Outdoor low-voltage line automatic monitoring data processing visualization system

Abstract

The invention discloses an outdoor low-voltage line automatic monitoring data processing visualization system, which belongs to the technical field of outdoor low-voltage line monitoring and comprises a user side and a platform side. The platform end comprises a demand analysis module, a reserve module and a simulation module; the demand analysis module is used for carrying out data processing demand analysis in real time and determining a data processing demand and a data processing mode; the reserve module is used for data storage and management; the simulation module is used for establishing a demand simulation model and arranging the demand simulation model into the custom module in the corresponding user side; the user side comprises an acquisition module, a custom module, a data processing module and a display module; the acquisition module is used for monitoring an outdoor low-voltage line in real time to obtain line monitoring data; the user-defined module is used for performing user-defined processing to obtain a user-defined demand and a data processing mode; the data processing module is used for processing the line monitoring data to obtain display material data, and the display module is used for monitoring display.

Description

Technical Field

[0001] The invention belongs to the technical field of outdoor low-voltage line monitoring, and in particular is an outdoor low-voltage line automatic monitoring data processing visualization system. Background Art

[0002] With the rapid development and intelligent transformation of the power industry, the monitoring and management of outdoor low-voltage lines has become increasingly important. In order to achieve real-time monitoring and data analysis of line operation status, various automatic monitoring systems and data processing technologies have emerged. Among them, visualization technology, as an intuitive and efficient means of information display, has been widely used in outdoor low-voltage line monitoring.

[0003] However, existing outdoor low-voltage line automatic monitoring data processing visualization systems generally have certain limitations in visualization. Specifically, these systems can often only display according to preset visualization modes, such as fixed chart types, layouts, and colors. Although this preset visualization mode can meet basic monitoring needs to a certain extent, it cannot be dynamically adjusted according to the personalized needs of users.

[0004] In actual applications, different users may have different concerns and analysis requirements for data. For example, some users may be more concerned about the voltage fluctuation of the line, while others may be more concerned about the changing trend of the current. In addition, users may need to achieve different display purposes for some special reasons. However, existing visualization systems often cannot provide sufficient flexibility and configurability to meet these personalized needs.

[0005] Therefore, how to design an outdoor low-voltage line automatic monitoring data processing visualization system that can be dynamically adjusted according to the user's personalized needs has become a problem that needs to be solved urgently. Summary of the invention

[0006] In order to solve the problems existing in the above-mentioned solutions, the present invention provides an outdoor low-voltage line automatic monitoring data processing visualization system.

[0007] The purpose of the present invention can be achieved through the following technical solutions: An outdoor low-voltage line automatic monitoring data processing visualization system includes a user end and a platform end; The platform end includes a demand analysis module, a reserve module and a simulation module; The demand analysis module is used to perform data processing demand analysis in real time, determine the corresponding data processing demand, and set the corresponding data processing method for the data processing demand; send the data processing demand and the data processing method to the reserve module; The reserve module is used for data storage and management, establishing a cloud storage repository, receiving data processing requirements and data processing methods in real time, sending the received data processing requirements and data processing methods to the cloud storage repository for storage; and generating a requirement reserve table according to the data processing requirements stored in the cloud storage repository, and sending the requirement reserve table to the requirement analysis module; The simulation module is used for establishing a requirement simulation model, and the requirement simulation model is used for simulating data processing according to monitoring requirements to form a corresponding data processing simulation process; arranging the requirement simulation model into a custom module in a corresponding client.

[0008] Furthermore, the method for determining data processing requirements includes: Step SA1: Obtain historical power grid monitoring data, analyze the historical power grid monitoring data to obtain several candidate historical requirements; Estimate the requirement values of the candidate historical requirements according to the historical power grid monitoring data; estimate the implementation costs of the candidate historical requirements to obtain corresponding implementation costs; Substitute the requirement values and implementation costs of the candidate historical requirements into the screening formula in the first stage to calculate the screening values of the candidate historical requirements; Screen the candidate historical requirements according to the screening values to determine several data processing requirements; Step SA2: Obtain a requirement reserve table, identify the application feedback requirements of each client; analyze the application feedback requirements through the requirement reserve table to determine new user requirements; Step SA3: Analyze the new user requirements to determine corresponding requirement values and implementation costs; Step SA4: Substitute the requirement values and implementation costs of the new user requirements into the screening formula in the second stage to calculate the screening values of the new user requirements; Step SA5: Screen the new user requirements according to the screening values to determine data processing requirements; Step SA6: Loop through steps SA2 to SA5.

[0009] Furthermore, the screening formula is: ; In the formula: SA is the screening value; XQ is the requirement value; CB is the implementation cost; b1 and b2 are both proportionality coefficients in the first stage, and the value ranges are 0 < b1 < 1, 0 < b2 < 1; b3 and b4 are both proportionality coefficients in the second stage, and the value ranges are 0 < b3 < 1, 0 < b4 < 1.

[0010] Furthermore, the method for analyzing application feedback requirements through a requirement reserve table includes: Establishing a reserve calibration model, performing real-time identification on the demand reserve table, and obtaining a calibration set, wherein the calibration set is composed of data processing requirements in the demand reserve table; Analyzing the application feedback requirement and the calibration set by using the reserve calibration model to obtain a reserve calibration value of the application feedback requirement; The application feedback demand with a reserve calibration value of 1 is marked as a new user demand.

[0011] Furthermore, the expression of the reserve calibration model is: ; Where: (s, U) is the input data, s is the corresponding application feedback requirement, and U is the calibration set; s→U means that the corresponding application feedback requirement does not belong to the calibration set; the output data is the reserve calibration value CP(s, U), and the reserve calibration value is 1 or 0.

[0012] The user terminal includes a collection module, a custom module, a data processing module and a display module; The acquisition module is used to monitor the outdoor low-voltage line in real time and obtain corresponding line monitoring data; The custom module is used by the user to perform custom processing according to monitoring requirements, and obtain corresponding custom requirements and data processing methods corresponding to the custom requirements; The data processing module is used to process the line monitoring data, receive the line monitoring data, and pre-process the line monitoring data; Determine user processing requirements; identify the data processing method of the user processing requirements, process the line monitoring data according to the data processing method, obtain display material data, and label the display material data with corresponding user processing requirement tags; The display module is used for monitoring and displaying. The platform establishes a monitoring and displaying model according to user requirements. The display material data that meets the user's processing requirements is acquired in real time, and the display material data is input into the monitoring and displaying model for display.

[0013] Furthermore, the custom processing methods include: Step SC1: Obtain the user's monitoring needs; connect to the cloud storage library, obtain the demand reserve table, screen the demand reserve table according to the monitoring needs, obtain the data processing needs that meet the monitoring needs, mark the data processing needs as recommended needs, and display the recommended needs to the user; When the user selects the recommended requirement as a custom requirement, the data processing method of the recommended requirement is identified and the analysis ends; When the user does not select the recommended requirement as the custom requirement, proceed to step SC2; Step SC2: Analyze the monitoring demand through the demand simulation model to obtain a data processing simulation process, and display the data processing simulation process to the user; the user adjusts the monitoring demand according to the data processing simulation process to obtain a new monitoring demand; Step SC3: loop step SC2 until the data processing simulation process meets the user's requirements, and determine the custom requirements and data processing method according to the data processing simulation process.

[0014] Furthermore, the method for determining the user processing requirements includes: Identify fixed processing requirements; identify users’ customized requirements and corresponding data processing methods in real time; Mark both custom requirements and fixed requirements as user-processed requirements.

[0015] Compared with the prior art, the present invention has the following beneficial effects: Through the present invention, users can freely select or define monitoring requirements according to their actual needs, thereby realizing personalized data display. This innovative design not only improves the user's monitoring experience, but also greatly improves the efficiency and accuracy of data analysis. The present invention also has good scalability and compatibility, and can facilitate monitoring expansion according to user needs, adapt to the user's changing monitoring needs, and avoid affecting the user experience due to solidified display. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention 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, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 This is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0018] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] like Figure 1 As shown, an outdoor low-voltage line automatic monitoring data processing visualization system includes a user end and a platform end; The platform end is used and updated by the platform party, including a demand analysis module, a reserve module and a simulation module; The requirement analysis module is used to conduct real-time data processing requirement analysis, determine corresponding data processing requirements, and set corresponding data processing methods for the data processing requirements.

[0020] In one embodiment, the method for determining data processing requirements includes: Obtain historical power grid monitoring data, mainly historical data for analyzing monitoring data, which is used to determine its monitoring requirements. Determine data processing requirements according to the monitoring requirements and mark them as candidate historical requirements; analyze the historical power grid monitoring data to obtain several candidate historical requirements; Estimate the sum of demand probabilities of corresponding candidate historical requirements in the context of outdoor low-voltage lines, and mark it as the demand value. This is equivalent to estimating the probability of needing this candidate historical requirement in the context of outdoor low-voltage lines. It can be corrected and estimated using historical ratios to determine the demand value; specifically, it can also be estimated based on other existing technologies, such as establishing a demand analysis model based on neural networks such as CNN or DNN, and establishing a corresponding training set for training through artificial means. The training set includes input data and output data. The input data is the candidate historical requirements to be analyzed and subsequent new user requirements, and the output data is the demand value; analyze through the demand analysis model after successful training to determine the corresponding demand value; Estimate the cost of candidate historical requirements to obtain the corresponding implementation cost, that is, estimate the cost based on the current system architecture. It is expected to cost to implement this candidate historical requirement in the current situation, because the implementation costs of the same candidate historical requirement in different situations are different; specifically, it can be estimated based on existing cost estimation methods. Calculate the screening value of the corresponding candidate historical requirement according to the screening formula. The screening formula is: ; In the formula: SA is the screening value; XQ is the demand value; CB is the implementation cost; b1 and b2 are both proportionality coefficients in the first stage, and the value range is 0 < b1 < 1, 0 < b2 < 1; b3 and b4 are both proportionality coefficients in the second stage, and the value range is 0 < b3 < 1, 0 < b4 < 1; the first stage is the stage of determining data processing requirements in the early stage, that is, the platform establishment stage; the second stage is the stage of determining data processing requirements in the subsequent stage, that is, the stage of updating according to the actual situation of the user side after the platform is established; Mark the candidate historical requirements with a screening value greater than the threshold X1 as data processing requirements; this is the first stage of determining data processing requirements; Obtain the demand reserve table in real time; identify the data processing requirements of each user-side application in real time. For the sake of distinction, mark the data processing requirements of the application at the user side as application feedback requirements; it needs to be collected under the authorization of the corresponding user. Analyze the identified application feedback requirements through the demand reserve table to determine the new user requirements; Analyze the needs of new users and determine the corresponding demand value and implementation cost; The corresponding screening value is calculated according to the screening formula, and the new user demands with screening values ​​greater than the threshold X1 are marked as data processing demands; this is the second stage of determining the data processing demands.

[0021] In one embodiment, each identified application feedback requirement is analyzed through a requirement reserve table, and verification analysis may be performed based on existing methods.

[0022] In one embodiment, the method for analyzing application feedback requirements through the requirement reserve table includes: A reserve calibration model is established, and the expression of the reserve calibration model is: ; Where: (s, U) is the input data, s is the corresponding application feedback requirement, and U is the calibration set; s→U means that the corresponding application feedback requirement does not belong to the calibration set; the output data is the reserve calibration value CP (s, U), and the reserve calibration value is 1 or 0; The demand reserve table is identified in real time to obtain a calibration set, where the calibration set is composed of various data processing requirements in the demand reserve table; Analyze application feedback requirements and calibration sets through a reserve calibration model to obtain reserve calibration values ​​corresponding to the application feedback requirements; The application feedback requirements with a reserve calibration value of 1 are marked as new user requirements.

[0023] The reserve module is used to store and manage data processing requirements and corresponding data processing methods using cloud storage technology. Cloud storage has the advantages of elastic scalability, high availability and low cost, and can meet the growing needs of data processing requirements and corresponding data processing methods. Specifically, a cloud storage library can be established based on cloud storage technology to store real-time data processing requirements and corresponding data processing methods.

[0024] The simulation module is used to establish a demand simulation model, dynamically update the demand simulation model, and place the demand simulation model in a custom module in the corresponding user terminal, and then update it according to the update of the demand simulation model. The demand simulation model is used to simulate data processing according to monitoring requirements and form a corresponding data processing simulation process, such as showing what data needs to be applied to achieve the monitoring requirements, what data processing results are obtained, and how to handle the restrictions in the monitoring requirements, that is, to display the detailed process as much as possible, so that users can adjust the monitoring requirements according to the data processing results.

[0025] In one embodiment, the demand simulation model is established based on existing intelligent technology, and can be subsequently optimized for learning based on user feedback data. For example, it is established based on a neural network, and a training set is established manually for training. The training set includes input data and output data, where the input data is the monitoring demand and the output data is the data processing simulation process.

[0026] The user terminal is used by the user and includes a collection module, a custom module, a data processing module and a display module; The acquisition module is used to monitor the outdoor low-voltage line in real time and obtain corresponding line monitoring data, which includes current, voltage and other related data.

[0027] In one embodiment, the outdoor low-voltage line can be monitored using existing monitoring equipment, such as current monitoring equipment, voltage monitoring equipment, multi-function monitoring equipment, and the like.

[0028] Exemplarily, a fixed current monitor may be used for current monitoring, and the fixed current monitor includes: Current Sensor: Function: The current sensor is the core component of the fixed current monitor, which is used to directly measure the current in the circuit. It can convert the current signal into a voltage signal or a digital signal for subsequent processing and analysis.

[0029] Type: Common current sensors include Hall sensors, shunts, transformers, etc. Different types of sensors may differ in measurement range, accuracy, response speed, etc.

[0030] Signal processing circuit: Function: The signal processing circuit is used to amplify, filter, linearize and process the signal output by the current sensor to improve the accuracy and stability of the measurement.

[0031] Composition: The signal processing circuit may include components such as operational amplifiers, filters, analog-to-digital converters, etc. The selection and design of these components will directly affect the measurement performance and stability of the equipment.

[0032] Microcontroller (MCU): Function: The microcontroller is responsible for receiving the signal output by the signal processing circuit and further processing and analysis. It can also control the operation of the communication interface, display module and other components of the device.

[0033] Features: Microcontrollers usually have the characteristics of low power consumption, high performance, and easy programming. Through programming, complex measurement algorithms and data processing functions can be realized.

[0034] Communication interface: Function: The communication interface is used to upload the data measured by the fixed current monitor to the host computer, cloud platform or other monitoring system. Common communication interfaces include RS-485, Ethernet, Wi-Fi, etc.

[0035] Selection: The choice of communication interface will depend on the user's specific needs and application scenarios. For example, in situations where remote monitoring is required, Ethernet or Wi-Fi interfaces can be selected.

[0036] Power module: Function: The power module provides a stable power supply for the fixed current monitor. It usually includes components such as power filters and voltage stabilizers to ensure that the equipment can work normally under various voltage fluctuations and interferences.

[0037] Design: The design of the power module needs to take into account factors such as the power consumption of the equipment and the operating environment temperature to ensure its long-term stable operation.

[0038] Display module (optional): Function: The display module is used to directly display the measured current value or other related information on the device. This helps users quickly understand the current status in the circuit.

[0039] Type: Common display modules include LCD screens, LED digital tubes, etc. According to the size and cost requirements of the equipment, you can choose a suitable display module.

[0040] Housing and installation accessories: Function: The housing is used to protect the internal components of the fixed current monitor from interference and damage from the external environment. The mounting accessories are used to fix the device on the circuit board or other mounting locations.

[0041] Design: The design of the housing and mounting accessories needs to take into account factors such as the size, weight, and heat dissipation of the device to ensure reliability and ease of use.

[0042] The custom module is used by the user to perform custom processing according to monitoring requirements, and obtain corresponding custom requirements and data processing methods corresponding to the custom requirements.

[0043] In one embodiment, the method of custom processing includes: Step SC1: The user inputs monitoring requirements, which are descriptions of the user's customized requirements and data processing methods, such as the desired data processing results, for example, active loss, reactive loss, real-time load, harmonic content, line impedance and other corresponding processing results, and can also limit time periods and other requirements; connect to the cloud storage library, obtain the demand reserve table, screen the demand reserve table according to the monitoring requirements, and determine the data processing requirements that meet the monitoring requirements. For example, if 80% is met, it is considered to meet the monitoring requirements. The specific settings are based on the platform or user needs; mark the data processing requirements that meet the monitoring requirements as recommended requirements, and there can be multiple recommended requirements, and display the recommended requirements to the user; When the user selects a recommended requirement as a custom requirement, the data processing method corresponding to the recommended requirement is identified, and the analysis ends without performing subsequent steps; When the user does not select the recommended requirement as the custom requirement, proceed to step SC2; Step SC2: Analyze the monitoring demand through the demand simulation model, obtain the data processing simulation process, and display the obtained data processing simulation process to the user; the user adjusts the monitoring demand according to the data processing simulation process to obtain new monitoring demand; Step SC3: loop step SC2 until the data processing simulation process meets the user's requirements, and determine the custom requirements and data processing methods according to the corresponding data processing simulation process.

[0044] The data processing module is used to process the line monitoring data, receive the line monitoring data, and pre-process the line monitoring data, such as cleaning, denoising, filtering, etc., to improve the accuracy and reliability of the line monitoring data; Determine the data processing requirements of the user terminal and mark them as user processing requirements; Identify the data processing method corresponding to the user processing requirement, process the line monitoring data according to the data processing method, obtain display material data, and mark the display material data with the corresponding user processing requirement label.

[0045] In one embodiment, a method for determining a user processing requirement includes: Connect to the cloud storage library, obtain the demand reserve table, display the demand reserve table to the user, and let the user determine the fixed processing demand; the fixed processing demand is generally determined by the platform and the user when the system is established; Identify users’ customized needs and corresponding data processing methods in real time; Mark both custom requirements and fixed requirements as user-processed requirements.

[0046] The display module is used for monitoring and displaying. A monitoring and displaying model is established according to user requirements. The monitoring and displaying model is established based on existing visualization technology and is used to display display material data according to a preset display mode, such as a chart, a three-dimensional display, and other display modes. For displaying customized requirements, the corresponding display part can be supplemented in the monitoring and displaying model according to user requirements, such as a curve chart form, and then the corresponding curve chart template is automatically supplemented according to the corresponding display material data, and then the monitoring and display is performed. Specifically, it can be implemented in combination with existing technologies, such as custom supplementation based on image recognition technology, generating a display template according to the display mode selected by the user, and supplementing it to the monitoring and displaying model after adjustment by the user. Obtain display material data for each user's processing needs, and input the display material data into the monitoring display model for display.

[0047] The above formulas are all calculated by removing dimensions and taking numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data.

[0048] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An outdoor low-voltage line automatic monitoring data processing visualization system, characterized in that: Including user side and platform side; The platform end includes a demand analysis module, a reserve module and a simulation module; The demand analysis module is used to perform data processing demand analysis in real time, determine the corresponding data processing demand, and set the corresponding data processing method for the data processing demand; send the data processing demand and the data processing method to the reserve module; The reserve module is used for data storage and management, establishing a cloud storage library, receiving data processing requirements and data processing methods in real time, and sending the received data processing requirements and data processing methods to the cloud storage library for storage; and generating a demand reserve table according to the data processing requirements stored in the cloud storage library, and sending the demand reserve table to the demand analysis module; The simulation module is used to establish a demand simulation model, and the demand simulation model is used to perform data processing simulation according to monitoring requirements to form a corresponding data processing simulation process; the demand simulation model is arranged in a custom module in the corresponding user terminal; The user terminal includes a collection module, a custom module, a data processing module and a display module; The acquisition module is used to monitor the outdoor low-voltage line in real time and obtain corresponding line monitoring data; The custom module is used by the user to perform custom processing according to monitoring requirements, and obtain corresponding custom requirements and data processing methods corresponding to the custom requirements; The data processing module is used to process the line monitoring data, receive the line monitoring data, and pre-process the line monitoring data; Determine user processing requirements; identify the data processing method of the user processing requirements, process the line monitoring data according to the data processing method, obtain display material data, and label the display material data with corresponding user processing requirement tags; The display module is used for monitoring and displaying. The platform establishes a monitoring and displaying model according to user requirements. The display material data that meets the user's processing requirements is acquired in real time, and the display material data is input into the monitoring and displaying model for display.

2. According to claim 1, an outdoor low-voltage line automatic monitoring data processing visualization system is characterized in that: Methods for determining data processing requirements include: Step SA1: acquiring historical power grid monitoring data, analyzing the historical power grid monitoring data, and obtaining a number of historical demands to be selected; Estimate the demand value of the selected historical demand according to the historical data of power grid monitoring; estimate the cost of the selected historical demand to obtain the corresponding implementation cost; Substituting the demand value and implementation cost of the historical demand to be selected into the screening formula of the first stage to calculate the screening value of the historical demand to be selected; Filter the historical requirements to be selected according to the filtering value to determine a number of data processing requirements; Step SA2: Obtain a demand reserve table to identify application feedback requirements of each user terminal; analyze the application feedback requirements through the demand reserve table to determine new user requirements; Step SA3: Analyze the newly added user needs and determine the corresponding demand value and implementation cost; Step SA4: Substituting the demand value and implementation cost of the newly added user demand into the screening formula of the second stage to calculate the screening value of the newly added user demand; Step SA5: Screen the new user requirements according to the screening value to determine the data processing requirements; Step SA6: Loop through Step SA2 to Step SA5.

3. The outdoor low-voltage line automatic monitoring data processing visualization system according to claim 2 is characterized in that: The screening formula is: ; Where: SA is the screening value; XQ is the requirement value; CB is the implementation cost; b1 and b2 are both proportionality coefficients in the first stage, with the value range of 0 < b1 < 1, 0 < b2 < 1; b3 and b4 are both proportionality coefficients in the second stage, with the value range of 0 < b3 < 1, 0 < b4 < 1.

4. The outdoor low-voltage line automatic monitoring data processing visualization system according to claim 2 is characterized in that: The method for analyzing application feedback requirements through a requirements reserve table includes: Establish a reserve calibration model to perform real-time identification on the requirements reserve table to obtain a calibration set, where the calibration set consists of data processing requirements in the requirements reserve table; Analyze the application feedback requirements and the calibration set through the reserve calibration model to obtain the reserve calibration value of the application feedback requirements; Mark the application feedback requirements with a reserve calibration value of 1 as new user requirements.

5. The outdoor low-voltage line automatic monitoring data processing visualization system according to claim 4 is characterized in that: The expression of the reserve calibration model is: ; Where: (s, U) is the input data, s is the corresponding application feedback requirement, and U is the calibration set; s → U indicates that the corresponding application feedback requirement does not belong to the calibration set; the output data is the reserve calibration value CP(s, U), and the reserve calibration value is 1 or 0.

6. The outdoor low-voltage line automatic monitoring data processing visualization system according to claim 1 is characterized in that: The method for custom processing includes: Step SC1: Obtain the monitoring requirements of the user; connect to the cloud storage repository, obtain the requirements reserve table, screen the requirements reserve table according to the monitoring requirements to obtain data processing requirements that meet the monitoring requirements, mark the data processing requirements as recommended requirements, and display the recommended requirements to the user; When the user selects a recommended requirement as a custom requirement, identify the data processing method of the recommended requirement and end the analysis; When the user does not select a recommended requirement as a custom requirement, go to Step SC2; Step SC2: Analyze the monitoring requirements through the requirements simulation model to obtain a data processing simulation process, and display the data processing simulation process to the user; the user adjusts the monitoring requirements according to the data processing simulation process to obtain new monitoring requirements; Step SC3: Loop through Step SC2 until the data processing simulation process meets the user's requirements, and determine the custom requirements and data processing methods according to the data processing simulation process.

7. The outdoor low-voltage line automatic monitoring data processing visualization system according to claim 6 is characterized in that: The method for determining user processing requirements includes: Identify fixed processing requirements; real-time identify the user's custom requirements and the corresponding data processing methods; Mark both the custom requirements and the fixed requirements as user processing requirements.

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