CN116660667A - Transformer abnormality monitoring method and system - Google Patents
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
- Y04S10/52—Outage or fault management, e.g. fault detection or location
Abstract
The application relates to the field of digital data processing, in particular to a transformer abnormality monitoring method and a system, wherein the method comprises the following steps: acquiring three-phase voltage and three-phase current data of a transformer, analyzing the acquired data, and determining the period time and the constant degree of each moment in the period; calculating the instability of each period based on the constancy of each moment; calculating the time offset of the period based on the time corresponding to the maximum current value, the minimum current value, the maximum voltage value and the minimum voltage value in the period; calculating the distortion degree between adjacent periods based on the instability degree and the moment offset degree of the adjacent periods; determining a preset k value in an LOF algorithm based on the distortion degree of adjacent periods; and based on a preset k value, performing fault judgment on the abnormality of the transformer by using an LOF algorithm. According to the method, namely the system, provided by the embodiment of the application, the faults of the transformer can be identified in real time.
Description
Technical Field
The application relates to the field of digital data processing, in particular to a transformer abnormality monitoring method and system.
Background
Modern economies have evolved without the availability of electrical energy, which is delivered from a power station to various locations via an electrical power system. The most important transformer in the power system is a transformer which is used as transfer equipment for power transmission, and the existence of the transformer is not avoided in each link. The main functions of the transformer are as follows: voltage transformation, current transformation, impedance transformation, isolation, voltage stabilization, etc. The transformer is basic equipment for power transmission and distribution, is widely applied to the fields of industry, agriculture, traffic, urban communities and the like, and has important significance for the development of national economy in terms of safety and stability.
Once the transformer fails, the transformer is not beneficial to daily life convenience, and even threatens personal safety. At present, a method for detecting faults of a transformer in a power system is single, and is basically characterized in that the faults are detected by manual inspection, time and labor are wasted, severe weather such as rainy and snowy days is particularly met, the faults cannot be timely and accurately judged by the manual inspection, the faults are often diagnosed after the faults occur, the fault is identified by going to the field, the fault identification time rate is low, and the diagnosis is often dependent on manual experience.
Disclosure of Invention
Based on the above, it is necessary to provide a method and a system for monitoring the abnormality of a transformer, which are necessary for solving the problems that the existing method for detecting the fault of the transformer in the power system cannot judge the occurrence of the fault timely and accurately, and often, the fault is diagnosed on site after the occurrence of the fault, and the time rate of fault identification is low.
The first aspect of the present application provides a method for monitoring an abnormality of a transformer, which is applied to a system for monitoring an abnormality of a transformer, and includes:
acquiring three-phase voltage and three-phase current data of a transformer, analyzing the acquired data, and determining the period time and the constant degree of each moment in the period; wherein, the constant degree is used for representing the sum of the voltage value and the current value at a certain moment;
calculating the instability of each period based on the constancy of each moment; the instability is used for representing the deviation degree of data corresponding to each acquisition time in the period and the same constant value;
calculating the time offset of the period based on the time corresponding to the maximum current value, the minimum current value, the maximum voltage value and the minimum voltage value in the period;
calculating the distortion degree between adjacent periods based on the instability degree and the moment offset degree of the adjacent periods;
determining a preset k value in an LOF algorithm based on the distortion degree of adjacent periods;
and based on a preset k value, performing fault judgment on the abnormality of the transformer by using an LOF algorithm.
In one of the embodiments, in the step of calculating the instability of each cycle based on the constancy of the respective moments;
the average value of the constant degree in the period is taken as a constant value in the period, and the instability is used for representing the deviation degree of the constant degree and the average value of the constant degree at each moment in the period.
In one embodiment, the step of calculating the instability of each cycle based on the constancy of each moment is specifically:
the average value of the constancy over the period is calculated first, and then the instability of the period is calculated based on the difference between the constancy at each time and the average value of the constancy.
In one embodiment, the step of calculating the time offset of the period based on the time corresponding to the maximum current value, the minimum current value, the maximum voltage value, and the minimum voltage value specifically includes:
and calculating the time offset of the period according to the time difference between the time when the maximum voltage value is located and the time when the minimum current value is located and the time difference between the time when the minimum voltage value is located and the time when the maximum current value is located.
In one embodiment, the calculating the time offset of the period according to the time difference between the time when the maximum voltage value is located and the time when the minimum current value is located and the time difference between the time when the minimum voltage value is located and the time when the maximum current value is located specifically includes:
and respectively calculating the time difference between the time at which the maximum voltage value is positioned and the time at which the minimum current value is positioned, and taking the sum of the time differences as the time offset of the corresponding period after the time difference between the time at which the minimum voltage value is positioned and the time at which the maximum current value is positioned.
In one embodiment, the step of calculating the distortion degree between adjacent periods based on the instability degree and the time offset degree of the adjacent periods specifically includes:
and calculating the product of the instability degree of the adjacent time and the time offset degree, and subtracting the absolute value to obtain the distortion degree of the adjacent two periods.
In one embodiment, when calculating the distortion degree of two adjacent periods, the time offset is added to the parameter adjustment factor, and then multiplied by the instability, and the parameter adjustment factor is an arbitrary constant.
In one embodiment, the step of determining the preset k value in the LOF algorithm according to the distortion degree of the adjacent period specifically includes:
firstly, the distortion degree of adjacent periods is normalized to obtain a normalized value, and then a preset k value is calculated according to the normalized value and a preset constant value.
In one embodiment, the step of performing fault determination on the abnormality of the transformer by using the LOF algorithm based on the preset k value specifically includes:
using LOF algorithm for each period to obtain local abnormal factor of each data;
if the local abnormal factor is greater than 1, the transformer has a fault at the acquisition time corresponding to the data; if the local abnormal factor is less than or equal to 1, the transformer works normally at the acquisition time corresponding to the data.
The second aspect of the present application provides a transformer abnormality monitoring system, comprising a data acquisition analysis section, an instability analysis section, a time offset analysis section, a distortion analysis section, a k value determination section, and an abnormality judgment section, wherein:
the data acquisition and analysis component is used for acquiring three-phase voltage and three-phase current data of the transformer, analyzing the acquired data and determining the period time and the constancy of each moment in the period; wherein, the constant degree is used for representing the sum of the voltage value and the current value at a certain moment;
the instability analyzing part is used for calculating the instability of each period based on the constancy of each moment; the instability is used for representing the deviation degree of data corresponding to each acquisition time in the period and the same constant value;
the time offset analysis component is used for calculating the time offset of the period based on the time corresponding to the maximum current value, the minimum current value, the maximum voltage value and the minimum voltage value in the period;
the distortion degree analysis component is used for calculating the distortion degree between adjacent periods based on the instability degree and the moment offset degree of the adjacent periods;
the k value determining part is used for determining a preset k value in an LOF algorithm based on the distortion degree of adjacent periods;
the abnormality judgment part is used for carrying out fault judgment on the abnormality of the transformer by using an LOF algorithm based on a preset k value.
According to the transformer anomaly monitoring method and system, the collected current and voltage data are analyzed, the instability is obtained based on the data analysis in the period, the distortion degree of the adjacent period is determined based on the instability of the adjacent period, the preset k value in the LOF algorithm is determined based on the distortion degree of the adjacent period, and an appropriate preset k value is calculated for each period, so that whether abnormal data exist in the period and whether the period is distorted can be identified, whether the transformer fails or not and in which period the transformer fails can be judged, and the transformer failure can be identified in real time.
Further, whether the fault is a short-term fault or a cross-period fault can be determined according to the instability and the distortion of the adjacent period, and whether the fault is a fault corresponding to waveform translation or a fault corresponding to waveform distortion can be determined according to the distortion value of the fault period.
Drawings
FIG. 1 is a flow chart of a transformer anomaly monitoring method according to an embodiment of the present application;
fig. 2 is a frame structure diagram of a transformer abnormality monitoring system according to an embodiment of the present application.
Detailed Description
In order that the application may be readily understood, a more complete description of the application will be rendered by reference to the appended drawings. The drawings illustrate preferred embodiments of the application. This application may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the description of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
Referring to fig. 1, a schematic flow chart illustrating a transformer abnormality monitoring method according to an embodiment of the present application is shown, where the transformer abnormality monitoring method according to the embodiment of the present application is executed by a transformer abnormality monitoring system, and the transformer abnormality monitoring system can analyze changes of voltage and current in transformer data, automatically determine a K value in an LOF algorithm, and further determine whether the transformer is abnormal or not by using the LOF algorithm. The transformer abnormality monitoring system can be an integrated system or a chip for controlling the operation of the transformer abnormality monitoring system. Therefore, hereinafter, when referring to an operation performed by the transformer abnormality monitoring system, it may also be understood as an operation performed by a chip controlling the operation of the transformer abnormality monitoring system.
A method for monitoring an abnormality of a transformer as shown in fig. 1 may include steps 101 to 106, which are described in detail below.
101: acquiring three-phase voltage and three-phase current data of a transformer, analyzing the acquired data, and determining the period time and the constant degree of each moment in the period;
according to the embodiment of the application, a voltage transformer or a capacitance voltage sensor can be arranged at the three-phase voltage output end of the transformer and used for collecting three-phase voltage signals; and a current transformer is arranged on a three-phase input line of the transformer and is used for collecting three-phase current signals.
The collection of the three-phase voltage and the three-phase current needs to be strictly synchronized to ensure the accuracy of the subsequent phase angle and waveform analysis. If multiple acquisition channels are used, it is also necessary to ensure synchronous acquisition between the channels. The collection can be real-time collection or can be carried out according to a preset time interval. When the acquisition is performed at preset time intervals, it is preferable to use shorter time intervals in order to capture the instantaneous imbalance condition, for example, data acquired every 0.5 s. The three-phase voltage and three-phase current data of the transformer are continuously collected and analyzed, so that the generation and development of the voltage/current unbalance condition are monitored in real time.
When the transformer operates normally, the voltage and current of the transformer can show a symmetrical sine wave; when the transformer fails, the waveform and amplitude of the current and voltage are unbalanced. For two sine waves symmetrical about the x-axis, the sum of the voltage and current values at the same instant is a fixed value, on the basis of which the concept of a constant is defined, which is used to characterize the sum of the voltage and current values at a certain instant.
Ideally, the sum of the voltage value and the current value at different times is the same value. Considering that the transmission of voltage and current is affected by various environmental factors and the loss in transmission is different under the actual working environment, the sum of the voltage value and the current value at different moments is difficult to be the same value, but the sum is close to the same value under the condition that no fault occurs. That is, in the absence of a fault, the constancy at different times is typically close to the same value. Based on such characteristics, series data analysis can be performed on a constant basis to determine whether or not a fault has occurred at a certain time.
Based on the periodically changing characteristic of the sine wave, the cycle time can be identified first when the collected voltage and current are analyzed, and then the analysis can be performed according to the cycle. For example, the degree of constancy at different times in each cycle is calculated, and series of calculations are performed based on the degree of constancy to perform failure analysis.
According to the embodiment of the application, the calculation formula of the constant degree C at a certain moment is as follows:
in the method, in the process of the application,the constant degree of the jth moment of the a-th period; />Is the voltage value at the j-th moment of the a-th period,the current value at the j-th time of the a-th cycle.
It is understood that in this context, a so-called time of day is a data acquisition time, e.g. voltage and current data is acquired every 0.5 seconds, then adjacent times are spaced 0.5 seconds apart.
After the constant degree is calculated, data analysis can be performed on the basis of the constant degree, and whether faults occur in the period time or not is recognized according to the period.
102: calculating the instability of each period based on the constancy of each moment;
based on the characteristic that the sine wave of the voltage and the current is symmetrical about the x-axis, the sum of the voltage value and the current value should be close to the same value at different moments, i.e. the constant approaches a constant value, if it deviates excessively from which an imbalance situation may occur. According to the embodiment of the application, the degree of deviation of the data corresponding to each acquisition time in the period from the same constant value is defined as the instability. Since the degree of constancy characterizes the sum of the current value and the voltage value, according to an embodiment of the present application, the degree of instability of each cycle is calculated based on the degree of constancy at each time, and correspondingly, the degree of instability is used to characterize the degree of deviation of the degree of constancy at each time from the same constant.
Since the analysis is performed periodically, and the difference of the external environment at each moment may cause the difference of the collected current value and the collected voltage value, it is difficult to separately determine a constant value for each period. According to the embodiment of the application, the average value of the constant degree in the period is taken as a constant value in the period, and the instability is used for representing the deviation degree of the constant degree and the average value of the constant degree at each moment in the period.
Specifically, in calculating the unstable concentration of each cycle based on the degree of constancy at each time, the degree of constancy average value in the cycle is calculated first, and then the degree of instability of the cycle is calculated based on the difference between the degree of constancy at each time and the degree of constancy average value.
According to an embodiment of the present application, the period instability S is calculated as follows:
in the method, in the process of the application,is the instability of the a-th period, because the voltage value and the current value show a symmetrical shape, and the sum of the voltage value and the current value of the transformer at different times is not much different; />Is the constant of the jth data of the a-th period; />Is the average of the n constancy of the a-th period.
According to the above, whenThe larger the constant degree is, the more discrete the voltage value and the current value acquired at each moment are, the more the voltage value and the current value deviate from a fixed value, the instability degree is +.>The larger. The greater the degree of instability, the greater the degree to which the degree of constancy within the cycle deviates from a fixed constant value, the more likely the transformer is to fail within the a-th cycle.
103: calculating the time offset of the period based on the time corresponding to the maximum current value, the minimum current value, the maximum voltage value and the minimum voltage value in the period;
since both the voltage and the current exhibit a sinusoidal waveform, the sinusoidal waveform is characterized by a periodic variation. Thus, by analyzing the collected current value and voltage value, the maximum current value, the minimum current value, the maximum voltage value, and the minimum voltage value in the period can be identified. The maximum current value and the minimum current value correspond to the wave crest and the wave trough of the current sine wave respectively, and the maximum voltage value and the minimum voltage value correspond to the wave crest and the wave trough of the voltage sine wave respectively.
Since the sine waves of the voltage and the current are symmetrical about the x-axis, the maximum value of the voltage and the minimum value of the current should theoretically correspond in one period and both should be at the same time. Similarly, the minimum value of the voltage corresponds to the maximum value of the current, and both are at the same time. Thus, it is possible to calculate the time shift degree of the cycle based on such correspondence relation that the maximum value and the minimum value of the current and the voltage are at the same time, and determine whether or not there is a failure in the cycle using the time shift degree.
According to the embodiment of the application, the time offset of the period is calculated based on the time corresponding to the maximum current value, the minimum current value, the maximum voltage value and the minimum voltage value, specifically:
and calculating the time offset of the period according to the time difference between the time when the maximum voltage value is located and the time when the minimum current value is located and the time difference between the time when the minimum voltage value is located and the time when the maximum current value is located.
Specifically, the time difference between the time when the maximum voltage value is located and the time when the minimum current value is located and the time difference between the time when the minimum voltage value is located and the time when the maximum current value is located are calculated respectively, and then the sum of the two time differences is used as the time offset of the corresponding period. According to an embodiment of the present application, the calculation formula of the time offset Q of a certain period is as follows:
a time offset for the a-th cycle; />Is the time value corresponding to the minimum voltage value in the a-th period;a time value corresponding to the maximum current value; />Is the time value corresponding to the maximum voltage value in the a-th period; />The time value corresponding to the minimum current value.
Since the voltage is the maximum value, the current should be the corresponding minimum value, and both should be at the same time, and for the data obtained from the transformer, both should theoretically be the data collected at the same collection time. So based on the above calculation, if the transformer is operating normallyAnd->Both are 0, if there is an abnormality, if there is a value other than 0 in both, the time offset is not 0, and the transformer may malfunction.
104: calculating the distortion degree between adjacent periods based on the instability degree and the moment offset degree of the adjacent periods;
when the transformer has a fault, the fault may be a single period, or a period shift may occur, or the size of the period may be distorted. The instability and the time offset are mainly analyzed for data in a single period, and are used for judging whether faults exist in the period. The period shift can be determined by comparing the instability of adjacent periods with the time shift.
When a period shift occurs, the waveform of the voltage and current is expressed as: the shift of the sinusoidal image, i.e. the period is unchanged and the amplitude is unchanged, only the shift is generated. At this time, the voltages and currents of adjacent cycles may be analyzed for instability and temporal offset to identify whether offset or local distortion.
When one sine in the sine graph generates translation, the numerical value in the period is stable, namely when the image generates translation, the image in each period is stable, the constant degree shows periodic variation, and the instability degree of each period is equal. Based on this, it can be judged whether the voltage and current of the transformer exhibit an offset phenomenon or a local distortion by the instability of the adjacent periods.
According to the embodiment of the application, the distortion degree of the adjacent period is determined according to the instability degree and the time offset degree of the adjacent period, and then the offset and the local distortion are distinguished according to the distortion degree of the adjacent period. Specifically, the product of the instability of adjacent time and the time offset is calculated, and then the absolute value is subtracted, so that the distortion degree of two adjacent periods is obtained.
In some embodiments, the time offset may be added to a parameter adjustment factor, which may be any constant, and multiplied by the instability. The parameter adjusting factors are added mainly to prevent nonsensical calculation of adjacent period distortion degrees caused by 0 of time offset, and the parameter adjusting factors are added to the time offset degrees of the front period and the rear period, so that the calculation result of the distortion degrees is not affected.
According to the embodiment of the application, the distortion degree D of the adjacent period is calculated as follows:
in the method, in the process of the application,instability for the a-th cycle; />Is the aThe time offset of the period; />The parameter is an arbitrary constant, for example, the value is 1; />Is the instability of the p-th cycle; />The time offset is the p-th period; the product of the instability of the a-th period and the time offset is compared with the absolute value of the difference between the two periods, and the total number of the two periods is 2, so that m is 2.
When the waveform diagram of current and voltage has a shift phenomenon, the instability and the time offset of each period are approximately the same, soSmaller, the distortion degree of adjacent periods is smaller. If the image is distorted, the instability is large in some periods, and the instability is small in the other periods without distortionThe distortion degree of adjacent periods is larger. Therefore, the greater the distortion degree of the adjacent period, the greater the possibility that the waveform patterns of the current and the voltage are distorted.
105: determining a preset k value in an LOF algorithm based on the distortion degree of adjacent periods;
and the LOF algorithm is used for calculating the voltage value and the current value in each period, and the LOF method traverses the whole data set to calculate the LOF value of each point in the process of detecting the outlier, so that the algorithm operation speed is low. Meanwhile, the number of the normal points of the data is generally far more than that of the outliers, and the LOF method judges the outlier degree by comparing the LOF values of the data points, so that a large amount of unnecessary calculation is generated, the time cost is too high, and the k value of the kth reachable distance in the LOF algorithm is improved.
The calculation of the LOF is greatly affected by the selection of the preset k value, and the root cause is that the distinction between the abnormal data and the normal data is not obvious enough, that is, if a small amount of abnormal values are mixed in a large amount of normal data in a certain area, the proper k value is difficult to select.
According to the embodiment of the application, the preset k value in the LOF algorithm is determined according to the distortion degree of the adjacent period. Specifically, firstly, the distortion degree of adjacent periods is normalized to obtain a normalized value, and then a preset k value is calculated according to the normalized value and a preset constant value. The k value in the LOF algorithm has an empirical value, and the preset constant is generally 10.
According to an embodiment of the application, the preset k value in the LOF algorithmThe calculation formula is as follows:
wherein D is the distortion degree of adjacent periods,the normalized value is obtained by normalizing the adjacent period distortion degree; />For preset residency, check value 10 is taken.
Because the smaller the k value is in a certain range in the LOF algorithm, the larger the value of the local outlier factor is, so that when the density of the outlier is increased, the k value is correspondingly reduced, and a better effect can be obtained. When the adjacent period distortion degree D is larger,smaller (less)>The smaller the new k value +.>The smaller. The larger the distortion degree of the adjacent period is, the smaller the k value is, representing the transformation in the corresponding periodThe abnormal condition exists, the density of abnormal points is increased at the moment, the small k selected can effectively identify the real abnormal points, and if the k value is larger, the abnormal points are possibly missed because of being denser, so that the accuracy of the LOF algorithm is reduced. The above procedure enables a suitable preset k value to be reached for each cycle.
106: and based on a preset k value, performing fault judgment on the abnormality of the transformer by using an LOF algorithm.
After calculating the preset k value of each period, LOF algorithm is used for each period to obtain the local anomaly factor of each data. Judging whether the transformer has faults or not at the acquisition time of the data according to the local abnormal factors. If the local abnormal factor is greater than 1, the transformer is considered to have faults at the time of data acquisition; if the local abnormal factor is less than or equal to 1, the transformer is considered to work normally at the time of data acquisition.
According to the transformer anomaly monitoring method and system, the collected current and voltage data are analyzed, the instability is obtained based on the data analysis in the period, the distortion degree of the adjacent period is determined based on the instability of the adjacent period, the preset k value in the LOF algorithm is determined based on the distortion degree of the adjacent period, and an appropriate preset k value is calculated for each period, so that whether the anomaly data exist in the period and whether the period is distorted can be identified, and whether the transformer fails or not and in which period the transformer fails or not can be judged.
Further, whether the fault is a short-term fault or a cross-period fault can be determined according to the instability and the distortion of the adjacent period, and whether the fault is a fault corresponding to waveform translation or a fault corresponding to waveform distortion can be determined according to the distortion value of the fault period.
It should be noted that, for simplicity of description, the method embodiments are shown as a series of acts, but it should be understood by those skilled in the art that the embodiments are not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the embodiments. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred embodiments, and that the acts are not necessarily required by the embodiments of the application.
Referring to fig. 2, the present application further provides a transformer abnormality monitoring system 20, where the transformer abnormality monitoring system 20 includes a data acquisition analysis unit 210, an instability analysis unit 220, a time offset analysis unit 230, a distortion analysis unit 240, a k value determination unit 250, and an abnormality determination unit 260, where:
the data acquisition and analysis unit 210 is configured to acquire three-phase voltage and three-phase current data of the transformer, analyze the acquired data, and determine a period time and a constant degree of each moment in the period; wherein, the constant degree is used for representing the sum of the voltage value and the current value at a certain moment;
the instability analyzing unit 220 is configured to calculate an instability of each cycle based on a constant degree at each time; the instability is used for representing the deviation degree of data corresponding to each acquisition time in the period and the same constant value;
the time offset analysis unit 230 is configured to calculate a time offset of the period based on a time corresponding to the maximum current value, the minimum current value, the maximum voltage value, and the minimum voltage value in the period;
the distortion degree analysis unit 240 is configured to calculate a distortion degree between adjacent periods based on the instability degree and the time offset degree of the adjacent periods;
the k value determining unit 250 is configured to determine a preset k value in the LOF algorithm based on the distortion degree of the adjacent periods;
the abnormality determining unit 260 is configured to perform fault determination on the abnormality of the transformer using an LOF algorithm based on a preset k value.
Wherein the instability analyzing unit 220 uses the average value of the constant degree in the period as a constant value in the period when calculating the instability of each period based on the constant degree at each time, and the instability is used to characterize the deviation degree of the constant degree at each time in the period from the average value of the constant degree.
In some embodiments, the instability analysis component 220 is specifically configured to: the average value of the constancy over the period is calculated first, and then the instability of the period is calculated based on the difference between the constancy at each time and the average value of the constancy.
In some embodiments, the time offset analysis component 230 is specifically configured to: and calculating the time offset of the period according to the time difference between the time when the maximum voltage value is located and the time when the minimum current value is located and the time difference between the time when the minimum voltage value is located and the time when the maximum current value is located. Specifically, the time difference between the time when the maximum voltage value is located and the time when the minimum current value is located and the time difference between the time when the minimum voltage value is located and the time when the maximum current value is located are calculated respectively, and then the sum of the two time differences is used as the time offset of the corresponding period.
In some embodiments, the distortion analyzing unit 240 is specifically configured to calculate the product of the instability of adjacent time and the offset of time, and then subtract the absolute value, so as to obtain the distortion of two adjacent periods.
In some embodiments, when calculating the distortion degree of two adjacent periods, the time offset is added to the parameter adjustment factor, and then multiplied by the instability, and the parameter adjustment factor is an arbitrary constant.
In some embodiments, the k-value determining unit 250 is specifically configured to: firstly, the distortion degree of adjacent periods is normalized to obtain a normalized value, and then a preset k value is calculated according to the normalized value and a preset constant value.
In some embodiments, the anomaly determination unit 260 is specifically configured to:
using LOF algorithm for each period to obtain local abnormal factor of each data;
judging whether the transformer has faults or not at the acquisition time of the data according to the local abnormal factors; if the local abnormal factor is greater than 1, the transformer is considered to have faults at the time of data acquisition; if the local abnormal factor is less than or equal to 1, the transformer is considered to work normally at the time of data acquisition.
An embodiment of the application also provides a machine-readable storage medium, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the method of any of the embodiments described above.
The components/modules/units of the system/computer apparatus integration, if implemented as software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, the present application may also be implemented by implementing all or part of the flow of the method of the above embodiment, or by instructing the relevant hardware by a computer program, where the computer program may be stored in a computer readable storage medium, and where the computer program, when executed by a processor, may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable storage medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a Read-only memory (ROM), a random access memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.
The present application also provides a computer device comprising: a processor; a memory for storing executable instructions of the processor; wherein the processor is configured to perform the method of any of the embodiments described above via execution of the executable instructions.
In the several embodiments provided herein, it should be understood that the disclosed systems and methods may be implemented in other ways. For example, the system embodiments described above are merely illustrative, e.g., the division of the components is merely a logical functional division, and additional divisions may be implemented in practice.
In addition, each functional module/component in the embodiments of the present application may be integrated in the same processing module/component, or each module/component may exist alone physically, or two or more modules/components may be integrated in the same module/component. The integrated modules/components described above may be implemented in hardware or in hardware plus software functional modules/components.
It will be evident to those skilled in the art that the embodiments of the application are not limited to the details of the foregoing illustrative embodiments, and that the embodiments of the present application may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of embodiments being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. A plurality of units, modules or means recited in a system, means or terminal claim may also be implemented by means of software or hardware by means of one and the same unit, module or means. The terms first, second, etc. are used to denote a name, but not any particular order.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (10)
1. The transformer abnormality monitoring method is applied to a transformer abnormality monitoring system and is characterized by comprising the following steps of:
acquiring three-phase voltage and three-phase current data of a transformer, analyzing the acquired data, and determining the period time and the constant degree of each moment in the period; wherein, the constant degree is used for representing the sum of the voltage value and the current value at a certain moment;
calculating the instability of each period based on the constancy of each moment; the instability is used for representing the deviation degree of data corresponding to each acquisition time in the period and the same constant value;
calculating the time offset of the period based on the time corresponding to the maximum current value, the minimum current value, the maximum voltage value and the minimum voltage value in the period;
calculating the distortion degree between adjacent periods based on the instability degree and the moment offset degree of the adjacent periods;
determining a preset k value in an LOF algorithm based on the distortion degree of adjacent periods;
and based on a preset k value, performing fault judgment on the abnormality of the transformer by using an LOF algorithm.
2. The transformer abnormality monitoring method according to claim 1, wherein in the step of calculating the instability of each cycle based on the constancy of each time;
the average value of the constant degree in the period is taken as a constant value in the period, and the instability is used for representing the deviation degree of the constant degree and the average value of the constant degree at each moment in the period.
3. The method for monitoring abnormal conditions of a transformer according to claim 2, wherein the step of calculating the instability of each cycle based on the constancy of each moment is specifically:
the average value of the constancy over the period is calculated first, and then the instability of the period is calculated based on the difference between the constancy at each time and the average value of the constancy.
4. The method for monitoring abnormal state of transformer according to claim 1, wherein the step of calculating the time offset of the cycle based on the time corresponding to the maximum current value, the minimum current value, the maximum voltage value, and the minimum voltage value comprises:
and calculating the time offset of the period according to the time difference between the time when the maximum voltage value is located and the time when the minimum current value is located and the time difference between the time when the minimum voltage value is located and the time when the maximum current value is located.
5. The method for monitoring abnormal conditions of a transformer according to claim 4, wherein the calculating the time offset of the cycle according to the time difference between the time when the maximum voltage value is located and the time when the minimum current value is located and the time difference between the time when the minimum voltage value is located and the time when the maximum current value is located comprises:
and respectively calculating the time difference between the time at which the maximum voltage value is positioned and the time at which the minimum current value is positioned, and taking the sum of the time differences as the time offset of the corresponding period after the time difference between the time at which the minimum voltage value is positioned and the time at which the maximum current value is positioned.
6. The method for monitoring abnormal conditions of a transformer according to claim 1, wherein the step of calculating the distortion between adjacent periods based on the instability and the time offset of the adjacent periods comprises:
and calculating the product of the instability degree of the adjacent time and the time offset degree, and subtracting the absolute value to obtain the distortion degree of the adjacent two periods.
7. The method for monitoring abnormal conditions of a transformer according to claim 6, wherein when calculating the distortion degree of two adjacent periods, the time offset is added to a parameter adjustment factor, and the added value is multiplied by the instability, and the parameter adjustment factor is an arbitrary constant.
8. The method for monitoring abnormal condition of transformer according to claim 6, wherein the step of determining the preset k value in the LOF algorithm according to the distortion degree of the adjacent period comprises:
firstly, the distortion degree of adjacent periods is normalized to obtain a normalized value, and then a preset k value is calculated according to the normalized value and a preset constant value.
9. The method for monitoring abnormal conditions of a transformer according to claim 1, wherein the step of using the LOF algorithm to perform fault determination on abnormal conditions of the transformer based on the preset k value specifically comprises:
using LOF algorithm for each period to obtain local abnormal factor of each data;
if the local abnormal factor is greater than 1, the transformer has a fault at the acquisition time corresponding to the data; if the local abnormal factor is less than or equal to 1, the transformer works normally at the acquisition time corresponding to the data.
10. The transformer abnormality monitoring system is characterized by comprising a data acquisition analysis component, an instability analysis component, a moment offset analysis component, a distortion analysis component, a k value determination component and an abnormality judgment component, wherein:
the data acquisition and analysis component is used for acquiring three-phase voltage and three-phase current data of the transformer, analyzing the acquired data and determining the period time and the constancy of each moment in the period; wherein, the constant degree is used for representing the sum of the voltage value and the current value at a certain moment;
the instability analyzing part is used for calculating the instability of each period based on the constancy of each moment; the instability is used for representing the deviation degree of data corresponding to each acquisition time in the period and the same constant value;
the time offset analysis component is used for calculating the time offset of the period based on the time corresponding to the maximum current value, the minimum current value, the maximum voltage value and the minimum voltage value in the period;
the distortion degree analysis component is used for calculating the distortion degree between adjacent periods based on the instability degree and the moment offset degree of the adjacent periods;
the k value determining part is used for determining a preset k value in an LOF algorithm based on the distortion degree of adjacent periods;
the abnormality judgment part is used for carrying out fault judgment on the abnormality of the transformer by using an LOF algorithm based on a preset k value.
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| CN116879662A (en) * | 2023-09-06 | 2023-10-13 | 山东华尚电气有限公司 | Transformer fault detection method based on data analysis |
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| CN116955895A (en) * | 2023-09-21 | 2023-10-27 | 山东博诚电气有限公司 | Transformer operation abnormity monitoring method and system |
| CN116955895B (en) * | 2023-09-21 | 2023-12-15 | 山东博诚电气有限公司 | Transformer operation abnormity monitoring method and system |
| CN117349781A (en) * | 2023-12-06 | 2024-01-05 | 东莞市郡嘉电子科技有限公司 | Intelligent diagnosis method and system for faults of transformer |
| CN117349781B (en) * | 2023-12-06 | 2024-03-22 | 东莞市郡嘉电子科技有限公司 | Intelligent diagnosis method and system for faults of transformer |
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