Special transformer state management method and system based on intelligent monitoring and remote diagnosis

Abstract

The invention discloses a special transformer state management method and system based on intelligent monitoring and remote diagnosis. The method comprises the steps that electrical parameters of a special transformer user are collected through monitoring equipment; the collected data parameters are analyzed in real time, and the operation state and the abnormal condition of the equipment are judged; monitoring data are transmitted through a communication network, and remote monitoring is achieved; and when an abnormality is detected, triggering an alarm mechanism, and providing fault diagnosis information. According to the invention, the safety and operation efficiency of the power system are improved. Key parameters such as voltage, current, power and frequency can be collected in real time, abnormal conditions such as overload and undervoltage can be rapidly detected through an intelligent algorithm, and an alarm is triggered in time. The system adopts AES encryption to guarantee data transmission security, supports 4G / 5G network to realize remote monitoring, and ensures that operation and maintenance personnel can quickly obtain fault diagnosis information and personalized processing suggestions. The fault response speed and the system stability are obviously improved, and the operation and maintenance cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of power system monitoring and fault diagnosis, and in particular to a special transformer state management method and system based on intelligent monitoring and remote diagnosis. Background Art

[0002] In modern power systems, high-voltage drop-out fuses are a commonly used protective device that cuts off the circuit by melting the fuse element to protect power lines and equipment from short-circuit faults. However, existing high-voltage drop-out fuses still have many technical limitations and are difficult to meet the needs of today's complex power grid systems, which are specifically manifested in the following aspects:

[0003] Current high-voltage drop-out fuses mainly respond to short-circuit faults by blowing the circuit. Although they can provide protection in the case of severe faults, they cannot provide effective protection in the case of other types of electrical faults (such as overload, undervoltage, etc.). This single fault response method limits the protection capabilities of drop-out fuses under a variety of operating conditions and cannot meet the complex operating requirements of modern power grids.

[0004] Existing high-voltage drop-out fuses usually do not have intelligent and automated functions, and cannot realize functions such as remote monitoring, real-time fault diagnosis, and early warning. With the expansion of the scale of the power grid and the increase in operational complexity, modern power systems have increasingly higher requirements for intelligent equipment. Intelligent functions not only help improve the operating efficiency of the system, but also can detect potential problems in a timely manner through remote monitoring and fault early warning, avoiding equipment damage or grid failure. However, most current drop-out fuses lack such functions, resulting in operation and maintenance personnel having to rely on on-site inspections and unable to understand the operating status of the equipment in real time, increasing operation and maintenance costs and the risks of power system operation.

[0005] Therefore, the existing high-voltage drop-out fuses have obvious deficiencies in functionality and intelligence, and cannot effectively meet the diverse needs of modern power grids. Therefore, there is an urgent need for a solution that integrates intelligent monitoring, remote diagnosis and automated management to improve the safety, reliability and operation and maintenance efficiency of the power system. Summary of the invention

[0006] In view of the above-mentioned problems, the present invention is proposed.

[0007] Therefore, the technical problem solved by the present invention is that the current high-voltage drop-out fuse mainly responds to short-circuit faults by fusing the circuit. Although it can play a protective role in response to severe faults, it cannot provide effective protection in the face of other types of electrical faults (such as overload, undervoltage, etc.). This single fault response mode limits the protection capability of the drop-out fuse under various operating conditions and cannot meet the complex operating requirements of modern power grids.

[0008] Existing high-voltage drop-out fuses usually do not have intelligent and automated functions, and cannot realize functions such as remote monitoring, real-time fault diagnosis, and early warning. With the expansion of the scale of the power grid and the increase in operational complexity, modern power systems have increasingly higher requirements for intelligent equipment. Intelligent functions not only help improve the operating efficiency of the system, but also can detect potential problems in a timely manner through remote monitoring and fault early warning, avoiding equipment damage or grid failure. However, most current drop-out fuses lack such functions, resulting in operation and maintenance personnel having to rely on on-site inspections and unable to understand the operating status of the equipment in real time, increasing operation and maintenance costs and the risks of power system operation.

[0009] In order to solve the above technical problems, the present invention provides the following technical solutions: a special transformer status management method based on intelligent monitoring and remote diagnosis, comprising: collecting electrical parameters of special transformer users through monitoring equipment;

[0010] Analyze the collected data parameters in real time to determine the operating status and abnormal conditions of the equipment;

[0011] Transmit monitoring data through communication network to achieve remote monitoring;

[0012] When an anomaly is detected, an alarm mechanism is triggered and fault diagnosis information is provided.

[0013] As a preferred solution of the special transformer status management method based on intelligent monitoring and remote diagnosis described in the present invention, the monitoring equipment includes, by integrating a low-power current transformer, a voltage transformer and a power supply unit into a high-voltage drop-out fuse, an integrated casting design, and real-time collection of the voltage and current of each phase.

[0014] As a preferred solution of the special transformer state management method based on intelligent monitoring and remote diagnosis described in the present invention, wherein: 3. the acquisition of electrical parameters of the special transformer user includes real-time acquisition of each phase voltage value through a voltage transformer and recording the fluctuation of the line voltage;

[0015] The current value of each phase is collected in real time through low-power current transformers to analyze the line current load;

[0016] Based on the collected voltage and current values, calculate the active power and reactive power of each phase and the total, and provide an analysis basis for power consumption and power factor;

[0017] Calculate apparent power based on voltage and current values, and monitor the operating efficiency of the power supply system by combining active power and reactive power data;

[0018] The power factor is calculated by the ratio of active power to apparent power and is used to evaluate the power quality of the power supply system;

[0019] The monitoring equipment collects grid frequency parameters in real time to determine the stability of the power system and monitor frequency deviations to prevent power supply failures.

[0020] As a preferred solution of the special transformer state management method based on intelligent monitoring and remote diagnosis described in the present invention, wherein: the judging the operation state and abnormal situation of the equipment includes analyzing the collected voltage value through an intelligent algorithm, if the voltage value is the normal line working voltage and the circuit breaker is in an online state, it is judged that the equipment is working normally; if the voltage value is zero and the circuit breaker is still in an online state, it is judged that the circuit breaker is in a drop state;

[0021] Collect and monitor the opening or closing position information of the drop-out fuse in real time, determine whether the circuit breaker is in the open or closed state, and record the opening and closing actions of the circuit breaker;

[0022] By analyzing the current data, if the current exceeds the rated load of the equipment, it is judged that the equipment is in an overload state, the protection mechanism is triggered and the operation and maintenance personnel are notified;

[0023] By monitoring the voltage value in real time, when the voltage is lower than the set normal range, it is judged as undervoltage state and the device enters abnormal monitoring state;

[0024] When the voltage value exceeds the set upper or lower limit, it is judged as voltage over-limit state, and the system immediately issues an alarm and initiates protection measures;

[0025] According to the set collection cycle, the real-time operation data of voltage, current and power are stored regularly to generate load curves for historical analysis and evaluation of equipment operation status;

[0026] When overload, undervoltage, or voltage exceeding the limit is detected, the system actively triggers the alarm mechanism and sends alarm information to the operation and maintenance personnel through the communication network, indicating the specific fault details and providing targeted processing suggestions.

[0027] As a preferred solution of the special transformer state management method based on intelligent monitoring and remote diagnosis described in the present invention, wherein: the transmission of monitoring data through the communication network includes uploading the collected voltage, current, active power, reactive power, apparent power, power factor and grid frequency data to the remote server in real time;

[0028] Supports short-distance communication via local micro-power wireless or Bluetooth to transmit data to a nearby monitoring center, and combines with long-range 4G / 5G network communication to achieve multi-level transmission of monitoring data;

[0029] All transmitted data is processed through the AES encryption algorithm to ensure that it is not attacked or tampered with by external parties during the data upload process;

[0030] Each time data is transmitted, the remote server sends a confirmation response to the monitoring device to ensure that all monitoring data is successfully transmitted and fully stored on the server side;

[0031] Based on actual needs, monitoring data is divided into two modes: real-time transmission and periodic synchronization. Real-time transmission is used for alarm information and abnormal situations, while periodic synchronization is used to store historical operation data and load curves.

[0032] As a preferred solution of the special transformer state management method based on intelligent monitoring and remote diagnosis described in the present invention, wherein: the triggering alarm mechanism includes that when an abnormal state is detected, the system immediately activates the alarm mechanism, analyzes the abnormal parameters, and generates an abnormal data packet, the data packet includes the abnormal type, and the specific values ​​of the relevant electrical parameters;

[0033] The alarm information contains the unique identification of the device, the specific time when the abnormality occurred, the detailed values ​​of the electrical parameters, the geographical location information of the device, and the current working status of the device;

[0034] The system classifies alarm information according to the severity of the fault. The priority of current overload alarm information is higher than that of voltage fluctuation alarm. The priority of frequency abnormality alarm is determined according to the fluctuation amplitude. The alarm information will indicate the priority to help operation and maintenance personnel prioritize serious faults.

[0035] As a preferred solution of the special transformer state management method based on intelligent monitoring and remote diagnosis described in the present invention, the provision of fault diagnosis information includes: when the current is continuously overloaded and accompanied by a voltage drop, the system determines that the equipment is overloaded or the transformer is abnormal; through the linkage analysis of frequency anomalies and voltage fluctuations, it is determined that the equipment failure is caused by the instability of the power grid;

[0036] Combined with historical operation data, a fault cause analysis report is generated, and the maintenance records of the equipment are compared to determine whether the fault is caused by equipment aging or long-term lack of maintenance, and provide corresponding analysis conclusions;

[0037] For overload failures, adjust load distribution or replace overloaded equipment immediately; for frequency anomalies, check the upstream power grid or use backup power; processing suggestions will be personalized based on the operating environment and historical records of the equipment;

[0038] The diagnosis results and treatment suggestions are synchronized to the monitoring terminal of the operation and maintenance personnel through the remote server.

[0039] The special transformer status management system based on intelligent monitoring and remote diagnosis is characterized by: including:

[0040] Data acquisition module: collects electrical parameters of dedicated transformer users through monitoring equipment;

[0041] Data analysis and judgment module: real-time analysis of collected data parameters to determine the operating status and abnormal conditions of the equipment;

[0042] Data transmission and remote monitoring module: transmit monitoring data through the communication network to achieve remote monitoring;

[0043] Alarm and fault diagnosis module: When an abnormality is detected, the alarm mechanism is triggered and fault diagnosis information is provided.

[0044] Beneficial effects of the invention: The invention can monitor the electrical parameters of the dedicated transformer users in real time, including voltage, current, active power, reactive power, apparent power, power factor and grid frequency, by integrating low-power current transformer (LPCT), voltage transformer (EVT) and intelligent monitoring system. It can not only deal with short-circuit faults, but also effectively monitor and protect against electrical abnormalities such as overload and undervoltage. This multifunctional protection improves the adaptability of the equipment, enabling it to provide more comprehensive electrical protection under complex grid conditions.

[0045] The present invention integrates low-power current transformer, voltage transformer and power supply unit into an integrated design, which reduces the size of the equipment and simplifies the on-site installation and maintenance process. The integrated design not only reduces the space occupied by the equipment, but also improves the reliability of the system and the accuracy of data acquisition, and reduces the difficulty of equipment maintenance.

[0046] Through real-time monitoring and intelligent analysis, the present invention can timely discover potential hidden dangers in the power grid and prevent large-scale failures and power outages caused by electrical anomalies. In addition, through the monitoring of power factor and power grid frequency, the present invention can ensure the stable operation of the power grid, improve the quality of power, and ensure the safety of the power supply system. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the figures required for use in the description of the embodiments will be briefly introduced below. Obviously, the figures described below are only some embodiments of the present invention. For ordinary technicians in this field, other figures can be obtained based on these figures without paying creative work.

[0048] Figure 1 A flow chart of a special transformer status management method based on intelligent monitoring and remote diagnosis provided for the first embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the specification drawings. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0050] Example 1, reference Figure 1 , is an embodiment of the present invention, and provides a special transformer state management method based on intelligent monitoring and remote diagnosis, comprising:

[0051] S1: Collect the electrical parameters of the dedicated transformer user through monitoring equipment.

[0052] By integrating low-power current transformer, voltage transformer and power taking unit into the high-voltage drop-out fuse, the integrated casting design can collect the voltage and current of each phase in real time.

[0053] The voltage value of each phase is collected in real time through the voltage transformer, and the fluctuation of the line voltage is recorded; the current value of each phase is collected in real time through the low-power current transformer, and the current load of the line is analyzed; based on the collected voltage and current values, the active power and reactive power of each phase and the total are calculated to provide a basis for the analysis of power consumption and power factor; the apparent power is calculated based on the voltage and current values, and the operating efficiency of the power supply system is monitored in combination with the active power and reactive power data; the power factor is calculated through the ratio of active power to apparent power, which is used to evaluate the power quality of the power supply system; the grid frequency parameters are collected in real time through monitoring equipment to determine the stability of the power system and monitor frequency deviations to prevent power supply failures.

[0054] Furthermore, the integrated design of low-power current transformer (LPCT), voltage transformer (EVT) and power supply unit. This design integrates these three components into the high-voltage drop-out fuse, which not only simplifies the installation and maintenance process of the equipment and reduces the complexity of the system, but also significantly improves the efficiency and accuracy of data collection. Although this integrated design has applications in other power equipment, its use in high-voltage drop-out fuses can solve its existing technical problems of single function and lack of intelligence. Through this design, the voltage and current of each phase can be continuously and stably collected, providing a basis for subsequent electrical parameter analysis.

[0055] Secondly, the voltage transformer (EVT) is used to collect the voltage value of each phase in real time and record the fluctuation of the line voltage. The beneficial effect of this step is that it can capture the changes in the line voltage in a timely manner, especially abnormal conditions such as overvoltage or undervoltage. This real-time collection function can greatly improve the ability to perceive the line status, so that the system can quickly take response measures when voltage anomalies are detected, and effectively prevent faults caused by voltage fluctuations. In the operation of modern power grids, voltage fluctuations are one of the common causes of equipment damage and system failures. Therefore, accurate voltage monitoring can significantly improve the safety and stability of the power supply system.

[0056] The real-time collection of current values ​​of each phase by low-power current transformers and analysis of the current load of the line solves the problem of the inability to accurately detect load changes in existing technologies. Real-time collection of current data can not only detect faults such as overload and short circuit, but also provide basic data for subsequent power calculations. In particular, for the monitoring of current loads, the accumulation of historical data can help operation and maintenance personnel predict the change trend of loads, thereby optimizing the management of the distribution system.

[0057] Based on the collected voltage and current values, the system can calculate the active power and reactive power of each phase and the total. The beneficial effect of this process is that it can provide real-time information on power consumption and evaluate the efficiency of the power supply system through the data of active power and reactive power. For example, when the reactive power is too high, the efficiency of power utilization is reduced. At this time, the system can improve efficiency by adjusting the corresponding compensation measures. This real-time power calculation function provides an important basis for improving power quality and optimizing the efficiency of the power supply system.

[0058] Furthermore, the calculation of apparent power combines the data of active power and reactive power to further refine the monitoring of the operating efficiency of the power supply system. Through the ratio of active power to apparent power, the system can accurately calculate the power factor for evaluating the power quality. The power factor is an important indicator for evaluating efficiency and stability in the power system. By improving the power factor, the power loss can be effectively reduced, and the economy and operating quality of the system can be improved.

[0059] Finally, real-time collection of grid frequency parameters is used to determine the stability of the power system and monitor frequency deviations to prevent power supply failures, which is one of the core steps to ensure the safe operation of the power grid. In actual operation, changes in grid frequency are often early signals of decreased system stability. Through real-time monitoring of frequency, the system can detect potential risks of the power grid in advance, take corresponding emergency plans, and avoid power accidents caused by frequency anomalies.

[0060] S2: Analyze the collected data parameters in real time to determine the operating status and abnormal conditions of the equipment.

[0061] The collected voltage value is analyzed by an intelligent algorithm. If the voltage value is the normal line operating voltage and the circuit breaker is in an online state, it is determined that the equipment is working normally; if the voltage value is zero and the circuit breaker is still in an online state, it is determined that the circuit breaker is in a drop state.

[0062] Collect and monitor the opening or closing position information of the drop-out fuse in real time, determine whether the circuit breaker is in the open or closed state, and record the opening and closing actions of the circuit breaker.

[0063] By analyzing the current data, if the current exceeds the rated load of the equipment, it is judged that the equipment is in an overload state, the protection mechanism is triggered and the operation and maintenance personnel are notified.

[0064] By real-time monitoring of the voltage value, when the voltage is lower than the set normal range, it is judged as undervoltage state and the device enters abnormal monitoring state.

[0065] When the voltage value exceeds the set upper or lower limit, it is judged as a voltage over-limit state, and the system immediately issues an alarm and initiates protection measures.

[0066] According to the set collection cycle, the real-time operating data of voltage, current and power are stored regularly to generate load curves for historical analysis and evaluation of equipment operating status.

[0067] When overload, undervoltage, or voltage exceeding the limit is detected, the system actively triggers the alarm mechanism and sends alarm information to the operation and maintenance personnel through the communication network, indicating the specific fault details and providing targeted processing suggestions.

[0068] Furthermore, the voltage value is analyzed by an intelligent algorithm, and combined with the online status of the circuit breaker to determine whether the equipment is in normal operation or a drop state. The combination of real-time monitoring of the voltage value and circuit breaker status information realizes the intelligent monitoring of the drop-out fuse. If the voltage is zero and the circuit breaker is online, it is judged to be in a drop state. This method avoids the limitations of traditional reliance on single voltage monitoring and improves the accuracy of equipment operation status judgment. The beneficial effect is that by judging the drop state in real time, the drop fault can be quickly discovered and located, avoiding equipment damage and power outages caused by the failure to detect the drop state in time.

[0069] Real-time collection and monitoring of the opening and closing position information of the drop-out fuse is an important function that can record the operation of the circuit breaker. Compared with the existing technology that relies solely on manual inspection, this real-time recording and automatic monitoring effectively improves operational efficiency and data accuracy. Real-time monitoring of the opening and closing status can not only reflect the normal working status of the circuit breaker, but also provide data support for subsequent maintenance to prevent power accidents caused by misoperation or equipment failure. Its beneficial effect is that it can provide a continuous circuit breaker operation history, providing accurate judgment basis for operation and maintenance personnel.

[0070] Current data analysis can identify overload conditions in a timely manner and automatically trigger protection mechanisms. The innovation is that the system can monitor in real time whether the current exceeds the equipment's carrying capacity through the set rated load standard, and immediately trigger alarms and protective measures when overload occurs. Compared with traditional overload protection devices, this method can automatically start protective measures when the operation and maintenance personnel fail to discover it in time, thus avoiding damage to the equipment due to long-term overload. The beneficial effect is that the system's autonomous protection capability is improved and the loss of equipment caused by overload is reduced.

[0071] For the monitoring of undervoltage and voltage overlimit, the invention sets a voltage threshold, and can quickly determine and take corresponding measures when the voltage is lower than or exceeds the normal range. This function is particularly suitable for voltage fluctuations or sudden changes that may occur in the power system. Compared with the relatively backward voltage monitoring method in the prior art, the present invention continuously monitors the voltage and automatically makes judgments through an intelligent algorithm, which significantly improves the response speed to abnormal voltage conditions, and can trigger an alarm and protection mechanism as soon as the voltage exceeds the limit, avoiding greater accidents in the power supply system. Its beneficial effects are reflected in ensuring the stability of the power grid by effectively controlling the voltage, and preventing equipment damage or system collapse caused by abnormal voltage.

[0072] The generation of load curves is another key step in the invention. The system regularly stores voltage, current and power data according to the collection cycle for historical analysis and evaluation of the equipment's operating status. Compared with relying solely on real-time data, this method can detect potential operating problems through historical data analysis and provide strong data support for equipment optimization and grid control. Its beneficial effect is that it can achieve long-term monitoring and trend prediction, helping power system operators to make more scientific decisions.

[0073] Finally, the active alarm mechanism plays a key role in overload, undervoltage or voltage overrun. The system can convey specific fault information to operation and maintenance personnel in real time through the communication network and provide detailed processing suggestions. Compared with the traditional alarm system, the active alarm mechanism of the present invention can not only notify the fault, but also combine the collected data to provide targeted solutions, further improving the efficiency of fault handling. Its beneficial effect is to reduce power outage time and ensure the continuity and stability of power supply by quickly responding to faults.

[0074] S3: Transmit monitoring data through the communication network to achieve remote monitoring.

[0075] Upload the collected voltage, current, active power, reactive power, apparent power, power factor and grid frequency data to the remote server in real time;

[0076] Supports short-distance communication via local micro-power wireless or Bluetooth to transmit data to a nearby monitoring center, and combines with long-range 4G / 5G network communication to achieve multi-level transmission of monitoring data;

[0077] All transmitted data is processed through the AES encryption algorithm to ensure that it is not attacked or tampered with by external parties during the data upload process;

[0078] Each time data is transmitted, the remote server sends a confirmation response to the monitoring device to ensure that all monitoring data is successfully transmitted and fully stored on the server side;

[0079] Based on actual needs, monitoring data is divided into two modes: real-time transmission and periodic synchronization. Real-time transmission is used for alarm information and abnormal situations, while periodic synchronization is used to store historical operation data and load curves.

[0080] Furthermore, first of all, the key to the step of uploading electrical parameters in real time through the communication network is that the collected voltage, current, active power, reactive power, apparent power, power factor and grid frequency data are uploaded to the remote server in real time through the 4G / 5G network. This real-time transmission of multiple parameters not only provides all-round monitoring of the electrical system, but also ensures the timeliness of the data. In traditional power monitoring, data transmission often has delays or cannot fully cover all important electrical parameters. This real-time data upload function of the present invention can greatly improve the system's response speed to changes in electrical parameters, ensuring that accurate data can be obtained in time for processing when abnormal situations occur. The beneficial effect is that through the comprehensive monitoring of multiple electrical parameters, the system can make a more accurate assessment of the operating status of the power system, and promptly discover and prevent potential problems.

[0081] Secondly, local micro-power wireless or Bluetooth short-range communication combined with long-range 4G / 5G communication provides a multi-level data transmission structure. This design can rely on local short-range communication to ensure that monitoring data can be transmitted to a nearby monitoring center when long-range communication is interrupted or limited, further enhancing the reliability of the system. Compared with the traditional single communication method, this multi-level transmission can effectively cope with unstable communication networks and ensure the continuity of data transmission. The beneficial effect is that even when the remote network is interrupted, the system can still transmit data through the local network, avoiding monitoring blind spots and improving the fault tolerance of the system.

[0082] The introduction of the AES encryption algorithm ensures the security of transmitted data. AES (Advanced Encryption Standard) is a widely used encryption algorithm that can ensure that data is not tampered with or attacked during transmission. Compared with the unencrypted traditional data transmission method, the present invention uses AES encryption to process monitoring data, which can effectively prevent external attackers from intercepting, modifying or interfering with data. The beneficial effect is that AES encryption technology ensures the data transmission security of the power system, prevents malicious attackers from exploiting data vulnerabilities to perform illegal operations, and thus improves the security and stability of the entire system.

[0083] In addition, the confirmation response mechanism for data transmission also ensures the integrity of the data. After each data transmission, the remote server sends a confirmation response to the monitoring device to verify whether the data is successfully received and completely stored. This mechanism solves the risk of packet loss or transmission failure that may exist in the existing technology, ensuring that all critical data can be reliably stored and processed. Compared with traditional transmission methods, this confirmation mechanism can greatly reduce the possibility of data loss and ensure the reliability of the system. Its beneficial effect is that it improves the accuracy and reliability of data transmission, ensuring that operation and maintenance personnel can perform fault diagnosis and system analysis based on complete real-time data.

[0084] The division of real-time transmission and periodic synchronization modes. The real-time transmission mode is used for alarm information and abnormal situations, ensuring that when the system detects overload, undervoltage or voltage overrun, an alarm can be immediately sent to the operation and maintenance personnel. The periodic synchronization mode is used to store historical operation data and load curves for subsequent analysis and optimization management. Compared with traditional data collection methods, this dual-mode data transmission mechanism can not only ensure the instant transmission of key information, but also provide detailed historical records for long-term equipment monitoring. The beneficial effect is that the system can flexibly select the data transmission method according to different needs, which not only ensures a rapid response in abnormal situations, but also ensures long-term tracking and analysis of the equipment operation status.

[0085] S4: When an abnormality is detected, an alarm mechanism is triggered and fault diagnosis information is provided.

[0086] When an abnormal state is detected, the system immediately activates the alarm mechanism, analyzes the abnormal parameters, and generates an abnormal data packet, which contains the abnormal type and the specific values ​​of the relevant electrical parameters.

[0087] The alarm information contains the unique identification of the device, the specific time when the abnormality occurred, the detailed values ​​of the electrical parameters, the geographical location information of the device, and the current working status of the device.

[0088] The system classifies alarm information according to the severity of the fault. The priority of current overload alarm information is higher than that of voltage fluctuation alarm. The priority of frequency abnormality alarm is determined according to the fluctuation amplitude. The alarm information will indicate the priority to help operation and maintenance personnel prioritize serious faults.

[0089] When the current is continuously overloaded and accompanied by a voltage drop, the system determines that the equipment is overloaded or the transformer is abnormal; through the linkage analysis of frequency anomalies and voltage fluctuations, it is determined that the equipment failure is caused by grid instability.

[0090] Combined with historical operation data, a fault cause analysis report is generated, and the maintenance records of the equipment are compared to determine whether the fault is caused by equipment aging or long-term lack of maintenance, and provide corresponding analysis conclusions.

[0091] For overload failures, adjust the load distribution or immediately replace the overloaded equipment; for frequency anomalies, check the upstream power grid or use backup power supply; processing suggestions will be personalized based on the operating environment and historical records of the equipment.

[0092] The diagnosis results and treatment suggestions are synchronized to the monitoring terminal of the operation and maintenance personnel through the remote server.

[0093] Furthermore, the alarm information not only contains the unique identification and specific electrical parameters of the equipment, but also records the time when the abnormality occurred, the geographical location information of the equipment, and the current working status of the equipment. This multi-dimensional information transmission greatly improves the judgment efficiency of operation and maintenance personnel. Compared with the single fault prompt in the traditional alarm system, the present invention allows operation and maintenance personnel to quickly locate the specific location of the fault and make more accurate maintenance decisions based on the working status of the equipment. The beneficial effect is that by recording and transmitting the status information of the equipment in detail, the operation and maintenance personnel can quickly take targeted measures to reduce the downtime of the power system.

[0094] Furthermore, the classification and priority setting of alarm information allows the system to automatically assign the processing order according to the severity of the fault. For the alarm information of current overload, its priority is set higher than the voltage fluctuation alarm to ensure priority processing of high-risk faults. The alarm priority of frequency abnormality is set according to the fluctuation amplitude. Compared with the traditional equal processing method, this priority mechanism enables operation and maintenance personnel to concentrate resources and time to deal with the faults that have the greatest impact on the system, avoiding untimely processing due to resource dispersion. The beneficial effect is that by classifying the severity of the fault, the efficiency of operation and maintenance is effectively improved, ensuring that the most serious faults in the system can be responded to and resolved first.

[0095] In terms of fault diagnosis, the intelligent algorithm of the present invention can combine different electrical parameters for linkage analysis. When the current is continuously overloaded and the voltage drops, the system determines that the equipment is overloaded or the transformer is abnormal; through the correlation analysis of frequency anomalies and voltage fluctuations, the system can determine whether the equipment failure is caused by grid instability. This comprehensive analysis function is relatively rare in traditional power systems, and its beneficial effect is that it can more accurately determine the root cause of the fault through the correlation analysis of multi-dimensional data, avoiding misjudgment caused by single data.

[0096] By comparing the current fault information with the historical data of the equipment, the system can generate a detailed fault cause analysis report to determine whether the fault is caused by equipment aging or long-term lack of maintenance. This analysis based on historical data can detect potential problems of the equipment in advance and prevent major faults from being caused by long-term neglect of minor faults. Its beneficial effect is that by introducing historical data analysis, the system can achieve preventive maintenance of faults, improve equipment reliability, and reduce sudden faults caused by equipment aging or improper maintenance.

[0097] The generation of personalized processing suggestions is a targeted solution for different fault types. For example, for overload faults, the system recommends adjusting load distribution or immediately replacing overloaded equipment; for frequency anomalies, the system recommends checking the upstream power grid or using a backup power supply. Compared with the general prompts in traditional systems, the processing suggestions provided by the present invention are more personalized and accurate, and can generate solutions adapted to specific fault conditions based on the operating environment and historical records of the equipment. The beneficial effect is that the processing suggestions provided are more practical, reduce the risk of blind operation, and improve the decision-making quality of operation and maintenance personnel.

[0098] Finally, the synchronization function of diagnostic results and processing suggestions ensures that operation and maintenance personnel can obtain equipment fault diagnosis information and processing suggestions in real time through the remote server.

[0099] Embodiment 2 is the second embodiment of the present invention, which is different from the previous embodiment in that:

[0100] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the current technical solution, can be embodied in the form of a software product. The current computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0101] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, system or device (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, system or device and execute the instructions), or in conjunction with these instruction execution systems, systems or devices. For the purpose of this specification, "computer-readable medium" can be any system that can contain, store, communicate, propagate or transport a program for use by an instruction execution system, system or device, or in conjunction with these instruction execution systems, systems or devices.

[0102] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic systems), a portable computer disk case (magnetic systems), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber system, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0103] Example 3 is an embodiment of the present invention, which provides a special transformer status management system based on intelligent monitoring and remote diagnosis, characterized in that it includes a data acquisition module, a data analysis and judgment module, a data transmission and remote monitoring module, and an alarm and fault diagnosis module.

[0104] Data acquisition module: collects the electrical parameters of the dedicated transformer users through monitoring equipment.

[0105] Data analysis and judgment module: Real-time analysis of collected data parameters to determine the operating status and abnormal conditions of the equipment.

[0106] Data transmission and remote monitoring module: transmit monitoring data through the communication network to realize remote monitoring.

[0107] Alarm and fault diagnosis module: When an abnormality is detected, the alarm mechanism is triggered and fault diagnosis information is provided.

[0108] Example 4 is an embodiment of the present invention, which provides a special transformer status management method based on intelligent monitoring and remote diagnosis. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation / comparative experiments.

[0109] This experiment targets 6 dedicated transformer user devices, namely test objects A to F, and uses monitoring equipment to collect electrical parameters of each device in real time. The main purpose of the experiment is to verify the electrical parameter collection, fault detection and alarm response performance of the system of the present invention under different loads and operating conditions. The equipment monitors key parameters such as voltage, current, power and frequency in real time by integrating low-power current transformers and voltage transformers. In order to simulate the actual operating environment, the test equipment is under different load conditions, and some equipment has experienced abnormal conditions such as overload, undervoltage and frequency fluctuation during operation.

[0110] The monitoring system of each device transmits the collected parameters to the remote server in real time through the 4G / 5G network, and triggers the alarm mechanism immediately when an abnormality is detected. Each time data is transmitted, the server sends a confirmation response to ensure the integrity of the transmitted data. The system classifies the faults according to the severity of the alarm information and prioritizes high-risk issues. The entire experiment lasts 24 hours, and data is collected in real time and stored regularly for subsequent load curve generation and operation status analysis. For specific data content, please refer to Table 1.

[0111]

[0112]

[0113] From the data in the table, it can be seen that there are significant differences in the operation of the equipment under different voltages and currents, especially in test object D, the voltage reaches 245V and the current is 19A, which indicates that the equipment is in a high-load operation state. Correspondingly, the active power of test object D is 3.80kW, which is significantly higher than other equipment, which is consistent with the actual operation state of the equipment, further verifying the monitoring accuracy of the system of the present invention for high-load equipment.

[0114] Compared with the prior art, the innovation of the present invention lies in the system's ability to accurately detect and classify alarms. For example, when the current exceeds the rated load, such as the current value of test object D that exceeds the standard range, the system immediately triggers an overload alarm. At the same time, the voltage and frequency data of test objects B and F are relatively stable, indicating that the system can operate efficiently under normal working conditions and analyze various parameters in real time.

[0115] Through the analysis of frequency data, the frequency values ​​of test objects A, C, E and F are all close to 50Hz, showing the stability of power grid operation, but in test object D, the system detected a frequency fluctuation of 50.2Hz, and the system promptly issued a frequency abnormality alarm, indicating that the equipment may have power grid instability problems. Through this real-time alarm mechanism, operation and maintenance personnel can take quick measures to avoid potential equipment damage and system failures.

[0116] In addition, the system can also generate load curves based on historical data to evaluate the long-term operating status of the equipment. For example, the power factor of test object B is 0.98, indicating that the equipment is operating at a relatively high efficiency; while the power factor of test object C is 0.97, which is slightly lower but still within the normal range. By comparing the operating data of each device, the real-time and accuracy of the system of the present invention are verified, and it can provide reliable data support for the maintenance and regulation of the equipment.

[0117] In summary, the experimental data show that the system of the present invention has significant advantages in electrical parameter collection, fault analysis, real-time alarm, etc., and can effectively make up for the problems of monitoring lag, incomplete data and untimely response of alarm mechanism in the prior art.

[0118] It should be noted that the above embodiments are only used to illustrate the technical solutions 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 solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A special transformer status management method based on intelligent monitoring and remote diagnosis, characterized in that: include: Collect electrical parameters of dedicated transformer users through monitoring equipment; Analyze the collected data parameters in real time to determine the operating status and abnormal conditions of the equipment; Transmit monitoring data through communication network to achieve remote monitoring; When an anomaly is detected, an alarm mechanism is triggered and fault diagnosis information is provided.

2. The method for managing the state of a special transformer based on intelligent monitoring and remote diagnosis as claimed in claim 1, characterized in that: The monitoring device includes an integrated casting design by integrating a low-power current transformer, a voltage transformer and a power-taking unit into a high-voltage drop-out fuse to collect the voltage and current of each phase in real time.

3. The method for managing the state of a special transformer based on intelligent monitoring and remote diagnosis as claimed in claim 2, characterized in that: The electrical parameters of the user of the special transformer are collected including: The voltage value of each phase is collected in real time through the voltage transformer, and the fluctuation of the line voltage is recorded; The current value of each phase is collected in real time through low-power current transformers to analyze the line current load; Based on the collected voltage and current values, calculate the active power and reactive power of each phase and the total, and provide an analysis basis for power consumption and power factor; Calculate apparent power based on voltage and current values, and monitor the operating efficiency of the power supply system by combining active power and reactive power data; The power factor is calculated by the ratio of active power to apparent power and is used to evaluate the power quality of the power supply system; The monitoring equipment collects grid frequency parameters in real time to determine the stability of the power system and monitor frequency deviations to prevent power supply failures.

4. The method for managing the state of a special transformer based on intelligent monitoring and remote diagnosis as claimed in claim 3, characterized in that: The judging of the operating status and abnormal conditions of the equipment includes analyzing the collected voltage value through an intelligent algorithm, and if the voltage value is a normal line operating voltage and the circuit breaker is in an online state, it is judged that the equipment is operating normally; If the voltage value is zero and the circuit breaker is still online, it is determined that the circuit breaker is in a drop state; Collect and monitor the opening or closing position information of the drop-out fuse in real time, determine whether the circuit breaker is in the open or closed state, and record the opening and closing actions of the circuit breaker; By analyzing the current data, if the current exceeds the rated load of the equipment, it is judged that the equipment is in an overload state, the protection mechanism is triggered and the operation and maintenance personnel are notified; By monitoring the voltage value in real time, when the voltage is lower than the set normal range, it is judged as undervoltage state and the device enters abnormal monitoring state; When the voltage value exceeds the set upper or lower limit, it is judged as voltage over-limit state, and the system immediately issues an alarm and initiates protection measures; According to the set collection cycle, the real-time operation data of voltage, current and power are stored regularly to generate load curves for historical analysis and evaluation of equipment operation status; When overload, undervoltage, or voltage exceeding the limit is detected, the system actively triggers the alarm mechanism and sends alarm information to the operation and maintenance personnel through the communication network, indicating the specific fault details and providing targeted processing suggestions.

5. The method for managing the state of a special transformer based on intelligent monitoring and remote diagnosis as claimed in claim 4, characterized in that: The transmission of monitoring data via the communication network includes uploading the collected voltage, current, active power, reactive power, apparent power, power factor and grid frequency data to a remote server in real time; Supports short-distance communication via local micro-power wireless or Bluetooth to transmit data to a nearby monitoring center, and combines with long-range 4G / 5G network communication to achieve multi-level transmission of monitoring data; All transmitted data is processed through the AES encryption algorithm to ensure that it is not attacked or tampered with by external parties during the data upload process; Each time data is transmitted, the remote server sends a confirmation response to the monitoring device to ensure that all monitoring data is successfully transmitted and fully stored on the server side; Based on actual needs, monitoring data is divided into two modes: real-time transmission and periodic synchronization. Real-time transmission is used for alarm information and abnormal situations, while periodic synchronization is used to store historical operation data and load curves.

6. The method for managing the state of a special transformer based on intelligent monitoring and remote diagnosis as claimed in claim 5, characterized in that: The triggering alarm mechanism includes that when an abnormal state is detected, the system immediately activates the alarm mechanism, analyzes the abnormal parameters, and generates an abnormal data packet, which contains the abnormal type and the specific values ​​of the relevant electrical parameters; The alarm information contains the unique identification of the device, the specific time when the abnormality occurred, the detailed values ​​of the electrical parameters, the geographical location information of the device, and the current working status of the device; The system classifies alarm information according to the severity of the fault. The priority of current overload alarm information is higher than that of voltage fluctuation alarm. The priority of frequency abnormality alarm is determined according to the fluctuation amplitude. The alarm information will indicate the priority to help operation and maintenance personnel prioritize serious faults.

7. The method for managing the state of a special transformer based on intelligent monitoring and remote diagnosis as claimed in claim 6, characterized in that: The provision of fault diagnosis information includes: when the current is continuously overloaded and accompanied by a voltage drop, the system determines that the equipment is overloaded or the transformer is abnormal; Through the linkage analysis of frequency anomalies and voltage fluctuations, it is determined that the equipment failure is caused by grid instability; Combined with historical operation data, a fault cause analysis report is generated, and the maintenance records of the equipment are compared to determine whether the fault is caused by equipment aging or long-term lack of maintenance, and provide corresponding analysis conclusions; In case of overload failure, adjust the load distribution or replace the overloaded equipment immediately; In case of frequency anomalies, check the upstream power grid or use backup power supply; processing suggestions will be personalized according to the operating environment and historical records of the equipment; The diagnosis results and treatment suggestions are synchronized to the monitoring terminal of the operation and maintenance personnel through the remote server.

8. A special transformer status management system based on intelligent monitoring and remote diagnosis using the method according to any one of claims 1 to 7, characterized in that: Data acquisition module: collects electrical parameters of dedicated transformer users through monitoring equipment; Data analysis and judgment module: real-time analysis of collected data parameters to determine the operating status and abnormal conditions of the equipment; Data transmission and remote monitoring module: transmit monitoring data through the communication network to achieve remote monitoring; Alarm and fault diagnosis module: When an abnormality is detected, the alarm mechanism is triggered and fault diagnosis information is provided.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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