Transformer-based anomaly monitoring methods, devices, equipment, and storage media

Abstract

This application provides a method, apparatus, device, and storage medium for transformer-based anomaly monitoring. The method includes: acquiring first temperature information of a target transformer; if the first temperature information of the target transformer meets a first preset condition, acquiring first load information of the target transformer, and acquiring first temperature information and first load information of a preset transformer; determining a first difference based on the first temperature information of the target transformer and the first temperature information of the preset transformer, and determining a second difference based on the first load information of the target transformer and the first load information of the preset transformer; determining anomaly information based on the first difference and the second difference; the anomaly information characterizes whether the target transformer has an operational anomaly. This method is used to improve the accuracy of transformer anomaly monitoring.

Description

Technical Field

[0001] This application relates to the field of power electronics technology, and in particular to a transformer-based anomaly monitoring method, device, equipment, and storage medium. Background Technology

[0002] In power systems, transformers are the core equipment of substations, undertaking the crucial functions of voltage transformation and power transmission. Abnormal transformer temperatures may be caused by internal faults, and if not detected and addressed in a timely manner, they can lead to serious consequences such as equipment damage and power grid outages.

[0003] In related technologies, the temperature of a transformer is monitored, and the monitored temperature value is compared with a static threshold to determine whether there is a temperature anomaly.

[0004] However, during low-load periods, as temperatures approach the static threshold, monitoring methods relying on this threshold are prone to generating numerous false alarms, resulting in low accuracy in transformer anomaly monitoring. Therefore, improving the accuracy of transformer anomaly monitoring has become an urgent technical problem to be solved. Summary of the Invention

[0005] This application provides a method, apparatus, device, and storage medium for transformer-based anomaly monitoring, which aims to improve the accuracy of transformer anomaly monitoring.

[0006] In a first aspect, embodiments of this application provide a transformer-based anomaly monitoring method, comprising:

[0007] Acquire the first temperature information of the target transformer; the first temperature information represents the temperature change of the transformer within a first preset time period.

[0008] If the first temperature information of the target transformer meets the first preset condition, then the first load information of the target transformer is obtained, as well as the first temperature information and the first load information of the preset transformer are obtained; the first load information represents the change of the transformer load within a first preset time period.

[0009] A first difference is determined based on the first temperature information of the target transformer and the first temperature information of the preset transformer, and a second difference is determined based on the first load information of the target transformer and the first load information of the preset transformer; the first difference represents the difference between the average temperature of the target transformer and the average temperature of the preset transformer within a first preset time period; the second difference represents the difference between the average load of the target transformer and the average load of the preset transformer within the first preset time period.

[0010] Based on the first difference and the second difference, abnormal information is determined; the abnormal information indicates whether the target transformer has an operational abnormality.

[0011] In one possible implementation, determining the first difference based on the first temperature information of the target transformer and the first temperature information of the preset transformer includes:

[0012] Based on the first temperature information of the target transformer, the first average information of the target transformer is determined, and based on the first temperature information of the preset transformer, the first average information of the preset transformer is determined; the first average information represents the average temperature of the transformer within a first preset time period.

[0013] Based on the first average information of the target transformer and the first average information of the preset transformer, a first difference is determined; based on the first load information of the target transformer and the first load information of the preset transformer, a second difference is determined, including:

[0014] Based on the first load information of the target transformer, the second average information of the target transformer is determined, and based on the first load information of the preset transformer, the second average information of the preset transformer is determined; the second average information represents the average load of the transformer within a first preset time period.

[0015] The second difference is determined based on the second average information of the target transformer and the second average information of the preset transformer.

[0016] In one possible implementation, determining the anomaly information based on the first difference and the second difference includes:

[0017] If the first difference satisfies the second preset condition and the second difference satisfies the third preset condition, then a first ratio between the first difference and the first average information of the target transformer is determined, and a second ratio between the second difference and the second average information of the target transformer is determined.

[0018] A third ratio is determined between the first ratio and the second ratio, and the abnormal information of the target transformer is determined based on the third ratio.

[0019] In one possible implementation, it also includes:

[0020] If the first difference satisfies the second preset condition and the second difference does not satisfy the third preset condition, then doubling information is determined based on the first difference; the doubling information represents the information obtained by doubling the first difference.

[0021] Based on the second difference, reverse information is determined; the reverse information and the second difference are positive and negative numbers respectively.

[0022] The abnormal information is determined based on the doubling information and the reversal information.

[0023] In one possible implementation, it also includes:

[0024] If the first difference does not meet the second preset condition, then the second temperature information and the second load information of the target transformer are obtained; the second temperature information represents the temperature change of the transformer within a second preset time period; the second load information represents the load change of the transformer within a second preset time period; the second preset time period has the same length as the first preset time period, and the second preset time period is located before the first preset time period;

[0025] A third difference is determined based on the first temperature information and the second temperature information of the target transformer, and a fourth difference is determined based on the first load information and the second load information of the target transformer; the third difference represents the difference between the average temperature of the target transformer in a first preset time period and the average temperature of the target transformer in a second preset time period; the fourth difference represents the difference between the average load of the target transformer in the first preset time period and the average load of the target transformer in the second preset time period.

[0026] The abnormal information is determined based on the third and fourth differences.

[0027] In one possible implementation, it also includes:

[0028] Based on the first temperature information of the target transformer, fluctuation information is determined; the fluctuation information characterizes the temperature change range of the target transformer within a first preset time period.

[0029] If the fluctuation information meets the fourth preset condition, then an early warning information is generated based on the fluctuation information; the early warning information indicates that a temperature change occurs during the operation of the target transformer.

[0030] In one possible implementation, it also includes:

[0031] The target temperature is determined from the first temperature information of the target transformer; the target temperature represents the temperature value of the target transformer last collected within a first preset time period;

[0032] If the target temperature is greater than a first preset threshold, then fault information is generated based on the target temperature; the fault information indicates that the target transformer has experienced a device failure.

[0033] Secondly, embodiments of this application provide a transformer-based anomaly monitoring device, comprising:

[0034] The first acquisition module is used to acquire the first temperature information of the target transformer; the first temperature information represents the temperature change of the transformer within a first preset time period.

[0035] The second acquisition module is used to acquire the first load information of the target transformer if the first temperature information of the target transformer meets the first preset condition, and to acquire the first temperature information and the first load information of the preset transformer; the first load information represents the change of the transformer load within a first preset time period.

[0036] The first determining module is used to determine a first difference based on the first temperature information of the target transformer and the first temperature information of the preset transformer, and to determine a second difference based on the first load information of the target transformer and the first load information of the preset transformer; the first difference represents the difference between the average temperature of the target transformer and the average temperature of the preset transformer within a first preset time period; the second difference represents the difference between the average load of the target transformer and the average load of the preset transformer within the first preset time period.

[0037] The second determining module is used to determine abnormal information based on the first difference and the second difference; the abnormal information indicates whether the target transformer has an operational abnormality.

[0038] Thirdly, embodiments of this application provide a transformer-based anomaly monitoring device, including: a memory and a processor;

[0039] The memory stores computer-executed instructions;

[0040] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0041] The transformer-based anomaly monitoring method, apparatus, equipment, and storage medium provided in this application acquire first temperature information of a target transformer, which represents the temperature change of the transformer within a first preset time period. By determining whether the first temperature information of the target transformer meets a first preset condition, when the first temperature information of the target transformer meets the first preset condition, first load information of the target transformer, as well as first temperature information and first load information of a preset transformer, are acquired. The first load information represents the load change of the transformer within the first preset time period. This enables immediate analysis to be initiated when the first temperature information of the transformer meets the first preset condition but has not yet reached a dangerous level, providing a valuable window for early intervention for maintenance personnel. Subsequently, a first difference is determined based on the first temperature information of the target transformer and the first temperature information of the preset transformer, and a second difference is determined based on the first load information of the target transformer and the first load information of the preset transformer. Anomaly information is identified through correlation analysis of the first and second differences, changing the traditional single-threshold alarm mode. By performing correlation analysis on the transformer's temperature and load, it is possible to effectively distinguish between temperature rise caused by normal high load and temperature rise caused by equipment anomalies. This allows for the deletion of alarms from a large number of normally operating transformers, even if the temperature is high, due to the correlation analysis between temperature and load. This significantly reduces the number of alarms requiring manual attention, making monitoring more targeted. Furthermore, by correlating the temperature and load information of the target transformer with that of preset transformers, compared to comparing only a single threshold, dynamic data comparison makes it easier to uncover transformer anomalies, thereby improving the accuracy of transformer anomaly monitoring. Attached Figure Description

[0042] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0043] Figure 1 A flowchart illustrating the transformer-based anomaly monitoring method provided in this application embodiment. Figure 1 ;

[0044] Figure 2 A flowchart illustrating the transformer-based anomaly monitoring method provided in this application embodiment. Figure 2 ;

[0045] Figure 3 A flowchart illustrating the transformer-based anomaly monitoring method provided in this application embodiment. Figure 3 ;

[0046] Figure 4A flowchart illustrating the transformer-based anomaly monitoring method provided in this application embodiment. Figure 4 ;

[0047] Figure 5 A schematic diagram of the structure of the transformer-based anomaly monitoring device provided in the embodiments of this application;

[0048] Figure 6 This is a schematic diagram of the structure of a transformer-based anomaly monitoring device provided in an embodiment of this application.

[0049] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0050] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0051] In power systems, transformers are the core equipment of substations, undertaking the crucial functions of voltage transformation and power transmission. Transformers achieve voltage level conversion through their iron core and coil windings, but they generate a large amount of heat during operation.

[0052] The coil windings continuously heat up under the load current, while the oil in the transformer tank dissipates heat from the windings through a cooling system (such as a fan or oil pump) to maintain normal operation of the equipment.

[0053] Transformers are typically equipped with temperature measuring devices that collect oil temperature and winding temperature data in real time and transmit the data to the dispatch center through a remote monitoring system.

[0054] However, abnormal transformer temperatures (such as a sudden rise in oil or winding temperature) may be caused by internal faults (such as winding short circuits or decreased insulation performance) or cooling system failures (such as fan / oil pump failures). If not detected and addressed in time, they may lead to serious consequences such as equipment damage and power grid outages.

[0055] In actual operation, transformer load and temperature are positively correlated, but existing monitoring methods mostly rely on fixed threshold alarms.

[0056] For example, in related technologies, fixed defect thresholds are set for oil temperature and winding temperature respectively. If the oil temperature or winding temperature exceeds the defect threshold, an alarm is triggered. This method collects temperature data in real time through built-in sensors and uploads it to the dispatching system via a communication network. The dispatcher then determines whether to initiate a defect handling process based on the alarm information, such as whether load transfer or emergency power outage is necessary.

[0057] However, relying solely on static thresholds cannot identify short-term temperature fluctuations or abnormal deviations in the load-temperature relationship, leading to delayed fault detection and making it difficult for maintenance personnel to intervene before a fault occurs. During low-load periods, many main transformers are misjudged as abnormal due to temperatures approaching the threshold, requiring significant manpower for investigation, even though the actual risk is low, thus reducing response efficiency. During high-load periods, thresholds may not cover sudden faults, resulting in missed alarms. Furthermore, the relevant technologies do not incorporate multi-dimensional comparisons with historical load-temperature curves, data from other main transformers at the same station, or data from different dates, making it difficult to distinguish between normal load fluctuations and potential fault characteristics.

[0058] The present application provides a transformer-based anomaly monitoring method, device, equipment, and storage medium to solve the aforementioned technical problems.

[0059] The technical solution of this application and how it solves the above-mentioned technical problems will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0060] Figure 1 A flowchart illustrating the transformer-based anomaly monitoring method provided in this application embodiment. Figure 1 ,like Figure 1 As shown, the method includes:

[0061] S101. Obtain the first temperature information of the target transformer; the first temperature information represents the temperature change of the transformer within a first preset time period.

[0062] It should be noted that this application can be applied to intelligent monitoring systems for substations, and is particularly suitable for the early identification of temperature anomalies in oil-immersed power transformers.

[0063] This application focuses on the main transformer oil temperature or the main transformer winding temperature as the main monitoring object. Through real-time acquisition, storage, and comparative analysis of main transformer temperature and load data, it realizes intelligent judgment and early warning of the main transformer operating status.

[0064] The intelligent monitoring system pre-sets two temperature thresholds, which are the defect temperature setpoints. (e.g., 85 degrees Celsius) and warning temperature setpoint (e.g., 75 degrees Celsius), and Meanwhile, the intelligent monitoring system defines a first preset time period (e.g., 5 minutes) as the time window for data comparison and analysis.

[0065] The intelligent monitoring system monitors the oil temperature (or winding temperature) of all main transformers in real time. Unless otherwise specified, the transformer temperature referred to in this application refers to the oil temperature of the main transformer. If it is the winding temperature, the data processing method for the winding temperature is similar to that for the oil temperature, with only some threshold settings being different. This application uses the oil temperature of the main transformer as an example to illustrate this application.

[0066] Acquire the first temperature information of any target transformer. The first temperature information represents the temperature change of the transformer within a first preset time period. That is, the oil temperature of the transformer at multiple preset times within the first preset time period is collected at a preset sampling frequency (e.g., the temperature of the transformer is collected in real time by a temperature sensor at a preset sampling frequency). The first temperature information includes the oil temperature of the transformer at these multiple preset times.

[0067] When the real-time oil temperature of the target transformer is continuously monitored to be at and When the real-time oil temperature is between 75 degrees Celsius and 85 degrees Celsius, and this temperature remains above 85 degrees Celsius for a duration of 5 minutes (a first preset time period), the first temperature information is deemed to meet the first preset condition. In other words, the first preset condition is that the temperature at each preset moment in the first temperature information is within the first preset time period. and At this point, the intelligent monitoring system triggers the early warning analysis process.

[0068] S102. If the first temperature information of the target transformer meets the first preset condition, then the first load information of the target transformer is obtained, as well as the first temperature information and the first load information of the preset transformer are obtained; the first load information represents the change of the transformer load within the first preset time period.

[0069] For example, when the first temperature information of the target transformer is detected to meet the first preset condition, the first load information of the target transformer is obtained. The first load information represents the change of the transformer load within a first preset time period. That is, the first load information includes the load value of the transformer at each preset time within the first preset time period.

[0070] The first temperature information and the first load information of the target transformer are used as the anomaly analysis data of the target transformer.

[0071] Simultaneously, the system acquires the first temperature information and the first load information of the preset transformer. The preset transformer can be another transformer located in the same substation as the target transformer. There can be one or more preset transformers. The preset transformer and the target transformer are put into operation simultaneously.

[0072] The first load information of the target transformer and the first load information of the preset transformer can be obtained from the data acquisition and monitoring control system, or the first load information of the target transformer and the first load information of the preset transformer can be obtained through other means, such as obtaining the first load information of the target transformer and the first load information of the preset transformer from a historical database. This application does not limit this. The sampling frequency of the first load information and the first temperature information is the same.

[0073] The first temperature information and the first load information of the preset transformer are used as comparison data. That is, the first temperature information and the first load information of the target transformer are compared and analyzed with the first temperature information and the first load information of each preset transformer to analyze the abnormal information of the target transformer.

[0074] If the first temperature information of the target transformer does not meet the first preset condition, that is, when the real-time oil temperature of the target transformer is not continuously at a certain level... and In between, the real-time oil temperature of the transformer will continue to be monitored in order to conduct the next early warning analysis.

[0075] For example, if the first temperature information of the target transformer does not meet the first preset condition, then the real-time oil temperature of the target transformer is at... and The duration between these intervals is reset to zero, and the timer is restarted. During continuous monitoring, each time the oil temperature is detected to be below a certain level... At the same time, the real-time oil temperature of the target transformer is at and The duration between intervals is reset to zero, and the timing is restarted until the real-time oil temperature of the target transformer is monitored to be within a certain range. and If the duration between events is the same as the duration of the first preset time period, then the next warning analysis will be performed.

[0076] S103. Based on the first temperature information of the target transformer and the first temperature information of the preset transformer, determine the first difference, and based on the first load information of the target transformer and the first load information of the preset transformer, determine the second difference; the first difference represents the difference between the average temperature of the target transformer and the average temperature of the preset transformer within the first preset time period; the second difference represents the difference between the average load of the target transformer and the average load of the preset transformer within the first preset time period.

[0077] For example, a first difference is determined based on the first temperature information of the target transformer and the first temperature information of the preset transformer. The first difference represents the difference between the average temperature of the target transformer and the average temperature of the preset transformer within a first preset time period.

[0078] For example, the first difference is the difference between the average temperature of the target transformer within a first preset time period and the average temperature of the preset transformer within the same preset time period. The average temperature of the target transformer within the first preset time period can be calculated from the first temperature information of the target transformer.

[0079] Based on the first load information of the target transformer and the first load information of the preset transformer, a second difference is determined. The second difference represents the difference between the average load of the target transformer and the average load of the preset transformer during the first preset time period.

[0080] For example, the second difference is the difference between the average load of the target transformer and the average load of the preset transformer within the first preset time period. The average load of the target transformer within the first preset time period can be calculated from the first load information of the target transformer.

[0081] S104. Determine the abnormal information based on the first difference and the second difference; the abnormal information indicates whether the target transformer has an operational abnormality.

[0082] For example, after obtaining the first difference and the second difference, a correlation analysis is performed on the first difference and the second difference to determine the abnormal information. The abnormal information indicates whether the target transformer has an operational abnormality, that is, whether the oil temperature of the target transformer is continuously too high or too low during the operation of the target transformer.

[0083] It should be noted that under similar external environments, such as within the same substation, if the loads of two transformers are not significantly different, but their oil temperatures differ significantly, it indicates that the temperature rise of the transformer being compared (i.e., the target transformer) may be unrelated to the load, but more likely due to internal anomalies, such as decreased cooling efficiency or insulation aging, leading to the transformer's temperature increase. Therefore, based on a preset judgment algorithm, a correlation analysis can be performed on the first and second differences to obtain anomaly information.

[0084] For example, by comparing the ratio of the first difference and the second difference with the ratio of the historical first difference and the historical second difference, it is possible to analyze whether the target transformer has any operational abnormalities.

[0085] Among them, the first historical difference is the difference between the average temperature of the target transformer obtained from historical operating data and the average temperature of the preset transformer, and the second historical difference is the difference between the average load of the target transformer obtained from historical operating data and the average load of the preset transformer.

[0086] When the ratio of the first difference to the second difference differs significantly from the ratio of the historical first difference to the historical second difference, the target transformer is likely to have an operational abnormality. In this case, it is necessary to notify the abnormality information to inform maintenance personnel to perform manual inspection of the transformer.

[0087] The transformer-based anomaly monitoring method provided in this application acquires first temperature information of the target transformer, which represents the temperature change of the transformer within a first preset time period. By determining whether the first temperature information of the target transformer meets a first preset condition, when the first temperature information of the target transformer meets the first preset condition, the method acquires first load information of the target transformer, as well as first temperature information and first load information of a preset transformer. The first load information represents the load change of the transformer within the first preset time period. This allows for immediate analysis to be initiated when the first temperature information of the transformer meets the first preset condition but has not yet reached a dangerous level, providing a valuable window for early intervention for maintenance personnel. Subsequently, a first difference is determined based on the first temperature information of the target transformer and the first temperature information of the preset transformer, and a second difference is determined based on the first load information of the target transformer and the first load information of the preset transformer. By performing correlation analysis on the first and second differences, anomaly information is identified, changing the traditional single-threshold alarm mode. Through correlation analysis of transformer temperature and load, it is possible to effectively distinguish between temperature rise caused by normal high load and temperature rise caused by equipment anomalies. This allows for the deletion of alarms from a large number of normally operating transformers, even if the temperature is high, due to the correlation analysis between temperature and load. This significantly reduces the number of alarms requiring manual attention, making monitoring more targeted. Furthermore, by correlating the temperature and load information of the target transformer with that of preset transformers, compared to comparing only a single threshold, dynamic data comparison makes it easier to uncover transformer anomalies, thereby improving the accuracy of transformer anomaly monitoring.

[0088] Figure 2 A flowchart illustrating the transformer-based anomaly monitoring method provided in this application embodiment. Figure 2 ,like Figure 2As shown, determining the first difference based on the first temperature information of the target transformer and the first temperature information of the preset transformer includes: determining the first average information of the target transformer based on the first temperature information of the target transformer, and determining the first average information of the preset transformer based on the first temperature information of the preset transformer; the first average information represents the average temperature of the transformer within a first preset time period; determining the first difference based on the first average information of the target transformer and the first average information of the preset transformer; determining the second difference based on the first load information of the target transformer and the first load information of the preset transformer includes: determining the second average information of the target transformer based on the first load information of the target transformer, and determining the second average information of the preset transformer based on the first load information of the preset transformer; the second average information represents the average load of the transformer within a first preset time period; determining the second difference based on the second average information of the target transformer and the second average information of the preset transformer. This method includes:

[0089] S201. Obtain the first temperature information of the target transformer.

[0090] S202. If the first temperature information of the target transformer meets the first preset condition, then the first load information of the target transformer is obtained, and the first temperature information and the first load information of the preset transformer are obtained.

[0091] S203. Based on the first temperature information of the target transformer, determine the first average information of the target transformer, and based on the first temperature information of the preset transformer, determine the first average information of the preset transformer; the first average information represents the average temperature of the transformer within a first preset time period.

[0092] For example, based on the first temperature information of the target transformer, the first average information of the target transformer is determined. The first average information represents the average temperature of the transformer within a first preset time period, that is, the first average information is the average temperature at all preset times within the first preset time period.

[0093] For example, if the first temperature information of the target transformer includes temperature values ​​at multiple preset times within a first preset time period (e.g., within 5 minutes) (e.g., temperature is collected once per second, including...) If the temperature values ​​at 300 preset times are used as the first temperature information of the target transformer, then the average value of the temperature values ​​at 300 preset times is calculated, and the calculated average value is used as the first average information of the target transformer.

[0094] Similarly, based on the first temperature information of the preset transformer, the first average information of the preset transformer is determined. For example, if the first temperature information of the preset transformer includes temperature values ​​at multiple preset times within a first preset time period (e.g., within 5 minutes), If the temperature values ​​at 300 preset times are used as the preset transformer's first temperature information, then the average value of the temperature values ​​at 300 preset times is calculated, and the calculated average value is used as the preset transformer's first average information.

[0095] S204. Determine the first difference based on the first average information of the target transformer and the first average information of the preset transformer.

[0096] The first average information of the target transformer is used as the minuend, and the first average information of the preset transformer is used as the subtrahend. The subtraction operation is performed to obtain the first difference value.

[0097] S205. Based on the first load information of the target transformer, determine the second average information of the target transformer, and based on the first load information of the preset transformer, determine the second average information of the preset transformer; the second average information represents the average load of the transformer within the first preset time period.

[0098] The data processing flow for the first load information of the target transformer and the first load information of the preset transformer is similar to the data processing flow for the first temperature information of the target transformer or the first temperature information of the preset transformer.

[0099] Specifically, based on the first load information of the target transformer, the second average information of the target transformer is determined. The second average information represents the average load of the transformer within the first preset time period, that is, the second average information is the average load at all preset times within the first preset time period.

[0100] For example, if the first load information of the target transformer includes load values ​​at multiple preset times within a first preset time period (e.g., within 5 minutes) (e.g., load values ​​at 300 preset times), then the average value of the load values ​​at the 300 preset times in the first load information of the target transformer is calculated, and the calculated average value is used as the second average information of the target transformer.

[0101] Furthermore, based on the first load information of the preset transformer, the second average information of the preset transformer is determined. For example, if the first load information of the preset transformer includes load values ​​at multiple preset times within a first preset time period (e.g., within 5 minutes), If the load value at a preset time is calculated, then the average value of the load value at 300 preset times in the first load information of the preset transformer is calculated, and the calculated average value is used as the second average information of the preset transformer.

[0102] S206. Determine the second difference based on the second average information of the target transformer and the second average information of the preset transformer.

[0103] For example, the second average information of the target transformer is used as the minuend, and the second average information of the preset transformer is used as the subtrahend, and a subtraction operation is performed to obtain the second difference.

[0104] S207. Determine the abnormal information based on the first difference and the second difference.

[0105] For example, correlation analysis is performed on the first difference and the second difference to identify anomalies. Specifically, this includes:

[0106] S2071. If the first difference satisfies the second preset condition and the second difference satisfies the third preset condition, then determine the first ratio between the first difference and the first average information of the target transformer, and determine the second ratio between the second difference and the second average information of the target transformer.

[0107] For example, if the first difference satisfies the second preset condition and the third difference satisfies the third preset condition (e.g., the first difference is greater than 0 and the second difference is greater than 0), that is, within the first preset time period, the average temperature of the target transformer is greater than the average temperature of the preset transformer, and the average load of the target transformer is greater than the average load of the preset transformer. That is, the second preset condition is that the first difference is greater than 0, and the third preset condition is that the second difference is greater than 0. Then, a first ratio between the first difference and the first average information of the target transformer is determined, and a second ratio between the second difference and the second average information of the target transformer is determined.

[0108] It should be noted that when the first difference satisfies the second preset condition and the third difference satisfies the third preset condition, the average temperature of the target transformer is greater than the average temperature of the preset transformer and the average load of the target transformer is greater than the average load of the preset transformer within the first preset time period. This ensures the accuracy of the comparison results by using a healthy preset transformer with normal (lower) temperature and the same trend in temperature and load as a benchmark when it is suspected that the target transformer may have abnormal temperature rise.

[0109] Temperature comparisons rely on a first ratio between the first difference and the first average information of the target transformer. For example, the first difference is used as the dividend, and the first average information of the target transformer is used as the divisor; a division operation is performed to obtain the first ratio. This first ratio reflects the rate of temperature change of the target transformer. A larger first ratio indicates a greater rate of temperature change in the target transformer.

[0110] Load comparison relies on a second ratio between the second difference and the second average information of the target transformer. For example, the second difference is used as the dividend, and the second average information of the target transformer is used as the divisor; a division operation is performed to obtain the second ratio. This second ratio reflects the rate of change of the target transformer's load. A larger second ratio indicates a larger rate of change of the target transformer's load.

[0111] S2072. Determine the third ratio between the first ratio and the second ratio, and determine the abnormal information of the target transformer based on the third ratio.

[0112] After obtaining the first ratio and the second ratio, determine the third ratio between the first ratio and the second ratio. For example, the third ratio can be calculated according to the following formula (1):

[0113] (1);

[0114] In the formula, k represents the third ratio; Indicates the first ratio; Indicates the second ratio; Indicates the first difference; T represents the first average information of the target transformer; Indicates the second difference; This represents the second average information of the target transformer.

[0115] Next, based on the third ratio, the abnormal information of the target transformer is determined. For example, if the third ratio is greater than the second preset threshold, it is determined that the target transformer has an operational abnormality. If the third ratio is less than or equal to the second preset threshold, it is determined that the target transformer does not have an operational abnormality. The second preset threshold can be calculated as D times the ratio measured when both the target transformer and the preset transformer are operating healthily, where D can range from 2 to 2.5. The physical meaning of the third ratio is: the temperature rise caused by a unit load increase in the target transformer. When the temperature rise caused by a unit load increase in the target transformer is significantly higher than the healthy baseline (by comparison with the second preset threshold), it indicates that the heat dissipation performance of the target transformer may be deteriorating.

[0116] The advantage of this approach is that when the first difference meets the second preset condition and the second difference meets the third preset condition, a first ratio between the first difference and the first average information of the target transformer is determined, thus obtaining the rate of temperature change of the target transformer. Similarly, a second ratio between the second difference and the second average information of the target transformer is determined, thus obtaining the rate of load change of the target transformer. Subsequently, a third ratio between the first and second ratios is determined, and based on this third ratio, abnormal information about the target transformer is identified. This third ratio reflects the temperature rise caused by the increase in unit load of the target transformer, enabling monitoring of the temperature rise caused by the increase in unit load. When the temperature rise caused by the increase in unit load is significantly higher than the healthy baseline, abnormal information is generated, allowing for timely investigation into whether any related factors are causing the deterioration of the target transformer's heat dissipation performance.

[0117] S2073. If the first difference satisfies the second preset condition and the second difference does not satisfy the third preset condition, then the doubling information is determined based on the first difference; the doubling information represents the information obtained by doubling the first difference.

[0118] For example, if the first difference satisfies the second preset condition, but the second difference does not satisfy the third preset condition (e.g., the first difference is greater than 0, and the second difference is less than or equal to 0), then a situation arises where the target transformer has a higher oil temperature but a lower load. Based on the first difference, a doubling information is determined. This doubling information represents the information obtained by doubling the first difference. For example, the doubling information is two times or more than the first difference. The purpose of this is to amplify the effect of the temperature difference.

[0119] S2074. Determine the reverse information based on the second difference; the reverse information and the second difference are positive and negative numbers respectively.

[0120] For example, to ensure that the ratio calculated subsequently for comparison with the second preset threshold is positive, reverse information is determined based on the second difference, where the reverse information and the second difference are mutually positive and negative. That is, by taking the negative of the second difference, direction information is obtained, such that the reverse information and the doubling information are both positive or both negative.

[0121] S2075. Determine abnormal information based on doubling and reversal information.

[0122] For example, abnormal information is determined based on doubling information and reverse information. Specifically, similar to obtaining abnormal information by processing the first difference and the second difference, the first difference is replaced with doubling information, and the second difference is replaced with reverse information, so as to obtain abnormal information by processing the doubling information and the reverse information.

[0123] For example, a fourth ratio is determined between the doubling information and the first average information of the target transformer, and a fifth ratio is determined between the reverse information and the second average information of the target transformer. A sixth ratio is determined between the fourth and fifth ratios, and based on the sixth ratio, abnormal information of the target transformer is determined. If the sixth ratio is greater than a second preset threshold, the abnormal information is determined to be that the target transformer has an operational abnormality; if the sixth ratio is less than or equal to the second preset threshold, the abnormal information is determined to be that the target transformer does not have an operational abnormality.

[0124] The advantage of this approach is that when the first difference meets the second preset condition, but the second difference does not meet the third preset condition, doubling information is determined based on the first difference. This doubling information represents the information obtained by doubling the first difference. Converse information is determined based on the second difference, which is positive and negative of the second difference. This amplifies the temperature difference even when the target transformer oil temperature is higher than the load, effectively capturing anomalies. Simultaneously, adjusting the second difference to double the information ensures the accuracy of subsequent data processing. By determining anomaly information based on both the doubling and reverse information, the method can effectively capture anomalies even under various edge conditions, thus improving its robustness and reliability.

[0125] The transformer-based anomaly monitoring method provided in this application refines the calculation methods for the first and second differences. By calculating the average temperature and average load of the target transformer and a preset transformer within a preset time period, and then calculating the difference based on this, the interference of random factors such as instantaneous fluctuations and sampling noise on the judgment results is effectively eliminated. Data processing using the first and second average information more realistically reflects the differences in stable equipment operation, enabling fair and scientific horizontal comparisons between transformers of different capacities, models, and operating conditions, thereby improving the accuracy of transformer anomaly monitoring.

[0126] Figure 3 A flowchart illustrating the transformer-based anomaly monitoring method provided in this application embodiment. Figure 3 ,like Figure 3 As shown, the above method includes:

[0127] S301. Obtain the first temperature information of the target transformer.

[0128] S302. If the first temperature information of the target transformer meets the first preset condition, then the first load information of the target transformer is obtained, as well as the first temperature information and the first load information of the preset transformer are obtained.

[0129] S303. Determine a first difference based on the first temperature information of the target transformer and the first temperature information of the preset transformer, and determine a second difference based on the first load information of the target transformer and the first load information of the preset transformer.

[0130] S304. If the first difference does not meet the second preset condition, then the second temperature information and the second load information of the target transformer are obtained; the second temperature information represents the temperature change of the transformer within the second preset time period; the second load information represents the load change of the transformer within the second preset time period; the second preset time period has the same length as the first preset time period, and the second preset time period is located before the first preset time period.

[0131] For example, if the first difference does not meet the second preset condition (e.g., the first difference is less than or equal to 0), then regardless of whether the second difference meets the third preset condition, the second temperature information and the second load information of the target transformer are obtained. The second temperature information represents the temperature change of the transformer within a second preset time period. The second load information represents the load change of the transformer within the second preset time period. The second preset time period is the same length as the first preset time period and is located before the first preset time period. That is, the second temperature information and the second load information of the target transformer within the historical second preset time period are obtained. There can be multiple second preset time periods.

[0132] For example, assuming the first preset time period is 5 minutes from 09:35:00 to 09:40:00 on June 24, 2025, and it is monitored that the oil temperature of the target transformer is consistently within the range of 5 minutes during the first preset time period. and Between 09:35:00 and 09:40:00 on June 24, 2025, obtain the first load information of the target transformer within a 5-minute period.

[0133] When the first difference is detected as not meeting the second preset condition, assuming the selected comparison date is June 23, and the second preset time period is from 09:35:00 to 09:40:00 on June 23, 2025, the second temperature information and the second load information of the target transformer within 5 minutes from 09:35:00 to 09:40:00 on June 23, 2025 are obtained.

[0134] If there are multiple second preset time periods, for example, assuming the selected comparison days are June 23 and June 22, similarly, for June 22, obtain the second temperature information and second load information of the target transformer within 5 minutes from 09:35:00 to 09:40:00 on June 22, 2025.

[0135] S305. Based on the first temperature information and the second temperature information of the target transformer, determine the third difference, and based on the first load information and the second load information of the target transformer, determine the fourth difference; the third difference represents the difference between the average temperature of the target transformer in the first preset time period and the average temperature of the target transformer in the second preset time period; the fourth difference represents the difference between the average load of the target transformer in the first preset time period and the average load of the target transformer in the second preset time period.

[0136] For example, for each second preset time period, the temperature and load of the target transformer in the first preset time period are compared and analyzed with the temperature and load of the target transformer in the second preset time period.

[0137] Specifically, a third difference is determined based on the first and second temperature information of the target transformer. For example, based on the first temperature information of the target transformer, the average temperature of the target transformer within a first preset time period is calculated; based on the second temperature information of the target transformer, the average temperature of the target transformer within a second preset time period is calculated. The number of preset times within the second preset time period is the same as the number of preset times within the first preset time period. The third difference is equal to the difference between the average temperature corresponding to the first temperature information and the average temperature corresponding to the second temperature information of the target transformer.

[0138] Furthermore, a fourth difference is determined based on the first load information and the second load information of the target transformer. For example, based on the first load information of the target transformer, the average load of the target transformer within a first preset time period is calculated. Based on the second load information of the target transformer, the average load of the target transformer within a second preset time period is calculated. The number of preset times within the second preset time period is the same as the number of preset times within the first preset time period. The fourth difference is equal to the difference between the average load corresponding to the first load information and the average load corresponding to the second load information of the target transformer.

[0139] The advantage of this approach is that when the first difference does not meet the second preset condition, the second temperature information and the second load information of the target transformer within the second preset time period are obtained. That is, when the temperature and load of other transformers in the same station cannot be used for comparison, the temperature and load (second temperature information and second load information) of the target transformer during its normal operation in the past (second preset time period) are used for comparative analysis. Based on the first temperature information and the second temperature information of the target transformer, the third difference is determined, and based on the first load information and the second load information of the target transformer, the fourth difference is determined. Based on the third difference and the fourth difference, abnormal information is determined, ensuring the feasibility of the pre-control analysis of the target transformer.

[0140] S306. Determine the abnormal information based on the third and fourth differences.

[0141] Specifically, the process of determining abnormal information based on the third and fourth differences is similar to the process of determining abnormal information based on the first and second differences, except that the first difference is replaced with the third difference and the second difference is replaced with the fourth difference. This will not be elaborated further here.

[0142] S307. If the first difference satisfies the second preset condition and the second difference satisfies the third preset condition, then determine the first ratio between the first difference and the first average information of the target transformer, and determine the second ratio between the second difference and the second average information of the target transformer.

[0143] S308. Determine the third ratio between the first ratio and the second ratio, and determine the abnormal information of the target transformer based on the third ratio.

[0144] In some specific implementations of this embodiment, the temperature and load of multiple other main transformers, as well as the temperature and load of the target transformer within multiple second preset time periods, can be compared and analyzed.

[0145] For example, when the first temperature information of the target transformer meets the first preset condition, the first load information of the target transformer is acquired. Simultaneously, the first temperature information and first load information of each of at least one preset transformer are acquired, as well as the second temperature information and second load information of the target transformer within each of at least one second preset time period. The method for selecting the second preset time period is to select a second preset time period corresponding to the first preset time period within at least one day of a specified time (e.g., within the past month).

[0146] The first temperature and first load information of the target transformer within a first preset time period are used as the comparison data. The first temperature and first load information of each preset transformer within the first preset time period are used as the comparison data. The second temperature and second load information of the target transformer within each second preset time period are also used as the comparison data. The comparison process between any comparison data and the comparison data is the same; only the data used for comparison is different.

[0147] Two comparison data are randomly selected from all the comparison data. If both comparison data can be used to compare with the comparison data and obtain abnormal information, when the abnormal information corresponding to the two comparison data both show that the target transformer has an operational abnormality, then it is determined that the target transformer has an abnormality. The target transformer will be marked with an abnormality and enter the handling process. At the same time, the oil temperature monitoring calculation will no longer perform pre-control analysis on the target transformer, nor will it use the target transformer as a comparison object for other transformers in the same station.

[0148] If either of the abnormal information corresponding to the two comparison data points indicates that the target transformer does not have any operational abnormalities, then it is determined that the target transformer does not have any abnormalities and there is no need to proceed with the handling process. The oil temperature monitoring and calculation will continue to perform pre-control analysis on the target transformer.

[0149] If one or both of the two sets of comparison data are unavailable for comparison with the original data (e.g., incomplete data), new comparison data can be selected from the remaining data until two suitable comparison data sets are chosen. These two sets of comparison data are then compared with the original data to determine whether maintenance personnel need to be notified for inspection.

[0150] Figure 4 A flowchart illustrating the transformer-based anomaly monitoring method provided in this application embodiment. Figure 4 ,like Figure 4 As shown, the above method includes:

[0151] S401. Obtain the first temperature information of the target transformer.

[0152] S402. Determine the target temperature from the first temperature information of the target transformer; the target temperature represents the temperature value of the target transformer last collected within the first preset time period.

[0153] For example, the time when the temperature value of the target transformer was last collected is determined from the first preset time period. The last sampling time is the current time, that is, the oil temperature of the target transformer sampled at the current time is taken as the target temperature.

[0154] S403. If the target temperature is greater than the first preset threshold, then generate fault information based on the target temperature; the fault information indicates that the target transformer has experienced a device failure.

[0155] For example, the first preset threshold is a defect temperature setpoint. If the target temperature is detected to be greater than the first preset threshold, that is, the target temperature is greater than the defect temperature setpoint. A fault message needs to be generated, indicating that the target transformer has experienced a equipment failure. In other words, the fault message indicates that the transformer has a defect and the defect handling process needs to be initiated.

[0156] The advantage of this approach is that it allows for real-time monitoring of the target transformer's temperature. When the temperature exceeds the set defect temperature, the defect handling process can be triggered immediately. This enables a rapid and direct response to serious anomalies, preventing the accident from escalating.

[0157] S404. Determine the fluctuation information based on the first temperature information of the target transformer; the fluctuation information represents the temperature change range of the target transformer within a first preset time period.

[0158] For example, fluctuation information is determined based on the maximum and minimum temperatures in the first temperature information of the target transformer. The fluctuation information represents the temperature change range of the target transformer within a first preset time period. For example, the fluctuation information is the absolute value of the difference between the maximum and minimum temperatures.

[0159] S405. If the fluctuation information meets the fourth preset condition, then an early warning information is generated based on the fluctuation information; the early warning information indicates that a temperature change occurs during the operation of the target transformer.

[0160] When the monitored fluctuation information meets the fourth preset condition, such as the fluctuation information exceeding the third preset threshold, an early warning message is generated based on the fluctuation information. This warning message indicates a sudden temperature change during the operation of the target transformer. For example, when the fluctuation information exceeds the third preset threshold (e.g., the third preset threshold ranges from 5 to 8 degrees Celsius), it is considered a significant change in the target transformer oil temperature, potentially indicating an abnormality in the temperature monitoring system or an urgent defect, requiring immediate attention. The generated early warning message, including the fluctuation information, is sent to maintenance personnel to promptly initiate equipment inspection and maintenance.

[0161] The advantage of this approach is that by monitoring the temperature fluctuations of the target transformer in real time, it is possible to detect and address emergency faults that could cause a sharp rise in temperature, such as sudden failure of the cooling system or a sudden short circuit inside the transformer. By monitoring the temperature change amplitude within a short time window, i.e., the fluctuation information, it is possible to immediately identify and issue an alarm in the initial extreme period of an anomaly, thereby improving the coverage and accuracy of transformer anomaly monitoring.

[0162] S406. If the first temperature information of the target transformer meets the first preset condition, then the first load information of the target transformer is obtained, as well as the first temperature information and the first load information of the preset transformer are obtained.

[0163] S407. Determine a first difference based on the first temperature information of the target transformer and the first temperature information of the preset transformer, and determine a second difference based on the first load information of the target transformer and the first load information of the preset transformer.

[0164] S408. Determine the abnormal information based on the first difference and the second difference.

[0165] Figure 5 This is a schematic diagram of the structure of the transformer-based anomaly monitoring device provided in the embodiments of this application, as shown below. Figure 5 As shown, the transformer-based anomaly monitoring device 50 provided in this embodiment includes:

[0166] The first acquisition module 501 is used to acquire the first temperature information of the target transformer; the first temperature information represents the temperature change of the transformer within a first preset time period.

[0167] The second acquisition module 502 is used to acquire the first load information of the target transformer if the first temperature information of the target transformer meets the first preset condition, and to acquire the first temperature information and the first load information of the preset transformer; the first load information represents the change of the transformer load within a first preset time period.

[0168] The first determining module 503 is used to determine a first difference based on the first temperature information of the target transformer and the first temperature information of the preset transformer, and to determine a second difference based on the first load information of the target transformer and the first load information of the preset transformer; the first difference represents the difference between the average temperature of the target transformer and the average temperature of the preset transformer within a first preset time period; the second difference represents the difference between the average load of the target transformer and the average load of the preset transformer within the first preset time period.

[0169] The second determining module 504 is used to determine abnormal information based on the first difference and the second difference; the abnormal information indicates whether the target transformer has an operational abnormality.

[0170] In one possible implementation, the first determining module 503 is further configured to:

[0171] Based on the first temperature information of the target transformer, the first average information of the target transformer is determined, and based on the first temperature information of the preset transformer, the first average information of the preset transformer is determined; the first average information represents the average temperature of the transformer within a first preset time period.

[0172] Based on the first load information of the target transformer, the second average information of the target transformer is determined, and based on the first load information of the preset transformer, the second average information of the preset transformer is determined; the second average information represents the average load of the transformer within a first preset time period.

[0173] The second difference is determined based on the second average information of the target transformer and the second average information of the preset transformer.

[0174] In one possible implementation, the second determining module 504 is further configured to:

[0175] If the first difference satisfies the second preset condition and the second difference satisfies the third preset condition, then the first ratio between the first difference and the first average information of the target transformer is determined, and the second ratio between the second difference and the second average information of the target transformer is determined.

[0176] Determine a third ratio between the first and second ratios, and based on the third ratio, determine the abnormal information of the target transformer.

[0177] In one possible implementation, the transformer-based anomaly monitoring device 50 further includes a third determining module, used for:

[0178] If the first difference satisfies the second preset condition, and the second difference does not satisfy the third preset condition, then the doubling information is determined based on the first difference; the doubling information represents the information obtained by doubling the first difference.

[0179] Based on the second difference, the reverse information is determined; the reverse information and the second difference are opposite numbers.

[0180] Based on the doubling and reversal information, identify abnormal information.

[0181] In one possible implementation, the transformer-based anomaly monitoring device 50 further includes a fourth determining module, used for:

[0182] If the first difference does not meet the second preset condition, then the second temperature information and the second load information of the target transformer are obtained; the second temperature information represents the temperature change of the transformer within the second preset time period; the second load information represents the load change of the transformer within the second preset time period; the second preset time period has the same length as the first preset time period, and the second preset time period is located before the first preset time period.

[0183] Based on the first temperature information and the second temperature information of the target transformer, a third difference is determined, and based on the first load information and the second load information of the target transformer, a fourth difference is determined; the third difference represents the difference between the average temperature of the target transformer in the first preset time period and the average temperature of the target transformer in the second preset time period; the fourth difference represents the difference between the average load of the target transformer in the first preset time period and the average load of the target transformer in the second preset time period.

[0184] The abnormal information is determined based on the third and fourth differences.

[0185] In one possible implementation, the transformer-based anomaly monitoring device 50 further includes a fifth determining module, used for:

[0186] Based on the first temperature information of the target transformer, the fluctuation information is determined; the fluctuation information represents the temperature change range of the target transformer within a first preset time period.

[0187] If the fluctuation information meets the fourth preset condition, then an early warning information is generated based on the fluctuation information; the early warning information indicates that a temperature change occurs during the operation of the target transformer.

[0188] In one possible implementation, the fifth determining module is also used for:

[0189] The target temperature is determined from the first temperature information of the target transformer; the target temperature represents the temperature value of the target transformer last collected within a first preset time period.

[0190] If the target temperature is greater than the first preset threshold, a fault message is generated based on the target temperature; the fault message indicates that the target transformer has experienced a device failure.

[0191] The transformer-based anomaly monitoring device provided in this embodiment can execute the method provided in the above-described method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0192] Figure 6 This is a schematic diagram of the structure of a transformer-based anomaly monitoring device provided in an embodiment of this application. Figure 6As shown, the transformer-based anomaly monitoring device 60 provided in this embodiment includes at least one processor 601 and a memory 602. Optionally, the transformer-based anomaly monitoring device 60 further includes a communication component 603. The processor 601, memory 602, and communication component 603 are connected via a bus.

[0193] In a specific implementation, at least one processor 601 executes computer execution instructions stored in memory 602, causing at least one processor 601 to perform the above-described method.

[0194] The specific implementation process of processor 601 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0195] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0196] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0197] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0198] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0199] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0200] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0201] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0202] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0203] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0204] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0205] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0206] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0207] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A transformer-based anomaly monitoring method, characterized in that, include: Obtain the first temperature information of the target transformer; The first temperature information represents the temperature change of the transformer within a first preset time period. If the first temperature information of the target transformer meets the first preset condition, then the first load information of the target transformer is obtained, and the first temperature information and the first load information of the preset transformer are obtained. The first load information represents the change in the transformer load within a first preset time period; A first difference is determined based on the first temperature information of the target transformer and the first temperature information of the preset transformer, and a second difference is determined based on the first load information of the target transformer and the first load information of the preset transformer. The first difference represents the difference between the average temperature of the target transformer and the average temperature of the preset transformer during the first preset time period; The second difference represents the difference between the average load of the target transformer and the average load of the preset transformer during the first preset time period; Based on the first difference and the second difference, anomaly information is determined; The abnormal information indicates whether the target transformer has any operational abnormalities.

2. The method according to claim 1, characterized in that, Based on the first temperature information of the target transformer and the first temperature information of the preset transformer, a first difference is determined, including: Based on the first temperature information of the target transformer, the first average information of the target transformer is determined, and based on the first temperature information of the preset transformer, the first average information of the preset transformer is determined; the first average information represents the average temperature of the transformer within a first preset time period. The first difference is determined based on the first average information of the target transformer and the first average information of the preset transformer.

3. The method according to claim 2, characterized in that, The second difference is determined based on the first load information of the target transformer and the first load information of the preset transformer, including: Based on the first load information of the target transformer, the second average information of the target transformer is determined, and based on the first load information of the preset transformer, the second average information of the preset transformer is determined; the second average information represents the average load of the transformer within a first preset time period. The second difference is determined based on the second average information of the target transformer and the second average information of the preset transformer.

4. The method according to claim 3, characterized in that, Based on the first difference and the second difference, abnormal information is determined, including: If the first difference satisfies the second preset condition and the second difference satisfies the third preset condition, then a first ratio between the first difference and the first average information of the target transformer is determined, and a second ratio between the second difference and the second average information of the target transformer is determined. A third ratio is determined between the first ratio and the second ratio, and the abnormal information of the target transformer is determined based on the third ratio.

5. The method according to claim 2, characterized in that, Also includes: If the first difference satisfies the second preset condition, and the second difference does not satisfy the third preset condition, then the doubling information is determined based on the first difference. The doubling information represents the information obtained by doubling the first difference; Based on the second difference, determine the reverse information; The reverse information and the second difference are positive and negative numbers respectively; The abnormal information is determined based on the doubling information and the reversal information.

6. The method according to claim 2, characterized in that, Also includes: If the first difference does not meet the second preset condition, then the second temperature information and the second load information of the target transformer are obtained; The second temperature information represents the temperature change of the transformer within a second preset time period; the second load information represents the load change of the transformer within a second preset time period; the second preset time period has the same length as the first preset time period, and the second preset time period is located before the first preset time period; A third difference is determined based on the first temperature information and the second temperature information of the target transformer, and a fourth difference is determined based on the first load information and the second load information of the target transformer. The third difference represents the difference between the average temperature of the target transformer during the first preset time period and the average temperature of the target transformer during the second preset time period. The fourth difference represents the difference between the average load of the target transformer during the first preset time period and the average load of the target transformer during the second preset time period; The abnormal information is determined based on the third and fourth differences.

7. The method according to any one of claims 1-6, characterized in that, Also includes: Based on the first temperature information of the target transformer, the fluctuation information is determined; The fluctuation information represents the temperature change amplitude of the target transformer within a first preset time period. If the fluctuation information meets the fourth preset condition, then an early warning message is generated based on the fluctuation information; The warning message indicates that a sudden temperature change occurred during the operation of the target transformer.

8. The method according to any one of claims 1-6, characterized in that, Also includes: The target temperature is determined from the first temperature information of the target transformer; The target temperature represents the temperature value of the target transformer last collected within the first preset time period. If the target temperature is greater than the first preset threshold, then fault information is generated based on the target temperature; The fault information indicates that the target transformer has experienced a device malfunction.

9. An anomaly monitoring device based on a transformer, characterized in that, include: The first acquisition module is used to acquire the first temperature information of the target transformer; The first temperature information represents the temperature change of the transformer within a first preset time period. The second acquisition module is used to acquire the first load information of the target transformer if the first temperature information of the target transformer meets the first preset condition, and to acquire the first temperature information and the first load information of the preset transformer. The first load information represents the change in the transformer load within a first preset time period; The first determining module is used to determine a first difference based on the first temperature information of the target transformer and the first temperature information of the preset transformer, and to determine a second difference based on the first load information of the target transformer and the first load information of the preset transformer; The first difference represents the difference between the average temperature of the target transformer and the average temperature of the preset transformer during the first preset time period; The second difference represents the difference between the average load of the target transformer and the average load of the preset transformer during the first preset time period; The second determining module is used to determine abnormal information based on the first difference and the second difference; The abnormal information indicates whether the target transformer has any operational abnormalities.

10. An anomaly monitoring device based on a transformer, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-8.

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