are placed on a conveyor belt on the platform, and robotic arms positioned on both sides of the conveyor belt transmit the power data from the meters to complete the verification process.

[0003] Currently, existing robotic arms positioned on both sides of a conveyor belt wirelessly transmit data to the backend server of the electricity meter sorting and identification platform for analysis and processing. However, due to the large number of electricity meters on the conveyor belt and the massive amount of real-time electricity data uploaded by the robotic arms during transport, a large data stream is generated. The electricity meter sorting and identification platform's statistical analysis of all collected data from the robotic arms leads to excessive data processing pressure. Furthermore, the real-time nature of the data transmission can cause network congestion when the platform receives electricity data. Therefore, a new electricity transmission detection method for electricity meter sorting and identification is urgently needed to address these issues. Summary of the Invention

[0004] In view of this, the present invention provides a method and system for detecting power transmission in the sorting and identification of electricity meters, the main purpose of which is to solve the problem of poor efficiency in the existing power transmission detection methods for sorting and identification of electricity meters.

[0005] According to one aspect of the present invention, a method for power transmission detection in the sorting and identification of electricity meters is provided, comprising:

[0006] The historical transmission duration of the conveyor belt of the electricity meter to be sorted and the historical power data corresponding to the historical transmission duration are obtained, and the transmission fluctuation time range is determined by the historical transmission duration and the historical power data.

[0007] The power data to be transmitted is configured with correction parameters according to the transmission fluctuation time range, and the transmission start time of the power data is predicted based on the correction parameters. The correction parameters are used to characterize the elastic time of the expected transmission of power data by different mechanical equipment. The power data is the detection content of the expected power data to be collected and transmitted by the mechanical equipment.

[0008] If the number of transmissions corresponding to the transmission start time point is greater than a preset threshold, the target energy meters are classified, and the transmission start time point is adjusted according to the classification results.

[0009] A transmission instruction is sent to the mechanical equipment that transmits the power data. The transmission instruction carries an adjusted transmission start time point to instruct the mechanical equipment to upload real-time power data according to the transmission start time point and to detect the power data.

[0010] Furthermore, determining the transmission fluctuation time range using the historical transmission duration and the historical power data includes:

[0011] The historical transmission duration is segmented based on a preset time length, and the target time length of the segmented historical transmission duration without bound power data is extracted based on the historical power data.

[0012] If a target time length exists within the preset time length, the transmission fluctuation time range is determined based on the time boundary of the target time length;

[0013] If there are multiple target time lengths within the preset time length, the multiple target time lengths are integrated, and the transmission fluctuation time range is determined based on the time boundary of the integrated target time length.

[0014] Furthermore, configuring correction parameters for the power data to be transmitted according to the transmission fluctuation time range includes:

[0015] When a target time length exists, a correction parameter is calculated based on a first preset ratio of the target time length, where the first preset ratio is less than 1.

[0016] When there are multiple target time lengths, a correction parameter is calculated based on the sum of the multiple target time lengths and a second preset ratio, where the second preset ratio is greater than 1.

[0017] Furthermore, predicting the transmission start time of the power data based on the correction parameters includes:

[0018] Add the correction parameter to the transmission fluctuation time range to obtain the transmission start time point of the power data; or,

[0019] A time prediction model matching the transmission fluctuation time range is retrieved, and the correction parameters are predicted using the time prediction model to determine the transmission start time. The time prediction model is trained based on correction samples and start time samples corresponding to different transmission fluctuation time ranges.

[0020] Furthermore, the process of classifying the target electricity meters and adjusting the transmission start time point according to the classification results includes:

[0021] The sorting and identification batch, equipment model, and identification object of the target energy meter are obtained, and the sorting and identification batch, equipment model, and identification object are classified in sequence according to batch priority, model priority, and object priority to obtain the target energy meter with different classification results;

[0022] The preset classification adjustment strategy retrieves the adjustment value and adjusts the transmission start time of the target energy meter based on the adjustment value. The preset classification adjustment strategy is used to characterize the method of adjusting the numerical value of the transmission start time for different classification results.

[0023] Furthermore, the method also includes:

[0024] If the number of transmissions corresponding to the transmission start time point is less than or equal to a preset threshold, a transmission instruction is generated for the mechanical equipment to instruct the mechanical equipment to upload real-time power data according to the transmission start time point and to detect the power data.

[0025] Furthermore, the method also includes:

[0026] The power data of the target electricity meter is statistically analyzed, and detection is performed based on the statistical results.

[0027] According to another aspect of the present invention, a power transmission detection system for sorting and identifying electricity meters is provided, comprising:

[0028] The acquisition module is used to acquire the historical transmission duration of the transmission belt of the electricity meter to be sorted and the historical power data corresponding to the historical transmission duration, and to determine the transmission fluctuation time range through the historical transmission duration and the historical power data.

[0029] The prediction module is used to configure correction parameters for the power data to be transmitted according to the transmission fluctuation time range, and to predict the transmission start time of the power data based on the correction parameters. The correction parameters are used to characterize the elastic time of expected power data transmission for different mechanical equipment.

[0030] The classification module is used to classify the target energy meter if the number of transmissions corresponding to the transmission start time point is greater than a preset threshold, and adjust the transmission start time point according to the classification result;

[0031] The sending module is used to send a transmission instruction to the mechanical equipment that transmits the power data. The transmission instruction carries an adjusted transmission start time point to instruct the mechanical equipment to upload real-time power data according to the transmission start time point and to detect the power data.

[0032] According to another aspect of the present invention, a storage medium is provided, wherein at least one executable instruction is stored therein, the executable instruction causing a processor to perform an operation corresponding to the power transmission detection method for sorting and identifying electricity meters described above.

[0033] According to another aspect of the present invention, a terminal is provided, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus;

[0034] The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the power transmission detection method for sorting and identifying the above-mentioned electricity meter.

[0035] By employing the above-described technical solutions, the technical solutions provided by the embodiments of the present invention have at least the following advantages:

[0036] This invention provides a power transmission detection method and system for sorting and identifying electricity meters. Compared with existing technologies, this invention obtains the historical transmission duration of the transmission belt of the electricity meter to be sorted and the historical power data corresponding to the historical transmission duration. It then determines the transmission fluctuation time range using the historical transmission duration and the historical power data. Correction parameters are configured for the power data to be transmitted according to the transmission fluctuation time range, and the transmission start time point of the power data is predicted based on the correction parameters. The correction parameters characterize the elasticity time of expected power data transmission for different mechanical devices. If the number of transmissions corresponding to the transmission start time point is greater than a preset threshold, the target electricity meters are classified, and the transmission start time point is adjusted according to the classification results. A transmission command is sent to the mechanical device transmitting the power data, carrying the adjusted transmission start time point, to instruct the mechanical device to upload real-time power data according to the transmission start time point. The power data is then detected. This significantly reduces the possibility of network congestion when the electricity meter sorting and identification platform receives data, reduces the amount of data transmitted, and ensures the accuracy of data transmission, thereby improving data transmission efficiency.

[0037] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0038] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0039] Figure 1 This invention provides a flowchart of a power transmission detection method for sorting and identifying electricity meters according to an embodiment of the present invention.

[0040] Figure 2 This diagram illustrates a block diagram of a power transmission detection system for sorting and identifying electricity meters, provided by an embodiment of the present invention.

[0041] Figure 3 A schematic diagram of the structure of a terminal provided in an embodiment of the present invention is shown. Detailed Implementation

[0042] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0043] This invention provides a method for power transmission detection in the sorting and identification of electricity meters, such as... Figure 1 As shown, the method includes:

[0044] 101. Obtain the historical transmission duration of the transmission belt of the electricity meter to be sorted and the historical power data corresponding to the historical transmission duration, and determine the transmission fluctuation time range through the historical transmission duration and the historical power data.

[0045] In this embodiment of the invention, the current execution end is the backend server of the sorting and identification platform, which can be a main control server or a cloud server, to receive and analyze the electricity meter data collected by the mechanical equipment configured on the electricity meter conveyor belt. This embodiment does not impose specific limitations on the data. The mechanical equipment can be a robotic arm configured on the electricity meter conveyor belt. Since the transmission time periods for different electricity meter conveyor belts to the current execution end are different, before detecting the electricity meter, the historical transmission duration corresponding to the current electricity meter conveyor belt and the historical power data corresponding to the historical transmission duration are retrieved. The historical transmission duration can be preset, such as 1 hour, half an hour, etc., or it can be the running time of the detection line corresponding to the electricity meter conveyor belt. This embodiment does not impose specific limitations on the data. Furthermore, the current execution end determines the transmission fluctuation time range through the historical transmission duration and historical power data. At this point, the transmission fluctuation time range is used to characterize the time range during which mechanical equipment transmits and stops transmitting power data. Different mechanical equipment has different transmission fluctuation time ranges. In addition, since the time point at which each mechanical equipment transmits power data is different in different time periods, that is, the transmission time is a fluctuating time and may be different every day, the transmission fluctuation time range is used for definition. This embodiment of the invention does not make specific limitations.

[0046] In another embodiment of the invention, for further definition and explanation, the step of determining the transmission fluctuation time range using the historical transmission duration and the historical power data includes:

[0047] The historical transmission duration is segmented based on a preset time length, and the target time length of the segmented historical transmission duration without bound power data is extracted based on the historical power data.

[0048] If a target time length exists within the preset time length, the transmission fluctuation time range is determined based on the time boundary of the target time length;

[0049] If there are multiple target time lengths within the preset time length, the multiple target time lengths are integrated, and the transmission fluctuation time range is determined based on the time boundary of the integrated target time length.

[0050] In this embodiment of the invention, to make the timing of data transmission more accurate and thus meet the effectiveness requirements of power data transmission, the current execution terminal, when determining the transmission fluctuation time range, firstly segments the historical transmission duration based on a preset time length. Specifically, the preset time length is shorter than the historical transmission duration, and this segmentation can be configured based on segmentation requirements. For example, if the historical transmission duration is 10 hours and the preset time length is 2 hours, then the historical transmission duration is divided into 5 time periods after segmentation. This embodiment of the invention does not impose specific limitations. Furthermore, to accurately find the time when no data was transmitted, the current execution terminal extracts the target time length of the segmented historical transmission duration that is not bound to power data. For example, based on all historical power data, it searches for the time periods in the above 5 time periods where no power data was recorded and calculates the time length as the target time length. For instance, if all historical power data was transmitted in the first, second, third, and fifth time periods, and no power data was transmitted at time point a in the fourth time period, but power data began to be transmitted at time point b, then the target time length is based on time point a and time point b.

[0051] It should be noted that after determining the target time length, the current execution end integrates the transmission fluctuation time range based on the corresponding strategy according to the number of target time lengths. Specifically, when only one target time length is obtained after segmenting the historical transmission duration, the start and end times (i.e., time boundaries) of this target time length can be determined as the time boundary of the transmission fluctuation time range. Alternatively, at least one of the start and end times of this target time length can be positively or negatively corrected to become the time boundary of the transmission fluctuation time range. When two or more target time lengths are obtained after segmenting the historical transmission duration, the target time lengths are integrated. During the integration process, if there is a time interval between two adjacent target time lengths, and the duration of this time interval is less than or equal to the duration of the shortest target time length, then the start time of the first target time length will be used as the start time of the integrated target time length, and the end time of the second target time length will be used as the end time of the integrated target time length, before being integrated with other target time lengths. If there is a time interval between two adjacent target time lengths, and the duration of this time interval is greater than the duration of the longest target time length, then if one of the target time lengths is the first or last in the total target time lengths, then this target time length is deleted from the total target time lengths; if any target time length is neither the first nor the last in the total target time lengths, then the start time of the first target time length is used as the start time of the integrated target time length, and the end time of the second target time length is used as the end time of the integrated target time length.

[0052] 102. Configure correction parameters for the power data to be transmitted according to the transmission fluctuation time range, and predict the transmission start time of the power data based on the correction parameters.

[0053] In this embodiment of the invention, to prevent data loss during transmission by mechanical equipment, the current execution terminal configures a correction parameter for the mechanical equipment. This correction parameter characterizes the elasticity of the expected power data transmission time for different mechanical equipment, ensuring that the mechanical equipment transmits power data at the most accurate time. Furthermore, after configuring the correction parameter for the transmission fluctuation time range, the transmission start time of the mechanical equipment is predicted based on this parameter. This transmission start time is then used to ultimately control the mechanical equipment to transmit power data, allowing the mechanical equipment to enter sleep mode at other times and ensuring its operational status.

[0054] In another embodiment of the invention, for further definition and explanation, the step of configuring correction parameters for the power data to be transmitted according to the transmission fluctuation time range includes:

[0055] When a target time length exists, a correction parameter is calculated based on a first preset ratio of the target time length;

[0056] When there are multiple target time lengths, a correction parameter is calculated based on the sum of the multiple target time lengths and a second preset ratio.

[0057] In this embodiment of the invention, when there is one target time length, the correction parameter is the product of the target time length and a first preset ratio. The first preset ratio is less than 1, meaning the correction parameter is less than the target time length. When there are multiple target time lengths, the correction parameter is the product of the sum of all target time lengths and a second preset ratio. The second preset ratio is greater than 1, meaning the correction parameter is greater than the sum of all target time lengths. The specific values ​​of the first and second preset ratios can be customized according to actual application needs, and this embodiment of the invention does not impose specific limitations. By configuring different preset ratios for different numbers of target time lengths to calculate the corresponding correction parameters, it is possible to configure longer correction parameters when the transmission fluctuation time range is long, and shorter correction parameters when the transmission fluctuation time range is short, thereby improving the adaptability of the correction parameters and the accuracy of subsequent transmission start time point prediction.

[0058] In another embodiment of the invention, for further definition and explanation, the step of predicting the transmission start time of the power data based on the correction parameters includes:

[0059] Add the correction parameter to the transmission fluctuation time range to obtain the transmission start time point of the power data; or,

[0060] A time prediction model matching the transmission fluctuation time range is retrieved, and the correction parameters are predicted using the time prediction model to determine the transmission start time.

[0061] In this embodiment of the invention, the start time point of power data transmission can be determined through two methods: direct correction using correction parameters or prediction using a model. Specifically, the start time point of power data transmission is obtained by adding the correction parameters to the transmission fluctuation time range. The correction parameters can be added to one of the boundary time points of the transmission fluctuation time range to correct a single boundary time point. This means either extending the start time point of the transmission fluctuation time range to an earlier time point or extending the end time point of the transmission fluctuation time range to a later time point. Alternatively, the overall duration of the transmission fluctuation time range can be adjusted using the correction parameters to correct bidirectional boundary time points. That is, both the start and end times of the transmission fluctuation time range are adjusted to ensure that the adjusted transmission fluctuation time range equals the sum of the initial transmission fluctuation time range and the correction parameters. This embodiment of the invention does not specifically limit the method of adding the correction parameters to the transmission fluctuation time range.

[0062] The model prediction method uses a time prediction model matched to the transmission fluctuation time range to predict the correction parameters, thereby determining the transmission start time of power data. The time prediction model is trained based on correction samples and start time samples corresponding to different transmission fluctuation time ranges, and can predict the transmission start time corresponding to different correction parameters under different transmission fluctuation time ranges. The time prediction model can be a Gated Recurrent Unit (GRU), Multilayer Perceptron (MLP), or other models suitable for classification and prediction.

[0063] It should be noted that the determination of the power data transmission start time point through either direct correction of calibration parameters or model prediction can be tailored to the specific application scenario. For example, when the transmission fluctuation time range has a large time span, direct correction of calibration parameters can be used; when the transmission fluctuation time range has a large time span, model prediction can be used. This embodiment of the invention does not impose specific limitations. Determining the power data transmission start time point through two selectable methods can meet the needs of different application scenarios, thereby improving adaptability to various scenarios.

[0064] 103. If the number of transmissions corresponding to the transmission start time point is greater than a preset threshold, the target electricity meters are classified, and the transmission start time point is adjusted according to the classification results.

[0065] In this embodiment of the invention, to avoid an excessive number of mechanical devices uploading data within the same time period, the current execution terminal calculates the number of mechanical devices corresponding to the same transmission start time point and compares it with a preset threshold. This preset threshold can be configured based on the system processing capacity of the current execution terminal, including but not limited to 100, 200, etc., and is not specifically limited in this embodiment. When the counted number exceeds the preset threshold, the current execution terminal classifies the target energy meters sorted by the mechanical devices with the same transmission start time point, and adjusts the transmission start time point of the corresponding mechanical devices according to the classification results to avoid uploading too much electricity data at the same time.

[0066] In another embodiment of the invention, for further definition and explanation, the step of classifying the target electricity meters and adjusting the transmission start time point according to the classification results includes:

[0067] The sorting and identification batch, equipment model, and identification object of the target energy meter are obtained, and the sorting and identification batch, equipment model, and identification object are classified in sequence according to batch priority, model priority, and object priority to obtain the target energy meter with different classification results;

[0068] The adjustment value is retrieved based on the preset classification adjustment strategy, and the transmission start time of the target energy meter is adjusted based on the adjustment value.

[0069] In this embodiment of the invention, the transmission start time is adjusted based on the classification results of the target energy meters sorted by the mechanical equipment and a preset classification adjustment strategy. In this process, firstly, the target energy meters are classified according to their sorting and identification batch, equipment model, and identification object. Here, the identification batch refers to the batch corresponding to the target energy meter, the equipment model refers to the model information of the target energy meter, and the identification object refers to the items tested on the target energy meter. Different sorting and identification batches, equipment models, and identification objects are pre-configured with different priorities, which can be defined by the user according to actual production needs. A priority coefficient is obtained by summing the priorities of the current sorted target energy meters' identification batch, equipment model, and identification object. Based on this priority coefficient, the target energy meters can be classified into different categories such as Class I, Class II, and Class III. For example, if the priority of the target energy meter's identification batch is 1, the priority of the equipment model is 2, and the priority of the identification object is 1, then the priority coefficient is 4, corresponding to a Class I target energy meter classification. If the priority of the target energy meter's identification batch is 2, the priority of the equipment model is 2, and the priority of the identification object is 2, then the priority coefficient is 6, corresponding to a Class II target energy meter classification. The preset classification adjustment strategy is used to characterize the method of adjusting the transmission start time point for different classification results. For example, the adjustment value of the transmission start time point for Class I target energy meters is zero or a negative value (characterizing advance), the adjustment value for the transmission start time point for Class II target energy meters is delayed by 5 minutes, and the adjustment value for the transmission start time point for Class III target energy meters is delayed by 15 minutes. The larger the sum of priorities, the lower the indicated priority, and the longer the delay time for adjusting the numerical value of the transmission start time point. Conversely, the smaller the sum of priorities, the higher the indicated priority, which can keep the transmission start time point unchanged or adjust it forward, thereby meeting the timeliness requirements of power data transmission while distributing the power data transmission time and improving data transmission efficiency.

[0070] 104. Send a transmission command to the mechanical equipment that transmits the power data.

[0071] In this embodiment of the invention, after adjusting the transmission start time point, the current execution terminal generates transmission instructions for each mechanical device. These instructions carry the adjusted transmission start time point, instructing the mechanical devices to upload real-time power data according to that start time point. Since the transmission start time point is predicted based on correction parameters and adjusted according to the classification results of the mechanical devices, it fully considers the balanced distribution of power data transmission time, avoiding network congestion when the electricity meter sorting and identification platform receives data, thus ensuring smooth and efficient power data transmission.

[0072] In another embodiment of the invention, for further definition and explanation, the steps further include:

[0073] If the number of transmissions corresponding to the transmission start time point is less than or equal to a preset threshold, a transmission instruction is generated for the mechanical equipment to instruct the mechanical equipment to upload real-time power data according to the transmission start time point and to detect the power data.

[0074] In this embodiment of the invention, when the number of transmissions corresponding to the transmission start time point is less than or equal to a preset threshold, that is, when the number of mechanical devices transmitting data at the same time point is less than or equal to the preset threshold, it can be determined that the distribution of transmission start time points of different mechanical devices is relatively reasonable, and each mechanical device can upload real-time power data according to the current transmission start time point. After receiving the power data uploaded by each mechanical device according to the corresponding transmission start time point, the current execution terminal performs energy meter detection based on the power data.

[0075] In another embodiment of the invention, for further definition and explanation, the steps further include:

[0076] The power data of the target electricity meter is statistically analyzed, and detection is performed based on the statistical results.

[0077] In this embodiment of the invention, the detection content includes metrological performance verification, electrical safety testing, and electromagnetic compatibility (EMC) testing. The corresponding power data includes current, voltage, and load data output by the target energy meter for metrological performance verification; high-voltage test data, insulation resistance test data, grounding resistance test data, and leakage current test data for electrical safety testing; and electrostatic discharge immunity test data and electrical fast transient / burst immunity test data for EMC testing. After receiving the power data corresponding to each target energy meter, the current execution terminal performs statistical analysis from both the target energy meter dimension (all power data of the same target energy meter) and the test item dimension (power data of different target energy meters corresponding to the same test item) to perform detection based on statistical data from different dimensions. At the target energy meter dimension, the detection result of the target energy meter is mainly determined based on abnormal data items in the statistical data. At the test item dimension, the difference between a certain test data of each target energy meter and the average value of all target energy meters is used; if the difference exceeds the abnormal range, the detection of the target energy meter can also be determined as abnormal.

[0078] Furthermore, as a response to the above Figure 1 The implementation of the method shown in this invention provides a power transmission detection system for sorting and identifying electricity meters, as described in this embodiment. Figure 2 As shown, the system includes:

[0079] The acquisition module 21 is used to acquire the historical transmission duration of the transmission belt of the energy meter to be sorted and the historical power data corresponding to the historical transmission duration, and to determine the transmission fluctuation time range through the historical transmission duration and the historical power data.

[0080] Prediction module 22 is used to configure correction parameters for the power data to be transmitted according to the transmission fluctuation time range, and to predict the transmission start time of the power data based on the correction parameters. The correction parameters are used to characterize the elastic time of expected power data transmission for different mechanical equipment.

[0081] The classification module 23 is used to classify the target energy meter if the number of transmissions corresponding to the transmission start time point is greater than a preset threshold, and adjust the transmission start time point according to the classification result;

[0082] The sending module 24 is used to send a transmission instruction to the mechanical equipment that transmits the power data. The transmission instruction carries an adjusted transmission start time point to instruct the mechanical equipment to upload real-time power data according to the transmission start time point and to detect the power data.

[0083] Further, the acquisition module 21 includes:

[0084] The segmentation unit is used to segment the historical transmission duration based on a preset time length, and extract the target time length of the segmented historical transmission duration without bound power data based on the historical power data.

[0085] The determining unit is configured to determine the transmission fluctuation time range based on the time boundary of the target time length if a target time length exists within the preset time length.

[0086] An integration unit is used to integrate multiple target time lengths if there are multiple target time lengths in the preset time length, and to determine the transmission fluctuation time range based on the time boundary of the integrated target time length.

[0087] Furthermore, the prediction module 22 includes:

[0088] The first calculation unit is used to calculate a correction parameter based on a first preset ratio of the target time length when there is a target time length, wherein the first preset ratio is less than 1.

[0089] The second calculation unit is used to calculate a correction parameter based on the sum of the multiple target time lengths and a second preset ratio when there are multiple target time lengths, wherein the second preset ratio is greater than 1.

[0090] Furthermore, the prediction module 32 includes:

[0091] The third calculation unit is used to add the correction parameter to the transmission fluctuation time range to obtain the transmission start time point of the power data; or,

[0092] The prediction unit is used to retrieve a time prediction model that matches the transmission fluctuation time range, and use the time prediction model to predict the correction parameters to determine the transmission start time point. The time prediction model is trained based on correction samples and start time samples corresponding to different transmission fluctuation time ranges.

[0093] Furthermore, the classification includes:

[0094] The acquisition unit is used to acquire the sorting and identification batch, equipment model, and identification object of the target energy meter, and classify the sorting and identification batch, equipment model, and identification object in sequence according to batch priority, model priority, and object priority to obtain the target energy meter with different classification results;

[0095] An adjustment unit is used to retrieve adjustment values ​​based on a preset classification adjustment strategy, and to adjust the transmission start time of the target energy meter based on the adjustment values. The preset classification adjustment strategy is used to characterize the method of adjusting the numerical value of the transmission start time for different classification results.

[0096] Furthermore, the device also includes:

[0097] The generating device is configured to generate a transmission instruction for the mechanical equipment if the number of transmissions corresponding to the transmission start time point is less than or equal to a preset threshold, so as to instruct the mechanical equipment to upload real-time power data according to the transmission start time point and to detect the power data.

[0098] Furthermore, the device also includes:

[0099] The detection module is used to statistically analyze the power data of the target electricity meter and perform detection based on the statistical results.

[0100] This invention provides a power transmission detection system for sorting and identifying electricity meters. Compared with existing technologies, this invention obtains the historical transmission duration of the transmission belt of the electricity meters to be sorted and the historical power data corresponding to the historical transmission duration. It then determines the transmission fluctuation time range based on the historical transmission duration and the historical power data. Correction parameters are configured for the power data to be transmitted according to the transmission fluctuation time range, and the transmission start time point of the power data is predicted based on the correction parameters. The correction parameters characterize the elasticity time of expected power data transmission for different mechanical devices. If the number of transmissions corresponding to the transmission start time point is greater than a preset threshold, the target electricity meters are classified, and the transmission start time point is adjusted according to the classification results. A transmission command is sent to the mechanical device transmitting the power data, carrying the adjusted transmission start time point, to instruct the mechanical device to upload real-time power data according to the transmission start time point. The power data is then detected. This significantly reduces the possibility of network congestion when the electricity meter sorting and identification platform receives data, reduces the amount of data transmitted, and ensures the accuracy of data transmission, thereby improving the efficiency of data transmission.

[0101] According to one embodiment of the present invention, a storage medium is provided, the storage medium storing at least one executable instruction, the computer-executable instruction being able to execute the power transmission detection method for energy meter sorting and identification in any of the above method embodiments.

[0102] Figure 3 The diagram shows a structural schematic of a terminal according to an embodiment of the present invention. The specific implementation of the terminal is not limited by the specific embodiments of the present invention.

[0103] like Figure 3 As shown, the terminal may include: a processor 302, a communications interface 304, a memory 306, and a communications bus 308.

[0104] The processor 302, communication interface 304, and memory 306 communicate with each other via communication bus 308.

[0105] Communication interface 304 is used to communicate with other network elements such as clients or other servers.

[0106] The processor 302 is used to execute program 310, which can specifically execute the relevant steps in the above-described embodiment of the power transmission detection method for sorting and identifying electricity meters.

[0107] Specifically, program 310 may include program code that includes computer operation instructions.

[0108] Processor 302 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The terminal may include one or more processors of the same type, such as one or more CPUs; or it may include processors of different types, such as one or more CPUs and one or more ASICs.

[0109] Memory 306 is used to store program 310. Memory 306 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0110] Specifically, program 310 can be used to cause processor 302 to perform the following operations:

[0111] The historical transmission duration of the conveyor belt of the electricity meter to be sorted and the historical power data corresponding to the historical transmission duration are obtained, and the transmission fluctuation time range is determined by the historical transmission duration and the historical power data.

[0112] The power data to be transmitted is configured with correction parameters according to the transmission fluctuation time range, and the transmission start time of the power data is predicted based on the correction parameters. The correction parameters are used to characterize the elastic time of expected power data transmission for different mechanical equipment.

[0113] If the number of transmissions corresponding to the transmission start time point is greater than a preset threshold, the target energy meters are classified, and the transmission start time point is adjusted according to the classification results.

[0114] A transmission instruction is sent to the mechanical equipment that transmits the power data. The transmission instruction carries an adjusted transmission start time point to instruct the mechanical equipment to upload real-time power data according to the transmission start time point and to detect the power data.

[0115] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing systems. They can be centralized on a single computing system or distributed across a network of multiple computing systems. Optionally, they can be implemented using program code executable by a computing system, thereby storing them in a storage system for execution by the computing system. In some cases, the steps shown or described can be performed in a different order than those presented herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0116] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for power transmission detection in the sorting and identification of electricity meters, characterized in that, include: The historical transmission duration of the conveyor belt of the energy meter to be sorted and the historical power data corresponding to the historical transmission duration are obtained. The transmission fluctuation time range is determined by the historical transmission duration and the historical power data. The transmission fluctuation time range is used to characterize the time range during which the mechanical equipment transmits power data and stops transmitting data. The power data to be transmitted is configured with correction parameters according to the transmission fluctuation time range, and the transmission start time of the power data is predicted based on the correction parameters. The correction parameters are used to characterize the elastic time of the expected transmission of power data by different mechanical equipment. The power data is the detection content of the expected power data to be collected and transmitted by the mechanical equipment. If the number of mechanical devices corresponding to the same transmission start time point is greater than a preset threshold, the target energy meters sorted by the mechanical devices with the same transmission start time point are classified, and the transmission start time point is adjusted according to the classification results. A transmission instruction is sent to the mechanical equipment that transmits the power data. The transmission instruction carries an adjusted transmission start time point to instruct the mechanical equipment to upload real-time power data according to the transmission start time point and to detect the power data.

2. The method according to claim 1, characterized in that, The determination of the transmission fluctuation time range using the historical transmission duration and the historical power data includes: The historical transmission duration is segmented based on a preset time length, and the target time length of the segmented historical transmission duration without bound power data is extracted based on the historical power data. If a target time length exists within the preset time length, the transmission fluctuation time range is determined based on the time boundary of the target time length; If there are multiple target time lengths within the preset time length, the multiple target time lengths are integrated, and the transmission fluctuation time range is determined based on the time boundary of the integrated target time length.

3. The method according to claim 2, characterized in that, The configuration of correction parameters for the power data to be transmitted according to the transmission fluctuation time range includes: When a target time length exists, a correction parameter is calculated based on a first preset ratio of the target time length, where the first preset ratio is less than 1. When there are multiple target time lengths, a correction parameter is calculated based on the sum of the multiple target time lengths and a second preset ratio, where the second preset ratio is greater than 1.

4. The method according to claim 3, characterized in that, The prediction of the power data transmission start time point based on the correction parameters includes: Add the correction parameter to the transmission fluctuation time range to obtain the transmission start time point of the power data; or, A time prediction model matching the transmission fluctuation time range is retrieved, and the correction parameters are predicted using the time prediction model to determine the transmission start time. The time prediction model is trained based on correction samples and start time samples corresponding to different transmission fluctuation time ranges.

5. The method according to claim 4, characterized in that, The process of classifying target energy meters sorted by mechanical equipment at the same transmission start time and adjusting the transmission start time according to the classification results includes: The sorting and identification batch, equipment model, and identification object of the target energy meter are obtained, and the sorting and identification batch, equipment model, and identification object are classified in sequence according to batch priority, model priority, and object priority, respectively, to obtain the target energy meter with different classification results; The preset classification adjustment strategy retrieves the adjustment value and adjusts the transmission start time of the target energy meter based on the adjustment value. The preset classification adjustment strategy is used to characterize the method of adjusting the numerical value of the transmission start time for different classification results.

6. The method according to any one of claims 1-5, characterized in that, The method further includes: If the number of mechanical devices corresponding to the same transmission start time point is less than or equal to a preset threshold, a transmission instruction is generated for the mechanical devices to instruct them to upload real-time power data according to the transmission start time point and to detect the power data.

7. The method according to claim 1, characterized in that, The method further includes: The power data of the target electricity meter is statistically analyzed, and detection is performed based on the statistical results.

8. A power transmission detection system for sorting and identifying electricity meters, characterized in that, include: The acquisition module is used to acquire the historical transmission duration of the conveyor belt of the energy meter to be sorted and the historical power data corresponding to the historical transmission duration, and to determine the transmission fluctuation time range through the historical transmission duration and the historical power data. The transmission fluctuation time range is used to characterize the time range during which the mechanical equipment transmits power data and stops transmitting data. The prediction module is used to configure correction parameters for the power data to be transmitted according to the transmission fluctuation time range, and to predict the transmission start time of the power data based on the correction parameters. The correction parameters are used to characterize the elastic time of expected power data transmission for different mechanical equipment. The classification module is used to classify the target energy meters sorted by the mechanical devices with the same transmission start time if the number of mechanical devices corresponding to the same transmission start time is greater than a preset threshold, and adjust the transmission start time according to the classification result. The sending module is used to send a transmission instruction to the mechanical equipment that transmits the power data. The transmission instruction carries an adjusted transmission start time point to instruct the mechanical equipment to upload real-time power data according to the transmission start time point and to detect the power data.

9. A storage medium storing at least one executable instruction that causes a processor to perform an operation corresponding to the power transmission detection method for energy meter sorting and identification as described in any one of claims 1-7.

10. A terminal, comprising: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction that causes the processor to perform the operation corresponding to the power transmission detection method for energy meter sorting and identification as described in any one of claims 1-7.

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