Transformer intelligent temperature monitoring device based on monitoring technology

Abstract

The invention discloses a transformer intelligent temperature monitoring device based on a monitoring technology, which relates to the technical field of transformer intelligent temperature monitoring and comprises a temperature sensing module, a data processing module, a fault diagnosis module, a data transmission module and a remote monitoring module. And the temperature sensing module is used for acquiring temperature information of each key part of the transformer in real time. According to the invention, high-precision temperature monitoring is realized through the fiber grating sensor, the anti-interference capability is enhanced, and accurate fault diagnosis is realized through the GRU neural network and the fuzzy logic algorithm. And a dual-channel redundancy communication mechanism is adopted to ensure the stability and safety of data transmission. A Web-based remote monitoring platform improves the operation convenience, and a multi-level alarm function ensures safe operation. The system integration module realizes seamless connection with the existing power monitoring platform, has high adaptability and expansibility, reduces the deployment cost, and improves the equipment management efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent temperature monitoring of transformers, and in particular to an intelligent temperature monitoring device for transformers based on monitoring technology. Background Art

[0002] In the power system, transformers are key equipment, and the monitoring of their operating temperature is crucial to the stability and reliability of the power system. At present, the mainstream transformer temperature monitoring technologies include resistance temperature detectors (RTDs), thermocouples, fiber grating sensors, infrared thermal imagers, and intelligent wireless sensor networks. These technologies have their own advantages and disadvantages: RTDs can monitor temperature indirectly, but the response speed is slow and the maintenance cost is high; thermocouples are suitable for high temperature environments, but are easily affected by electromagnetic interference; fiber grating sensors have good corrosion resistance in harsh environments, but the cost is high; infrared thermal imagers are suitable for non-contact rapid scanning of temperature distribution, but the measurement accuracy is limited in complex environments; intelligent wireless sensor networks are suitable for large-scale or distributed temperature monitoring, but there are problems with data transmission delays and signal interference.

[0003] Although the existing temperature monitoring technology has met the needs of transformer operation to a certain extent, there are still some obvious shortcomings. First, many high-precision devices are expensive, especially when large-scale deployment is required, the cost issue is more prominent. Secondly, the maintenance of some monitoring equipment is complicated and requires regular calibration, which increases the operating cost and difficulty of use. In addition, strong electromagnetic interference can easily affect the accuracy of measurement and cause data deviation. More importantly, when the existing system responds to rapid temperature changes, the data update is not timely enough, which may affect the response speed of the system. Finally, in extreme environments, some sensors may have difficulty working properly or their lifespan may be significantly shortened, which will affect the long-term reliability of the equipment. Therefore, it is particularly necessary to develop a new intelligent transformer temperature monitoring device to improve monitoring accuracy, stability and environmental adaptability.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent transformer temperature monitoring device based on monitoring technology, which realizes high-precision temperature monitoring through fiber grating sensors, enhances anti-interference ability, and realizes accurate fault diagnosis through GRU neural network and fuzzy logic algorithm. A dual-channel redundant communication mechanism is adopted to ensure the stability and security of data transmission. The Web-based remote monitoring platform improves the convenience of operation, and the multi-level alarm function ensures safe operation. The system integration module realizes seamless connection with the existing power monitoring platform, has high adaptability and scalability, reduces deployment costs, and improves equipment management efficiency to solve the problems in the above-mentioned background technology.

[0006] In order to achieve the above-mentioned object, the present invention provides the following technical solutions: an intelligent transformer temperature monitoring device based on monitoring technology, comprising a temperature sensing module, a data processing module, a fault diagnosis module, a data transmission module, a remote monitoring module and a power management module;

[0007] The temperature sensing module is used to collect the temperature information of each key part of the transformer in real time. The temperature sensing module includes multiple fiber grating sensors, which are distributed in the oil tank, winding, core and various connection parts of the transformer, and can accurately reflect the temperature changes of different parts;

[0008] A data processing module is connected to the temperature sensing module for receiving and processing the collected temperature information. The data processing module further includes a data filtering unit for eliminating noise signals in the temperature data and extracting high-frequency and low-frequency components of the temperature signal through wavelet packet decomposition technology to identify subtle temperature fluctuations.

[0009] The fault diagnosis module performs anomaly detection based on the received data, and accurately judges the potential fault type by integrating the GRU (Gated Recurrent Unit) neural network model and fuzzy logic algorithm, combined with the transformer's historical operation data and real-time temperature data. The module can output corresponding diagnostic reports for different fault types;

[0010] Data transmission module, including wireless communication unit and redundant communication mechanism, used to transmit processed temperature data and diagnostic results to the remote monitoring center through wireless network or wired network. The wireless communication unit adopts DM9000AEP chip design to ensure the stability and low latency of data transmission, and supports remote data transmission of 4G / 5G network;

[0011] Remote monitoring module, including a Web-based visualization platform and a local monitoring terminal. The visualization platform displays the real-time temperature status, historical temperature curves, fault diagnosis results and alarm information of the transformer, and provides remote control functions. Users can remotely set temperature thresholds and alarm conditions through the platform. The monitoring platform supports cross-platform operation and multi-user access;

[0012] The power management module is used to provide a stable power supply for each module and has an automatic power failure switching function. When the main power fails, it can switch to the backup power supply to ensure the continuous operation of the system.

[0013] Preferably, the fiber grating sensor of the temperature sensing module further includes a temperature compensation unit to reduce the influence of ambient temperature changes on the measurement accuracy of the sensor.

[0014] Preferably, the data processing module further includes a temperature trend analysis unit, which predicts the temperature trend of the transformer by comparing historical data with real-time data, provides warning information, and can automatically adjust the temperature threshold.

[0015] Preferably, the fault diagnosis module optimizes the hyperparameters of the GRU neural network by introducing the GridSearchCV algorithm to ensure that the fault diagnosis model can meet the requirements of high precision and high stability under different working conditions.

[0016] Preferably, the data transmission module has a dual-channel redundant design, including a main channel for conventional data transmission and a backup channel for data transmission in emergency situations, ensuring that critical data can be transmitted to the remote monitoring center in real time under any circumstances.

[0017] Preferably, the visualization platform of the remote monitoring module further includes a fault location function, which automatically generates a fault location map by analyzing the temperature changes and diagnosis results of various parts of the transformer, so that maintenance personnel can quickly find the fault location.

[0018] Preferably, the device also includes an abnormal alarm module, which automatically triggers a multi-level alarm system when a transformer fault or temperature abnormality is diagnosed, including local sound and light alarms and remote SMS and email alarm functions, to ensure that relevant personnel receive alarm information in a timely manner.

[0019] Preferably, the system integration module is used to seamlessly integrate the temperature monitoring system into the existing power system monitoring platform, supporting multiple protocol interfaces such as Modbus, DNP3 and IEC 61850, and realizing data sharing, linkage and unified management.

[0020] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0021] The present invention adopts a fiber grating sensor as the core component of temperature detection, and the device can achieve high-precision temperature monitoring of key parts of the transformer. The fiber grating sensor has strong anti-electromagnetic interference ability and high sensitivity, and can accurately reflect the temperature changes inside and outside the transformer. At the same time, the sensor layout covers the high thermal sensitivity area of ​​the transformer, ensuring the real-time capture of temperature changes in different parts. The application of the temperature compensation unit further reduces the impact of ambient temperature changes on measurement accuracy. Since the system can monitor and automatically calibrate the temperature sensor in real time, the user can track the temperature changes of the transformer in real time, ensuring the safe operation of the transformer under various working conditions, and greatly improving the reliability of equipment operation.

[0022] The present invention realizes accurate diagnosis of transformer faults by integrating GRU neural network and fuzzy logic algorithm. GRU neural network is good at processing time series data, can analyze long-term temperature change patterns, and identify potential fault signs in the data. Combined with fuzzy logic algorithm, the system can deal with complex nonlinear problems, accurately classify and judge different temperature states, and thus accurately identify the type of fault. Through this advanced diagnostic method, the system can not only detect potential faults, but also provide detailed fault location and severity judgment to help maintenance personnel quickly locate the problem. This high-precision fault diagnosis capability greatly reduces the probability of false alarms and improves the efficiency and accuracy of fault handling.

[0023] The present invention designs a dual-channel redundant communication mechanism and uses the DM9000AEP chip to support 4G / 5G network communication. Through the combination of the main channel and the backup channel, the system can ensure stable data transmission in various complex environments. Even if the main channel fails, the backup channel can be automatically enabled to ensure uninterrupted data transmission. In addition, the system has data compression and AES encryption functions, which ensures data security while improving data transmission efficiency and prevents data from being intercepted or tampered with during transmission. This design ensures data transmission speed and stability in high-load power systems, greatly enhancing the reliability of the system and the confidentiality of data.

[0024] The remote monitoring module of this device provides a Web-based visualization platform that supports cross-platform operations, allowing users to monitor the operating status of the transformer in real time through PCs, tablets or mobile terminals. The platform provides a variety of data display methods, including real-time temperature curves, fault location diagrams and historical data backtracking functions, to help operators quickly understand the operating status and historical performance of the equipment. Users can also use the platform to remotely adjust the temperature alarm threshold, start or shut down the cooling system, etc., to achieve remote operation of the transformer. The multi-level alarm function ensures that when an abnormal situation occurs, relevant personnel can receive alarm information in a timely manner through multiple channels (such as text messages, emails, etc.). The convenience of this remote monitoring and operation not only improves the efficiency of equipment management, but also greatly enhances the safety of transformer operation.

[0025] The present invention realizes seamless connection between the temperature monitoring system and the existing power system monitoring platform through the system integration module. The system supports multiple protocol interfaces, such as Modbus, DNP3 and IEC 61850, ensuring compatibility and data sharing capabilities with other monitoring systems. This high integration enables the device to be easily integrated into the existing power system, which not only reduces additional hardware investment, but also realizes linkage and unified management between different systems. In addition, the modular design of the device makes it highly adaptable, and can be flexibly configured and expanded according to different application scenarios to meet the personalized needs of different users. This integration and adaptability not only reduces the deployment cost of the system, but also greatly improves the expansion capability and practicality of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0027] Figure 1 It is the overall design diagram of the present invention;

[0028] Figure 2 The hardware structure diagram of the transformer information collection and transmission module of the present invention;

[0029] Figure 3 The transformer operation process and equipment status abnormal online diagnosis system architecture of the present invention;

[0030] Figure 4 Provides technical architecture for remote monitoring and abnormal diagnosis;

[0031] Figure 5 Implement the process for transformer online abnormality diagnosis based on Labviwe mode;

[0032] Figure 6 Schematic diagram of the main program execution flow.

[0033] Figure 7 It is a module schematic diagram of the intelligent transformer temperature monitoring device based on the monitoring technology of the present invention. DETAILED DESCRIPTION

[0034] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that the description of the present disclosure will be more comprehensive and complete, and the concept of the example embodiments will be fully conveyed to those skilled in the art.

[0035] The present invention provides Figures 1 to 7 The transformer intelligent temperature monitoring device based on monitoring technology shown includes a temperature sensing module, a data processing module, a fault diagnosis module, a data transmission module, a remote monitoring module and a power management module;

[0036] The temperature sensing module is used to collect the temperature information of each key part of the transformer in real time. The temperature sensing module includes multiple fiber grating sensors, which are distributed in the oil tank, winding, core and various connection parts of the transformer, and can accurately reflect the temperature changes of different parts;

[0037] A data processing module is connected to the temperature sensing module for receiving and processing the collected temperature information. The data processing module further includes a data filtering unit for eliminating noise signals in the temperature data and extracting high-frequency and low-frequency components of the temperature signal through wavelet packet decomposition technology to identify subtle temperature fluctuations.

[0038] The fault diagnosis module performs anomaly detection based on the received data, and accurately judges the potential fault type by integrating the GRU (Gated Recurrent Unit) neural network model and fuzzy logic algorithm, combined with the transformer's historical operation data and real-time temperature data. The module can output corresponding diagnostic reports for different fault types;

[0039] Data transmission module, including wireless communication unit and redundant communication mechanism, used to transmit processed temperature data and diagnostic results to the remote monitoring center through wireless network or wired network. The wireless communication unit adopts DM9000AEP chip design to ensure the stability and low latency of data transmission, and supports remote data transmission of 4G / 5G network;

[0040] Remote monitoring module, including a Web-based visualization platform and a local monitoring terminal. The visualization platform displays the real-time temperature status, historical temperature curves, fault diagnosis results and alarm information of the transformer, and provides remote control functions. Users can remotely set temperature thresholds and alarm conditions through the platform. The monitoring platform supports cross-platform operation and multi-user access;

[0041] The power management module is used to provide a stable power supply for each module and has an automatic power failure switching function. When the main power fails, it can switch to the backup power supply to ensure the continuous operation of the system.

[0042] The fiber grating sensor of the temperature sensing module further includes a temperature compensation unit to reduce the impact of ambient temperature changes on the sensor's measurement accuracy. The data processing module further includes a temperature trend analysis unit, which predicts the temperature trend of the transformer by comparing historical data with real-time data, gives warning information, and can automatically adjust the temperature threshold. The fault diagnosis module optimizes the hyperparameters of the GRU neural network by introducing the GridSearchCV algorithm to ensure that the fault diagnosis model can meet the requirements of high accuracy and high stability under different working conditions. The data transmission module has a dual-channel redundant design, including a main channel for conventional data transmission and a backup channel for data transmission in emergency situations, ensuring that key data can be transmitted to the remote monitoring center in real time under any circumstances. The visualization platform of the remote monitoring module further includes a fault location function, which automatically generates a fault location map by analyzing the temperature changes and diagnosis results of various parts of the transformer, so that maintenance personnel can quickly find the fault location. The device also includes an abnormal alarm module. When a fault or temperature abnormality is diagnosed in the transformer, a multi-level alarm system is automatically triggered, including local sound and light alarms and remote SMS and email alarm functions, to ensure that relevant personnel receive alarm information in a timely manner. The system integration module is used to seamlessly integrate the temperature monitoring system into the existing power system monitoring platform. It supports multiple protocol interfaces such as Modbus, DNP3 and IEC 61850 to achieve data sharing, linkage and unified management.

[0043] Example 1: Installation and temperature monitoring of fiber grating sensors;

[0044] In a typical transformer temperature monitoring system, fiber grating sensors are core components responsible for real-time monitoring of the temperature of key parts of the transformer. These sensors are installed in the transformer's oil tank, windings, core, and major connection points. To ensure the accuracy of the measurement, these sensors are distributed in highly thermally sensitive areas, such as the transformer's upper oil tank, the outer layer of the winding, and the hot zone near the core to capture temperature changes inside and outside the transformer.

[0045] Each fiber grating sensor is equipped with a temperature compensation unit to reduce the impact of ambient temperature fluctuations on measurement accuracy. The sensor detects temperature changes by monitoring the wavelength changes of reflected light and transmits these data to the data processing module in real time. The system is able to process data transmitted by multiple sensors at the same time, ensuring that temperature changes in all parts of the transformer can be monitored in real time.

[0046] In addition, the layout of the sensors has been carefully designed to ensure that the most critical temperature information can be captured under any operating conditions. The system also has an automatic calibration function to regularly adjust the zero point of the sensor to ensure long-term operational stability. With this deployment, the system can immediately issue an alarm when an abnormal temperature is detected, thereby effectively preventing transformer failures due to overheating or other reasons.

[0047] Example 2: Application of data processing and wavelet packet decomposition technology;

[0048] This embodiment describes in detail the workflow and technical implementation of the data processing module. The temperature data collected by the temperature sensing module is first transmitted to the data processing module, which includes a preprocessing unit and a wavelet packet decomposition unit. The preprocessing unit uses a high-precision filtering algorithm, such as a Kalman filter, to remove high-frequency noise from the sensor or the environment to ensure the purity of the data.

[0049] After data filtering, the system applies wavelet packet decomposition technology to process the temperature signal. Wavelet packet decomposition can decompose complex temperature signals into multiple frequency bands, from which high-frequency and low-frequency information can be extracted. High-frequency components usually contain transient temperature changes and are suitable for detecting sudden temperature fluctuations; low-frequency components reflect the overall trend of temperature and are suitable for monitoring long-term temperature changes of transformers.

[0050] The system can not only decompose and analyze these signals, but also generate different alarm levels according to the temperature fluctuation characteristics of different frequencies. For example, the system can set a multi-level alarm mechanism. When the high-frequency component exceeds a certain threshold, a first-level warning is triggered; when the low-frequency component continues to be higher than the set value, a second or third-level alarm is triggered. In this way, the data processing module can promptly and accurately identify potential thermal faults of the transformer and avoid accidents.

[0051] Example 3: Fault diagnosis using GRU neural network and fuzzy logic algorithm;

[0052] In this embodiment, the fault diagnosis module uses a combination of GRU (Gated Recurrent Unit) neural network and fuzzy logic algorithm to provide a high-precision fault diagnosis method. First, the system extracts features from historical operation data and real-time temperature data and inputs these features into the GRU neural network. The GRU neural network can effectively capture the time series characteristics of temperature data through its internal memory unit, especially when processing long-term temperature change patterns.

[0053] The fuzzy logic algorithm introduced in the system is used to deal with complex nonlinear problems caused by temperature changes. Through the fuzzy rule base and membership function, the system can fuzzily classify different temperature states to determine whether the temperature fluctuation is within the normal range or indicates a potential fault. By combining the time series analysis capability of the GRU neural network with the nonlinear processing capability of fuzzy logic, the system can accurately judge the possible fault type when a temperature anomaly is detected.

[0054] For example, when the winding temperature rises abnormally, the system will analyze the speed and amplitude of the temperature rise, and combine the fuzzy logic algorithm to determine whether a winding short circuit or local overheating fault may occur. The fault diagnosis report generated by the system includes not only the fault type, but also the possible fault location and degree, providing detailed decision support for maintenance personnel.

[0055] Embodiment 4: Data transmission and redundant communication design;

[0056] This embodiment demonstrates the detailed design and implementation of the data transmission module of the intelligent transformer temperature monitoring device. The temperature data and fault diagnosis results are transmitted to the remote monitoring center in real time through the data transmission module. In order to ensure the reliability and stability of data transmission, the data transmission module is designed with a dual-channel redundant communication mechanism.

[0057] The main communication channel uses a wireless communication unit designed based on the DM9000AEP chip, supports 4G / 5G wireless networks, and provides high-speed and stable data transmission capabilities. When the main channel is working normally, all data is transmitted through this channel, ensuring the real-time and reliability of data transmission. In order to deal with the failure of the main channel or unstable communication, the system also designs a backup channel, which is connected through a wired network or based on a low-frequency wireless communication protocol (such as LoRa or ZigBee) for data transmission. The backup channel will be automatically enabled when the main channel fails to ensure uninterrupted data transmission.

[0058] In addition, the system also has data compression and encryption functions to improve data transmission efficiency and ensure data security. Before data transmission, the system will compress the temperature data and diagnostic results to reduce the transmission bandwidth occupation. At the same time, the system uses the AES encryption algorithm to encrypt the data to prevent the data from being intercepted or tampered during transmission. The design of the data transmission module ensures efficient and secure data transmission in various complex environments.

[0059] Example 5: Remote monitoring and visualization platform;

[0060] In this embodiment, the remote monitoring module provides a Web-based visualization platform, which is designed as a cross-platform application and supports access from multiple devices such as PCs, tablets, and mobile terminals. Operators can use the platform to monitor the temperature status, historical temperature data, fault diagnosis results, and alarm information of the transformer in real time. The platform uses modern Web technologies such as HTML5 and JavaScript frameworks to ensure a friendly interface and smooth operation.

[0061] The visualization platform provides a variety of data display methods, including real-time temperature curves, fault location maps, and historical temperature data backtracking. The temperature curve can intuitively display the real-time temperature changes and historical trends of various parts of the transformer, helping operators to quickly understand the operating status of the equipment. The fault location map automatically generates the temperature distribution map and faults inside the transformer through comprehensive analysis of the data from each sensor.

[0062] The platform also has powerful data analysis capabilities, which can predict future temperature trends based on the changing trends of temperature data, detect potential risks in advance, and support custom settings of temperature thresholds. Users can flexibly adjust the trigger conditions of temperature alarms according to different operating environments and equipment characteristics. In addition, the platform integrates a multi-level alarm function. When the temperature exceeds the set threshold or a fault occurs, the system will notify relevant personnel through local sound and light alarms, text messages, emails, etc. to ensure that abnormal situations are responded to in a timely manner.

[0063] The present invention adopts a fiber grating sensor as the core component of temperature detection, and the device can achieve high-precision temperature monitoring of key parts of the transformer. The fiber grating sensor has strong anti-electromagnetic interference ability and high sensitivity, and can accurately reflect the temperature changes inside and outside the transformer. At the same time, the sensor layout covers the high thermal sensitivity area of ​​the transformer, ensuring the real-time capture of temperature changes in different parts. The application of the temperature compensation unit further reduces the impact of ambient temperature changes on measurement accuracy. Since the system can monitor and automatically calibrate the temperature sensor in real time, the user can track the temperature changes of the transformer in real time, ensuring the safe operation of the transformer under various working conditions, and greatly improving the reliability of equipment operation.

[0064] The present invention realizes accurate diagnosis of transformer faults by integrating GRU neural network and fuzzy logic algorithm. GRU neural network is good at processing time series data, can analyze long-term temperature change patterns, and identify potential fault signs in the data. Combined with fuzzy logic algorithm, the system can deal with complex nonlinear problems, accurately classify and judge different temperature states, and thus accurately identify the type of fault. Through this advanced diagnostic method, the system can not only detect potential faults, but also provide detailed fault location and severity judgment to help maintenance personnel quickly locate the problem. This high-precision fault diagnosis capability greatly reduces the probability of false alarms and improves the efficiency and accuracy of fault handling.

[0065] The present invention designs a dual-channel redundant communication mechanism and uses the DM9000AEP chip to support 4G / 5G network communication. Through the combination of the main channel and the backup channel, the system can ensure stable data transmission in various complex environments. Even if the main channel fails, the backup channel can be automatically enabled to ensure uninterrupted data transmission. In addition, the system has data compression and AES encryption functions, which ensures data security while improving data transmission efficiency and prevents data from being intercepted or tampered with during transmission. This design ensures data transmission speed and stability in high-load power systems, greatly enhancing the reliability of the system and the confidentiality of data.

[0066] The remote monitoring module of this device provides a Web-based visualization platform that supports cross-platform operations, allowing users to monitor the operating status of the transformer in real time through PCs, tablets or mobile terminals. The platform provides a variety of data display methods, including real-time temperature curves, fault location diagrams and historical data backtracking functions, to help operators quickly understand the operating status and historical performance of the equipment. Users can also use the platform to remotely adjust the temperature alarm threshold, start or shut down the cooling system, etc., to achieve remote operation of the transformer. The multi-level alarm function ensures that when an abnormal situation occurs, relevant personnel can receive alarm information in a timely manner through multiple channels (such as text messages, emails, etc.). The convenience of this remote monitoring and operation not only improves the efficiency of equipment management, but also greatly enhances the safety of transformer operation.

[0067] The present invention realizes seamless connection between the temperature monitoring system and the existing power system monitoring platform through the system integration module. The system supports multiple protocol interfaces, such as Modbus, DNP3 and IEC 61850, ensuring compatibility and data sharing capabilities with other monitoring systems. This high integration enables the device to be easily integrated into the existing power system, which not only reduces additional hardware investment, but also realizes linkage and unified management between different systems. In addition, the modular design of the device makes it highly adaptable, and can be flexibly configured and expanded according to different application scenarios to meet the personalized needs of different users. This integration and adaptability not only reduces the deployment cost of the system, but also greatly improves the expansion capability and practicality of the equipment.

[0068] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. The intelligent transformer temperature monitoring device based on monitoring technology is characterized by: It includes temperature sensing module, data processing module, fault diagnosis module, data transmission module and remote monitoring module; The temperature sensing module is used to collect the temperature information of each key part of the transformer in real time. The temperature sensing module includes multiple fiber grating sensors, which are distributed in the oil tank, winding, iron core and various connection parts of the transformer; A data processing module is connected to the temperature sensing module for receiving and processing the collected temperature information. The data processing module further includes a data filtering unit for eliminating noise signals in the temperature data and extracting high-frequency and low-frequency components of the temperature signal through wavelet packet decomposition technology to identify subtle temperature fluctuations. The fault diagnosis module performs anomaly detection based on the received data and accurately determines the potential fault type by integrating the GRU neural network model and fuzzy logic algorithm, combined with the transformer's historical operation data and real-time temperature data; Data transmission module, including wireless communication unit and redundant communication mechanism, used to transmit processed temperature data and diagnostic results to the remote monitoring center through wireless network or wired network. The wireless communication unit adopts DM9000AEP chip design and supports remote data transmission of 4G / 5G network; The remote monitoring module includes a visualization platform based on a Web interface and a local monitoring terminal. The visualization platform displays the real-time temperature status, historical temperature curve, fault diagnosis results and alarm information of the transformer, and provides remote control functions.

2. The intelligent transformer temperature monitoring device based on monitoring technology according to claim 1 is characterized in that: The fiber grating sensor of the temperature sensing module further includes a temperature compensation unit to reduce the influence of ambient temperature changes on the sensor measurement accuracy.

3. The intelligent transformer temperature monitoring device based on monitoring technology according to claim 1 is characterized in that: The data processing module further includes a temperature trend analysis unit, which predicts the temperature trend of the transformer by comparing historical data with real-time data, gives early warning information, and can automatically adjust the temperature threshold.

4. The intelligent transformer temperature monitoring device based on monitoring technology according to claim 1 is characterized in that: The fault diagnosis module optimizes the hyperparameters of the GRU neural network by introducing the GridSearchCV algorithm to ensure that the fault diagnosis model can meet the requirements of high accuracy and high stability under different working conditions.

5. The intelligent transformer temperature monitoring device based on monitoring technology according to claim 1 is characterized in that: The data transmission module has a dual-channel redundant design, including a main channel for conventional data transmission and a backup channel for data transmission in emergency situations, ensuring that critical data can be transmitted to the remote monitoring center in real time under any circumstances.

6. The intelligent transformer temperature monitoring device based on monitoring technology according to claim 1 is characterized in that: The visualization platform of the remote monitoring module further includes a fault location function. By analyzing the temperature changes and diagnostic results of various parts of the transformer, a fault location map is automatically generated, making it easier for maintenance personnel to quickly find the fault location.

7. The intelligent transformer temperature monitoring device based on monitoring technology according to claim 1 is characterized in that: It also includes an abnormal alarm module. When a transformer fault or temperature abnormality is diagnosed, it automatically triggers a multi-level alarm system, including local sound and light alarms and remote SMS and email alarm functions, to ensure that relevant personnel receive alarm information in a timely manner.

8. The intelligent transformer temperature monitoring device based on monitoring technology according to claim 1 is characterized in that: The system integration module is used to seamlessly integrate the temperature monitoring system into the power system monitoring platform, supports multiple protocol interfaces, and realizes data sharing, linkage and unified management.

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