A power supply management system based on remote monitoring

Abstract

This invention discloses a power supply management system based on remote monitoring, belonging to the field of power monitoring and management technology. It includes an information acquisition module for acquiring information about power equipment. This invention utilizes a set health assessment method to evaluate the health status of target equipment based on its operational information. By analyzing and identifying the operating parameters of the target equipment, it determines hidden faults and obtains the health status. Before the health status assessment process, the power equipment is categorized, with information for different target categories stored in different databases to improve information processing efficiency. A set strategy output method adjusts the discharge strategy of the target equipment based on its health status to obtain the target strategy. By proactively addressing potential risks, it optimizes the operation of the target equipment, manages it, extends its service life, and reduces the risk of sudden power outages.

Description

Technical Field

[0001] This invention relates to the field of power monitoring and management technology, specifically to a power supply management system based on remote monitoring. Background Technology

[0002] Electrical power supply refers to a dedicated power supply used in railway or rail transit systems to ensure the normal operation of railway maintenance equipment such as electrical communication, signaling, and control systems. It typically includes DC power supply, backup power supply, and power distribution equipment. In order to ensure that critical communication and signaling equipment can work stably under various operating and emergency conditions, electrical power supply management is often required.

[0003] A remote monitoring system for railway signal power supply based on wireless communication, disclosed in patent publication number CN116707142A, comprises the following components: a remote control center, a wireless communication base station, a power supply monitoring terminal, a power supply monitoring node, and a mobile sharing terminal. The remote control center receives monitoring data from various distributed monitoring terminals. The wireless communication base station receives and transmits communication connections between the terminals and the center. The power supply monitoring terminal monitors the health status of the signal power supply in real time and controls and adjusts the signal power supply based on the monitoring results. The power supply monitoring node monitors the signal equipment and transmission lines supplied by the signal power supply in real time. The mobile sharing terminal provides communication services to maintenance personnel. This invention significantly improves the monitoring range and capability of the signal power supply through an intelligent monitoring system, thereby enhancing the accuracy of remote monitoring of the signal power supply.

[0004] Some power equipment in substations may experience "hidden faults" (such as intermittent voltage fluctuations and early-stage capacity decay of batteries). These faults are not easily detected in time, leading to the accumulation of potential risks despite the system appearing normal. Existing remote monitoring methods have the drawback of being unable to address the accumulation of potential risks. Existing monitoring systems struggle to analyze and identify changes in the health status of power equipment caused by hidden faults such as "lifespan decay" and "performance edge degradation" during operation. They cannot effectively address related equipment in advance based on the accumulation of potential risks, thus hindering management efficiency. The lack of awareness of the potential risk accumulation process results in hidden dangers not being detected and addressed in a timely manner. Equipment maintenance remains in a post-fault repair mode, missing opportunities for early intervention, extending equipment lifespan, and reducing the risk of sudden power outages. Therefore, this invention is proposed. Summary of the Invention

[0005] The purpose of this invention is to provide a power supply management system based on remote monitoring to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a power supply management system based on remote monitoring, comprising:

[0007] Information acquisition module: Acquires information about the power supply equipment to obtain equipment information, and acquires real-time and historical operating parameters of the power supply equipment to obtain real-time and historical parameters;

[0008] Information processing module: Based on device information, classify devices according to usage scenarios and types to obtain classification information. The classification information includes several target categories, and each target category includes device information corresponding to the target category.

[0009] Data processing module: Verifies the accuracy of real-time parameters under different target categories using verification methods to obtain verification parameters and discrepancies;

[0010] Data classification module: Establish an information database of the same number as the number of target categories. The information database is used to store validation parameters and past parameters.

[0011] Status assessment module: Identify the devices whose health status needs to be assessed to obtain target devices; select the corresponding information database based on the target devices to obtain target database; assess the health status of the target devices using health assessment methods based on the target devices and target database to obtain assessment results; and establish a directory table to store the target devices and their assessment results.

[0012] Strategy formulation module: Based on the catalog table, the discharge strategy of the target device is updated through the strategy output method to obtain the target strategy;

[0013] Policy output module: Feeds back the target policy to the target device, and the target device operates according to the target policy;

[0014] Feedback Update Module: Based on the information database, the module iteratively processes the information in the information database and the directory table using an update method to obtain the updated information database and directory table.

[0015] The health assessment method includes: pre-setting target factors, establishing a health assessment scope based on the target factors and target categories to obtain health level assessment standards, obtaining the lifespan level of the target equipment through a joint analysis method based on the health level assessment standards, establishing the correlation between the lifespan level and the target equipment, and the lifespan level being the assessment result;

[0016] The process of establishing a health assessment scope based on target factors and target categories to obtain health level assessment standards is as follows: Determine the target factors, obtain the normal working range information of the target factors to obtain normal range information, the normal range information is the first lifespan level, preset the added value, add the added value to the normal range information to obtain the second lifespan level, add the added value to the range information of the second lifespan level to obtain the third lifespan level, integrate the first lifespan level, the second lifespan level and the third lifespan level to obtain the target lifespan level, establish the correlation between the target factors and the target lifespan level, and integrate all target factors, target lifespan levels and correlations to obtain the health level assessment standards;

[0017] The joint analysis method includes: splitting the health level assessment criteria to obtain several target factors, target lifespan levels, and correlations; extracting parameters corresponding to the target factors from the real-time parameters and past parameters of the target equipment to obtain real-time selection parameters and past selection parameters; when there is only one parameter in the real-time selection parameters and past selection parameters, determining the inclusion relationship between the real-time selection parameters and the target lifespan level to obtain the real-time lifespan level; and determining the inclusion relationship between the past selection parameters and the target lifespan level to obtain the past lifespan level.

[0018] Furthermore, when there are multiple parameters in the real-time and previously selected parameters, the real-time lifespan level and the previously selected lifespan level are obtained through a deep segmentation method based on the real-time and previously selected parameters and the target lifespan level. The generation time difference between the real-time and previously selected parameters is obtained to obtain the time difference value. The lifespan change trend is obtained based on the previously selected lifespan level, the real-time lifespan level and the time difference value. The lifespan level of the target device is obtained based on the real-time lifespan level. The lifespan change trend and lifespan level are integrated to obtain the evaluation result.

[0019] Furthermore, the deep segmentation method includes: assigning weights to target factors based on the influence relationship between target factors and the lifespan of target devices to obtain target weights; determining the inclusion relationship between real-time selected parameters and target lifespan levels to obtain several first sub-lifespan levels; obtaining real-time lifespan levels based on target weights and several first sub-lifespan levels; determining the inclusion relationship between past selected parameters and target lifespan levels to obtain several second sub-lifespan levels; and obtaining past lifespan levels based on target weights and several second sub-lifespan levels.

[0020] Furthermore, the strategy output method includes: obtaining the work tasks of the target device to obtain task requirements; determining the number of target devices; when there are multiple target devices, extracting the evaluation results of the target devices from the catalog table to obtain the target lifespan level; sorting the target devices from best to worst based on their target lifespan levels to obtain a sorting result; presetting a task threshold for the worst target device among the target lifespan levels; when the work tasks of the same target device exceed the task threshold, removing the task threshold from the task requirements of the worst-level target device and adding it to the best target device to obtain the target strategy for the target device; when there is only one target device and the target lifespan level feedback for the target device is the worst level, then extracting the task requirements, the target device, and its target lifespan level to generate feedback information.

[0021] Furthermore, the verification method includes: determining the usage scenario of the real-time parameters to obtain environmental parameters; judging whether there are strong fluctuations in the environmental parameters to obtain a judgment result; presetting a verification threshold based on the judgment result and the device operation status; obtaining the change value of the real-time parameters; judging the magnitude of the verification threshold and the change value to obtain a verification result; when the change value is greater than the verification threshold, the real-time parameter is a difference item; when the change value is less than the verification threshold, the real-time parameter is a verification parameter.

[0022] Furthermore, the update method includes: setting a preset update time point, re-evaluating the health status of the target device based on the update time point to obtain a re-evaluation result, overwriting the evaluation results in the catalog table with the re-evaluation result to obtain an updated catalog table, and after the re-evaluation result of the target device is generated, setting a preset time node, and removing past parameters and real-time parameters located before the time node from the information database to obtain an updated information database.

[0023] Compared with the prior art, the beneficial effects of the present invention are:

[0024] This remote monitoring-based power supply management system can assess the health status of target equipment based on its operational information using a set health assessment method. It analyzes and identifies hidden faults by analyzing and recognizing the operating parameters of the target equipment to determine its health status. Before the health status assessment, the power equipment is categorized, with information for different target categories stored in separate databases to improve information processing efficiency. A set strategy output method adjusts the discharge strategy of the target equipment based on its health status to obtain the target strategy. This allows for proactive handling of relevant equipment based on potential risks, optimizing and adjusting the operation of the target equipment. Ultimately, managing the target equipment extends its service life and reduces the risk of sudden power outages.

[0025] Meanwhile, real-time parameters are verified using a set verification method to improve the accuracy of the acquired parameters. This also helps determine whether the corresponding sensors are operating normally, facilitates the timely detection of faulty sensors, and improves overall operational efficiency. The number of databases is consistent with the target categories, and each database stores only the verification parameters and past parameters for one target category to improve the efficiency of subsequent data processing and health status assessment. Through a set joint analysis method, target devices with single or multiple target factors are processed separately to more accurately assess the health status of the target devices.

[0026] Meanwhile, by setting a deep segmentation method, when classifying the health status of target devices with multiple target factors, a weighted approach is adopted. Different weights are assigned to target factors according to their different degrees of influence on the health status of target devices, thereby improving the accuracy of the assessment. Through the set update method, the information in the information database and catalog can be iteratively updated in real time according to the update time point, thereby improving the real-time nature of the information in the information database and catalog, reducing the processing load of subsequent information search and information processing, improving the system's response speed, and helping to improve the operational efficiency of the health assessment method. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of the upper part of the structure of the present invention;

[0028] Figure 2 This is a schematic diagram of the lower half of the structure of the present invention;

[0029] Figure 3 This is a schematic diagram of the target library structure obtained in this invention;

[0030] Figure 4 This is a schematic diagram of the health assessment level structure of the present invention. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] Electrical power supply management is the process or system for monitoring, regulating, maintaining, and optimizing electrical power supplies. It includes monitoring power status, controlling power supply parameters, providing fault warnings, and scheduling maintenance, aiming to ensure high reliability and stability of the power supply and reduce operational risks caused by faults. Railway signaling, communication, locomotives, and onboard equipment require stable power support. The electrical power supply management system achieves real-time monitoring and scheduling of substations, overhead contact line power supply, battery banks, etc., through remote monitoring. The remote monitoring electrical power supply system enables real-time acquisition and fault warning of parameters such as power quality, battery voltage, and temperature within substations.

[0033] like Figures 1-4 As shown, the present invention provides a technical solution: a power supply management system based on remote monitoring, comprising:

[0034] Information acquisition module: Acquires information about the power supply equipment to obtain equipment information, and acquires real-time and historical operating parameters of the power supply equipment to obtain real-time and historical parameters;

[0035] It is important to note that the equipment information includes the equipment name, the equipment manual, and the equipment application scenario. The real-time and past operating parameters of the power supply equipment are obtained through the corresponding sensors. Specific parameters may include temperature, vibration, insulation resistance, or leakage current, etc.

[0036] Information processing module: Based on device information, classify devices according to usage scenarios and types to obtain classification information. The classification information includes several target categories, and each target category includes device information corresponding to the target category.

[0037] It is important to note that the devices are classified according to their specific working scenarios and categories as described in the device information. The target category is a specific name category that contains several device information items. The category is defined by combining the specific usage scenario and the device category.

[0038] Example 1:

[0039] In the electrical power supply equipment used in the system application, the power supply equipment information is obtained to obtain equipment information. In the equipment information work log, the data of monitoring equipment operation is obtained to obtain real-time parameters and past parameters. The equipment is classified according to the usage scenario and type, and several information databases corresponding to the target categories are established to store the real-time parameters and past parameters generated under the target category. Nodes for sending and receiving information are established to obtain the user's address information, including but not limited to email and phone number. The generated evaluation results and feedback information are fed back to the user through the nodes.

[0040] Data processing module: Verifies the accuracy of real-time parameters under different target categories using verification methods to obtain verification parameters and discrepancies;

[0041] It is important to note that by setting up a verification method to verify the real-time parameters, the accuracy of the acquired real-time parameters can be improved. This also helps to determine whether the corresponding sensors are operating normally, facilitates the timely detection of faulty sensors, and improves overall operating efficiency.

[0042] Data classification module: Establish an information database of the same number as the number of target categories. The information database is used to store validation parameters and past parameters.

[0043] It is important to note that the number of databases should match the target categories. Each database should store only the verification parameters and past parameters for one target category to improve the efficiency of subsequent data processing and health status assessment.

[0044] Status assessment module: Identify the devices whose health status needs to be assessed to obtain target devices; select the corresponding information database based on the target devices to obtain target database; assess the health status of the target devices using health assessment methods based on the target devices and target database to obtain assessment results; and establish a directory table to store the target devices and their assessment results.

[0045] It is important to note that the process of identifying the equipment requiring health status assessment to obtain the target equipment involves determining the equipment that needs assessment based on usage requirements. Specifically, this can be done through random or targeted selection. The target equipment is the power supply equipment within the electrical power supply system. The process of selecting the corresponding information database based on the target equipment to obtain the target database is as follows: Figure 3 As shown, the information database corresponds to the target category. That is, the target database is obtained by selecting the information database corresponding to the target category according to the target device. By setting the health assessment method, the health status of the target device can be assessed according to the operating information of the target device, so that the subsequent strategy output method can output the corresponding discharge strategy, so as to adjust the target device and extend the service life of the target device.

[0046] Strategy formulation module: Based on the catalog table, the discharge strategy of the target device is updated through the strategy output method to obtain the target strategy;

[0047] It should be noted that the target strategy is obtained by adjusting the discharge strategy of the target device according to the health status of the target device through the set strategy output method, so as to optimize the operation of the target device, manage the target device, and extend its service life.

[0048] Policy output module: Feeds back the target policy to the target device, and the target device operates according to the target policy;

[0049] It is important to note that the process of feeding the target strategy back to the target device involves the target strategy overriding the original discharge strategy, and the target device operating according to the target strategy.

[0050] Feedback Update Module: Based on the information database, the module periodically iterates through the information database and the directory table using an update method to obtain the updated information database and directory table.

[0051] It is important to note that by setting the update method, the information in the database and catalog can be updated and iterated at fixed intervals, thereby streamlining the database and target table and improving the efficiency and accuracy of subsequent health status assessments and strategy outputs.

[0052] like Figure 1 As shown, the health assessment method includes: pre-setting target factors, establishing a health assessment scope based on the target factors and target categories to obtain health level assessment standards, obtaining the lifespan level of the target equipment through joint analysis based on the health level assessment standards, establishing the correlation between the lifespan level and the target equipment, and the lifespan level is the assessment result.

[0053] It is important to note that the target factors are determined based on actual usage requirements. Specific target factors are operational data that can reflect the health status of the target equipment. Specific target factors include temperature, vibration, etc. More specifically, when the target equipment is a transformer, oil temperature can be selected as the target factor. Based on the target factors and the target category, a health level assessment standard is formulated. The life level of the target equipment is obtained through the set joint analysis method. The assessment results include the specific life level, the target equipment, and the correlation.

[0054] like Figure 4 As shown, the process of establishing a health assessment range based on target factors and target categories to obtain health level assessment standards is as follows: determine the target factors, obtain the normal working range information of the target factors to obtain normal range information, the normal range information is the first lifespan level, preset the added value, add the added value to the normal range information to obtain the second lifespan level, add the added value to the range information of the second lifespan level to obtain the third lifespan level, integrate the first lifespan level, the second lifespan level and the third lifespan level to obtain the target lifespan level, establish the correlation between the target factors and the target lifespan level, and integrate all target factors, target lifespan levels and correlations to obtain the health level assessment standards.

[0055] It is important to note that identifying the target factor means identifying a specific factor. For example, if oil temperature is identified as the target factor, the normal operating range information of the target factor is obtained. This means obtaining the range information of the target factor in the target equipment under normal operating conditions. The added value is determined based on actual use, and the specific unit changes with the target factor. The specific value is determined based on actual usage. There are two boundary values ​​in the normal range information. The added value is added to one of the boundary values ​​in the normal range information, and the second lifespan level is obtained by adding the value to that boundary value. And so on. Figure 4 As shown, a single lifespan level in a specific health level assessment standard may include multiple levels, such as the first lifespan level, the second lifespan level, the third lifespan level, the fourth lifespan level, and so on up to the Nth lifespan level. The specific number is determined based on actual usage. The more precise the lifespan level classification, the more accurate the subsequent processing will be.

[0056] Example 2:

[0057] More specifically, when the target equipment is a transformer, oil temperature (or winding temperature) can be selected as the target factor. Distribution transformers are commonly used power supply equipment in power systems. Common faults are often related to winding overheating, insulation aging, and abnormal oil temperature. Monitoring oil temperature or winding temperature is very effective in judging the health of the equipment. Key single factor recommendation: oil temperature (or winding temperature). Oil temperature is an important indicator reflecting the internal operating status of the transformer. Sustained excessively high oil temperature will accelerate the aging of insulation materials and shorten its lifespan. Equipment manufacturers and industry standards usually give a safe operating range for oil temperature. Specific threshold design examples (refer to IEC standards and engineering experience). Oil temperature (°C) health status description: When oil temperature < 65°C, it represents normal and stable equipment operation and normal lifespan. When oil temperature is between 65°C and 75°C, it represents the beginning of temperature rise and requires attention. When oil temperature is between 75°C and 85°C, it represents sub-health and overheating, requiring load reduction or inspection. When oil temperature is between 85°C and 95°C, it represents a high temperature alarm, indicating potential hidden dangers. When oil temperature > 95°C... At a certain temperature (℃), it indicates danger and the machine should be shut down immediately. Example of health status judgment rules: Oil temperature < 65℃, health status = normal; 65℃ ≤ Oil temperature < 75℃, health status = slightly elevated; 75℃ ≤ Oil temperature < 85℃, health status = sub-healthy; 85℃ ≤ Oil temperature < 95℃, health status = warning; Oil temperature > 95℃, health status = danger. Based on the above ranges, corresponding first, second, third, fourth, and fifth lifespan levels can be generated. The specific acquisition method is through real-time monitoring, using an oil temperature sensor to collect temperature data, updated every second or minute. The above thresholds can be adjusted according to the manufacturer's manual or historical operating data. Maintenance decisions can also be added: when the temperature reaches "sub-healthy" or higher, arrange for inspection or load reduction; exceeding "warning" will activate alarms and emergency strategies.

[0058] The joint analysis method includes: breaking down the health level assessment criteria to obtain several target factors, target lifespan levels, and correlations; extracting parameters corresponding to the target factors from the real-time and historical parameters of the target equipment to obtain real-time and historical selection parameters; when there is only one parameter in the real-time and historical selection parameters, determining the inclusion relationship between the real-time selection parameter and the target lifespan level to obtain the real-time lifespan level; determining the inclusion relationship between the historical selection parameter and the target lifespan level to obtain the historical lifespan level; when there are multiple parameters in the real-time and historical selection parameters, obtaining the real-time lifespan level and historical lifespan level through a deep segmentation method based on the real-time and historical selection parameters and the target lifespan level; obtaining the time difference between the generation time of the real-time and historical parameters to obtain the time difference value; obtaining the lifespan change trend based on the historical lifespan level, the real-time lifespan level, and the time difference value; obtaining the lifespan level of the target equipment based on the real-time lifespan level; and integrating the lifespan change trend and lifespan level to obtain the assessment result.

[0059] It is important to note that the joint analysis method separates the target devices with single and multiple target factors for more accurate assessment of their health status. The process of determining the real-time lifespan level involves identifying the inclusion relationship between the real-time selected parameters and the target lifespan level. Specifically, it involves determining which lifespan level the real-time selected parameters correspond to within the target lifespan level, or identifying the inclusion relationship between the real-time selected parameters and multiple levels within the target lifespan level. Finding the level that includes the real-time selected parameters yields the real-time lifespan level. The lifespan change trend indicator is used to assess the aging degree of the target device, reflecting changes in its health status over time intervals. Specifically, it can be assessed by selecting real-time selected parameters generated by target devices operating under normal conditions. Using these real-time selected parameters makes the lifespan change trend indicator more accurate, indirectly reflecting whether the target device requires maintenance, thus achieving the effect of monitoring and managing the target device and extending its service life. The time difference value is a specific numerical value, representing the difference between the real-time parameter generation time and the previous parameter generation time.

[0060] The deep segmentation method includes: assigning weights to target factors based on their impact on the lifespan of target equipment to obtain target weights; determining the inclusion relationship between real-time selected parameters and target lifespan levels to obtain several first sub-lifespan levels; obtaining real-time lifespan levels based on target weights and several first sub-lifespan levels; determining the inclusion relationship between past selected parameters and target lifespan levels to obtain several second sub-lifespan levels; and obtaining past lifespan levels based on target weights and several second sub-lifespan levels.

[0061] It is important to note that when classifying the health status of a target device using the depth-based segmentation method, a weighted approach is adopted. Different weights are assigned to the target factors based on their varying degrees of influence on the health status of the target device. The specific weights are determined based on actual usage. Specifically, the factors reflecting the degree of influence on the health status of the target device can be ranked, and corresponding weights are assigned based on the ranking. The specific weight values ​​are determined by the degree of influence. By combining the lifespan levels of multiple target factors, the specific real-time lifespan level and past lifespan level are obtained.

[0062] Example 3:

[0063] When there are two target factors, namely Factor 1 and Factor 2, Factor 1 represents the first lifespan level (assuming a level value of 1), and Factor 2 represents the second lifespan level (assuming a level value of 2). They are assigned weights based on their impact on the health of the target equipment, with weights of 0.7 and 0.3 respectively. The level value represents the quantitative index of the lifespan level (the smaller the number, the better the lifespan level; typically 1 is excellent, and 2 is second best). The final lifespan level value is calculated using the weighted average method: Lfinal = 0.7 × 1 + 0.3 × 2 = 0.7 + 0.6 = 1.3. Specifically, the lifespan level is a discrete classification, with only integer levels 1, 2, 3, etc. The result is obtained by directly rounding to the nearest integer to obtain the first lifespan level, or by defining a range, for example: a level range corresponds to a lifespan level; values ​​in [1, 1.5) represent level 1, values ​​in [1.5, 2.5) represent level 2, and values ​​in [2.5, 1.5, 2.5) represent level 2, and values ​​in [2.5, 1.5, 2.5) represent level 3, 1.5, 2 ... 3.5) is level 3. In this case, 1.3 falls in [1,1.5), which still belongs to the first lifespan level.

[0064] like Figure 2 As shown, the strategy output method includes: obtaining the work tasks of the target device to obtain the task requirements; determining the number of target devices; when there are multiple target devices, extracting the evaluation results of the target devices from the catalog table to obtain the target lifespan level; sorting the target devices from best to worst based on their target lifespan levels to obtain the sorting results; pre-setting the task threshold for the worst target device among the target lifespan levels; when the work tasks of the same target device exceed the task threshold, removing the task threshold from the task requirements of the worst-level target device and adding it to the best target device to obtain the target strategy for the target device; when there is only one target device and the target lifespan level feedback for the target device is the worst level, then extracting the task requirements, the target device and its target lifespan level to generate feedback information.

[0065] It is important to note that the process of obtaining the task requirements for the target equipment can be achieved by acquiring the target equipment's work needs. The target strategy is then obtained by adjusting the discharge strategy for the target equipment based on the number of target devices using a set strategy output method. Based on this strategy, the workload of target devices with low health status can be reduced, thereby extending their lifespan and stability, reducing the probability of sudden power outages due to accumulated potential risks, and improving the user experience. Task thresholds are set according to the target equipment's corresponding lifespan level, and these thresholds represent specific discharge tasks. By generating feedback information, individual target devices with poor health status can be promptly notified to the user, reminding them to address the issue in a timely manner, thus improving the stability of the power supply.

[0066] Example 4:

[0067] The system uses a ranking system to determine the "good" or "bad" lifespan of equipment. For equipment with lower lifespan levels (i.e., poor health and high risk), the discharge strategy is adjusted to mitigate wear and tear. For "healthy" equipment, the discharge load can be appropriately increased to distribute the overall workload and extend the lifespan of the equipment. The goal is to intelligently allocate load and discharge time to prevent overloading and premature retirement of low-lifespan equipment, ensuring continuous power supply. Specific steps include: Determining the lifespan level: Based on the ranking, determine the current lifespan level of each device (e.g., 1 is best, 5 is worst). Grouping the equipment into "high-lifespan group" (higher levels) and "low-lifespan group" (lower levels). Adjusting discharge parameters: For low-lifespan group equipment: reduce discharge depth, shorten discharge time, and reduce discharge power. For high-lifespan equipment: Appropriately increase discharge depth and time; dynamically adjust load distribution ratio based on remaining lifespan and health level; monitor and provide feedback to monitor equipment status in real time; dynamically adjust discharge schemes; and provide maintenance warnings to plan maintenance or replacement in advance for equipment with extremely low lifespan to avoid sudden power outages. Example of discharge strategy adjustment: Lifespan level, discharge depth (DoD), discharge power, discharge frequency description: Level 1-2 (healthy), fully utilize resources and share the load; Level 3-4 (sub-healthy), reduce load, protect equipment, and prevent further deterioration; Level 5 (dangerous), shallow discharge with low power to mitigate risk. A mapping table between lifespan level and discharge parameters can be established for automatic program invocation. The discharge strategy can be adjusted based on environmental conditions (temperature, humidity, etc.) to improve applicability. Machine learning is used to optimize load distribution, dynamically optimizing strategies based on equipment status and historical discharge impacts. Graded thresholds and event triggers are set, such as automatically switching discharge modes at lifespan level thresholds, to fully extend the effective service life of low-lifespan equipment, reduce premature power outages caused by accelerated aging due to over-discharge, share the load, improve overall system reliability and availability, and reduce maintenance and replacement costs.

[0068] like Figure 1 As shown, the verification method includes: determining the usage scenario of the real-time parameters to obtain environmental parameters, judging whether there are strong fluctuations in the environmental parameters to obtain a judgment result, preset a verification threshold based on the judgment result and the device operation status, obtaining the change value of the real-time parameters, judging the magnitude of the verification threshold and the change value to obtain the verification result, when the change value is greater than the verification threshold, the real-time parameter is a difference item, and when the change value is less than the verification threshold, the real-time parameter is a verification parameter.

[0069] It is important to note that the process of determining the application scenario of real-time parameters to obtain environmental parameters involves acquiring the environmental parameters of the sensor that generates the real-time parameters. The process of determining whether there are strong fluctuations in these environmental parameters involves judging whether there are large fluctuations in the environmental parameters. Based on the judgment result and the equipment's operating status, a verification threshold is preset. Specifically, the process involves determining whether there are deviations in the sensor readings based on the environmental parameters. If deviations exist, they are accommodated and combined with the normal value of the parameter during equipment operation to obtain the verification threshold. The verification threshold is a range value. The real-time parameters are then used to determine whether they conform to the actual situation. When the real-time parameters do not conform to the verification threshold, it means that the acquisition of real-time parameters is clearly inconsistent with the actual situation. By setting the verification method, the accuracy of data acquisition can be improved, thereby improving the accuracy of health assessment methods.

[0070] like Figure 2 As shown, the update method includes: setting a preset update time point, re-evaluating the health status of the target device based on the update time point to obtain a re-evaluation result, overwriting the evaluation results in the catalog table based on the re-evaluation result to obtain an updated catalog table, and after the re-evaluation result of the target device is generated, setting a preset time node, removing the previous parameters and real-time parameters located before the time node in the information database to obtain an updated information database.

[0071] It is important to note that by setting the update method, the information in the database and catalog can be iteratively updated in real time according to the update time point. This improves the real-time performance of the information in the database and catalog, reduces the processing load of subsequent information searches and processing, improves the system's response speed, and helps improve the operational efficiency of the health assessment method. The update time point is specific time information, which is determined according to the actual usage situation. Specifically, it can be set to update weekly or daily, etc.

[0072] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended embodiments and their equivalents.

Claims

1. A power supply management system based on remote monitoring, comprising: Information acquisition module: Acquires information about the power supply equipment to obtain equipment information, and acquires real-time and historical operating parameters of the power supply equipment to obtain real-time and historical parameters; Information processing module: Based on device information, classify devices according to usage scenarios and types to obtain classification information. The classification information includes several target categories, and each target category includes device information corresponding to the target category. Its features include: Data processing module: Verifies the accuracy of real-time parameters under different target categories using verification methods to obtain verification parameters and discrepancies; Data classification module: Establish an information database of the same number as the number of target categories. The information database is used to store validation parameters and past parameters. Status assessment module: Identify the devices whose health status needs to be assessed to obtain target devices; select the corresponding information database based on the target devices to obtain target database; assess the health status of the target devices using health assessment methods based on the target devices and target database to obtain assessment results; and establish a directory table to store the target devices and their assessment results. Strategy formulation module: Based on the catalog table, the discharge strategy of the target device is updated through the strategy output method to obtain the target strategy; Policy output module: Feeds back the target policy to the target device, and the target device operates according to the target policy; Feedback Update Module: Based on the information database, the module iteratively processes the information in the information database and the directory table using an update method to obtain the updated information database and directory table. The health assessment method includes: pre-setting target factors, establishing a health assessment scope based on the target factors and target categories to obtain health level assessment standards, obtaining the lifespan level of the target equipment through a joint analysis method based on the health level assessment standards, establishing the correlation between the lifespan level and the target equipment, and the lifespan level being the assessment result; The process of establishing a health assessment scope based on target factors and target categories to obtain health level assessment standards is as follows: Determine the target factors, obtain the normal working range information of the target factors to obtain normal range information, the normal range information is the first lifespan level, preset the added value, add the added value to the normal range information to obtain the second lifespan level, add the added value to the range information of the second lifespan level to obtain the third lifespan level, integrate the first lifespan level, the second lifespan level and the third lifespan level to obtain the target lifespan level, establish the correlation between the target factors and the target lifespan level, and integrate all target factors, target lifespan levels and correlations to obtain the health level assessment standards; The joint analysis method includes: splitting the health level assessment criteria to obtain several target factors, target lifespan levels, and correlations; extracting parameters corresponding to the target factors from the real-time parameters and past parameters of the target equipment to obtain real-time selection parameters and past selection parameters; when there is only one parameter in the real-time selection parameters and past selection parameters, determining the inclusion relationship between the real-time selection parameters and the target lifespan level to obtain the real-time lifespan level; and determining the inclusion relationship between the past selection parameters and the target lifespan level to obtain the past lifespan level.

2. The power supply management system based on remote monitoring according to claim 1, characterized in that: When there are multiple parameters in the real-time and previously selected parameters, the real-time lifespan level and the previous lifespan level are obtained by deep segmentation based on the real-time and previously selected parameters and the target lifespan level. The time difference between the generation time of the real-time and previous parameters is obtained to obtain the time difference value. The lifespan change trend is obtained based on the previous lifespan level, the real-time lifespan level and the time difference value. The lifespan level of the target device is obtained based on the real-time lifespan level. The lifespan change trend and lifespan level are integrated to obtain the evaluation result.

3. The power supply management system based on remote monitoring according to claim 2, characterized in that: The deep segmentation method includes: assigning weights to target factors based on their impact on the lifespan of target devices to obtain target weights; determining the inclusion relationship between real-time selected parameters and target lifespan levels to obtain several first sub-lifespan levels; obtaining real-time lifespan levels based on target weights and several first sub-lifespan levels; determining the inclusion relationship between past selected parameters and target lifespan levels to obtain several second sub-lifespan levels; and obtaining past lifespan levels based on target weights and several second sub-lifespan levels.

4. The power supply management system based on remote monitoring according to claim 1, characterized in that: The strategy output method includes: obtaining the work tasks of the target devices to obtain task requirements; determining the number of target devices; when there are multiple target devices, extracting the evaluation results of the target devices from the catalog table to obtain the target lifespan level; sorting the target devices from best to worst based on their target lifespan levels to obtain a sorting result; presetting a task threshold for the worst target device among the target lifespan levels; when the work tasks of the same target device exceed the task threshold, removing the task threshold from the task requirements of the worst-level target device and adding it to the best target device to obtain the target strategy for the target device; when there is only one target device and the target lifespan level feedback for the target device is the worst level, then extracting the task requirements, the target device and its target lifespan level to generate feedback information.

5. A power supply management system based on remote monitoring according to claim 1, characterized in that: The verification method includes: determining the usage scenario of the real-time parameters to obtain environmental parameters; judging whether there are strong fluctuations in the environmental parameters to obtain a judgment result; presetting a verification threshold based on the judgment result and the equipment operation status; obtaining the change value of the real-time parameters; judging the magnitude of the verification threshold and the change value to obtain a verification result; when the change value is greater than the verification threshold, the real-time parameter is a difference item; when the change value is less than the verification threshold, the real-time parameter is a verification parameter.

6. The power supply management system based on remote monitoring according to claim 1, characterized in that: The update method includes: setting a preset update time point, re-evaluating the health status of the target device based on the update time point to obtain a re-evaluation result, overwriting the evaluation results in the catalog table with the re-evaluation result to obtain an updated catalog table, and after the re-evaluation result of the target device is generated, setting a preset time node, and removing the previous parameters and real-time parameters located before the time node in the information database to obtain an updated information database.

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