Power transformer winding fault complex frequency domain on-line diagnosis method and device

Abstract

The embodiment of the application discloses a kind of power transformer winding fault complex frequency domain online diagnosis method and equipment, by obtaining the midpoint voltage of different winding of power transformer under reference complex impedance, and according to midpoint voltage, obtain the midpoint voltage distance vector between different winding, according to midpoint voltage distance vector and preset midpoint voltage distance vector threshold, obtain the winding fault diagnosis result of power transformer.The midpoint voltage vector in the embodiment can reflect the electrical state inside winding, compared with existing detection method, midpoint voltage vector is more sensitive to winding fault, and is relatively smaller by load fluctuation Impact, while midpoint voltage vector is not easy to be affected by electromagnetic interference and wiring mode, therefore, the winding fault diagnosis mode of midpoint voltage distance obtained according to midpoint voltage is not easy to produce misjudgment, improve the accuracy of alternating current transformer, converter transformer winding fault online diagnosis result.

Description

Technical Field

[0001] This invention relates to the field of transformer winding fault diagnosis technology, and in particular to a method and equipment for online diagnosis of winding faults in AC power transformers and converter transformers in the complex frequency domain. Background Technology

[0002] In power systems, power transformers are widely used in substations and industrial plants because they offer a wider range of voltage levels. Power transformers typically have three independent windings, each connected to a different voltage level to meet varying power demands. The correctness of these transformer windings is crucial for the stable operation of the system; incorrect winding connections can lead to serious power outages and equipment damage. Therefore, determining and ensuring the correctness of power transformer windings is an important issue.

[0003] As core equipment in new power systems, AC power transformers and converter transformers have significant technical value and socio-economic benefits from online diagnosis of their winding conditions. Windings are typically subjected to complex electromagnetic, thermal stresses, and mechanical vibrations over long periods, making them prone to deformation and displacement. Traditional offline detection methods have monitoring blind spots and struggle to capture dynamic defects in a timely manner. Online diagnostic technology, by collecting transformer operating characteristic parameters in real time and combining them with intelligent algorithms for condition assessment, can significantly improve the ability to predict potential hazards. Furthermore, it can promote the digital transformation of power equipment operation and maintenance from "planned maintenance" to "condition-based maintenance," providing critical equipment reliability assurance for power grids with high penetration of new energy sources, and yielding significant power grid safety benefits and low-carbon economic value.

[0004] The patent "A Three-Phase Transformer Fault Detection Method and System (Publication No.: CN115792733A)" calculates secondary side parameters by measuring primary voltage and current and combining Kirchhoff's voltage law, and then derives short-circuit reactance value to determine winding deformation. This method relies on accurate instrument transformer measurement and is easily affected by electromagnetic interference and wiring method (such as YD connection), resulting in inaccurate winding fault judgment results.

[0005] The patent "A method, device and system for detecting winding deformation faults in a three-phase transformer (publication number: CN115574710A)" proposes to detect faults by analyzing changes in winding capacitance to ground, phase-to-phase capacitance and oscillation wave parameters. This method is sensitive to the transformer's operating status (such as load fluctuations) and is prone to misjudgment, resulting in inaccurate winding fault judgment results.

[0006] It is evident that existing online diagnostic methods for winding faults are still susceptible to load fluctuations, electromagnetic interference, and wiring methods, which can easily lead to misjudgments and result in poor accuracy of winding fault diagnosis results. Summary of the Invention

[0007] In view of this, the present invention provides a method and device for online diagnosis of winding faults in power transformers in the complex frequency domain, which can realize online, efficient and high-precision evaluation of the health status of AC transformers and converter transformer windings.

[0008] The specific technical solution of the first embodiment of the present invention is as follows: a method for online diagnosis of winding faults in a power transformer in the complex frequency domain, the method comprising: acquiring a first midpoint voltage vector of a first winding of a power transformer, acquiring a second midpoint voltage vector of a second winding of a power transformer, and acquiring a third midpoint voltage vector of a third winding of a power transformer; acquiring different midpoint voltage distance vectors between different windings based on the first midpoint voltage vector, the second midpoint voltage vector, and the third midpoint voltage vector; the different midpoint voltage distance vectors include a first midpoint voltage distance vector between the first winding and the second winding, a second midpoint voltage distance vector between the second winding and the third winding, and a third midpoint voltage distance vector between the first winding and the third winding; and acquiring the winding fault diagnosis result of the power transformer based on the different midpoint voltage distance vectors and a preset midpoint voltage distance vector.

[0009] Preferably, the first midpoint voltage vector, the second midpoint voltage vector, and the third midpoint voltage vector are obtained using the following formula:

[0010]

[0011] in, The voltage vector at the first midpoint; The voltage vector at the second midpoint; The third midpoint voltage vector, Let be the positive-sequence phase voltage vector of the first winding. This is the positive-sequence phase voltage vector of the second winding referred to the first winding. The positive-sequence phase voltage vector of the third winding referred to the first winding. Let be the positive sequence line current vector of the first winding. This is the positive sequence line current vector of the second winding referred to the first winding. Z is the positive sequence line current vector of the third winding referred to the first winding. 1z Z is the reference complex impedance of the first winding. 2z Z is the reference complex impedance of the second winding. 3z This is the reference complex impedance of the third winding.

[0012] Preferably, the reference complex impedance of the first winding, the reference complex impedance of the second winding, and the reference complex impedance of the third winding are the complex impedances measured offline by the first winding, the second winding, and the third winding.

[0013] Preferably, the midpoint voltage distance vector is obtained using the following formula:

[0014]

[0015] in, Let be the midpoint voltage distance vector between the i-th winding and the j-th winding. Let be the midpoint voltage vector of the i-th winding. Let be the voltage vector at the midpoint of the j-th winding.

[0016] Preferably, the step of obtaining the winding fault diagnosis result of the power transformer based on the different midpoint voltage distance vectors and the preset midpoint voltage distance vector includes: comparing the first midpoint voltage distance vector, the second midpoint voltage distance vector, and the third midpoint voltage distance vector with the preset midpoint voltage distance vector threshold respectively; if the amplitude or phase of the target midpoint voltage distance vector is greater than the amplitude or phase of the preset midpoint voltage distance vector threshold, then the winding corresponding to the target midpoint voltage distance vector has a fault; the target midpoint voltage distance vector is any one of the first midpoint voltage distance vector, the second midpoint voltage distance vector, and the third midpoint voltage distance vector.

[0017] Preferably, the preset midpoint voltage distance vector threshold is determined by the vector deviation of the complex impedance under rated load measured by offline testing.

[0018] The specific technical solution of the second embodiment of the present invention is as follows: a power transformer winding fault online diagnostic system in the complex frequency domain, the system comprising: a midpoint voltage acquisition module, a midpoint voltage distance acquisition module, and a diagnostic module; the midpoint voltage acquisition module is used to acquire a first midpoint voltage vector of a first winding of the power transformer, a second midpoint voltage vector of a second winding of the power transformer, and a third midpoint voltage vector of a third winding of the power transformer; the midpoint voltage distance acquisition module is used to acquire different midpoint voltage distance vectors between different windings based on the first midpoint voltage vector, the second midpoint voltage vector, and the third midpoint voltage vector; the different midpoint voltage distance vectors include a first midpoint voltage distance vector between the first winding and the second winding, a second midpoint voltage distance vector between the second winding and the third winding, and a third midpoint voltage distance vector between the first winding and the third winding; the diagnostic module is used to acquire the winding fault diagnosis result of the power transformer based on the different midpoint voltage distance vectors and a preset midpoint voltage distance vector.

[0019] Preferably, the reference complex impedance of the first winding, the reference complex impedance of the second winding, and the reference complex impedance of the third winding are the complex impedances measured offline by the first winding, the second winding, and the third winding.

[0020] The specific technical solution of the third embodiment of the present invention is as follows: a winding fault judgment device for a power transformer, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the method as described in any one of the first embodiments of this application.

[0021] The specific technical solution of the fourth embodiment of the present invention is as follows: a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor performs the steps of the method as described in any one of the first embodiments of this application.

[0022] Implementing the embodiments of the present invention will have the following beneficial effects:

[0023] This invention obtains the midpoint voltage of different windings of a power transformer under a reference complex impedance, and then obtains the midpoint voltage distance vector between different windings based on the midpoint voltage. The winding fault diagnosis result of the power transformer is obtained by comparing the midpoint voltage distance vector with a preset midpoint voltage distance vector. The midpoint voltage in this invention reflects the internal electrical state of the winding. Compared with existing detection methods, the midpoint voltage vector is more sensitive to winding faults and is less affected by load fluctuations. Furthermore, obtaining the midpoint voltage does not require high-precision measuring instruments and is less susceptible to electromagnetic interference and wiring variations. Therefore, the method of diagnosing winding faults based on the midpoint voltage distance is less prone to misjudgment, improving the accuracy of the winding fault diagnosis results. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 A flowchart illustrating the steps of a method for online diagnosis of power transformer winding faults in the complex frequency domain;

[0026] Figure 2 This is a schematic diagram of a complex frequency domain online diagnostic system for power transformer winding faults.

[0027] Figure 3 This is a diagram of the internal structure of a computer device.

[0028] Among them, 201 is the midpoint voltage acquisition module; 202 is the midpoint voltage distance acquisition module; and 203 is the diagnostic module. Detailed Implementation

[0029] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0030] The terms "first," "second," etc., used in the specification, claims, and drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or modules is not limited to the listed steps or modules, but may optionally include steps or modules not listed, or may optionally include other steps or modules inherent to such processes, methods, products, or apparatus.

[0031] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0032] Please see Figure 1 This is a flowchart illustrating the steps of a method for online diagnosis of power transformer winding faults in the complex frequency domain, as described in the first embodiment of this application, to improve the accuracy of winding fault diagnosis results. The method includes:

[0033] Step 101: Obtain the first midpoint voltage vector of the first winding of the power transformer, obtain the second midpoint voltage vector of the second winding of the power transformer, and obtain the third midpoint voltage vector of the third winding of the power transformer.

[0034] Step 102: Obtain different midpoint voltage distance vectors between different windings based on the first midpoint voltage vector, the second midpoint voltage vector, and the third midpoint voltage vector; the different midpoint voltage distance vectors include the first midpoint voltage distance vector between the first winding and the second winding, the second midpoint voltage distance vector between the second winding and the third winding, and the third midpoint voltage distance vector between the first winding and the third winding.

[0035] Step 103: Obtain the winding fault diagnosis results of the power transformer based on the different midpoint voltage distance vectors and the preset midpoint voltage distance vector.

[0036] Specifically, the reference complex impedances of the first, second, and third windings of the transformer were obtained through offline testing and are 0.26+21.15i (Ω), 0.26-1.56i (Ω), and 0.26+13.73i (Ω), respectively. The positive sequence voltage and current of each winding of the power transformer were measured simultaneously. The output positive sequence voltage and current of the second and third windings were then generalized to the first winding. The positive sequence voltage of the first winding is -63.51i (kV), and the positive sequence voltage of the second winding is -0.85-22.09i (kV). After generalization to the first winding, the values ​​are...

[0037] -2.43-63.1i(kV); the positive sequence voltage of the third winding is 2.73-5.36i(kV), which is -3.31-62.97i(kV) after being referred to the first winding. The positive sequence current of the first winding is -17.92-119.92i(A), the positive sequence current of the second winding is -24.97-179.59i(A), which is -8.74-62.86i(A) after being referred to the first winding, and the positive sequence current of the third winding is 219.5-563.63i(A), which is -8.76-57.07i(A) after being referred to the first winding.

[0038] According to the formula The calculated first midpoint voltage vector is -2.532-63.1i (kV), the second midpoint voltage vector is -2.53-63.103i (kV), and the third midpoint voltage vector is -2.529-63.105i (kV).

[0039] Furthermore, according to the formula The calculated voltage distance vector at the first midpoint is -0.001 + 0.003i, with an amplitude of 0.0032 and a phase of 108.5°; the voltage distance vector at the second midpoint is -0.002 + 0.002i, with an amplitude of 0.0028 and a phase of 135°; and the voltage distance vector at the third midpoint is -0.003 + 0.005i, with an amplitude of 0.0058 and a phase of 121°.

[0040] The midpoint voltage distance vector threshold was determined by the vector deviation of the complex impedance under rated load through offline testing as -0.001+0.003i. The amplitude of the midpoint voltage distance vector threshold is 0.0032 and the phase is 108.5°.

[0041] The first, second, and third midpoint voltage distance vectors are compared with preset midpoint voltage distance vector thresholds. The phase of the second midpoint voltage distance vector is greater than the preset threshold; both the amplitude and phase of the third midpoint voltage distance vector are greater than the preset midpoint voltage distance vector threshold. The second midpoint voltage distance vector corresponds to the second and third windings, and the third midpoint voltage distance vector corresponds to the first and third windings. Therefore, it is determined that there is a fault in the third winding of the transformer.

[0042] The method in this embodiment obtains the midpoint voltage of different windings of a power transformer under a reference complex impedance, and obtains the midpoint voltage distance vector between different windings based on the midpoint voltage. The winding fault diagnosis result of the power transformer is obtained based on the midpoint voltage distance vector and a preset midpoint voltage distance vector threshold. The midpoint voltage vector in this embodiment can reflect the internal electrical state of the winding. Compared with existing detection methods, the midpoint voltage vector is more sensitive to winding faults and is less affected by load fluctuations. Furthermore, the midpoint voltage vector is less susceptible to electromagnetic interference and wiring variations. Therefore, the method of diagnosing winding faults based on the midpoint voltage distance is less prone to misjudgment, improving the accuracy of online winding fault diagnosis results.

[0043] In a specific embodiment, the midpoint voltage distance vector is obtained using the following formula:

[0044]

[0045] in, Let be the midpoint voltage distance vector between the i-th winding and the j-th winding. Let be the midpoint voltage vector of the i-th winding. Let be the voltage vector at the midpoint of the j-th winding.

[0046] In a specific embodiment, the preset midpoint voltage distance vector threshold is determined by the vector deviation of the complex impedance measured offline under rated load. Specifically, this method improves the accuracy of fault diagnosis. By measuring the complex impedance offline and calculating the vector deviation under rated load, the internal electrical state of the winding can be more accurately reflected. Compared with traditional detection methods, this method is more sensitive to winding faults and can capture fault signals at an early stage, thereby preventing the further development of the fault. Secondly, this method enhances the reliability of the diagnostic results. The preset midpoint voltage distance vector threshold is derived from a large amount of offline test data and empirical analysis, and has high accuracy and reliability. When the measured vector deviation exceeds this threshold, the winding can be considered to have a fault, reducing the possibility of misjudgment. In addition, this method also reduces diagnostic costs. The process of offline testing to measure complex impedance is relatively simple and does not rely on high-precision real-time measuring instruments, reducing detection costs. At the same time, the preset threshold can be applied to different types of windings, has wide applicability, and further reduces diagnostic costs. Finally, this method provides strong support for the prevention and maintenance of winding faults. By regularly conducting offline tests to measure complex impedance and calculate vector deviation, potential faults in the windings can be detected in a timely manner, providing a basis for decision-making on maintenance and replacement, and ensuring the safe and stable operation of the power system.

[0047] In a specific embodiment, please refer to Figure 2 This is a schematic diagram of a complex frequency domain online diagnostic system for power transformer winding faults, provided in a second embodiment of this application. The system includes: a midpoint voltage acquisition module 201, a midpoint voltage distance acquisition module 202, and a diagnostic module 203. The midpoint voltage acquisition module 201 is used to acquire a first midpoint voltage vector of the first winding of the power transformer, a second midpoint voltage vector of the second winding of the power transformer, and a third midpoint voltage vector of the third winding of the power transformer. The midpoint voltage distance acquisition module 202 is used to acquire different midpoint voltage distance vectors between different windings based on the first midpoint voltage vector, the second midpoint voltage vector, and the third midpoint voltage vector. The different midpoint voltage distance vectors include a first midpoint voltage distance vector between the first winding and the second winding, a second midpoint voltage distance vector between the second winding and the third winding, and a third midpoint voltage distance vector between the first winding and the third winding. The diagnostic module 203 is used to acquire the winding fault diagnosis result of the power transformer based on the different midpoint voltage distance vectors and a preset midpoint voltage distance vector.

[0048] The system in this embodiment acquires the midpoint voltage of different windings of a power transformer under a reference complex impedance, and obtains the midpoint voltage distance vector between different windings based on the midpoint voltage. The winding fault diagnosis result of the power transformer is obtained based on the midpoint voltage distance vector and a preset midpoint voltage distance vector threshold. The midpoint voltage vector in this embodiment reflects the internal electrical state of the winding. Compared with existing detection methods, the midpoint voltage vector is more sensitive to winding faults and is less affected by load fluctuations. Furthermore, the midpoint voltage vector is less susceptible to electromagnetic interference and wiring variations. Therefore, the method of diagnosing winding faults based on the midpoint voltage distance is less prone to misjudgment, improving the accuracy of online winding fault diagnosis results.

[0049] In a specific embodiment, the reference complex impedance of the first winding, the reference complex impedance of the second winding, and the reference complex impedance of the third winding are the complex impedances measured offline by the first winding, the second winding, and the third winding.

[0050] In a specific embodiment, obtaining the winding fault diagnosis result of the power transformer based on the different midpoint voltage distance vectors and the preset midpoint voltage distance vector includes: comparing the first midpoint voltage distance vector, the second midpoint voltage distance vector, and the third midpoint voltage distance vector with the preset midpoint voltage distance vector threshold respectively; if the amplitude or phase of the target midpoint voltage distance vector is greater than the amplitude or phase of the preset midpoint voltage distance vector threshold, then the winding corresponding to the target midpoint voltage distance vector has a fault; the target midpoint voltage distance vector is any one of the first midpoint voltage distance vector, the second midpoint voltage distance vector, and the third midpoint voltage distance vector.

[0051] Specifically, the reference complex impedances of the first, second, and third windings of the transformer were obtained through offline testing and are 0.26+21.15i (Ω), 0.26-1.56i (Ω), and 0.26+13.73i (Ω), respectively. The positive sequence voltage and current of each winding of the power transformer were measured simultaneously. The output positive sequence voltage and current of the second and third windings were then generalized to the first winding. The positive sequence voltage of the first winding is -63.51i (kV), and the positive sequence voltage of the second winding is -0.85-22.09i (kV). After generalization to the first winding, the values ​​are...

[0052] -2.43-63.1i(kV); the positive sequence voltage of the third winding is 2.73-5.36i(kV), which is -3.31-62.97i(kV) after being referred to the first winding. The positive sequence current of the first winding is -17.92-119.92i(A), the positive sequence current of the second winding is -24.97-179.59i(A), which is -8.74-62.86i(A) after being referred to the first winding, and the positive sequence current of the third winding is 219.5-563.63i(A), which is -8.76-57.07i(A) after being referred to the first winding.

[0053] According to the formula The calculated first midpoint voltage vector is -2.532-63.1i (kV), the second midpoint voltage vector is -2.53-63.103i (kV), and the third midpoint voltage vector is -2.529-63.105i (kV).

[0054] Furthermore, according to the formula The calculated voltage distance vector at the first midpoint is -0.001 + 0.003i, with an amplitude of 0.0032 and a phase of 108.5°; the voltage distance vector at the second midpoint is -0.002 + 0.002i, with an amplitude of 0.0028 and a phase of 135°; and the voltage distance vector at the third midpoint is -0.003 + 0.005i, with an amplitude of 0.0058 and a phase of 121°.

[0055] The midpoint voltage distance vector threshold was determined by the vector deviation of the complex impedance under rated load through offline testing as -0.001+0.003i. The amplitude of the midpoint voltage distance vector threshold is 0.0032 and the phase is 108.5°.

[0056] The first, second, and third midpoint voltage distance vectors are compared with preset midpoint voltage distance vector thresholds. The phase of the second midpoint voltage distance vector is greater than the preset threshold; both the amplitude and phase of the third midpoint voltage distance vector are greater than the preset midpoint voltage distance vector threshold. The second midpoint voltage distance vector corresponds to the second and third windings, and the third midpoint voltage distance vector corresponds to the first and third windings. Therefore, it is determined that there is a fault in the third winding of the transformer.

[0057] In a specific embodiment, the third embodiment of this application provides a winding fault diagnosis device for a power transformer, including a memory and a processor. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the method described in any of the first embodiments of this application. The device in this embodiment obtains the midpoint voltage of different windings of the power transformer under a reference complex impedance, and obtains the midpoint voltage distance vector between different windings based on the midpoint voltage. It then obtains the winding fault diagnosis result of the power transformer based on the midpoint voltage distance vector and a preset midpoint voltage distance vector threshold. The midpoint voltage vector in this embodiment can reflect the internal electrical state of the winding. Compared with existing detection methods, the midpoint voltage vector is more sensitive to winding faults and is less affected by load fluctuations. Furthermore, the midpoint voltage vector is less susceptible to electromagnetic interference and wiring variations. Therefore, the method of diagnosing winding faults based on the midpoint voltage distance obtained from the midpoint voltage is less prone to misjudgment, improving the accuracy of online winding fault diagnosis results.

[0058] In a specific embodiment, the fourth embodiment of this application provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program causes the processor to perform the steps of the method described in any one of the first embodiments of this application. In this embodiment, the storage medium acquires the midpoint voltage of different windings of a power transformer under a reference complex impedance, obtains the midpoint voltage distance vector between different windings based on the midpoint voltage, and obtains the winding fault diagnosis result of the power transformer based on the midpoint voltage distance vector and a preset midpoint voltage distance vector threshold. Midpoint voltage, as an advanced detection technology, exhibits unique advantages in the field of winding condition monitoring and fault diagnosis. It not only effectively reflects the internal electrical state of the winding, but also significantly improves the sensitivity of the midpoint voltage vector to winding faults compared to traditional detection methods. This characteristic means that the midpoint voltage can capture these changes when early faults or minor anomalies occur in the winding, thus providing the possibility for early warning and timely maintenance. Furthermore, the midpoint voltage also exhibits good stability in practical applications. Even under large load fluctuations, the change in the midpoint voltage is relatively small, which further enhances its reliability in winding fault diagnosis. This characteristic makes midpoint voltage an ideal tool for maintaining accurate diagnostic results under various operating conditions. It's worth noting that obtaining midpoint voltage is relatively simple, requiring no high-precision measuring instruments. This not only reduces testing costs but also makes midpoint voltage technology easier to promote and popularize in practical applications. Furthermore, midpoint voltage is less susceptible to electromagnetic interference and wiring variations, further improving the accuracy and stability of its diagnostic results. Based on these advantages, using midpoint voltage distance for winding fault diagnosis has achieved significant results in practical applications. This method not only reduces the possibility of misdiagnosis but also greatly improves the accuracy of winding fault diagnosis results.

[0059] Figure 3 An internal structural diagram of a computer device in one embodiment is shown. This computer device can specifically be a terminal or a server. See also... Figure 3 The computer device includes a processor, memory, etc., connected via a system bus. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and may also store a computer program. When executed by the processor, this computer program causes the processor to implement the method described in this embodiment. The internal memory may also store a computer program, which, when executed by the processor, causes the processor to perform the method described in this embodiment. Those skilled in the art will understand that... Figure 3The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0060] The above embodiments merely illustrate several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

[0061] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments for application in other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for online diagnosis of winding faults in a power transformer in the complex frequency domain, characterized in that, The method includes: Obtain the first midpoint voltage vector of the first winding of the power transformer, obtain the second midpoint voltage vector of the second winding of the power transformer, and obtain the third midpoint voltage vector of the third winding of the power transformer; Different midpoint voltage distance vectors between different windings are obtained based on the first midpoint voltage vector, the second midpoint voltage vector, and the third midpoint voltage vector; the different midpoint voltage distance vectors include the first midpoint voltage distance vector between the first winding and the second winding, the second midpoint voltage distance vector between the second winding and the third winding, and the third midpoint voltage distance vector between the first winding and the third winding. The first midpoint voltage distance vector, the second midpoint voltage distance vector, and the third midpoint voltage distance vector are compared with a preset midpoint voltage distance vector threshold, respectively. If the magnitude or phase of the target midpoint voltage distance vector is greater than the magnitude or phase of the preset midpoint voltage distance vector threshold, then the winding corresponding to the target midpoint voltage distance vector has a fault; the target midpoint voltage distance vector is any one of the first midpoint voltage distance vector, the second midpoint voltage distance vector, and the third midpoint voltage distance vector. The first midpoint voltage vector, the second midpoint voltage vector, and the third midpoint voltage vector are obtained using the following formula: in, The voltage vector at the first midpoint; The voltage vector at the second midpoint; The third midpoint voltage vector, Let be the positive-sequence phase voltage vector of the first winding. This is the positive-sequence phase voltage vector of the second winding referred to the first winding. The positive-sequence phase voltage vector of the third winding referred to the first winding. Let be the positive sequence line current vector of the first winding. This is the positive sequence line current vector of the second winding referred to the first winding. The positive sequence line current vector of the third winding is referred to the first winding. This is the reference complex impedance of the first winding. This is the reference complex impedance of the second winding. This is the reference complex impedance of the third winding.

2. The online multi-frequency domain diagnostic method for power transformer winding faults as described in claim 1, characterized in that, The reference complex impedances of the first winding, the second winding, and the third winding are the complex impedances measured offline by the first winding, the second winding, and the third winding.

3. The online multi-frequency domain diagnostic method for power transformer winding faults as described in claim 1, characterized in that, The midpoint voltage distance vector is obtained using the following formula: in, For the first i Winding and the first j The midpoint voltage distance vector between windings For the first i Midpoint voltage vector of the winding For the first j The voltage vector at the midpoint of the winding.

4. The online multi-frequency domain diagnostic method for power transformer winding faults as described in claim 1, characterized in that, The preset midpoint voltage distance vector threshold is determined by the vector deviation of the complex impedance under rated load measured by offline testing.

5. A complex frequency domain online diagnostic system for power transformer winding faults, applied to the complex frequency domain online diagnostic method for power transformer winding faults as described in claim 1, characterized in that, The system includes: a midpoint voltage acquisition module, a midpoint voltage distance acquisition module, and a diagnostic module; The midpoint voltage acquisition module is used to acquire the first midpoint voltage vector of the first winding of the power transformer, the second midpoint voltage vector of the second winding of the power transformer, and the third midpoint voltage vector of the third winding of the power transformer. The midpoint voltage distance acquisition module is used to acquire different midpoint voltage distance vectors between different windings based on the first midpoint voltage vector, the second midpoint voltage vector, and the third midpoint voltage vector; the different midpoint voltage distance vectors include the first midpoint voltage distance vector between the first winding and the second winding, the second midpoint voltage distance vector between the second winding and the third winding, and the third midpoint voltage distance vector between the first winding and the third winding; The diagnostic module is used to obtain the winding fault diagnosis results of the power transformer based on the different midpoint voltage distance vectors and the preset midpoint voltage distance vector.

6. The online multi-frequency domain diagnostic system for power transformer winding faults as described in claim 5, characterized in that, The reference complex impedances of the first winding, the second winding, and the third winding are the complex impedances measured offline by the first winding, the second winding, and the third winding.

7. A winding fault detection device for a power transformer, comprising a memory and a processor, characterized in that, The memory stores a computer program that, when executed by the processor, causes the processor to perform the steps of the method as described in any one of claims 1 to 4.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it causes the processor to perform the steps of the method as described in any one of claims 1 to 4.

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