An oil level detection system for liquid-immersed transformers

Abstract

The present invention relates to the technical field of transformer oil level detection technology, and discloses an oil level detection system for liquid-immersed transformers. The system comprises: a detection module disposed within the transformer oil chamber, the detection module being configured to obtain temperature data, oil level data, and vibration data from the transformer oil chamber; a central control module electrically connected to the detection module, the central control module being configured to correct the oil level data based on the temperature data and vibration data; and an early warning module electrically connected to the central control module, the early warning module being configured to determine whether to send an early warning message based on the corrected oil level data. The present invention can intelligently correct and determine risk of oil level information based on multi-source sensing data, significantly improving the accuracy of transformer oil level monitoring and the reliability of early warning responses.

Description

Technical Field

[0001] The present invention relates to the technical field of transformer oil level detection, and in particular to an oil level detection system for a liquid-immersed transformer. Background Art

[0002] Liquid-immersed transformers are widely used in power systems. The oil within them not only provides excellent insulation but also serves as a heat dissipator and cooler. To ensure safe and stable operation of the transformer, real-time oil level monitoring is often required through an oil level detection system. Existing technologies typically use float-type, capacitive, or magnetostrictive oil level sensors to collect oil level data, which is then uploaded to a monitoring platform for operational status assessment.

[0003] However, during actual operation, the oil level inside a transformer is affected by a variety of factors. Temperature fluctuations, in particular, can cause the oil to expand or contract, and vibration and shock can cause sensor readings to fluctuate. Failure to fully account for these external disturbances can easily lead to deviations in oil level data, potentially causing false alarms and missed alerts, impacting the accuracy of equipment warnings and the reliability of operational decisions. Furthermore, most traditional oil level detection systems lack the ability to integrate and process multi-source data, making it difficult to dynamically correct and comprehensively assess oil level data.

[0004] In view of this, it is necessary to propose an oil level detection system that can integrate temperature and vibration factors, dynamically correct oil level data and have intelligent early warning function, so as to improve the accuracy of transformer operation status monitoring and the reliability of system response. Summary of the Invention

[0005] In view of this, the present invention proposes an oil level detection system for liquid-immersed transformers, aiming to solve the problems of inaccurate oil level data, high early warning misjudgment rate, and lack of multi-source data fusion and dynamic correction capabilities in existing oil level detection systems in current technology under temperature changes and vibration interference.

[0006] The present invention proposes an oil level detection system for a liquid-immersed transformer, comprising:

[0007] A detection module is disposed inside the transformer oil cavity, and is configured to obtain temperature data, oil level data, and vibration data inside the transformer oil cavity;

[0008] a central control module, electrically connected to the detection module, and configured to correct the oil level data according to the temperature data and the vibration data;

[0009] The early warning module is electrically connected to the central control module, and the early warning module is configured to determine whether to send an early warning message based on the corrected oil level data.

[0010] Furthermore, the detection module includes:

[0011] A capacitive oil level sensor is disposed inside the oil cavity of the transformer, and the capacitive oil level sensor is configured to obtain oil level data inside the oil cavity of the transformer;

[0012] A plurality of temperature sensors are provided, and the plurality of temperature sensors are arranged side by side in a vertical direction of the transformer inside the transformer oil cavity based on a preset distance, and the temperature sensors are configured to obtain temperature data of the oil;

[0013] The vibration sensor is arranged on the inner wall of the transformer oil cavity and is configured to obtain vibration data of the transformer box.

[0014] Furthermore, the central control module includes:

[0015] an acquisition unit, electrically connected to each sensor, configured to acquire real-time oil level data inside the transformer oil cavity and, based on a relationship between the real-time oil level data and historical oil level data from adjacent time periods, determine whether to control the capacitive oil level sensor to perform secondary collection of the oil level data inside the transformer oil cavity; the acquisition unit is further configured to acquire oil temperature data detected by each temperature sensor and determine total temperature data inside the transformer oil cavity based on the sum of the number of temperature sensors and the distances between the temperature sensors; and the acquisition unit is further configured to acquire real-time vibration data of the transformer;

[0016] an analyzing unit electrically connected to the acquiring unit, the analyzing unit being configured to adjust the oil level data inside the transformer oil cavity according to the total temperature data, and to correct the adjusted oil level data according to the real-time vibration data;

[0017] The evaluation unit is electrically connected to the analysis unit, and is configured to determine a warning score inside the transformer oil cavity according to a relationship between the corrected oil level data and preset oil level data configured by the evaluation unit.

[0018] Furthermore, the acquisition unit determines whether to control the capacitive oil level sensor to perform secondary collection of oil level data inside the transformer oil cavity based on the relationship between the real-time oil level data and the historical oil level data of adjacent time periods, including:

[0019] The acquisition unit is further configured to acquire an oil level difference between the real-time oil level data and the historical oil level data of adjacent time periods;

[0020] The acquisition unit is further configured to determine whether to control the capacitive oil level sensor to perform secondary collection of oil level data inside the transformer oil cavity based on a relationship between the oil level difference and a preset oil level difference pre-configured by the acquisition unit:

[0021] When the oil level difference is lower than or equal to the preset oil level difference, the acquisition unit determines not to control the capacitive oil level sensor to perform secondary collection of oil level data inside the transformer oil cavity;

[0022] When the oil level difference is higher than the preset oil level difference, the acquisition unit determines to control the capacitive oil level sensor to perform secondary collection of oil level data inside the transformer oil cavity.

[0023] Furthermore, obtaining the preset oil level difference value pre-configured by the unit includes:

[0024] The acquisition unit is further configured to acquire each historical oil level data within a preset historical period, and acquire the oil level difference between each adjacent historical oil level data and the time interval of the oil level difference;

[0025] The acquisition unit establishes a correlation equation according to the oil level difference and time detection, and obtains a distance metric between each correlation equation based on the Euclidean distance;

[0026] The acquisition unit establishes a distance matrix according to each distance metric, and clusters each correlation expression based on the distance matrix;

[0027] The acquiring unit is further configured to determine a preset oil level difference value according to the clustering result.

[0028] Furthermore, when the analysis unit adjusts the oil level data inside the transformer oil cavity according to the total temperature data, it includes:

[0029] The analyzing unit is further configured to: determine the average temperature value between each temperature data in the total temperature data;

[0030] The analysis unit is further configured to perform clustering based on the relationship between each temperature data and the temperature mean, obtain clustering results, and determine the top temperature and base temperature of the oil chamber;

[0031] The analysis unit is further configured to determine an adjustment coefficient according to a temperature difference between the top temperature of the oil cavity and the base temperature, and adjust the oil level data inside the transformer oil cavity according to the adjustment coefficient.

[0032] Furthermore, the analysis unit determines the adjustment coefficient according to the temperature difference between the top temperature of the oil chamber and the base temperature, including:

[0033] The analysis unit is further configured to determine an adjustment coefficient according to a relationship between the temperature difference and a first preset temperature difference and a second preset temperature difference configured by the analysis unit:

[0034] When the temperature difference is lower than the first preset temperature difference, the analysis unit determines the adjustment coefficient to be L1;

[0035] When the temperature difference is higher than or equal to the first preset temperature difference and lower than the second preset temperature difference, the analysis unit determines the adjustment coefficient to be L2;

[0036] When the temperature difference is higher than or equal to the second preset temperature difference, the analysis unit determines the adjustment coefficient to be L3;

[0037] The first preset temperature difference is smaller than the second preset temperature difference, and 0<L1<L2<L3<0.5.

[0038] Furthermore, when the analysis unit corrects the adjusted oil level data according to the real-time vibration data, it includes:

[0039] The analysis unit is further configured to determine a correction coefficient based on a relationship between the real-time vibration data and the first preset vibration data and the second preset vibration data configured by the analysis unit, and to correct the adjustment coefficient Li according to the correction coefficient, where i=1, 2, 3;

[0040] When the real-time vibration data is less than or equal to the first preset vibration data, the analysis unit determines the correction coefficient as Q1;

[0041] When the real-time vibration data is greater than the first preset vibration data and the real-time vibration data is less than or equal to the second preset vibration data, the analysis unit determines the correction coefficient to be Q2;

[0042] When the real-time vibration data is greater than the second preset vibration data, the analysis unit determines the correction coefficient as Q3;

[0043] The first preset vibration data is smaller than the second preset vibration data, and 0<Q1<Q2<Q3<0.5.

[0044] Furthermore, the evaluation unit determines the early warning score inside the transformer oil cavity based on the relationship between the corrected oil level data and the preset oil level data configured by the evaluation unit, including:

[0045] The evaluation unit is further configured to determine a warning score based on a relationship between the corrected oil level data and the preset oil level data:

[0046] F= ;

[0047] Among them, F is the early warning score, S is the corrected oil level data, sl is the preset oil level data, smax is the second preset oil level data, and sl<smax.

[0048] Furthermore, when the warning module determines whether to send a warning message based on the corrected oil level data, it includes:

[0049] The early warning module is further configured to determine whether to send an early warning message based on the relationship between the early warning score of the evaluation unit and the preset score:

[0050] When the warning score is less than the preset score, the warning module determines not to send a warning message;

[0051] When the warning score is greater than or equal to the preset score, the warning module determines to send a warning message.

[0052] Compared with existing technologies, the present invention offers the following advantages: by providing a detection module, a central control module, and an early warning module, a complete oil-level sensing and early warning system is formed. The detection module, deployed within the transformer's oil chamber, collects key operating parameters, including oil level, temperature, and vibration, in real time. This overcomes the limitations of traditional oil-level detection systems, which only collect a single physical quantity, and provides a data foundation for subsequent data fusion processing. Secondly, the central control module, as the core processing unit, receives data uploaded by the detection module and dynamically corrects the raw oil-level data based on the oil volume expansion caused by temperature changes and the impact of vibration interference on sensor stability. Through a built-in correction model or algorithm, it effectively compensates for oil-level deviations caused by environmental disturbances, significantly improving the stability and reliability of the oil-level data and avoiding false alarms and missed alarms caused by error accumulation. Finally, the early warning module performs real-time evaluation of the corrected oil-level data. When an abnormal oil-level deviation from a set threshold is detected, a warning signal is promptly output, enabling operations and maintenance personnel to quickly respond and take intervention measures. Compared with traditional oil level detection systems that only determine whether to issue an alarm based on raw readings, the present invention improves the intelligence level of early warning on the basis of achieving accurate monitoring and enhances the system's ability to proactively identify potential faults. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0054] Figure 1 This is a functional block diagram of an oil level detection system for a liquid-immersed transformer provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0055] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, unless there is a conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0056] like Figure 1 As shown, in some embodiments of the present application, this embodiment provides an oil level detection system for a liquid-immersed transformer, including: a detection module, a central control module and an early warning module.

[0057] Specifically, the detection module is configured inside the oil cavity of the transformer, and the detection module is configured to obtain temperature data, oil level data and vibration data inside the oil cavity of the transformer.

[0058] Specifically, the detection module includes: a capacitive oil level sensor is configured inside the transformer oil cavity, and the capacitive oil level sensor is configured to obtain oil level data inside the transformer oil cavity; a plurality of temperature sensors are configured, and the plurality of temperature sensors are arranged side by side inside the transformer oil cavity along the vertical direction of the transformer based on a preset distance, and the temperature sensors are configured to obtain oil temperature data; a vibration sensor is configured on the inner wall of the transformer oil cavity, and the vibration sensor is configured to obtain vibration data of the transformer box.

[0059] As can be understood, by placing the detection module inside the transformer's oil chamber, it can directly obtain key environmental parameters during transformer operation, enabling real-time sensing of oil level changes. The detection module integrates a capacitive oil level sensor, multiple temperature sensors, and a vibration sensor, forming a multi-source sensing system that works in tandem. Compared to traditional single-source oil level detection methods, this system offers more comprehensive monitoring capabilities. Specifically, the capacitive oil level sensor senses changes in the relative dielectric constant of the oil within the transformer, accurately reflecting the real-time oil level. This sensor's sensitive response and compact structure make it suitable for long-term, stable operation in a sealed oil chamber. Temperature sensors are distributed vertically along the transformer at predetermined intervals, capturing temperature gradient information at different oil layers and supporting subsequent correction of oil level data based on thermal expansion models. This multi-point layout also improves the spatial resolution of temperature monitoring. Furthermore, a vibration sensor, fixed to the inner wall of the oil chamber, monitors structural vibration data generated during transformer operation. Because vibration can disrupt the instantaneous readings of the oil level sensor, obtaining this information helps establish a vibration compensation mechanism within the central control module, thereby improving the stability and accuracy of oil level measurement. The three sensors work together to provide reliable raw data support for the subsequent multi-factor correction and intelligent early warning of oil level data, and build a high-reliability monitoring system for liquid-immersed transformers.

[0060] Specifically, the central control module is electrically connected to the detection module, and the central control module is configured to correct the oil level data according to the temperature data and the vibration data.

[0061] Specifically, the central control module includes: an acquisition unit electrically connected to each sensor, the acquisition unit is configured to acquire real-time oil level data inside the transformer oil cavity, and determine whether to control the capacitive oil level sensor to perform secondary collection of oil level data inside the transformer oil cavity based on the relationship between the real-time oil level data and the historical oil level data of adjacent time periods. The acquisition unit is also configured to acquire oil temperature data detected by each temperature sensor, and determine the total temperature data inside the transformer oil cavity based on the number of each temperature sensor and the sum of the distances between each temperature sensor. The acquisition unit is also configured to acquire real-time vibration data of the transformer; the analysis unit is electrically connected to the acquisition unit, the analysis unit is configured to adjust the oil level data inside the transformer oil cavity according to the total temperature data, and correct the adjusted oil level data according to the real-time vibration data; the evaluation unit is electrically connected to the analysis unit, and the evaluation unit is configured to determine the early warning score inside the transformer oil cavity based on the relationship between the corrected oil level data and the preset oil level data configured by the evaluation unit.

[0062] As can be understood, the central control module, as the core control and data processing unit, electrically connects to various sensors to collect multiple types of raw data from the transformer oil chamber in real time. This data is then combined with historical data for judgment and correction, enhancing the accuracy and intelligence of oil level monitoring. The central control module integrates an acquisition unit, an analysis unit, and an evaluation unit, which work together to form a closed loop of oil level data processing driven by dynamic feedback and early warning. The acquisition unit collects data from capacitive oil level sensors, temperature sensors, and vibration sensors in real time. It compares current oil level data with oil level trends over adjacent historical periods. Upon identifying abnormal fluctuations or measurement anomalies, it triggers a secondary oil level acquisition mechanism, thereby improving oil level sensing accuracy. Furthermore, the acquisition unit calculates the transformer oil chamber's total temperature index based on the number of sensors deployed and their spacing, integrating temperature data from each point. It also simultaneously collects vibration signals, providing comprehensive input for subsequent multi-factor oil level correction. The analysis unit is responsible for dynamically correcting the oil level data. It first derives the oil level offset caused by thermal expansion or contraction based on the total temperature data, completing a primary adjustment. It then performs a secondary calibration of the initially corrected oil level, incorporating transient disturbances introduced by the vibration data, to further improve the stability and reliability of the oil level data. Finally, the evaluation unit calculates a quantitative early warning score based on the difference between the corrected oil level data and the preset oil level data set in the system. This provides a decision-making basis for the early warning module, enabling early identification of fault risks and intelligent response.

[0063] Specifically, the acquisition unit determines whether to control the capacitive oil level sensor to perform secondary collection of the oil level data inside the oil cavity of the transformer based on the relationship between the real-time oil level data and the historical oil level data of the adjacent time periods, including: the acquisition unit is also configured to obtain the oil level difference between the real-time oil level data and the historical oil level data of the adjacent time periods; the acquisition unit is also configured to determine whether to control the capacitive oil level sensor to perform secondary collection of the oil level data inside the oil cavity of the transformer based on the relationship between the oil level difference and the preset oil level difference pre-configured by the acquisition unit: when the oil level difference is lower than or equal to the preset oil level difference, the acquisition unit determines not to control the capacitive oil level sensor to perform secondary collection of the oil level data inside the oil cavity of the transformer; when the oil level difference is higher than the preset oil level difference, the acquisition unit determines to control the capacitive oil level sensor to perform secondary collection of the oil level data inside the oil cavity of the transformer.

[0064] Specifically, when the preset oil level difference value pre-configured by the acquisition unit is obtained, it includes: the acquisition unit is also configured to obtain each historical oil level data within a historical preset time period, and obtain the oil level difference value between each adjacent historical oil level data and the time interval of the oil level difference value; the acquisition unit establishes an association expression based on the oil level difference value and time detection, and obtains the distance measurement between each association expression based on the Euclidean distance; the acquisition unit establishes a distance matrix based on each distance measurement, and clusters each association expression based on the distance matrix; the acquisition unit is also configured to determine the preset oil level difference value based on the clustering result.

[0065] As can be understood, by real-time monitoring of the variation between current oil level data and oil level data from adjacent historical time periods (i.e., the oil level difference), the system dynamically determines whether abnormal fluctuations exist and decides whether to trigger the capacitive oil level sensor to perform secondary oil level data collection. This eliminates bias caused by occasional disturbances or acquisition errors, thereby improving the timeliness and accuracy of oil level monitoring. Secondly, to scientifically determine the judgment threshold, the acquisition unit, during system initialization or operation, pre-analyzes oil level changes within a preset historical time period. It extracts the oil level differences and corresponding time intervals between adjacent oil level data points and constructs a correlation expression between oil level differences and time changes. This expression reflects the dynamic characteristics of oil level fluctuations under different operating conditions and serves as an important reference for assessing whether the current oil level fluctuation is abnormal. Subsequently, the acquisition unit calculates the Euclidean distance between the correlation expressions for oil level changes from different historical time periods to obtain a similarity measure between the fluctuation patterns and constructs a corresponding distance matrix. Based on this, the system incorporates clustering algorithms (such as K-means and hierarchical clustering) to classify and organize various oil level change trends, thereby identifying typical data patterns representing normal fluctuations. This process helps the system automatically adapt to the natural range of oil level fluctuations under different operating environments and enhances the robustness of identifying abnormal behavior. Ultimately, the acquisition unit uses the representative sample difference in the cluster analysis results as a dynamic reference standard for the preset oil level difference. The preset oil level difference determined in this way has adaptive and data-driven characteristics, and can be closer to the actual operating status of the transformer under specific working conditions. When the real-time oil level difference exceeds the threshold, the system determines that there is an abnormal fluctuation and triggers the secondary collection mechanism to ensure that subsequent analysis and judgment are based on high-confidence data, thereby improving the stability, reliability and intelligent response capabilities of the entire system.

[0066] Specifically, when the analysis unit adjusts the oil level data inside the transformer oil cavity according to the total temperature data, it includes: the analysis unit is also configured to perform clustering based on the temperature mean between each temperature data in the total temperature data; the analysis unit is also configured to perform clustering based on the relationship between each temperature data and the temperature mean, and obtain the clustering results to determine the top temperature and the basic temperature of the oil cavity; the analysis unit is also configured to determine the adjustment coefficient according to the temperature difference between the top temperature and the basic temperature of the oil cavity, and adjust the oil level data inside the transformer oil cavity according to the adjustment coefficient.

[0067] Specifically, when the analysis unit determines the adjustment coefficient based on the temperature difference between the top temperature of the oil chamber and the base temperature, it includes: the analysis unit is also configured to determine the adjustment coefficient based on the relationship between the temperature difference and the first preset temperature difference and the second preset temperature difference configured by the analysis unit: when the temperature difference is lower than the first preset temperature difference, the analysis unit determines the adjustment coefficient to be L1; when the temperature difference is higher than or equal to the first preset temperature difference, and the temperature difference is lower than the second preset temperature difference, the analysis unit determines the adjustment coefficient to be L2; when the temperature difference is higher than or equal to the second preset temperature difference, the analysis unit determines the adjustment coefficient to be L3; wherein, the first preset temperature difference is less than the second preset temperature difference, and 0<L1<L2<L3<0.5.

[0068] Specifically, when the analysis unit corrects the adjusted oil level data according to the real-time vibration data, it includes: the analysis unit is also configured to determine a correction coefficient based on the relationship between the real-time vibration data and the first preset vibration data and the second preset vibration data configured by the analysis unit, and correct the adjustment coefficient Li according to the correction coefficient, where i=1,2,3; when the real-time vibration data is less than or equal to the first preset vibration data, the analysis unit determines the correction coefficient to be Q1; when the real-time vibration data is greater than the first preset vibration data, and the real-time vibration data is less than or equal to the second preset vibration data, the analysis unit determines the correction coefficient to be Q2; when the real-time vibration data is greater than the second preset vibration data, the analysis unit determines the correction coefficient to be Q3; where the first preset vibration data is less than the second preset vibration data, and 0<Q1<Q2<Q3<0.5.

[0069] As can be understood, multiple temperature sensors are arranged vertically along the transformer oil chamber to collect temperature data from the upper and lower layers of the oil. Clustering is performed based on the mean relationship between the temperature data, automatically identifying data representing the top and base oil chamber temperatures. This automatically establishes a mapping relationship between temperature changes and oil level changes. Based on this, the analysis unit calculates the temperature difference between the top and base oil chamber temperatures and introduces a stepwise adjustment coefficient setting mechanism. Based on the relationship between this temperature difference and the first and second preset temperature difference thresholds, different levels of adjustment coefficients, L1, L2, and L3, are assigned, respectively. This design effectively differentiates the degree of volume expansion corresponding to each temperature difference level, ensuring the rationality and physical consistency of the oil level correction. Furthermore, the adjustment coefficients meet the constraints of 0 < L1 < L2 < L3 < 0.5, controlling the adjustment range and avoiding overcompensation. Furthermore, the analysis unit takes into account the measurement disturbance effects caused by mechanical vibration during transformer operation. The current vibration intensity level is determined by collecting vibration data in real time and comparing it with the first and second preset vibration thresholds. Based on this, the system sets different correction coefficients Q1, Q2, and Q3 to fine-tune the adjustment coefficient Li originally derived from the temperature difference, recalibrating the temperature model correction results to offset the transient errors caused by vibration and improve overall correction accuracy. Overall, this technology achieves multi-parameter adaptive correction of oil level data by establishing a three-level dynamic correlation model of "temperature difference-adjustment coefficient-correction coefficient." This ensures that oil level drift caused by temperature gradients can be scientifically modeled and quantified, while also providing targeted compensation for vibration disturbances during actual operation. This creates a high-precision oil level data correction solution based on the fusion of physical mechanisms and environmental perception.

[0070] Specifically, when the evaluation unit determines the early warning score inside the transformer oil cavity based on the relationship between the corrected oil level data and the preset oil level data configured by the evaluation unit, the evaluation unit is further configured to determine the early warning score based on the relationship between the corrected oil level data and the preset oil level data:

[0071] F= ;

[0072] Among them, F is the early warning score, S is the corrected oil level data, sl is the preset oil level data, smax is the second preset oil level data, and sl<smax.

[0073] Specifically, the early warning module is electrically connected to the central control module, and the early warning module is configured to determine whether to send an early warning message based on the corrected oil level data.

[0074] Specifically, when the early warning module determines whether to send an early warning message based on the corrected oil level data, it includes: the early warning module is also configured to determine whether to send an early warning message based on the relationship between the early warning score of the evaluation unit and the preset score: when the early warning score is less than the preset score, the early warning module determines not to send an early warning message; when the early warning score is greater than or equal to the preset score, the early warning module determines to send an early warning message.

[0075] As can be understood, the early warning module, as the system's final decision-making output unit, is electrically connected to the central control module. Its primary function is to intelligently determine whether to trigger an early warning message based on the corrected oil level data analyzed and evaluated by the central control module, combined with predefined criteria. This ensures system safety while avoiding interference caused by false alarms and frequent alerts. In specific implementations, the early warning module uses the early warning score output by the evaluation unit as its primary decision-making basis. This score quantifies the deviation between the corrected oil level data and the preset oil level data, reflecting the risk level between the current oil level and the normal state. The system has a preset score threshold (i.e., the preset score) that serves as the trigger for an early warning response. When the early warning score is less than the preset score threshold, the system deems the current oil level change within a safe range, and the early warning module will not issue any alarm messages to avoid unnecessary intervention. However, when the early warning score is greater than or equal to the preset score, a potential risk is identified, and the early warning module immediately triggers an alarm message, prompting maintenance personnel to pay attention or intervene. This mechanism ensures accurate and timely early warning responses, enhancing the intelligence and practical value of the transformer operating condition monitoring system.

[0076] In the above-described embodiment, a complete oil-level sensing and warning system is formed by configuring a detection module, a central control module, and an early warning module. The detection module, deployed within the transformer's oil chamber, collects key operating parameters, including oil level, temperature, and vibration, in real time. This overcomes the limitation of traditional oil-level detection systems that only collect a single physical quantity and provides a data foundation for subsequent data fusion processing. Secondly, the central control module, as the core processing unit, receives data uploaded by the detection module and dynamically corrects the raw oil-level data based on the oil volume expansion caused by temperature changes and the impact of vibration interference on sensor stability. Through a built-in correction model or algorithm, it effectively compensates for oil-level deviations caused by environmental disturbances, significantly improving the stability and reliability of the oil-level data and avoiding false alarms and missed alarms caused by error accumulation. Finally, the early warning module performs real-time evaluation of the corrected oil-level data. When an abnormal oil-level deviation from a set threshold is detected, a warning signal is promptly issued, enabling operations and maintenance personnel to quickly respond and take intervention measures. Compared with traditional oil level detection systems that only determine whether to issue an alarm based on raw readings, the present invention improves the intelligence level of early warning on the basis of achieving accurate monitoring and enhances the system's ability to proactively identify potential faults.

[0077] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0078] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0079] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0080] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0081] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. An oil level gauge for a liquid-immersed transformer, characterized in that: include: A detection module is disposed inside the transformer oil cavity, and is configured to obtain temperature data, oil level data, and vibration data inside the transformer oil cavity; a central control module, electrically connected to the detection module, and configured to correct the oil level data according to the temperature data and the vibration data; An early warning module is electrically connected to the central control module, and the early warning module is configured to determine whether to send an early warning message based on the corrected oil level data; Among them, the central control module is equipped with an analysis unit, which is configured to determine an adjustment coefficient based on the temperature difference between the top temperature and the base temperature of the oil cavity, and adjust the oil level data inside the transformer oil cavity according to the adjustment coefficient.

2. The oil level gauge for a liquid-immersed transformer according to claim 1, characterized in that: The detection module includes: A capacitive oil level sensor is disposed inside the oil cavity of the transformer, and the capacitive oil level sensor is configured to obtain oil level data inside the oil cavity of the transformer; A plurality of temperature sensors are provided, and the plurality of temperature sensors are arranged side by side in a vertical direction of the transformer inside the transformer oil cavity based on a preset distance, and the temperature sensors are configured to obtain temperature data of the oil; The vibration sensor is arranged on the inner wall of the transformer oil cavity and is configured to obtain vibration data of the transformer box.

3. The oil level gauge for a liquid-immersed transformer according to claim 2, characterized in that: The central control module includes: an acquisition unit, electrically connected to each sensor, configured to acquire real-time oil level data inside the transformer oil cavity and, based on a relationship between the real-time oil level data and historical oil level data from adjacent time periods, determine whether to control the capacitive oil level sensor to perform secondary collection of the oil level data inside the transformer oil cavity; the acquisition unit is further configured to acquire oil temperature data detected by each temperature sensor and determine total temperature data inside the transformer oil cavity based on the sum of the number of temperature sensors and the distances between the temperature sensors; and the acquisition unit is further configured to acquire real-time vibration data of the transformer; an analyzing unit electrically connected to the acquiring unit, the analyzing unit being configured to adjust the oil level data inside the transformer oil cavity according to the total temperature data, and to correct the adjusted oil level data according to the real-time vibration data; The evaluation unit is electrically connected to the analysis unit, and is configured to determine a warning score inside the transformer oil cavity according to a relationship between the corrected oil level data and preset oil level data configured by the evaluation unit.

4. The oil level gauge for a liquid-immersed transformer according to claim 3, characterized in that: The acquisition unit determines whether to control the capacitive oil level sensor to perform secondary collection of oil level data inside the transformer oil cavity based on the relationship between the real-time oil level data and the historical oil level data of adjacent time periods, including: The acquisition unit is further configured to acquire an oil level difference between the real-time oil level data and the historical oil level data of adjacent time periods; The acquisition unit is further configured to determine whether to control the capacitive oil level sensor to perform secondary collection of oil level data inside the transformer oil cavity based on a relationship between the oil level difference and a preset oil level difference pre-configured by the acquisition unit: When the oil level difference is lower than or equal to the preset oil level difference, the acquisition unit determines not to control the capacitive oil level sensor to perform secondary collection of oil level data inside the transformer oil cavity; When the oil level difference is higher than the preset oil level difference, the acquisition unit determines to control the capacitive oil level sensor to perform secondary collection of oil level data inside the transformer oil cavity.

5. The oil level gauge for a liquid-immersed transformer according to claim 4, characterized in that: When obtaining the preset oil level difference value pre-configured by the unit, including: The acquisition unit is further configured to acquire each historical oil level data within a preset historical period, and acquire the oil level difference between each adjacent historical oil level data and the time interval of the oil level difference; The acquisition unit establishes a correlation equation according to the oil level difference and time detection, and obtains a distance metric between each correlation equation based on the Euclidean distance; The acquisition unit establishes a distance matrix according to each distance metric, and clusters each correlation expression based on the distance matrix; The acquiring unit is further configured to determine a preset oil level difference value according to the clustering result.

6. The oil level gauge for a liquid-immersed transformer according to claim 3, characterized in that: When the analysis unit adjusts the oil level data inside the transformer oil cavity according to the total temperature data, it includes: The analyzing unit is further configured to: determine the average temperature value between each temperature data in the total temperature data; The analysis unit is further configured to perform clustering based on the relationship between each temperature data and the temperature mean, obtain clustering results, and determine the top temperature and base temperature of the oil chamber; The analysis unit is further configured to determine an adjustment coefficient according to a temperature difference between the top temperature of the oil cavity and the base temperature, and adjust the oil level data inside the transformer oil cavity according to the adjustment coefficient.

7. The oil level gauge for a liquid-immersed transformer according to claim 6, characterized in that: The analysis unit determines the adjustment coefficient based on the temperature difference between the top temperature of the oil chamber and the base temperature, including: The analysis unit is further configured to determine an adjustment coefficient according to a relationship between the temperature difference and a first preset temperature difference and a second preset temperature difference configured by the analysis unit: When the temperature difference is lower than the first preset temperature difference, the analysis unit determines the adjustment coefficient to be L1; When the temperature difference is higher than or equal to the first preset temperature difference and lower than the second preset temperature difference, the analysis unit determines the adjustment coefficient to be L2; When the temperature difference is higher than or equal to the second preset temperature difference, the analysis unit determines the adjustment coefficient to be L3; The first preset temperature difference is smaller than the second preset temperature difference, and 0<L1<L2<L3<0.

5.

8. The oil level gauge for a liquid-immersed transformer according to claim 7, characterized in that: When the analysis unit corrects the adjusted oil level data based on the real-time vibration data, it includes: The analysis unit is further configured to determine a correction coefficient based on a relationship between the real-time vibration data and the first preset vibration data and the second preset vibration data configured by the analysis unit, and to correct the adjustment coefficient Li according to the correction coefficient, where i=1, 2, 3; When the real-time vibration data is less than or equal to the first preset vibration data, the analysis unit determines the correction coefficient as Q1; When the real-time vibration data is greater than the first preset vibration data and the real-time vibration data is less than or equal to the second preset vibration data, the analysis unit determines the correction coefficient to be Q2; When the real-time vibration data is greater than the second preset vibration data, the analysis unit determines the correction coefficient as Q3; The first preset vibration data is smaller than the second preset vibration data, and 0<Q1<Q2<Q3<0.

5.

9. The oil level gauge for a liquid-immersed transformer according to claim 3, characterized in that: The evaluation unit determines the early warning score inside the transformer oil cavity based on the relationship between the corrected oil level data and the preset oil level data configured by the evaluation unit, including: The evaluation unit is further configured to determine a warning score based on a relationship between the corrected oil level data and the preset oil level data: F= ； Among them, F is the early warning score, S is the corrected oil level data, sl is the preset oil level data, smax is the second preset oil level data, and sl<smax.

10. The oil level gauge for a liquid-immersed transformer according to claim 9, characterized in that: The early warning module determines whether to send an early warning message based on the corrected oil level data, including: The early warning module is further configured to determine whether to send an early warning message based on the relationship between the early warning score of the evaluation unit and the preset score: When the warning score is less than the preset score, the warning module determines not to send a warning message; When the warning score is greater than or equal to the preset score, the warning module determines to send a warning message.

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