A method and system for monitoring abnormal operation of transformer

Abstract

The present invention relates to the technical field of transformer monitoring, and discloses a transformer operation abnormality monitoring method and system, the method comprising: obtaining the real-time operation parameters of the transformer, preprocessing the real-time operation parameters, and obtaining a real-time operation parameter sequence of several cycles; determining the average value, maximum value and minimum value of each parameter in the cycle in the real-time operation parameter sequence; determining whether the real-time operation parameter sequence of each cycle is an abnormal parameter sequence according to the maximum value and the minimum value; if the real-time operation parameter sequence is an abnormal parameter sequence, setting an abnormal correction factor for each parameter according to the difference between the average value and the maximum value or the minimum value; and correcting the abnormal parameter sequence according to the abnormal correction factor to realize abnormal monitoring of transformer operation. The present invention facilitates timely discovery of abnormalities by analyzing and processing the transformer parameters, ensures the accuracy of monitoring, and improves the operation reliability of the transformer and the overall stability of the power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of transformer monitoring, and in particular to a method and system for monitoring abnormal operation of a transformer. Background Art

[0002] With the rapid development and expansion of the power system, it is particularly important to ensure the stable operation of power equipment, especially key equipment such as transformers. During operation, the transformer may be affected by a variety of internal and external factors, causing its performance to gradually degrade or even fail, thus affecting the safe and stable operation of the entire power grid. Therefore, effective monitoring of transformer operation anomalies is of great significance for preventing large-scale power outages, reducing economic losses, and improving power supply reliability.

[0003] At present, the abnormal operation monitoring of transformers mainly relies on regular manual inspections and some online monitoring technologies. Although manual inspections can find some problems, they are inefficient and difficult to achieve real-time monitoring. Existing online monitoring technologies mostly rely on single sensor signals, such as temperature monitoring. Although these methods can provide certain information, they often have problems such as limited coverage and low early warning accuracy. Therefore, there is an urgent need for a transformer operation abnormality monitoring method and system that can integrate multiple monitoring data and realize comprehensive analysis and early warning of transformer operation abnormality monitoring. Summary of the invention

[0004] The purpose of the present invention is to provide a transformer operation abnormality monitoring method and system to solve the problems of low efficiency of manual inspection and difficulty in achieving real-time monitoring, while existing monitoring technologies mostly rely on a single sensor, have limited coverage, and low early warning accuracy.

[0005] The present invention provides a method for monitoring abnormal operation of a transformer, the method comprising:

[0006] Acquiring real-time operating parameters of the transformer, wherein the real-time operating parameters include current, voltage, temperature and vibration frequency;

[0007] Preprocessing the real-time operation parameters to obtain a real-time operation parameter sequence of several periods, wherein the preprocessing includes missing value processing, standardization processing, normalization processing and delimiting time periods;

[0008] Determine the average value, maximum value and minimum value of each parameter in the period of the real-time operating parameter sequence;

[0009] Determine whether the real-time operation parameter sequence of each cycle is an abnormal parameter sequence according to the maximum value and the minimum value;

[0010] If the real-time operating parameter sequence is an abnormal parameter sequence, an abnormal correction factor of each parameter is set according to the difference between the average value and the maximum value or the minimum value, and the abnormal correction factor includes a current abnormal correction factor, a voltage abnormal correction factor, a temperature abnormal correction factor and a vibration frequency abnormal correction factor;

[0011] The abnormal parameter sequence is corrected according to the abnormal correction factor to achieve abnormal monitoring of transformer operation.

[0012] Preferably, the method for defining a time period for the real-time operating parameter includes:

[0013] A voltage threshold is set;

[0014] Comparing the voltage threshold with the voltage to determine a time period corresponding to when the voltage is greater than the voltage threshold;

[0015] Determine the median time point of the time period, and determine the time point difference between adjacent median time points;

[0016] If the fluctuation range of the time point difference is within an acceptable range, a time period is defined according to the time point difference.

[0017] Preferably, determining whether the real-time operating parameter sequence of each cycle is an abnormal parameter sequence according to the maximum value and the minimum value includes:

[0018] The setting has a preset maximum value and a preset minimum value;

[0019] Compare the maximum value with the preset maximum value, compare the minimum value with the preset minimum value, and determine whether the real-time operation parameter sequence of each cycle is an abnormal parameter sequence according to the comparison result;

[0020] If the maximum value is greater than the preset maximum value, determining the real-time operation parameter sequence of the corresponding period as an abnormal parameter sequence;

[0021] If the maximum value is less than or equal to the preset maximum value, and the minimum value is less than the preset minimum value, then the real-time operation parameter sequence of the corresponding period is determined to be an abnormal parameter sequence;

[0022] If the maximum value is less than or equal to the preset maximum value, and the minimum value is greater than or equal to the preset minimum value, it is determined that the real-time operating parameter sequence of the corresponding period is not an abnormal parameter sequence.

[0023] Preferably, setting the abnormal correction factor of each parameter according to the difference between the average value and the maximum value or the minimum value includes:

[0024] determining a first difference between the average value and the maximum value, and determining a second difference between the average value and the minimum value;

[0025] Comparing the first difference with the second difference, and determining a correction difference according to the comparison result, wherein the correction difference includes a current correction difference, a voltage correction difference, a temperature correction difference, and a vibration frequency correction difference;

[0026] If the first difference is greater than or equal to the second difference, determining the corrected difference to be the first difference, and setting an abnormality correction factor according to the corrected difference;

[0027] If the first difference is smaller than the second difference, the corrected difference is determined to be the second difference, and an abnormality correction factor is set according to the corrected difference.

[0028] Preferably, setting the abnormality correction factor according to the correction difference includes:

[0029] A first preset current correction difference and a second preset current correction difference are set, wherein the first preset current correction difference is smaller than the second preset current correction difference;

[0030] comparing the current correction difference with the first preset current correction difference and the second preset current correction difference;

[0031] If the current correction difference is less than the first preset current correction difference, the current abnormality correction factor ka is determined to be the first preset current abnormality correction factor ka1, that is, ka=ka1;

[0032] If the current correction difference is greater than or equal to the first preset current correction difference, and the current correction difference is less than or equal to the second preset current correction difference, the current abnormality correction factor ka is determined to be the second preset current abnormality correction factor ka2, that is, ka=ka2;

[0033] If the current correction difference is greater than the second preset current correction difference, the current abnormality correction factor ka is determined to be the third preset current abnormality correction factor ka3, that is, ka=ka3, wherein ka1<ka2<ka3.

[0034] Preferably, setting the abnormality correction factor according to the correction difference includes:

[0035] A first preset voltage correction difference and a second preset voltage correction difference are set, wherein the first preset voltage correction difference is smaller than the second preset voltage correction difference;

[0036] comparing the voltage correction difference with the first preset voltage correction difference and the second preset voltage correction difference;

[0037] If the voltage correction difference is less than the first preset voltage correction difference, the voltage anomaly correction factor ku is determined to be the first preset voltage anomaly correction factor ku1, that is, ku=ku1;

[0038] If the voltage correction difference is greater than or equal to the first preset voltage correction difference, and the voltage correction difference is less than or equal to the second preset voltage correction difference, then the voltage abnormality correction factor ku is determined to be the second preset voltage abnormality correction factor ku2, that is, ku=ku2;

[0039] If the voltage correction difference is greater than the second preset voltage correction difference, the voltage anomaly correction factor ku is determined to be the third preset voltage anomaly correction factor ku3, that is, ku=ku3, wherein ku1<ku2<ku3.

[0040] Preferably, setting the abnormality correction factor according to the correction difference includes:

[0041] A first preset temperature correction difference and a second preset temperature correction difference are set, wherein the first preset temperature correction difference is smaller than the second preset temperature correction difference;

[0042] comparing the temperature correction difference with the first preset temperature correction difference and the second preset temperature correction difference;

[0043] If the temperature correction difference is less than the first preset temperature correction difference, the temperature anomaly correction factor kt is determined to be the first preset temperature anomaly correction factor kt1, that is, kt=kt1;

[0044] If the temperature correction difference is greater than or equal to the first preset temperature correction difference, and the temperature correction difference is less than or equal to the second preset temperature correction difference, the temperature anomaly correction factor kt is determined to be the second preset temperature anomaly correction factor kt2, that is, kt=kt2;

[0045] If the temperature correction difference is greater than the second preset temperature correction difference, the temperature anomaly correction factor kt is determined to be a third preset temperature anomaly correction factor kt3, that is, kt=kt3, wherein kt1<kt2<kt3.

[0046] Preferably, setting the abnormality correction factor according to the correction difference also includes:

[0047] A first preset vibration frequency correction difference and a second preset vibration frequency correction difference are set, wherein the first preset vibration frequency correction difference is smaller than the second preset vibration frequency correction difference;

[0048] comparing the vibration frequency correction difference with the first preset vibration frequency correction difference and the second preset vibration frequency correction difference;

[0049] If the vibration frequency correction difference is less than the first preset vibration frequency correction difference, the vibration frequency abnormality correction factor kv is determined to be the first preset vibration frequency abnormality correction factor kv1, that is, kv=kv1;

[0050] If the vibration frequency correction difference is greater than or equal to the first preset vibration frequency correction difference, and the vibration frequency correction difference is less than or equal to the second preset vibration frequency correction difference, then the vibration frequency abnormality correction factor kv is determined to be the second preset vibration frequency abnormality correction factor kv2, that is, kv=kv2;

[0051] If the vibration frequency correction difference is greater than the second preset vibration frequency correction difference, the vibration frequency abnormality correction factor kv is determined to be the third preset vibration frequency abnormality correction factor kv3, that is, kv=kv3, wherein kv1<kv2<kv3.

[0052] Preferably, the abnormal parameter sequence is corrected according to the abnormal correction factor, including:

[0053] The abnormal correction factor is used to correct the parameters corresponding to the abnormal correction factor respectively to obtain the abnormal value of the transformer, and the abnormality monitoring of the transformer operation is realized according to the abnormal value;

[0054] The outlier value is calculated according to the following formula:

[0055]

[0056] Where N is the number of abnormal parameter sequences, Fa is the abnormal value of the transformer, ku is the voltage anomaly correction factor, and U is the voltage anomaly correction factor. i It is represented as the voltage in the abnormal parameter sequence, ka is represented as the current abnormal correction factor, I i is represented by the current in the abnormal parameter sequence, kt is represented by the temperature anomaly correction factor, T i It is represented as the temperature in the abnormal parameter sequence, kv is represented as the vibration frequency abnormal correction factor, V i Expressed as the frequency of vibration in the anomalous parameter sequence.

[0057] The present invention also provides a transformer operation abnormality monitoring system, which is used to apply the above transformer operation abnormality monitoring method, and the system comprises:

[0058] A parameter acquisition module, wherein the parameter acquisition module is used to acquire real-time operating parameters of the transformer, wherein the real-time operating parameters include current, voltage, temperature and vibration frequency;

[0059] A preprocessing module, the preprocessing module is used to preprocess the real-time operation parameters to obtain a real-time operation parameter sequence of several cycles, the preprocessing includes missing value processing, standardization processing, normalization processing and delimiting time periods;

[0060] An abnormal parameter determination module, the abnormal parameter determination module is used to determine the average value, maximum value and minimum value of each parameter in the cycle of the real-time operation parameter sequence; and determine whether the real-time operation parameter sequence of each cycle is an abnormal parameter sequence according to the maximum value and the minimum value;

[0061] An abnormality monitoring module, wherein the abnormality monitoring module is used to set an abnormality correction factor for each parameter according to the difference between the average value and the maximum value or the minimum value when the real-time operating parameter sequence is an abnormal parameter sequence; and to correct the abnormal parameter sequence according to the abnormality correction factor to realize abnormal monitoring of transformer operation; wherein the abnormality correction factor includes a current abnormality correction factor, a voltage abnormality correction factor, a temperature abnormality correction factor and a vibration frequency abnormality correction factor.

[0062] Compared with the prior art, the beneficial effect of the present invention is that the present invention realizes abnormal monitoring of transformer operation by analyzing and processing the real-time operating parameters of the transformer, which is convenient for timely detection of abnormalities. At the same time, because the detection is performed based on multi-dimensional parameters, the accuracy of monitoring is effectively guaranteed, and the possibility of false alarms and missed alarms is reduced. The entire monitoring process of the present invention is automated intelligent monitoring without manual intervention, which not only reduces the workload of the staff and reduces the operation and maintenance costs, but also improves the accuracy of early warning, as well as the operational reliability of the transformer and the overall stability of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0064] Figure 1 The present invention is a flowchart of a method for monitoring abnormal transformer operation.

[0065] Figure 2 It is a functional block diagram of a transformer operation abnormality monitoring system of the present invention. DETAILED DESCRIPTION

[0066] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0067] With the rapid development and expansion of the power system, it is particularly important to ensure the stable operation of power equipment, especially key equipment such as transformers. During operation, the transformer may be affected by a variety of internal and external factors, causing its performance to gradually degrade or even fail, thus affecting the safe and stable operation of the entire power grid. Therefore, effective monitoring of transformer operation anomalies is of great significance for preventing large-scale power outages, reducing economic losses, and improving power supply reliability.

[0068] At present, the abnormal operation monitoring of transformers mainly relies on regular manual inspections and some online monitoring technologies. Although manual inspections can find some problems, they are inefficient and difficult to achieve real-time monitoring. Existing online monitoring technologies mostly rely on single sensor signals, such as temperature monitoring. Although these methods can provide certain information, they often have problems such as limited coverage and low early warning accuracy. Therefore, there is an urgent need for a transformer operation abnormality monitoring method and system that can integrate multiple monitoring data and realize comprehensive analysis and early warning of transformer operation abnormality monitoring.

[0069] like Figure 1 As shown, the present invention provides a method for monitoring abnormal operation of a transformer, the method comprising:

[0070] S1, obtaining real-time operating parameters of the transformer, wherein the real-time operating parameters include current, voltage, temperature and vibration frequency.

[0071] S2, preprocessing the real-time operation parameters to obtain a real-time operation parameter sequence of several periods, wherein the preprocessing includes missing value processing, standardization processing, normalization processing and delimiting time periods.

[0072] S3, determining the average value, maximum value and minimum value of each parameter in the period of the real-time operation parameter sequence.

[0073] S4, determining whether the real-time operating parameter sequence of each cycle is an abnormal parameter sequence according to the maximum value and the minimum value.

[0074] S5. If the real-time operating parameter sequence is an abnormal parameter sequence, an abnormal correction factor for each parameter is set according to the difference between the average value and the maximum value or the minimum value, and the abnormal correction factor includes a current abnormal correction factor, a voltage abnormal correction factor, a temperature abnormal correction factor and a vibration frequency abnormal correction factor.

[0075] S6, correcting the abnormal parameter sequence according to the abnormal correction factor to achieve abnormal monitoring of transformer operation.

[0076] Preferably, the preprocessing includes missing value processing, standardization processing, normalization processing and demarcating time periods.

[0077] In this embodiment, the real-time operating parameters can be obtained by testing and monitoring the transformer through different sensors. In the embodiment of the present application, preprocessing includes but is not limited to missing value processing, outlier processing, data smoothing, data standardization, feature selection and data balancing.

[0078] In this embodiment, since the magnitude and range scale of each feature are different, it is necessary to normalize the input parameters when processing the parameters. Data normalization can compress the data values ​​within the range of [0, 1] without changing the parameter distribution. This process ensures that the profile quantities of various features remain consistent, thereby enhancing the accuracy of the final monitoring and solving the problem of high error in monitoring abnormal transformer operation. Min-Max Scaling can be applied. The formula is:

[0079]

[0080] Among them, x norm is the normalized data, x i is the original data, x min is the minimum value in the original data set, x max is the maximum value in the original data set.

[0081] In some embodiments of the present application, the method for defining a time period for the real-time operating parameters includes: setting a voltage threshold; comparing the voltage threshold with the voltage, and determining a time period corresponding to when the voltage is greater than the voltage threshold; determining the median time point of the time period, and determining the time point difference between adjacent median time points; if the fluctuation range of the time point difference is within an acceptable range, defining a time period according to the time point difference.

[0082] In this embodiment, the real-time operating parameters are usually collected based on the time series, so the time period is defined to divide the continuous time series data into data points of fixed period. The time period can be selected according to the needs of the specific application. For example, the data points can be divided into every hour, every minute or every second, etc., to meet different time and analysis requirements. The voltage used by the transformer is an alternating voltage, and the voltage data is similar to a sine function and changes periodically. Therefore, the time period is determined by determining the time period corresponding to the voltage greater than the voltage threshold and the time point difference between the median time points of adjacent time periods. Among them, the minimum value of the acceptance range can be 95% of the time point difference, and the maximum value of the acceptance range can be 105% of the time point difference.

[0083] In some embodiments of the present application, determining whether the real-time operation parameter sequence of each cycle is an abnormal parameter sequence according to the maximum value and the minimum value includes: setting a preset maximum value and a preset minimum value; comparing the maximum value with the preset maximum value, and comparing the minimum value with the preset minimum value, and determining whether the real-time operation parameter sequence of each cycle is an abnormal parameter sequence according to the comparison result; if the maximum value is greater than the preset maximum value, determining that the real-time operation parameter sequence of the corresponding cycle is an abnormal parameter sequence; if the maximum value is less than or equal to the preset maximum value, and the minimum value is less than the preset minimum value, determining that the real-time operation parameter sequence of the corresponding cycle is an abnormal parameter sequence; if the maximum value is less than or equal to the preset maximum value, and the minimum value is greater than or equal to the preset minimum value, determining that the real-time operation parameter sequence of the corresponding cycle is not an abnormal parameter sequence.

[0084] In this embodiment, when judging the current, the maximum current value and the minimum current value in the real-time operation parameter sequence are obtained; and a preset maximum current value and a preset minimum current value are set, the maximum current value is compared with the preset maximum current value, and the minimum current value is compared with the preset minimum current value, and it is determined whether the real-time operation parameter sequence is an abnormal parameter sequence based on the comparison result; the judgment of other parameters, such as voltage, temperature and vibration frequency, is the same as the steps for judging the current.

[0085] In this embodiment, when the transformer is running stably, the current and voltage show periodic changes, and the maximum and minimum values ​​in each cycle are within a certain range. When the maximum and minimum values ​​are within the specified range, it means that the transformer is running stably, and the real-time operation parameter sequence of the corresponding cycle is not an abnormal parameter sequence; when the maximum and minimum values ​​are not within the specified range, it means that the transformer is running abnormally, and the real-time operation parameter sequence of the corresponding cycle is an abnormal parameter sequence. When judging whether the real-time operation parameter sequence is an abnormal parameter sequence, it is necessary to judge all parameters in the real-time operation parameter sequence. As long as one parameter does not meet the requirements, the entire real-time operation parameter sequence is an abnormal parameter sequence.

[0086] In some embodiments of the present application, the abnormal correction factor of each parameter is set according to the difference between the average value and the maximum value or the minimum value, including: determining a first difference between the average value and the maximum value, and determining a second difference between the average value and the minimum value; comparing the first difference with the second difference, and determining a correction difference according to the comparison result, the correction difference including a current correction difference, a voltage correction difference, a temperature correction difference and a vibration frequency correction difference; if the first difference is greater than or equal to the second difference, determining the correction difference as the first difference, and setting the abnormal correction factor according to the correction difference; if the first difference is less than the second difference, determining the correction difference as the second difference, and setting the abnormal correction factor according to the correction difference.

[0087] In this embodiment, the premise for setting the abnormal correction factor is that the real-time operating parameter sequence of the current cycle is an abnormal parameter sequence, and the abnormal correction factor of each parameter is set by the difference between the average value and the maximum value or the minimum value of the abnormal parameter sequence. The first difference between the average value and the maximum value, and the second difference between the average value and the minimum value are calculated. When the first difference is greater than or equal to the second difference, it means that the difference between the average value and the maximum value is greater than the difference between the average value and the minimum value; when the first difference is less than the second difference, it means that the difference between the average value and the maximum value is less than the difference between the average value and the minimum value. When the abnormal parameter sequence is subsequently corrected according to the abnormal correction factor, the difference with a larger difference should be selected to set the abnormal correction factor.

[0088] In some embodiments of the present application, an abnormal correction factor is set according to a correction difference, including: setting a first preset current correction difference and a second preset current correction difference, the first preset current correction difference being smaller than the second preset current correction difference; comparing the current correction difference with the first preset current correction difference and the second preset current correction difference; if the current correction difference is smaller than the first preset current correction difference, determining the current abnormality correction factor ka to be the first preset current abnormality correction factor ka1, i.e., ka=ka1; if the current correction difference is greater than or equal to the first preset current correction difference, and the current correction difference is less than or equal to the second preset current correction difference, determining the current abnormality correction factor ka to be the second preset current abnormality correction factor ka2, i.e., ka=ka2; if the current correction difference is greater than the second preset current correction difference, determining the current abnormality correction factor ka to be the third preset current abnormality correction factor ka3, i.e., ka=ka3, wherein ka1<ka2<ka3.

[0089] In this embodiment, several preset current correction differences are set, the current correction difference is compared with the first preset current correction difference and the second preset current correction difference, the range of the current correction difference is determined, and the corresponding preset current abnormal correction factor is determined to ensure the accuracy of abnormal analysis and improve the accuracy of transformer abnormal parameter correction.

[0090] In some embodiments of the present application, setting an abnormality correction factor according to a correction difference includes: setting a first preset voltage correction difference and a second preset voltage correction difference, the first preset voltage correction difference being smaller than the second preset voltage correction difference; comparing the voltage correction difference with the first preset voltage correction difference and the second preset voltage correction difference; if the voltage correction difference is smaller than the first preset voltage correction difference, determining the voltage abnormality correction factor ku to be the first preset voltage abnormality correction factor ku1, i.e., ku=ku1; if the voltage correction difference is greater than or equal to the first preset voltage correction difference, and the voltage correction difference is less than or equal to the second preset voltage correction difference, determining the voltage abnormality correction factor ku to be the second preset voltage abnormality correction factor ku2, i.e., ku=ku2; if the voltage correction difference is greater than the second preset voltage correction difference, determining the voltage abnormality correction factor ku to be the third preset voltage abnormality correction factor ku3, i.e., ku=ku3, wherein ku1<ku2<ku3.

[0091] In this embodiment, the voltage correction difference is positively correlated with the voltage anomaly correction factor. The larger the voltage correction difference, the larger the voltage anomaly correction factor. The present invention sets several preset voltage correction differences, compares the voltage-current correction difference with the first preset voltage correction difference and the second preset voltage correction difference, determines the range of the voltage correction difference, and determines the corresponding preset voltage anomaly correction factor.

[0092] In some embodiments of the present application, an abnormal correction factor is set according to a correction difference, including: setting a first preset temperature correction difference and a second preset temperature correction difference, the first preset temperature correction difference being smaller than the second preset temperature correction difference; comparing the temperature correction difference with the first preset temperature correction difference and the second preset temperature correction difference; if the temperature correction difference is smaller than the first preset temperature correction difference, determining the temperature abnormality correction factor kt to be the first preset temperature abnormality correction factor kt1, i.e., kt=kt1; if the temperature correction difference is greater than or equal to the first preset temperature correction difference, and the temperature correction difference is less than or equal to the second preset temperature correction difference, determining the temperature abnormality correction factor kt to be the second preset temperature abnormality correction factor kt2, i.e., kt=kt2; if the temperature correction difference is greater than the second preset temperature correction difference, determining the temperature abnormality correction factor kt to be the third preset temperature abnormality correction factor kt3, i.e., kt=kt3, wherein kt1<kt2<kt3.

[0093] In this embodiment, the temperature of the transformer during normal operation is affected by its insulation grade and cooling method. If the temperature of the transformer exceeds the allowable value for a long time, the insulating material will age due to long-term heat. The higher the temperature, the faster the insulation will age. This may cause insulation rupture or even electrical breakdown to cause a fault. At the same time, after the operating temperature of the insulation exceeds the allowable value, its service life will be shortened accordingly. The temperature of the transformer during operation needs to be strictly controlled to ensure its safe and stable operation and to extend its service life as much as possible. Therefore, temperature is also an important dimension for transformer abnormality monitoring. By comparing the temperature correction difference with the first preset temperature correction difference and the second preset temperature correction difference, the range of the temperature correction difference is determined, and a corresponding preset temperature abnormality correction factor is set in each range. The corresponding preset temperature abnormality correction factor is determined according to the range of the temperature correction difference to ensure the accuracy of subsequent transformer monitoring.

[0094] In some embodiments of the present application, setting an abnormality correction factor according to a correction difference also includes: setting a first preset vibration frequency correction difference and a second preset vibration frequency correction difference, wherein the first preset vibration frequency correction difference is less than the second preset vibration frequency correction difference; comparing the vibration frequency correction difference with the first preset vibration frequency correction difference and the second preset vibration frequency correction difference; if the vibration frequency correction difference is less than the first preset vibration frequency correction difference, determining the vibration frequency abnormality correction factor kv to be the first preset vibration frequency abnormality correction factor kv1, i.e., kv=kv1; if the vibration frequency correction difference is greater than or equal to the first preset vibration frequency correction difference, and the vibration frequency correction difference is less than or equal to the second preset vibration frequency correction difference, determining the vibration frequency abnormality correction factor kv to be the second preset vibration frequency abnormality correction factor kv2, i.e., kv=kv2; if the vibration frequency correction difference is greater than the second preset vibration frequency correction difference, determining the vibration frequency abnormality correction factor kv to be the third preset vibration frequency abnormality correction factor kv3, i.e., kv=kv3, wherein kv1<kv2<kv3.

[0095] In this embodiment, the transformer will generate vibrations during operation, and these vibration frequencies are usually related to the operating frequency of the transformer and its mechanical structure characteristics. Different types of transformers have different operating frequencies. The common industrial frequency AC frequency in daily life is 50Hz, and the corresponding low-frequency transformer operates at this frequency; while the operating frequency of the high-frequency transformer can reach tens of kHz to hundreds of kHz. When the transformer winding coil is passed through an alternating current, they will vibrate under the action of electromagnetic force in the magnetic field. The characteristics of this vibration are closely related to the mechanical structure of the transformer. Once the mechanical structure changes (for example, due to looseness or bulging), the vibration signal generated by the winding will change significantly. Therefore, in this embodiment, an analysis of the vibration frequency dimension is added. Monitoring these vibration frequencies can provide important information about the health of the transformer, which helps to detect potential problems in a timely manner and take maintenance measures.

[0096] In some embodiments of the present application, the abnormal parameter sequence is corrected according to the abnormal correction factor, including: using the abnormal correction factor to correct the parameters corresponding to the abnormal correction factor respectively to obtain the abnormal value of the transformer, and realizing abnormal monitoring of the transformer operation according to the abnormal value.

[0097] The outlier value is calculated according to the following formula:

[0098]

[0099] Where N is the number of abnormal parameter sequences, Fa is the abnormal value of the transformer, ku is the voltage anomaly correction factor, and U is the voltage anomaly correction factor.i It is represented as the voltage in the abnormal parameter sequence, ka is represented as the current abnormal correction factor, I i is represented by the current in the abnormal parameter sequence, kt is represented by the temperature anomaly correction factor, T i It is represented as the temperature in the abnormal parameter sequence, kv is represented as the vibration frequency abnormal correction factor, V i Expressed as the frequency of vibration in the anomalous parameter sequence.

[0100] The present invention also discloses a transformer operation abnormality monitoring system, which is used to apply the transformer operation abnormality monitoring method. The system comprises:

[0101] A parameter acquisition module, wherein the parameter acquisition module is used to acquire real-time operating parameters of the transformer, wherein the real-time operating parameters include current, voltage, temperature and vibration frequency.

[0102] A preprocessing module is used to preprocess the real-time operation parameters to obtain a real-time operation parameter sequence of several cycles, wherein the preprocessing includes missing value processing, standardization processing, normalization processing and demarcating time periods.

[0103] The abnormal parameter determination module is used to determine the average value, maximum value and minimum value of each parameter in the cycle of the real-time operation parameter sequence; and determine whether the real-time operation parameter sequence of each cycle is an abnormal parameter sequence based on the maximum value and the minimum value.

[0104] An abnormality monitoring module, wherein the abnormality monitoring module is used to set an abnormality correction factor for each parameter according to the difference between the average value and the maximum value or the minimum value when the real-time operating parameter sequence is an abnormal parameter sequence; and to correct the abnormal parameter sequence according to the abnormality correction factor to realize abnormal monitoring of transformer operation; wherein the abnormality correction factor includes a current abnormality correction factor, a voltage abnormality correction factor, a temperature abnormality correction factor and a vibration frequency abnormality correction factor.

[0105] In this embodiment, a transformer operation abnormality monitoring system is disclosed. By setting a parameter acquisition module, a preprocessing module, an abnormal parameter determination module and an abnormal monitoring module, the real-time operation parameters of the transformer are analyzed and processed to realize abnormal monitoring of the transformer operation, which is convenient for timely discovery of abnormalities, and at the same time increases the detection of multi-dimensional parameters, ensures the accuracy of monitoring, and reduces the possibility of false alarms and missed alarms. The entire monitoring process of the present invention is automated intelligent monitoring, without manual intervention, which not only reduces the workload of staff, reduces operation and maintenance costs, but also improves the accuracy of early warning, as well as the operational reliability of the transformer and the overall stability of the power grid.

[0106] In some embodiments of the present application, the parameter acquisition module includes a current sensor, a voltage sensor, a temperature sensor, and a vibration sensor.

[0107] The current sensor is used to detect the real-time current of the transformer, the voltage sensor is used to detect the real-time voltage of the transformer, the temperature sensor is used to detect the real-time temperature of the transformer, and the vibration sensor is used to detect the real-time vibration frequency of the transformer.

[0108] Preferably, all or some of the steps, systems, and functional modules / units in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. In a hardware implementation, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed by several physical components in cooperation. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or may be implemented as hardware, or may be implemented as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable storage medium, which may include a computer-readable storage medium (or a non-transitory medium) and a communication medium (or a temporary medium).

[0109] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

[0110] The system provided in the above embodiment is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the modules or steps in the embodiments of the present invention can be decomposed or combined. For example, the modules in the above embodiment can be combined into one module, or further divided into multiple sub-modules to complete all or part of the functions described above. The names of the modules and steps involved in the embodiments of the present invention are only for distinguishing the modules or steps, and are not regarded as improper limitations of the present invention.

[0111] Those skilled in the art should be able to appreciate that the modules and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, computer software or a combination of the two, and the programs corresponding to the software modules and method steps can be placed in random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium known in the technical field. In order to clearly illustrate the interchangeability of electronic hardware and software, the composition and steps of each example have been generally described in the above description according to the function. Whether these functions are performed in electronic hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

Claims

1. A method for monitoring abnormal operation of a transformer, characterized in that: The method comprises: Acquiring real-time operating parameters of the transformer, wherein the real-time operating parameters include current, voltage, temperature and vibration frequency; Preprocessing the real-time operation parameters to obtain a real-time operation parameter sequence of several periods, wherein the preprocessing includes missing value processing, standardization processing, normalization processing and delimiting time periods; Determine the average value, maximum value and minimum value of each parameter in the period of the real-time operating parameter sequence; Determine whether the real-time operation parameter sequence of each cycle is an abnormal parameter sequence according to the maximum value and the minimum value; If the real-time operating parameter sequence is an abnormal parameter sequence, an abnormal correction factor of each parameter is set according to the difference between the average value and the maximum value or the minimum value, and the abnormal correction factor includes a current abnormal correction factor, a voltage abnormal correction factor, a temperature abnormal correction factor and a vibration frequency abnormal correction factor; Correcting the abnormal parameter sequence according to the abnormal correction factor to achieve abnormal monitoring of transformer operation; The method for defining a time period for the real-time operating parameters includes: setting a voltage threshold; comparing the voltage threshold with the voltage, and determining a time period corresponding to when the voltage is greater than the voltage threshold; determining a median time point of the time period, and determining a time point difference between adjacent median time points; if a fluctuation range of the time point difference is within an acceptable range, defining a time period according to the time point difference.

2. The transformer operation abnormality monitoring method according to claim 1 is characterized in that: Determining whether the real-time operating parameter sequence of each cycle is an abnormal parameter sequence according to the maximum value and the minimum value includes: The setting has a preset maximum value and a preset minimum value; Compare the maximum value with the preset maximum value, compare the minimum value with the preset minimum value, and determine whether the real-time operation parameter sequence of each cycle is an abnormal parameter sequence according to the comparison result; If the maximum value is greater than the preset maximum value, determining the real-time operation parameter sequence of the corresponding period as an abnormal parameter sequence; If the maximum value is less than or equal to the preset maximum value, and the minimum value is less than the preset minimum value, then the real-time operation parameter sequence of the corresponding period is determined to be an abnormal parameter sequence; If the maximum value is less than or equal to the preset maximum value, and the minimum value is greater than or equal to the preset minimum value, it is determined that the real-time operating parameter sequence of the corresponding period is not an abnormal parameter sequence.

3. The transformer operation abnormality monitoring method according to claim 1, characterized in that: The abnormal correction factor of each parameter is set according to the difference between the average value and the maximum value or the minimum value, including: determining a first difference between the average value and the maximum value, and determining a second difference between the average value and the minimum value; Comparing the first difference with the second difference, and determining a correction difference according to the comparison result, wherein the correction difference includes a current correction difference, a voltage correction difference, a temperature correction difference, and a vibration frequency correction difference; If the first difference is greater than or equal to the second difference, determining the corrected difference to be the first difference, and setting an abnormality correction factor according to the corrected difference; If the first difference is smaller than the second difference, the corrected difference is determined to be the second difference, and an abnormality correction factor is set according to the corrected difference.

4. The transformer operation abnormality monitoring method according to claim 3 is characterized in that: The abnormal correction factor is set according to the correction difference, including: A first preset current correction difference and a second preset current correction difference are set, wherein the first preset current correction difference is smaller than the second preset current correction difference; comparing the current correction difference with the first preset current correction difference and the second preset current correction difference; If the current correction difference is less than the first preset current correction difference, the current abnormality correction factor ka is determined to be the first preset current abnormality correction factor ka1, that is, ka=ka1; If the current correction difference is greater than or equal to the first preset current correction difference, and the current correction difference is less than or equal to the second preset current correction difference, the current abnormality correction factor ka is determined to be the second preset current abnormality correction factor ka2, that is, ka=ka2; If the current correction difference is greater than the second preset current correction difference, the current abnormality correction factor ka is determined to be the third preset current abnormality correction factor ka3, that is, ka=ka3, wherein ka1<ka2<ka3.

5. The transformer operation abnormality monitoring method according to claim 4 is characterized in that: The abnormal correction factor is set according to the correction difference, including: A first preset voltage correction difference and a second preset voltage correction difference are set, wherein the first preset voltage correction difference is smaller than the second preset voltage correction difference; comparing the voltage correction difference with the first preset voltage correction difference and the second preset voltage correction difference; If the voltage correction difference is less than the first preset voltage correction difference, the voltage anomaly correction factor ku is determined to be the first preset voltage anomaly correction factor ku1, that is, ku=ku1; If the voltage correction difference is greater than or equal to the first preset voltage correction difference, and the voltage correction difference is less than or equal to the second preset voltage correction difference, then the voltage abnormality correction factor ku is determined to be the second preset voltage abnormality correction factor ku2, that is, ku=ku2; If the voltage correction difference is greater than the second preset voltage correction difference, the voltage anomaly correction factor ku is determined to be the third preset voltage anomaly correction factor ku3, that is, ku=ku3, wherein ku1<ku2<ku3.

6. The transformer operation abnormality monitoring method according to claim 5, characterized in that: The abnormal correction factor is set according to the correction difference, including: A first preset temperature correction difference and a second preset temperature correction difference are set, wherein the first preset temperature correction difference is smaller than the second preset temperature correction difference; comparing the temperature correction difference with the first preset temperature correction difference and the second preset temperature correction difference; If the temperature correction difference is less than the first preset temperature correction difference, the temperature anomaly correction factor kt is determined to be the first preset temperature anomaly correction factor kt1, that is, kt=kt1; If the temperature correction difference is greater than or equal to the first preset temperature correction difference, and the temperature correction difference is less than or equal to the second preset temperature correction difference, the temperature anomaly correction factor kt is determined to be the second preset temperature anomaly correction factor kt2, that is, kt=kt2; If the temperature correction difference is greater than the second preset temperature correction difference, the temperature anomaly correction factor kt is determined to be a third preset temperature anomaly correction factor kt3, that is, kt=kt3, wherein kt1<kt2<kt3.

7. The transformer operation abnormality monitoring method according to claim 6, characterized in that: The abnormal correction factor is set according to the correction difference, and also includes: A first preset vibration frequency correction difference and a second preset vibration frequency correction difference are set, wherein the first preset vibration frequency correction difference is smaller than the second preset vibration frequency correction difference; comparing the vibration frequency correction difference with the first preset vibration frequency correction difference and the second preset vibration frequency correction difference; If the vibration frequency correction difference is less than the first preset vibration frequency correction difference, the vibration frequency abnormality correction factor kv is determined to be the first preset vibration frequency abnormality correction factor kv1, that is, kv=kv1; If the vibration frequency correction difference is greater than or equal to the first preset vibration frequency correction difference, and the vibration frequency correction difference is less than or equal to the second preset vibration frequency correction difference, then the vibration frequency abnormality correction factor kv is determined to be the second preset vibration frequency abnormality correction factor kv2, that is, kv=kv2; If the vibration frequency correction difference is greater than the second preset vibration frequency correction difference, the vibration frequency abnormality correction factor kv is determined to be the third preset vibration frequency abnormality correction factor kv3, that is, kv=kv3, wherein kv1<kv2<kv3.

8. The transformer operation abnormality monitoring method according to claim 7, characterized in that: Correcting the abnormal parameter sequence according to the abnormal correction factor includes: The abnormal correction factor is used to correct the parameters corresponding to the abnormal correction factor respectively to obtain the abnormal value of the transformer, and the abnormality monitoring of the transformer operation is realized according to the abnormal value; The outlier value is calculated according to the following formula: Where N is the number of abnormal parameter sequences, Fa is the abnormal value of the transformer, ku is the voltage anomaly correction factor, and U is the voltage anomaly correction factor. i It is represented as the voltage in the abnormal parameter sequence, ka is represented as the current abnormal correction factor, I i is represented by the current in the abnormal parameter sequence, kt is represented by the temperature anomaly correction factor, T i It is represented as the temperature in the abnormal parameter sequence, kv is represented as the vibration frequency abnormal correction factor, V i Expressed as the frequency of vibration in the anomalous parameter sequence.

9. A transformer operation abnormality monitoring system, used for applying the transformer operation abnormality monitoring method according to any one of claims 1 to 8, characterized in that: The system comprises: A parameter acquisition module, wherein the parameter acquisition module is used to acquire real-time operating parameters of the transformer, wherein the real-time operating parameters include current, voltage, temperature and vibration frequency; A preprocessing module, the preprocessing module is used to preprocess the real-time operation parameters to obtain a real-time operation parameter sequence of several cycles, the preprocessing includes missing value processing, standardization processing, normalization processing and delimiting time periods; An abnormal parameter determination module, the abnormal parameter determination module is used to determine the average value, maximum value and minimum value of each parameter in the cycle of the real-time operation parameter sequence; and determine whether the real-time operation parameter sequence of each cycle is an abnormal parameter sequence according to the maximum value and the minimum value; An abnormality monitoring module, wherein the abnormality monitoring module is used to set an abnormality correction factor for each parameter according to the difference between the average value and the maximum value or the minimum value when the real-time operating parameter sequence is an abnormal parameter sequence; and to correct the abnormal parameter sequence according to the abnormality correction factor to realize abnormal monitoring of transformer operation; wherein the abnormality correction factor includes a current abnormality correction factor, a voltage abnormality correction factor, a temperature abnormality correction factor and a vibration frequency abnormality correction factor.

Images