Oil level detection system for liquid-immersed transformer

Abstract

The invention relates to the technical field of transformer oil level detection, and discloses an oil level detection system for a liquid-immersed transformer, and the system comprises a detection module which is disposed in an oil cavity of the transformer, and the detection module is configured to obtain temperature data, oil level data and vibration data in the oil cavity of the transformer; the central control module is electrically connected with 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; and the early warning module is electrically connected with the central control module, and the early warning module is configured to determine whether to send early warning information or not according to the corrected oil level data. Intelligent correction and risk judgment can be carried out on the oil level information based on the multi-source sensing data, and the accuracy of transformer oil level monitoring and the reliability of early warning response are remarkably improved.

Description

Technical Field

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

[0002] Oil-immersed transformers are widely used in power systems. The internal oil not only has good insulation performance but also plays a role in heat dissipation and cooling. To ensure the safe and stable operation of the transformer, it is usually necessary to monitor the internal oil level in real time through an oil level detection system. In the prior art, float-type, capacitive, or magnetostrictive oil level sensors are mostly used to collect the oil level data and upload the data to a monitoring platform for operation status evaluation.

[0003] However, during the actual operation process, the internal oil level of the transformer is affected by various factors. In particular, temperature changes can cause the volume of the oil to expand or contract, and vibration shocks may also cause fluctuations in the sensor readings. When these external disturbances are not fully considered, it is easy to cause deviations in the oil level data, which in turn leads to problems such as false alarms and missed alarms, affecting the accuracy of equipment early warning and the reliability of operation decisions. In addition, most traditional oil level detection systems lack the ability to fuse multi-source data and are difficult to achieve dynamic correction and comprehensive judgment of oil level data.

[0004] In view of this, it is necessary to propose an oil level detection system that can fuse temperature and vibration factors, dynamically correct oil level data, and have an intelligent early warning function 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 an oil-immersed transformer, aiming to solve the problems in the current technology that the existing oil level detection system has inaccurate oil level data, a high false alarm rate in early warning, and a lack of multi-source data fusion and dynamic correction ability under temperature changes and vibration interference.

[0006] The present invention proposes an oil level detection system for an oil-immersed transformer, comprising: A detection module, configured inside the transformer oil chamber, and the detection module is configured to obtain temperature data, oil level data, and vibration data inside the transformer oil chamber; A central control module, 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 vibration data; An early warning module, electrically connected to the central control module, and the early warning module is configured to determine whether to send an early warning message according to the corrected oil level data.

[0007] Further, the detection module includes: A capacitive oil level sensor is configured inside the transformer oil chamber, and the capacitive oil level sensor is configured to obtain the oil level data inside the transformer oil chamber; A number of temperature sensors are configured, and the number of temperature sensors are arranged side by side along the vertical direction of the transformer inside the transformer oil chamber based on a preset distance. The temperature sensors are configured to obtain the temperature data of the oil; A vibration sensor is configured on the inner side wall of the transformer oil chamber, and the vibration sensor is configured to obtain the vibration data of the transformer box body.

[0008] Further, the central control module includes: An acquisition unit is electrically connected to each sensor respectively. The acquisition unit is configured to obtain the real-time oil level data inside the transformer oil chamber, and determine whether to control the capacitive oil level sensor to perform secondary acquisition of the oil level data inside the transformer oil chamber according to the relationship between the real-time oil level data and the historical oil level data in the adjacent period. The acquisition unit is also configured to obtain the oil temperature data detected by each temperature sensor, and determine the total temperature data inside the transformer oil chamber based on the sum of the number of each temperature sensor and the distance between each temperature sensor. The acquisition unit is also configured to obtain the real-time vibration data of the transformer; An analysis unit is electrically connected to the acquisition unit. The analysis unit is configured to adjust the oil level data inside the transformer oil chamber according to the total temperature data, and correct the adjusted oil level data according to the real-time vibration data; An evaluation unit is electrically connected to the analysis unit. The evaluation unit is configured to determine the warning score inside the transformer oil chamber according to the relationship between the corrected oil level data and the preset oil level data configured by the evaluation unit.

[0009] Further, when the acquisition unit determines whether to control the capacitive oil level sensor to perform secondary acquisition of the oil level data inside the transformer oil chamber according to the relationship between the real-time oil level data and the historical oil level data in the adjacent period, it includes: 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 in the adjacent period; The acquisition unit is also configured to determine whether to control the capacitive oil level sensor to perform secondary acquisition of the oil level data inside the transformer oil chamber according to 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 acquisition of the oil level data inside the transformer oil chamber; 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 acquisition of the oil level data inside the transformer oil chamber.

[0010] Further, when obtaining the preset oil level difference preconfigured by the obtaining unit, it includes: The obtaining unit is further configured to obtain each historical oil level data within a historical preset period, and obtain the oil level difference between adjacent historical oil level data and the time interval of the oil level difference; The obtaining unit establishes a correlation formula based on the oil level difference and time detection, and obtains the distance metric between each correlation formula based on the Euclidean distance; The obtaining unit establishes a distance matrix based on each distance metric, and clusters each correlation formula based on the distance matrix; The obtaining unit is further configured to determine the preset oil level difference according to the clustering result.

[0011] Further, when the analysis unit adjusts the oil level data inside the transformer oil chamber according to the total temperature data, it includes: The analysis unit is further configured to calculate the temperature mean 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 value, obtain the clustering result, and determine the top layer temperature and the base temperature of the oil chamber; The analysis unit is further configured to determine the adjustment coefficient according to the temperature difference between the top layer temperature and the base temperature of the oil chamber, and adjust the oil level data inside the transformer oil chamber according to the adjustment coefficient.

[0012] Further, when the analysis unit determines the adjustment coefficient according to the temperature difference between the top layer temperature and the base temperature of the oil chamber, it includes: The analysis unit is further configured to determine the adjustment coefficient according to 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 as 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 as L2; When the temperature difference is higher than or equal to the second preset temperature difference, the analysis unit determines the adjustment coefficient as L3; Wherein, the first preset temperature difference is less than the second preset temperature difference, and 0 < L1 < L2 < L3 < 0.5.

[0013] Further, when the analysis unit corrects the adjusted oil level data according to the real-time vibration data, it includes: The analysis unit is further configured to determine the correction coefficient according to 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 that the correction coefficient is Q1; When the real-time vibration data is greater than the first preset vibration data and less than or equal to the second preset vibration data, the analysis unit determines that the correction coefficient is Q2; When the real-time vibration data is greater than the second preset vibration data, the analysis unit determines that the correction coefficient is Q3; Wherein, the first preset vibration data is less than the second preset vibration data, and 0 < Q1 < Q2 < Q3 < 0.5.

[0014] Further, when the evaluation unit determines the warning score inside the transformer oil chamber according to the relationship between the corrected oil level data and the preset oil level data configured by the evaluation unit, it includes: The evaluation unit is further configured to determine the warning score according to the relationship between the corrected oil level data and the preset oil level data: F = ; Wherein, F is the 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.

[0015] Further, when the warning module determines whether to send a warning message according to the corrected oil level data, it includes: The warning module is further configured to determine whether to send a warning message based on the relationship between the 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.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: By setting up a detection module, a central control module and a warning module, a complete oil level perception and warning system is formed. The detection module is deployed inside the transformer oil chamber and can collect key operation parameters including oil level, temperature and vibration in real time, breaking through the limitation of traditional oil level detection systems that only collect a single physical quantity, and providing a data basis for subsequent data fusion processing. Secondly, as the core processing unit, the central control module can dynamically correct the original oil level data according to the law of oil volume expansion caused by temperature changes and the influence of vibration interference on the stability of sensors after receiving the data uploaded by the detection module. Through the built-in correction model or algorithm, the oil level deviation caused by environmental disturbances is effectively compensated, thus significantly improving the stability and reliability of the oil level data and avoiding phenomena such as false alarms and missed alarms caused by error accumulation. Finally, the warning module makes real-time judgments on the corrected oil level data. When it detects that the oil level abnormally deviates from the set threshold, it outputs a warning signal in time, which helps the operation and maintenance personnel to respond quickly and take intervention measures. Compared with traditional oil level detection systems that only judge whether to alarm based on the original readings, the present invention improves the intelligence level of warning on the basis of realizing accurate monitoring and enhances the system's forward-looking recognition ability of potential faults. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. Moreover, throughout the drawings, the same reference numerals are used to represent the same components. In the drawings: Figure 1 FIG. is a functional block diagram of an oil level detection system for an oil-immersed transformer provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the drawings. Although the exemplary embodiments of the present disclosure are shown in the 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 so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be completely conveyed to those skilled in the art. It should be noted that, without conflict, the embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will be described in detail below with reference to the drawings and in combination with the embodiments.

[0019] As Figure 1 shown, in some embodiments of the present application, the present embodiment provides an oil level detection system for an oil-immersed transformer, including: a detection module, a central control module and a warning module.

[0020] Specifically, the detection module is configured inside the transformer oil chamber, and the detection module is configured to obtain temperature data, oil level data, and vibration data inside the transformer oil chamber.

[0021] Specifically, the detection module includes: a capacitive oil level sensor configured inside the transformer oil chamber, and the capacitive oil level sensor is configured to obtain the oil level data inside the transformer oil chamber; several temperature sensors are configured, and the several temperature sensors are arranged side by side along the vertical direction of the transformer at a preset distance inside the transformer oil chamber, and the temperature sensors are configured to obtain the temperature data of the oil; a vibration sensor is configured on the inner side wall of the transformer oil chamber, and the vibration sensor is configured to obtain the vibration data of the transformer box body.

[0022] It can be understood that by arranging the detection module inside the transformer oil chamber, it can directly obtain the key environmental parameters of the transformer during operation and realize the real-time perception of the oil level change. The detection module integrates a capacitive oil level sensor, multiple temperature sensors, and a vibration sensor to form a detection system with multi-source sensing collaborative work. Compared with the traditional single oil level detection method, it has more comprehensive monitoring capabilities. Specifically, the capacitive oil level sensor is used to sense the change in the relative permittivity of the oil inside the transformer, so as to accurately reflect the real-time height of the oil level. The sensor has sensitive response and compact structure, and is suitable for long-term stable operation in a closed oil chamber environment. The temperature sensors are distributed along the vertical direction of the transformer at a preset interval, and can obtain the temperature gradient information of different oil layer positions, providing support for the subsequent correction of the oil level data based on the thermal expansion model. At the same time, the spatial resolution of temperature monitoring is improved through multi-point layout. In addition, the vibration sensor is fixed on the inner wall of the oil chamber and is used to monitor the structural vibration data generated during the operation of the transformer. Since vibration may cause disturbance to the instantaneous reading of the oil level sensor, obtaining this information helps to establish a vibration compensation mechanism in the central control module, thereby improving the stability and accuracy of oil level measurement. The three sensors work together to provide reliable original data support for the multi-factor correction and intelligent early warning of the subsequent oil level data, and construct a highly reliable monitoring system for liquid-immersed transformers.

[0023] 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.

[0024] Specifically, the central control module includes: An acquisition unit is electrically connected to each sensor respectively. The acquisition unit is configured to acquire real-time oil level data inside the transformer oil chamber, and determine whether to control the capacitive oil level sensor to perform secondary acquisition of the oil level data inside the transformer oil chamber according to the relationship between the real-time oil level data and the historical oil level data in the adjacent period. The acquisition unit is also configured to acquire the oil temperature data detected by each temperature sensor, and determine the total temperature data inside the transformer oil chamber based on the sum of the number of each temperature sensor and the distances between each temperature sensor. The acquisition unit is further configured to acquire the real-time vibration data of the transformer; An analysis unit is electrically connected to the acquisition unit. The analysis unit is configured to adjust the oil level data inside the transformer oil chamber according to the total temperature data, and correct the adjusted oil level data according to the real-time vibration data; An evaluation unit is electrically connected to the analysis unit. The evaluation unit is configured to determine the early warning score inside the transformer oil chamber according to the relationship between the corrected oil level data and the preset oil level data configured by the evaluation unit.

[0025] It can be understood that, as the core control and data processing unit, the central control module can collect various types of raw data inside the transformer oil chamber in real time by being electrically connected to each sensor, and make judgments and corrections in combination with historical data, improving the accuracy and intelligence level of oil level monitoring. The central control module integrates an acquisition unit, an analysis unit and an evaluation unit internally. The three cooperate with each other to build a closed-loop of oil level data processing driven by dynamic feedback and early warning. Among them, the acquisition unit is used to collect the data of the capacitive oil level sensor, the temperature sensor and the vibration sensor in real time. On the one hand, it can compare the current oil level data with the oil level change trend in the adjacent historical period, and trigger the secondary acquisition mechanism of the oil level when identifying abnormal fluctuations or measurement anomalies, thereby improving the accuracy of oil level perception. On the other hand, the acquisition unit also calculates the total temperature index of the transformer oil chamber based on the number of sensors arranged and their spacing, and comprehensively calculates the temperature data of each point, and at the same time synchronously collects vibration signals, providing comprehensive inputs for subsequent multi-factor oil level correction. The analysis unit is responsible for dynamically correcting the oil level data. First, it derives the oil level offset caused by thermal expansion or contraction according to the total temperature data to complete a primary adjustment; then it combines the instantaneous disturbance introduced by the vibration data to perform secondary calibration on the preliminarily corrected oil level, further improving the stability and reliability of the oil level data. Finally, the evaluation unit calculates a quantified early warning score based on the difference between the corrected oil level data and the preset oil level data set in the system, provides a decision-making basis for the early warning module, and realizes the early identification and intelligent response of fault risks.

[0026] Specifically, when the acquisition unit determines whether to control the capacitive oil level sensor to perform secondary acquisition of the oil level data inside the transformer oil chamber according to the relationship between the real-time oil level data and the historical oil level data in the adjacent period, it includes: the acquisition unit is further configured to obtain the oil level difference between the real-time oil level data and the historical oil level data in the adjacent period; the acquisition unit is further configured to determine whether to control the capacitive oil level sensor to perform secondary acquisition of the oil level data inside the transformer oil chamber according to 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 acquisition of the oil level data inside the transformer oil chamber; 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 acquisition of the oil level data inside the transformer oil chamber.

[0027] Specifically, when pre-configuring the preset oil level difference by the acquisition unit, it includes: the acquisition unit is further configured to obtain each historical oil level data within the historical preset period, and obtain 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 formula based on the oil level difference and time detection, and obtains the distance metric between each correlation formula based on the Euclidean distance; the acquisition unit establishes a distance matrix according to each distance metric, and clusters each correlation formula based on the distance matrix; the acquisition unit is further configured to determine the preset oil level difference according to the clustering result.

[0028] It is understandable that by real-time monitoring the change amplitude (i.e., the oil level difference) between the current oil level data and the oil level data in adjacent historical periods, it is dynamically determined whether there is abnormal fluctuation, so as to decide whether to trigger the capacitive oil level sensor to perform secondary acquisition of the oil level data, so as to exclude the deviation caused by accidental disturbance or acquisition error, and improve the timeliness and accuracy of oil level monitoring. Secondly, in order to scientifically set the judgment threshold, during system initialization or operation, the acquisition unit will pre-analyze the oil level change situation within the historical preset period, extract the oil level difference and the corresponding time interval between adjacent oil level data, and construct a correlation expression of oil level difference - time change. This expression can reflect the dynamic characteristics of oil level fluctuation under different operating states and constitutes an important reference for evaluating whether the current oil level change is abnormal. Subsequently, the acquisition unit calculates the Euclidean distance between the correlation expressions of oil level changes in different historical periods to obtain the similarity measure between various fluctuation modes, and then constructs a corresponding distance matrix. On this basis, the system introduces clustering algorithms (such as K-means, hierarchical clustering, etc.) to classify and sort various oil level change trends, so as to identify the typical data patterns representing normal fluctuations. This process helps the system to automatically adapt to the natural range of oil level fluctuations under different operating environments and enhance the recognition robustness of abnormal behaviors. Finally, the acquisition unit uses the representative sample difference in the clustering analysis result as the dynamic reference standard of the preset oil level difference. The preset oil level difference determined in this way has the characteristics of self-adaptability and data-driven, and can be closer to the actual operating state of the transformer under specific working conditions. When the real-time oil level difference exceeds this threshold, the system determines that there is abnormal fluctuation and triggers the secondary acquisition mechanism to ensure that subsequent analysis and judgment are based on high-confidence data, thereby improving the stability, reliability and intelligent response ability of the entire system.

[0029] Specifically, when the analysis unit adjusts the oil level data inside the transformer oil chamber according to the total temperature data, it includes: the analysis unit is also configured to calculate the temperature mean value among the 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 value, obtain the clustering result, and determine the top-layer temperature and the base temperature of the oil chamber; the analysis unit is also configured to determine the adjustment coefficient according to the temperature difference between the top-layer temperature and the base temperature of the oil chamber, and adjust the oil level data inside the transformer oil chamber according to the adjustment coefficient.

[0030] Specifically, when the analysis unit determines the adjustment coefficient according to the temperature difference between the top temperature of the oil chamber and the base temperature, it includes: The analysis unit is further configured to determine the adjustment coefficient according to 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 as 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 as L2; when the temperature difference is higher than or equal to the second preset temperature difference, the analysis unit determines the adjustment coefficient as L3; where the first preset temperature difference is less than the second preset temperature difference, and 0 < L1 < L2 < L3 < 0.5.

[0031] Specifically, when the analysis unit corrects the adjusted oil level data according to the real-time vibration data, it includes: The analysis unit is further configured to determine the correction coefficient according to 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 as Q1; when the real-time vibration data is greater than the first preset vibration data and less than or equal to the second preset vibration data, the analysis unit determines the correction coefficient as Q2; when the real-time vibration data is greater than the second preset vibration data, the analysis unit determines the correction coefficient as Q3; where the first preset vibration data is less than the second preset vibration data, and 0 < Q1 < Q2 < Q3 < 0.5.

[0032] It is understandable that, by arranging multiple temperature sensors vertically along the transformer oil chamber, temperature data of the upper and lower layers of the oil is collected, and clustering is performed based on the mean relationship between the temperature data to automatically identify the data representing the top temperature and the base temperature of the oil chamber, thereby establishing a mapping relationship between the temperature change and the oil level change. On this basis, the analysis unit calculates the temperature difference between the top temperature and the base temperature of the oil chamber, and introduces a segmented adjustment coefficient setting mechanism. According to the relationship between this temperature difference and the preset first and second temperature difference thresholds, different levels of adjustment coefficients L1, L2, and L3 are assigned respectively. This design effectively distinguishes the volume expansion degree corresponding to different temperature difference levels, ensuring the rationality and physical consistency of the oil level correction amount. At the same time, the adjustment coefficients satisfy the limitation of 0 < L1 < L2 < L3 < 0.5, controlling the adjustment range and avoiding overcompensation. Further, the analysis unit also takes into account the measurement disturbance effect caused by mechanical vibration during the operation of the transformer. By collecting vibration data in real time and comparing it with the first and second preset vibration thresholds, the current vibration intensity level is determined. The system accordingly sets different correction coefficients Q1, Q2, and Q3 to fine-tune the adjustment coefficient Li originally obtained based on the temperature difference, realizing the recalibration of the temperature model correction result to offset the instantaneous error caused by vibration and improve the overall correction accuracy. Generally speaking, this technology realizes the multi-parameter adaptive correction of the oil level data by establishing a three-level dynamic association model of "temperature difference - adjustment coefficient - correction coefficient". It not only ensures that the oil level drift caused by the temperature gradient can be scientifically modeled and quantified, but also compensates for the vibration disturbance in actual operation, constructing a high-precision oil level data correction scheme based on the integration of physical mechanism and environmental perception.

[0033] Specifically, when the evaluation unit determines the warning score inside the transformer oil chamber according to the relationship between the corrected oil level data and the preset oil level data configured by the evaluation unit, it includes: The evaluation unit is further configured to determine the warning score according to the relationship between the corrected oil level data and the preset oil level data: F = ; where F is the 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.

[0034] Specifically, the warning module is electrically connected to the central control module, and the warning module is configured to determine whether to send a warning message according to the corrected oil level data.

[0035] Specifically, when the warning module determines whether to send a warning message based on the corrected oil level data, it includes: The warning module is further configured to determine whether to send a warning message based on the relationship between the 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.

[0036] It can be understood that the warning module, as the final decision-making output unit of the system, is electrically connected to the central control module. Its main function is to intelligently judge whether to trigger the sending of warning messages based on the corrected oil level data obtained from the analysis and evaluation in the central control module, combined with the set judgment criteria, so as to avoid interference caused by false alarms and frequent alarms while ensuring the safety of the system. In the specific implementation process, the warning module uses the warning score output by the evaluation unit as the main judgment basis. This score is an index quantified based on the deviation degree between the corrected oil level data and the preset oil level data, reflecting the risk level between the current oil level state and the normal state. The system presets a score threshold (i.e., the preset score) as the trigger standard for warning response. When the warning score is less than this preset score threshold, the system believes that the current oil level change is within the safe range, and the warning module will not send any alarm messages to avoid unnecessary intervention. When the warning score is greater than or equal to this preset score, it is determined that there is a potential risk, and the warning module will immediately trigger the sending of alarm messages to prompt maintenance personnel to pay attention or intervene in the handling. This mechanism ensures the accuracy and timeliness of warning responses, improving the intelligent level and practical value of the transformer operation status monitoring system.

[0037] In the above embodiments, by setting up a detection module, a central control module, and an early warning module, a complete oil level perception and early warning system is formed. The detection module is deployed inside the transformer oil chamber and can collect key operation parameters including oil level, temperature, and vibration in real time, breaking through the limitation of traditional oil level detection systems that only collect a single physical quantity and providing a data basis for subsequent data fusion processing. Secondly, as the core processing unit, the central control module can dynamically correct the original oil level data according to the law of oil volume expansion caused by temperature changes and the influence of vibration interference on the stability of sensors after receiving the data uploaded by the detection module. Through the built-in correction model or algorithm, it effectively compensates for the oil level deviation caused by environmental disturbances, thus significantly improving the stability and reliability of the oil level data and avoiding phenomena such as false alarms and missed alarms caused by error accumulation. Finally, the early warning module makes a real-time judgment on the corrected oil level data. When it detects that the oil level abnormally deviates from the set threshold, it promptly outputs an early warning signal, which helps the operation and maintenance personnel to quickly respond and take intervention measures. Compared with traditional oil level detection systems that only judge whether to alarm based on the original readings, the present invention improves the intelligence level of early warning on the basis of achieving accurate monitoring and enhances the system's forward-looking recognition ability of potential faults.

[0038] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0039] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams can be implemented by computer program instructions, and the combination of flows and / or blocks in the flowcharts and / or block diagrams can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in Figure 1 one or more of these processes or multiple processes and / or blocks Figure 1 one or more of these blocks.

[0040] These computer program instructions can 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 generate a manufactured article including an instruction device that realizes the functions in the processFigure 1 one process or multiple processes and / or blocks Figure 1 the functions specified in one block or multiple blocks.

[0041] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0042] 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 them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: the specific implementation manners of the present invention can still be modified or equivalently replaced, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention shall be covered by the protection scope of the claims of the present invention.

Claims

1. An oil level detection system for a liquid-immersed transformer, characterized in that: include: A detection module is disposed inside the transformer oil cavity, and the detection module is configured to obtain temperature data, oil level data, and vibration data inside the transformer oil cavity; A 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; The early warning module is electrically connected to the central control module, and the early warning module is configured to determine whether to send early warning information according to the corrected oil level data.

2. The oil level detection system 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 the transformer oil cavity along the vertical direction of the transformer 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 arranged to obtain vibration data of the transformer box.

3. The oil level detection system 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, respectively, the acquisition unit is configured to acquire real-time oil level data inside the oil cavity of the transformer, and 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 according to the relationship 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 acquire oil temperature data detected by each temperature sensor, and determine the total temperature data inside the oil cavity of the transformer based on the number of each temperature sensor and the sum of the distances between each temperature sensor, and the acquisition unit is also configured to acquire real-time vibration data of the transformer; An analysis unit, electrically connected to the acquisition unit, the analysis 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 oil cavity of the transformer according to a relationship between the corrected oil level data and preset oil level data configured by the evaluation unit.

4. The oil level detection system 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 the oil level data inside the transformer oil cavity according to 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 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 according to the 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 the 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 the oil level data inside the transformer oil cavity.

5. The oil level detection system for a liquid-immersed transformer according to claim 4, characterized in that: When obtaining the preset oil level differential value pre-configured by the unit, including: The acquisition unit is further configured to acquire each historical oil level data of the historical preset time 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 the time detection, and acquires the distance measurement 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 equation based on the distance matrix; The acquisition unit is further configured to determine a preset oil level difference value according to the clustering result.

6. The oil level detection system 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: according to the temperature average 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 cavity; The analysis unit is also configured to determine an adjustment coefficient according to a temperature difference between a top temperature of the oil cavity and a base temperature, and adjust the oil level data inside the transformer oil cavity according to the adjustment coefficient.

7. The oil level detection system for a liquid-immersed transformer according to claim 6, characterized in that: The analysis unit determines the adjustment factor 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 detection system for a liquid-immersed transformer according to claim 7, characterized in that: When the analysis unit corrects the adjusted oil level data according to the real-time vibration data, it includes: The analysis unit is further configured to determine a correction coefficient according to 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, wherein 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; The first preset vibration data is smaller than the second preset vibration data, and 0<Q1<Q2<Q3<0.

5.

9. The oil level detection system 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 according to 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 according to 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 detection system for a liquid-immersed transformer according to claim 9, characterized in that: When the warning module determines whether to send a warning message based on the corrected oil level data, it includes: 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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