A transformer oil seal intelligent automatic pressure supplementing device and system

Abstract

The application discloses a transformer oil seal intelligent automatic pressure supplement device and system, and relates to the technical field of power equipment monitoring and maintenance.The device comprises a central monitoring platform, at least one field intelligent pressure supplement unit and a communication network connecting the central monitoring platform and each field intelligent pressure supplement unit; the application deploys a local intelligent control module with a built-in adaptive pressure supplement strategy model, realizes dynamic correction of pressure setting value and pressure supplement timing according to multi-dimensional data such as environmental temperature and load current, overcomes the defects of traditional fixed threshold control mode, such as rigidity and inability to adapt to dynamic working conditions of the transformer, makes up for the lack of fine perception and intelligent early warning capability of the prior art, and fundamentally solves the technical problems of isolated operation of each pressure supplement unit, difficulty in realizing global optimization and collaborative management by constructing a 'cloud edge collaboration' architecture, and significantly improves the pressure supplement accuracy, system reliability and operation and maintenance intelligence level.

Description

Technical Field

[0001] This invention relates to the field of power equipment monitoring and maintenance technology, specifically to an intelligent automatic pressure replenishment device and system for transformer oil sealing. Background Technology

[0002] As a core piece of equipment in the power system, the safe and stable operation of transformers is of paramount importance. The transformer oil conservator employs a sealed structure and is filled with a dry insulating gas (such as nitrogen) to isolate the oil from air and prevent oxidation and moisture absorption. Maintaining a stable pressure within this sealed gas space is crucial for ensuring the transformer's internal insulation strength, preventing external moisture intrusion, and preventing the escape of gases during internal faults. Insufficient pressure may lead to seal failure or damage to internal insulation, while excessive pressure poses safety risks. Therefore, a reliable and precise pressure maintenance system is required.

[0003] Currently, the industry mainly uses two methods to maintain the sealing pressure of transformer oil conservator: manual periodic pressure replenishment and automatic pressure replenishment based on simple threshold control. Manual pressure replenishment relies on inspection personnel using portable gas cylinders for manual operation, making it difficult to guarantee the timeliness and accuracy of pressure replenishment. Existing automatic pressure replenishment devices typically use pressure switches or simple controllers, which monitor the pressure in the gas chamber and initiate gas replenishment when the pressure falls below a certain fixed set value, stopping once the pressure recovers. These systems reduce manual intervention to some extent, but their control logic is relatively simple and rigid.

[0004] However, the aforementioned existing technologies have significant shortcomings. First, the pressure changes in the transformer's sealing gas space are complexly affected by multiple factors, including ambient temperature and oil temperature fluctuations caused by transformer load current. Fixed threshold control cannot dynamically adapt to these changes, potentially leading to inappropriate timing of pressure replenishment (such as excessive frequency or delay), which can affect equipment lifespan and potentially cause safety hazards. Second, existing technologies lack refined perception (such as humidity and purity) and intelligent analysis of the pressure replenishment process and gas quality, making it impossible to effectively identify potential risks such as micro-leakage trends or gas deterioration. Finally, each pressure replenishment unit typically operates in isolation, making centralized data analysis and collaborative optimization impossible. Maintenance personnel cannot grasp the sealing health status of all transformers in the network from a global perspective, and preventive maintenance and dynamic strategy upgrades are also impossible. Summary of the Invention

[0005] Based on this, the purpose of the present invention is to provide an intelligent automatic pressure replenishment device and system for transformer oil sealing, so as to solve the technical problems in the prior art, such as rigid pressure replenishment control strategies, inability to adapt to the dynamic operating conditions of transformers, lack of refined perception and intelligent analysis capabilities, isolated operation of each pressure replenishment unit, difficulty in achieving global optimization and collaborative management, resulting in inaccurate pressure replenishment, delayed discovery of potential risks, and low operation and maintenance efficiency.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a transformer oil sealing intelligent automatic pressure replenishment system, comprising: a central monitoring platform, at least one field intelligent pressure replenishment unit, and a communication network connecting the central monitoring platform and each field intelligent pressure replenishment unit; the field intelligent pressure replenishment unit, deployed near the corresponding transformer body, comprises: a pressure replenishment execution module, which is connected to the sealing gas space of the transformer oil conservator through a pipeline, for replenishing the sealing gas space with dry insulating gas; a multi-dimensional sensing module, for real-time acquisition of field data related to pressure replenishment, the field data including at least the pressure data of the sealing gas space, ambient temperature, transformer load current, and the working status data of the pressure replenishment execution module; a local intelligent control module, whose signal input terminal is connected to the multi-dimensional sensing module and whose control output terminal is connected to the pressure replenishment execution module; the local intelligent control module has a built-in adaptive pressure replenishment strategy model, which is configured to: receive the field data sent by the multi-dimensional sensing module, and based on the pressure data, ambient temperature, and transformer load current, dynamically calculate the pressure setpoint and pressure replenishment timing through a built-in algorithm, and generate control commands to drive the pressure replenishment execution module to operate; The present invention is further configured such that the central monitoring platform includes: a system management module for registering, configuring, and monitoring the status of each field intelligent pressure replenishment unit; a data analysis and strategy optimization module for receiving historical and real-time data uploaded by all field intelligent pressure replenishment units through a communication network, and for globally optimizing the adaptive pressure replenishment strategy model through a machine learning algorithm to generate strategy update instructions; and a remote interaction module for providing users with a visual interface and alarm information, and for receiving advanced instructions from users; wherein the local intelligent control module and the central monitoring platform interact bidirectionally through the communication network, and the local intelligent control module is able to receive and execute strategy update instructions from the data analysis and strategy optimization module, while uploading local data and events to the central monitoring platform.

[0007] The present invention is further configured such that the algorithm of the adaptive pressure compensation strategy model considers the following factors: dynamically correcting the pressure-temperature balance baseline of the sealing gas space based on the conversion relationship between ambient temperature and transformer load current on transformer oil temperature rise; and predicting the micro-leakage trend of the sealing system based on historical pressure compensation frequency and pressure compensation amount.

[0008] The present invention is further configured such that the pressure replenishment execution module includes: a gas storage unit for storing dry insulating gas; and a precision pressure regulation and flow control unit, the gas inlet of which is connected to the gas storage unit and the gas outlet of which is connected to the transformer oil tank through the pipeline; the precision pressure regulation and flow control unit can realize stepless precise adjustment of the replenishment pressure and programmed control of the replenishment flow rate under the control of the local intelligent control module.

[0009] The present invention is further configured such that the multi-dimensional sensing module also includes a gas humidity sensor and / or a gas purity sensor, which are installed on the gas outlet pipe of the pressure compensation execution module or on the sampling point of the sealed gas space of the transformer oil tank; the local intelligent control module or the data analysis and strategy optimization module of the central monitoring platform is configured to trigger a quality alarm and record the event when the gas humidity or purity is detected to exceed a preset threshold.

[0010] The present invention is further configured such that the system also includes an edge coordination gateway; multiple field intelligent pressure replenishment units in the same substation or physical area are locally networked through the edge coordination gateway, and the edge coordination gateway is configured to: coordinate the pressure replenishment actions of each unit in the area according to preset rules when the communication network is interrupted, so as to avoid simultaneous start-up and sudden drop in gas source pressure; and synchronize the cached data to the central monitoring platform after the network is restored.

[0011] The present invention is further configured such that the global optimization function of the data analysis and strategy optimization module includes: aggregating and analyzing the sealing pressure changes, pressure replenishment records and environmental operating condition data of multiple transformers, and establishing a system-level leakage correlation model for early detection of potential systemic sealing risks or abnormal modes.

[0012] The present invention is further configured such that the communication network adopts wired industrial Ethernet and / or wireless private network, and supports at least one of the communication protocols MODBUS TCP and MQTT; the local intelligent control module has the functions of resuming transmission after network interruption and local autonomy, that is, during the network interruption, it works independently according to the latest effective strategy and local data, and retransmits data after the network is restored.

[0013] The present invention is further configured such that the components of the on-site intelligent pressure compensation unit include: a control unit, comprising the local intelligent control module; a sensing interface unit, for accessing sensor signals from the multi-dimensional sensing module; a drive unit, for driving electrical components in the pressure compensation execution module; a communication unit, for accessing the communication network; and a human-machine interaction unit, for local status display and parameter setting; wherein the control unit is electrically connected to the sensing interface unit, the drive unit, the communication unit, and the human-machine interaction unit respectively.

[0014] In summary, the present invention has the following main beneficial effects: This invention, by deploying a local intelligent control module with a built-in adaptive pressure compensation strategy model, achieves dynamic correction of pressure setpoints and pressure compensation timing based on multi-dimensional data such as ambient temperature and transformer load current. This overcomes the shortcomings of traditional fixed threshold control methods, which are rigid and unable to adapt to the dynamic operating conditions of transformers. By integrating sensors such as gas humidity / purity and establishing a two-level data analysis mechanism at both the local and platform levels, it achieves deep perception of sealing status and gas quality, as well as prediction of micro-leakage trends, making up for the lack of refined perception and intelligent early warning capabilities in existing technologies. By constructing a "cloud-edge collaboration" architecture, the central monitoring platform can aggregate and analyze data across the entire domain based on machine learning algorithms, optimize models, and remotely distribute strategies. At the same time, the edge units have the ability to be autonomous when offline and to collaborate locally. This fundamentally solves the technical problem of isolated operation of each pressure compensation unit and difficulty in achieving global optimization and collaborative management, significantly improving the accuracy of pressure compensation, system reliability, and the level of intelligent operation and maintenance. Attached Figure Description

[0015] Figure 1 This is a system architecture diagram of the present invention; Figure 2 This is a system workflow diagram of the present invention; Figure 3 This is a component diagram of the on-site intelligent pressure replenishment device of the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings, so that those skilled in the art can implement the present invention. It should be understood that the specific embodiments described herein are only for explaining the present invention and are not intended to limit the scope of protection of the present invention.

[0017] Example 1: An intelligent automatic pressure compensation system for transformer oil sealing like Figures 1-3 As shown, this embodiment provides an intelligent automatic pressure replenishment system for transformer oil seals. This system adopts a cloud-edge-device collaborative architecture to achieve intelligent, adaptive maintenance and management of the transformer oil conservator sealing pressure. The system mainly includes: a central monitoring platform, at least one field intelligent pressure replenishment unit, and a communication network connecting the central monitoring platform and each field intelligent pressure replenishment unit.

[0018] 1. On-site intelligent pressure compensation unit The on-site intelligent pressure replenishment unit is deployed near the corresponding transformer body, with each unit responsible for the oil conservator seal pressure replenishment task of one transformer. It mainly consists of the following modules: Pressure replenishment execution module: This module is connected to the sealed gas space (usually a nitrogen bladder or gas chamber) of the transformer oil conservator via a pipeline, and is used to replenish the sealed gas space with dry insulating gas (such as high-purity nitrogen). Specifically, the pressure replenishment execution module includes: Gas storage unit: typically one or more high-pressure gas cylinders or storage tanks, used to store dry insulating gas as a pressurization source.

[0019] Precision pressure regulation and flow control unit: Its inlet is connected to the gas storage unit via a high-pressure hose, and its outlet is connected to the transformer oil tank via the same pipeline. This unit integrates a precision proportional valve or servo valve, a flow meter, and a pressure regulator. Driven by a control signal, it can achieve stepless precise adjustment of the replenishment pressure and programmed control of the replenishment flow rate, ensuring a smooth and accurate replenishment process and avoiding pressure surges.

[0020] Multi-dimensional sensing module: Used for real-time acquisition of comprehensive field data related to pressure replenishment. It includes at least: Pressure sensor: directly or indirectly measures the real-time pressure value of the sealed gas space of the transformer oil conservator, which serves as the core control parameter.

[0021] Temperature sensor: Collects real-time ambient temperature data of the transformer installation environment.

[0022] Current transformer or interface: Used to acquire real-time load current data of the transformer. This data can be obtained directly through the associated monitoring device or connected to the substation monitoring system.

[0023] Operating status sensor: monitors the operating status of the pressure replenishment execution module, such as valve opening and closing status, air source pressure, and cumulative air replenishment volume.

[0024] Furthermore, the multi-dimensional sensing module may also include a gas humidity sensor and / or a gas purity sensor. These sensors can be installed on the outlet pipeline of the pressure replenishment execution module to monitor the quality of the gas to be replenished; or they can be installed at the sampling point in the sealed gas space of the transformer oil conservator to sample and monitor the existing gas in the gas chamber.

[0025] Local intelligent control module: This module is the "brain" of the field unit. Its signal input terminal is connected to the sensors of the multi-dimensional sensing module, and its control output terminal is connected to the drive component of the pressure compensation execution module (especially the precision pressure regulation and flow control unit).

[0026] The local intelligent control module has a built-in adaptive pressure compensation strategy model. This model is configured to receive real-time field data (including pressure, ambient temperature, transformer load current, etc.) from the multi-dimensional sensing module, and based on this data, dynamically calculate the most suitable pressure setpoint and the optimal timing for pressure compensation initiation and termination under the current operating conditions using a built-in core algorithm. The calculation process considers the following factors: Based on the combined effects of ambient temperature and transformer load current (which can be converted into the effect of oil temperature rise) on the volume change of transformer oil, the "pressure-temperature" balance baseline of the sealed gas space is dynamically corrected, rather than using a fixed pressure threshold.

[0027] Based on historical pressure replenishment records (such as pressure replenishment frequency and single pressure replenishment amount), combined with pressure change trends, a trend analysis algorithm is used to predict whether there is micro-leakage in the sealing system and its development trend.

[0028] Based on the above calculations and judgments, the adaptive pressure compensation strategy model generates precise control commands (such as switching signals and analog adjustment signals) to drive the pressure compensation execution module to perform intelligent pressure compensation.

[0029] 2. Communication Network The communication network is responsible for data interaction between the central monitoring platform and all field intelligent pressure compensation units. It can employ reliable communication methods such as wired industrial Ethernet and / or wireless private networks (e.g., 4G / 5G private networks, LoRa). The network protocol supports at least one of MODBUS TCP and MQTT to adapt to the communication protocol requirements of different substations. The local intelligent control module has the functions of network interruption resumption and local autonomy: that is, during network interruption, it independently makes judgments and controls based on the latest effective strategy model stored locally and real-time collected local data to maintain the normal operation of the device; at the same time, it caches all locally generated data and event logs, and automatically re-transmits them to the central monitoring platform after the network is restored.

[0030] 3. Central monitoring platform The central monitoring platform is deployed in a remote monitoring center or cloud server to achieve global management, analysis, and optimization. It includes: System Management Module: Provides lifecycle management functions for all field intelligent pressure compensation units across the network, including unit registration, remote parameter configuration (such as initial strategy, alarm threshold), real-time status monitoring (online / offline, health status), and remote software upgrades.

[0031] Data Analysis and Strategy Optimization Module: This is the core intelligent module of the platform. It continuously receives historical and real-time operational data uploaded by all on-site intelligent pressure replenishment units via the communication network. Using machine learning algorithms (such as regression analysis, time series forecasting, and cluster analysis), it aggregates, mines, and deeply analyzes this massive amount of data to achieve the following global optimization functions: Model optimization: Analyze the optimal voltage compensation mode of transformers of different regions and models under different operating conditions, discover the shortcomings or general optimization rules in the existing adaptive voltage compensation strategy model, and generate more accurate and efficient strategy update instructions (such as updating algorithm parameters and correcting the calculation model).

[0032] System-level risk insight: By aggregating and analyzing the sealing pressure variation curves, pressure replenishment records, and environmental operating condition data of multiple transformers, a system-level leakage correlation model is established. By comparing the behavioral differences of different transformers under similar operating conditions, or discovering abnormal pressure variation patterns across equipment, it can be used to detect potential systemic sealing risks (such as defects in a batch of seals) or abnormal patterns at an early stage.

[0033] Remote Interaction Module: Provides maintenance personnel with a visual human-machine interface based on web or client software. The interface can display a network-wide transformer sealing pressure distribution map, real-time curves, alarm lists, statistical analysis reports, etc. It also receives advanced commands from users, such as manual forced pressure replenishment, manual intervention in strategy models, and generation of specific analysis reports.

[0034] 4. System Collaboration Workflow The local intelligent control module and the central monitoring platform interact bidirectionally via the communication network. In addition to performing local intelligent control, the local intelligent control module periodically or in real-time uploads collected field data, pressure compensation event records, and self-diagnostic information to the central monitoring platform. Simultaneously, it can receive and execute strategy update commands from the data analysis and strategy optimization module, dynamically updating the local adaptive pressure compensation strategy model to achieve continuous iterative optimization of the control strategy.

[0035] Example 2: System including edge collaboration gateway Based on Example 1, in order to further improve the system's reliability and regional collaboration capabilities in complex network environments, the system also includes an edge collaboration gateway.

[0036] Multiple field intelligent pressure replenishment units located in the same substation or the same physical area are first connected to a local edge collaboration gateway via a local area network (such as RS485, CAN, or industrial Ethernet) to form a local subnet.

[0037] The edge collaboration gateway is then connected to the central monitoring platform via a communication network (such as an uplink wide area network).

[0038] The edge collaboration gateway is configured with the following intelligent collaboration functions: Local Coordinated Scheduling: When the uplink communication network is interrupted and contact with the central monitoring platform is lost, the edge coordinated gateway coordinates the pressure replenishment actions of each field intelligent pressure replenishment unit within its jurisdiction according to preset coordination rules (such as polling, priority scheduling, and scheduling based on shared gas source pressure feedback). For example, it avoids the instantaneous pressure drop or impact on the public gas source or power grid load caused by multiple units starting pressure replenishment simultaneously, thus achieving orderly pressure replenishment within the region.

[0039] Data caching and synchronization: During network outages, the edge collaborative gateway caches data reported by each field unit. Once the network is restored, the cached data is automatically and completely synchronized to the central monitoring platform, ensuring data continuity.

[0040] Regional edge computing: Edge collaborative gateways can also have certain data aggregation and simple analysis capabilities, perform preliminary data processing and alarm judgment locally, reduce platform pressure and speed up local response.

[0041] Example 3: An intelligent automatic pressure compensation device for transformer oil sealing like Figure 3 As shown, this embodiment provides a physical device for implementing the aforementioned system functions. This device, as the core hardware carrier of the field intelligent pressure compensation unit, adopts an integrated design and is installed in a protection box near the transformer. The device includes the following units integrated within the same chassis: Control Unit: Its core is the local intelligent control module, which is usually composed of a high-performance microprocessor or industrial PLC. It is responsible for running the adaptive pressure compensation strategy model and executing the core control logic.

[0042] Sensing interface unit: Provides multiple standardized sensor interfaces (such as analog input AI, digital input DI, RS485, etc.) for reliably accessing various sensor signals (pressure, temperature, current, humidity, purity, status signals, etc.) of the multidimensional sensing module, and performing signal conditioning and analog-to-digital conversion.

[0043] Drive unit: includes relay output, solid-state switch or analog output module, used to drive the electrical components (such as solenoid valve, electric regulating valve, pump, etc.) in the pressure compensation execution module to operate according to the instructions of the control unit.

[0044] Communication unit: integrates wired Ethernet port, wireless communication module (such as 4G / 5G module), etc., for accessing the communication network and realizing data communication with the central monitoring platform or edge collaborative gateway.

[0045] Human-machine interface unit: Typically includes an LCD screen and buttons or a touch screen, mounted on the chassis panel. It is used for local status display (such as current pressure, mode, alarm information), viewing and setting operating parameters (under authorized conditions), manual operation control, etc., facilitating on-site commissioning and inspection.

[0046] The aforementioned units are electrically connected inside the chassis via a backplane bus or internal cables, and are coordinated by the control unit to form a compact and fully functional field intelligent pressure compensation device.

[0047] Implementation of gas quality monitoring: When the multi-dimensional sensing module includes a gas humidity sensor and / or a gas purity sensor, the local intelligent control module or the data analysis and strategy optimization module of the central monitoring platform is configured to: monitor sensor data in real time; and immediately trigger a gas quality alarm when gas humidity or purity exceeds a preset safety threshold (e.g., excessively high dew point temperature or excessive oxygen content). The alarm information is displayed through the local human-machine interface unit and uploaded to the remote interaction module of the central monitoring platform via the communication network, generating audible and visual alarms and event logs to prompt maintenance personnel to check the gas source quality or the integrity of the sealing system.

[0048] This invention details a complete technical solution for an intelligent automatic pressure replenishment device and system for transformer oil seals. This solution deploys an intelligent field unit integrating multi-dimensional sensing modules and an adaptive pressure replenishment strategy model to achieve dynamic pressure control and precise pressure replenishment based on multi-source data such as ambient temperature and transformer load current. It constructs a cloud-edge collaborative architecture centered on a central monitoring platform, relying on machine learning algorithms to aggregate and analyze data across the entire domain, continuously optimizing the pressure replenishment strategy and achieving system-level risk warning. Simultaneously, it employs a communication mechanism with local autonomy and network outage recovery capabilities, and can optionally be equipped with an edge collaborative gateway to achieve orderly collaboration and data synchronization of regional devices. The entire device adopts an integrated design, ensuring stability and reliability. This invention effectively solves the problems of rigid strategies, insufficient sensing, and isolated operation in traditional pressure replenishment methods, achieving intelligent, adaptive, and globally optimized transformer seal pressure management.

[0049] Although embodiments of the present invention have been shown and described, these specific embodiments are merely explanations of the invention and are not intended to limit it. The specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. After reading this specification, those skilled in the art may make modifications, substitutions, and variations to the embodiments as needed without departing from the principles and spirit of the invention, but such modifications, substitutions, and variations are protected by patent law as long as they are within the scope of the claims of the present invention.

Claims

1. A transformer oil sealing intelligent automatic pressure compensation system, characterized in that, include: A central monitoring platform, at least one field intelligent pressure compensation unit, and a communication network connecting the central monitoring platform and each of the field intelligent pressure compensation units; The on-site intelligent pressure compensation unit is deployed near the corresponding transformer body and includes: The pressure replenishment module is connected to the sealed gas space of the transformer oil tank through a pipeline, and is used to replenish the sealed gas space with dry insulating gas; A multi-dimensional sensing module is used to collect real-time field data related to pressure replenishment. The field data includes at least the pressure data of the sealed gas space, the ambient temperature, the transformer load current, and the working status data of the pressure replenishment execution module. The local intelligent control module has its signal input terminal connected to the multi-dimensional sensing module and its control output terminal connected to the pressure compensation execution module. The local intelligent control module has a built-in adaptive pressure compensation strategy model, which is configured to receive field data sent by the multi-dimensional sensing module and, based on the pressure data, ambient temperature, and transformer load current, dynamically calculate the pressure setpoint and pressure compensation timing through a built-in algorithm, and generate control commands to drive the pressure compensation execution module to act. The central monitoring platform includes: The system management module is used to register, configure, and monitor the status of each field intelligent pressure compensation unit; The data analysis and strategy optimization module receives historical and real-time data uploaded by all on-site intelligent pressure replenishment units through the communication network, performs global optimization of the adaptive pressure replenishment strategy model through machine learning algorithms, and generates strategy update instructions. The remote interaction module is used to provide users with a visual interface and alarm information, and to receive advanced commands from users; The local intelligent control module and the central monitoring platform interact bidirectionally through the communication network. The local intelligent control module can receive and execute policy update instructions from the data analysis and policy optimization module, and simultaneously upload local data and events to the central monitoring platform. The algorithm of the adaptive pressure compensation strategy model considers the following factors: dynamically correcting the pressure-temperature balance baseline of the sealing gas space based on the conversion relationship between ambient temperature and transformer load current on transformer oil temperature rise; and predicting the micro-leakage trend of the sealing system based on historical pressure compensation frequency and pressure compensation amount. The system also includes an edge coordination gateway; multiple field intelligent pressure replenishment units in the same substation or physical area are locally networked through the edge coordination gateway. The edge coordination gateway is configured to: coordinate the pressure replenishment actions of each unit in the area according to preset rules when the communication network is interrupted, so as to avoid simultaneous start-up and sudden drop in gas source pressure; and synchronize the cached data to the central monitoring platform after the network is restored.

2. The intelligent automatic pressure compensation system for transformer oil sealing according to claim 1, characterized in that, The pressure compensation execution module includes: Gas storage unit for storing dry insulating gas; The precision pressure regulation and flow control unit has its inlet connected to the gas storage unit and its outlet connected to the transformer oil tank via the pipeline. Under the control of the local intelligent control module, the precision pressure regulation and flow control unit can achieve stepless precise adjustment of the replenishment pressure and programmed control of the replenishment flow rate.

3. The intelligent automatic pressure compensation system for transformer oil sealing according to claim 2, characterized in that, The multi-dimensional sensing module also includes a gas humidity sensor and / or a gas purity sensor, which are installed on the gas outlet pipe of the pressure compensation execution module or at the sampling point of the sealed gas space of the transformer oil tank; the local intelligent control module or the data analysis and strategy optimization module of the central monitoring platform is configured to trigger a quality alarm and record the event when the gas humidity or purity exceeds the preset threshold.

4. The intelligent automatic pressure compensation system for transformer oil sealing according to claim 1, characterized in that, The global optimization function of the data analysis and strategy optimization module includes: aggregating and analyzing the sealing pressure changes, pressure replenishment records and environmental operating condition data of multiple transformers, and establishing a system-level leakage correlation model to detect potential systemic sealing risks or abnormal patterns at an early stage.

5. The intelligent automatic pressure compensation system for transformer oil sealing according to claim 1, characterized in that, The communication network adopts wired industrial Ethernet and / or wireless private network, and supports at least one of the communication protocols MODBUS TCP and MQTT; the local intelligent control module has the functions of resuming transmission after network interruption and local autonomy, that is, during the network interruption, it works independently according to the latest effective strategy and local data, and retransmits data after the network is restored.

6. A transformer oil sealing intelligent automatic pressure replenishing device for use in the system according to any one of claims 1-5, characterized in that, As a component of the aforementioned on-site intelligent pressure compensation unit, it includes components integrated within the same chassis: The control unit includes the local intelligent control module; A sensing interface unit is used to receive sensor signals from the multi-dimensional sensing module; A drive unit is used to drive the electrical components in the pressure compensation execution module; A communication unit for accessing the communication network; The human-computer interaction unit is used for local status display and parameter setting. The control unit is electrically connected to the sensing interface unit, the driving unit, the communication unit, and the human-computer interaction unit, respectively.

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