Monitoring method, monitoring device and monitoring equipment for electric meter box

Abstract

The present application discloses a monitoring method, a monitoring device and a monitoring equipment for an electric meter box, and relates to the field of electric power technology. The monitoring method for the electric meter box comprises: obtaining operation data and environmental data of the electric meter box; generating corresponding target operation status data based on a first algorithm, the operation data and the environmental data; determining abnormal data of the target operation status data according to the target operation status data and a preset operation model to determine the abnormal distribution of the target operation status data; evaluating the abnormality degree of the electric meter box according to the abnormal data and the abnormal distribution, and generating an operation status score based on the abnormality degree; evaluating the operation status level of the electric meter box according to the operation status score and a preset score threshold; generating corresponding status information according to the operation status level, and sending the status information to a command center, so as to timely discover the abnormal state of the electric meter box and ensure the stability and safety of the power supply.

Description

Technical Field

[0001] The present application relates to the field of electric power technology, and in particular to a monitoring method, a monitoring device and a monitoring equipment for an electric meter box. Background Art

[0002] With the continuous development of the power industry, the operation status of the meter box, as a key equipment for power supply, directly affects the stability and safety of power supply. However, traditional meter box monitoring methods mostly rely on manual inspections, which are not only inefficient, but also prone to missed inspections or misdetections, and cannot detect abnormal status of the meter box in time. Therefore, how to achieve real-time monitoring and fault warning of the meter box and improve the reliability and safety of power supply has become an urgent problem to be solved in the current power industry. Summary of the invention

[0003] The main purpose of the present application is to provide a monitoring method, a monitoring device and a monitoring equipment for an electric meter box, aiming to improve the real-time monitoring capability and fault warning capability of the existing electric meter box.

[0004] To achieve the above purpose, the present application proposes a monitoring method for an electric meter box, the monitoring method comprising:

[0005] Obtaining operation data and environmental data of the electric meter box;

[0006] Based on the first algorithm, the operating data and the environmental data, generating corresponding target operating state data;

[0007] Determine abnormal data of the target operating state data according to the target operating state data and a preset operating model to determine abnormal distribution of the target operating state data;

[0008] According to the abnormal data and the abnormal distribution, the abnormal degree of the electric meter box is evaluated, and based on the abnormal degree, an operation status score is generated;

[0009] According to the operating status score and a preset scoring threshold, evaluating the operating status level of the electric meter box;

[0010] According to the operating status level, corresponding status information is generated and sent to the command center.

[0011] In one embodiment, the step of evaluating the abnormality degree of the electric meter box according to the abnormal data and the abnormal distribution, and generating the operating status score based on the abnormality degree includes:

[0012] Generate a corresponding abnormal state distribution diagram according to the abnormal data and abnormal distribution;

[0013] Identify the abnormal state distribution map, determine the abnormal area position existing in the abnormal state distribution map and the abnormal index corresponding to the abnormal area position;

[0014] Determining the abnormality degree of the electric meter box according to the abnormal area position and the abnormality index;

[0015] The operating status score is generated according to the abnormality degree and a preset status scoring standard.

[0016] In one embodiment, the monitoring method further comprises:

[0017] Acquire multiple historical operation data of the electric meter box, historical environment data corresponding to time nodes of the historical operation data, and historical fault types;

[0018] Constructing a target operation model of the electric meter box according to the historical operation data;

[0019] Based on the second algorithm, the historical environmental data, the historical environmental data, and the historical fault types, training the target operation model to generate a corresponding first operation model;

[0020] Randomly selecting a plurality of the historical operation data and importing them into the first operation model to evaluate the operation accuracy of the first operation model;

[0021] If the operation accuracy exceeds a preset threshold, modifying the first operation model and re-importing the historical operation data for evaluation;

[0022] If the operation accuracy meets the requirement, the first operation model is confirmed as the preset operation model.

[0023] In one embodiment, the step of constructing a target operation model of the electric meter box according to the historical operation data includes:

[0024] Constructing an initial training data set based on the historical operation data, historical environmental data, and historical fault types;

[0025] Dividing the initial training data set into a training set, a validation set, and a test set;

[0026] The step of training the target operation model based on the second algorithm, the historical environment data, the historical environment data and the historical fault type to generate a corresponding first operation model includes:

[0027] According to the training set, training the initial operation model to generate multiple candidate operation models;

[0028] Importing the verification set into the plurality of candidate operation models respectively, and calculating the accuracy of each candidate operation model according to the output result of each candidate operation model and the actual result of the verification set;

[0029] Determining the candidate operation model with the highest accuracy as the first operation model;

[0030] The step of randomly selecting a plurality of the historical operation data and importing them into the first operation model to evaluate the operation accuracy of the first operation model includes:

[0031] The test set is imported into the first operation model. If the error rate between the output result of the first operation model and the actual result of the test set is less than a preset threshold, the first operation model is determined to be a preset operation model.

[0032] In one embodiment, the step of evaluating the operating status level of the electric meter box according to the operating status score and a preset score threshold comprises:

[0033] Obtain a level relationship mapping set corresponding to the running status score;

[0034] Generate a corresponding state score segment according to the running state score and the preset score threshold, and identify the corresponding score stage label;

[0035] The operating status level of the electric meter box is evaluated according to the level relationship mapping set, the status score segment and the score stage label.

[0036] In one embodiment, the step of generating a corresponding state score segment according to the running state score and the preset score threshold, and identifying the corresponding score stage label at that time includes:

[0037] Determine the target score range to which the running status score belongs according to the running status score and the preset score threshold;

[0038] According to the target score interval, generating a corresponding state score segment;

[0039] According to the state score segment, determining the target score stage label corresponding to the state score segment;

[0040] According to the target score stage label, the score stage label corresponding to the current time is identified.

[0041] In one embodiment, the step of generating corresponding status information according to the operating status level and sending the status information to the command center includes:

[0042] According to the operating status level, determining the corresponding abnormal area information of the electric meter box and the abnormal problem corresponding to the abnormal area information;

[0043] Generate corresponding status information according to the abnormal area information and the abnormal problem;

[0044] Generate a corresponding warning information data packet according to the status information;

[0045] Based on the first communication protocol, the warning information data packet is sent to the command center so that the command center can remotely monitor and handle faults of the electric meter box.

[0046] In one embodiment, after the step of generating a corresponding warning information data packet according to the status information, the method further includes:

[0047] Obtaining geographical location information of the electric meter box and maintenance personnel information within a preset distance from the geographical location information;

[0048] Generate a corresponding maintenance instruction according to the status information and the maintenance personnel information;

[0049] Based on the second communication protocol, the maintenance instruction is sent to the intelligent terminal of the corresponding maintenance personnel to notify the corresponding maintenance personnel to maintain the electric meter box according to the maintenance instruction.

[0050] In addition, to achieve the above-mentioned purpose, the present application also proposes a monitoring device, which includes: a memory, a processor, and a monitoring program for an electric meter box stored on the memory and runnable on the processor, and the monitoring program for the electric meter box is configured to implement the monitoring method for the electric meter box as described above.

[0051] In addition, to achieve the above objectives, the present application also proposes a monitoring device, including the monitoring apparatus as described above.

[0052] The embodiment of the present invention obtains the operation data and environmental data of the electric meter box, and then processes them based on the first algorithm to generate corresponding target operation status data, compares the target operation status data with the preset operation model, determines the abnormal data of the target operation status data, and determines the abnormal distribution of the target operation status data; then evaluates the abnormality degree of the electric meter box, and generates an operation status score based on the abnormality degree, compares the operation status score with the preset score threshold to evaluate the operation status level of the electric meter box, and finally generates corresponding status information, and sends the status information to the command center, thereby improving the real-time monitoring and fault warning capabilities of the electric meter box, and can achieve comprehensive inspection without relying on manual inspections, and can timely discover the abnormal state of the electric meter box, ensuring the stability and safety of the power supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0054] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0055] Figure 1 A schematic diagram of a method flow of an embodiment of a monitoring method for an electric meter box of the present application;

[0056] Figure 2 A method flow chart of another embodiment of the method for monitoring an electric meter box of the present application;

[0057] Figure 3 A method flow chart of another embodiment of the monitoring method of the electric meter box of the present application;

[0058] Figure 4 A method flow chart of another embodiment of the method for monitoring an electric meter box of the present application;

[0059] Figure 5 A method flow chart of another embodiment of the monitoring method of the electric meter box of the present application;

[0060] Figure 6 A method flow chart of another embodiment of the method for monitoring an electric meter box of the present application;

[0061] Figure 7 A method flow chart of another embodiment of the monitoring method of the electric meter box of the present application;

[0062] Figure 8 This is a method flow chart of another embodiment of the monitoring method of the electric meter box of the present application.

[0063] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0064] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments, and the well-known modules, units and their connections, links, communications or operations are not shown or described in detail. In addition, the described features, architectures or functions can be combined in any way in one or more embodiments. It should be understood by those skilled in the art that the various embodiments described below are only for illustration and not for limiting the scope of protection of the present invention. It can also be easily understood that the modules or units or processing methods in the various embodiments described herein and shown in the drawings can be combined and designed according to various different configurations. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0065] The limitations of various nouns or methods referred to in the following embodiments, except for those that are logically untenable, are generally based on the broad concepts that can be implemented under the premise of the disclosure in the embodiments. Under such understanding, the various specific subordinate specific limitations of the nouns or methods should be regarded as the inventive content of the present invention, and should not be understood narrowly or interpreted in a biased manner on the grounds that the specification does not disclose the specific limitations. Similarly, under the premise that it can be implemented logically, the order of the steps in the method is flexible and changeable, and the specific subordinate specific limitations in the broad concepts of various nouns or methods all fall within the scope of protection of the present invention.

[0066] With the continuous development of the power industry, the operating status of the meter box, as a key equipment for power supply, directly affects the stability and safety of power supply.

[0067] In the process of conceiving and implementing this application, the inventors found that there are at least the following problems: traditional meter box monitoring methods mostly rely on manual inspections, which are not only inefficient, but also prone to missed or false inspections, and cannot detect abnormal conditions of the meter box in a timely manner.

[0068] To this end, the present invention proposes a monitoring method for an electric meter box; it can be understood that a monitoring device for storing and executing the following method is provided in the monitoring equipment, and the monitoring device can be implemented by a main controller, such as MCU (Microcontroller Unit), DSP (Digital Signal Process), FPGA (Field Programmable Gate Array), SOC (System On Chip), etc.

[0069] Reference Figure 1 , Figure 1 The present invention is a flow chart of a monitoring method for an electric meter box according to an embodiment of the present invention. In an embodiment of the present invention, the monitoring method includes steps S100-S600, wherein:

[0070] S100, obtaining operation data and environmental data of the electric meter box;

[0071] S200, generating corresponding target operating state data based on the first algorithm, the operating data and the environmental data;

[0072] S300, determining abnormal data of the target operating status data according to the target operating status data and a preset operating model to determine abnormal distribution of the target operating status data;

[0073] S400, evaluating the abnormality degree of the electric meter box according to the abnormal data and the abnormal distribution, and generating an operation status score based on the abnormality degree;

[0074] S500, evaluating the operating status level of the electric meter box according to the operating status score and a preset score threshold;

[0075] S600: Generate corresponding status information according to the operating status level, and send the status information to a command center.

[0076] In this embodiment, the operation data may include at least one of voltage data, current data, power factor data, active power data and reactive power data; the environmental data may include at least one of temperature data, humidity data, air pressure data and wind speed data. The first algorithm may be an analysis algorithm based on machine learning, such as a deep learning algorithm, a neural network algorithm, etc., which is used to generate corresponding target operation status data according to the operation data and environmental data analysis of the electric meter box. The preset operation model may be a data model established according to the normal operation state of the electric meter box, which is used to compare with the predicted target operation status data to identify abnormal data. The distribution of abnormal data can reflect the problems that may exist in different parts or different operation parameters of the electric meter box, so as to more comprehensively evaluate its abnormality. The operation status score is a quantitative evaluation of the abnormality of the electric meter box, and the higher the score, the more serious the abnormality. The preset score threshold is used to divide the operation status score into different levels, so as to judge whether the operation status of the electric meter box is good. Finally, the status information generated according to the operation status level can be in the form of text, image or sound, etc., which is used to report the operation status of the electric meter box to the command center so that corresponding treatment measures can be taken in time.

[0077] This embodiment can realize real-time monitoring and fault warning of the meter box without relying on manual inspection, thus improving the monitoring efficiency and accuracy. At the same time, through comprehensive analysis of operation data and environmental data, the operation status of the meter box can be more comprehensively understood, and potential problems can be discovered and handled in time, thereby ensuring the stability and safety of power supply.

[0078] In addition, this embodiment can also be combined with other technical means to achieve all-round monitoring and management of the meter box. For example, the Internet of Things technology can be used to connect the meter box with the monitoring equipment to achieve real-time data transmission and sharing; big data analysis technology can be used to deeply mine and analyze the operation data of the meter box to discover potential rules and trends; cloud computing technology can also be used to store monitoring data on a cloud server to achieve remote backup and sharing of data.

[0079] This embodiment obtains the operating data and environmental data of the meter box, and then processes them based on the first algorithm to generate corresponding target operating status data, compares the target operating status data with the preset operating model, determines the abnormal data of the target operating status data, and determines the abnormal distribution of the target operating status data; then evaluates the abnormality level of the meter box, and generates an operating status score based on the abnormality level, compares the operating status score with a preset score threshold to evaluate the operating status level of the meter box, and finally generates corresponding status information, and sends the status information to the command center, thereby improving the real-time monitoring and fault warning capabilities of the meter box, and can achieve comprehensive inspection without relying on manual inspections, and can promptly detect abnormal conditions of the meter box, ensuring the stability and safety of power supply.

[0080] Further, see Figure 2 Another embodiment of the present invention provides a monitoring method for an electric meter box. Figure 1 In the embodiment shown, the step of evaluating the abnormality degree of the electric meter box according to the abnormal data and the abnormal distribution, and generating the operation status score based on the abnormality degree includes S410-S440, wherein:

[0081] S410, generating a corresponding abnormal state distribution diagram according to the abnormal data and abnormal distribution;

[0082] S420, identifying the abnormal state distribution map, determining the abnormal region position existing in the abnormal state distribution map and the abnormal index corresponding to the abnormal region position;

[0083] S430, determining the abnormality degree of the electric meter box according to the abnormal area position and the abnormality index;

[0084] S440: Generate the operation status score according to the abnormality degree and a preset status scoring standard.

[0085] In this embodiment, the abnormal data may include voltage anomaly, current anomaly, temperature anomaly, etc., and the abnormal distribution may reflect the spatial distribution or time change of these abnormal data in the meter box. By generating the corresponding abnormal state distribution map, the abnormal state inside the meter box can be intuitively displayed, which is convenient for operators to understand and analyze. The abnormal state distribution map can be in the form of a two-dimensional or three-dimensional image, and the degree and distribution of abnormal data can be represented by visual elements such as color and shape. When identifying the abnormal state distribution map, the location and range of the abnormal area can be determined by image recognition technology or manual analysis, and the corresponding abnormal index can be calculated. The abnormal index can be a quantitative value used to indicate the severity of the abnormal degree. According to the location and abnormal index of the abnormal area, the overall abnormal degree of the meter box can be comprehensively evaluated. The preset state scoring standard is a rule or standard for converting the abnormal degree into an operating state score. The preset state scoring standard can be formulated according to the actual situation, and the abnormal degree and the operating state score are mapped so as to generate a corresponding operating state score according to the abnormal degree. The operating state score can be a value between 0 and 100, which is used to quantitatively represent the operating state of the meter box. The higher the score, the more serious the abnormal degree. Through the steps of this embodiment, the abnormality of the meter box can be evaluated more accurately, and an accurate operating status score can be generated, providing strong support for subsequent fault warning and processing. The real-time monitoring and fault warning of the meter box can be better realized, the monitoring efficiency and accuracy are improved, and the stability and safety of the power supply are provided. Strong guarantee.

[0086] It should be noted that the above embodiments are only exemplary descriptions and do not constitute a limitation on the scope of protection of the present invention. In practical applications, the monitoring method can be appropriately adjusted and optimized according to specific needs, such as adding more monitoring parameters, using more advanced algorithms for data analysis, etc., to achieve more comprehensive and accurate monitoring and management of the meter box.

[0087] In this embodiment, based on the abnormal data and the abnormal distribution, an intuitive abnormal state distribution map can be generated, which can clearly show the abnormal states of different parts of the meter box or different operating parameters. By identifying the abnormal state distribution map, the location of the area where the abnormality exists and the abnormal index of these areas can be determined. The abnormal index is an indicator for quantitatively evaluating the degree of abnormality, which can be defined and calculated based on specific monitoring data and business needs. By combining the abnormal area location and the abnormal index, the degree of abnormality of the meter box can be more accurately evaluated, which improves the accuracy and reliability of the evaluation, helps to timely discover and deal with the fault problems of the meter box, and ensures the stable operation of the power system.

[0088] Further, see Figure 3 Another embodiment of the present invention provides a monitoring method for an electric meter box. Figure 2 In the embodiment shown, the monitoring method further includes S700-S1200, wherein:

[0089] S700, obtaining a plurality of historical operation data of the electric meter box, historical environment data corresponding to time nodes of the historical operation data, and historical fault types;

[0090] S800: constructing a target operation model of the electric meter box according to the historical operation data;

[0091] S900, training the target operation model based on the second algorithm, the historical environment data, the historical environment data and the historical fault type to generate a corresponding first operation model;

[0092] S1000, randomly selecting a plurality of the historical operation data and importing them into the first operation model to evaluate the operation accuracy of the first operation model;

[0093] S1100, if the operation accuracy exceeds a preset threshold, modifying the first operation model and re-importing the historical operation data for evaluation;

[0094] S1200: If the operation accuracy meets the requirement, confirm that the first operation model is a preset operation model.

[0095] In this embodiment, by obtaining multiple historical operation data of the meter box, historical environmental data corresponding to the time nodes of these historical operation data, and historical fault types, rich data support can be provided for subsequent model construction and training. The historical operation data may include historical records of parameters such as voltage, current, and power of the meter box, the historical environmental data may include historical data of environmental factors such as temperature and humidity, and the historical fault types record the types and situations of faults that occurred in the meter box in the past. These data are the basis for building and training accurate operation models.

[0096] Next, based on the historical operation data obtained, a target operation model of the meter box can be constructed. The target operation model is a mathematical model used to simulate and predict the operation status of the meter box. It can output the operation status information of the meter box based on the input operation data and environmental data. By constructing the target operation model, real-time monitoring and prediction of the operation status of the meter box can be achieved.

[0097] Then, the target operation model is trained using the second algorithm as well as historical environmental data, historical operation data, and historical fault types to generate a first operation model. The second algorithm can be a machine learning algorithm or a deep learning algorithm. By continuously iterating and optimizing the parameters and structure of the model, the model can better fit the historical data and have the ability to predict unknown data. During the training process, the model will learn the changing rules of the operating state of the meter box under different environmental conditions, as well as the possibility and characteristics of faults.

[0098] After the model training is completed, the model's operating accuracy needs to be evaluated. By randomly selecting multiple historical operating data and importing them into the first operating model, the model's prediction results for these data can be obtained, and the prediction results are compared with the actual results to calculate the model's accuracy. If the operating accuracy exceeds the preset threshold, it means that the model's prediction performance is poor, and the model needs to be corrected and the historical operating data needs to be re-imported for training. Methods for correcting the model can include adjusting model parameters, changing the model structure, etc. to improve the model's prediction performance.

[0099] If the operation accuracy of the model meets the requirements after correction, the first operation model can be determined as the preset operation model. The preset operation model is a fully trained and verified model that can accurately predict the operation status of the meter box under different conditions, providing a reliable basis for subsequent real-time monitoring and fault warning.

[0100] Through the steps of this embodiment, an accurate and reliable meter box operation model can be constructed to achieve real-time monitoring and prediction of the meter box operation status. This not only improves the monitoring efficiency and accuracy, but also provides strong support for timely discovery and handling of meter box faults, which helps to ensure the stable operation and power supply quality of the power system.

[0101] Further, see Figure 4 Another embodiment of the present invention provides a monitoring method for an electric meter box. Figure 3 In the embodiment shown, the step of constructing the target operation model of the electric meter box according to the historical operation data includes S810-S820, wherein:

[0102] S810, constructing an initial training data set according to the historical operation data, historical environment data, and historical fault types;

[0103] S820: Divide the initial training data set into a training set, a validation set, and a test set.

[0104] In this embodiment, an initial training data set is constructed based on historical operation data, historical environmental data, and historical fault types. This data set contains various information about the meter box during past operation and is the basis for subsequent construction and training of the target operation model. By collating and cleaning this data, the quality and accuracy of the data can be ensured, providing reliable data support for subsequent steps.

[0105] Next, the initial training data set is divided into a training set, a validation set, and a test set. The training set is used to train the target running model. By continuously iterating and optimizing the parameters and structure of the model, the model can learn the laws and features in the data. The validation set is used for verification during the model training process to evaluate the performance of the model and prevent overfitting. The test set is used for testing after the model training is completed to evaluate the generalization ability of the model and the actual application effect.

[0106] By dividing different data sets, historical data can be fully utilized to build and verify the target operation model, improving the reliability and stability of the model. At the same time, this division method also helps to timely discover and solve problems during the model training process, ensuring that the final model can accurately predict the operating status of the meter box, providing strong support for subsequent real-time monitoring and fault warning.

[0107] It should be noted that when dividing the data set, it is necessary to ensure that the data distribution and characteristics between the training set, validation set, and test set are similar to avoid the degradation of model performance due to data differences. At the same time, it is also necessary to select the appropriate data division ratio according to the specific application scenario and requirements to make full use of historical data and ensure the performance of the model.

[0108] The step of training the target operation model based on the second algorithm, the historical environment data, the historical environment data and the historical fault type to generate a corresponding first operation model includes S910-S930, wherein:

[0109] S910, training the initial operation model according to the training set to generate multiple candidate operation models;

[0110] S920, importing the verification set into the plurality of candidate operation models respectively, and calculating the accuracy of each candidate operation model according to the output result of each candidate operation model and the actual result of the verification set;

[0111] S930: Determine the candidate operation model with the highest accuracy as the first operation model.

[0112] In this embodiment, the initial operation model is trained according to the training set, and multiple candidate operation models are generated by continuously iterating and optimizing the parameters and structure of the model. These candidate operation models are gradually formed during the training process. They have different parameters and structures and can predict the operating status of the meter box. During the training process, the model will learn the laws and features in the historical data and try to fit these laws to improve the accuracy of the prediction.

[0113] In order to evaluate the performance of each candidate running model, the validation set is imported into these models respectively to obtain the output results of each model. Then, these output results are compared with the actual results of the validation set to calculate the accuracy of each model. Accuracy is an important indicator for measuring the prediction performance of a model, which reflects the closeness between the model prediction results and the actual results. By comparing the accuracy of different models, the model with the best performance can be selected.

[0114] Finally, the candidate operation model with the highest accuracy is determined as the first operation model. This model performs best among all candidate models and has high prediction accuracy and stability. It can be used as the final meter box operation model for subsequent real-time monitoring and fault warning. At the same time, through continuous iteration and optimization of the model, the performance and accuracy of the model can be further improved to meet the needs of practical applications.

[0115] The step of randomly selecting a plurality of the historical operation data and importing them into the first operation model to evaluate the operation accuracy of the first operation model includes S1010, wherein:

[0116] S1010. Import the test set into the first operation model. If the error rate between the output result of the first operation model and the actual result of the test set is less than a preset threshold, determine that the first operation model is a preset operation model.

[0117] In this embodiment, in order to more comprehensively evaluate the performance of the first running model, in addition to using the validation set for preliminary evaluation, the test set can be further used for more rigorous testing. The test set usually contains data different from the training set and the validation set, and is used to test the performance of the model on unseen data. The test set is imported into the first running model, the difference between the output results of the model and the actual results is observed, and the error rate is calculated. The error rate is an important indicator for measuring the prediction performance of the model, which reflects the prediction accuracy of the model on unknown data.

[0118] If the error rate between the output of the first running model and the actual results of the test set is less than the preset threshold, it means that the model can maintain a high prediction accuracy on unseen data and has good generalization ability. At this time, the first running model can be determined as the preset running model, that is, the model is considered to be mature and stable enough to be used for subsequent real-time monitoring and fault warning tasks. This helps to ensure that the final preset running model has high prediction accuracy and stability, providing reliable support for subsequent real-time monitoring and fault warning.

[0119] It should be noted that the setting of the preset threshold needs to be determined according to the actual application scenario and requirements. If the preset threshold is set too high, the model may be too conservative and unable to accurately predict some abnormal situations; if the preset threshold is set too low, it may introduce too many false positives and false negatives, affecting the actual application effect. Therefore, in actual applications, it is necessary to flexibly adjust the preset threshold according to the actual situation to find the best balance point.

[0120] Further, see Figure 5 Another embodiment of the present invention provides a monitoring method for an electric meter box. Figures 1 to 4 In any of the embodiments shown, the step of evaluating the operating status level of the electric meter box according to the operating status score and a preset score threshold includes S510-S530, wherein:

[0121] S510, obtaining a level relationship mapping set corresponding to the running status score;

[0122] S520, generating a corresponding state score segment according to the running state score and the preset score threshold, and identifying the corresponding score stage label;

[0123] S530: Evaluate the operating status level of the electric meter box according to the level relationship mapping set, the status score segment, and the score stage label.

[0124] In this embodiment, the operation status score is calculated based on multiple factors such as the operation data of the meter box, historical environmental data, and historical fault types, and is used to reflect the current operation status of the meter box. The higher the score, the better the operation status of the meter box; the lower the score, the more likely there is a fault or abnormality in the meter box.

[0125] In this embodiment, a hierarchical relationship mapping set corresponding to the operating status score is obtained. The hierarchical relationship mapping set is a pre-set mapping table used to map the operating status score to the corresponding operating status level. It is usually formulated according to actual application requirements and business rules, and includes different scoring ranges and corresponding level labels. According to the operating status score and the preset scoring threshold, a corresponding status score segment is generated. The preset scoring threshold is determined based on factors such as historical data, expert experience or business needs, and is used to divide different operating status levels. According to the score and threshold, the operating status score can be divided into different score segments, and each score segment corresponds to a specific operating status level range.

[0126] At the same time, the corresponding score stage label is identified. In the process of generating the status score segment, a corresponding label is assigned to each score segment to identify the operating status level represented by the score segment. These labels can be text descriptions, digital codes or other forms of identifiers to facilitate subsequent processing and display.

[0127] Finally, the operating status level of the meter box is evaluated according to the level relationship mapping set, the state score segment, and the score stage label. By comparing the operating status score with the level relationship mapping set, the corresponding operating status level is found. At the same time, combined with the state score segment and the score stage label, the specific operating status level range of the meter box can be further determined, and the corresponding evaluation results can be given, which can comprehensively and accurately evaluate the operating status level of the meter box.

[0128] Further, see Figure 6 Another embodiment of the present invention provides a monitoring method for an electric meter box. Figure 5 In the embodiment shown, the step of generating a corresponding state score segment according to the running state score and the preset score threshold, and identifying the corresponding score stage label at that time, includes S521-S524, wherein:

[0129] S521, determining a target score interval to which the running status score belongs according to the running status score and the preset score threshold;

[0130] S522, generating a corresponding state score segment according to the target score interval;

[0131] S523, determining a target score stage label corresponding to the state score segment according to the state score segment;

[0132] S524: According to the target score stage label, identify the score stage label corresponding to the current time.

[0133] In this embodiment, the target score interval to which the operating status score belongs is determined based on the operating status score and a preset score threshold, wherein the preset score threshold divides the score range into a plurality of continuous intervals, each interval corresponding to a specific operating status level. By comparing the operating status score with these thresholds, the target score interval to which the score belongs can be determined. After determining the target score interval, a corresponding state score segment is generated based on the interval. The state score segment is a specific description of the target score interval, which includes all possible scores within the interval. Generating state score segments helps to divide the operating status levels more finely.

[0134] Next, the corresponding target score stage label is determined according to the state score segment. The target score stage label is an identifier associated with the state score segment, which is used to identify the operating state level represented by the score segment. These labels can be customized according to actual application requirements for easy understanding and use.

[0135] Finally, according to the target score stage label, the corresponding score stage label is identified. This means that the target score stage label is associated with the current operating status score to indicate the current operating status level of the meter box. This can clearly identify the operating status level of the meter box, accurately and objectively reflect the operating status of the meter box, and avoid the interference of subjective judgment. At the same time, by generating status score segments and score stage labels, the operating status level of the meter box can be more intuitively displayed, which improves the efficiency and accuracy of monitoring.

[0136] Further, see Figure 7 Another embodiment of the present invention provides a monitoring method for an electric meter box. Figures 1 to 4 In any of the embodiments shown, the step of generating corresponding status information according to the operating status level and sending the status information to the command center includes:

[0137] S610, determining, according to the operating status level, corresponding abnormal area information of the electric meter box and an abnormal problem corresponding to the abnormal area information;

[0138] S620, generating corresponding status information according to the abnormal area information and the abnormal problem;

[0139] S630, generating a corresponding warning information data packet according to the status information;

[0140] S640: Based on the first communication protocol, send the warning information data packet to the command center so that the command center can remotely monitor and handle faults of the electric meter box.

[0141] In this embodiment, abnormal problems may include damage to internal components of the meter box, abnormal power lines, communication failures, etc. These abnormal problems are determined based on the operating status level and the specific operating data of the meter box, and can directly reflect the specific problems currently existing in the meter box. At the same time, the abnormal area information is used to indicate the specific location or area where the abnormal problem occurs, which may be a component, circuit board or power line inside the meter box. By determining the abnormal area information, the source of the fault can be located more accurately. According to the abnormal area information and the abnormal problem, the corresponding status information is generated. The status information is a detailed description of the current operating status of the meter box, including key information such as the abnormal area, abnormal problem, and occurrence time.

[0142] After determining the abnormal area information and abnormal problems, the corresponding status information is generated. The status information is a detailed description of the current operating status of the meter box, including abnormal area information, abnormal problems and other possible operating data. These status information can fully reflect the operating status of the meter box and provide important reference for subsequent analysis and processing.

[0143] Next, a corresponding warning information data packet is generated based on the status information. The warning information data packet is an encapsulation and formatting of the status information for easy transmission and processing. The warning information data packet may contain necessary information such as status information, unique identification of the meter box, and timestamp to ensure that the command center can accurately receive and understand the status information of the meter box.

[0144] Finally, based on the first communication protocol, the warning information data packet is sent to the command center. The first communication protocol is a protocol for data transmission, which ensures the stability and accuracy of data during transmission. After receiving the warning information data packet, the command center can understand the operating status of the meter box in real time, and perform remote monitoring and fault handling. This step realizes remote monitoring and management of the meter box, improves the timeliness and efficiency of fault handling, and reduces operating costs and maintenance costs.

[0145] In this embodiment, the corresponding abnormal area information of the meter box and the abnormal problem corresponding to the abnormal area information are determined according to the operating status level. The operating status level reflects the overall operating status of the meter box, while the abnormal area information and abnormal problem are detailed descriptions of specific faults or abnormal conditions. By comprehensively evaluating the operating status level and other relevant information, it is possible to determine the faults or abnormalities that may exist in the meter box, and determine the specific location and type of problem. This helps the command center quickly locate and handle faults or abnormal conditions in the meter box.

[0146] Further, see Figure 8 Another embodiment of the present invention provides a monitoring method for an electric meter box. Figure 7In the embodiment shown, after the step of generating a corresponding warning information data packet according to the status information, the step further includes:

[0147] S650, obtaining geographical location information of the electric meter box and information of maintenance personnel within a preset distance from the geographical location information;

[0148] S660, generating a corresponding maintenance instruction according to the status information and the maintenance personnel information;

[0149] S670. Based on the second communication protocol, send the maintenance instruction to the smart terminal of the corresponding maintenance personnel to notify the corresponding maintenance personnel to maintain the electric meter box according to the maintenance instruction.

[0150] In this embodiment, the preset distance can be set according to the actual situation, and is usually determined according to the geographical location of the meter box and the distribution of maintenance personnel. This distance is intended to ensure that maintenance personnel can respond in time and arrive at the site for repair or processing. First, through relevant positioning technology, the geographical location information of the meter box is obtained. This can be achieved through GPS positioning, base station positioning or other positioning technologies. The accuracy of the geographical location information is crucial for the subsequent determination of maintenance personnel to ensure that the maintenance personnel can accurately find the location of the meter box.

[0151] Next, based on the acquired geographic location information, query the maintenance personnel information within the preset distance. This information may include the maintenance personnel's name, contact information, identifier of the smart terminal device, etc. By comparing the geographic location information and the distribution information of the maintenance personnel, it can be determined which maintenance personnel are close to the meter box and have the ability to handle related issues. After obtaining the maintenance personnel information, the corresponding maintenance instructions are generated based on the previously generated status information and maintenance personnel information. The maintenance instructions should include key information such as the specific location of the meter box, fault description, and measures to be taken to ensure that the maintenance personnel can clearly understand the problems that need to be dealt with and take appropriate measures to repair or maintain them.

[0152] Finally, based on the second communication protocol, the maintenance instruction is sent to the smart terminal of the corresponding maintenance personnel. The second communication protocol can be a text message, email, instant messaging tool or other communication method suitable for smart terminals. Through the smart terminal, the maintenance personnel can receive the maintenance instruction in real time, respond quickly according to the instruction content, and go to the meter box to perform maintenance operations.

[0153] In this embodiment, by obtaining the geographical location information of the meter box, the specific location of the meter box can be accurately understood, which is helpful for subsequent fault handling and maintenance work. At the same time, based on the geographical location information, the maintenance personnel information within a preset distance close to the location can be queried, including the contact information and location of the maintenance personnel. This can ensure that when a fault or abnormal situation occurs, the nearby maintenance personnel can be quickly contacted for processing. After obtaining the geographical location information and the maintenance personnel information, the corresponding maintenance instructions are generated according to the status information and the maintenance personnel information. The maintenance instructions contain key contents such as the status information, location information and maintenance operations required of the meter box, which can guide the maintenance personnel to accurately and efficiently handle faults or abnormal situations.

[0154] Then, based on the second communication protocol, the maintenance instruction is sent to the corresponding maintenance personnel's smart terminal. The second communication protocol is a protocol for sending maintenance instructions, ensuring that the instructions can be accurately and promptly conveyed to the maintenance personnel. After receiving the maintenance instruction, the maintenance personnel can perform corresponding maintenance operations on the meter box according to the instruction content, which improves processing efficiency and accuracy and reduces the impact of faults on power supply. At the same time, by using geographic location information and maintenance personnel information, resources can be dispatched and maintained more accurately, improving resource utilization efficiency.

[0155] The present invention also proposes a control device, comprising: the control device comprising: a memory, a processor, and a monitoring program for an electric meter box stored in the memory and executable on the processor, the monitoring program for the electric meter box being configured to implement the monitoring method for the electric meter box as described above.

[0156] It is worth noting that since the control device of the present invention is based on the above-mentioned monitoring method for the electric meter box, the embodiments of the control device of the present invention include all technical solutions of all embodiments of the above-mentioned monitoring method for the electric meter box, and the technical effects achieved are also exactly the same, which will not be repeated here.

[0157] The present invention further provides a monitoring device, which includes the control device as described in the above embodiment.

[0158] It is worth noting that since the monitoring device of the present invention is based on the above-mentioned control device, the embodiments of the monitoring device of the present invention include all technical solutions of all embodiments of the above-mentioned control device, and the technical effects achieved are also exactly the same, which will not be repeated here.

[0159] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0160] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0161] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, including a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0162] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for monitoring an electric meter box, characterized in that: The monitoring method comprises: Obtaining operation data and environmental data of the electric meter box; Based on the first algorithm, the operating data and the environmental data, generating corresponding target operating state data; Determine abnormal data of the target operating state data according to the target operating state data and a preset operating model to determine abnormal distribution of the target operating state data; According to the abnormal data and the abnormal distribution, the abnormal degree of the electric meter box is evaluated, and based on the abnormal degree, an operation status score is generated; According to the operating status score and a preset scoring threshold, evaluating the operating status level of the electric meter box; Generate corresponding status information according to the operating status level, and send the status information to the command center; The step of evaluating the abnormality degree of the electric meter box according to the abnormal data and the abnormal distribution, and generating the operating status score based on the abnormality degree, comprises: Generate a corresponding abnormal state distribution diagram according to the abnormal data and abnormal distribution; Identify the abnormal state distribution map, determine the abnormal area position existing in the abnormal state distribution map and the abnormal index corresponding to the abnormal area position; Determining the abnormality degree of the electric meter box according to the abnormal area position and the abnormality index; Generating the operating status score according to the abnormality degree and a preset status scoring standard; The monitoring method further comprises: Acquire multiple historical operation data of the electric meter box, historical environment data corresponding to time nodes of the historical operation data, and historical fault types; Constructing a target operation model of the electric meter box according to the historical operation data; Based on the second algorithm, the historical environmental data, the historical environmental data, and the historical fault types, training the target operation model to generate a corresponding first operation model; Randomly selecting a plurality of the historical operation data and importing them into the first operation model to evaluate the operation accuracy of the first operation model; If the operation accuracy exceeds a preset threshold, modifying the first operation model and re-importing the historical operation data for evaluation; If the operation accuracy meets the requirement, confirming that the first operation model is a preset operation model; The step of constructing a target operation model of the electric meter box according to the historical operation data comprises: Constructing an initial training data set based on the historical operation data, historical environmental data, and historical fault types; Dividing the initial training data set into a training set, a validation set, and a test set; The step of training the target operation model based on the second algorithm, the historical environment data, the historical environment data and the historical fault type to generate a corresponding first operation model includes: According to the training set, an initial operation model is trained to generate multiple candidate operation models; Importing the verification set into the plurality of candidate operation models respectively, and calculating the accuracy of each candidate operation model according to the output result of each candidate operation model and the actual result of the verification set; Determining the candidate operation model with the highest accuracy as the first operation model; The step of randomly selecting a plurality of the historical operation data and importing them into the first operation model to evaluate the operation accuracy of the first operation model includes: The test set is imported into the first operation model. If the error rate between the output result of the first operation model and the actual result of the test set is less than a preset threshold, the first operation model is determined to be a preset operation model.

2. The monitoring method according to claim 1, characterized in that: The step of evaluating the operating status level of the electric meter box according to the operating status score and a preset score threshold comprises: Obtain a level relationship mapping set corresponding to the running status score; Generate a corresponding state score segment according to the running state score and the preset score threshold, and identify the corresponding score stage label; The operating status level of the electric meter box is evaluated according to the level relationship mapping set, the status score segment and the score stage label.

3. The monitoring method according to claim 2, characterized in that: The step of generating a corresponding state score segment according to the running state score and the preset score threshold, and identifying the corresponding score stage label at that time, includes: Determine the target score range to which the running status score belongs according to the running status score and the preset score threshold; According to the target score interval, generating a corresponding state score segment; According to the state score segment, determining the target score stage label corresponding to the state score segment; According to the target score stage label, the score stage label corresponding to the current time is identified.

4. The monitoring method according to claim 1, characterized in that: The step of generating corresponding status information according to the operating status level and sending the status information to the command center includes: According to the operating status level, determining the corresponding abnormal area information of the electric meter box and the abnormal problem corresponding to the abnormal area information; Generate corresponding status information according to the abnormal area information and the abnormal problem; Generate a corresponding warning information data packet according to the status information; Based on the first communication protocol, the warning information data packet is sent to the command center so that the command center can remotely monitor and handle faults of the electric meter box.

5. The monitoring method according to claim 4, characterized in that: After the step of generating a corresponding warning information data packet according to the status information, the method further includes: Obtaining geographical location information of the electric meter box and maintenance personnel information within a preset distance from the geographical location information; Generate a corresponding maintenance instruction according to the status information and the maintenance personnel information; Based on the second communication protocol, the maintenance instruction is sent to the intelligent terminal of the corresponding maintenance personnel to notify the corresponding maintenance personnel to maintain the electric meter box according to the maintenance instruction.

6. A monitoring device, characterized in that: The monitoring device comprises: a memory, a processor, and a monitoring program for an electric meter box stored in the memory and executable on the processor, wherein the monitoring program for the electric meter box is configured to implement the monitoring method for an electric meter box as claimed in any one of claims 1 to 5.

7. A monitoring device, characterized in that: Comprising the monitoring device as claimed in claim 6.

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